Spurious correlation #3,071 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is American cheese consumption and the second variable is ResMed's stock price (RMD). The chart goes from 2002 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is American cheese consumption and the second variable is ResMed's stock price (RMD). The chart goes from 2002 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

America's obsession with grilled cheese sandwiches led to a spike in happiness, prompting more people to invest in sleep apnea solutions like ResMed. It's a gouda investment for a feta night's sleep!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a vibrant American diner filled with a pastel-colored, vaporwave-inspired ambiance. The scene captures the joyful atmosphere as people relish grilled cheese sandwiches and cheesy fries in a nostalgic, neon-lit setting. Outside the diner, a sleek, retro digital ticker board prominently displays ResMed's soaring stock price (RMD), symbolizing the correlation with the dreamy satisfaction experienced by the diner's patrons. The image is rich in vivid, vintage tones and radiates a playful, dreamlike aesthetic. 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: American cheese consumption and ResMed's stock price (RMD). 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: Surrealism Art nouveau Vaporwave Photorealism Hyper-realistic
ChatGPT: Vaporwave

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 American cheese consumption and ResMed's stock price (RMD), in the following situation: As Americans consumed more American cheese, ResMed's stock price soared due to the cheesy grin-inducing dreams caused by sleep apnea, increasing demand for their products. Say cheese for the stock market!. Keep the description simple.
ChatGPT: In a bustling American diner, people are happily enjoying grilled cheese sandwiches with a side of cheesy fries. The aroma of melted American cheese fills the air, as patrons smile and chat, displaying cheesy grins. Meanwhile, on a digital ticker board outside the diner, ResMed's stock price (RMD) is seen rapidly climbing, reflecting the surge in demand for their sleep apnea products, fueled by the happy dreams induced by the cheesy meals consumed inside.

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: [ Vaporwave ] and depicting this scene: In a bustling American diner, people are happily enjoying grilled cheese sandwiches with a side of cheesy fries. The aroma of melted American cheese fills the air, as patrons smile and chat, displaying cheesy grins. Meanwhile, on a digital ticker board outside the diner, ResMed's stock price (RMD) is seen rapidly climbing, reflecting the surge in demand for their sleep apnea products, fueled by the happy dreams induced by the cheesy meals consumed inside. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a vibrant American diner filled with a pastel-colored, vaporwave-inspired ambiance. The scene captures the joyful atmosphere as people relish grilled cheese sandwiches and cheesy fries in a nostalgic, neon-lit setting. Outside the diner, a sleek, retro digital ticker board prominently displays ResMed's soaring stock price (RMD), symbolizing the correlation with the dreamy satisfaction experienced by the diner's patrons. The image is rich in vivid, vintage tones and radiates a playful, dreamlike aesthetic.

*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.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
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 American cheese consumption caused ResMed's stock price (RMD) to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

The Whey to Wealth: A Cheesy Connection Between American Cheese Consumption and ResMed's Stock Price

The International Journal of Dairy Economics and Finance

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 American cheese consumption and ResMed's stock price (RMD). 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 few real TV shows that sound like they might be relevant to the topic that you watched as research.

Here is the title and abstract of the paper:
[[TITLE]]
The Whey to Wealth: A Cheesy Connection Between American Cheese Consumption and ResMed's Stock Price

[[ABSTRACT]]
This research delves into the curious correlation between American cheese consumption and ResMed's stock price, aiming to uncover whether there is a substantial link between these seemingly unrelated entities. Utilizing data from the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv) from the period spanning 2002 to 2021, our study reveals a correlation coefficient of 0.9023719 and a statistically significant p-value of less than 0.01.

Our findings demonstrate that as American cheese consumption rises, ResMed's stock price follows suit, creating a brie-lliant positive correlation between the two variables. This association challenges conventional economic theories and highlights the importance of considering unconventional factors in stock price movement.

Our study sparks a gouda discussion in the finance realm, shedding light on the potential influence of dairy products on stock market dynamics. The cheddarly delightful connection between American cheese and ResMed's stock price opens the door to further exploration of unorthodox determinants of financial markets, provolone to be an area ripe for investigation.

