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Spurious correlation #2,148 · 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 The Coca-Cola Company's stock price (KO).  The chart goes from 2002 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

The more American cheese people ate, the more they craved a refreshing Coke to wash it down. This increased demand for Coca-Cola products, leading to higher sales and ultimately driving up the stock price of The Coca-Cola Company. It's a gouda-licious partnership that's grate for business!

Model: dalle-3
Prompt: Generate an image of a group of friends sitting around a sleek, futuristic table, savoring delicious cheeseburgers with golden, gooey American cheese. They're joyfully raising their Coca-Cola bottles, while a state-of-the-art digital display in the background showcases The Coca-Cola Company's stock price sharply rising. The setting should be modern, with minimalist and high-tech elements, creating a sense of innovation and the future. 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 The Coca-Cola Company's stock price. 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: Whimsical illustration Cutsy art illustration Vaporwave Sci-fi fantacy High-tech
ChatGPT: High-tech

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 The Coca-Cola Company's stock price together. Keep the description simple.
ChatGPT: A group of friends enjoying juicy cheeseburgers with melted American cheese as they raise their Coca-Cola bottles for a cheers. Meanwhile, a digital screen in the background displays The Coca-Cola Company's stock price skyrocketing.

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: [ High-tech ] and depicting this scene: A group of friends enjoying juicy cheeseburgers with melted American cheese as they raise their Coca-Cola bottles for a cheers. Meanwhile, a digital screen in the background displays The Coca-Cola Company's stock price skyrocketing. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a group of friends sitting around a sleek, futuristic table, savoring delicious cheeseburgers with golden, gooey American cheese. They're joyfully raising their Coca-Cola bottles, while a state-of-the-art digital display in the background showcases The Coca-Cola Company's stock price sharply rising. The setting should be modern, with minimalist and high-tech elements, creating a sense of innovation and the future.

*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.

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 The Coca-Cola Company's stock price (KO) to increase.

AI academic paper

(Because p < 0.01)
The Cheddar and Coca-Cola Connection: An Examination of American Cheese Consumption and KO Stock Price Fluctuations

The Journal of Unlikely Connections

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between American cheese consumption and The Coca-Cola Company's stock price (KO). Make lots of jokes, goofy observations, and puns.

Rhyme words in the title.

Your research team used data from USDA and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9083366 and p < 0.01 for 2002 to 2021.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
The Cheddar and Coca-Cola Connection: An Examination of American Cheese Consumption and KO Stock Price Fluctuations

[[ABSTRACT]]
In this study, we delved into the intriguing relationship between the consumption of American cheese and the stock price of The Coca-Cola Company (KO). Utilizing data from the USDA and LSEG Analytics (Refinitiv) spanning nearly two decades, we set out to determine whether there exists a substantive correlation between these seemingly disparate elements. To our astonishment, we discovered a striking correlation coefficient of 0.9083366 and p < 0.01, prompting us to further investigate this curious phenomenon. Our findings not only raise eyebrows but also provoke questions about the potential influence of cheesy indulgences on the fizzy fortunes of Coca-Cola. Our study sheds light on this peculiarity and adds a slice of cheese to the complex tapestry of stock market dynamics.


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 introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between American cheese consumption and The Coca-Cola Company's stock price (KO). Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
The Cheddar and Coca-Cola Connection: An Examination of American Cheese Consumption and KO Stock Price Fluctuations

[[ABSTRACT]]
In this study, we delved into the intriguing relationship between the consumption of American cheese and the stock price of The Coca-Cola Company (KO). Utilizing data from the USDA and LSEG Analytics (Refinitiv) spanning nearly two decades, we set out to determine whether there exists a substantive correlation between these seemingly disparate elements. To our astonishment, we discovered a striking correlation coefficient of 0.9083366 and p < 0.01, prompting us to further investigate this curious phenomenon. Our findings not only raise eyebrows but also provoke questions about the potential influence of cheesy indulgences on the fizzy fortunes of Coca-Cola. Our study sheds light on this peculiarity and adds a slice of cheese to the complex tapestry of stock market dynamics.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
INTRODUCTION

The whimsical world of stock market analysis often leads us down unexpected paths, and our journey into the connection between American cheese consumption and The Coca-Cola Company's stock price (KO) is certainly no exception. While one might expect the stock market to be influenced by economic indicators, company performance, and global events, the notion of cheese – yes, cheese – playing a role in stock price fluctuations may strike some as utterly cheesy. But hold your laughter, dear reader, for our findings may just melt away any skepticism.

As we embark on this fromage-filled voyage, it is crucial to appreciate the significance of both American cheese and Coca-Cola in the broader context of consumer behavior and market dynamics. The enduring appeal of American cheese as a quintessential ingredient in burgers, grilled cheese sandwiches, and cheese fries suggests a deep-seated connection to the American palate. Similarly, The Coca-Cola Company's ubiquitous presence in the global beverage market makes it a stalwart contender in the corporate arena. Yet, as disparate as these entities may seem, our research aims to unravel the uncanny correlation between them.

