Spurious correlation #3,454 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Butter consumption and the second variable is Illumina's stock price (ILMN). The chart goes from 2002 to 2021, and the two variables track closely in value over that time.

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

Download png, svg

AI explanation

As butter consumption increases, so does happiness. Happy people are more productive. With increased productivity, companies like Illumina experience higher stock prices as a result of the butter-induced productivity boost. It's a slippery but profitable correlation!

^{Show image generation prompt} Model: dalle-3
Prompt: [A photo-realistic image] depicts a serene morning scene, where the warm glow of the rising sun illuminates a group of people gathered around a table, happily spreading butter on their toast. Their joyful expressions and the soft radiance of the sunlight create an atmosphere of contentment and delight. In the background, a digital stock price ticker for Illumina (ILMN) climbs steadily, reflecting the growing optimism among investors. The image captures the harmonious blend of human enjoyment and financial optimism amidst the tranquil ambiance of a breakfast setting. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Butter consumption and Illumina's stock price (ILMN). 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: Voxel art A photo-realistic image Psychedelic Celtic art Scalar art
ChatGPT: A photo-realistic image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Butter consumption and Illumina's stock price (ILMN), in the following situation: Because as Butter consumption increased, people were spreading the news of its creamy benefits, causing a rise in happiness. With hearts aflutter, investors turned to Illumina, hoping to churn out profits like a well-oiled machine.. Keep the description simple.
ChatGPT: Amidst the rising sun, people happily spread butter on their toast, smiles lighting up their faces as they savor the creamy delight. In the background, the stock price ticker for Illumina (ILMN) climbs steadily, mirroring the growing excitement and optimism among investors.

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: [ A photo-realistic image ] and depicting this scene: Amidst the rising sun, people happily spread butter on their toast, smiles lighting up their faces as they savor the creamy delight. In the background, the stock price ticker for Illumina (ILMN) climbs steadily, mirroring the growing excitement and optimism among investors. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [A photo-realistic image] depicts a serene morning scene, where the warm glow of the rising sun illuminates a group of people gathered around a table, happily spreading butter on their toast. Their joyful expressions and the soft radiance of the sunlight create an atmosphere of contentment and delight. In the background, a digital stock price ticker for Illumina (ILMN) climbs steadily, reflecting the growing optimism among investors. The image captures the harmonious blend of human enjoyment and financial optimism amidst the tranquil ambiance of a breakfast setting.

*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 Butter consumption caused Illumina's stock price (ILMN) to increase.

AI academic paper

(Because p < 0.01)

Spreading the Wealth: Exploring the Butter-Illumina Stock Connection

The Journal of Gastronomical Finance

Jan 2024

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

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

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Butter consumption and Illumina's stock price (ILMN). 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. Then name a few real TV shows that sound like they might be relevant to the topic that you watched as research.

Here is the title and abstract of the paper:
[[TITLE]]
Spreading the Wealth: Exploring the Butter-Illumina Stock Connection

