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AI explanation
As household spending on meats, poultry, fish, and eggs rose, more people were grilling and hosting backyard BBQs. This led to a spike in demand for home improvement products at The Home Depot, boosting their stock price. You could say it was a real "grill and drill" situation for the company!
Model: dalle-3
Prompt: Create an image of a vibrant backyard filled with families joyfully grilling steaks and kebabs on gleaming new barbecues from The Home Depot. The scene is accentuated by the laughter of children and the delightful aroma of succulent food. In the background, display a vivid stock ticker screen showing The Home Depot's (HD) stock price steadily ascending, portraying a prosperous and fulfilling family gathering in conjunction with the success of the company. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:
Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Realistic Photorealism Whimsical illustration Whimsical illustration 3D Pixar Style
ChatGPT: Realistic
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD), in the following situation: As households bought more meat for barbecues, they needed grills and tools to cook them, so they went to The Home Depot, boosting its stock price.. Keep the description simple.
ChatGPT: Families happily gathered in their backyard, grilling juicy steaks and sizzling kebabs while laughing and creating treasured memories. The patio was adorned with shiny new grills and cooking tools from The Home Depot. At the same time, a stock ticker screen in the background showed The Home Depot's (HD) stock price rising steadily.
Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Realistic ] and depicting this scene: Families happily gathered in their backyard, grilling juicy steaks and sizzling kebabs while laughing and creating treasured memories. The patio was adorned with shiny new grills and cooking tools from The Home Depot. At the same time, a stock ticker screen in the background showed The Home Depot's (HD) stock price rising steadily. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a vibrant backyard filled with families joyfully grilling steaks and kebabs on gleaming new barbecues from The Home Depot. The scene is accentuated by the laughter of children and the delightful aroma of succulent food. In the background, display a vivid stock ticker screen showing The Home Depot's (HD) stock price steadily ascending, portraying a prosperous and fulfilling family gathering in conjunction with the success of the company.
*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.
I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Annual US household spending on meats, poultry, fish, and eggs caused The Home Depot's stock price (HD) to increase. Include one good pun.
AI academic paper
 |
Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price The Journal of Finances and Food Trends Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Make the title punny if you can come up with clever pun. If not, make it sound serious.
Your research team used data from Bureau of Labor Statistics and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9547119 and p < 0.01 for 2002 to 2022.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
"Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price"
[[ABSTRACT]]
In this study, we set out to uncover the unexpected common ground between the annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). By delving into data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we sought to demonstrate that, much like a well-marbled steak, these seemingly disparate entities are more connected than we might think. Upon conducting our analysis, we discovered a striking correlation coefficient of 0.9547119 and p < 0.01 for the period spanning from 2002 to 2022.
Our findings illuminate the interplay between consumer dietary preferences and the retail home improvement sector, painting a picture of interconnected markets that may raise some eyebrows—just like a particularly intriguing fish at the market. Unexpectedly, our research suggests that as household spending on animal products rises, so does The Home Depot's stock price, demonstrating a trend reminiscent of a well-planned barbecue—both markets heat up together. As the saying goes, "Where there's smoke, there's fire"—and in this case, where there's meat, there's a parallel rise in HD stock price. Our study not only sheds light on this surprising relationship, but also offers a rare opportunity to pepper our analysis with some punny humor. After all, in the world of research, it's important to have a little fun—just like grilling season. So, let’s steak our claim in this delightful correlation with the confidence of a seasoned grillmaster.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Here is the title and abstract of the paper:
[[TITLE]]
"Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price"
[[ABSTRACT]]
In this study, we set out to uncover the unexpected common ground between the annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). By delving into data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we sought to demonstrate that, much like a well-marbled steak, these seemingly disparate entities are more connected than we might think. Upon conducting our analysis, we discovered a striking correlation coefficient of 0.9547119 and p < 0.01 for the period spanning from 2002 to 2022.
Our findings illuminate the interplay between consumer dietary preferences and the retail home improvement sector, painting a picture of interconnected markets that may raise some eyebrows—just like a particularly intriguing fish at the market. Unexpectedly, our research suggests that as household spending on animal products rises, so does The Home Depot's stock price, demonstrating a trend reminiscent of a well-planned barbecue—both markets heat up together. As the saying goes, "Where there's smoke, there's fire"—and in this case, where there's meat, there's a parallel rise in HD stock price. Our study not only sheds light on this surprising relationship, but also offers a rare opportunity to pepper our analysis with some punny humor. After all, in the world of research, it's important to have a little fun—just like grilling season. So, let’s steak our claim in this delightful correlation with the confidence of a seasoned grillmaster.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
It is a truth universally acknowledged, that a hungry man in possession of a good fortune must be in want of a hearty meal. However, what may not be so widely acknowledged is the potential link between the consumption of meats, poultry, fish, and eggs and the prosperity of The Home Depot (HD) as a company. As the old saying goes, "What do you call a pig thief? A hamburglar!" But, in the world of academic research, we're not out to steal any puns, just to dig deep into the data to see how these markets are "bacon" (making)!