The notion that a dairy delight could hold sway over the fortunes of a beverage behemoth may seem udderly preposterous at first glance. However, as we delve into the empirical evidence, we find ourselves confronted with a correlation coefficient of 0.9083366 and a p-value less than 0.01, revealing a relationship that simply cannot be dismissed as mere coincidence. This discovery propels us into uncharted territory, where the aroma of cheese and the sound of stock tickers commingle in intriguing ways.

Before we delve into our methodology and findings, it is imperative to acknowledge the potential for confounding variables and spurious correlations in our analysis. After all, it is entirely possible that the observed connection between American cheese consumption and KO stock price fluctuations is a queso fortuitous fluke. Nonetheless, our rigorous approach and comprehensive dataset lend credibility to our investigation, leaving us with a gouda feeling about the validity of our results.

As we illuminate this enigmatic correlation, we invite readers to embrace the unexpected, to savor the unexpected interplay between cheddar and Coca-Cola, and to join us in unraveling the mysteries of the stock market – one cheesy bite at a time. So, without further ado, let us delve into the cheddar and Coca-Cola connection and uncover the savory secrets that lie within.


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 The Coca-Cola Company's stock price (KO). Make lots of 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
The Cheddar and Coca-Cola Connection: An Examination of American Cheese Consumption and KO Stock Price Fluctuations

[[ABSTRACT]]
In this study, we delved into the intriguing relationship between the consumption of American cheese and the stock price of The Coca-Cola Company (KO). Utilizing data from the USDA and LSEG Analytics (Refinitiv) spanning nearly two decades, we set out to determine whether there exists a substantive correlation between these seemingly disparate elements. To our astonishment, we discovered a striking correlation coefficient of 0.9083366 and p < 0.01, prompting us to further investigate this curious phenomenon. Our findings not only raise eyebrows but also provoke questions about the potential influence of cheesy indulgences on the fizzy fortunes of Coca-Cola. Our study sheds light on this peculiarity and adds a slice of cheese to the complex tapestry of stock market dynamics.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The whimsical world of stock market analysis often leads us down unexpected paths, and our journey into the connection between American cheese consumption and The Coca-Cola Company's stock price (KO) is certainly no exception. While one might expect the stock market to be influenced by economic indicators, company performance, and global events, the notion of cheese – yes, cheese – playing a role in stock price fluctuations may strike some as utterly cheesy. But hold your laughter, dear reader, for our findings may just melt away any skepticism.
As we embark on this fromage-filled voyage, it is crucial to appreciate the significance of both American cheese and Coca-Cola in the broader context of consumer behavior and market dynamics. The enduring appeal of American cheese as a quintessential ingredient in burgers, grilled cheese sandwiches, and cheese fries suggests a deep-seated connection to the American palate. Similarly, The Coca-Cola Company's ubiquitous presence in the global beverage market makes it a stalwart contender in the corporate arena. Yet, as disparate as these entities may seem, our research aims to unravel the uncanny correlation between them.
The notion that a dairy delight could hold sway over the fortunes of a beverage behemoth may seem udderly preposterous at first glance. However, as we delve into the empirical evidence, we find ourselves confronted with a correlation coefficient of 0.9083366 and a p-value less than 0.01, revealing a relationship that simply cannot be dismissed as mere coincidence. This discovery propels us into uncharted territory, where the aroma of cheese and the sound of stock tickers commingle in intriguing ways.
Before we delve into our methodology and findings, it is imperative to acknowledge the potential for confounding variables and spurious correlations in our analysis. After all, it is entirely possible that the observed connection between American cheese consumption and KO stock price fluctuations is a queso fortuitous fluke. Nonetheless, our rigorous approach and comprehensive dataset lend credibility to our investigation, leaving us with a gouda feeling about the validity of our results.
As we illuminate this enigmatic correlation, we invite readers to embrace the unexpected, to savor the unexpected interplay between cheddar and Coca-Cola, and to join us in unraveling the mysteries of the stock market – one cheesy bite at a time. So, without further ado, let us delve into the cheddar and Coca-Cola connection and uncover the savory secrets that lie within.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The examination of seemingly incongruous variables in the context of stock market dynamics has been a subject of intrigue for scholars and practitioners alike. Smith et al. (2015) explored the influence of dairy products on consumer spending patterns, shedding light on the potential impact of cheese consumption on economic behaviors. Similarly, Doe and Jones (2018) conducted a comprehensive analysis of food industry trends and their ripple effects on stock market performance, offering valuable insights into the interconnectedness of consumer preferences and investment outcomes.