[[ABSTRACT]]
Butter consumption and stock prices may seem like an odd couple, but our research delves into the surprising link between these seemingly unrelated entities. Using USDA and LSEG Analytics data, we scrutinized the correlation between butter consumption and Illumina's stock price (ILMN) over the period from 2002 to 2021. Our findings revealed a impressively high correlation coefficient of 0.9189503 with statistical significance (p < 0.01), suggesting that the relationship between butter and Illumina's stock price is no mere fluke. Join us for a journey through the dairy aisle and stock market, as we uncover the buttery secret that may just churn up your investment strategy!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of butter consumption and stock prices may seem like a curious place to search for financial insight, but as the saying goes, "Where there’s a will, there’s a whey." In the realm of financial markets, seemingly unrelated factors often display unexpected connections, much like how a stock trader might unexpectedly find a stick of butter in their briefcase. Our study ventures into this uncharted territory to unravel the enigmatic relationship between butter consumption and Illumina's stock price (ILMN).
As we embark on this quest, we are reminded of the words of Mark Twain, who famously remarked, "The report of my death was an exaggeration." Similarly, the correlation between butter and Illumina's stock price may be seen as an exaggeration at first glance, but our findings reveal a tale that could rival any work of fiction. To quote another literary luminary, Charles Dickens, "It was the best of times, it was the worst of times," and indeed, our analysis uncovers a tale of buttery delight and financial insight.
The purpose of this research is not merely to butter up our readers with whimsical anecdotes, but rather to present a rigorous exploration of the data to uncover any substantive relationship between butter consumption and Illumina's stock price. With the use of USDA and LSEG Analytics data, we have conducted a comprehensive investigation from 2002 to 2021 to determine the extent of this unforeseen connection. Much like a chef meticulously crafting a complex dish, we have diligently sifted through the data to serve up a deliciously informative analysis.
Our findings, much like a well-churned batch of butter, present a smooth and consistent narrative. The correlation coefficient of 0.9189503 stands as a testament to the unexpected harmony between these two seemingly unrelated variables, with statistical significance (p < 0.01) leaving little room for doubt. The implications of this connection extend beyond the dairy aisle, potentially offering investors a fresh perspective when considering their portfolio strategies. Join us as we delve into this unlikely pairing, and discover how a little bit of butter may just be the secret ingredient for a successful stock market recipe.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Numerous studies have delved into the realm of seemingly unrelated correlations between consumer behavior and stock prices. Smith et al. (2015) examined the connection between avocado consumption and Tesla's stock price, while Doe and Jones (2018) investigated the link between coffee consumption and Amazon's stock price. However, the relationship between butter consumption and Illumina's stock price (ILMN) has remained largely unexplored in the academic literature.

In "The Big Fat Surprise," Teicholz (2014) presents an in-depth examination of the historical significance of dietary fats, shedding light on the societal perceptions of butter and its impact on consumer behavior. Similarly, "Bread, Wine, Chocolate" by Sims (2015) offers a compelling narrative on the interconnectedness of food, culture, and economics, highlighting the potential influence of culinary preferences on market dynamics.

Moving beyond non-fiction literature, the works of fiction also offer intriguing perspectives that could bear relevance to the topic at hand. In "The Butter Battle Book" by Dr. Seuss, the author humorously explores the societal implications of a conflict over buttering bread, providing a satirical take on the potential consequences of culinary preferences on larger social systems. Additionally, in "Like Water for Chocolate" by Laura Esquivel, the powerful interplay between food and emotional experience is portrayed, hinting at the potential for gustatory desires to influence broader human behavior, including economic decision-making.

As part of the researcher's data-gathering efforts, exploration of popular culture also became essential. The television series "The Great British Baking Show" offers a rich tapestry of culinary delights and competitive spirit, providing a flavorful backdrop for understanding the multifaceted influence of food trends on popular sentiment. In contrast, the show "Breaking Bad" delves into the world of illicit drug trade, demonstrating the far-reaching repercussions of hidden connections and unexpected correlations, albeit in a slightly different context.

Although the literature and popular culture offer valuable insights into related concepts, their direct application to the specific relationship between butter consumption and Illumina's stock price warrants further empirical investigation.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Butter consumption and Illumina's stock price (ILMN). 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]]
Spreading the Wealth: Exploring the Butter-Illumina Stock Connection

[[ABSTRACT]]
Butter consumption and stock prices may seem like an odd couple, but our research delves into the surprising link between these seemingly unrelated entities. Using USDA and LSEG Analytics data, we scrutinized the correlation between butter consumption and Illumina's stock price (ILMN) over the period from 2002 to 2021. Our findings revealed a impressively high correlation coefficient of 0.9189503 with statistical significance (p < 0.01), suggesting that the relationship between butter and Illumina's stock price is no mere fluke. Join us for a journey through the dairy aisle and stock market, as we uncover the buttery secret that may just churn up your investment strategy!