In conclusion, our research not only provides valuable insight for investors and financial analysts but also levitates the discussion of dairy-based influences on stock prices to a whole new level. This study serves as a feta-accompli in unraveling the enigmatic forces driving stock market movements, illustrating that, indeed, there is more than meets the eye in the relationship between American cheese consumption and a company’s stock valuation.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The notorious phrase "say cheese" takes on a whole new meaning in the context of our research. In this study, we explore the potential, and dare I say, grate connection between American cheese consumption and ResMed's stock price. It's a cheesy endeavor, to be sure, but the correlation we've uncovered has implications that are anything but mild.
As researchers, we are constantly on the hunt for correlations, much like a mouse sniffing out a particularly pungent piece of cheddar. And in the case of our investigation, we have stumbled upon a correlation that is as unexpected as finding a mozzarella stick in a bowl of cereal. It's a gouda job that we embarked on this study, for what we found is no mere curdiosity.
The empirical evidence we present challenges the notion that stock prices are influenced solely by traditional economic indicators. With a correlation coefficient as striking as a well-aged gouda and a statistically significant p-value of less than 0.01, our findings are not to be dismissed as mere brie-jections. Instead, they demand a thorough examination.
By delving into the interplay between American cheese consumption and ResMed's stock price, we unravel a narrative that is both creamy and compelling. This research endeavors to break free from the shackles of conventional economic thinking and embrace the cheddar side of stock market dynamics. As economists, we cannot camembert the idea of dismissing any potential influence, no matter how unconventional it may seem.
Stay tuned for a study that is sure to melt away any skepticism and usher in a new era of cheese-related stock market analysis. This research is bound to provoke an assortment of responses, from mild amusement to sharp cheddar-cisms, but one thing is for sure - it has the potential to open the door to a whole new whey of thinking about financial markets.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find a statistically significant positive correlation between American cheese consumption and financial market movements. Similarly, in "Doe and Jones," the authors present evidence suggesting that unconventional factors, such as dairy product consumption, may have unexplored impacts on stock prices.

However, as we delve deeper into the literature, we encounter a rather surprising study by "Cheesy and Wensleydale," which unveils a correlation between ResMed's stock price and the average number of holes in Swiss cheese. This unexpected finding not only adds a layer of complexity to the existing research but also exudes a gouda level of cheesiness in its implications.

Turning to non-fiction sources, "The Big Cheese: A Comprehensive Analysis of Dairy in Economics" by Parmesan and Romano provides a thorough overview of the historical significance of cheese consumption in economic paradigms. Additionally, "Milk Money: The Economics of Dairy Farming" by Cheddar and Monterey Jack sheds light on the intricate interplay between dairy markets and financial systems.

On a more speculative note, the fictional works "The Gouda Code" by Dan Brown and "Cheddar Games" by Suzanne Collins offer intriguing narratives that, while not rooted in empirical evidence, spark the imagination and prompt consideration of cheese-related influences on speculative fiction.

In our quest for empirical grounding, we ventured beyond the bounds of academic literature and turned to television for insights. Series such as "Cheese and the City" and "Breaking Brie" somewhat facetiously explore the intersection of cheese and urban life, while providing intriguing parallels to the complexities of financial markets.

As we navigate through this literature, we encounter a smorgasbord of perspectives that range from the conventional to the outright whimsical. While some sources maintain a sober and scholarly tone, others bring forth a sense of levity and cheese-related puns that are as difficult to resist as a well-aged cheddar.

It appears that the influence of cheese on financial markets may be more far-reaching and multifaceted than previously assumed, perhaps even permeating the realms of fiction and entertainment. With a nod to the wacky world of cheese-related research, we proceed to unpack the empirical evidence that underpins our investigation into the curious relationship between American cheese consumption and ResMed's stock price.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 American cheese consumption and ResMed's stock price (RMD). 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]]
The Whey to Wealth: A Cheesy Connection Between American Cheese Consumption and ResMed's Stock Price

[[ABSTRACT]]
This research delves into the curious correlation between American cheese consumption and ResMed's stock price, aiming to uncover whether there is a substantial link between these seemingly unrelated entities. Utilizing data from the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv) from the period spanning 2002 to 2021, our study reveals a correlation coefficient of 0.9023719 and a statistically significant p-value of less than 0.01.

Our findings demonstrate that as American cheese consumption rises, ResMed's stock price follows suit, creating a brie-lliant positive correlation between the two variables. This association challenges conventional economic theories and highlights the importance of considering unconventional factors in stock price movement.

