Spurious correlation #2,365 · 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 Nasdaq's stock price (NDAQ). The chart goes from 2003 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 Nasdaq's stock price (NDAQ). The chart goes from 2003 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As more people indulged in gooey grilled cheese sandwiches, they found themselves in a euphoric state of cheesiness. This led to an increase in overall optimism, causing a spike in the stock market, including the Nasdaq. It seems like the phrase "say cheese" took on a whole new financial meaning!

^{Show image generation prompt} Model: dalle-3
Prompt: Generating Prompt... Description: [ An image that looks like it is a scene from a Pixar movie ] In a colorful, bustling American city, a fast-food restaurant is depicted, with people of various ages and backgrounds joyfully enjoying delicious cheeseburgers. The vibrant scene showcases the excitement and satisfaction of the customers as they savor their tasty meals. The air is filled with the mouthwatering aroma of sizzling American cheese, adding to the lively atmosphere. In the background, the iconic Nasdaq stock exchange is visualized with a digital display showing stock prices on the rise, highlighting the increased investor interest in fast-food chains. The prompt portrays a charming and captivating representation of a traditional American experience where the simple joy of savoring a cheeseburger is combined with the dynamic world of finance and investment. 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 Nasdaq's stock price (NDAQ). 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: Oragami Sci-fi fantacy Cutsy graphics Scalar art An image that looks like it is a scene from a Pixar movie
ChatGPT: An image that looks like it is a scene from a Pixar 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 American cheese consumption and Nasdaq's stock price (NDAQ), in the following situation: As American cheese consumption increased, so did the desire for cheeseburgers. This led to a surge in sales for fast food chains, prompting investors to buy more stocks in those companies. This increased demand for fast food stocks caused a ripple effect in the stock market, including the rise in Nasdaq's stock price.. Keep the description simple.
ChatGPT: In a bustling American city, people are seen enjoying delicious cheeseburgers at a fast-food restaurant. The aroma of sizzling American cheese fills the air as more and more cheeseburgers are being prepared to meet the growing demand. In the background, the Nasdaq stock exchange is depicted with stock prices rising on a digital display, showcasing the increased investor interest in fast food chains.

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 Pixar movie ] and depicting this scene: In a bustling American city, people are seen enjoying delicious cheeseburgers at a fast-food restaurant. The aroma of sizzling American cheese fills the air as more and more cheeseburgers are being prepared to meet the growing demand. In the background, the Nasdaq stock exchange is depicted with stock prices rising on a digital display, showcasing the increased investor interest in fast food chains. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generating Prompt... Description: [ An image that looks like it is a scene from a Pixar movie ] In a colorful, bustling American city, a fast-food restaurant is depicted, with people of various ages and backgrounds joyfully enjoying delicious cheeseburgers. The vibrant scene showcases the excitement and satisfaction of the customers as they savor their tasty meals. The air is filled with the mouthwatering aroma of sizzling American cheese, adding to the lively atmosphere. In the background, the iconic Nasdaq stock exchange is visualized with a digital display showing stock prices on the rise, highlighting the increased investor interest in fast-food chains. The prompt portrays a charming and captivating representation of a traditional American experience where the simple joy of savoring a cheeseburger is combined with the dynamic world of finance and investment.

*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 Nasdaq's stock price (NDAQ) to increase.

AI academic paper

(Because p < 0.01)

Say Cheese: The Gouda, The Bad, and The Nasdaq - Exploring the Correlation Between American Cheese Consumption and NDAQ Stock Price

The Dairy Economist

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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Nasdaq's stock price (NDAQ). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
"Say Cheese: The Gouda, The Bad, and The Nasdaq - Exploring the Correlation Between American Cheese Consumption and NDAQ Stock Price"

[[ABSTRACT]]
In this study, we delve into the curd-ious relationship between American cheese consumption and the stock market performance of Nasdaq (NDAQ). Using data sourced from the USDA and LSEG Analytics (Refinitiv), we sought to answer the age-old question: does American cheese have more influence on the economy than just being a sandwich topping? Our analysis covers the years 2003 to 2021, a period ripe with fluctuations in both cheese consumption and stock prices.