While these seminal works provide a sober foundation for understanding the broader landscape of consumer behavior and market dynamics, our inquiry into the association between American cheese consumption and The Coca-Cola Company's stock price (KO) expands the horizons of financial research into the realm of dairy-derived delight and carbonated conundrums.

Drawing from the wider literature on food economics and market interplay, pivotal works such as "The Omnivore's Dilemma" by Michael Pollan and "The Taste of Country Cooking" by Edna Lewis beckon us to contemplate the profound influence of culinary choices on economic systems. These thought-provoking narratives offer a delectable intersection of gastronomic delights and economic ramifications, setting the stage for our exploration of cheese’s whimsical dance with Coca-Cola's stock performance.

As we tread into the realm of speculative fiction and satirical musings, the allegorical tales of "Cheese Monopoly: A Culinary Adventure" and "A Carbonated Conspiracy: The Fizzy Follies" serve as whimsical reminders of the fantastical possibilities that underpin our academic pursuits. While these fictitious works may not offer empirical evidence, they kindle the imagination and provoke contemplation about the surreal potential of cheese and fizzy beverages shaping the financial markets.

Additionally, the influence of board games, such as "Cheeseopoly" and "Stock Market Showdown," subtly nudges us to consider the playful reverberations of cheese-themed economic ventures and stock market follies. Though far removed from the rigorous analysis of academic literature, these lighthearted diversions infuse a dash of levity into our scholarly pursuit and underscore the eclectic sources of inspiration that fuel our foray into the cheddar and Coca-Cola connection.

With this eclectic backdrop in mind, we embark on our investigation with a spirit of mirth and intellectual curiosity, ready to dissect the enigmatic correlation between American cheese consumption and the stock price fluctuations of The Coca-Cola Company (KO). Let the odyssey of cheese and fizz unfold as we unravel the intriguing enigma that lies at the intersection of dairy and dividends.


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 The Coca-Cola Company's stock price (KO). Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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 Cheddar and Coca-Cola Connection: An Examination of American Cheese Consumption and KO Stock Price Fluctuations

[[ABSTRACT]]
In this study, we delved into the intriguing relationship between the consumption of American cheese and the stock price of The Coca-Cola Company (KO). Utilizing data from the USDA and LSEG Analytics (Refinitiv) spanning nearly two decades, we set out to determine whether there exists a substantive correlation between these seemingly disparate elements. To our astonishment, we discovered a striking correlation coefficient of 0.9083366 and p < 0.01, prompting us to further investigate this curious phenomenon. Our findings not only raise eyebrows but also provoke questions about the potential influence of cheesy indulgences on the fizzy fortunes of Coca-Cola. Our study sheds light on this peculiarity and adds a slice of cheese to the complex tapestry of stock market dynamics.

[[INTRODUCTION]]
INTRODUCTION
The whimsical world of stock market analysis often leads us down unexpected paths, and our journey into the connection between American cheese consumption and The Coca-Cola Company's stock price (KO) is certainly no exception. While one might expect the stock market to be influenced by economic indicators, company performance, and global events, the notion of cheese – yes, cheese – playing a role in stock price fluctuations may strike some as utterly cheesy. But hold your laughter, dear reader, for our findings may just melt away any skepticism.
As we embark on this fromage-filled voyage, it is crucial to appreciate the significance of both American cheese and Coca-Cola in the broader context of consumer behavior and market dynamics. The enduring appeal of American cheese as a quintessential ingredient in burgers, grilled cheese sandwiches, and cheese fries suggests a deep-seated connection to the American palate. Similarly, The Coca-Cola Company's ubiquitous presence in the global beverage market makes it a stalwart contender in the corporate arena. Yet, as disparate as these entities may seem, our research aims to unravel the uncanny correlation between them.
The notion that a dairy delight could hold sway over the fortunes of a beverage behemoth may seem udderly preposterous at first glance. However, as we delve into the empirical evidence, we find ourselves confronted with a correlation coefficient of 0.9083366 and a p-value less than 0.01, revealing a relationship that simply cannot be dismissed as mere coincidence. This discovery propels us into uncharted territory, where the aroma of cheese and the sound of stock tickers commingle in intriguing ways.
Before we delve into our methodology and findings, it is imperative to acknowledge the potential for confounding variables and spurious correlations in our analysis. After all, it is entirely possible that the observed connection between American cheese consumption and KO stock price fluctuations is a queso fortuitous fluke. Nonetheless, our rigorous approach and comprehensive dataset lend credibility to our investigation, leaving us with a gouda feeling about the validity of our results.
As we illuminate this enigmatic correlation, we invite readers to embrace the unexpected, to savor the unexpected interplay between cheddar and Coca-Cola, and to join us in unraveling the mysteries of the stock market – one cheesy bite at a time. So, without further ado, let us delve into the cheddar and Coca-Cola connection and uncover the savory secrets that lie within.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To investigate the curiously cheddarific connection between American cheese consumption and The Coca-Cola Company's stock price (KO), our research team employed a blend of rigorous quantitative analysis, statistical wizardry, and a sprinkle of good old-fashioned dairy detective work. Our data, spanning the years from 2002 to 2021, was meticulously sourced from reputable institutions such as the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv), ensuring a dollop of reliability in our investigation.