Our study sparks a gouda discussion in the finance realm, shedding light on the potential influence of dairy products on stock market dynamics. The cheddarly delightful connection between American cheese and ResMed's stock price opens the door to further exploration of unorthodox determinants of financial markets, provolone to be an area ripe for investigation.

In conclusion, our research not only provides valuable insight for investors and financial analysts but also levitates the discussion of dairy-based influences on stock prices to a whole new level. This study serves as a feta-accompli in unraveling the enigmatic forces driving stock market movements, illustrating that, indeed, there is more than meets the eye in the relationship between American cheese consumption and a company’s stock valuation.

[[INTRODUCTION]]
The notorious phrase "say cheese" takes on a whole new meaning in the context of our research. In this study, we explore the potential, and dare I say, grate connection between American cheese consumption and ResMed's stock price. It's a cheesy endeavor, to be sure, but the correlation we've uncovered has implications that are anything but mild.
As researchers, we are constantly on the hunt for correlations, much like a mouse sniffing out a particularly pungent piece of cheddar. And in the case of our investigation, we have stumbled upon a correlation that is as unexpected as finding a mozzarella stick in a bowl of cereal. It's a gouda job that we embarked on this study, for what we found is no mere curdiosity.
The empirical evidence we present challenges the notion that stock prices are influenced solely by traditional economic indicators. With a correlation coefficient as striking as a well-aged gouda and a statistically significant p-value of less than 0.01, our findings are not to be dismissed as mere brie-jections. Instead, they demand a thorough examination.
By delving into the interplay between American cheese consumption and ResMed's stock price, we unravel a narrative that is both creamy and compelling. This research endeavors to break free from the shackles of conventional economic thinking and embrace the cheddar side of stock market dynamics. As economists, we cannot camembert the idea of dismissing any potential influence, no matter how unconventional it may seem.
Stay tuned for a study that is sure to melt away any skepticism and usher in a new era of cheese-related stock market analysis. This research is bound to provoke an assortment of responses, from mild amusement to sharp cheddar-cisms, but one thing is for sure - it has the potential to open the door to a whole new whey of thinking about financial markets.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the connection between American cheese consumption and ResMed's stock price, our research team employed a methodological approach that was as thorough as a cheese grater and as meticulous as a cheese-monger inspecting his wares.

First, we gathered data on American cheese consumption from the United States Department of Agriculture (USDA). Our data collection process was as precise as slicing through a block of cheddar, ensuring that we captured the cheese consumption patterns across different regions and demographic groups. We also cross-referenced our findings with international cheese consumption trends to ensure a comprehensive understanding of the global cheese landscape. After all, a study on American cheese should not overlook its international cheese-mates.

Next, we obtained stock price data for ResMed from LSEG Analytics (Refinitiv). This involved sifting through an immense amount of financial data, akin to separating curds from whey, to isolate the specific movements of ResMed's stock price. We delved into the intricacies of stock market fluctuations, much like a scientist studying the fermentation process of cheese, to capture the nuances of ResMed's stock performance with precision.

Once the data were gathered, we embarked on a journey through statistical analysis that would make even the most seasoned cheesemakers envious. Employing regression analysis, we sought to identify any correlations between American cheese consumption and ResMed's stock price. Our regression model was as robust as a mature Parmigiano-Reggiano and as resilient as a wheel of Gruyère, ensuring that we accounted for potential confounding variables and spurious correlations.

Additionally, we conducted heteroscedasticity tests and multicollinearity diagnostics to ensure the validity of our findings. We scrutinized our statistical models like a cheese connoisseur examining the aroma and texture of a fine Roquefort, leaving no room for ambiguity or unaccounted variables.

To further validate our results, we performed sensitivity analysis, akin to testing the versatility of a Swiss cheese in various culinary creations. This allowed us to gauge the robustness of the observed correlation and ascertain its stability under different scenarios, ensuring that our findings stood strong like a well-aged Gouda in the face of alternative assumptions.

Finally, we subjected our findings to rigorous peer review, inviting perspectives from experts in finance, economics, and dairy industry aficionados. This process was as thorough as a cheese tasting competition, where only the most palatable and well-rounded findings earned a place on the research platter.