Upon conducting our research, we discovered a correlation coefficient of 0.9358575 with a significance level of p < 0.01, revealing a strong association between the two variables. While some may brie skeptical of such a connection, our findings cheddar light on the matter, highlighting the potential influence of cheese consumption on market sentiment and trading patterns. We discuss the implications of our results and propose further avenues of research to explore the wheyward impact of cheese on financial markets. So, grab some cheese and crackers, and let's fondue deeper into this dairy stock market relationship.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The interplay between food consumption and economic indicators has long been a subject of scholarly interest. From the infamous "butterfly effect" to the well-studied influence of coffee prices on productivity, the relationship between what we consume and the performance of financial markets has captivated researchers and pundits alike. In this vein, our study delves into the world of American cheese and its potential impact on the Nasdaq (NDAQ) stock price.
While some may view the consumption of American cheese as merely a dairy delight, we posited that there may be deeper implications for the stock market. After all, the cheesy correlation between consumer behavior and market movements is no longer just a "gouda" laugh at cocktail parties but a topic worthy of serious investigation.
To peel back the layers of this relationship, we conducted an in-depth analysis spanning the years 2003 to 2021, leveraging data from the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv). Our aim was to melt away any doubts regarding the potential impact of American cheese consumption on the stock performance of Nasdaq.
The results of our investigation unveiled a correlation coefficient of 0.9358575, with a significance level of p < 0.01, implicating a robust association between American cheese consumption and the stock price of Nasdaq. This finding may appear "grate," but it provides compelling evidence of a link that extends beyond mere coincidence. We acknowledge the sharp cheddar of skepticism that may accompany such a correlation, yet our analysis aims to slice through the conjecture and present a Parmesan-telligent argument for the influence of cheese on financial markets.
In the following sections, we will delve into the potential mechanisms underlying this relationship, consider the broader implications for market sentiment and trading behavior, and propose avenues for further research. As we embark on this fromage of investigation, we encourage readers to approach our findings with a discerning palate, leaning into the potential power of American cheese as an unlikely player in the stock market arena. So, grab a slice of cheese, raise a toast to empirical inquiry, and let's embark on this gouda journey together.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith and Doe (2018)," the authors find a positive correlation between cheese consumption and stock market performance, sparking further interest in the potential influence of dairy products on financial indicators. Expanding upon this, Jones et al. (2020) examined the specific case of American cheese and its impact on the Nasdaq (NDAQ) stock price, laying the foundation for our current investigation.

Adding a layer of complexity to the literature, "The Big Cheese: A Historical Analysis of Dairy and Dollars" by A. Gouda sheds light on the historical patterns of cheese consumption and economic trends, providing a matured perspective on the subject matter. Furthermore, "The Swiss Connection: A Tale of Emmental and Economics" by G. Brie offers a nuanced exploration of the international cheese trade and its potential reverberations on global financial markets.

In the realm of fiction, the novel "Cheesy Business: A Wall Street Fable" by R. Fondue playfully delves into the whimsical world of dairy-derived economic theories, drawing allegorical parallels to the real-world dynamics of market forces. Similarly, "The Cheddar Conundrum" by E. Gruyère weaves a satirical narrative of cheese-induced stock market havoc, melding financial intrigue with dairy-based humor.

On the internet, the meme "Cheese Investing: Making Cheddar Moves in the Stock Market" captures the humorously quixotic intersection of cheese enthusiasm and financial acumen, showcasing the playful engagement of online communities with the topic. Additionally, the viral sensation "Brie-lliant Trades: How Cheese Predicts Stock Surges" humorously speculates on the forecasting potential of cheese varieties in predicting market movements, encapsulating the whimsical side of this scholarly pursuit.

As we digest the diverse array of literature surrounding cheese and its enigmatic relationship with stock markets, our research aims to complement these perspectives, offering empirical evidence and analytical rigor to the fromaggio of scholarly inquiry. Let us now delve into the cheesy depths of this literature and navigate the intersection of American cheese consumption and NDAQ stock price with a spirit of intellectual curiosity and perhaps a sprinkle of grated wit.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Nasdaq's stock price (NDAQ). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. 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 2003 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]]
"Say Cheese: The Gouda, The Bad, and The Nasdaq - Exploring the Correlation Between American Cheese Consumption and NDAQ Stock Price"

[[ABSTRACT]]
In this study, we delve into the curd-ious relationship between American cheese consumption and the stock market performance of Nasdaq (NDAQ). Using data sourced from the USDA and LSEG Analytics (Refinitiv), we sought to answer the age-old question: does American cheese have more influence on the economy than just being a sandwich topping? Our analysis covers the years 2003 to 2021, a period ripe with fluctuations in both cheese consumption and stock prices.

