Spurious correlation #3,282 · 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 Trane Technologies' stock price (TT). The chart goes from 2002 to 2021, and the two variables track closely in value over that time.

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

Download png, svg

AI explanation

As Americans consumed more American cheese, their desire for the classic comfort of grilled cheese sandwiches grew. This led to an uptick in the use of kitchen appliances, including refrigerators. With an increase in the demand for refrigerators, Trane Technologies, a company that also manufactures cooling systems, saw a parallel rise in interest. As a result, investors flocked to TT, driving up the stock price. So, in a bizarrely cheesy twist, it seems that the path to higher stock prices truly is paved with slices of American cheese!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a futuristic diner with a sleek and sophisticated interior. Show patrons seated at high-tech tables, enjoying gourmet grilled cheese sandwiches made with American cheese. In the background, display a digital stock market ticker prominently featuring the soaring stock price of Trane Technologies (TT). The ambiance should exude a sense of modernity and innovation, with subtle nods to the high-tech nature of the 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: American cheese consumption and Trane Technologies' stock price (TT). 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: a funny image you would see on reddit Glitch art Realistic Scalar art 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 Trane Technologies' stock price (TT), in the following situation: Because American cheese consumption increased, more people craved grilled cheese, causing a surge in demand for Trane Technologies' energy-efficient appliances, raising TT stock price.. Keep the description simple.
ChatGPT: A bustling diner with people enjoying grilled cheese sandwiches made with American cheese, while in the background, the stock market ticker shows Trane Technologies' (TT) stock price soaring.

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 bustling diner with people enjoying grilled cheese sandwiches made with American cheese, while in the background, the stock market ticker shows Trane Technologies' (TT) stock price soaring. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a futuristic diner with a sleek and sophisticated interior. Show patrons seated at high-tech tables, enjoying gourmet grilled cheese sandwiches made with American cheese. In the background, display a digital stock market ticker prominently featuring the soaring stock price of Trane Technologies (TT). The ambiance should exude a sense of modernity and innovation, with subtle nods to the high-tech nature of the 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 American cheese consumption caused Trane Technologies' stock price (TT) to increase. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Feta or Cheddar, TT Gets Better: The Whey to Wealth Connection Between American Cheese Consumption and Trane Technologies' Stock Price

Journal of Dairy Economics and Financial Analysis

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between American cheese consumption and Trane Technologies' stock price (TT). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.

Here is the title and abstract of the paper:
[[TITLE]]
Feta or Cheddar, TT Gets Better: The Whey to Wealth Connection Between American Cheese Consumption and Trane Technologies' Stock Price

[[ABSTRACT]]
This paper examines the relationship between American cheese consumption and the stock price of Trane Technologies (TT) from 2002 to 2021. We hypothesized that the consumption of American cheese, a beloved staple in many households, may have an impact on the financial performance of Trane Technologies, a global leader in climate technology. Our research team used data from the USDA and LSEG Analytics (Refinitiv) to assess this curious correlation. Surprisingly, we found a strong positive correlation coefficient of 0.9022704 and p < 0.01, indicating a robust association between American cheese consumption and TT's stock price.

It seems that the old adage "buy low, sell high" could be updated to "grate more, accumulate more." Our findings suggest that as American cheese consumption rises, so does the stock price of Trane Technologies. Perhaps this phenomenon can be attributed to the comforting nature of cheese, leading to increased investor confidence and a "gouda" feeling about TT's prospects.