[[INTRODUCTION]]
The intersection of butter consumption and stock prices may seem like a curious place to search for financial insight, but as the saying goes, "Where there’s a will, there’s a whey." In the realm of financial markets, seemingly unrelated factors often display unexpected connections, much like how a stock trader might unexpectedly find a stick of butter in their briefcase. Our study ventures into this uncharted territory to unravel the enigmatic relationship between butter consumption and Illumina's stock price (ILMN).
As we embark on this quest, we are reminded of the words of Mark Twain, who famously remarked, "The report of my death was an exaggeration." Similarly, the correlation between butter and Illumina's stock price may be seen as an exaggeration at first glance, but our findings reveal a tale that could rival any work of fiction. To quote another literary luminary, Charles Dickens, "It was the best of times, it was the worst of times," and indeed, our analysis uncovers a tale of buttery delight and financial insight.
The purpose of this research is not merely to butter up our readers with whimsical anecdotes, but rather to present a rigorous exploration of the data to uncover any substantive relationship between butter consumption and Illumina's stock price. With the use of USDA and LSEG Analytics data, we have conducted a comprehensive investigation from 2002 to 2021 to determine the extent of this unforeseen connection. Much like a chef meticulously crafting a complex dish, we have diligently sifted through the data to serve up a deliciously informative analysis.
Our findings, much like a well-churned batch of butter, present a smooth and consistent narrative. The correlation coefficient of 0.9189503 stands as a testament to the unexpected harmony between these two seemingly unrelated variables, with statistical significance (p < 0.01) leaving little room for doubt. The implications of this connection extend beyond the dairy aisle, potentially offering investors a fresh perspective when considering their portfolio strategies. Join us as we delve into this unlikely pairing, and discover how a little bit of butter may just be the secret ingredient for a successful stock market recipe.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data for this study was collected from 2002 to 2021 from a variety of sources, primarily the United States Department of Agriculture (USDA) and LSEG Analytics (Refinitiv). The selection of this timeframe was intentional, as it captures a period of significant economic and market fluctuations, allowing for a robust assessment of the relationship between butter consumption and Illumina's stock price (ILMN).

To examine the butter-Illumina stock connection, various methodologies were employed to ensure a comprehensive analysis. Firstly, the butter consumption data was meticulously scrutinized, akin to a dairy farmer inspecting each churn for the perfect batch of butter. Factors such as per capita butter consumption, regional consumption variations, and seasonal patterns were taken into account. Correlations were also explored between butter consumption and broader economic indicators, such as GDP and consumer spending, to contextualize the butter consumption patterns.

Secondly, the stock price data of Illumina (ILMN) was subjected to a rigorous analysis, drawing from both fundamental and technical perspectives. Candlestick charts were consulted, not for their wax, but for insights on market sentiment and price movements. Additionally, quantitative models, including ARIMA and GARCH, were utilized to capture the volatility and time series dynamics of Illumina's stock price.

Next, advanced statistical techniques were employed to establish the correlation between butter consumption and Illumina's stock price. This involved calculating the Pearson correlation coefficient, spearheading an expedition into uncharted territories with confidence intervals, and conducting Granger causality tests to discern any potential lead-lag relationship between the variables.

Furthermore, supplementary analyses were conducted to control for confounding variables, such as interest rates, inflation, and market sentiment. This approach ensured that the observed relationship between butter consumption and Illumina's stock price remained robust and not merely a result of external factors or spurious correlations. Sensitivity analyses were also performed to assess the stability of findings under varying model specifications.

Lastly, to elucidate the narrative behind the data, qualitative insights from industry experts and market participants were sought. Through interviews and surveys, the qualitative data enriched the study with on-the-ground perspectives, adding a layer of richness much like a pat of butter melting over a warm slice of bread.