Upon conducting our research, we discovered a correlation coefficient of 0.9358575 with a significance level of p < 0.01, revealing a strong association between the two variables. While some may brie skeptical of such a connection, our findings cheddar light on the matter, highlighting the potential influence of cheese consumption on market sentiment and trading patterns. We discuss the implications of our results and propose further avenues of research to explore the wheyward impact of cheese on financial markets. So, grab some cheese and crackers, and let's fondue deeper into this dairy stock market relationship.

[[INTRODUCTION]]
The interplay between food consumption and economic indicators has long been a subject of scholarly interest. From the infamous "butterfly effect" to the well-studied influence of coffee prices on productivity, the relationship between what we consume and the performance of financial markets has captivated researchers and pundits alike. In this vein, our study delves into the world of American cheese and its potential impact on the Nasdaq (NDAQ) stock price.
While some may view the consumption of American cheese as merely a dairy delight, we posited that there may be deeper implications for the stock market. After all, the cheesy correlation between consumer behavior and market movements is no longer just a "gouda" laugh at cocktail parties but a topic worthy of serious investigation.
To peel back the layers of this relationship, we conducted an in-depth analysis spanning the years 2003 to 2021, leveraging data from the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv). Our aim was to melt away any doubts regarding the potential impact of American cheese consumption on the stock performance of Nasdaq.
The results of our investigation unveiled a correlation coefficient of 0.9358575, with a significance level of p < 0.01, implicating a robust association between American cheese consumption and the stock price of Nasdaq. This finding may appear "grate," but it provides compelling evidence of a link that extends beyond mere coincidence. We acknowledge the sharp cheddar of skepticism that may accompany such a correlation, yet our analysis aims to slice through the conjecture and present a Parmesan-telligent argument for the influence of cheese on financial markets.
In the following sections, we will delve into the potential mechanisms underlying this relationship, consider the broader implications for market sentiment and trading behavior, and propose avenues for further research. As we embark on this fromage of investigation, we encourage readers to approach our findings with a discerning palate, leaning into the potential power of American cheese as an unlikely player in the stock market arena. So, grab a slice of cheese, raise a toast to empirical inquiry, and let's embark on this gouda journey together.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the twisty, labyrinthine connection between American cheese consumption and the stock price of Nasdaq (NDAQ), our research team employed a multifaceted methodology that combined traditional statistical analyses with a sprinkle of dairy-based detective work. The dataset was meticulously curated from sources such as the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv), providing a robust foundation for our cheesy exploration.

First, we compiled historical data on American cheese consumption patterns from 2003 to 2021, tapping into the USDA's treasure trove of dairy statistics. The collection process involved scouring through muenster-sized spreadsheets, navigating wheyward trends, and ensuring that our data remained feta-clean and free from extraneous confoundments. We then juxtaposed this cheese consumption data with the daily stock prices of Nasdaq (NDAQ), meticulously logging the ebbs and flows of market activity like diligent cheese connoisseurs documenting the aging process of a fine Gouda.

Unearthing the statistical nuances necessitated wrangling the data into a format amenable to analysis. Utilizing statistical software with the precision of a cheese slicer, we conducted a variety of tests, including correlation analyses, time-series modeling, and possibly some mild hallucinations induced by the hypnotic patterns of stock price fluctuations. In our pursuit of truth, we left no statistical stone unturned, ensuring our methods were as rigorous as a Swiss cheese's holey structure.

To assess the relationship between American cheese consumption and NDAQ stock prices, we deployed various statistical tools with the strategic finesse of a chess grandmaster protecting their king. This included calculating correlation coefficients and conducting regression analyses to disentangle the complex interplay between cheese-infused dietary choices and market dynamics. The aim was to cheddar light on the potential mechanisms underlying any observed associations, unraveling the intricate web of influences with the intellectual curiosity of a scholar and the insatiable appetite of a mouse in a cheese factory.

