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Spurious correlation #3,044 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of Breweries in the United States and the second variable is Monster Beverage's stock price (MNST).  The chart goes from 2002 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the number of breweries in the United States hops up, there's a corresponding spike in demand for specialty and craft beers. This leads to a surge in the consumption of hoppy, malted beverages. As more people ale out, they're searching for unique and energizing drinks to lager their spirits. This shift in drinking preferences creates a monster of a situation for the beverage industry, as it prompts a booming interest in Monster Beverage's products. It seems the competition is getting lager, but for Monster Beverage, it's a stout reminder that when it comes to quenching modern thirsts, they're the real ale.

Model: dalle-3
Prompt: [A photo-realistic image] Show a bustling street in the United States, lined with numerous brewery signs, with people walking on the sidewalk and cars driving along the road. Additionally, include a large price tag soaring upwards on a bottle of hops and barley, symbolizing the increased demand and higher prices for ingredients. In the background, depict the stock price chart of Monster Beverage (MNST) as a rising, frothy wave, reflecting the surge in their stock price due to the brewing ingredients' price hike. 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: The number of Breweries in the United States and Monster Beverage's stock price (MNST). 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 photo-realistic image An image that looks like it is a scene from A Disney Movie Hyper-realistic Voxel art a funny image macro
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 The number of Breweries in the United States and Monster Beverage's stock price (MNST), in the following situation: As the number of breweries in the US increased, so did the demand for hops and barley, leading to higher prices for Monster Beverage's ingredients. This caused their stock price to brew up a storm and hop right on up!. Keep the description simple.
ChatGPT: A bustling street in the United States, with numerous brewery signs lining the road, indicating the increasing number of breweries in the country. Alongside, a large price tag is shown soaring upwards on a bottle of hops and barley, symbolizing the increased demand and higher prices for ingredients. In the background, the stock price chart of Monster Beverage (MNST) is depicted as a rising, frothy wave, reflecting the surge in their stock price due to the brewing ingredients' price hike.

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: A bustling street in the United States, with numerous brewery signs lining the road, indicating the increasing number of breweries in the country. Alongside, a large price tag is shown soaring upwards on a bottle of hops and barley, symbolizing the increased demand and higher prices for ingredients. In the background, the stock price chart of Monster Beverage (MNST) is depicted as a rising, frothy wave, reflecting the surge in their stock price due to the brewing ingredients' price hike. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [A photo-realistic image] Show a bustling street in the United States, lined with numerous brewery signs, with people walking on the sidewalk and cars driving along the road. Additionally, include a large price tag soaring upwards on a bottle of hops and barley, symbolizing the increased demand and higher prices for ingredients. In the background, depict the stock price chart of Monster Beverage (MNST) as a rising, frothy wave, reflecting the surge in their stock price due to the brewing ingredients' price hike.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in The number of Breweries in the United States caused Monster Beverage's stock price (MNST) to increase. Include one good pun.

AI academic paper

(Because p < 0.01)
Brewing Up Stock: The Ale-urement of Breweries in the United States and Monster Beverage's Stock Price

Journal of Fermentation Finance

Jan 2024

Reminder: This paper is AI-generated. Not real!
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Monster Beverage's stock price (MNST). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Make the title punny if you can come up with clever pun. If not, make it sound serious.

Your research team used data from Brewers Association and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9687541 and p < 0.01 for 2002 to 2022.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Brewing Up Stock: The Ale-urement of Breweries in the United States and Monster Beverage's Stock Price

[[ABSTRACT]]
This study investigates the frothy relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST), exploring the potential ale-urements and impacts on investment decision ale-rtness. Utilizing data from the Brewers Association and LSEG Analytics (Refinitiv), our analysis covers the period from 2002 to 2022, imbuing both statistical rigor and hoppy humor. The results reveal a striking correlation coefficient of 0.9687541 and a p-value less than 0.01, suggesting a significant and robust relationship. As we delve into the foam of statistical significance, the findings brew a compelling narrative merging craft beer culture and financial market dynamics. It seems that when it comes to the stock market, the hops and barley may not be the only things bubbling. This research offers a refreshing perspective on the intersection of beverage industries and financial markets, hop-ing to stimulate further interest in this unconventional but statistically significant relationship.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Monster Beverage's stock price (MNST). 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.

Here is the title and abstract of the paper:
[[TITLE]]
Brewing Up Stock: The Ale-urement of Breweries in the United States and Monster Beverage's Stock Price

[[ABSTRACT]]
This study investigates the frothy relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST), exploring the potential ale-urements and impacts on investment decision ale-rtness. Utilizing data from the Brewers Association and LSEG Analytics (Refinitiv), our analysis covers the period from 2002 to 2022, imbuing both statistical rigor and hoppy humor. The results reveal a striking correlation coefficient of 0.9687541 and a p-value less than 0.01, suggesting a significant and robust relationship. As we delve into the foam of statistical significance, the findings brew a compelling narrative merging craft beer culture and financial market dynamics. It seems that when it comes to the stock market, the hops and barley may not be the only things bubbling. This research offers a refreshing perspective on the intersection of beverage industries and financial markets, hop-ing to stimulate further interest in this unconventional but statistically significant relationship.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

As the saying goes, "Time flies when you're having pun!" In the world of finance and investment, finding unique and unexpected connections between seemingly unrelated variables can be as refreshing as a crisp, cold beer on a hot summer day. The aroma of statistical significance and the bouquet of market dynamics often collide to produce findings that are both enlightening and entertaining. In this study, we set out to froth up the financial research field by investigating the relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST). So grab a cold one and prepare yourself for a brew-tiful journey through statistics and finance!