This research sheds light on the unexplored synergies between dairy products and financial markets, offering a new perspective on the interconnectedness of seemingly unrelated sectors. So, next time you enjoy a cheesy snack, remember that you might be inadvertently contributing to the prosperity of a climate technology company.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of finance and dairy may seem as unusual as pairing blue cheese with chocolate, but our investigation into the relationship between American cheese consumption and the stock price of Trane Technologies (TT) suggests otherwise. As the saying goes, "Don't put all your eggs in one basket," but what about putting all your cheese in one portfolio? (I can hear the groans already!)
In the world of finance, various factors drive stock price movements, and it’s often a brie-lliant task to discern the hidden correlations. However, our study aims to gouda-n the missing link between a beloved household dairy product and the financial performance of a juggernaut in the climate technology industry. The stakes are high, but can we say the same about the curds? (Pun intended, of course!)
Cheese is renowned for its ability to enhance the flavor of a dish, but could it also enhance the flavor of an investment portfolio? Our paper aims to provoke such thought-provolone ideas. (You see what I did there?) By examining data from 2002 to 2021, we dive into the cheddar-ting world of statistical analysis to investigate the whey in which American cheese consumption impacts TT's stock price.
This study not only offers a novel perspective on the dynamics of financial markets and consumer behavior, but it also stands as a testament to the vaste potential for unearthing unexpected interactions between disparate industries. After all, who would have thought that the cheese on your grilled cheese sandwich might hold the secret to investment success? (Cheesy, I know!)

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Several studies have investigated the relationship between various consumer goods and stock prices, shedding light on the potential impacts of everyday consumption habits on financial markets. In "Smith et al.," the authors find that chocolate consumption is positively correlated with the performance of confectionery companies, while in "Doe and Jones," the authors examine the influence of coffee consumption on the stock prices of multinational coffee chains. These studies demonstrate the significance of consumer behaviors in shaping stock market dynamics.

Now, turning to the broader literature related to food and finance, "The Omnivore's Dilemma" by Michael Pollan and "Fast Food Nation" by Eric Schlosser illuminate the complex interplay between food production, consumption, and financial interests. On a more fictional note, the novels "American Psycho" by Bret Easton Ellis and "The Bonfire of the Vanities" by Tom Wolfe offer satirical perspectives on the excesses of Wall Street and consumer culture.

Expanding our review further, we must acknowledge the unconventional sources of insight that have contributed to our understanding of this peculiar correlation. While we did not encounter any scholarly work specifically on American cheese consumption and stock prices, an in-depth analysis of grocery store receipts, particularly those from local supermarkets and patisseries, provided anecdotal evidence of a potential linkage between cheese-related purchases and financial market trends.

In addition, the meticulous scrutiny of random internet forums and the analysis of whimsical theories put forth by self-proclaimed "investment gurus" on social media platforms have undoubtedly added a layer of "provolone" to our investigation. While not methodologically rigorous, these unconventional sources have contributed to the breadth of our inquiry, reminding us of the importance of exploring diverse perspectives, no matter how unconventional they may appear.

In summary, the existing literature has provided valuable insights into the complex relationship between consumer behavior and stock market performance, with a significant gap in the specific analysis of American cheese consumption and its impact on Trane Technologies' stock price. The diversity of sources consulted, ranging from reputable academic studies to whimsical musings, has enriched the scope of our inquiry and expanded the horizons of our investigation, demonstrating the need for interdisciplinary approaches in exploring unexpected connections in the world of finance.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between American cheese consumption and Trane Technologies' stock price (TT). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from USDA and LSEG Analytics (Refinitiv) . You used data from 2002 to 2021

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Feta or Cheddar, TT Gets Better: The Whey to Wealth Connection Between American Cheese Consumption and Trane Technologies' Stock Price

[[ABSTRACT]]
This paper examines the relationship between American cheese consumption and the stock price of Trane Technologies (TT) from 2002 to 2021. We hypothesized that the consumption of American cheese, a beloved staple in many households, may have an impact on the financial performance of Trane Technologies, a global leader in climate technology. Our research team used data from the USDA and LSEG Analytics (Refinitiv) to assess this curious correlation. Surprisingly, we found a strong positive correlation coefficient of 0.9022704 and p < 0.01, indicating a robust association between American cheese consumption and TT's stock price.

It seems that the old adage "buy low, sell high" could be updated to "grate more, accumulate more." Our findings suggest that as American cheese consumption rises, so does the stock price of Trane Technologies. Perhaps this phenomenon can be attributed to the comforting nature of cheese, leading to increased investor confidence and a "gouda" feeling about TT's prospects.

This research sheds light on the unexplored synergies between dairy products and financial markets, offering a new perspective on the interconnectedness of seemingly unrelated sectors. So, next time you enjoy a cheesy snack, remember that you might be inadvertently contributing to the prosperity of a climate technology company.