The resulting findings yielded more surprises than a Swiss cheese sampler, unveiling insights that went beyond the initial curd-iosity that inspired our research. Our methods, though not as sharp as aged cheddar, provided a sturdy framework for unraveling the mysterious dalliance between American cheese consumption and stock market behavior. With the precision of a skilled cheesemonger and the discernment of a wine taster, we sifted through the data, embracing the uncertainties with the unbridled enthusiasm of a cheese enthusiast at a tasting event.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Nasdaq's stock price (NDAQ). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. 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 2003 to 2021, you found a correlation 0.9358575, r-squared of 0.8758292, 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]]
"Say Cheese: The Gouda, The Bad, and The Nasdaq - Exploring the Correlation Between American Cheese Consumption and NDAQ Stock Price"

[[ABSTRACT]]
In this study, we delve into the curd-ious relationship between American cheese consumption and the stock market performance of Nasdaq (NDAQ). Using data sourced from the USDA and LSEG Analytics (Refinitiv), we sought to answer the age-old question: does American cheese have more influence on the economy than just being a sandwich topping? Our analysis covers the years 2003 to 2021, a period ripe with fluctuations in both cheese consumption and stock prices.

Upon conducting our research, we discovered a correlation coefficient of 0.9358575 with a significance level of p < 0.01, revealing a strong association between the two variables. While some may brie skeptical of such a connection, our findings cheddar light on the matter, highlighting the potential influence of cheese consumption on market sentiment and trading patterns. We discuss the implications of our results and propose further avenues of research to explore the wheyward impact of cheese on financial markets. So, grab some cheese and crackers, and let's fondue deeper into this dairy stock market relationship.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The interplay between food consumption and economic indicators has long been a subject of scholarly interest. From the infamous "butterfly effect" to the well-studied influence of coffee prices on productivity, the relationship between what we consume and the performance of financial markets has captivated researchers and pundits alike. In this vein, our study delves into the world of American cheese and its potential impact on the Nasdaq (NDAQ) stock price.
While some may view the consumption of American cheese as merely a dairy delight, we posited that there may be deeper implications for the stock market. After all, the cheesy correlation between consumer behavior and market movements is no longer just a "gouda" laugh at cocktail parties but a topic worthy of serious investigation.
To peel back the layers of this relationship, we conducted an in-depth analysis spanning the years 2003 to 2021, leveraging data from the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv). Our aim was to melt away any doubts regarding the potential impact of American cheese consumption on the stock performance of Nasdaq.
The results of our investigation unveiled a correlation coefficient of 0.9358575, with a significance level of p < 0.01, implicating a robust association between American cheese consumption and the stock price of Nasdaq. This finding may appear "grate," but it provides compelling evidence of a link that extends beyond mere coincidence. We acknowledge the sharp cheddar of skepticism that may accompany such a correlation, yet our analysis aims to slice through the conjecture and present a Parmesan-telligent argument for the influence of cheese on financial markets.
In the following sections, we will delve into the potential mechanisms underlying this relationship, consider the broader implications for market sentiment and trading behavior, and propose avenues for further research. As we embark on this fromage of investigation, we encourage readers to approach our findings with a discerning palate, leaning into the potential power of American cheese as an unlikely player in the stock market arena. So, grab a slice of cheese, raise a toast to empirical inquiry, and let's embark on this gouda journey together.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis revealed a remarkably high correlation between American cheese consumption and the stock price of Nasdaq (NDAQ) during the period from 2003 to 2021. The correlation coefficient of 0.9358575 indicates a strong positive relationship between these two seemingly unrelated variables. In simpler terms, as American cheese consumption increased, so did the Nasdaq stock price, drawing attention to this rather unexpected association.

The coefficient of determination (R-squared) of 0.8758292 further emphasized the strength of the relationship, indicating that approximately 87.58% of the variation in Nasdaq's stock price can be explained by changes in American cheese consumption. This suggests that there is indeed a substantial degree of explanatory power packed within the cheese consumption data, proving that this isn't just a "cheesy" coincidence.

Moreover, with a significance level of p < 0.01, the results are statistically significant, providing robust evidence to support the existence of a meaningful connection between American cheese consumption and Nasdaq's stock performance. In essence, the probability of observing such a strong relationship by random chance is less than 1%, solidifying the validity of our findings.

The visual representation of this intriguing relationship is presented in Figure 1, a scatterplot that vividly illustrates the striking correlation between American cheese consumption and the stock price of Nasdaq. The figure speaks volumes, depicting a trend that is not only statistically sound but also visually compelling.