As much as I'd like to say we churned through the data with lightning speed, the process was as slow as waiting for butter to soften at room temperature. Nonetheless, the painstaking and multifaceted approach to this study encapsulates the thoroughness and depth of our investigation into the butter-Illumina stock connection.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Butter consumption and Illumina's stock price (ILMN). 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 0.9189503, r-squared of 0.8444696, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
Spreading the Wealth: Exploring the Butter-Illumina Stock Connection

[[ABSTRACT]]
Butter consumption and stock prices may seem like an odd couple, but our research delves into the surprising link between these seemingly unrelated entities. Using USDA and LSEG Analytics data, we scrutinized the correlation between butter consumption and Illumina's stock price (ILMN) over the period from 2002 to 2021. Our findings revealed a impressively high correlation coefficient of 0.9189503 with statistical significance (p < 0.01), suggesting that the relationship between butter and Illumina's stock price is no mere fluke. Join us for a journey through the dairy aisle and stock market, as we uncover the buttery secret that may just churn up your investment strategy!

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intersection of butter consumption and stock prices may seem like a curious place to search for financial insight, but as the saying goes, "Where there’s a will, there’s a whey." In the realm of financial markets, seemingly unrelated factors often display unexpected connections, much like how a stock trader might unexpectedly find a stick of butter in their briefcase. Our study ventures into this uncharted territory to unravel the enigmatic relationship between butter consumption and Illumina's stock price (ILMN).
As we embark on this quest, we are reminded of the words of Mark Twain, who famously remarked, "The report of my death was an exaggeration." Similarly, the correlation between butter and Illumina's stock price may be seen as an exaggeration at first glance, but our findings reveal a tale that could rival any work of fiction. To quote another literary luminary, Charles Dickens, "It was the best of times, it was the worst of times," and indeed, our analysis uncovers a tale of buttery delight and financial insight.
The purpose of this research is not merely to butter up our readers with whimsical anecdotes, but rather to present a rigorous exploration of the data to uncover any substantive relationship between butter consumption and Illumina's stock price. With the use of USDA and LSEG Analytics data, we have conducted a comprehensive investigation from 2002 to 2021 to determine the extent of this unforeseen connection. Much like a chef meticulously crafting a complex dish, we have diligently sifted through the data to serve up a deliciously informative analysis.
Our findings, much like a well-churned batch of butter, present a smooth and consistent narrative. The correlation coefficient of 0.9189503 stands as a testament to the unexpected harmony between these two seemingly unrelated variables, with statistical significance (p < 0.01) leaving little room for doubt. The implications of this connection extend beyond the dairy aisle, potentially offering investors a fresh perspective when considering their portfolio strategies. Join us as we delve into this unlikely pairing, and discover how a little bit of butter may just be the secret ingredient for a successful stock market recipe.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The results of our investigation into the relationship between butter consumption and Illumina's stock price (ILMN) from 2002 to 2021 revealed a remarkably high correlation coefficient of 0.9189503, indicative of a strong positive association between these two seemingly incongruous elements. This finding suggests that the fluctuations in butter consumption may indeed be related to the movements of Illumina's stock price, and not just because investors were buttering up each other.

Furthermore, the r-squared value of 0.8444696 indicates that approximately 84.45% of the variability in Illumina's stock price can be explained by changes in butter consumption. This high explanatory power suggests that butter consumption may act as a creamy indicator of the movements in Illumina's stock price, much like a flaky pastry is a reliable indicator of a delightful dessert.

Moreover, the statistical significance of our findings (p < 0.01) lends strong support to the notion that the observed correlation is not simply a result of chance. This statistically significant relationship between butter consumption and Illumina's stock price may leave some scratching their heads, much like trying to understand the plot of a David Lynch film. However, the numbers don't lie; there's definitely something churn-worthy going on here.

The surprisingly strong association between these variables is visually depicted in Fig. 1, which showcases a scatterplot illustrating the tight relationship between butter consumption and Illumina's stock price. Just as the marriage of peanut butter and jelly creates a winning combination, the plot visually confirms the robust connection we have uncovered between these two unlikely bedfellows.

