Download png, svg
AI explanation
As people buttered up their cornbread and biscuits, they were in a better mood, leading to an increase in Southern hospitality. This in turn attracted more tourists to the South, boosting the demand for copper to build quirky roadside attractions like the world's largest garden gnome made entirely of copper. This increased demand for copper drove up Southern Copper's stock price. So, remember, spread a little butter, and watch those stocks sizzle!
Model: dalle-3
Prompt: Generate an image that looks like a scene from a Disney movie, depicting a sunny southern town where people happily enjoy buttery biscuits and cornbread. Their smiles reflect a surge of positivity as they savor these treats. In the background, the town's trading post is bustling with activity, where fingers slick with butter seamlessly count money. The stock price for Southern Copper surges as the demand for copper in the region increases, all thanks to the buttery delights and the positive outlook they bring. 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: Butter consumption and Southern Copper's stock price (SCCO). 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: Parallax art A photo-realistic image Voxel art An image that looks like it is a scene from A Disney Movie Cybernetic art
ChatGPT: An image that looks like it is a scene from A Disney Movie
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 Butter consumption and Southern Copper's stock price (SCCO), in the following situation: As butter consumption increased, people's arteries became more lubricated, leading to a smoother flow of blood and a general feeling of well-being. This resulted in a surge of positivity, leading to a higher demand for copper in the Southern region. Plus, buttery fingers made it easier to count money, prompting more investments in Southern Copper. After all, who can resist a stock that's "buttering up" investors? . Keep the description simple.
ChatGPT: In a sunny southern town, people happily enjoy buttery biscuits and cornbread, their smiles reflecting the surge of positivity. As they savor their treats, the arteries in their bodies appear well-lubricated, ensuring a smooth flow of blood and an overall feeling of well-being. Meanwhile, at the local trading post, fingers slick with butter seamlessly count money, prompting more investments in Southern Copper. The stock price for Southern Copper (SCCO) surges as the demand for copper in the region increases, all thanks to the buttery delights and the positive outlook they bring.
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: [ An image that looks like it is a scene from A Disney Movie ] and depicting this scene: In a sunny southern town, people happily enjoy buttery biscuits and cornbread, their smiles reflecting the surge of positivity. As they savor their treats, the arteries in their bodies appear well-lubricated, ensuring a smooth flow of blood and an overall feeling of well-being. Meanwhile, at the local trading post, fingers slick with butter seamlessly count money, prompting more investments in Southern Copper. The stock price for Southern Copper (SCCO) surges as the demand for copper in the region increases, all thanks to the buttery delights and the positive outlook they bring. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that looks like a scene from a Disney movie, depicting a sunny southern town where people happily enjoy buttery biscuits and cornbread. Their smiles reflect a surge of positivity as they savor these treats. In the background, the town's trading post is bustling with activity, where fingers slick with butter seamlessly count money. The stock price for Southern Copper surges as the demand for copper in the region increases, all thanks to the buttery delights and the positive outlook they bring.
*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 Butter consumption caused Southern Copper's stock price (SCCO) to increase.
AI academic paper
 |
Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO) The Journal of Culinary Finance Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Butter consumption and Southern Copper's stock price (SCCO). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Include a pun in the title.
Your research team used data from USDA and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.8329561 and p < 0.01 for 2002 to 2021.
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]]
Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO)
[[ABSTRACT]]
The relationship between butter consumption and stock prices may seem like a strange pairing, but our research sets out to butter up the idea that there might be a connection. Analysts have long debated what makes the stock market churn, and our findings suggest that butter consumption could be a key ingredient. Using data from the USDA and LSEG Analytics, we uncovered a strong correlation between butter consumption and the stock price of Southern Copper (SCCO). Our regression analysis revealed a correlation coefficient of 0.8329561 and a p-value less than 0.01 for the period from 2002 to 2021.
It's highly unusual to consider butter as a potential determinant of stock prices, but as the saying goes, "Where there's a will, there's a way," or in this case, "Where there's a whey, there's a whey!" We delve into the potential mechanisms underlying this surprising correlation, exploring the spread of information, market sentiment, and consumer behavior. By churning through the data, we hope to butter the bread of knowledge and shed light on this unanticipated link. After all, in the world of finance, it's important to take everything with a grain of salt – or perhaps a pat of butter.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Butter consumption and Southern Copper's stock price (SCCO). 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]]
Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO)
[[ABSTRACT]]
The relationship between butter consumption and stock prices may seem like a strange pairing, but our research sets out to butter up the idea that there might be a connection. Analysts have long debated what makes the stock market churn, and our findings suggest that butter consumption could be a key ingredient. Using data from the USDA and LSEG Analytics, we uncovered a strong correlation between butter consumption and the stock price of Southern Copper (SCCO). Our regression analysis revealed a correlation coefficient of 0.8329561 and a p-value less than 0.01 for the period from 2002 to 2021.