Overall, our findings not only melt away any doubt about the intriguing link between American cheese consumption and financial markets but also provoke further reflection on the potential influence of dairy products on economic indicators. This study lends credence to the idea that, whether you are "gouda" believer or not, there may be more to cheese consumption than meets the eye when it comes to market dynamics. Further research and deeper analysis are warranted to explore the nuances of this unexpected relationship and uncover the "wheys" in which cheese consumption may shape market sentiments and trading patterns. After all, it's not every day you stumble upon such a "gouda" opportunity for scholarly investigation in the dairy aisle of the economic landscape.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Nasdaq's stock price (NDAQ). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. 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]]
"Say Cheese: The Gouda, The Bad, and The Nasdaq - Exploring the Correlation Between American Cheese Consumption and NDAQ Stock Price"

[[ABSTRACT]]
In this study, we delve into the curd-ious relationship between American cheese consumption and the stock market performance of Nasdaq (NDAQ). Using data sourced from the USDA and LSEG Analytics (Refinitiv), we sought to answer the age-old question: does American cheese have more influence on the economy than just being a sandwich topping? Our analysis covers the years 2003 to 2021, a period ripe with fluctuations in both cheese consumption and stock prices.

Upon conducting our research, we discovered a correlation coefficient of 0.9358575 with a significance level of p < 0.01, revealing a strong association between the two variables. While some may brie skeptical of such a connection, our findings cheddar light on the matter, highlighting the potential influence of cheese consumption on market sentiment and trading patterns. We discuss the implications of our results and propose further avenues of research to explore the wheyward impact of cheese on financial markets. So, grab some cheese and crackers, and let's fondue deeper into this dairy stock market relationship.

[[LITERATURE REVIEW]]
In "Smith and Doe (2018)," the authors find a positive correlation between cheese consumption and stock market performance, sparking further interest in the potential influence of dairy products on financial indicators. Expanding upon this, Jones et al. (2020) examined the specific case of American cheese and its impact on the Nasdaq (NDAQ) stock price, laying the foundation for our current investigation.
Adding a layer of complexity to the literature, "The Big Cheese: A Historical Analysis of Dairy and Dollars" by A. Gouda sheds light on the historical patterns of cheese consumption and economic trends, providing a matured perspective on the subject matter. Furthermore, "The Swiss Connection: A Tale of Emmental and Economics" by G. Brie offers a nuanced exploration of the international cheese trade and its potential reverberations on global financial markets.
In the realm of fiction, the novel "Cheesy Business: A Wall Street Fable" by R. Fondue playfully delves into the whimsical world of dairy-derived economic theories, drawing allegorical parallels to the real-world dynamics of market forces. Similarly, "The Cheddar Conundrum" by E. Gruyère weaves a satirical narrative of cheese-induced stock market havoc, melding financial intrigue with dairy-based humor.
On the internet, the meme "Cheese Investing: Making Cheddar Moves in the Stock Market" captures the humorously quixotic intersection of cheese enthusiasm and financial acumen, showcasing the playful engagement of online communities with the topic. Additionally, the viral sensation "Brie-lliant Trades: How Cheese Predicts Stock Surges" humorously speculates on the forecasting potential of cheese varieties in predicting market movements, encapsulating the whimsical side of this scholarly pursuit.
As we digest the diverse array of literature surrounding cheese and its enigmatic relationship with stock markets, our research aims to complement these perspectives, offering empirical evidence and analytical rigor to the fromaggio of scholarly inquiry. Let us now delve into the cheesy depths of this literature and navigate the intersection of American cheese consumption and NDAQ stock price with a spirit of intellectual curiosity and perhaps a sprinkle of grated wit.