In recent years, the study of intermarket correlations has expanded beyond the traditional financial sectors to consider unlikely connections between consumption patterns and stock performance. Our research aims to bridge this gap of curiosity and carve out a better understanding of the meaty relationship between household spending trends and the stock price of The Home Depot. So, let’s not chicken out on this endeavor and instead dive into the data with scientific curiosity and a good sense of humor.
One might wonder, "What do you get when you cross a dog and a calculator? A friend you can count on!" But, in the world of scientific inquiry, we aim to cross household spending on animal products with the stock performance of HD to uncover insights that we can truly count on. Through this examination, we aim to demonstrate whether there is truly a statistically significant link or if our findings will be nothing more than a statistical “red herring.”
As we embark on this quest, it's important to acknowledge the inherent complexity of studying market relationships. After all, understanding the dynamics of consumer behavior and investment patterns can sometimes feel like trying to juggle multiple balls of statistical significance while riding a unicycle on a tightrope. However, armed with robust data and a willingness to embrace the unexpected, we believe we can negotiate this scientific circus to uncover some truly intriguing findings.
So, grab your lab coat and spatula—I mean, your data analysis software—and let's sizzle our way through the steak of statistics to reveal the tender truth behind this unlikely correlation. After all, in the world of research, as in the world of grilling, it's all about finding that perfect medium rare.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between Annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.
Here is the title and abstract of the paper:
[[TITLE]]
"Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price"
[[ABSTRACT]]
In this study, we set out to uncover the unexpected common ground between the annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). By delving into data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we sought to demonstrate that, much like a well-marbled steak, these seemingly disparate entities are more connected than we might think. Upon conducting our analysis, we discovered a striking correlation coefficient of 0.9547119 and p < 0.01 for the period spanning from 2002 to 2022.
Our findings illuminate the interplay between consumer dietary preferences and the retail home improvement sector, painting a picture of interconnected markets that may raise some eyebrows—just like a particularly intriguing fish at the market. Unexpectedly, our research suggests that as household spending on animal products rises, so does The Home Depot's stock price, demonstrating a trend reminiscent of a well-planned barbecue—both markets heat up together. As the saying goes, "Where there's smoke, there's fire"—and in this case, where there's meat, there's a parallel rise in HD stock price. Our study not only sheds light on this surprising relationship, but also offers a rare opportunity to pepper our analysis with some punny humor. After all, in the world of research, it's important to have a little fun—just like grilling season. So, let’s steak our claim in this delightful correlation with the confidence of a seasoned grillmaster.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
It is a truth universally acknowledged, that a hungry man in possession of a good fortune must be in want of a hearty meal. However, what may not be so widely acknowledged is the potential link between the consumption of meats, poultry, fish, and eggs and the prosperity of The Home Depot (HD) as a company. As the old saying goes, "What do you call a pig thief? A hamburglar!" But, in the world of academic research, we're not out to steal any puns, just to dig deep into the data to see how these markets are "bacon" (making)!
In recent years, the study of intermarket correlations has expanded beyond the traditional financial sectors to consider unlikely connections between consumption patterns and stock performance. Our research aims to bridge this gap of curiosity and carve out a better understanding of the meaty relationship between household spending trends and the stock price of The Home Depot. So, let’s not chicken out on this endeavor and instead dive into the data with scientific curiosity and a good sense of humor.
One might wonder, "What do you get when you cross a dog and a calculator? A friend you can count on!" But, in the world of scientific inquiry, we aim to cross household spending on animal products with the stock performance of HD to uncover insights that we can truly count on. Through this examination, we aim to demonstrate whether there is truly a statistically significant link or if our findings will be nothing more than a statistical “red herring.”
As we embark on this quest, it's important to acknowledge the inherent complexity of studying market relationships. After all, understanding the dynamics of consumer behavior and investment patterns can sometimes feel like trying to juggle multiple balls of statistical significance while riding a unicycle on a tightrope. However, armed with robust data and a willingness to embrace the unexpected, we believe we can negotiate this scientific circus to uncover some truly intriguing findings.
So, grab your lab coat and spatula—I mean, your data analysis software—and let's sizzle our way through the steak of statistics to reveal the tender truth behind this unlikely correlation. After all, in the world of research, as in the world of grilling, it's all about finding that perfect medium rare.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
Scholars have long sought to unravel the complexities of market relationships, often casting their net wide in an effort to capture unexpected correlations and uncover hidden patterns. In "Meats and Markets: A Statistical Analysis," Smith and Doe present a comprehensive analysis examining the relationship between annual US household spending on meats, poultry, fish, and eggs and the stock price of The Home Depot. Their rigorous approach highlights the importance of understanding consumer dietary preferences as a potential driving force behind market dynamics. Our findings align with their insights, painting a vivid picture of how consumer choices can impact not only the dinner table but also the stock market. As the French say, "No matter how you slice it, the link between meat and HD stock price is hard to ignore."
Furthermore, Jones discusses the impact of consumer trends on retail sectors in "Economics of Consumption: From Milk to Lumber." While the book primarily focuses on broader consumer behaviors, it does recognize possible interactions between seemingly unrelated markets. This notion echoes our own research, which reveals a surprisingly strong connection between household spending on animal products and The Home Depot's stock price. It seems that in the realm of market analysis, there's always room for some unexpected interplay, much like finding a fish in the lumber aisle—it's all interconnected, even when it seems fishy.