First and foremost, we tackled the bewildering task of quantifying American cheese consumption across the United States. This involved an age-old technique known as "Internet scouring," where our intrepid researchers combed through countless database entries, market reports, and possibly one too many cheese-themed memes to obtain a comprehensive overview of cheese consumption trends. Delicately balancing a love for cheese with a dedication to scientific inquiry, our team skillfully pieced together a cheesy mosaic of consumption patterns, mindful of the multitude of considerations that go into fromage-fueled data collection.

Simultaneously, in the caffeinated confines of our research headquarters, we diligently harnessed the power of LSEG Analytics (Refinitiv) to extract historical stock price data for The Coca-Cola Company (KO). This involved navigating through labyrinthine spreadsheets, dodging the occasional rogue coffee spill, and extracting copious amounts of data to construct a robust timeline of stock price fluctuations. And yes, there may have been a fondue-related pun or two along the way.

With our meticulously gathered data in hand, we embarked on a journey through the enchanting realm of statistical analysis. Armed with the mystical incantations of correlation coefficients, p-values, and regression analyses, we set out to unravel the enigmatic relationship between cheese consumption and stock market movements. Our computations were not for the faint of heart, requiring a blend of Excel wizardry, caffeinated endurance, and an enthusiastic appreciation for dairy-derived delirium.

Moreover, in our valiant quest to uncover the fromage-infused mysteries of the stock market, we remained acutely aware of potential confounding variables and unexpected quirks that could turn our research into a cheesy detective novel. With a discerning eye and the occasional eye roll at the punny nature of our investigation, we meticulously accounted for factors such as market volatility, consumer behavior shifts, and the ever-ambiguous whims of the stock market gods.

In delving into causality, we recognize the potential limitations of observational data and the need for further studies to explore the mechanisms behind this curious correlation. Nonetheless, armed with a spirit of inquiry as strong as a stilton and a determination as unwavering as aged cheddar, we embraced the challenge of unraveling the savory secrets that lie within the cheddar and Coca-Cola connection.

So, with a dash of statistical stardust and a sprinkle of dairy-fueled determination, our methodology forged a path through the fromage-riddled wilderness and propelled us into the heart of this delightful conundrum. With our findings ready to emerge from the oven of analysis, we invite readers to don their metaphorical cheese hats and march boldly into the realm of data-driven dairy discoveries. Onward, dear colleagues, to the land of empirical edam and statistical Swissness!


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 The Coca-Cola Company's stock price (KO). Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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 0.9083366, r-squared of 0.8250754, 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 Cheddar and Coca-Cola Connection: An Examination of American Cheese Consumption and KO Stock Price Fluctuations

[[ABSTRACT]]
In this study, we delved into the intriguing relationship between the consumption of American cheese and the stock price of The Coca-Cola Company (KO). Utilizing data from the USDA and LSEG Analytics (Refinitiv) spanning nearly two decades, we set out to determine whether there exists a substantive correlation between these seemingly disparate elements. To our astonishment, we discovered a striking correlation coefficient of 0.9083366 and p < 0.01, prompting us to further investigate this curious phenomenon. Our findings not only raise eyebrows but also provoke questions about the potential influence of cheesy indulgences on the fizzy fortunes of Coca-Cola. Our study sheds light on this peculiarity and adds a slice of cheese to the complex tapestry of stock market dynamics.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
The whimsical world of stock market analysis often leads us down unexpected paths, and our journey into the connection between American cheese consumption and The Coca-Cola Company's stock price (KO) is certainly no exception. While one might expect the stock market to be influenced by economic indicators, company performance, and global events, the notion of cheese – yes, cheese – playing a role in stock price fluctuations may strike some as utterly cheesy. But hold your laughter, dear reader, for our findings may just melt away any skepticism.
As we embark on this fromage-filled voyage, it is crucial to appreciate the significance of both American cheese and Coca-Cola in the broader context of consumer behavior and market dynamics. The enduring appeal of American cheese as a quintessential ingredient in burgers, grilled cheese sandwiches, and cheese fries suggests a deep-seated connection to the American palate. Similarly, The Coca-Cola Company's ubiquitous presence in the global beverage market makes it a stalwart contender in the corporate arena. Yet, as disparate as these entities may seem, our research aims to unravel the uncanny correlation between them.
The notion that a dairy delight could hold sway over the fortunes of a beverage behemoth may seem udderly preposterous at first glance. However, as we delve into the empirical evidence, we find ourselves confronted with a correlation coefficient of 0.9083366 and a p-value less than 0.01, revealing a relationship that simply cannot be dismissed as mere coincidence. This discovery propels us into uncharted territory, where the aroma of cheese and the sound of stock tickers commingle in intriguing ways.
Before we delve into our methodology and findings, it is imperative to acknowledge the potential for confounding variables and spurious correlations in our analysis. After all, it is entirely possible that the observed connection between American cheese consumption and KO stock price fluctuations is a queso fortuitous fluke. Nonetheless, our rigorous approach and comprehensive dataset lend credibility to our investigation, leaving us with a gouda feeling about the validity of our results.
As we illuminate this enigmatic correlation, we invite readers to embrace the unexpected, to savor the unexpected interplay between cheddar and Coca-Cola, and to join us in unraveling the mysteries of the stock market – one cheesy bite at a time. So, without further ado, let us delve into the cheddar and Coca-Cola connection and uncover the savory secrets that lie within.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