In essence, our methodology combined the precision of a skilled cheesemaker with the rigor of a seasoned statistician, resulting in an analysis that is as rich and flavorful as a perfectly aged cheese. Our endeavors aimed to unveil a correlation as captivating as a cheese sculpture, carving out a niche in the realm of empirical finance and challenging traditional assumptions with a hint of dairy-inspired whimsy.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 American cheese consumption and ResMed's stock price (RMD). 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 0.9023719, r-squared of 0.8142751, 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]]
The Whey to Wealth: A Cheesy Connection Between American Cheese Consumption and ResMed's Stock Price

[[ABSTRACT]]
This research delves into the curious correlation between American cheese consumption and ResMed's stock price, aiming to uncover whether there is a substantial link between these seemingly unrelated entities. Utilizing data from the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv) from the period spanning 2002 to 2021, our study reveals a correlation coefficient of 0.9023719 and a statistically significant p-value of less than 0.01.

Our findings demonstrate that as American cheese consumption rises, ResMed's stock price follows suit, creating a brie-lliant positive correlation between the two variables. This association challenges conventional economic theories and highlights the importance of considering unconventional factors in stock price movement.

Our study sparks a gouda discussion in the finance realm, shedding light on the potential influence of dairy products on stock market dynamics. The cheddarly delightful connection between American cheese and ResMed's stock price opens the door to further exploration of unorthodox determinants of financial markets, provolone to be an area ripe for investigation.

In conclusion, our research not only provides valuable insight for investors and financial analysts but also levitates the discussion of dairy-based influences on stock prices to a whole new level. This study serves as a feta-accompli in unraveling the enigmatic forces driving stock market movements, illustrating that, indeed, there is more than meets the eye in the relationship between American cheese consumption and a company’s stock valuation.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The notorious phrase "say cheese" takes on a whole new meaning in the context of our research. In this study, we explore the potential, and dare I say, grate connection between American cheese consumption and ResMed's stock price. It's a cheesy endeavor, to be sure, but the correlation we've uncovered has implications that are anything but mild.
As researchers, we are constantly on the hunt for correlations, much like a mouse sniffing out a particularly pungent piece of cheddar. And in the case of our investigation, we have stumbled upon a correlation that is as unexpected as finding a mozzarella stick in a bowl of cereal. It's a gouda job that we embarked on this study, for what we found is no mere curdiosity.
The empirical evidence we present challenges the notion that stock prices are influenced solely by traditional economic indicators. With a correlation coefficient as striking as a well-aged gouda and a statistically significant p-value of less than 0.01, our findings are not to be dismissed as mere brie-jections. Instead, they demand a thorough examination.
By delving into the interplay between American cheese consumption and ResMed's stock price, we unravel a narrative that is both creamy and compelling. This research endeavors to break free from the shackles of conventional economic thinking and embrace the cheddar side of stock market dynamics. As economists, we cannot camembert the idea of dismissing any potential influence, no matter how unconventional it may seem.
Stay tuned for a study that is sure to melt away any skepticism and usher in a new era of cheese-related stock market analysis. This research is bound to provoke an assortment of responses, from mild amusement to sharp cheddar-cisms, but one thing is for sure - it has the potential to open the door to a whole new whey of thinking about financial markets.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The data analysis revealed a strong positive correlation (r = 0.9023719) between American cheese consumption and ResMed's stock price for the period 2002 to 2021. This finding indicates that as American cheese consumption increased, there was a corresponding upward movement in ResMed's stock price. The r-squared value of 0.8142751 suggests that approximately 81.43% of the variance in RMD stock price can be explained by changes in American cheese consumption. The p-value, being less than 0.01, attests to the statistical significance of the correlation.

It seems that, just like a well-aged cheddar, the relationship between American cheese consumption and stock prices has matured over time, leaving a strong aftertaste in the world of finance. The cheesier the research topic, the greater the stock price impact – a correlation that is anything but grating. Just remember, it's not easy being cheesy, especially when it comes to influencing financial markets.

As depicted in Fig. 1, the scatterplot visually depicts the strong positive correlation between American cheese consumption and ResMed's stock price. The data points tightly hug the upward-sloping regression line, illustrating the close connection between these seemingly unrelated variables. One might say that the relationship is as tight as the packaging on a block of gouda.

These findings provide empirical support for the notion that there may be more than meets the eye when it comes to the determinants of stock price movements. While traditional economic theories often overlook the potential influence of dairy products, our study emphasizes the need to consider unorthodox factors that may impact financial markets. After all, in the world of finance, it's not just about the cheddar – it's also about the cheese.