The implications of these findings extend beyond the confines of both the dairy aisle and the stock market, as they may offer investors a unique and unexpected perspective for potential inclusion in their portfolio strategies. Like a chef experimenting with unusual ingredients, investors may need to consider the buttery goodness of this correlation when whipping up their investment portfolios.

In conclusion, our investigation has unveiled an extraordinary connection between butter consumption and Illumina's stock price, challenging conventional wisdom and providing a savory opportunity for further exploration. This unexpected link begs the question: could butter be the unsung hero of stock market predictions, or is it just churning out random correlations? Further research in this uncharted territory will undoubtedly shed more light on this peculiar phenomenon.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Butter consumption and Illumina's stock price (ILMN). 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]]
Spreading the Wealth: Exploring the Butter-Illumina Stock Connection

[[ABSTRACT]]
Butter consumption and stock prices may seem like an odd couple, but our research delves into the surprising link between these seemingly unrelated entities. Using USDA and LSEG Analytics data, we scrutinized the correlation between butter consumption and Illumina's stock price (ILMN) over the period from 2002 to 2021. Our findings revealed a impressively high correlation coefficient of 0.9189503 with statistical significance (p < 0.01), suggesting that the relationship between butter and Illumina's stock price is no mere fluke. Join us for a journey through the dairy aisle and stock market, as we uncover the buttery secret that may just churn up your investment strategy!

[[LITERATURE REVIEW]]
Numerous studies have delved into the realm of seemingly unrelated correlations between consumer behavior and stock prices. Smith et al. (2015) examined the connection between avocado consumption and Tesla's stock price, while Doe and Jones (2018) investigated the link between coffee consumption and Amazon's stock price. However, the relationship between butter consumption and Illumina's stock price (ILMN) has remained largely unexplored in the academic literature.
In "The Big Fat Surprise," Teicholz (2014) presents an in-depth examination of the historical significance of dietary fats, shedding light on the societal perceptions of butter and its impact on consumer behavior. Similarly, "Bread, Wine, Chocolate" by Sims (2015) offers a compelling narrative on the interconnectedness of food, culture, and economics, highlighting the potential influence of culinary preferences on market dynamics.
Moving beyond non-fiction literature, the works of fiction also offer intriguing perspectives that could bear relevance to the topic at hand. In "The Butter Battle Book" by Dr. Seuss, the author humorously explores the societal implications of a conflict over buttering bread, providing a satirical take on the potential consequences of culinary preferences on larger social systems. Additionally, in "Like Water for Chocolate" by Laura Esquivel, the powerful interplay between food and emotional experience is portrayed, hinting at the potential for gustatory desires to influence broader human behavior, including economic decision-making.
As part of the researcher's data-gathering efforts, exploration of popular culture also became essential. The television series "The Great British Baking Show" offers a rich tapestry of culinary delights and competitive spirit, providing a flavorful backdrop for understanding the multifaceted influence of food trends on popular sentiment. In contrast, the show "Breaking Bad" delves into the world of illicit drug trade, demonstrating the far-reaching repercussions of hidden connections and unexpected correlations, albeit in a slightly different context.
Although the literature and popular culture offer valuable insights into related concepts, their direct application to the specific relationship between butter consumption and Illumina's stock price warrants further empirical investigation.

[[RESULTS]]
The results of our investigation into the relationship between butter consumption and Illumina's stock price (ILMN) from 2002 to 2021 revealed a remarkably high correlation coefficient of 0.9189503, indicative of a strong positive association between these two seemingly incongruous elements. This finding suggests that the fluctuations in butter consumption may indeed be related to the movements of Illumina's stock price, and not just because investors were buttering up each other.
Furthermore, the r-squared value of 0.8444696 indicates that approximately 84.45% of the variability in Illumina's stock price can be explained by changes in butter consumption. This high explanatory power suggests that butter consumption may act as a creamy indicator of the movements in Illumina's stock price, much like a flaky pastry is a reliable indicator of a delightful dessert.
Moreover, the statistical significance of our findings (p < 0.01) lends strong support to the notion that the observed correlation is not simply a result of chance. This statistically significant relationship between butter consumption and Illumina's stock price may leave some scratching their heads, much like trying to understand the plot of a David Lynch film. However, the numbers don't lie; there's definitely something churn-worthy going on here.
The surprisingly strong association between these variables is visually depicted in Fig. 1, which showcases a scatterplot illustrating the tight relationship between butter consumption and Illumina's stock price. Just as the marriage of peanut butter and jelly creates a winning combination, the plot visually confirms the robust connection we have uncovered between these two unlikely bedfellows.
The implications of these findings extend beyond the confines of both the dairy aisle and the stock market, as they may offer investors a unique and unexpected perspective for potential inclusion in their portfolio strategies. Like a chef experimenting with unusual ingredients, investors may need to consider the buttery goodness of this correlation when whipping up their investment portfolios.
In conclusion, our investigation has unveiled an extraordinary connection between butter consumption and Illumina's stock price, challenging conventional wisdom and providing a savory opportunity for further exploration. This unexpected link begs the question: could butter be the unsung hero of stock market predictions, or is it just churning out random correlations? Further research in this uncharted territory will undoubtedly shed more light on this peculiar phenomenon.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study have brought to light a surprisingly strong connection between butter consumption and Illumina's stock price, echoing previous research on seemingly unrelated correlations. The high correlation coefficient and r-squared value, along with the statistically significant relationship, offer compelling evidence in support of the notion that butter consumption may indeed be linked to movements in Illumina's stock price.

Drawing upon the literature review, it's evident that our findings align with previous works investigating unexpected connections between consumer behavior and stock prices. The parallels between butter consumption and Illumina's stock price and the avocado consumption-Tesla stock price and coffee consumption-Amazon stock price connections underscore the potential influence of dietary preferences on investment patterns. Moreover, the playful exploration of culinary influences in "The Butter Battle Book," "Like Water for Chocolate," and "The Great British Baking Show" offers a whimsical backdrop to our serious findings, highlighting the subtleties of gustatory desires in shaping economic phenomena.

While the nature of the relationship between butter consumption and stock prices may seem incongruous, the strong empirical support for the correlation prompts serious contemplation of its potential implications for investment strategies. Just as the unexpected twists and turns in an M. Night Shyamalan film keep audiences on their toes, the revelation of this buttery connection may revolutionize the way investors perceive and interpret market indicators. Indeed, as the saying goes, the proof of the pudding is in the eating, and our findings affirm the robustness of the butter-Illumina stock relationship.

The results of our investigation not only add a touch of whimsy to the world of finance but also emphasize the importance of considering unconventional indicators in investment decision-making. In a field often characterized by rigid models and predictable patterns, our study serves as a delicious reminder that innovation in financial analysis may stem from unexpected sources – much like the invention of the cronut or the fusion cuisine movement. Therefore, our findings present a buttery opportunity for further exploration and may pave the way for a more nuanced understanding of the interplay between consumer behaviors and stock market dynamics. As we continue to churn out new research in this captivating area, the tantalizing aroma of butter may just lead us to butter understanding of market trends.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Butter consumption and Illumina's stock price (ILMN). 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]]
Spreading the Wealth: Exploring the Butter-Illumina Stock Connection

[[ABSTRACT]]
Butter consumption and stock prices may seem like an odd couple, but our research delves into the surprising link between these seemingly unrelated entities. Using USDA and LSEG Analytics data, we scrutinized the correlation between butter consumption and Illumina's stock price (ILMN) over the period from 2002 to 2021. Our findings revealed a impressively high correlation coefficient of 0.9189503 with statistical significance (p < 0.01), suggesting that the relationship between butter and Illumina's stock price is no mere fluke. Join us for a journey through the dairy aisle and stock market, as we uncover the buttery secret that may just churn up your investment strategy!

[[INTRDUCTION]]
The intersection of butter consumption and stock prices may seem like a curious place to search for financial insight, but as the saying goes, "Where there’s a will, there’s a whey." In the realm of financial markets, seemingly unrelated factors often display unexpected connections, much like how a stock trader might unexpectedly find a stick of butter in their briefcase. Our study ventures into this uncharted territory to unravel the enigmatic relationship between butter consumption and Illumina's stock price (ILMN).
As we embark on this quest, we are reminded of the words of Mark Twain, who famously remarked, "The report of my death was an exaggeration." Similarly, the correlation between butter and Illumina's stock price may be seen as an exaggeration at first glance, but our findings reveal a tale that could rival any work of fiction. To quote another literary luminary, Charles Dickens, "It was the best of times, it was the worst of times," and indeed, our analysis uncovers a tale of buttery delight and financial insight.
The purpose of this research is not merely to butter up our readers with whimsical anecdotes, but rather to present a rigorous exploration of the data to uncover any substantive relationship between butter consumption and Illumina's stock price. With the use of USDA and LSEG Analytics data, we have conducted a comprehensive investigation from 2002 to 2021 to determine the extent of this unforeseen connection. Much like a chef meticulously crafting a complex dish, we have diligently sifted through the data to serve up a deliciously informative analysis.
Our findings, much like a well-churned batch of butter, present a smooth and consistent narrative. The correlation coefficient of 0.9189503 stands as a testament to the unexpected harmony between these two seemingly unrelated variables, with statistical significance (p < 0.01) leaving little room for doubt. The implications of this connection extend beyond the dairy aisle, potentially offering investors a fresh perspective when considering their portfolio strategies. Join us as we delve into this unlikely pairing, and discover how a little bit of butter may just be the secret ingredient for a successful stock market recipe.

[[RESULTS]]
The results of our investigation into the relationship between butter consumption and Illumina's stock price (ILMN) from 2002 to 2021 revealed a remarkably high correlation coefficient of 0.9189503, indicative of a strong positive association between these two seemingly incongruous elements. This finding suggests that the fluctuations in butter consumption may indeed be related to the movements of Illumina's stock price, and not just because investors were buttering up each other.
Furthermore, the r-squared value of 0.8444696 indicates that approximately 84.45% of the variability in Illumina's stock price can be explained by changes in butter consumption. This high explanatory power suggests that butter consumption may act as a creamy indicator of the movements in Illumina's stock price, much like a flaky pastry is a reliable indicator of a delightful dessert.
Moreover, the statistical significance of our findings (p < 0.01) lends strong support to the notion that the observed correlation is not simply a result of chance. This statistically significant relationship between butter consumption and Illumina's stock price may leave some scratching their heads, much like trying to understand the plot of a David Lynch film. However, the numbers don't lie; there's definitely something churn-worthy going on here.
The surprisingly strong association between these variables is visually depicted in Fig. 1, which showcases a scatterplot illustrating the tight relationship between butter consumption and Illumina's stock price. Just as the marriage of peanut butter and jelly creates a winning combination, the plot visually confirms the robust connection we have uncovered between these two unlikely bedfellows.
The implications of these findings extend beyond the confines of both the dairy aisle and the stock market, as they may offer investors a unique and unexpected perspective for potential inclusion in their portfolio strategies. Like a chef experimenting with unusual ingredients, investors may need to consider the buttery goodness of this correlation when whipping up their investment portfolios.
In conclusion, our investigation has unveiled an extraordinary connection between butter consumption and Illumina's stock price, challenging conventional wisdom and providing a savory opportunity for further exploration. This unexpected link begs the question: could butter be the unsung hero of stock market predictions, or is it just churning out random correlations? Further research in this uncharted territory will undoubtedly shed more light on this peculiar phenomenon.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation has churned up a delectable dish of data, unveiling the unexpected harmony between butter consumption and Illumina's stock price. This correlation, as strong as a well-churned batch of butter, has left us all a bit befuddled - much like trying to figure out the plot of a David Lynch film. The statistical significance of our findings (p < 0.01) reminds us that the numbers don't lie, even when they seem to spread the truth a little thin.

The implications of this buttery connection extend beyond the financial markets, potentially offering investors a unique and unexpected perspective when considering their portfolio strategies. Just as a chef might experiment with unusual ingredients, investors may need to consider the creamy goodness of this correlation when cooking up their investment portfolios.

However, before we fully spread the news of this unlikely pairing, it is important to take our findings with a grain of salted butter. While the connection between butter consumption and Illumina's stock price certainly seems robust, further research is needed to confirm whether butter truly churns out reliable stock market predictions or if there's just something dairy strange going on here.

In light of our findings, it may be tempting to dive headfirst into a "butter for stocks" investment strategy, but we urge caution. After all, we wouldn't want to risk investors becoming too buttered up and ending up in a jam. Therefore, we conclude that no more research is needed in this area, and we await future studies to butter us up with further insights into this surprising correlation.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Spreading the Wealth: Exploring the Butter-Illumina Stock Connection. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Gastronomical Finance

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Spreading the Wealth: Exploring the Butter-Illumina Stock Connection. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Dairy Economic Research

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Spreading the Wealth: Exploring the Butter-Illumina Stock Connection with an abstract of Butter consumption and stock prices may seem like an odd couple, but our research delves into the surprising link between these seemingly unrelated entities. Using USDA and LSEG Analytics data, we scrutinized the correlation between butter consumption and Illumina's stock price (ILMN) over the period from 2002 to 2021. Our findings revealed a impressively high correlation coefficient of 0.9189503 with statistical significance (p < 0.01), suggesting that the relationship between butter and Illumina's stock price is no mere fluke. Join us for a journey through the dairy aisle and stock market, as we uncover the buttery secret that may just churn up your investment strategy!

ChatGPT:

butter consumption, Illumina stock, USDA data, LSEG Analytics, correlation, stock prices, investment strategy, dairy market, statistical significance, butter consumption trends, stock price correlation

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

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Data details

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

Illumina's stock price (ILMN)
Detailed data title: Opening price of Illumina (ILMN) 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 Illumina's stock price (ILMN)

Correlation r = 0.9189503 (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 = 0.8444696 (Coefficient of determination)
This means 84.4% of the change in the one variable (i.e., Illumina's stock price (ILMN)) is predictable based on the change in the other (i.e., Butter consumption) over the 20 years from 2002 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.07E-8.^Show 0.0000000106512589754003400000
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 0.92 in 1.07E-6% of random cases. Said differently, if you correlated 93,885,615 random variables^Note You don't actually need 93 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 19 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.8, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Butter consumption (Pounds per person)	4.4	4.5	4.5	4.5	4.7	4.7	5	5	4.9	5.4	5.5	5.5	5.5	5.6	5.7	5.7	6	6.2	6.3	6.5
Illumina's stock price (ILMN) (Stock price)	5.93	1.71	3.65	4.71	7.13	19.63	29.91	26.05	31.12	64.05	31	56.1	110.48	186.17	187.65	129.17	224.78	294.71	329.05	370.84

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([4.4,4.5,4.5,4.5,4.7,4.7,5,5,4.9,5.4,5.5,5.5,5.5,5.6,5.7,5.7,6,6.2,6.3,6.5,])
array_2 = np.array([5.93,1.71,3.65,4.71,7.13,19.63,29.91,26.05,31.12,64.05,31,56.1,110.48,186.17,187.65,129.17,224.78,294.71,329.05,370.84,])
array_1_name = "Butter consumption"
array_2_name = "Illumina's stock price (ILMN)"

# 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 Butter consumption
Line chart for only Illumina's stock price (ILMN)
AI-generated correlation image
The spurious research paper: Spreading the Wealth: Exploring the Butter-Illumina Stock Connection

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Correlation ID: 3454 · Black Variable ID: 557 · Red Variable ID: 1880


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