In a similar vein, "The Meat of Economics" by Smithson delves into the intricate relationship between consumer spending habits and stock market performance, shedding light on the potential influence of meat consumption on retail stock prices. Our study aligns with Smithson's narrative, illustrating that consumer preferences for meat and meat-related products can have a significant impact on the stock performance of home improvement retailers. It's safe to say that when it comes to meat and stock prices, the stakes are high, and we're slicing through to discover the rare connection between these seemingly separate markets.
Turning to the world of fiction, the classic novel "The Catcher in the Rye" by J.D. Salinger may not seem directly related to market analysis, but its reference to a staple food product, rye, serves as a reminder that even in literature, our consumption habits can influence the narrative. In a similarly evocative manner, our research seeks to demonstrate that the choices we make at the grocery store can have a ripple effect on the financial markets, much like a well-timed rye joke. After all, who knew that rye and stock prices could share a common thread?
On the internet, the "Distracted Boyfriend" meme has taken social media by storm, humorously depicting a man being distracted from his current partner by an alluring passerby. In a parallel sense, our findings may captivate researchers with a similarly unexpected twist, drawing attention to the captivating relationship between the consumption of animal products and The Home Depot's stock price. As the meme humorously reveals, sometimes the most captivating subjects are the ones we least expect—much like stumbling upon an incredibly attractive cut of meat in the supermarket.
In summary, our literature review demonstrates the breadth of research on market correlations and their unexpected associations with consumer behavior and stock performance. From serious academic analysis to lighthearted references in popular culture, it's clear that the relationship between household spending on meats, poultry, fish, and eggs and The Home Depot's stock price is a rich tapestry of unexpected connections, ready to be grilled to perfection. As we forge ahead with our own study, we hold firm to the belief that every market has a story to tell, and it's our mission to uncover the juiciest cuts of insight, even if it means seasoning our analysis with a healthy dose of humor.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between Annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Your research team collected data from all across the internet, but mostly just used information from Bureau of Labor Statistics and LSEG Analytics (Refinitiv) . You used data from 2002 to 2022
Make up the research methods you don't know. Make them a bit goofy and convoluted.
Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price"
[[ABSTRACT]]
In this study, we set out to uncover the unexpected common ground between the annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). By delving into data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we sought to demonstrate that, much like a well-marbled steak, these seemingly disparate entities are more connected than we might think. Upon conducting our analysis, we discovered a striking correlation coefficient of 0.9547119 and p < 0.01 for the period spanning from 2002 to 2022.
Our findings illuminate the interplay between consumer dietary preferences and the retail home improvement sector, painting a picture of interconnected markets that may raise some eyebrows—just like a particularly intriguing fish at the market. Unexpectedly, our research suggests that as household spending on animal products rises, so does The Home Depot's stock price, demonstrating a trend reminiscent of a well-planned barbecue—both markets heat up together. As the saying goes, "Where there's smoke, there's fire"—and in this case, where there's meat, there's a parallel rise in HD stock price. Our study not only sheds light on this surprising relationship, but also offers a rare opportunity to pepper our analysis with some punny humor. After all, in the world of research, it's important to have a little fun—just like grilling season. So, let’s steak our claim in this delightful correlation with the confidence of a seasoned grillmaster.
[[INTRODUCTION]]
It is a truth universally acknowledged, that a hungry man in possession of a good fortune must be in want of a hearty meal. However, what may not be so widely acknowledged is the potential link between the consumption of meats, poultry, fish, and eggs and the prosperity of The Home Depot (HD) as a company. As the old saying goes, "What do you call a pig thief? A hamburglar!" But, in the world of academic research, we're not out to steal any puns, just to dig deep into the data to see how these markets are "bacon" (making)!
In recent years, the study of intermarket correlations has expanded beyond the traditional financial sectors to consider unlikely connections between consumption patterns and stock performance. Our research aims to bridge this gap of curiosity and carve out a better understanding of the meaty relationship between household spending trends and the stock price of The Home Depot. So, let’s not chicken out on this endeavor and instead dive into the data with scientific curiosity and a good sense of humor.
One might wonder, "What do you get when you cross a dog and a calculator? A friend you can count on!" But, in the world of scientific inquiry, we aim to cross household spending on animal products with the stock performance of HD to uncover insights that we can truly count on. Through this examination, we aim to demonstrate whether there is truly a statistically significant link or if our findings will be nothing more than a statistical “red herring.”
As we embark on this quest, it's important to acknowledge the inherent complexity of studying market relationships. After all, understanding the dynamics of consumer behavior and investment patterns can sometimes feel like trying to juggle multiple balls of statistical significance while riding a unicycle on a tightrope. However, armed with robust data and a willingness to embrace the unexpected, we believe we can negotiate this scientific circus to uncover some truly intriguing findings.
So, grab your lab coat and spatula—I mean, your data analysis software—and let's sizzle our way through the steak of statistics to reveal the tender truth behind this unlikely correlation. After all, in the world of research, as in the world of grilling, it's all about finding that perfect medium rare.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To conduct this meaty investigation, we amassed a veritable smorgasbord of data from sources including the Bureau of Labor Statistics and LSEG Analytics (Refinitiv). But, let’s not get too carried away with the word "smorgasbord," or we might start making statistical comparisons between household spending and the popularity of Swedish meatballs at a buffet!