**RESULTS**

The statistical analysis conducted in this study yielded fascinating results, shedding light on the unforeseen connection between American cheese consumption and The Coca-Cola Company's stock price (KO). The correlation coefficient of 0.9083366 illuminated a robust relationship between these seemingly unrelated variables. With an r-squared value of 0.8250754 and a p-value less than 0.01, the strength of this correlation surpassed all initial expectations.

The figure (Fig. 1) illustrates the striking correlation between American cheese consumption and KO stock price fluctuations, providing a visual representation of the unexpected bond between dairy delicacies and fizzy finances. The scatterplot depicts a positively sloped trendline, emphasizing the synchronous movements of these variables over the course of nearly two decades.

Our findings not only confirm the presence of a substantial correlation but also challenge conventional notions of stock market influences. The notion that the consumption of American cheese, a staple in burgers and comfort foods, could have a discernible impact on the stock price of a global beverage giant is as surprising as finding a slice of cheddar in your soda. However, it must be acknowledged that correlation does not imply causation, and further research is warranted to explore the underlying mechanisms driving this peculiar association.

This empirical evidence presents an intriguing paradox: while one might expect stock prices to be predominantly shaped by economic indicators and corporate performance, the aroma of melted cheese and the effervescence of soda may hold more sway than previously imagined. This unorthodox correlation paves the whey for future investigations into the esoteric forces that underpin stock market dynamics.

In summary, our results unveil a curiously compelling correlation between American cheese consumption and The Coca-Cola Company's stock price, underscoring the whimsical interplay of seemingly incongruous elements in the grand symphony of market forces. These findings beckon researchers and investors alike to venture beyond the ordinary and explore the surprising connections that lie beneath the surface of financial markets. As we savor the unexpected, let us embark on a journey that promises to be cheddar than fiction.


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 The Coca-Cola Company's stock price (KO). Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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 Cheddar and Coca-Cola Connection: An Examination of American Cheese Consumption and KO Stock Price Fluctuations

[[ABSTRACT]]
In this study, we delved into the intriguing relationship between the consumption of American cheese and the stock price of The Coca-Cola Company (KO). Utilizing data from the USDA and LSEG Analytics (Refinitiv) spanning nearly two decades, we set out to determine whether there exists a substantive correlation between these seemingly disparate elements. To our astonishment, we discovered a striking correlation coefficient of 0.9083366 and p < 0.01, prompting us to further investigate this curious phenomenon. Our findings not only raise eyebrows but also provoke questions about the potential influence of cheesy indulgences on the fizzy fortunes of Coca-Cola. Our study sheds light on this peculiarity and adds a slice of cheese to the complex tapestry of stock market dynamics.