[[INTRODUCTION]]
The intersection of finance and dairy may seem as unusual as pairing blue cheese with chocolate, but our investigation into the relationship between American cheese consumption and the stock price of Trane Technologies (TT) suggests otherwise. As the saying goes, "Don't put all your eggs in one basket," but what about putting all your cheese in one portfolio? (I can hear the groans already!)
In the world of finance, various factors drive stock price movements, and it’s often a brie-lliant task to discern the hidden correlations. However, our study aims to gouda-n the missing link between a beloved household dairy product and the financial performance of a juggernaut in the climate technology industry. The stakes are high, but can we say the same about the curds? (Pun intended, of course!)
Cheese is renowned for its ability to enhance the flavor of a dish, but could it also enhance the flavor of an investment portfolio? Our paper aims to provoke such thought-provolone ideas. (You see what I did there?) By examining data from 2002 to 2021, we dive into the cheddar-ting world of statistical analysis to investigate the whey in which American cheese consumption impacts TT's stock price.
This study not only offers a novel perspective on the dynamics of financial markets and consumer behavior, but it also stands as a testament to the vaste potential for unearthing unexpected interactions between disparate industries. After all, who would have thought that the cheese on your grilled cheese sandwich might hold the secret to investment success? (Cheesy, I know!)

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the connection between American cheese consumption and Trane Technologies' stock price (TT), a thorough and meticulous research approach was employed. The study utilized a combination of data mining, econometric modeling, and cheesy puns to unravel the wheyward path that leads from dairy consumption to stock market movements.

Firstly, data on American cheese consumption was obtained from the United States Department of Agriculture (USDA), which provided comprehensive statistics on cheese production and consumption from 2002 to 2021. The LSEG Analytics (Refinitiv) platform was leveraged to procure precise and timely stock price data for Trane Technologies over the same time period. The combination of these data sources ensured a comprehensive and holistic understanding of the variables under scrutiny, much like a well-ripened cheese paired with the perfect wine.

The research team then embarked on an extensive data cleansing process, removing outliers and discrepancies to ensure the purity and integrity of the dataset. After all, much like aging cheese, accurate data requires time, patience, and the occasional cringe-worthy dad joke to make the process more palatable for all involved.

Following the data preparation phase, the statistical analysis began with the calculation of relevant parameters such as mean, median, and standard deviation of both the American cheese consumption and TT's stock price. These critical measures provided a foundational understanding of the central tendencies and dispersion characteristics within the datasets, allowing for informed comparisons and correlations to be drawn. We must note that the process of statistical compilation can be as delicate and nuanced as crafting a perfect cheese soufflé, although with less risk of collapsing under pressure.

The Spearman correlation coefficient was employed to examine the strength and direction of the association between American cheese consumption and TT's stock price, taking into account potential non-linear relationships that traditional correlation measures might overlook. The analysis aimed to melt away any doubts about the significance of this relationship, much like a warm cheese fondue on a cold winter's night.

To assess the statistical significance of the findings, a hypothesis test was conducted with a null hypothesis stating no relationship between American cheese consumption and TT's stock price. The p-value obtained from this test allowed for a robust conclusion regarding the presence or absence of a meaningful association, demonstrating that the impact of cheese on financial markets is not just a mere fondue-m of imagination.

In conclusion, the methodology employed in this study combined rigorous statistical techniques with a light sprinkling of cheesiness to uncover the surprising connection between American cheese consumption and Trane Technologies' stock price. The resulting analysis provides a feta-bulous insight into the uncharted potential of dairy products to influence financial markets, albeit with the occasional cliche dad joke to ensure the research remains gouda-natured throughout.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between American cheese consumption and Trane Technologies' stock price (TT). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
Feta or Cheddar, TT Gets Better: The Whey to Wealth Connection Between American Cheese Consumption and Trane Technologies' Stock Price

[[ABSTRACT]]
This paper examines the relationship between American cheese consumption and the stock price of Trane Technologies (TT) from 2002 to 2021. We hypothesized that the consumption of American cheese, a beloved staple in many households, may have an impact on the financial performance of Trane Technologies, a global leader in climate technology. Our research team used data from the USDA and LSEG Analytics (Refinitiv) to assess this curious correlation. Surprisingly, we found a strong positive correlation coefficient of 0.9022704 and p < 0.01, indicating a robust association between American cheese consumption and TT's stock price.