Our first step was to gather information on annual US household spending on meats, poultry, fish, and eggs from the Bureau of Labor Statistics. We meticulously combed through the data, just like a catfish at the bottom of a pond—but with less slime and more spreadsheets, of course. Our team carefully ensured that only the most prime cuts of reliable, high-quality data made it onto our research plate. We wanted a well-done dataset, not one that was half-baked!
Now, when it comes to the stock market data, we turned to LSEG Analytics (Refinitiv) for a serving of The Home Depot's (HD) stock prices. We wanted to make sure our findings were as fresh as a just-caught salmon, not something that had been sitting on the market shelf for too long. Our statistical seasonings had to be as robust as a hearty marinade—no bland or stale figures for this research study!
With our data in hand, we conducted a rigorous statistical analysis, akin to a barbecue pitmaster diligently checking the temperature of the grill to ensure the perfect cooking conditions. We employed correlation analysis to determine the relationship between the annual US household spending on animal products and The Home Depot's stock price. Just like marinating a tender brisket, we let the data simmer and cooked up a correlation coefficient to sizzle up our findings.
To ensure the reliability of our results, we also conducted a series of robustness checks, because in the world of research, it's important to double-check everything, like you would double-check if the grill is off after a barbecue. We assessed the sensitivity of our results to different time periods and statistical methodologies, ensuring that our findings were not just a statistical fluke. We wanted our results to be as reliable as the tried-and-true method of brining a Thanksgiving turkey.
Lastly, we carefully considered potential confounding variables and market conditions to avoid skewing our findings. We didn't want any sneaky variables hiding in the statistical shadows, like a rogue piece of bone-in chicken thigh hiding under a pile of chicken breasts. We aimed to carve out a clear and accurate picture of the relationship between household spending on animal products and HD stock performance, leaving no statistical stone unturned.
All in all, our methodology was a well-orchestrated symphony of statistical analysis, ensuring that our findings were as robust and succulent as a perfectly cooked steak—bringing a whole new meaning to the phrase "rare findings" in the world of academic research!
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Your research team collected data from all across the internet, but mostly just used information from Bureau of Labor Statistics and LSEG Analytics (Refinitiv) .
For the time period 2002 to 2022, you found a correlation 0.9547119, r-squared of 0.9114749, and p < 0.01.
One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.
Here is the title and abstract of the paper:
[[TITLE]]
"Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price"
[[ABSTRACT]]
In this study, we set out to uncover the unexpected common ground between the annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). By delving into data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we sought to demonstrate that, much like a well-marbled steak, these seemingly disparate entities are more connected than we might think. Upon conducting our analysis, we discovered a striking correlation coefficient of 0.9547119 and p < 0.01 for the period spanning from 2002 to 2022.
Our findings illuminate the interplay between consumer dietary preferences and the retail home improvement sector, painting a picture of interconnected markets that may raise some eyebrows—just like a particularly intriguing fish at the market. Unexpectedly, our research suggests that as household spending on animal products rises, so does The Home Depot's stock price, demonstrating a trend reminiscent of a well-planned barbecue—both markets heat up together. As the saying goes, "Where there's smoke, there's fire"—and in this case, where there's meat, there's a parallel rise in HD stock price. Our study not only sheds light on this surprising relationship, but also offers a rare opportunity to pepper our analysis with some punny humor. After all, in the world of research, it's important to have a little fun—just like grilling season. So, let’s steak our claim in this delightful correlation with the confidence of a seasoned grillmaster.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
It is a truth universally acknowledged, that a hungry man in possession of a good fortune must be in want of a hearty meal. However, what may not be so widely acknowledged is the potential link between the consumption of meats, poultry, fish, and eggs and the prosperity of The Home Depot (HD) as a company. As the old saying goes, "What do you call a pig thief? A hamburglar!" But, in the world of academic research, we're not out to steal any puns, just to dig deep into the data to see how these markets are "bacon" (making)!
In recent years, the study of intermarket correlations has expanded beyond the traditional financial sectors to consider unlikely connections between consumption patterns and stock performance. Our research aims to bridge this gap of curiosity and carve out a better understanding of the meaty relationship between household spending trends and the stock price of The Home Depot. So, let’s not chicken out on this endeavor and instead dive into the data with scientific curiosity and a good sense of humor.
One might wonder, "What do you get when you cross a dog and a calculator? A friend you can count on!" But, in the world of scientific inquiry, we aim to cross household spending on animal products with the stock performance of HD to uncover insights that we can truly count on. Through this examination, we aim to demonstrate whether there is truly a statistically significant link or if our findings will be nothing more than a statistical “red herring.”
As we embark on this quest, it's important to acknowledge the inherent complexity of studying market relationships. After all, understanding the dynamics of consumer behavior and investment patterns can sometimes feel like trying to juggle multiple balls of statistical significance while riding a unicycle on a tightrope. However, armed with robust data and a willingness to embrace the unexpected, we believe we can negotiate this scientific circus to uncover some truly intriguing findings.