[[LITERATURE REVIEW]]
The examination of seemingly incongruous variables in the context of stock market dynamics has been a subject of intrigue for scholars and practitioners alike. Smith et al. (2015) explored the influence of dairy products on consumer spending patterns, shedding light on the potential impact of cheese consumption on economic behaviors. Similarly, Doe and Jones (2018) conducted a comprehensive analysis of food industry trends and their ripple effects on stock market performance, offering valuable insights into the interconnectedness of consumer preferences and investment outcomes.
While these seminal works provide a sober foundation for understanding the broader landscape of consumer behavior and market dynamics, our inquiry into the association between American cheese consumption and The Coca-Cola Company's stock price (KO) expands the horizons of financial research into the realm of dairy-derived delight and carbonated conundrums.
Drawing from the wider literature on food economics and market interplay, pivotal works such as "The Omnivore's Dilemma" by Michael Pollan and "The Taste of Country Cooking" by Edna Lewis beckon us to contemplate the profound influence of culinary choices on economic systems. These thought-provoking narratives offer a delectable intersection of gastronomic delights and economic ramifications, setting the stage for our exploration of cheese’s whimsical dance with Coca-Cola's stock performance.
As we tread into the realm of speculative fiction and satirical musings, the allegorical tales of "Cheese Monopoly: A Culinary Adventure" and "A Carbonated Conspiracy: The Fizzy Follies" serve as whimsical reminders of the fantastical possibilities that underpin our academic pursuits. While these fictitious works may not offer empirical evidence, they kindle the imagination and provoke contemplation about the surreal potential of cheese and fizzy beverages shaping the financial markets.
Additionally, the influence of board games, such as "Cheeseopoly" and "Stock Market Showdown," subtly nudges us to consider the playful reverberations of cheese-themed economic ventures and stock market follies. Though far removed from the rigorous analysis of academic literature, these lighthearted diversions infuse a dash of levity into our scholarly pursuit and underscore the eclectic sources of inspiration that fuel our foray into the cheddar and Coca-Cola connection.
With this eclectic backdrop in mind, we embark on our investigation with a spirit of mirth and intellectual curiosity, ready to dissect the enigmatic correlation between American cheese consumption and the stock price fluctuations of The Coca-Cola Company (KO). Let the odyssey of cheese and fizz unfold as we unravel the intriguing enigma that lies at the intersection of dairy and dividends.

[[RESULTS]]
The statistical analysis conducted in this study yielded fascinating results, shedding light on the unforeseen connection between American cheese consumption and The Coca-Cola Company's stock price (KO). The correlation coefficient of 0.9083366 illuminated a robust relationship between these seemingly unrelated variables. With an r-squared value of 0.8250754 and a p-value less than 0.01, the strength of this correlation surpassed all initial expectations.
The figure (Fig. 1) illustrates the striking correlation between American cheese consumption and KO stock price fluctuations, providing a visual representation of the unexpected bond between dairy delicacies and fizzy finances. The scatterplot depicts a positively sloped trendline, emphasizing the synchronous movements of these variables over the course of nearly two decades.
Our findings not only confirm the presence of a substantial correlation but also challenge conventional notions of stock market influences. The notion that the consumption of American cheese, a staple in burgers and comfort foods, could have a discernible impact on the stock price of a global beverage giant is as surprising as finding a slice of cheddar in your soda. However, it must be acknowledged that correlation does not imply causation, and further research is warranted to explore the underlying mechanisms driving this peculiar association.
This empirical evidence presents an intriguing paradox: while one might expect stock prices to be predominantly shaped by economic indicators and corporate performance, the aroma of melted cheese and the effervescence of soda may hold more sway than previously imagined. This unorthodox correlation paves the whey for future investigations into the esoteric forces that underpin stock market dynamics.
In summary, our results unveil a curiously compelling correlation between American cheese consumption and The Coca-Cola Company's stock price, underscoring the whimsical interplay of seemingly incongruous elements in the grand symphony of market forces. These findings beckon researchers and investors alike to venture beyond the ordinary and explore the surprising connections that lie beneath the surface of financial markets. As we savor the unexpected, let us embark on a journey that promises to be cheddar than fiction.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The findings of this study provide robust evidence supporting the unexpected relationship between American cheese consumption and The Coca-Cola Company's stock price (KO), as suggested by prior research. Smith et al. (2015) and Doe and Jones (2018) laid the groundwork for our investigation by elucidating the potential impact of dairy products on consumer spending patterns and the ripple effects of food industry trends on stock market performance. Our results align with these seminal works, revealing a substantial correlation between cheese consumption and KO stock price fluctuations.

The observed correlation coefficient of 0.9083366, exceeding expectations, highlights the cheese-terious influence of American cheese on the fizzy fortunes of Coca-Cola. While the idea of dairy delicacies influencing stock prices may initially seem as unlikely as finding a slice of cheddar in one's soda, our study underlines the importance of considering the broader spectrum of consumer preferences and gastronomic indulgences in the realm of economic behaviors.

Drawing from the eclectic backdrop of literature, including Michael Pollan's "The Omnivore's Dilemma" and Edna Lewis's "The Taste of Country Cooking," our findings echo the imaginative intersection of culinary choices and economic ramifications. As we consider the whimsical dance of cheese with Coca-Cola's stock performance, our study breathes life into the once-fantastical notion that consumable commodities can indeed wield unexpected influence over the financial markets.

While our results provide compelling empirical evidence of the correlation, it is crucial to acknowledge that correlation does not imply causation. The aroma of melted cheese and the effervescence of soda may be synchronous, but this observation does not establish a causal relationship. Further research is warranted to disentangle the underlying mechanisms driving this peculiar association, encouraging scholars to delve deeper into the enigmatic forces shaping market dynamics.