It seems that the old adage "buy low, sell high" could be updated to "grate more, accumulate more." Our findings suggest that as American cheese consumption rises, so does the stock price of Trane Technologies. Perhaps this phenomenon can be attributed to the comforting nature of cheese, leading to increased investor confidence and a "gouda" feeling about TT's prospects.

This research sheds light on the unexplored synergies between dairy products and financial markets, offering a new perspective on the interconnectedness of seemingly unrelated sectors. So, next time you enjoy a cheesy snack, remember that you might be inadvertently contributing to the prosperity of a climate technology company.

[[LITERATURE REVIEW]]
Several studies have investigated the relationship between various consumer goods and stock prices, shedding light on the potential impacts of everyday consumption habits on financial markets. In "Smith et al.," the authors find that chocolate consumption is positively correlated with the performance of confectionery companies, while in "Doe and Jones," the authors examine the influence of coffee consumption on the stock prices of multinational coffee chains. These studies demonstrate the significance of consumer behaviors in shaping stock market dynamics.
Now, turning to the broader literature related to food and finance, "The Omnivore's Dilemma" by Michael Pollan and "Fast Food Nation" by Eric Schlosser illuminate the complex interplay between food production, consumption, and financial interests. On a more fictional note, the novels "American Psycho" by Bret Easton Ellis and "The Bonfire of the Vanities" by Tom Wolfe offer satirical perspectives on the excesses of Wall Street and consumer culture.
Expanding our review further, we must acknowledge the unconventional sources of insight that have contributed to our understanding of this peculiar correlation. While we did not encounter any scholarly work specifically on American cheese consumption and stock prices, an in-depth analysis of grocery store receipts, particularly those from local supermarkets and patisseries, provided anecdotal evidence of a potential linkage between cheese-related purchases and financial market trends.
In addition, the meticulous scrutiny of random internet forums and the analysis of whimsical theories put forth by self-proclaimed "investment gurus" on social media platforms have undoubtedly added a layer of "provolone" to our investigation. While not methodologically rigorous, these unconventional sources have contributed to the breadth of our inquiry, reminding us of the importance of exploring diverse perspectives, no matter how unconventional they may appear.
In summary, the existing literature has provided valuable insights into the complex relationship between consumer behavior and stock market performance, with a significant gap in the specific analysis of American cheese consumption and its impact on Trane Technologies' stock price. The diversity of sources consulted, ranging from reputable academic studies to whimsical musings, has enriched the scope of our inquiry and expanded the horizons of our investigation, demonstrating the need for interdisciplinary approaches in exploring unexpected connections in the world of finance.

[[RESULTS]]
The examination of data from 2002 to 2021 revealed a strong positive correlation between American cheese consumption and Trane Technologies' stock price (TT). The correlation coefficient of 0.9022704 suggests a robust association between these seemingly unrelated variables. This finding is quite grate news for those who enjoy indulging in a cheesy snack while keeping an eye on their investment portfolio. It appears that the saying "cheddar makes everything better" extends to stock prices as well.
The r-squared value of 0.8140919 indicates that approximately 81.41% of the variability in TT's stock price can be explained by changes in American cheese consumption. This suggests a remarkably high degree of predictability in the stock price based on the fluctuations in cheese consumption. It seems that the more American cheese that finds its way onto sandwiches and burgers, the more Trane Technologies' stock price matures like a fine cheddar.
The p-value of less than 0.01 further strengthens the evidence of a significant relationship between these two variables. The probability of observing such a strong correlation by chance is as low as finding a needle in a haystack made entirely of cheese. This result provides compelling support for the hypothesis that American cheese consumption and TT's stock price are indeed intertwined.
Fig. 1 depicts the scatterplot illustrating the clear positive correlation between American cheese consumption and Trane Technologies' stock price. As American cheese consumption increases, the stock price of TT tends to follow suit, creating a pattern that is as noticeable as a bright orange cheese slice on a platter of crackers.
In conclusion, this research not only adds a layer of provolone to the traditional understanding of financial market dynamics but also emphasizes the potential impact of unexpected factors, such as American cheese consumption, on stock prices. It appears that the age-old investment advice should be updated to "buy cheese, sell with ease." This research serves as a reminder that even in the world of finance, the power of cheese should not be underestimated.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study have strikingly reinforced the prior research examining the influence of consumer consumption habits on stock market dynamics. As predicted in "Smith et al.," where chocolate consumption was found to positively correlate with confectionery company performance, our findings extol a similar tune with American cheese consumption and Trane Technologies' stock price. It appears that the saying "too gouda to be true" does not apply in this case, as the correlation is undeniably robust.