It's highly unusual to consider butter as a potential determinant of stock prices, but as the saying goes, "Where there's a will, there's a way," or in this case, "Where there's a whey, there's a whey!" We delve into the potential mechanisms underlying this surprising correlation, exploring the spread of information, market sentiment, and consumer behavior. By churning through the data, we hope to butter the bread of knowledge and shed light on this unanticipated link. After all, in the world of finance, it's important to take everything with a grain of salt – or perhaps a pat of butter.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
The study of economics and finance often involves delving into unexpected relationships, but few would expect to find a connection between the world of butter and the stock market. However, our research aims to spread light on the potential link between butter consumption and the stock price of Southern Copper (SCCO). As the old saying goes, "I can't believe it's not butter," but our findings may just have you believing in this unlikely relationship.
It's common for researchers to be dairy interested in exploring diverse factors that influence stock prices, but our study takes the cake in terms of unusual variables. With the rise of big data and complex statistical models, we have the tools to investigate correlations that may have previously been overlooked – or, in this case, over-churned.
While the idea of butter affecting stock prices may seem like a slippery slope, our analysis reveals a strong correlation coefficient that can't simply be margarined over. We sought to butter up the research community's appetite for unorthodox correlations and hope our findings spread like, well, butter on toast.
In the following sections, we will churn through the existing literature and theoretical frameworks, before diving into our methodology and results. So, butter get ready for an illuminating journey into the surprisingly interconnected world of butter consumption and stock market dynamics – and don’t forget to pack your sense of humor. After all, in the world of research, a good pun is like a well-spread layer of butter – it just makes everything better.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Butter consumption and Southern Copper's stock price (SCCO). 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. Perhaps you also got inspiration from some board games that are vaugely related.
Here is the title and abstract of the paper:
[[TITLE]]
Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO)
[[ABSTRACT]]
The relationship between butter consumption and stock prices may seem like a strange pairing, but our research sets out to butter up the idea that there might be a connection. Analysts have long debated what makes the stock market churn, and our findings suggest that butter consumption could be a key ingredient. Using data from the USDA and LSEG Analytics, we uncovered a strong correlation between butter consumption and the stock price of Southern Copper (SCCO). Our regression analysis revealed a correlation coefficient of 0.8329561 and a p-value less than 0.01 for the period from 2002 to 2021.
It's highly unusual to consider butter as a potential determinant of stock prices, but as the saying goes, "Where there's a will, there's a way," or in this case, "Where there's a whey, there's a whey!" We delve into the potential mechanisms underlying this surprising correlation, exploring the spread of information, market sentiment, and consumer behavior. By churning through the data, we hope to butter the bread of knowledge and shed light on this unanticipated link. After all, in the world of finance, it's important to take everything with a grain of salt – or perhaps a pat of butter.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The study of economics and finance often involves delving into unexpected relationships, but few would expect to find a connection between the world of butter and the stock market. However, our research aims to spread light on the potential link between butter consumption and the stock price of Southern Copper (SCCO). As the old saying goes, "I can't believe it's not butter," but our findings may just have you believing in this unlikely relationship.
It's common for researchers to be dairy interested in exploring diverse factors that influence stock prices, but our study takes the cake in terms of unusual variables. With the rise of big data and complex statistical models, we have the tools to investigate correlations that may have previously been overlooked – or, in this case, over-churned.
While the idea of butter affecting stock prices may seem like a slippery slope, our analysis reveals a strong correlation coefficient that can't simply be margarined over. We sought to butter up the research community's appetite for unorthodox correlations and hope our findings spread like, well, butter on toast.