In conclusion, our study unearths a correlation that may initially seem cheesy, but upon closer examination, reveals a significant and thought-provoking connection between American cheese consumption and stock price movements. It is clear that the influence of dairy products extends beyond the kitchen and into the realm of finance, where it shapes the appetite for investment and offers a different perspective on the forces driving market dynamics. This research may just be the queso to unlocking a new understanding of stock price determinants and stimulating a wave of fromage-related financial analysis.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 American cheese consumption and ResMed's stock price (RMD). 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]]
The Whey to Wealth: A Cheesy Connection Between American Cheese Consumption and ResMed's Stock Price

[[ABSTRACT]]
This research delves into the curious correlation between American cheese consumption and ResMed's stock price, aiming to uncover whether there is a substantial link between these seemingly unrelated entities. Utilizing data from the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv) from the period spanning 2002 to 2021, our study reveals a correlation coefficient of 0.9023719 and a statistically significant p-value of less than 0.01.

Our findings demonstrate that as American cheese consumption rises, ResMed's stock price follows suit, creating a brie-lliant positive correlation between the two variables. This association challenges conventional economic theories and highlights the importance of considering unconventional factors in stock price movement.

Our study sparks a gouda discussion in the finance realm, shedding light on the potential influence of dairy products on stock market dynamics. The cheddarly delightful connection between American cheese and ResMed's stock price opens the door to further exploration of unorthodox determinants of financial markets, provolone to be an area ripe for investigation.

In conclusion, our research not only provides valuable insight for investors and financial analysts but also levitates the discussion of dairy-based influences on stock prices to a whole new level. This study serves as a feta-accompli in unraveling the enigmatic forces driving stock market movements, illustrating that, indeed, there is more than meets the eye in the relationship between American cheese consumption and a company’s stock valuation.

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find a statistically significant positive correlation between American cheese consumption and financial market movements. Similarly, in "Doe and Jones," the authors present evidence suggesting that unconventional factors, such as dairy product consumption, may have unexplored impacts on stock prices.
However, as we delve deeper into the literature, we encounter a rather surprising study by "Cheesy and Wensleydale," which unveils a correlation between ResMed's stock price and the average number of holes in Swiss cheese. This unexpected finding not only adds a layer of complexity to the existing research but also exudes a gouda level of cheesiness in its implications.
Turning to non-fiction sources, "The Big Cheese: A Comprehensive Analysis of Dairy in Economics" by Parmesan and Romano provides a thorough overview of the historical significance of cheese consumption in economic paradigms. Additionally, "Milk Money: The Economics of Dairy Farming" by Cheddar and Monterey Jack sheds light on the intricate interplay between dairy markets and financial systems.
On a more speculative note, the fictional works "The Gouda Code" by Dan Brown and "Cheddar Games" by Suzanne Collins offer intriguing narratives that, while not rooted in empirical evidence, spark the imagination and prompt consideration of cheese-related influences on speculative fiction.
In our quest for empirical grounding, we ventured beyond the bounds of academic literature and turned to television for insights. Series such as "Cheese and the City" and "Breaking Brie" somewhat facetiously explore the intersection of cheese and urban life, while providing intriguing parallels to the complexities of financial markets.
As we navigate through this literature, we encounter a smorgasbord of perspectives that range from the conventional to the outright whimsical. While some sources maintain a sober and scholarly tone, others bring forth a sense of levity and cheese-related puns that are as difficult to resist as a well-aged cheddar.
It appears that the influence of cheese on financial markets may be more far-reaching and multifaceted than previously assumed, perhaps even permeating the realms of fiction and entertainment. With a nod to the wacky world of cheese-related research, we proceed to unpack the empirical evidence that underpins our investigation into the curious relationship between American cheese consumption and ResMed's stock price.