In a similar vein, the insights from "Doe and Jones" regarding the impact of coffee consumption on multinational coffee chains' stock prices find a parallel in our study. It seems that while coffee may provide the daily jolt for many, American cheese could be the subtle yet influential force shaping the rise of Trane Technologies' stock price.

While our investigation may seem unorthodox considering the whimsical theories from unconventional sources, including grocery store receipts and self-proclaimed "investment gurus," the unexpected connections uncovered between American cheese consumption and TT's stock price cannot be dismissed as mere "cheese dreams." Our study has lent credence to these seemingly fanciful notions, emphasizing the need to take these unorthodox perspectives seriously.

The impressive correlation coefficient of 0.9022704 and the high explanatory power indicated by the r-squared value of 0.8140919 provide compelling evidence of the substantial association between American cheese consumption and Trane Technologies' stock price. It seems that the more cheese enthusiasts embrace their dairy delight, the more the stock price of TT matures like a fine cheddar, echoing the sentiment that "cheddar makes everything better," even in the domain of finance.

The p-value of less than 0.01 further solidifies the robustness of the relationship, akin to finding a rare gouda among a sea of ordinary cheeses. These statistical findings underscore the significance of the unexpected connection between American cheese consumption and TT's stock price, warranting serious attention in the realm of financial market analyses.

In light of our results, the age-old adage "buy low, sell high" may need to be rephrased as "grate more, accumulate more" for those eyeing the movement of Trane Technologies' stock price. This finding implies a newfound perspective on investment strategies, where keeping an eye on American cheese consumption patterns might just provide the edge required for informed investment decisions.

In conclusion, this research highlights the need to take unconventional correlations seriously and recognizes the interplay between seemingly disparate elements in financial market dynamics. The unexpected influence of American cheese consumption on Trane Technologies' stock price serves as a reminder that in the economic and financial domain, one must always expect the unexpected, and the power of cheese should not be overlooked. After all, as the saying goes, "in queso emergency, expect the unexpected!"

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between American cheese consumption and Trane Technologies' stock price (TT). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Feta or Cheddar, TT Gets Better: The Whey to Wealth Connection Between American Cheese Consumption and Trane Technologies' Stock Price

[[ABSTRACT]]
This paper examines the relationship between American cheese consumption and the stock price of Trane Technologies (TT) from 2002 to 2021. We hypothesized that the consumption of American cheese, a beloved staple in many households, may have an impact on the financial performance of Trane Technologies, a global leader in climate technology. Our research team used data from the USDA and LSEG Analytics (Refinitiv) to assess this curious correlation. Surprisingly, we found a strong positive correlation coefficient of 0.9022704 and p < 0.01, indicating a robust association between American cheese consumption and TT's stock price.

It seems that the old adage "buy low, sell high" could be updated to "grate more, accumulate more." Our findings suggest that as American cheese consumption rises, so does the stock price of Trane Technologies. Perhaps this phenomenon can be attributed to the comforting nature of cheese, leading to increased investor confidence and a "gouda" feeling about TT's prospects.

This research sheds light on the unexplored synergies between dairy products and financial markets, offering a new perspective on the interconnectedness of seemingly unrelated sectors. So, next time you enjoy a cheesy snack, remember that you might be inadvertently contributing to the prosperity of a climate technology company.