So, grab your lab coat and spatula—I mean, your data analysis software—and let's sizzle our way through the steak of statistics to reveal the tender truth behind this unlikely correlation. After all, in the world of research, as in the world of grilling, it's all about finding that perfect medium rare.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
Our analysis revealed a substantial correlation coefficient of 0.9547119 between annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). This correlation coefficient indicates a strong positive linear relationship between the two variables, suggesting that as household spending on animal products increased, so did the stock price of The Home Depot. It's like the old adage, "You can't have too much of a good thing"—especially if that "good thing" is a juicy steak on the grill.
The r-squared value of 0.9114749 further underscores the robustness of this relationship. This means that a whopping 91.15% of the variability in The Home Depot's stock price can be explained by changes in annual US household spending on meats, poultry, fish, and eggs. That's almost as solid as a well-built BBQ grill.
Furthermore, with a p-value of less than 0.01, our findings attest to the statistical significance of this correlation. In other words, the likelihood of observing such a strong relationship by chance alone is less than 1%, which is about as rare as a blue steak. Our results provide compelling evidence to support the notion that there is indeed a tangible link between consumer spending on animal products and the performance of The Home Depot in the stock market.
Fig. 1 (to be included) visually encapsulates this noteworthy correlation, illustrating the tight clustering of data points around the upward-sloping trend line. The scatterplot drives home the point that, much like a well-curated charcuterie board, these two variables are artfully interconnected.
In summary, our results offer a rare glimpse into the flavorful convergence of consumer spending habits and stock market performance. It's as if the financial markets and the meat markets have been cooking up a recipe for success all along—proving that when it comes to market trends, everything's better with a little bit of seasoning.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between Annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Limit your response to 500 tokens.
Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.
Do not write a conclusion. I will add a conclusion after this.
[[TITLE]]
"Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price"
[[ABSTRACT]]
In this study, we set out to uncover the unexpected common ground between the annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). By delving into data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we sought to demonstrate that, much like a well-marbled steak, these seemingly disparate entities are more connected than we might think. Upon conducting our analysis, we discovered a striking correlation coefficient of 0.9547119 and p < 0.01 for the period spanning from 2002 to 2022.
Our findings illuminate the interplay between consumer dietary preferences and the retail home improvement sector, painting a picture of interconnected markets that may raise some eyebrows—just like a particularly intriguing fish at the market. Unexpectedly, our research suggests that as household spending on animal products rises, so does The Home Depot's stock price, demonstrating a trend reminiscent of a well-planned barbecue—both markets heat up together. As the saying goes, "Where there's smoke, there's fire"—and in this case, where there's meat, there's a parallel rise in HD stock price. Our study not only sheds light on this surprising relationship, but also offers a rare opportunity to pepper our analysis with some punny humor. After all, in the world of research, it's important to have a little fun—just like grilling season. So, let’s steak our claim in this delightful correlation with the confidence of a seasoned grillmaster.
[[LITERATURE REVIEW]]
Scholars have long sought to unravel the complexities of market relationships, often casting their net wide in an effort to capture unexpected correlations and uncover hidden patterns. In "Meats and Markets: A Statistical Analysis," Smith and Doe present a comprehensive analysis examining the relationship between annual US household spending on meats, poultry, fish, and eggs and the stock price of The Home Depot. Their rigorous approach highlights the importance of understanding consumer dietary preferences as a potential driving force behind market dynamics. Our findings align with their insights, painting a vivid picture of how consumer choices can impact not only the dinner table but also the stock market. As the French say, "No matter how you slice it, the link between meat and HD stock price is hard to ignore."
Furthermore, Jones discusses the impact of consumer trends on retail sectors in "Economics of Consumption: From Milk to Lumber." While the book primarily focuses on broader consumer behaviors, it does recognize possible interactions between seemingly unrelated markets. This notion echoes our own research, which reveals a surprisingly strong connection between household spending on animal products and The Home Depot's stock price. It seems that in the realm of market analysis, there's always room for some unexpected interplay, much like finding a fish in the lumber aisle—it's all interconnected, even when it seems fishy.
In a similar vein, "The Meat of Economics" by Smithson delves into the intricate relationship between consumer spending habits and stock market performance, shedding light on the potential influence of meat consumption on retail stock prices. Our study aligns with Smithson's narrative, illustrating that consumer preferences for meat and meat-related products can have a significant impact on the stock performance of home improvement retailers. It's safe to say that when it comes to meat and stock prices, the stakes are high, and we're slicing through to discover the rare connection between these seemingly separate markets.
Turning to the world of fiction, the classic novel "The Catcher in the Rye" by J.D. Salinger may not seem directly related to market analysis, but its reference to a staple food product, rye, serves as a reminder that even in literature, our consumption habits can influence the narrative. In a similarly evocative manner, our research seeks to demonstrate that the choices we make at the grocery store can have a ripple effect on the financial markets, much like a well-timed rye joke. After all, who knew that rye and stock prices could share a common thread?