In conclusion, our study adds a slice of cheese to the complex tapestry of stock market forces, challenging the conventional wisdom of stock market influences and highlighting the unforeseen connections that underscore the whimsical interplay of seemingly incongruous elements. As we ponder the cheesy depths of consumer choices and market dynamics, our findings beckon researchers and investors alike to appreciate the peculiarity and potential implications of the cheddar and Coca-Cola connection. Indeed, the coalescence of dairy and dividends promises to be cheddar than fiction, paving the way for a richer understanding of the enigmatic undercurrents that govern financial markets.


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 The Coca-Cola Company's stock price (KO). Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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 Cheddar and Coca-Cola Connection: An Examination of American Cheese Consumption and KO Stock Price Fluctuations

[[ABSTRACT]]
In this study, we delved into the intriguing relationship between the consumption of American cheese and the stock price of The Coca-Cola Company (KO). Utilizing data from the USDA and LSEG Analytics (Refinitiv) spanning nearly two decades, we set out to determine whether there exists a substantive correlation between these seemingly disparate elements. To our astonishment, we discovered a striking correlation coefficient of 0.9083366 and p < 0.01, prompting us to further investigate this curious phenomenon. Our findings not only raise eyebrows but also provoke questions about the potential influence of cheesy indulgences on the fizzy fortunes of Coca-Cola. Our study sheds light on this peculiarity and adds a slice of cheese to the complex tapestry of stock market dynamics.

[[INTRDUCTION]]
INTRODUCTION
The whimsical world of stock market analysis often leads us down unexpected paths, and our journey into the connection between American cheese consumption and The Coca-Cola Company's stock price (KO) is certainly no exception. While one might expect the stock market to be influenced by economic indicators, company performance, and global events, the notion of cheese – yes, cheese – playing a role in stock price fluctuations may strike some as utterly cheesy. But hold your laughter, dear reader, for our findings may just melt away any skepticism.
As we embark on this fromage-filled voyage, it is crucial to appreciate the significance of both American cheese and Coca-Cola in the broader context of consumer behavior and market dynamics. The enduring appeal of American cheese as a quintessential ingredient in burgers, grilled cheese sandwiches, and cheese fries suggests a deep-seated connection to the American palate. Similarly, The Coca-Cola Company's ubiquitous presence in the global beverage market makes it a stalwart contender in the corporate arena. Yet, as disparate as these entities may seem, our research aims to unravel the uncanny correlation between them.
The notion that a dairy delight could hold sway over the fortunes of a beverage behemoth may seem udderly preposterous at first glance. However, as we delve into the empirical evidence, we find ourselves confronted with a correlation coefficient of 0.9083366 and a p-value less than 0.01, revealing a relationship that simply cannot be dismissed as mere coincidence. This discovery propels us into uncharted territory, where the aroma of cheese and the sound of stock tickers commingle in intriguing ways.
Before we delve into our methodology and findings, it is imperative to acknowledge the potential for confounding variables and spurious correlations in our analysis. After all, it is entirely possible that the observed connection between American cheese consumption and KO stock price fluctuations is a queso fortuitous fluke. Nonetheless, our rigorous approach and comprehensive dataset lend credibility to our investigation, leaving us with a gouda feeling about the validity of our results.
As we illuminate this enigmatic correlation, we invite readers to embrace the unexpected, to savor the unexpected interplay between cheddar and Coca-Cola, and to join us in unraveling the mysteries of the stock market – one cheesy bite at a time. So, without further ado, let us delve into the cheddar and Coca-Cola connection and uncover the savory secrets that lie within.

[[RESULTS]]
The statistical analysis conducted in this study yielded fascinating results, shedding light on the unforeseen connection between American cheese consumption and The Coca-Cola Company's stock price (KO). The correlation coefficient of 0.9083366 illuminated a robust relationship between these seemingly unrelated variables. With an r-squared value of 0.8250754 and a p-value less than 0.01, the strength of this correlation surpassed all initial expectations.
The figure (Fig. 1) illustrates the striking correlation between American cheese consumption and KO stock price fluctuations, providing a visual representation of the unexpected bond between dairy delicacies and fizzy finances. The scatterplot depicts a positively sloped trendline, emphasizing the synchronous movements of these variables over the course of nearly two decades.
Our findings not only confirm the presence of a substantial correlation but also challenge conventional notions of stock market influences. The notion that the consumption of American cheese, a staple in burgers and comfort foods, could have a discernible impact on the stock price of a global beverage giant is as surprising as finding a slice of cheddar in your soda. However, it must be acknowledged that correlation does not imply causation, and further research is warranted to explore the underlying mechanisms driving this peculiar association.
This empirical evidence presents an intriguing paradox: while one might expect stock prices to be predominantly shaped by economic indicators and corporate performance, the aroma of melted cheese and the effervescence of soda may hold more sway than previously imagined. This unorthodox correlation paves the whey for future investigations into the esoteric forces that underpin stock market dynamics.
In summary, our results unveil a curiously compelling correlation between American cheese consumption and The Coca-Cola Company's stock price, underscoring the whimsical interplay of seemingly incongruous elements in the grand symphony of market forces. These findings beckon researchers and investors alike to venture beyond the ordinary and explore the surprising connections that lie beneath the surface of financial markets. As we savor the unexpected, let us embark on a journey that promises to be cheddar than fiction.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study has unraveled the queso mysterious and whimsical connection between American cheese consumption and The Coca-Cola Company's stock price, offering food for thought and perhaps a slice of provolone for the curious mind.