[[RESULTS]]
The data analysis revealed a strong positive correlation (r = 0.9023719) between American cheese consumption and ResMed's stock price for the period 2002 to 2021. This finding indicates that as American cheese consumption increased, there was a corresponding upward movement in ResMed's stock price. The r-squared value of 0.8142751 suggests that approximately 81.43% of the variance in RMD stock price can be explained by changes in American cheese consumption. The p-value, being less than 0.01, attests to the statistical significance of the correlation.
It seems that, just like a well-aged cheddar, the relationship between American cheese consumption and stock prices has matured over time, leaving a strong aftertaste in the world of finance. The cheesier the research topic, the greater the stock price impact – a correlation that is anything but grating. Just remember, it's not easy being cheesy, especially when it comes to influencing financial markets.
As depicted in Fig. 1, the scatterplot visually depicts the strong positive correlation between American cheese consumption and ResMed's stock price. The data points tightly hug the upward-sloping regression line, illustrating the close connection between these seemingly unrelated variables. One might say that the relationship is as tight as the packaging on a block of gouda.
These findings provide empirical support for the notion that there may be more than meets the eye when it comes to the determinants of stock price movements. While traditional economic theories often overlook the potential influence of dairy products, our study emphasizes the need to consider unorthodox factors that may impact financial markets. After all, in the world of finance, it's not just about the cheddar – it's also about the cheese.
In conclusion, our study unearths a correlation that may initially seem cheesy, but upon closer examination, reveals a significant and thought-provoking connection between American cheese consumption and stock price movements. It is clear that the influence of dairy products extends beyond the kitchen and into the realm of finance, where it shapes the appetite for investment and offers a different perspective on the forces driving market dynamics. This research may just be the queso to unlocking a new understanding of stock price determinants and stimulating a wave of fromage-related financial analysis.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of our study corroborate the observations made by Smith et al. and Doe and Jones, which posited a substantial association between American cheese consumption and stock market movements. The statistically significant positive correlation we identified aligns with the prior research, reinforcing the indication that the dairy industry exerts a pronounced influence on financial dynamics. It appears that when it comes to the impact of cheese, the evidence is as sharp as a well-aged cheddar.

Furthermore, our results introduce a novel dimension to the existing literature by shedding light on the specific relationship between American cheese consumption and the stock price of ResMed (RMD). This connection adds depth to the discourse on the influence of unconventional factors, such as dairy products, on stock valuations, allowing us to gratefully appreciate the significance of such unorthodox determinants in the cheesterpieces of modern finance.

Our study builds upon the rather unexpected revelation by Cheesy and Wensleydale, who brought attention to the correlation between ResMed's stock price and the number of holes in Swiss cheese. While their findings may have initially seemed like a queso non-grata in the field of financial research, our discovery reinforces the idea that even the most seemingly random variables can have an impact, turning Swiss cheese holes into wholehearted considerations in stock market analyses.

The strong correlation between American cheese consumption and ResMed's stock price indicates that traders and investors may need to embrace an entirely new metric for evaluating market movements. After all, in the world of finance, it's not just about the cheddar – it's also about the cheese. This humorous aside indicates the seriousness with which the research findings are being considered, acknowledging the unexpected nature of the connection being made.

As our research continues to Roule on, it becomes increasingly evident that the influence of American cheese consumption on ResMed's stock price is not just a curdiosity but a significant phenomenon worthy of further examination.

In summary, the findings of our study serve to confirm the substantial connection between American cheese consumption and ResMed's stock price. This cheese-parable correlation underscores the need to broaden the scope of financial inquiry to encompass untraditional influences, as the potential for unexpected revelations in the dairy market may be grater than previously assumed.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 American cheese consumption and ResMed's stock price (RMD). 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]]
The Whey to Wealth: A Cheesy Connection Between American Cheese Consumption and ResMed's Stock Price

[[ABSTRACT]]
This research delves into the curious correlation between American cheese consumption and ResMed's stock price, aiming to uncover whether there is a substantial link between these seemingly unrelated entities. Utilizing data from the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv) from the period spanning 2002 to 2021, our study reveals a correlation coefficient of 0.9023719 and a statistically significant p-value of less than 0.01.

Our findings demonstrate that as American cheese consumption rises, ResMed's stock price follows suit, creating a brie-lliant positive correlation between the two variables. This association challenges conventional economic theories and highlights the importance of considering unconventional factors in stock price movement.

Our study sparks a gouda discussion in the finance realm, shedding light on the potential influence of dairy products on stock market dynamics. The cheddarly delightful connection between American cheese and ResMed's stock price opens the door to further exploration of unorthodox determinants of financial markets, provolone to be an area ripe for investigation.

In conclusion, our research not only provides valuable insight for investors and financial analysts but also levitates the discussion of dairy-based influences on stock prices to a whole new level. This study serves as a feta-accompli in unraveling the enigmatic forces driving stock market movements, illustrating that, indeed, there is more than meets the eye in the relationship between American cheese consumption and a company’s stock valuation.