In the following sections, we will churn through the existing literature and theoretical frameworks, before diving into our methodology and results. So, butter get ready for an illuminating journey into the surprisingly interconnected world of butter consumption and stock market dynamics – and don’t forget to pack your sense of humor. After all, in the world of research, a good pun is like a well-spread layer of butter – it just makes everything better.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
In the realm of unconventional economic indicators, the link between butter consumption and stock prices may appear as outlandish as a cow jumping over the moon. However, the literature offers some intriguing perspectives on unexpected determinants of financial markets. Smith and Doe (2015) provide a comprehensive analysis of traditional economic indicators, while also alluding to the potential influence of unorthodox factors such as dietary trends. Their work lays the groundwork for considering non-traditional variables in financial modeling, which sets the stage for our investigation into the connection between butter consumption and the stock price of Southern Copper (SCCO).
Jones (2017) further explores the complexities of market behavior, emphasizing the role of consumer sentiment and its impact on stock prices. While Jones's work does not specifically address butter consumption, it underscores the need to consider the interplay between consumer behavior and financial markets. As we delve into the nuances of butter consumption and its potential influence on stock prices, Jones's insights serve as a relevant backdrop for our analysis.
Turning to broader discussions of dietary habits and their societal implications, "Food Choice and Sustainability" by Smith et al. (2018) offers valuable insights into the factors shaping consumer food preferences. While this work focuses primarily on sustainability and ethical considerations, it prompts us to consider the multifaceted nature of food consumption patterns and their potential relevance to economic dynamics. Our investigation into butter consumption as a potential marker of market sentiment aligns with the underlying themes of consumer choice and its broader societal impact.
In the whimsical world of fiction, where butter churns alongside fantasy, J.K. Rowling's "Harry Potter and the Philosopher's Stone" incorporates references to magical butterbeer, a beverage enjoyed by the characters in the wizarding world. While the link between fictional beverages and stock prices may seem tenuous at best, the creative realm of fiction reminds us to embrace imaginative thinking, even in the context of economic research. Additionally, the strategic resource management depicted in "Settlers of Catan" presents valuable parallels to our exploration of resource utilization and market dynamics, albeit in a more whimsical and fictional context.
As we wade through the sea of literature, it becomes clear that our investigation into butter consumption and its potential impact on the stock price of Southern Copper (SCCO) possesses a blend of seriousness and levity. In the spirit of embracing unexpected connections and engaging in unconventional inquiries, we forge ahead with our data-driven analysis, seeking to butter up the world of financial research with our unorthodox yet compelling findings. As they say, "Don't go baking my heart," but our research might just have you rethinking the ingredients of market influence.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Butter consumption and Southern Copper's stock price (SCCO). 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 USDA and LSEG Analytics (Refinitiv) . You used data from 2002 to 2021
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]]
Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO)
[[ABSTRACT]]
The relationship between butter consumption and stock prices may seem like a strange pairing, but our research sets out to butter up the idea that there might be a connection. Analysts have long debated what makes the stock market churn, and our findings suggest that butter consumption could be a key ingredient. Using data from the USDA and LSEG Analytics, we uncovered a strong correlation between butter consumption and the stock price of Southern Copper (SCCO). Our regression analysis revealed a correlation coefficient of 0.8329561 and a p-value less than 0.01 for the period from 2002 to 2021.
It's highly unusual to consider butter as a potential determinant of stock prices, but as the saying goes, "Where there's a will, there's a way," or in this case, "Where there's a whey, there's a whey!" We delve into the potential mechanisms underlying this surprising correlation, exploring the spread of information, market sentiment, and consumer behavior. By churning through the data, we hope to butter the bread of knowledge and shed light on this unanticipated link. After all, in the world of finance, it's important to take everything with a grain of salt – or perhaps a pat of butter.
[[INTRODUCTION]]
The study of economics and finance often involves delving into unexpected relationships, but few would expect to find a connection between the world of butter and the stock market. However, our research aims to spread light on the potential link between butter consumption and the stock price of Southern Copper (SCCO). As the old saying goes, "I can't believe it's not butter," but our findings may just have you believing in this unlikely relationship.
It's common for researchers to be dairy interested in exploring diverse factors that influence stock prices, but our study takes the cake in terms of unusual variables. With the rise of big data and complex statistical models, we have the tools to investigate correlations that may have previously been overlooked – or, in this case, over-churned.
While the idea of butter affecting stock prices may seem like a slippery slope, our analysis reveals a strong correlation coefficient that can't simply be margarined over. We sought to butter up the research community's appetite for unorthodox correlations and hope our findings spread like, well, butter on toast.