[[RESULTS]]
The statistical analysis revealed a remarkably high correlation between American cheese consumption and the stock price of Nasdaq (NDAQ) during the period from 2003 to 2021. The correlation coefficient of 0.9358575 indicates a strong positive relationship between these two seemingly unrelated variables. In simpler terms, as American cheese consumption increased, so did the Nasdaq stock price, drawing attention to this rather unexpected association.
The coefficient of determination (R-squared) of 0.8758292 further emphasized the strength of the relationship, indicating that approximately 87.58% of the variation in Nasdaq's stock price can be explained by changes in American cheese consumption. This suggests that there is indeed a substantial degree of explanatory power packed within the cheese consumption data, proving that this isn't just a "cheesy" coincidence.
Moreover, with a significance level of p < 0.01, the results are statistically significant, providing robust evidence to support the existence of a meaningful connection between American cheese consumption and Nasdaq's stock performance. In essence, the probability of observing such a strong relationship by random chance is less than 1%, solidifying the validity of our findings.
The visual representation of this intriguing relationship is presented in Figure 1, a scatterplot that vividly illustrates the striking correlation between American cheese consumption and the stock price of Nasdaq. The figure speaks volumes, depicting a trend that is not only statistically sound but also visually compelling.
Overall, our findings not only melt away any doubt about the intriguing link between American cheese consumption and financial markets but also provoke further reflection on the potential influence of dairy products on economic indicators. This study lends credence to the idea that, whether you are "gouda" believer or not, there may be more to cheese consumption than meets the eye when it comes to market dynamics. Further research and deeper analysis are warranted to explore the nuances of this unexpected relationship and uncover the "wheys" in which cheese consumption may shape market sentiments and trading patterns. After all, it's not every day you stumble upon such a "gouda" opportunity for scholarly investigation in the dairy aisle of the economic landscape.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

In the grand tradition of academic research, our study has brought to light a gouda-licious relationship between American cheese consumption and the stock performance of Nasdaq (NDAQ). Our findings stand in agreement with the prior research by Smith and Doe (2018), who embraced the cheesy correlation between dairy and dollars, and Jones et al. (2020), who specifically honed in on the Nasdaq. It’s clear that our results have "brie"-led new insights into this dairy market dynamic, confirming and enhancing our understanding of the fromaggio of scholarly inquiry.

The correlation coefficient of 0.9358575 found in our study serves as a compelling testament to the strength of the connection between American cheese consumption and Nasdaq's stock price. This robust statistic underscores the idea that, when it comes to market movements, sometimes it's not just about "making cheddar," but about slicing and dicing the data. Our coefficient of determination (R-squared) of 0.8758292 has peeled back the layers of ambiguity around this relationship, revealing that approximately 87.58% of Nasdaq's stock price variations can be explained by changes in American cheese consumption. This further highlights the provolone-ce of the cheese data in shedding light on market dynamics.

As for the statistical significance, our findings hold up under scrutiny, with a p-value of less than 1%. This result suggests that the probability of observing the observed relationship by mere happenstance is less than the chance of finding a diamond in a 10-pound wheel of aged cheddar - quite rare indeed. Our scatterplot, the visual pièce de résistance of our findings, provides a gouda visual representation of this curiously compelling correlation, making it clear that this is no "brie"-f whimsy.

With such statistically sound evidence in hand, we can confidently proclaim that our study has not only bolstered the existing literature but has also set the stage for future exploration of this dairy market connection. Further research is warranted to dig deeper into the "wheys" in which cheese consumption influences market sentiments and trading patterns. After all, it's no small feat to stumble upon such a "gouda" opportunity for scholarly investigation in the dairy aisle of economic inquiry.

In conclusion...

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Nasdaq's stock price (NDAQ). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. 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]]
"Say Cheese: The Gouda, The Bad, and The Nasdaq - Exploring the Correlation Between American Cheese Consumption and NDAQ Stock Price"

[[ABSTRACT]]
In this study, we delve into the curd-ious relationship between American cheese consumption and the stock market performance of Nasdaq (NDAQ). Using data sourced from the USDA and LSEG Analytics (Refinitiv), we sought to answer the age-old question: does American cheese have more influence on the economy than just being a sandwich topping? Our analysis covers the years 2003 to 2021, a period ripe with fluctuations in both cheese consumption and stock prices.

Upon conducting our research, we discovered a correlation coefficient of 0.9358575 with a significance level of p < 0.01, revealing a strong association between the two variables. While some may brie skeptical of such a connection, our findings cheddar light on the matter, highlighting the potential influence of cheese consumption on market sentiment and trading patterns. We discuss the implications of our results and propose further avenues of research to explore the wheyward impact of cheese on financial markets. So, grab some cheese and crackers, and let's fondue deeper into this dairy stock market relationship.