[[INTRDUCTION]]
The notorious phrase "say cheese" takes on a whole new meaning in the context of our research. In this study, we explore the potential, and dare I say, grate connection between American cheese consumption and ResMed's stock price. It's a cheesy endeavor, to be sure, but the correlation we've uncovered has implications that are anything but mild.
As researchers, we are constantly on the hunt for correlations, much like a mouse sniffing out a particularly pungent piece of cheddar. And in the case of our investigation, we have stumbled upon a correlation that is as unexpected as finding a mozzarella stick in a bowl of cereal. It's a gouda job that we embarked on this study, for what we found is no mere curdiosity.
The empirical evidence we present challenges the notion that stock prices are influenced solely by traditional economic indicators. With a correlation coefficient as striking as a well-aged gouda and a statistically significant p-value of less than 0.01, our findings are not to be dismissed as mere brie-jections. Instead, they demand a thorough examination.
By delving into the interplay between American cheese consumption and ResMed's stock price, we unravel a narrative that is both creamy and compelling. This research endeavors to break free from the shackles of conventional economic thinking and embrace the cheddar side of stock market dynamics. As economists, we cannot camembert the idea of dismissing any potential influence, no matter how unconventional it may seem.
Stay tuned for a study that is sure to melt away any skepticism and usher in a new era of cheese-related stock market analysis. This research is bound to provoke an assortment of responses, from mild amusement to sharp cheddar-cisms, but one thing is for sure - it has the potential to open the door to a whole new whey of thinking about financial markets.

[[RESULTS]]
The data analysis revealed a strong positive correlation (r = 0.9023719) between American cheese consumption and ResMed's stock price for the period 2002 to 2021. This finding indicates that as American cheese consumption increased, there was a corresponding upward movement in ResMed's stock price. The r-squared value of 0.8142751 suggests that approximately 81.43% of the variance in RMD stock price can be explained by changes in American cheese consumption. The p-value, being less than 0.01, attests to the statistical significance of the correlation.
It seems that, just like a well-aged cheddar, the relationship between American cheese consumption and stock prices has matured over time, leaving a strong aftertaste in the world of finance. The cheesier the research topic, the greater the stock price impact – a correlation that is anything but grating. Just remember, it's not easy being cheesy, especially when it comes to influencing financial markets.
As depicted in Fig. 1, the scatterplot visually depicts the strong positive correlation between American cheese consumption and ResMed's stock price. The data points tightly hug the upward-sloping regression line, illustrating the close connection between these seemingly unrelated variables. One might say that the relationship is as tight as the packaging on a block of gouda.
These findings provide empirical support for the notion that there may be more than meets the eye when it comes to the determinants of stock price movements. While traditional economic theories often overlook the potential influence of dairy products, our study emphasizes the need to consider unorthodox factors that may impact financial markets. After all, in the world of finance, it's not just about the cheddar – it's also about the cheese.
In conclusion, our study unearths a correlation that may initially seem cheesy, but upon closer examination, reveals a significant and thought-provoking connection between American cheese consumption and stock price movements. It is clear that the influence of dairy products extends beyond the kitchen and into the realm of finance, where it shapes the appetite for investment and offers a different perspective on the forces driving market dynamics. This research may just be the queso to unlocking a new understanding of stock price determinants and stimulating a wave of fromage-related financial analysis.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study unearths a correlation that may initially seem cheesy, but upon closer examination, reveals a significant and thought-provoking connection between American cheese consumption and stock price movements. It is clear that the influence of dairy products extends beyond the kitchen and into the realm of finance, where it shapes the appetite for investment and offers a different perspective on the forces driving market dynamics. This research may just be the queso to unlocking a new understanding of stock price determinants and stimulating a wave of fromage-related financial analysis.

As we wrap up this research, it's evident that the connection between American cheese consumption and ResMed's stock price is no mere fondue-ing. The correlation we've uncovered is stronger than a block of parmesan, leaving us feeling gouda about the impact of dairy on stock prices.

We must admit, it's been a-mozzarella-ing journey delving into this unorthodox correlation. But as they say, when it comes to research, it's all gouda.

However, it's time to cut the cheese and conclude that no more research is needed in this area. We've already milked this topic for all it's worth, and to continue would just be over-doing it.

In the end, we can confidently say that this research serves as a halloumi-nating example of the multifaceted influences on stock prices, reminding us that in the world of finance, it's not just about the cheddar – it's also about the cheese.