Much like the blend of barley, hops, yeast, and water that comes together to create a flavorful brew, our investigation brews together data from the Brewers Association and LSEG Analytics (Refinitiv) to concoct a potion that merges the world of craft beer with the realm of financial markets. We aim to tap into the ale-urement of breweries and its potential impacts on the market's thirst for Monster Beverage's stock. As we embark on this unconventional exploration, we can't help but wonder: what's a statistician's favorite type of beer? A brew-sky!

Our investigation covers the period from 2002 to 2022, providing a comprehensive look at the historical trends and fluctuations in both the craft beer industry and Monster Beverage's stock performance. Using rigorous statistical techniques, we aim to pour over the data with precision and a keen eye for detecting any signs of a bubbly relationship between these variables. As we navigate through the complexities of financial data, we'll be sure to keep our spirits high and our jokes flowing – after all, laughter is the hoppiest medicine!

So, why did the statistician's experiment lead him to the local brewery? It was time for a pint of statistical significance! In the spirit of both good science and good cheer, let's raise a glass to the adventure ahead and see what effervescent discoveries await us in the ever-enthralling intersection of craft brewing and stock market dynamics. Cheers to uncovering ale-uring insights and brew-tiful correlations!


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 The number of Breweries in the United States and Monster Beverage's stock price (MNST). 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 the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
Brewing Up Stock: The Ale-urement of Breweries in the United States and Monster Beverage's Stock Price

[[ABSTRACT]]
This study investigates the frothy relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST), exploring the potential ale-urements and impacts on investment decision ale-rtness. Utilizing data from the Brewers Association and LSEG Analytics (Refinitiv), our analysis covers the period from 2002 to 2022, imbuing both statistical rigor and hoppy humor. The results reveal a striking correlation coefficient of 0.9687541 and a p-value less than 0.01, suggesting a significant and robust relationship. As we delve into the foam of statistical significance, the findings brew a compelling narrative merging craft beer culture and financial market dynamics. It seems that when it comes to the stock market, the hops and barley may not be the only things bubbling. This research offers a refreshing perspective on the intersection of beverage industries and financial markets, hop-ing to stimulate further interest in this unconventional but statistically significant relationship.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As the saying goes, "Time flies when you're having pun!" In the world of finance and investment, finding unique and unexpected connections between seemingly unrelated variables can be as refreshing as a crisp, cold beer on a hot summer day. The aroma of statistical significance and the bouquet of market dynamics often collide to produce findings that are both enlightening and entertaining. In this study, we set out to froth up the financial research field by investigating the relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST). So grab a cold one and prepare yourself for a brew-tiful journey through statistics and finance!
Much like the blend of barley, hops, yeast, and water that comes together to create a flavorful brew, our investigation brews together data from the Brewers Association and LSEG Analytics (Refinitiv) to concoct a potion that merges the world of craft beer with the realm of financial markets. We aim to tap into the ale-urement of breweries and its potential impacts on the market's thirst for Monster Beverage's stock. As we embark on this unconventional exploration, we can't help but wonder: what's a statistician's favorite type of beer? A brew-sky!

Our investigation covers the period from 2002 to 2022, providing a comprehensive look at the historical trends and fluctuations in both the craft beer industry and Monster Beverage's stock performance. Using rigorous statistical techniques, we aim to pour over the data with precision and a keen eye for detecting any signs of a bubbly relationship between these variables. As we navigate through the complexities of financial data, we'll be sure to keep our spirits high and our jokes flowing – after all, laughter is the hoppiest medicine!
So, why did the statistician's experiment lead him to the local brewery? It was time for a pint of statistical significance! In the spirit of both good science and good cheer, let's raise a glass to the adventure ahead and see what effervescent discoveries await us in the ever-enthralling intersection of craft brewing and stock market dynamics. Cheers to uncovering ale-uring insights and brew-tiful correlations!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Our exploration of the relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST) unfolds against the backdrop of a complex and multifaceted financial landscape. The literature on this entwined conundrum has yielded insights that range from the statistical to the sudsy, and we aim to traverse this diverse terrain with both rigor and a dash of frothy humor.

In "The Economics of Beer," Smith et al. delve into the economic impact of the brewing industry, revealing the substantial contributions it makes to both local and national economies. The authors find that the proliferation of craft breweries has sparked interest from investors and enthusiasts alike, creating a flourishing ecosystem that extends beyond the realm of beer connoisseurship. As the authors note, the allure of craft beer is not just about taste – it's also about tapping into a compelling investment arena. Speaking of tapping, why did the statistical analyst go to the brewery? To measure the hops and barley, of course!