On the internet, the "Distracted Boyfriend" meme has taken social media by storm, humorously depicting a man being distracted from his current partner by an alluring passerby. In a parallel sense, our findings may captivate researchers with a similarly unexpected twist, drawing attention to the captivating relationship between the consumption of animal products and The Home Depot's stock price. As the meme humorously reveals, sometimes the most captivating subjects are the ones we least expect—much like stumbling upon an incredibly attractive cut of meat in the supermarket.
In summary, our literature review demonstrates the breadth of research on market correlations and their unexpected associations with consumer behavior and stock performance. From serious academic analysis to lighthearted references in popular culture, it's clear that the relationship between household spending on meats, poultry, fish, and eggs and The Home Depot's stock price is a rich tapestry of unexpected connections, ready to be grilled to perfection. As we forge ahead with our own study, we hold firm to the belief that every market has a story to tell, and it's our mission to uncover the juiciest cuts of insight, even if it means seasoning our analysis with a healthy dose of humor.
[[RESULTS]]
Our analysis revealed a substantial correlation coefficient of 0.9547119 between annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). This correlation coefficient indicates a strong positive linear relationship between the two variables, suggesting that as household spending on animal products increased, so did the stock price of The Home Depot. It's like the old adage, "You can't have too much of a good thing"—especially if that "good thing" is a juicy steak on the grill.
The r-squared value of 0.9114749 further underscores the robustness of this relationship. This means that a whopping 91.15% of the variability in The Home Depot's stock price can be explained by changes in annual US household spending on meats, poultry, fish, and eggs. That's almost as solid as a well-built BBQ grill.
Furthermore, with a p-value of less than 0.01, our findings attest to the statistical significance of this correlation. In other words, the likelihood of observing such a strong relationship by chance alone is less than 1%, which is about as rare as a blue steak. Our results provide compelling evidence to support the notion that there is indeed a tangible link between consumer spending on animal products and the performance of The Home Depot in the stock market.
Fig. 1 (to be included) visually encapsulates this noteworthy correlation, illustrating the tight clustering of data points around the upward-sloping trend line. The scatterplot drives home the point that, much like a well-curated charcuterie board, these two variables are artfully interconnected.
In summary, our results offer a rare glimpse into the flavorful convergence of consumer spending habits and stock market performance. It's as if the financial markets and the meat markets have been cooking up a recipe for success all along—proving that when it comes to market trends, everything's better with a little bit of seasoning.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our investigation into the correlation between annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price has left us with some meaty food for thought. Our findings substantially support the prior research, affirming the unexpected yet robust connection between consumer dietary preferences and retail stock performance. It seems this relationship is not just a flimsy skewer, but a sturdy rotisserie of market dynamics.
Our results align closely with the insights presented by the "Meats and Markets: A Statistical Analysis" study conducted by Smith and Doe. Much like a meticulously prepared barbecue, their findings laid a solid foundation highlighting the integral connection between consumer dietary habits and stock prices. It's almost as if their study was the thorough seasoning that perfectly complemented the juicy steak of our own research.
Similarly, our findings resonate with the narrative put forth in "The Meat of Economics" by Smithson. Just as the marinade infuses flavor into a cut of meat, our analysis has illuminated the influential role of consumer spending on animal products in shaping the stock performance of retail giants. It seems that, much like the perfect blend of herbs and spices, the market dynamics surrounding these variables have all the makings of a delectable feast for statistical exploration.
Our results shed light on the substantial impact of consumer dietary preferences on the stock performance of The Home Depot, emphasizing the need to consider the meat of the matter in market analysis. The correlation coefficient of 0.9547119 serves as a sturdy meat thermometer, indicating the strong positive linear relationship between these variables. It's as if the market and consumer spending have turned into an unexpected pairing, much like discovering the perfect wine to complement a hearty steak dinner.
Furthermore, our study bolsters the notion that consumer choices at the supermarket can exert a tangible influence on retail stock prices, echoing the sentiments expressed in "Economics of Consumption: From Milk to Lumber" by Jones. This reinforces the idea that the financial markets are seasoned with the flavors of consumer behavior, creating an interplay that is both unexpected and remarkably impactful. The connection between household spending on meats, poultry, fish, and eggs and The Home Depot's stock price is like a delicious soup—complex, surprising, and undeniable.
In conclusion, our research not only unveils the unexpected correlation between these seemingly distinct entities but also adds a touch of humor to the otherwise serious world of academic inquiry. It's clear that just like a good meal, the field of research benefits from a dash of spice and humor. As we savor the flavor of our findings, it's evident that the link between consumer dietary preferences and stock market performance is more than just a casual encounter—it's a well-marinated relationship waiting to be explored.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between Annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.
Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price"
[[ABSTRACT]]
In this study, we set out to uncover the unexpected common ground between the annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). By delving into data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we sought to demonstrate that, much like a well-marbled steak, these seemingly disparate entities are more connected than we might think. Upon conducting our analysis, we discovered a striking correlation coefficient of 0.9547119 and p < 0.01 for the period spanning from 2002 to 2022.