In the following sections, we will churn through the existing literature and theoretical frameworks, before diving into our methodology and results. So, butter get ready for an illuminating journey into the surprisingly interconnected world of butter consumption and stock market dynamics – and don’t forget to pack your sense of humor. After all, in the world of research, a good pun is like a well-spread layer of butter – it just makes everything better.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To begin our quest to uncover the buttery secrets of stock prices, we first collected data from the United States Department of Agriculture (USDA) and the London Stock Exchange Group (LSEG) Analytics (Refinitiv). Our team was spread thinly across the internet, combing through various databases and sources to gather the necessary information. After all, in the world of research, it's important to have a strong "data foundation" – much like the base of a good butter sculpture.
Once we had amassed our data, we focused on the period from 2002 to 2021, allowing us to churn through nearly two decades of information. This extensive timeline gave us a well-rounded view of both butter consumption patterns and stock price movements, ensuring that our analysis was not just a flash in the pan.
With our data in hand, we embarked on the process of homogenizing and standardizing the variables of interest. The butter consumption data was obtained in pounds per capita, reflecting the "butter spread" across the population. Meanwhile, stock price data for Southern Copper (SCCO) was collected on a daily basis, as we "dipped into" the market movements over the years.
To uncover the potential correlation between butter consumption and stock prices, we engaged in a bit of statistical alchemy, employing the magical arts of regression analysis. We used a simple linear regression model to quantify the relationship between butter consumption and Southern Copper's stock price. As any good scientist knows, it's important to "spread" out our methods and avoid cutting corners, especially when dealing with such a unique combination of variables.
It's essential to mention that all precautionary measures were taken to ensure that our statistical assumptions were not "buttered up," and our analysis was rigorously tested for robustness. After all, in the world of research, we can't afford to let any unsavory statistical anomalies "slip through the cracks."
In addition to our regression analysis, we also explored potential confounding variables and conducted sensitivity analyses to ensure that our findings weren't simply a result of some other "spreadable" factors influencing stock prices. This process allowed us to "whisk" away any doubts about the validity of our results and present a "palatable" analysis to the research community.
Finishing off with our statistical testing, we engaged in a bit of Monte Carlo simulation to assess the stability and reliability of our results. This step allowed us to "butter up" our confidence intervals and ensure that our findings weren't "melting" under scrutiny.
As researchers, we always welcome a "healthy churn" of skepticism and critical evaluation, hoping to "spread" knowledge in the most engaging and impactful way possible. In the end, conducting research is a bit like making a complex dish – it requires patience, precision, and a dash of creativity. For our next steps, we will unveil the delectable results of our analysis, offering a "buttery spread" of insights into the remarkable relationship between butter consumption and stock prices.
In the wise words of Julia Child, "With enough butter, anything is good." And in the world of research, with enough data and meticulous methodology, anything is possible.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Butter consumption and Southern Copper's stock price (SCCO). 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 USDA and LSEG Analytics (Refinitiv) .
For the time period 2002 to 2021, you found a correlation 0.8329561, r-squared of 0.6938159, 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]]
Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO)
[[ABSTRACT]]
The relationship between butter consumption and stock prices may seem like a strange pairing, but our research sets out to butter up the idea that there might be a connection. Analysts have long debated what makes the stock market churn, and our findings suggest that butter consumption could be a key ingredient. Using data from the USDA and LSEG Analytics, we uncovered a strong correlation between butter consumption and the stock price of Southern Copper (SCCO). Our regression analysis revealed a correlation coefficient of 0.8329561 and a p-value less than 0.01 for the period from 2002 to 2021.
It's highly unusual to consider butter as a potential determinant of stock prices, but as the saying goes, "Where there's a will, there's a way," or in this case, "Where there's a whey, there's a whey!" We delve into the potential mechanisms underlying this surprising correlation, exploring the spread of information, market sentiment, and consumer behavior. By churning through the data, we hope to butter the bread of knowledge and shed light on this unanticipated link. After all, in the world of finance, it's important to take everything with a grain of salt – or perhaps a pat of butter.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
The study of economics and finance often involves delving into unexpected relationships, but few would expect to find a connection between the world of butter and the stock market. However, our research aims to spread light on the potential link between butter consumption and the stock price of Southern Copper (SCCO). As the old saying goes, "I can't believe it's not butter," but our findings may just have you believing in this unlikely relationship.
It's common for researchers to be dairy interested in exploring diverse factors that influence stock prices, but our study takes the cake in terms of unusual variables. With the rise of big data and complex statistical models, we have the tools to investigate correlations that may have previously been overlooked – or, in this case, over-churned.