Doe's "Financial Forecasting: A Comprehensive Guide" sheds light on the intricate blend of factors that influence stock prices, offering illuminating perspectives on the complexities of market dynamics. Their analysis uncovers the interplay of supply and demand, investor sentiment, and industry trends, providing a robust framework for understanding the nuances of stock valuation. Yet, amidst this sea of quantitative rigor, we cannot help but appreciate the simple pleasure of a well-crafted pun. After all, what do you get when you mix a financial analyst with a brewer? A balanced portfolio and a well-rounded beer selection!

Jones et al.'s "Beeronomics: How Beer Explains the World" delves into the cultural and social dimensions of the brewing industry, highlighting its ability to mirror and influence societal trends. Their narrative weaves together historical anecdotes, market analysis, and behavioral economics, painting a vivid portrait of beer's enduring relevance in human affairs. In this interconnected tapestry, the rise of craft breweries emerges as a testament to entrepreneurial spirit and consumer demand, adding a delightful fizz to the ever-expanding landscape of culinary creativity. But enough about the serious literature - let's hop over to some fictional works for a moment.

In "Microbrew Murder: A Frothy Mystery" by Ale Vera-Cruz, the protagonist uncovers a nefarious plot to manipulate stock prices through the subversive influence of a secret beer recipe. While we don't anticipate encountering any criminal masterminds in our investigation, the tale serves as a reminder of the captivating allure of both financial intrigues and fermented beverages. Speaking of captivating, did you hear about the beer that always had the last word in an argument? It was a real know-it-ale!

As we venture deeper into the frothy realms of literature, we cannot neglect the valuable insights gleaned from less traditional sources. From the whimsical musings of "Brewing Alchemy: A Witch's Guide to Potions and Pints" to the bountiful knowledge found in the backs of shampoo bottles (which, we assure you, have no relation to stock prices), our intellectual foray takes us to unexpected and unconventional destinations. Embracing the spirit of serendipity and scholarly curiosity, we imbibe the ale-uring essence of discovery, infusing our research with both levity and scholarly depth. So, without further ado, let's raise a glass to the delightful absurdity of academic pursuits and the truly diverse spectrum of knowledge that shapes our understanding of the world. Here's to statistical significance and the unrelenting quest for knowledge, one brew-tiful pun at a time! Cheers!


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 The number of Breweries in the United States and Monster Beverage's stock price (MNST). 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 Brewers Association and LSEG Analytics (Refinitiv) . You used data from 2002 to 2022

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]]
Brewing Up Stock: The Ale-urement of Breweries in the United States and Monster Beverage's Stock Price

[[ABSTRACT]]
This study investigates the frothy relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST), exploring the potential ale-urements and impacts on investment decision ale-rtness. Utilizing data from the Brewers Association and LSEG Analytics (Refinitiv), our analysis covers the period from 2002 to 2022, imbuing both statistical rigor and hoppy humor. The results reveal a striking correlation coefficient of 0.9687541 and a p-value less than 0.01, suggesting a significant and robust relationship. As we delve into the foam of statistical significance, the findings brew a compelling narrative merging craft beer culture and financial market dynamics. It seems that when it comes to the stock market, the hops and barley may not be the only things bubbling. This research offers a refreshing perspective on the intersection of beverage industries and financial markets, hop-ing to stimulate further interest in this unconventional but statistically significant relationship.

[[INTRODUCTION]]
As the saying goes, "Time flies when you're having pun!" In the world of finance and investment, finding unique and unexpected connections between seemingly unrelated variables can be as refreshing as a crisp, cold beer on a hot summer day. The aroma of statistical significance and the bouquet of market dynamics often collide to produce findings that are both enlightening and entertaining. In this study, we set out to froth up the financial research field by investigating the relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST). So grab a cold one and prepare yourself for a brew-tiful journey through statistics and finance!
Much like the blend of barley, hops, yeast, and water that comes together to create a flavorful brew, our investigation brews together data from the Brewers Association and LSEG Analytics (Refinitiv) to concoct a potion that merges the world of craft beer with the realm of financial markets. We aim to tap into the ale-urement of breweries and its potential impacts on the market's thirst for Monster Beverage's stock. As we embark on this unconventional exploration, we can't help but wonder: what's a statistician's favorite type of beer? A brew-sky!

Our investigation covers the period from 2002 to 2022, providing a comprehensive look at the historical trends and fluctuations in both the craft beer industry and Monster Beverage's stock performance. Using rigorous statistical techniques, we aim to pour over the data with precision and a keen eye for detecting any signs of a bubbly relationship between these variables. As we navigate through the complexities of financial data, we'll be sure to keep our spirits high and our jokes flowing – after all, laughter is the hoppiest medicine!
So, why did the statistician's experiment lead him to the local brewery? It was time for a pint of statistical significance! In the spirit of both good science and good cheer, let's raise a glass to the adventure ahead and see what effervescent discoveries await us in the ever-enthralling intersection of craft brewing and stock market dynamics. Cheers to uncovering ale-uring insights and brew-tiful correlations!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To ferment the findings of our study, we utilized a hop-forward approach that combined quantitative data analysis with a dash of whimsy. Our research team embarked on a quest for data, scouring the vast expanse of the internet with the vigor of beer enthusiasts on a brewery tour. Our primary sources of data were the Brewers Association and LSEG Analytics (Refinitiv), forming a symbiotic relationship between craft beer statistics and financial market data. It's safe to say that we had a real "ale-lotment" of data to work with!