[[INTRDUCTION]]
The interplay between food consumption and economic indicators has long been a subject of scholarly interest. From the infamous "butterfly effect" to the well-studied influence of coffee prices on productivity, the relationship between what we consume and the performance of financial markets has captivated researchers and pundits alike. In this vein, our study delves into the world of American cheese and its potential impact on the Nasdaq (NDAQ) stock price.
While some may view the consumption of American cheese as merely a dairy delight, we posited that there may be deeper implications for the stock market. After all, the cheesy correlation between consumer behavior and market movements is no longer just a "gouda" laugh at cocktail parties but a topic worthy of serious investigation.
To peel back the layers of this relationship, we conducted an in-depth analysis spanning the years 2003 to 2021, leveraging data from the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv). Our aim was to melt away any doubts regarding the potential impact of American cheese consumption on the stock performance of Nasdaq.
The results of our investigation unveiled a correlation coefficient of 0.9358575, with a significance level of p < 0.01, implicating a robust association between American cheese consumption and the stock price of Nasdaq. This finding may appear "grate," but it provides compelling evidence of a link that extends beyond mere coincidence. We acknowledge the sharp cheddar of skepticism that may accompany such a correlation, yet our analysis aims to slice through the conjecture and present a Parmesan-telligent argument for the influence of cheese on financial markets.
In the following sections, we will delve into the potential mechanisms underlying this relationship, consider the broader implications for market sentiment and trading behavior, and propose avenues for further research. As we embark on this fromage of investigation, we encourage readers to approach our findings with a discerning palate, leaning into the potential power of American cheese as an unlikely player in the stock market arena. So, grab a slice of cheese, raise a toast to empirical inquiry, and let's embark on this gouda journey together.

[[RESULTS]]
The statistical analysis revealed a remarkably high correlation between American cheese consumption and the stock price of Nasdaq (NDAQ) during the period from 2003 to 2021. The correlation coefficient of 0.9358575 indicates a strong positive relationship between these two seemingly unrelated variables. In simpler terms, as American cheese consumption increased, so did the Nasdaq stock price, drawing attention to this rather unexpected association.
The coefficient of determination (R-squared) of 0.8758292 further emphasized the strength of the relationship, indicating that approximately 87.58% of the variation in Nasdaq's stock price can be explained by changes in American cheese consumption. This suggests that there is indeed a substantial degree of explanatory power packed within the cheese consumption data, proving that this isn't just a "cheesy" coincidence.
Moreover, with a significance level of p < 0.01, the results are statistically significant, providing robust evidence to support the existence of a meaningful connection between American cheese consumption and Nasdaq's stock performance. In essence, the probability of observing such a strong relationship by random chance is less than 1%, solidifying the validity of our findings.
The visual representation of this intriguing relationship is presented in Figure 1, a scatterplot that vividly illustrates the striking correlation between American cheese consumption and the stock price of Nasdaq. The figure speaks volumes, depicting a trend that is not only statistically sound but also visually compelling.
Overall, our findings not only melt away any doubt about the intriguing link between American cheese consumption and financial markets but also provoke further reflection on the potential influence of dairy products on economic indicators. This study lends credence to the idea that, whether you are "gouda" believer or not, there may be more to cheese consumption than meets the eye when it comes to market dynamics. Further research and deeper analysis are warranted to explore the nuances of this unexpected relationship and uncover the "wheys" in which cheese consumption may shape market sentiments and trading patterns. After all, it's not every day you stumble upon such a "gouda" opportunity for scholarly investigation in the dairy aisle of the economic landscape.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has gratefully shredded light on the seemingly un-brielievable connection between American cheese consumption and Nasdaq's stock price. Our findings suggest a strong positive association, indicating that as Americans consumed more cheese, the Nasdaq stock price followed suit, proving that the cheese stands alone in its influence on market dynamics. However, while our study may leave some feeling a bit blue (cheese), it's important to remember that correlation does not always imply causation. It's no feta accompli that cheese consumption is the direct cause of stock price movements, but our findings do raise some serious food for thought.

The strong correlation coefficient of 0.9358575 and the high coefficient of determination (R-squared) of 0.8758292 highlight the robustness of this relationship, serving as a gouda foundation for future research. The significance level of p < 0.01 further underscores the statistical validity of our findings, presenting a compelling argument for the impact of cheese on financial markets. Our scatterplot depiction of this dairy stock market dance in Figure 1 is not only visually appealing but also offers a slice of insight into this surprising connection.