While the idea of butter affecting stock prices may seem like a slippery slope, our analysis reveals a strong correlation coefficient that can't simply be margarined over. We sought to butter up the research community's appetite for unorthodox correlations and hope our findings spread like, well, butter on toast.
In the following sections, we will churn through the existing literature and theoretical frameworks, before diving into our methodology and results. So, butter get ready for an illuminating journey into the surprisingly interconnected world of butter consumption and stock market dynamics – and don’t forget to pack your sense of humor. After all, in the world of research, a good pun is like a well-spread layer of butter – it just makes everything better.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
Our analysis revealed a significant positive correlation between butter consumption and the stock price of Southern Copper (SCCO) over the period from 2002 to 2021. The correlation coefficient of 0.8329561 indicates a strong positive relationship between these seemingly unrelated variables. It appears that in the world of finance, the "butterfly effect" could be more than just a whimsical concept.
Fig. 1 provides a visual representation of the relationship between butter consumption and SCCO stock price. The scatterplot clearly demonstrates the tight bond between these variables, serving as a reminder that sometimes, things are simply butter together.
Upon further analysis, our regression model indicated an r-squared of 0.6938159, suggesting that approximately 69.38% of the variability in SCCO stock price can be explained by fluctuations in butter consumption. While some may find this association hard to believe, it seems that in the world of economics, there's no such thing as "too much butter," statistically speaking.
It must be emphasized that the p-value of less than 0.01 provides strong evidence against the null hypothesis, indicating that this relationship is not merely the result of chance. In other words, it's no margarine of error – the connection between butter consumption and SCCO stock price is as solid as a well-churned block of butter.
In summary, our results indicate that butter consumption and SCCO stock price are significantly and positively correlated, contrary to conventional wisdom. This unexpected finding prompts us to reconsider the potential influence of dairy products on financial markets, proving that sometimes, the most outlandish-seeming hypotheses can be the real breadwinners.
As researchers, we often strive to uncover hidden connections and untangle complex relationships. In this case, it seems that the butter was right in front of us all along. This discovery goes to show that in the world of data analysis, delving into unusual variables can lead to some truly buttery-smooth results.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Butter consumption and Southern Copper's stock price (SCCO). 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]]
Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO)
[[ABSTRACT]]
The relationship between butter consumption and stock prices may seem like a strange pairing, but our research sets out to butter up the idea that there might be a connection. Analysts have long debated what makes the stock market churn, and our findings suggest that butter consumption could be a key ingredient. Using data from the USDA and LSEG Analytics, we uncovered a strong correlation between butter consumption and the stock price of Southern Copper (SCCO). Our regression analysis revealed a correlation coefficient of 0.8329561 and a p-value less than 0.01 for the period from 2002 to 2021.
It's highly unusual to consider butter as a potential determinant of stock prices, but as the saying goes, "Where there's a will, there's a way," or in this case, "Where there's a whey, there's a whey!" We delve into the potential mechanisms underlying this surprising correlation, exploring the spread of information, market sentiment, and consumer behavior. By churning through the data, we hope to butter the bread of knowledge and shed light on this unanticipated link. After all, in the world of finance, it's important to take everything with a grain of salt – or perhaps a pat of butter.
[[LITERATURE REVIEW]]
In the realm of unconventional economic indicators, the link between butter consumption and stock prices may appear as outlandish as a cow jumping over the moon. However, the literature offers some intriguing perspectives on unexpected determinants of financial markets. Smith and Doe (2015) provide a comprehensive analysis of traditional economic indicators, while also alluding to the potential influence of unorthodox factors such as dietary trends. Their work lays the groundwork for considering non-traditional variables in financial modeling, which sets the stage for our investigation into the connection between butter consumption and the stock price of Southern Copper (SCCO).
Jones (2017) further explores the complexities of market behavior, emphasizing the role of consumer sentiment and its impact on stock prices. While Jones's work does not specifically address butter consumption, it underscores the need to consider the interplay between consumer behavior and financial markets. As we delve into the nuances of butter consumption and its potential influence on stock prices, Jones's insights serve as a relevant backdrop for our analysis.
Turning to broader discussions of dietary habits and their societal implications, "Food Choice and Sustainability" by Smith et al. (2018) offers valuable insights into the factors shaping consumer food preferences. While this work focuses primarily on sustainability and ethical considerations, it prompts us to consider the multifaceted nature of food consumption patterns and their potential relevance to economic dynamics. Our investigation into butter consumption as a potential marker of market sentiment aligns with the underlying themes of consumer choice and its broader societal impact.
In the whimsical world of fiction, where butter churns alongside fantasy, J.K. Rowling's "Harry Potter and the Philosopher's Stone" incorporates references to magical butterbeer, a beverage enjoyed by the characters in the wizarding world. While the link between fictional beverages and stock prices may seem tenuous at best, the creative realm of fiction reminds us to embrace imaginative thinking, even in the context of economic research. Additionally, the strategic resource management depicted in "Settlers of Catan" presents valuable parallels to our exploration of resource utilization and market dynamics, albeit in a more whimsical and fictional context.
As we wade through the sea of literature, it becomes clear that our investigation into butter consumption and its potential impact on the stock price of Southern Copper (SCCO) possesses a blend of seriousness and levity. In the spirit of embracing unexpected connections and engaging in unconventional inquiries, we forge ahead with our data-driven analysis, seeking to butter up the world of financial research with our unorthodox yet compelling findings. As they say, "Don't go baking my heart," but our research might just have you rethinking the ingredients of market influence.
[[RESULTS]]
Our analysis revealed a significant positive correlation between butter consumption and the stock price of Southern Copper (SCCO) over the period from 2002 to 2021. The correlation coefficient of 0.8329561 indicates a strong positive relationship between these seemingly unrelated variables. It appears that in the world of finance, the "butterfly effect" could be more than just a whimsical concept.
Fig. 1 provides a visual representation of the relationship between butter consumption and SCCO stock price. The scatterplot clearly demonstrates the tight bond between these variables, serving as a reminder that sometimes, things are simply butter together.
Upon further analysis, our regression model indicated an r-squared of 0.6938159, suggesting that approximately 69.38% of the variability in SCCO stock price can be explained by fluctuations in butter consumption. While some may find this association hard to believe, it seems that in the world of economics, there's no such thing as "too much butter," statistically speaking.
It must be emphasized that the p-value of less than 0.01 provides strong evidence against the null hypothesis, indicating that this relationship is not merely the result of chance. In other words, it's no margarine of error – the connection between butter consumption and SCCO stock price is as solid as a well-churned block of butter.
In summary, our results indicate that butter consumption and SCCO stock price are significantly and positively correlated, contrary to conventional wisdom. This unexpected finding prompts us to reconsider the potential influence of dairy products on financial markets, proving that sometimes, the most outlandish-seeming hypotheses can be the real breadwinners.
As researchers, we often strive to uncover hidden connections and untangle complex relationships. In this case, it seems that the butter was right in front of us all along. This discovery goes to show that in the world of data analysis, delving into unusual variables can lead to some truly buttery-smooth results.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our research has churned out some fascinating findings regarding the unexpected connection between butter consumption and the stock price of Southern Copper (SCCO). Despite the initial skepticism surrounding this unorthodox pairing, our results support the notion that when it comes to financial markets, butter might just be the "bread and butter" of a surprising determinant. It seems that this unusual relationship has been buttering the bread of financial analysts without them even realizing it!
As we reflect on the literature, it's worth noting that Smith and Doe (2015) may have unknowingly spread the metaphorical butter on the idea of integrating unorthodox factors into financial modeling. With our findings corroborating the potential influence of butter consumption on stock prices, it becomes apparent that sometimes, even the most whimsical hypotheses can hold the churn of truth.
Our regression analysis revealed a correlation coefficient of 0.8329561, boasting a p-value less than 0.01, which suggests that this buttery bond is no fluke. It's truly remarkable how a seemingly innocent dairy product could be so closely tied to stock market dynamics. Our results align with Jones's (2017) emphasis on the impact of consumer sentiment on stock prices. It seems that the saying "spread the love" should perhaps be updated to "spread the butter, watch the stock price scatter!" Such is the power of butter in the world of finance – it can really make markets melt!
The correlation coefficient of 0.8329561 is quite a noteworthy value, much like the plot of a good crime novel. With a high r-squared of 0.6938159, we can confidently state that approximately 69.38% of the variability in SCCO stock price can be attributed to fluctuations in butter consumption. It appears that in this case, the butter truly does make the bread rise – and so do stock prices!
Our findings not only challenge conventional wisdom but also highlight the importance of exploring unorthodox variables in financial analysis. It's a reminder that when it comes to research, we shouldn't be afraid to "butter our bread on both sides" – explore unexpected connections and embrace unconventional theories. After all, sometimes the most unexpected ingredients can lead to the most delectable results! As the saying goes, "Where there's a whisk, there's a way," or should we say, "Where there's butter, there's a whey to financial discoveries!"
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Butter consumption and Southern Copper's stock price (SCCO). 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]]
Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO)
[[ABSTRACT]]
The relationship between butter consumption and stock prices may seem like a strange pairing, but our research sets out to butter up the idea that there might be a connection. Analysts have long debated what makes the stock market churn, and our findings suggest that butter consumption could be a key ingredient. Using data from the USDA and LSEG Analytics, we uncovered a strong correlation between butter consumption and the stock price of Southern Copper (SCCO). Our regression analysis revealed a correlation coefficient of 0.8329561 and a p-value less than 0.01 for the period from 2002 to 2021.
It's highly unusual to consider butter as a potential determinant of stock prices, but as the saying goes, "Where there's a will, there's a way," or in this case, "Where there's a whey, there's a whey!" We delve into the potential mechanisms underlying this surprising correlation, exploring the spread of information, market sentiment, and consumer behavior. By churning through the data, we hope to butter the bread of knowledge and shed light on this unanticipated link. After all, in the world of finance, it's important to take everything with a grain of salt – or perhaps a pat of butter.
[[INTRDUCTION]]
The study of economics and finance often involves delving into unexpected relationships, but few would expect to find a connection between the world of butter and the stock market. However, our research aims to spread light on the potential link between butter consumption and the stock price of Southern Copper (SCCO). As the old saying goes, "I can't believe it's not butter," but our findings may just have you believing in this unlikely relationship.
It's common for researchers to be dairy interested in exploring diverse factors that influence stock prices, but our study takes the cake in terms of unusual variables. With the rise of big data and complex statistical models, we have the tools to investigate correlations that may have previously been overlooked – or, in this case, over-churned.
While the idea of butter affecting stock prices may seem like a slippery slope, our analysis reveals a strong correlation coefficient that can't simply be margarined over. We sought to butter up the research community's appetite for unorthodox correlations and hope our findings spread like, well, butter on toast.
In the following sections, we will churn through the existing literature and theoretical frameworks, before diving into our methodology and results. So, butter get ready for an illuminating journey into the surprisingly interconnected world of butter consumption and stock market dynamics – and don’t forget to pack your sense of humor. After all, in the world of research, a good pun is like a well-spread layer of butter – it just makes everything better.
[[RESULTS]]
Our analysis revealed a significant positive correlation between butter consumption and the stock price of Southern Copper (SCCO) over the period from 2002 to 2021. The correlation coefficient of 0.8329561 indicates a strong positive relationship between these seemingly unrelated variables. It appears that in the world of finance, the "butterfly effect" could be more than just a whimsical concept.
Fig. 1 provides a visual representation of the relationship between butter consumption and SCCO stock price. The scatterplot clearly demonstrates the tight bond between these variables, serving as a reminder that sometimes, things are simply butter together.
Upon further analysis, our regression model indicated an r-squared of 0.6938159, suggesting that approximately 69.38% of the variability in SCCO stock price can be explained by fluctuations in butter consumption. While some may find this association hard to believe, it seems that in the world of economics, there's no such thing as "too much butter," statistically speaking.
It must be emphasized that the p-value of less than 0.01 provides strong evidence against the null hypothesis, indicating that this relationship is not merely the result of chance. In other words, it's no margarine of error – the connection between butter consumption and SCCO stock price is as solid as a well-churned block of butter.
In summary, our results indicate that butter consumption and SCCO stock price are significantly and positively correlated, contrary to conventional wisdom. This unexpected finding prompts us to reconsider the potential influence of dairy products on financial markets, proving that sometimes, the most outlandish-seeming hypotheses can be the real breadwinners.
As researchers, we often strive to uncover hidden connections and untangle complex relationships. In this case, it seems that the butter was right in front of us all along. This discovery goes to show that in the world of data analysis, delving into unusual variables can lead to some truly buttery-smooth results.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our research has spread light on the unexpected connection between butter consumption and the stock price of Southern Copper (SCCO). The significant positive correlation coefficient of 0.8329561 and the p-value less than 0.01 certainly butter the bread of evidence for this unlikely relationship. It appears that in the world of finance, making sense of stock prices is truly a "butterfly effect," where small changes can lead to larger consequences.
Our findings may have some investors spreading their portfolios thin, and others churning over the implications. As we often say in the world of research, "When it comes to unusual correlations, the truth will always rise to the top, like cream on butter." It's important for analysts to not be too easily swayed and to take any correlation with a grain of salt – or, in this case, a pinch of butter.
The strength of the relationship uncovered here suggests that future studies should carefully butter-up the data and delve into the underlying mechanisms that might drive this connection. However, it seems that we have truly spread our knowledge across this field, and no further research is needed. After all, when it comes to butter and stock prices, this research has churned out some truly unbeatable results.
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 Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO). Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Culinary Finance
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 Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO). Respond only with the name of a fictional organization.
ChatGPT:
The Society for Radical Dairy Research
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 Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO) with an abstract of The relationship between butter consumption and stock prices may seem like a strange pairing, but our research sets out to butter up the idea that there might be a connection. Analysts have long debated what makes the stock market churn, and our findings suggest that butter consumption could be a key ingredient. Using data from the USDA and LSEG Analytics, we uncovered a strong correlation between butter consumption and the stock price of Southern Copper (SCCO). Our regression analysis revealed a correlation coefficient of 0.8329561 and a p-value less than 0.01 for the period from 2002 to 2021.
It's highly unusual to consider butter as a potential determinant of stock prices, but as the saying goes, "Where there's a will, there's a way," or in this case, "Where there's a whey, there's a whey!" We delve into the potential mechanisms underlying this surprising correlation, exploring the spread of information, market sentiment, and consumer behavior. By churning through the data, we hope to butter the bread of knowledge and shed light on this unanticipated link. After all, in the world of finance, it's important to take everything with a grain of salt – or perhaps a pat of butter.
ChatGPT:
"butter consumption stock prices correlation," "Southern Copper stock price," "USDA butter consumption data," "LSEG Analytics data," "regression analysis correlation coefficient," "butter consumption market sentiment," "butter consumption consumer behavior," "butter consumption stock market," "finance unusual correlations," "stock market determinants," "unanticipated stock price determinants"
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Butter consumptionDetailed data title: Per capita consumption of Butter in the US
Source: USDA
See what else correlates with Butter consumption
Southern Copper's stock price (SCCO)
Detailed data title: Opening price of Southern Copper (SCCO) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function
See what else correlates with Southern Copper's stock price (SCCO)
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 = 0.6938159 (Coefficient of determination)
This means 69.4% of the change in the one variable (i.e., Southern Copper's stock price (SCCO)) is predictable based on the change in the other (i.e., Butter consumption) over the 20 years from 2002 through 2021.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.2E-6. 0.0000051564118075638800000000
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 0.83 in 0.00052% of random cases. Said differently, if you correlated 193,933 random variables You don't actually need 193 thousand 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 19 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 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.
[ 0.62, 0.93 ] 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 | |
| Butter consumption (Pounds per person) | 4.4 | 4.5 | 4.5 | 4.5 | 4.7 | 4.7 | 5 | 5 | 4.9 | 5.4 | 5.5 | 5.5 | 5.5 | 5.6 | 5.7 | 5.7 | 6 | 6.2 | 6.3 | 6.5 |
| Southern Copper's stock price (SCCO) (Stock price) | 1.98 | 2.39 | 7.82 | 7.83 | 11.05 | 17.48 | 35.04 | 16.07 | 32.99 | 48.95 | 30.83 | 38.9 | 28.78 | 28.06 | 25.4 | 32.28 | 47.94 | 30.11 | 42.96 | 67.38 |
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([4.4,4.5,4.5,4.5,4.7,4.7,5,5,4.9,5.4,5.5,5.5,5.5,5.6,5.7,5.7,6,6.2,6.3,6.5,])
array_2 = np.array([1.98,2.39,7.82,7.83,11.05,17.48,35.04,16.07,32.99,48.95,30.83,38.9,28.78,28.06,25.4,32.28,47.94,30.11,42.96,67.38,])
array_1_name = "Butter consumption"
array_2_name = "Southern Copper's stock price (SCCO)"
# 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.
Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.
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 Butter consumption
- Line chart for only Southern Copper's stock price (SCCO)
- AI-generated correlation image
- The spurious research paper: Spreading the Butter: An Unlikely Link Between Butter Consumption and the Stock Price of Southern Copper (SCCO)
Your dedication to rating warms my heart!
Correlation ID: 2533 · Black Variable ID: 557 · Red Variable ID: 1698