With the collected data covering the period from 2002 to 2022, we harnessed the power of statistical tools that could put even the most seasoned brewmaster's precision to shame. Our stout-y statistical techniques included correlation analysis, regression modeling, and time series analysis. We utilized these methods to distill the essence of the relationship between the number of breweries in the United States and Monster Beverage's stock price, brewing up a statistical froth that's sure to leave a mark in the annals of financial research.

Buoyed by the spirit of experimentation, we ventured into the realm of quantitative inquiry with a fervor that could rival a brewer's dedication to crafting the perfect ale. Our data analysis journey had more twists and turns than a labyrinthine beer garden, but with each statistical avenue explored, we seasoned our findings with a sprinkle of humor and a dash of irreverence. After all, what's a research paper without a pint of puns and a splash of statistical wit?

As we delved into the brew-tilicious process of analyzing the data, we employed a robust statistical framework to tease out the nuances of the relationship between the number of breweries and Monster Beverage's stock price. Our statistical models were fine-tuned and calibrated with the precision of a master brewer honing the recipe for a flagship ale. We attempted to craft a narrative that mirrors the intricate dance of flavor profiles in a well-crafted brew – complete with an unexpected twist in the form of statistically significant findings.

Speaking of twists, did you hear about the statistician who drowned in a river with an average depth of five feet? He underestimated the power of statistical variability! In the unpredictable world of statistics, it's important to keep a watchful eye for unexpected outcomes, much like brewing a new batch of experimental beer. With a wink and a nod to the unpredictability of statistical analysis, we forged ahead with an inquisitive spirit and an arsenal of statistical tools at our disposal, ready to uncover the intriguing dynamics between the variables at play.

So, armed with our statistical alechemists' toolkit and a good measure of academic curiosity, we embarked on a methodology that blends the precision of advanced statistical techniques with a refreshing dose of lighthearted statistical banter. It's in this vibrant blend of hard data and statistical humor that we believe the most refreshing and insightful discoveries are made. So, whether you prefer a lager, ale, or stout, join us on this exhilarating statistical journey as we unlock the effervescent secrets hidden within the intertwining realms of craft brewing and stock market dynamics. Cheers to the frothy fusion of quantitative inquiry and statistical gaiety!


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 The number of Breweries in the United States and Monster Beverage's stock price (MNST). 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 Brewers Association and LSEG Analytics (Refinitiv) .

For the time period 2002 to 2022, you found a correlation 0.9687541, r-squared of 0.9384845, 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]]
Brewing Up Stock: The Ale-urement of Breweries in the United States and Monster Beverage's Stock Price

[[ABSTRACT]]
This study investigates the frothy relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST), exploring the potential ale-urements and impacts on investment decision ale-rtness. Utilizing data from the Brewers Association and LSEG Analytics (Refinitiv), our analysis covers the period from 2002 to 2022, imbuing both statistical rigor and hoppy humor. The results reveal a striking correlation coefficient of 0.9687541 and a p-value less than 0.01, suggesting a significant and robust relationship. As we delve into the foam of statistical significance, the findings brew a compelling narrative merging craft beer culture and financial market dynamics. It seems that when it comes to the stock market, the hops and barley may not be the only things bubbling. This research offers a refreshing perspective on the intersection of beverage industries and financial markets, hop-ing to stimulate further interest in this unconventional but statistically significant relationship.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
As the saying goes, "Time flies when you're having pun!" In the world of finance and investment, finding unique and unexpected connections between seemingly unrelated variables can be as refreshing as a crisp, cold beer on a hot summer day. The aroma of statistical significance and the bouquet of market dynamics often collide to produce findings that are both enlightening and entertaining. In this study, we set out to froth up the financial research field by investigating the relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST). So grab a cold one and prepare yourself for a brew-tiful journey through statistics and finance!
Much like the blend of barley, hops, yeast, and water that comes together to create a flavorful brew, our investigation brews together data from the Brewers Association and LSEG Analytics (Refinitiv) to concoct a potion that merges the world of craft beer with the realm of financial markets. We aim to tap into the ale-urement of breweries and its potential impacts on the market's thirst for Monster Beverage's stock. As we embark on this unconventional exploration, we can't help but wonder: what's a statistician's favorite type of beer? A brew-sky!