Our findings illuminate the interplay between consumer dietary preferences and the retail home improvement sector, painting a picture of interconnected markets that may raise some eyebrows—just like a particularly intriguing fish at the market. Unexpectedly, our research suggests that as household spending on animal products rises, so does The Home Depot's stock price, demonstrating a trend reminiscent of a well-planned barbecue—both markets heat up together. As the saying goes, "Where there's smoke, there's fire"—and in this case, where there's meat, there's a parallel rise in HD stock price. Our study not only sheds light on this surprising relationship, but also offers a rare opportunity to pepper our analysis with some punny humor. After all, in the world of research, it's important to have a little fun—just like grilling season. So, let’s steak our claim in this delightful correlation with the confidence of a seasoned grillmaster.
[[INTRDUCTION]]
It is a truth universally acknowledged, that a hungry man in possession of a good fortune must be in want of a hearty meal. However, what may not be so widely acknowledged is the potential link between the consumption of meats, poultry, fish, and eggs and the prosperity of The Home Depot (HD) as a company. As the old saying goes, "What do you call a pig thief? A hamburglar!" But, in the world of academic research, we're not out to steal any puns, just to dig deep into the data to see how these markets are "bacon" (making)!
In recent years, the study of intermarket correlations has expanded beyond the traditional financial sectors to consider unlikely connections between consumption patterns and stock performance. Our research aims to bridge this gap of curiosity and carve out a better understanding of the meaty relationship between household spending trends and the stock price of The Home Depot. So, let’s not chicken out on this endeavor and instead dive into the data with scientific curiosity and a good sense of humor.
One might wonder, "What do you get when you cross a dog and a calculator? A friend you can count on!" But, in the world of scientific inquiry, we aim to cross household spending on animal products with the stock performance of HD to uncover insights that we can truly count on. Through this examination, we aim to demonstrate whether there is truly a statistically significant link or if our findings will be nothing more than a statistical “red herring.”
As we embark on this quest, it's important to acknowledge the inherent complexity of studying market relationships. After all, understanding the dynamics of consumer behavior and investment patterns can sometimes feel like trying to juggle multiple balls of statistical significance while riding a unicycle on a tightrope. However, armed with robust data and a willingness to embrace the unexpected, we believe we can negotiate this scientific circus to uncover some truly intriguing findings.
So, grab your lab coat and spatula—I mean, your data analysis software—and let's sizzle our way through the steak of statistics to reveal the tender truth behind this unlikely correlation. After all, in the world of research, as in the world of grilling, it's all about finding that perfect medium rare.
[[RESULTS]]
Our analysis revealed a substantial correlation coefficient of 0.9547119 between annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). This correlation coefficient indicates a strong positive linear relationship between the two variables, suggesting that as household spending on animal products increased, so did the stock price of The Home Depot. It's like the old adage, "You can't have too much of a good thing"—especially if that "good thing" is a juicy steak on the grill.
The r-squared value of 0.9114749 further underscores the robustness of this relationship. This means that a whopping 91.15% of the variability in The Home Depot's stock price can be explained by changes in annual US household spending on meats, poultry, fish, and eggs. That's almost as solid as a well-built BBQ grill.
Furthermore, with a p-value of less than 0.01, our findings attest to the statistical significance of this correlation. In other words, the likelihood of observing such a strong relationship by chance alone is less than 1%, which is about as rare as a blue steak. Our results provide compelling evidence to support the notion that there is indeed a tangible link between consumer spending on animal products and the performance of The Home Depot in the stock market.
Fig. 1 (to be included) visually encapsulates this noteworthy correlation, illustrating the tight clustering of data points around the upward-sloping trend line. The scatterplot drives home the point that, much like a well-curated charcuterie board, these two variables are artfully interconnected.
In summary, our results offer a rare glimpse into the flavorful convergence of consumer spending habits and stock market performance. It's as if the financial markets and the meat markets have been cooking up a recipe for success all along—proving that when it comes to market trends, everything's better with a little bit of seasoning.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our investigation into the connection between annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD) has brought some truly unexpected findings to the table. Our results reveal a strong correlation, reminding us of the importance of a well-balanced diet—of data, that is. It's clear that just like a well-marinated steak, these variables have been soaking in a flavorful relationship that has sizzled its way into the stock market.
The robustness of this correlation, with a r-squared value of 0.9114749, underscores the meaty nature of this connection. It seems that when it comes to market trends, this link has been simmering low and slow, ready to be served up as a delectable insight for analysts and investors alike. As they say, "No matter how you slice it, the stock market and meat market have carved out a connection worth savoring."
The statistical significance of our findings, with a p-value of less than 0.01, implies that this correlation is no fluke—unlike a rare sighting of a statistical unicorn. It's a real, tangible link that we believe deserves some serious consideration. We've gone beyond just skimming the surface of market trends; we've dived deep into the ocean of data and reeled in a catch that's as impressive as a marlin.
Our study not only sheds light on this surprising relationship but also offers a rare opportunity to drop some punny references into the mix. After all, when it comes to academic research, a little humor can turn a dry paper into a juicy steak of scientific inquiry. It's important to toe the line between statistical rigor and interesting storytelling; otherwise, we'd risk turning our readers into the statistical equivalent of overcooked chicken—tough to digest.
In light of these compelling findings, we are confident in asserting that no further research is needed in this area. We've grilled this topic to perfection and found it to be as rare as a statistical diamond in the rough. It's time to hang up our lab coats and enjoy the fruits of our labor—just like savoring a delicious barbecue dinner. In the world of research, as in the world of cooking, knowing when to take the steak off the grill is just as important as knowing when to put it on.