The robust correlation coefficient of 0.9083366, akin to a strong craving for cheesy goodness, has illuminated the surprising intertwining of these seemingly unrelated entities. Our findings not only provoke a chuckle but also urge further exploration into the enigmatic forces at play in the stock market.

As we wrap up this cheesy endeavor, it is evident that the influence of American cheese on KO stock prices is nothing short of a gouda surprise. The synchronous movements depicted in the scatterplot are as unexpected as finding a wedge of cheddar in a vending machine. While correlation does not necessarily imply causation, it's impossible to ignore the tantalizing aroma of causation lingering in the air, much like the scent of a freshly grilled cheese sandwich.

Despite the temptation to delve deeper into this savory saga, it is crucial to acknowledge the limitations of our study. Confounding variables, unexplored mechanisms, and the potential for coincidental correlation cannot be grated away lightly. Therefore, we assert, with the confidence of a connoisseur amid a platter of fine fromage, that further research in this area is as unnecessary as putting cheese on an apple pie – that is to say, entirely superfluous.

So, as we bid adieu to this cheesy escapade, let us remember that in the grand buffet of stock market dynamics, sometimes the most unexpected pairings yield the most palatable results. And with that, we proclaim, with all the certainty of choosing a grilled cheese over a salad, that no further research is needed in this delightfully cheesy realm.


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 Cheddar and Coca-Cola Connection: An Examination of American Cheese Consumption and KO Stock Price Fluctuations. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Unlikely Connections


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 Cheddar and Coca-Cola Connection: An Examination of American Cheese Consumption and KO Stock Price Fluctuations. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Culinary Economics and Financial 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 Cheddar and Coca-Cola Connection: An Examination of American Cheese Consumption and KO Stock Price Fluctuations with an abstract of In this study, we delved into the intriguing relationship between the consumption of American cheese and the stock price of The Coca-Cola Company (KO). Utilizing data from the USDA and LSEG Analytics (Refinitiv) spanning nearly two decades, we set out to determine whether there exists a substantive correlation between these seemingly disparate elements. To our astonishment, we discovered a striking correlation coefficient of 0.9083366 and p < 0.01, prompting us to further investigate this curious phenomenon. Our findings not only raise eyebrows but also provoke questions about the potential influence of cheesy indulgences on the fizzy fortunes of Coca-Cola. Our study sheds light on this peculiarity and adds a slice of cheese to the complex tapestry of stock market dynamics.

ChatGPT:

American cheese consumption, Coca-Cola stock price, correlation, USDA data, LSEG Analytics, stock market dynamics, Coca-Cola Company, KO stock, cheese consumption and stock prices, cheese and soda correlation, food and beverage industry correlation, stock market analysis, food industry trends

*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

The Coca-Cola Company's stock price (KO)
Detailed data title: Opening price of The Coca-Cola Company (KO) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function

See what else correlates with The Coca-Cola Company's stock price (KO)

Correlation r = 0.9083366 (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 = 0.8250754 (Coefficient of determination)
This means 82.5% of the change in the one variable (i.e., The Coca-Cola Company's stock price (KO)) 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 3.1E-8. 0.0000000309874599801748300000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.91 in 3.1E-6% of random cases. Said differently, if you correlated 32,271,119 random variables You don't actually need 32 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, 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.

[ 0.78, 0.96 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!


All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
20022003200420052006200720082009201020112012201320142015201620172018201920202021
American cheese consumption (Pounds per person)12.831412.561912.861212.64913.065612.792913.130613.355313.304813.039213.256913.357313.665614.044414.362115.090115.402715.538915.516.1
The Coca-Cola Company's stock price (KO) (Stock price)23.422.0825.420.9520.424.1830.7322.728.5832.9435.0836.9941.1242.2642.3441.545.9146.9455.3254.27




Why this works

  1. 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.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
  4. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."


# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([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([23.4,22.08,25.4,20.95,20.4,24.18,30.73,22.7,28.58,32.94,35.08,36.99,41.12,42.26,42.34,41.5,45.91,46.94,55.32,54.27,])
array_1_name = "American cheese consumption"
array_2_name = "The Coca-Cola Company's stock price (KO)"

# 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)



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Correlation ID: 2148 · Black Variable ID: 553 · Red Variable ID: 1565
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