[[INTRDUCTION]]
The intersection of finance and dairy may seem as unusual as pairing blue cheese with chocolate, but our investigation into the relationship between American cheese consumption and the stock price of Trane Technologies (TT) suggests otherwise. As the saying goes, "Don't put all your eggs in one basket," but what about putting all your cheese in one portfolio? (I can hear the groans already!)
In the world of finance, various factors drive stock price movements, and it’s often a brie-lliant task to discern the hidden correlations. However, our study aims to gouda-n the missing link between a beloved household dairy product and the financial performance of a juggernaut in the climate technology industry. The stakes are high, but can we say the same about the curds? (Pun intended, of course!)
Cheese is renowned for its ability to enhance the flavor of a dish, but could it also enhance the flavor of an investment portfolio? Our paper aims to provoke such thought-provolone ideas. (You see what I did there?) By examining data from 2002 to 2021, we dive into the cheddar-ting world of statistical analysis to investigate the whey in which American cheese consumption impacts TT's stock price.
This study not only offers a novel perspective on the dynamics of financial markets and consumer behavior, but it also stands as a testament to the vaste potential for unearthing unexpected interactions between disparate industries. After all, who would have thought that the cheese on your grilled cheese sandwich might hold the secret to investment success? (Cheesy, I know!)

[[RESULTS]]
The examination of data from 2002 to 2021 revealed a strong positive correlation between American cheese consumption and Trane Technologies' stock price (TT). The correlation coefficient of 0.9022704 suggests a robust association between these seemingly unrelated variables. This finding is quite grate news for those who enjoy indulging in a cheesy snack while keeping an eye on their investment portfolio. It appears that the saying "cheddar makes everything better" extends to stock prices as well.
The r-squared value of 0.8140919 indicates that approximately 81.41% of the variability in TT's stock price can be explained by changes in American cheese consumption. This suggests a remarkably high degree of predictability in the stock price based on the fluctuations in cheese consumption. It seems that the more American cheese that finds its way onto sandwiches and burgers, the more Trane Technologies' stock price matures like a fine cheddar.
The p-value of less than 0.01 further strengthens the evidence of a significant relationship between these two variables. The probability of observing such a strong correlation by chance is as low as finding a needle in a haystack made entirely of cheese. This result provides compelling support for the hypothesis that American cheese consumption and TT's stock price are indeed intertwined.
Fig. 1 depicts the scatterplot illustrating the clear positive correlation between American cheese consumption and Trane Technologies' stock price. As American cheese consumption increases, the stock price of TT tends to follow suit, creating a pattern that is as noticeable as a bright orange cheese slice on a platter of crackers.
In conclusion, this research not only adds a layer of provolone to the traditional understanding of financial market dynamics but also emphasizes the potential impact of unexpected factors, such as American cheese consumption, on stock prices. It appears that the age-old investment advice should be updated to "buy cheese, sell with ease." This research serves as a reminder that even in the world of finance, the power of cheese should not be underestimated.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, this research unraveled the surprising connection between American cheese consumption and the stock price of Trane Technologies (TT). The findings suggest that as American cheese consumption rises, so does TT's stock price, proving that "cheddar makes everything better," including investment portfolios. This phenomenon may be attributed to the "grate" impact of cheese on investor confidence, demonstrating that the market is not as "gouda" as it seems.

This study highlights the need to "brie" open to unconventional factors that may influence stock prices, reminding investors not to overlook the potential impact of dairy products on financial markets. It's as though the market operates on the principle of "say cheese, and smile all the way to the bank." (Yes, the pun was intentional!)

The outstandingly high correlation coefficient and r-squared value indicate a strong relationship between American cheese consumption and TT's stock price, suggesting that nearly 81.41% of stock price variability can be explained by changes in cheese consumption. It's almost as predictable as the likelihood of finding cheese at a wine tasting event!

Further research in this area may delve into the specific types of American cheese that have the most pronounced effect on TT's stock price – after all, not all cheeses are created equal, and the market may have a preference for certain "grate" varieties. However, it is safe to say that when it comes to American cheese and TT's stock price, the evidence is as solid as a block of aged cheddar.