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Finances and Food Trends
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price. Respond only with the name of a fictional organization.
ChatGPT:
The Center for Economic Analysis of Unusual Market Correlations
Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price with an abstract of In this study, we set out to uncover the unexpected common ground between the annual US household spending on meats, poultry, fish, and eggs and The Home Depot's stock price (HD). By delving into data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we sought to demonstrate that, much like a well-marbled steak, these seemingly disparate entities are more connected than we might think. Upon conducting our analysis, we discovered a striking correlation coefficient of 0.9547119 and p < 0.01 for the period spanning from 2002 to 2022.
Our findings illuminate the interplay between consumer dietary preferences and the retail home improvement sector, painting a picture of interconnected markets that may raise some eyebrows—just like a particularly intriguing fish at the market. Unexpectedly, our research suggests that as household spending on animal products rises, so does The Home Depot's stock price, demonstrating a trend reminiscent of a well-planned barbecue—both markets heat up together. As the saying goes, "Where there's smoke, there's fire"—and in this case, where there's meat, there's a parallel rise in HD stock price. Our study not only sheds light on this surprising relationship, but also offers a rare opportunity to pepper our analysis with some punny humor. After all, in the world of research, it's important to have a little fun—just like grilling season. So, let’s steak our claim in this delightful correlation with the confidence of a seasoned grillmaster.
ChatGPT:
household spending, animal products, meat, poultry, fish, eggs, Home Depot, stock price, correlation, consumer dietary preferences, retail sector, market analysis, Bureau of Labor Statistics, LSEG Analytics, Refinitiv, interconnected markets, correlation coefficient, consumer behavior, retail industry
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Annual US household spending on meats, poultry, fish, and eggsDetailed data title: Average annual household spend on meats, poultry, fish, and eggs
Source: Bureau of Labor Statistics
See what else correlates with Annual US household spending on meats, poultry, fish, and eggs
The Home Depot's stock price (HD)
Detailed data title: Opening price of The Home Depot (HD) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function
See what else correlates with The Home Depot's stock price (HD)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.
r2 = 0.9114749 (Coefficient of determination)
This means 91.1% of the change in the one variable (i.e., The Home Depot's stock price (HD)) is predictable based on the change in the other (i.e., Annual US household spending on meats, poultry, fish, and eggs) over the 21 years from 2002 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.9E-11. 0.0000000000187121267933805640
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.
But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.
Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.95 in 1.9E-9% of random cases. Said differently, if you correlated 53,441,279,607 random variables You don't actually need 53 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.
p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.
In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.
Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 20 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 20 because we have two variables measured over a period of 21 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.
[ 0.89, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
| 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | |
| Annual US household spending on meats, poultry, fish, and eggs (Household spend) | 798 | 825 | 880 | 764 | 797 | 777 | 846 | 841 | 784 | 832 | 852 | 856 | 892 | 896 | 890 | 944 | 961 | 980 | 1075 | 1115 | 1216 |
| The Home Depot's stock price (HD) (Stock price) | 51.01 | 24.21 | 35.75 | 42.99 | 40.39 | 41.3 | 27.13 | 23.07 | 29.15 | 35.2 | 42.41 | 63.57 | 82.11 | 105.16 | 130.11 | 135.1 | 190.21 | 169.71 | 219.08 | 266.01 | 416.57 |
Why this works
- Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
- Lack of causal connection: There is probably
Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied. - Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple
Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is. - Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves.
Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.Step 2: Open a plaintext editor like Notepad and paste the code below into it.
Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"
Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.
Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.
Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.
Step 7: Run the Python script by typing "python calculate_correlation.py"
If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:
"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."
# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats
# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):
# Calculate Pearson correlation coefficient and p-value
correlation, p_value = stats.pearsonr(array1, array2)
# Calculate R-squared as the square of the correlation coefficient
r_squared = correlation**2
return correlation, r_squared, p_value
# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([798,825,880,764,797,777,846,841,784,832,852,856,892,896,890,944,961,980,1075,1115,1216,])
array_2 = np.array([51.01,24.21,35.75,42.99,40.39,41.3,27.13,23.07,29.15,35.2,42.41,63.57,82.11,105.16,130.11,135.1,190.21,169.71,219.08,266.01,416.57,])
array_1_name = "Annual US household spending on meats, poultry, fish, and eggs"
array_2_name = "The Home Depot's stock price (HD)"
# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)
# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)Reuseable content
You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.
For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
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Download images for these variables:
- High resolution line chart
The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
Alternatively you can use a tool like Inkscape. - High resolution line chart, optimized for mobile
- Alternative high resolution line chart
- Scatterplot
- Portable line chart (png)
- Portable line chart (png), optimized for mobile
- Line chart for only Annual US household spending on meats, poultry, fish, and eggs
- Line chart for only The Home Depot's stock price (HD)
- AI-generated correlation image
- The spurious research paper: Meating Demands: The Correlation Between Household Spending on Animal Products and The Home Depot's Stock Price
Bravo! Your evaluation rocks!
Correlation ID: 3714 · Black Variable ID: 19888 · Red Variable ID: 1560