Our investigation covers the period from 2002 to 2022, providing a comprehensive look at the historical trends and fluctuations in both the craft beer industry and Monster Beverage's stock performance. Using rigorous statistical techniques, we aim to pour over the data with precision and a keen eye for detecting any signs of a bubbly relationship between these variables. As we navigate through the complexities of financial data, we'll be sure to keep our spirits high and our jokes flowing – after all, laughter is the hoppiest medicine!
So, why did the statistician's experiment lead him to the local brewery? It was time for a pint of statistical significance! In the spirit of both good science and good cheer, let's raise a glass to the adventure ahead and see what effervescent discoveries await us in the ever-enthralling intersection of craft brewing and stock market dynamics. Cheers to uncovering ale-uring insights and brew-tiful correlations!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The findings of our study reveal a remarkably strong and positive correlation between the number of breweries in the United States and Monster Beverage's stock price (MNST). The correlation coefficient of 0.9687541 indicates a robust relationship between these seemingly disparate variables. This result suggests that as the number of breweries in the United States increases, there is a hop-timistic impact on the stock price of Monster Beverage. It seems that the fermentation process inherent in craft brewing may also be at play in the dynamics of the stock market.

The r-squared value of 0.9384845 further emphasizes the strength of the relationship, indicating that approximately 93.85% of the variability in Monster Beverage's stock price can be explained by the number of breweries in the United States. This statistically significant relationship could be ale-arming for those invested in understanding the intricate connections between consumer preferences for craft beer and the financial performance of Monster Beverage.

Our analysis also yielded a p-value of less than 0.01, providing strong evidence against the null hypothesis of no relationship. This result further bolsters the notion that the number of breweries in the United States has a profound influence on Monster Beverage's stock price. It appears that the craft beer craze has extended beyond the taproom and into the realm of stock market valuation, creating a buzz of excitement in the world of financial research.

In Fig. 1, we present a scatterplot illustrating the striking correlation between the number of breweries in the United States and Monster Beverage's stock price. The data points form a pattern that is as clear as the appearance of a well-crafted craft beer, highlighting the compelling relationship uncovered in our analysis.

In conclusion, this research sheds light on the interconnectedness of the craft beer industry and the stock market, offering a flavorful perspective on the potential influences of consumer trends on investment opportunities. The findings of this study not only provide valuable insights for investors but also brew a refreshing narrative that intertwines statistical significance with the effervescence of craft brewing culture. It seems that in the world of finance, the stock market may be more susceptible to the hops and barley than previously thought. As the saying goes, "In hops we trust!"

So, what did one statistician say to the other over a couple of beers? "I've got my aleph-null eye on you!" This research, much like a well-crafted IPA, leaves us with a lingering aftertaste of joy and curiosity, inspiring further exploration at the intersection of consumer behavior and financial markets. Cheers to the exciting discoveries and the ale-urements that await future research endeavors in this brew-tiful domain!


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 The number of Breweries in the United States and Monster Beverage's stock price (MNST). 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]]
Brewing Up Stock: The Ale-urement of Breweries in the United States and Monster Beverage's Stock Price

[[ABSTRACT]]
This study investigates the frothy relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST), exploring the potential ale-urements and impacts on investment decision ale-rtness. Utilizing data from the Brewers Association and LSEG Analytics (Refinitiv), our analysis covers the period from 2002 to 2022, imbuing both statistical rigor and hoppy humor. The results reveal a striking correlation coefficient of 0.9687541 and a p-value less than 0.01, suggesting a significant and robust relationship. As we delve into the foam of statistical significance, the findings brew a compelling narrative merging craft beer culture and financial market dynamics. It seems that when it comes to the stock market, the hops and barley may not be the only things bubbling. This research offers a refreshing perspective on the intersection of beverage industries and financial markets, hop-ing to stimulate further interest in this unconventional but statistically significant relationship.

[[LITERATURE REVIEW]]
Our exploration of the relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST) unfolds against the backdrop of a complex and multifaceted financial landscape. The literature on this entwined conundrum has yielded insights that range from the statistical to the sudsy, and we aim to traverse this diverse terrain with both rigor and a dash of frothy humor.
In "The Economics of Beer," Smith et al. delve into the economic impact of the brewing industry, revealing the substantial contributions it makes to both local and national economies. The authors find that the proliferation of craft breweries has sparked interest from investors and enthusiasts alike, creating a flourishing ecosystem that extends beyond the realm of beer connoisseurship. As the authors note, the allure of craft beer is not just about taste – it's also about tapping into a compelling investment arena. Speaking of tapping, why did the statistical analyst go to the brewery? To measure the hops and barley, of course!
Doe's "Financial Forecasting: A Comprehensive Guide" sheds light on the intricate blend of factors that influence stock prices, offering illuminating perspectives on the complexities of market dynamics. Their analysis uncovers the interplay of supply and demand, investor sentiment, and industry trends, providing a robust framework for understanding the nuances of stock valuation. Yet, amidst this sea of quantitative rigor, we cannot help but appreciate the simple pleasure of a well-crafted pun. After all, what do you get when you mix a financial analyst with a brewer? A balanced portfolio and a well-rounded beer selection!
Jones et al.'s "Beeronomics: How Beer Explains the World" delves into the cultural and social dimensions of the brewing industry, highlighting its ability to mirror and influence societal trends. Their narrative weaves together historical anecdotes, market analysis, and behavioral economics, painting a vivid portrait of beer's enduring relevance in human affairs. In this interconnected tapestry, the rise of craft breweries emerges as a testament to entrepreneurial spirit and consumer demand, adding a delightful fizz to the ever-expanding landscape of culinary creativity. But enough about the serious literature - let's hop over to some fictional works for a moment.
In "Microbrew Murder: A Frothy Mystery" by Ale Vera-Cruz, the protagonist uncovers a nefarious plot to manipulate stock prices through the subversive influence of a secret beer recipe. While we don't anticipate encountering any criminal masterminds in our investigation, the tale serves as a reminder of the captivating allure of both financial intrigues and fermented beverages. Speaking of captivating, did you hear about the beer that always had the last word in an argument? It was a real know-it-ale!
As we venture deeper into the frothy realms of literature, we cannot neglect the valuable insights gleaned from less traditional sources. From the whimsical musings of "Brewing Alchemy: A Witch's Guide to Potions and Pints" to the bountiful knowledge found in the backs of shampoo bottles (which, we assure you, have no relation to stock prices), our intellectual foray takes us to unexpected and unconventional destinations. Embracing the spirit of serendipity and scholarly curiosity, we imbibe the ale-uring essence of discovery, infusing our research with both levity and scholarly depth. So, without further ado, let's raise a glass to the delightful absurdity of academic pursuits and the truly diverse spectrum of knowledge that shapes our understanding of the world. Here's to statistical significance and the unrelenting quest for knowledge, one brew-tiful pun at a time! Cheers!

[[RESULTS]]
The findings of our study reveal a remarkably strong and positive correlation between the number of breweries in the United States and Monster Beverage's stock price (MNST). The correlation coefficient of 0.9687541 indicates a robust relationship between these seemingly disparate variables. This result suggests that as the number of breweries in the United States increases, there is a hop-timistic impact on the stock price of Monster Beverage. It seems that the fermentation process inherent in craft brewing may also be at play in the dynamics of the stock market.
The r-squared value of 0.9384845 further emphasizes the strength of the relationship, indicating that approximately 93.85% of the variability in Monster Beverage's stock price can be explained by the number of breweries in the United States. This statistically significant relationship could be ale-arming for those invested in understanding the intricate connections between consumer preferences for craft beer and the financial performance of Monster Beverage.
Our analysis also yielded a p-value of less than 0.01, providing strong evidence against the null hypothesis of no relationship. This result further bolsters the notion that the number of breweries in the United States has a profound influence on Monster Beverage's stock price. It appears that the craft beer craze has extended beyond the taproom and into the realm of stock market valuation, creating a buzz of excitement in the world of financial research.
In Fig. 1, we present a scatterplot illustrating the striking correlation between the number of breweries in the United States and Monster Beverage's stock price. The data points form a pattern that is as clear as the appearance of a well-crafted craft beer, highlighting the compelling relationship uncovered in our analysis.
In conclusion, this research sheds light on the interconnectedness of the craft beer industry and the stock market, offering a flavorful perspective on the potential influences of consumer trends on investment opportunities. The findings of this study not only provide valuable insights for investors but also brew a refreshing narrative that intertwines statistical significance with the effervescence of craft brewing culture. It seems that in the world of finance, the stock market may be more susceptible to the hops and barley than previously thought. As the saying goes, "In hops we trust!"
So, what did one statistician say to the other over a couple of beers? "I've got my aleph-null eye on you!" This research, much like a well-crafted IPA, leaves us with a lingering aftertaste of joy and curiosity, inspiring further exploration at the intersection of consumer behavior and financial markets. Cheers to the exciting discoveries and the ale-urements that await future research endeavors in this brew-tiful domain!

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of this study confirm and expand upon prior research on the unexpected relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST), anchoring this frothy phenomenon in a sea of statistical significance. Our findings echo the insights of Smith et al., who highlighted the burgeoning economic impact of the brewery boom and its resonance in investment spheres. Indeed, the craft beer renaissance seems to have fermented not only a vibrant culture but also an unconventional link to stock market dynamics. It's a brew-tiful fusion of indulgence and investment, where hops and barley meet bull and bear markets.

Doe's "Financial Forecasting: A Comprehensive Guide" foretold the intricate tapestry of factors influencing stock prices, and our analysis corroborates the ale-arming effect of craft brewery proliferation on Monster Beverage's stock performance. The frothy allure of craft beer, it seems, can extend its effervescent charm to the stock market, creating a symphony of market movements that tantalizes both connoisseurs of beer and of financial markets. It's a blend as compelling as a stout with a touch of caramel - rich, complex, and unmistakably captivating.

Our study also supports Jones et al.'s exploration of the cultural and social dimensions of brewing, revealing how the rise of craft breweries mirrors and shapes consumer trends, and demonstrating how this influence extends to the valuation of Monster Beverage's stock. The subtleties of consumer preference, much like the nuances of a well-crafted ale, can send ripples through the financial seas, altering the course of stock prices in unanticipated ways.

The results of this investigation provide a refreshing perspective on the elusive intersection of consumer behavior and financial markets. Much like a perfect pint, the empirical evidence is rich in flavor and character, with a smooth finish that lingers in the palate of economic analysis. It's a study that demonstrates the real ale-urement of statistical exploration and the unexpected surprises that await those willing to venture into uncharted territories of research. So, here's to the fusion of brewed excellence and market prowess, and to the intriguing journey that lies ahead in this bubbling confluence of beer and finance! Cheers to the secrets and delights uncovered, one sip at a time.

In the realm of academia, brewing, and statistical significance, this research raises a glass to the joy of discovery, the frolic of puns, and the unyielding quest for deeper understanding. Here's to a future of findings that are as engaging as a lively pub debate and as robust as a well-aged barleywine. As researchers, we must keep our spirits high and our data-driven endeavors well-hopped. After all, it's not every day that statistics and stock prices come together in such an ale-uring fashion! Cheers to the insights unveiled and the ale-urements that beckon further exploration at the delicious crossroads of beer and financial markets.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 The number of Breweries in the United States and Monster Beverage's stock price (MNST). 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]]
Brewing Up Stock: The Ale-urement of Breweries in the United States and Monster Beverage's Stock Price

[[ABSTRACT]]
This study investigates the frothy relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST), exploring the potential ale-urements and impacts on investment decision ale-rtness. Utilizing data from the Brewers Association and LSEG Analytics (Refinitiv), our analysis covers the period from 2002 to 2022, imbuing both statistical rigor and hoppy humor. The results reveal a striking correlation coefficient of 0.9687541 and a p-value less than 0.01, suggesting a significant and robust relationship. As we delve into the foam of statistical significance, the findings brew a compelling narrative merging craft beer culture and financial market dynamics. It seems that when it comes to the stock market, the hops and barley may not be the only things bubbling. This research offers a refreshing perspective on the intersection of beverage industries and financial markets, hop-ing to stimulate further interest in this unconventional but statistically significant relationship.

[[INTRDUCTION]]
As the saying goes, "Time flies when you're having pun!" In the world of finance and investment, finding unique and unexpected connections between seemingly unrelated variables can be as refreshing as a crisp, cold beer on a hot summer day. The aroma of statistical significance and the bouquet of market dynamics often collide to produce findings that are both enlightening and entertaining. In this study, we set out to froth up the financial research field by investigating the relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST). So grab a cold one and prepare yourself for a brew-tiful journey through statistics and finance!
Much like the blend of barley, hops, yeast, and water that comes together to create a flavorful brew, our investigation brews together data from the Brewers Association and LSEG Analytics (Refinitiv) to concoct a potion that merges the world of craft beer with the realm of financial markets. We aim to tap into the ale-urement of breweries and its potential impacts on the market's thirst for Monster Beverage's stock. As we embark on this unconventional exploration, we can't help but wonder: what's a statistician's favorite type of beer? A brew-sky!

Our investigation covers the period from 2002 to 2022, providing a comprehensive look at the historical trends and fluctuations in both the craft beer industry and Monster Beverage's stock performance. Using rigorous statistical techniques, we aim to pour over the data with precision and a keen eye for detecting any signs of a bubbly relationship between these variables. As we navigate through the complexities of financial data, we'll be sure to keep our spirits high and our jokes flowing – after all, laughter is the hoppiest medicine!
So, why did the statistician's experiment lead him to the local brewery? It was time for a pint of statistical significance! In the spirit of both good science and good cheer, let's raise a glass to the adventure ahead and see what effervescent discoveries await us in the ever-enthralling intersection of craft brewing and stock market dynamics. Cheers to uncovering ale-uring insights and brew-tiful correlations!

[[RESULTS]]
The findings of our study reveal a remarkably strong and positive correlation between the number of breweries in the United States and Monster Beverage's stock price (MNST). The correlation coefficient of 0.9687541 indicates a robust relationship between these seemingly disparate variables. This result suggests that as the number of breweries in the United States increases, there is a hop-timistic impact on the stock price of Monster Beverage. It seems that the fermentation process inherent in craft brewing may also be at play in the dynamics of the stock market.
The r-squared value of 0.9384845 further emphasizes the strength of the relationship, indicating that approximately 93.85% of the variability in Monster Beverage's stock price can be explained by the number of breweries in the United States. This statistically significant relationship could be ale-arming for those invested in understanding the intricate connections between consumer preferences for craft beer and the financial performance of Monster Beverage.
Our analysis also yielded a p-value of less than 0.01, providing strong evidence against the null hypothesis of no relationship. This result further bolsters the notion that the number of breweries in the United States has a profound influence on Monster Beverage's stock price. It appears that the craft beer craze has extended beyond the taproom and into the realm of stock market valuation, creating a buzz of excitement in the world of financial research.
In Fig. 1, we present a scatterplot illustrating the striking correlation between the number of breweries in the United States and Monster Beverage's stock price. The data points form a pattern that is as clear as the appearance of a well-crafted craft beer, highlighting the compelling relationship uncovered in our analysis.
In conclusion, this research sheds light on the interconnectedness of the craft beer industry and the stock market, offering a flavorful perspective on the potential influences of consumer trends on investment opportunities. The findings of this study not only provide valuable insights for investors but also brew a refreshing narrative that intertwines statistical significance with the effervescence of craft brewing culture. It seems that in the world of finance, the stock market may be more susceptible to the hops and barley than previously thought. As the saying goes, "In hops we trust!"
So, what did one statistician say to the other over a couple of beers? "I've got my aleph-null eye on you!" This research, much like a well-crafted IPA, leaves us with a lingering aftertaste of joy and curiosity, inspiring further exploration at the intersection of consumer behavior and financial markets. Cheers to the exciting discoveries and the ale-urements that await future research endeavors in this brew-tiful domain!

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In wrapping up our findings, it's clear that the relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST) is as refreshing as a cold pint on a summer day. With a correlation coefficient of 0.9687541 and a p-value less than 0.01, the statistical evidence is stout and the implications are nothing to beer at! This connection is certainly something to hop about!

Our study has presented a compelling case for the influence of craft beer culture on the stock market, revealing a relationship that is as robust as a well-aged stout. The r-squared value of 0.9384845 confirms that approximately 93.85% of the variability in Monster Beverage's stock price can be attributed to the number of breweries in the United States. It seems the craft beer industry has ale-mented the financial market in ways we never quite brewed possible.

As we raise a glass to the insights unearthed in this research, it's evident that no more research is needed in this area. The findings are as clear as a filtered lager and as potent as a double IPA. This research, much like a fine brew, leaves a satisfying aftertaste and inspires us to savor the delights of statistical discovery. In the realm of beer and finance, it's safe to say that our study has tapped into the ultimate source of ale-urements. Cheers to that, and may your investments always be as hoppy as a well-balanced ale!


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 Brewing Up Stock: The Ale-urement of Breweries in the United States and Monster Beverage's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Fermentation 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 Brewing Up Stock: The Ale-urement of Breweries in the United States and Monster Beverage's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Fermentation Studies


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 Brewing Up Stock: The Ale-urement of Breweries in the United States and Monster Beverage's Stock Price with an abstract of This study investigates the frothy relationship between the number of breweries in the United States and Monster Beverage's stock price (MNST), exploring the potential ale-urements and impacts on investment decision ale-rtness. Utilizing data from the Brewers Association and LSEG Analytics (Refinitiv), our analysis covers the period from 2002 to 2022, imbuing both statistical rigor and hoppy humor. The results reveal a striking correlation coefficient of 0.9687541 and a p-value less than 0.01, suggesting a significant and robust relationship. As we delve into the foam of statistical significance, the findings brew a compelling narrative merging craft beer culture and financial market dynamics. It seems that when it comes to the stock market, the hops and barley may not be the only things bubbling. This research offers a refreshing perspective on the intersection of beverage industries and financial markets, hop-ing to stimulate further interest in this unconventional but statistically significant relationship.

ChatGPT:

Craft beer breweries, craft beer industry, beverage industry, stock market correlation, Monster Beverage stock price, Brewers Association data, LSEG Analytics, financial market dynamics, investment decisions, statistical significance, ale-urement, United States breweries, stock market impact

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



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Data details

The number of Breweries in the United States
Detailed data title: Number of Breweries in the United States
Source: Brewers Association
See what else correlates with The number of Breweries in the United States

Monster Beverage's stock price (MNST)
Detailed data title: Opening price of Monster Beverage (MNST) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function

See what else correlates with Monster Beverage's stock price (MNST)

Correlation r = 0.9687541 (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 = 0.9384845 (Coefficient of determination)
This means 93.8% of the change in the one variable (i.e., Monster Beverage's stock price (MNST)) is predictable based on the change in the other (i.e., The number of Breweries in the United States) over the 21 years from 2002 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.8E-13. 0.0000000000005816298165344983
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.97 in 5.8E-11% of random cases. Said differently, if you correlated 1,719,306,630,390 random variables You don't actually need 1 trillion 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 20 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 20 because we have two variables measured over a period of 21 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.

[ 0.92, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
200220032004200520062007200820092010201120122013201420152016201720182019202020212022
The number of Breweries in the United States (Number of breweries)157516291635161217411805189619332131252526703162401448475780676777228557909293849709
Monster Beverage's stock price (MNST) (Stock price)0.040.040.090.391.682.823.72.753.224.397.88.9511.3118.2324.4222.3331.724.2831.9846.2647.76




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([1575,1629,1635,1612,1741,1805,1896,1933,2131,2525,2670,3162,4014,4847,5780,6767,7722,8557,9092,9384,9709,])
array_2 = np.array([0.04,0.04,0.09,0.39,1.68,2.82,3.7,2.75,3.22,4.39,7.8,8.95,11.31,18.23,24.42,22.33,31.7,24.28,31.98,46.26,47.76,])
array_1_name = "The number of Breweries in the United States"
array_2_name = "Monster Beverage's stock price (MNST)"

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

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



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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. 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.

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Correlation ID: 3044 · Black Variable ID: 34 · Red Variable ID: 1703
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