Therefore, based on the compelling findings of this study, it can be confidently asserted that no further research is needed in this area. The relationship between American cheese consumption and Trane Technologies' stock price has been "whey" more than established, and it's time to "brie"lieve in the power of cheese in the financial market.

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 Feta or Cheddar, TT Gets Better: The Whey to Wealth Connection Between American Cheese Consumption and Trane Technologies' Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Dairy Economics and Financial Analysis

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 Feta or Cheddar, TT Gets Better: The Whey to Wealth Connection Between American Cheese Consumption and Trane Technologies' Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Consortium for Dairy Economics and Stock Price Forecasting

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 Feta or Cheddar, TT Gets Better: The Whey to Wealth Connection Between American Cheese Consumption and Trane Technologies' Stock Price with an abstract of This paper examines the relationship between American cheese consumption and the stock price of Trane Technologies (TT) from 2002 to 2021. We hypothesized that the consumption of American cheese, a beloved staple in many households, may have an impact on the financial performance of Trane Technologies, a global leader in climate technology. Our research team used data from the USDA and LSEG Analytics (Refinitiv) to assess this curious correlation. Surprisingly, we found a strong positive correlation coefficient of 0.9022704 and p < 0.01, indicating a robust association between American cheese consumption and TT's stock price.
It seems that the old adage "buy low, sell high" could be updated to "grate more, accumulate more." Our findings suggest that as American cheese consumption rises, so does the stock price of Trane Technologies. Perhaps this phenomenon can be attributed to the comforting nature of cheese, leading to increased investor confidence and a "gouda" feeling about TT's prospects.
This research sheds light on the unexplored synergies between dairy products and financial markets, offering a new perspective on the interconnectedness of seemingly unrelated sectors. So, next time you enjoy a cheesy snack, remember that you might be inadvertently contributing to the prosperity of a climate technology company.

ChatGPT:

American cheese consumption, Trane Technologies stock price, correlation, dairy products, financial markets, USDA data, LSEG Analytics, Refinitiv, cheese consumption and stock price, investment strategies, climate technology company, interconnectedness of sectors, investor confidence

*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

Trane Technologies' stock price (TT)
Detailed data title: Opening price of Trane Technologies (TT) 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 Trane Technologies' stock price (TT)

Correlation r = 0.9022704 (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 = 0.8140919 (Coefficient of determination)
This means 81.4% of the change in the one variable (i.e., Trane Technologies' stock price (TT)) is predictable based on the change in the other (i.e., American cheese consumption) over the 20 years from 2002 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.4E-8.^Show 0.0000000539243397353271800000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.9 in 5.4E-6% of random cases. Said differently, if you correlated 18,544,502 random variables^Note You don't actually need 18 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

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

[ 0.77, 0.96 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
American cheese consumption (Pounds per person)	12.8314	12.5619	12.8612	12.649	13.0656	12.7929	13.1306	13.3553	13.3048	13.0392	13.2569	13.3573	13.6656	14.0444	14.3621	15.0901	15.4027	15.5389	15.5	16.1
Trane Technologies' stock price (TT) (Stock price)	13.07	13.47	20.66	24.92	25	24.43	28.75	10.97	22.29	29.39	19.34	30.64	47.52	49.25	42.2	58.81	69.61	69.71	103.43	144.09

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([12.8314,12.5619,12.8612,12.649,13.0656,12.7929,13.1306,13.3553,13.3048,13.0392,13.2569,13.3573,13.6656,14.0444,14.3621,15.0901,15.4027,15.5389,15.5,16.1,])
array_2 = np.array([13.07,13.47,20.66,24.92,25,24.43,28.75,10.97,22.29,29.39,19.34,30.64,47.52,49.25,42.2,58.81,69.61,69.71,103.43,144.09,])
array_1_name = "American cheese consumption"
array_2_name = "Trane Technologies' stock price (TT)"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only American cheese consumption
Line chart for only Trane Technologies' stock price (TT)
AI-generated correlation image
The spurious research paper: Feta or Cheddar, TT Gets Better: The Whey to Wealth Connection Between American Cheese Consumption and Trane Technologies' Stock Price

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Correlation ID: 3282 · Black Variable ID: 553 · Red Variable ID: 1750


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