No more research is needed in this area.

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 The Whey to Wealth: A Cheesy Connection Between American Cheese Consumption and ResMed's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of Dairy Economics and 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 The Whey to Wealth: A Cheesy Connection Between American Cheese Consumption and ResMed's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Dairy Economics and Stock Market Analysis

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 The Whey to Wealth: A Cheesy Connection Between American Cheese Consumption and ResMed's Stock Price with an abstract of This research delves into the curious correlation between American cheese consumption and ResMed's stock price, aiming to uncover whether there is a substantial link between these seemingly unrelated entities. Utilizing data from the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv) from the period spanning 2002 to 2021, our study reveals a correlation coefficient of 0.9023719 and a statistically significant p-value of less than 0.01.
Our findings demonstrate that as American cheese consumption rises, ResMed's stock price follows suit, creating a brie-lliant positive correlation between the two variables. This association challenges conventional economic theories and highlights the importance of considering unconventional factors in stock price movement.
Our study sparks a gouda discussion in the finance realm, shedding light on the potential influence of dairy products on stock market dynamics. The cheddarly delightful connection between American cheese and ResMed's stock price opens the door to further exploration of unorthodox determinants of financial markets, provolone to be an area ripe for investigation.
In conclusion, our research not only provides valuable insight for investors and financial analysts but also levitates the discussion of dairy-based influences on stock prices to a whole new level. This study serves as a feta-accompli in unraveling the enigmatic forces driving stock market movements, illustrating that, indeed, there is more than meets the eye in the relationship between American cheese consumption and a company’s stock valuation.

ChatGPT:

American cheese consumption, ResMed stock price, correlation, unconventional factors, stock market dynamics, dairy products, finance, stock price movement, economic theories, United States Department of Agriculture (USDA), LSEG Analytics, Refinitiv, stock market influences

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.

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Data details

American cheese consumption
Detailed data title: Per capita consumption of American cheese in the US
Source: USDA
See what else correlates with American cheese consumption

ResMed's stock price (RMD)
Detailed data title: Opening price of ResMed (RMD) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: ^{See full details} Via Microsoft Excel Stockhistory function

See what else correlates with ResMed's stock price (RMD)

Correlation r = 0.9023719 (Pearson correlation coefficient)
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 = 0.8142751 (Coefficient of determination)
This means 81.4% of the change in the one variable (i.e., ResMed's stock price (RMD)) is predictable based on the change in the other (i.e., American cheese consumption) over the 20 years from 2002 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.3E-8.^Show 0.0000000534427625056064800000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note 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 0.9 in 5.3E-6% of random cases. Said differently, if you correlated 18,711,608 random variables^Note You don't actually need 18 million 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, ^Note 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.

[ 0.77, 0.96 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} 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: ^Note 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
American cheese consumption (Pounds per person)	12.8314	12.5619	12.8612	12.649	13.0656	12.7929	13.1306	13.3553	13.3048	13.0392	13.2569	13.3573	13.6656	14.0444	14.3621	15.0901	15.4027	15.5389	15.5	16.1
ResMed's stock price (RMD) (Stock price)	13.48	7.69	10.38	12.8	19.4	24.93	25.46	18.82	26.32	34.95	25.75	42.45	47.01	56.4	52.97	62.1	85.2	111.99	155.4	213.24

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^Note 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^Note 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. ^Note 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. ^{Show the steps to do this.} 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([12.8314,12.5619,12.8612,12.649,13.0656,12.7929,13.1306,13.3553,13.3048,13.0392,13.2569,13.3573,13.6656,14.0444,14.3621,15.0901,15.4027,15.5389,15.5,16.1,])
array_2 = np.array([13.48,7.69,10.38,12.8,19.4,24.93,25.46,18.82,26.32,34.95,25.75,42.45,47.01,56.4,52.97,62.1,85.2,111.99,155.4,213.24,])
array_1_name = "American cheese consumption"
array_2_name = "ResMed's stock price (RMD)"

# 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. ^Note 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 ^Note 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 American cheese consumption
Line chart for only ResMed's stock price (RMD)
AI-generated correlation image
The spurious research paper: The Whey to Wealth: A Cheesy Connection Between American Cheese Consumption and ResMed's Stock Price

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Correlation ID: 3071 · Black Variable ID: 553 · Red Variable ID: 1905


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