While our study may provoke some gouda laughs and eye-rolls, it's important to acknowledge the provolone limitations of our research. Causality remains a complex Swiss (cheese) of factors, and our study merely scratches the surface of this multifaceted relationship. Future research should aim to uncover the wheys and means by which cheese consumption may influence market sentiments and trading patterns, hopefully, camembert to a satisfying conclusion.

In closing, it appears that American cheese is not only a staple in sandwiches but may also have a place at the financial table. As such, we believe that the time has come to bid adieu to further research in this area. After all, there's no need to milk this topic dry – let's cheddar our efforts in more promising and less dairy-driven pursuits. Thank you for indulging in this cheesy investigation, but it's time for us to move on to fresher pastures.

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 Say Cheese: The Gouda, The Bad, and The Nasdaq - Exploring the Correlation Between American Cheese Consumption and NDAQ Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Dairy Economist

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 Say Cheese: The Gouda, The Bad, and The Nasdaq - Exploring the Correlation Between American Cheese Consumption and NDAQ Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

Institute for Dairy Economics and Statistics

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 Say Cheese: The Gouda, The Bad, and The Nasdaq - Exploring the Correlation Between American Cheese Consumption and NDAQ Stock Price with an abstract of In this study, we delve into the curd-ious relationship between American cheese consumption and the stock market performance of Nasdaq (NDAQ). Using data sourced from the USDA and LSEG Analytics (Refinitiv), we sought to answer the age-old question: does American cheese have more influence on the economy than just being a sandwich topping? Our analysis covers the years 2003 to 2021, a period ripe with fluctuations in both cheese consumption and stock prices.
Upon conducting our research, we discovered a correlation coefficient of 0.9358575 with a significance level of p < 0.01, revealing a strong association between the two variables. While some may brie skeptical of such a connection, our findings cheddar light on the matter, highlighting the potential influence of cheese consumption on market sentiment and trading patterns. We discuss the implications of our results and propose further avenues of research to explore the wheyward impact of cheese on financial markets. So, grab some cheese and crackers, and let's fondue deeper into this dairy stock market relationship.

ChatGPT:

American cheese consumption, stock market performance, Nasdaq stock price, correlation analysis, USDA data, LSEG Analytics, Refinitiv, cheese consumption and economy, cheese consumption and stock prices, cheese consumption and market sentiment, cheese consumption and trading patterns, cheese impact on financial markets

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

Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error

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

Nasdaq's stock price (NDAQ)
Detailed data title: Opening price of Nasdaq (NDAQ) 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 Nasdaq's stock price (NDAQ)

Correlation r = 0.9358575 (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 = 0.8758292 (Coefficient of determination)
This means 87.6% of the change in the one variable (i.e., Nasdaq's stock price (NDAQ)) is predictable based on the change in the other (i.e., American cheese consumption) over the 19 years from 2003 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.03E-9.^Show 0.0000000040280968595317630000
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 0.94 in 4.03E-7% of random cases. Said differently, if you correlated 248,256,195 random variables^Note You don't actually need 248 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 18 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 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.

[ 0.84, 0.98 ] 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.

	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)	12.5619	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
Nasdaq's stock price (NDAQ) (Stock price)	3.34	3	3.5	11.92	10.38	16.6	8.16	6.64	8	8.34	8.47	13.3	16.07	18.97	22.49	25.72	26.87	35.75	44.58

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([12.5619,12.8612,12.649,13.0656,12.7929,13.1306,13.3553,13.3048,13.0392,13.2569,13.3573,13.6656,14.0444,14.3621,15.0901,15.4027,15.5389,15.5,16.1,])
array_2 = np.array([3.34,3,3.5,11.92,10.38,16.6,8.16,6.64,8,8.34,8.47,13.3,16.07,18.97,22.49,25.72,26.87,35.75,44.58,])
array_1_name = "American cheese consumption"
array_2_name = "Nasdaq's stock price (NDAQ)"

# 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 Nasdaq's stock price (NDAQ)
AI-generated correlation image
The spurious research paper: Say Cheese: The Gouda, The Bad, and The Nasdaq - Exploring the Correlation Between American Cheese Consumption and NDAQ Stock Price

View another random correlation

How fun was this correlation?

Your rating skills are legendary!

Correlation ID: 2365 · Black Variable ID: 553 · Red Variable ID: 1869


Problem variable:
Issue:
Additional details: Optional
Confirm you are a human: