Spurious correlation #3,094 · 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 CoStar Group's stock price (CSGP). The chart goes from 2002 to 2022, 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 The number of Breweries in the United States and the second variable is CoStar Group's stock price (CSGP). The chart goes from 2002 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of breweries in the United States increased, so did the demand for industrial real estate to house these hoppy enterprises. This surge in demand for warehouse and distribution space boosted CoStar Group's stock price as investors hop-ed on board, realizing the frothy potential for increased property listings and leasing activity. It's a ale-to-the-real estate boom that's lager than life, proving that when it comes to the stock market, the only thing that's on tap is success!

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image that looks like it is a scene from a Pixar movie, depicting a bustling city street with numerous colorful breweries, each adorned with distinct brewery signs and vibrant outdoor seating areas. People are visible, joyfully savoring beers, sharing laughs, and engaging in lively conversations. In the distance, a gigantic digital billboard displays a soaring stock graph of CoStar Group's stock price, with bright green arrows pointing upwards. The scene captures the vivacious ambiance of the breweries and the increasing demand for spacious offices, reflected in the ascending stock price of CoStar Group. 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 CoStar Group's stock price (CSGP). 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: Parallax art Glitch art Symbolism An image that looks like it is a scene from a Pixar movie Minimalism
ChatGPT: An image that looks like it is a scene from a Pixar movie

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both The number of Breweries in the United States and CoStar Group's stock price (CSGP), in the following situation: Because the increase in breweries in the US means more people getting hoppy, which leads to an increase in beer bellies. This increases the demand for larger office spaces, which CoStar Group provides data on, sending their stock soaring!. Keep the description simple.
ChatGPT: Imagine a bustling city street filled with numerous breweries, each with their distinct brewery signs and outdoor seating areas. People are seen enjoying beers, laughing, and socializing. In the background, a soaring stock graph of CoStar Group's stock price is displayed on a large digital billboard, with bright green arrows pointing upwards. The scene captures the lively atmosphere of the breweries and the growing demand for larger office spaces, as indicated by the rising stock price of CoStar Group.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: Imagine a bustling city street filled with numerous breweries, each with their distinct brewery signs and outdoor seating areas. People are seen enjoying beers, laughing, and socializing. In the background, a soaring stock graph of CoStar Group's stock price is displayed on a large digital billboard, with bright green arrows pointing upwards. The scene captures the lively atmosphere of the breweries and the growing demand for larger office spaces, as indicated by the rising stock price of CoStar Group. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image that looks like it is a scene from a Pixar movie, depicting a bustling city street with numerous colorful breweries, each adorned with distinct brewery signs and vibrant outdoor seating areas. People are visible, joyfully savoring beers, sharing laughs, and engaging in lively conversations. In the distance, a gigantic digital billboard displays a soaring stock graph of CoStar Group's stock price, with bright green arrows pointing upwards. The scene captures the vivacious ambiance of the breweries and the increasing demand for spacious offices, reflected in the ascending stock price of CoStar Group.

*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 The number of Breweries in the United States caused CoStar Group's stock price (CSGP) to increase.

AI academic paper

(Because p < 0.01)

Foam and Finance: A Sudsy Connection Between Breweries and CoStar Group's Stock Price

The Journal of Fermented Finance

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and CoStar Group's stock price (CSGP). Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
Foam and Finance: A Sudsy Connection Between Breweries and CoStar Group's Stock Price

[[ABSTRACT]]
Craft beer enthusiasts and financial analysts alike may raise their glasses to the intriguing correlation between the proliferation of breweries in the United States and the stock price of CoStar Group (CSGP). In this frothy study, we tap into data from the Brewers Association and LSEG Analytics to investigate the relationship between the number of breweries and CSGP's stock price from 2002 to 2022. Our findings reveal a remarkably high correlation coefficient of 0.8907051 and a statistically significant p-value of less than 0.01, lending credence to the notion that the beer-brewing boom may have a foamy influence on the financial markets. This study offers a refreshing perspective on the interconnectedness of craft brewing and stock market dynamics, demonstrating that when it comes to financial forecasting, it pays to keep an eye on the frothy flow of the beer industry. Cheers to the unexpected ways in which hops and stock tickers intertwine!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Pour yourself a cold one and settle in, as we embark on an ale-mentary exploration into the curious relationship between the number of breweries in the United States and the stock price of CoStar Group (CSGP). In the world of finance, where numbers reign supreme, we mustn't underestimate the potential impact of the craft beer craze bubbling up in the U.S. And in the realm of brewing, where hops and barley rule, who would have thought that the whims of the stock market could have a say in the brewer's craft?
As craft beer enthusiasts raise their pint glasses in celebration, and financial analysts furrow their brows in contemplation, our study sets out to shed light on this sudsy connection. The idea that the frothy tide of craft breweries could somehow ebb and flow alongside the gyrations of a financial indicator like CSGP is enough to make even the most seasoned economist do a double take. But fear not, for we are here to hop into the data and hop-efully ferment some insights that will leave you hoppy and wiser.
Craft brewing has been on a frothy, foam-flecked rise in the U.S. over the past few decades, with the Brewers Association reporting an exponential growth in the number of breweries. Meanwhile, CoStar Group, a real estate information and analytics company, has been churning out its stock market performance, largely unfazed by the sudsy revolution brewing in the background. It's this dichotomy that piqued our interest, prompting us to ask the question: Could there be a brew-tiful correlation between the proliferation of breweries and the performance of CSGP's stock price?
The beer industry is no stranger to trends, flavors of the month, and seasonal fads, but what if we told you that it could also hold the frothy frolics that influence the tides of the stock market? It's a notion that may seem as unlikely as a non-alcoholic beer festival, but as the data begins to bubble to the surface, we start to see that there may be more to this brew-haha than meets the eye.
So, grab your favorite pint glass, pull up a barstool, and let's dive headfirst into the world of hops, barley, and stock tickers. In the spirit of scholarly inquiry, and perhaps a touch of whimsy, we aim to uncover the suds in the stocks and the stocks in the suds. Cheers to unraveling this boozy enigma and to finding out what happens when finance meets fermentation!

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The literature on the correlation between the number of breweries in the United States and stock prices is a bubbling cauldron of ideas, theories, and some rather sudsy speculation. It's a tale as old as time, or at least as old as the first recorded brew, as we strive to understand the frothy relationship between the craft beer industry and the stock market. We start our journey with serious studies by renowned economists such as Smith, Doe, and Jones.

In "Aleconomics: The Economics of Craft Beer," Smith et al. delve into the economic impact of craft breweries, uncovering fascinating insights into consumer behavior and market trends. Likewise, in "Hoponomics: The Hoppy World of Finance," Doe and colleagues explore the various factors influencing stock prices, albeit without a hop-centric lens. Jones' seminal work, "Brews and Bulls: Unraveling the Stock Market Mystery," attempts to demystify the intertwining pathways of brewing and finance, forging a path through the frothy wilderness of economic analysis.

While these scholarly works provide a solid framework for understanding the broader economic implications of the craft beer industry, we must also dip our toes into the pool of more eclectic sources. Who would have thought that the literature on beer and finance could extend beyond the hallowed halls of academic journals and textbooks? Yet here we find ourselves, exploring a world where financial data and frothy brews collide.

In "Yeast and Yield: A Fermentation Fable," the authors weave a captivating tale of a stock analyst who stumbles upon a magical brewery that seems to hold the key to predicting market trends. Meanwhile, "Barley and Bulls: A Brewmaster's Guide to Stock Market Success" offers a whimsical take on how the humble ingredients of beer may hold the secret to financial prosperity.

Venturing into the realm of fiction, we encounter books that, while not grounded in empirical data, still manage to capture the imagination. "Brews, Bulls, and Bubbles: A Financial Fairytale" spins a fantastical yarn about a group of beer-loving wizards who use their mystical powers to influence stock prices, while "The Stock Market Brewer: A Sudsy Saga" takes readers on a rollicking adventure through the highs and lows of both brewing and trading.

But wait, there's more! As we delve deeper into the pop culture universe, we stumble upon an unexpected trove of insights. Who could forget the classic cartoon "Cheers & Stocks," where a lovable group of animated characters run a brewery by day and dabble in the financial markets by night? Then there's the children's show "Hoppy Hedge Funders," featuring a group of hoppity rabbits who navigate the complexities of investment banking while juggling their love for brewing carrot beer.

As the literature takes us through serious studies, whimsical tales, and even animated adventures, we find ourselves at the intersection of tradition and tomfoolery, where the line between empirical evidence and fictional fun begins to blur. It's a world where the clinking of pint glasses meets the ringing of stock exchange bells, a realm where the frothy brews of the craft beer industry mingle with the heady highs and lows of stock prices. So, with a nod to the serious scholars and a wink to the fanciful storytellers, let's raise a toast to the unpredictable, yet undeniably fascinating, connection between breweries and the stock market!

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and CoStar Group's stock price (CSGP). Make lots of jokes, goofy observations, and puns.

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]]
Foam and Finance: A Sudsy Connection Between Breweries and CoStar Group's Stock Price

[[ABSTRACT]]
Craft beer enthusiasts and financial analysts alike may raise their glasses to the intriguing correlation between the proliferation of breweries in the United States and the stock price of CoStar Group (CSGP). In this frothy study, we tap into data from the Brewers Association and LSEG Analytics to investigate the relationship between the number of breweries and CSGP's stock price from 2002 to 2022. Our findings reveal a remarkably high correlation coefficient of 0.8907051 and a statistically significant p-value of less than 0.01, lending credence to the notion that the beer-brewing boom may have a foamy influence on the financial markets. This study offers a refreshing perspective on the interconnectedness of craft brewing and stock market dynamics, demonstrating that when it comes to financial forecasting, it pays to keep an eye on the frothy flow of the beer industry. Cheers to the unexpected ways in which hops and stock tickers intertwine!

[[LITERATURE REVIEW]]
The literature on the correlation between the number of breweries in the United States and stock prices is a bubbling cauldron of ideas, theories, and some rather sudsy speculation. It's a tale as old as time, or at least as old as the first recorded brew, as we strive to understand the frothy relationship between the craft beer industry and the stock market. We start our journey with serious studies by renowned economists such as Smith, Doe, and Jones.
In "Aleconomics: The Economics of Craft Beer," Smith et al. delve into the economic impact of craft breweries, uncovering fascinating insights into consumer behavior and market trends. Likewise, in "Hoponomics: The Hoppy World of Finance," Doe and colleagues explore the various factors influencing stock prices, albeit without a hop-centric lens. Jones' seminal work, "Brews and Bulls: Unraveling the Stock Market Mystery," attempts to demystify the intertwining pathways of brewing and finance, forging a path through the frothy wilderness of economic analysis.
While these scholarly works provide a solid framework for understanding the broader economic implications of the craft beer industry, we must also dip our toes into the pool of more eclectic sources. Who would have thought that the literature on beer and finance could extend beyond the hallowed halls of academic journals and textbooks? Yet here we find ourselves, exploring a world where financial data and frothy brews collide.
In "Yeast and Yield: A Fermentation Fable," the authors weave a captivating tale of a stock analyst who stumbles upon a magical brewery that seems to hold the key to predicting market trends. Meanwhile, "Barley and Bulls: A Brewmaster's Guide to Stock Market Success" offers a whimsical take on how the humble ingredients of beer may hold the secret to financial prosperity.
Venturing into the realm of fiction, we encounter books that, while not grounded in empirical data, still manage to capture the imagination. "Brews, Bulls, and Bubbles: A Financial Fairytale" spins a fantastical yarn about a group of beer-loving wizards who use their mystical powers to influence stock prices, while "The Stock Market Brewer: A Sudsy Saga" takes readers on a rollicking adventure through the highs and lows of both brewing and trading.
But wait, there's more! As we delve deeper into the pop culture universe, we stumble upon an unexpected trove of insights. Who could forget the classic cartoon "Cheers & Stocks," where a lovable group of animated characters run a brewery by day and dabble in the financial markets by night? Then there's the children's show "Hoppy Hedge Funders," featuring a group of hoppity rabbits who navigate the complexities of investment banking while juggling their love for brewing carrot beer.
As the literature takes us through serious studies, whimsical tales, and even animated adventures, we find ourselves at the intersection of tradition and tomfoolery, where the line between empirical evidence and fictional fun begins to blur. It's a world where the clinking of pint glasses meets the ringing of stock exchange bells, a realm where the frothy brews of the craft beer industry mingle with the heady highs and lows of stock prices. So, with a nod to the serious scholars and a wink to the fanciful storytellers, let's raise a toast to the unpredictable, yet undeniably fascinating, connection between breweries and the stock market!

[[RESULTS]]
The statistical analysis of the data obtained from the Brewers Association and LSEG Analytics revealed a strikingly high correlation coefficient of 0.8907051 between the number of breweries in the United States and CoStar Group's stock price (CSGP). This correlation indicates a robust relationship between the proliferation of breweries and the gyrations of CSGP's stock price, suggesting that the suds and stocks may frolic in unison more than previously anticipated.
Additionally, the coefficient of determination (r-squared) was calculated to be 0.7933556, signifying that approximately 79.3% of the variability in CSGP's stock price can be explained by the changes in the number of breweries. This finding underscores the significant influence exerted by the brewing industry on the performance of CSGP in the market, showcasing a connection that goes beyond mere happenstance and delves into the intriguing interplay between artisanal beer production and financial market dynamics.
Furthermore, the p-value of less than 0.01 obtained from the analysis implies a statistically significant relationship between the variables under investigation. In practical terms, this suggests that the correlation observed is highly unlikely to have occurred by chance alone, affirming the validity of the identified connection between the number of breweries and CSGP's stock price.
The results provide empirical support for the notion that the craft beer boom in the United States may indeed have a tangible impact on the financial markets, with implications that extend beyond mere sipping and savoring. As such, our findings not only add a spirited splash of froth to the literature on market dynamics but also raise a glass to the unexpected synergy between the world of brewing and the realm of finance.
In Fig. 1, the scatterplot vividly illustrates the strong positive correlation between the number of breweries and CSGP's stock price, offering a visual depiction of the foamy influence wielded by the brewing industry on financial markets. This figure underscores the captivating relationship uncovered in our investigation and provides a compelling testament to the interconnectedness of craft brewing and stock market dynamics.
The connection between breweries and CSGP's stock price discovered in this study serves as a reminder that, in the world of finance, keeping an eye on the ale-studded horizon may yield valuable insights, bringing new meaning to the term "liquid assets." Cheers to the unexpected celestial dance of hops and stock tickers, and to the realization that, in the grand symphony of financial markets, it pays to have a keen nose for the scent of barley and the heady aroma of market trends.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

In this sudsy adventure through the nexus of breweries and stock prices, our findings not only echo the reverberations of prior research but also pour a frothy pint of empirical evidence into the ever-foaming cauldron of market dynamics. As we venture into the discussion of our results, we raise our glasses to the serious scholars and offer a playful wink to the whimsical storytellers in the literature review, for their collective insights have paved the path to this seminal revelation.

The high correlation coefficient of 0.8907051 observed between the number of breweries in the United States and CoStar Group's stock price (CSGP) aligns harmoniously with the musings of esteemed economists in the field. As Smith, Doe, and Jones waded through the economic ripples of craft brewing and market forces, they laid the groundwork for our exploration of this sudsy liaison. Our results stand as a testament to the veracity of their inquiries, underlining the substantive impact of the craft beer industry on stock market gyrations. The froth of economic analysis and the heady bouquet of market trends converge in a symphony of statistical significance, validating the interconnectedness of these seemingly disparate realms.

Moreover, the coefficient of determination (r-squared) of 0.7933556 indicates that approximately 79.3% of the tempestuous undulations in CSGP's stock price can be illuminated by the mere flicker of change in the number of breweries. This luminous insight not only corroborates the scholarly conjectures of Smith, Doe, and Jones but also adds a glimmer to the dazzling tapestry of beer-infused market influence. As we traverse the frothy seas of financial portent, we glimpse the shadow of barley in the ebb and flow of stock charts, a phenomenon that is as captivating as it is lucrative.

The statistically significant p-value of less than 0.01 further fortifies the fortuitous alliance between the brewing industry and the financial markets. Our findings echo the sentiments of the whimsical tales in the literature review, where the magical allure of breweries and the mystique of market trends intertwine in a captivating dance. This statistical verdict dispels any lingering doubts, affirming that the correlation we have unveiled is not a mere flight of fancy but a tangible phenomenon worthy of contemplation and further inquiry.

Fig. 1, our visual magnum opus of the alliance between breweries and stock prices, serves as an overture to the intricate ballet of market forces and brewing fervor. The scatterplot, akin to a canvas painted with the hues of market exuberance, vividly illustrates the coalescence of craft brewing's exuberance and CSGP's financial fervor. It stands as a testament to the enduring allure of hops and financial tides, inviting us to bask in the radiance of their intertwined destinies.

In essence, our findings beckon us to lift the veil on the enigmatic connection between breweries and stock prices, offering a poignant reminder that in the realm of finance, the effervescent effusions of the brewing world are not to be underestimated. The coalescence of froth and finance, as captured by our study, calls for a toast to the whimsical and the wondrous, the serious and the surreal, and to the enduring symphony of hops and stock tickers that enlivens the staid halls of economic analysis. As we conclude this revelatory discussion, we raise our glasses to the unexpected union of brewing and finance, reminding ourselves that in the grand tapestry of market forces, the bubbles of beer and the bourses of stocks may indeed frolic in unison, yielding intoxicating insights into the capricious dance of market dynamics. Cheers to the serendipity of sudsy statistics, the alchemy of financial fervor, and the enduring saga of hops and stock prices!

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and CoStar Group's stock price (CSGP). Make lots of jokes, goofy observations, and puns.

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]]
Foam and Finance: A Sudsy Connection Between Breweries and CoStar Group's Stock Price

[[ABSTRACT]]
Craft beer enthusiasts and financial analysts alike may raise their glasses to the intriguing correlation between the proliferation of breweries in the United States and the stock price of CoStar Group (CSGP). In this frothy study, we tap into data from the Brewers Association and LSEG Analytics to investigate the relationship between the number of breweries and CSGP's stock price from 2002 to 2022. Our findings reveal a remarkably high correlation coefficient of 0.8907051 and a statistically significant p-value of less than 0.01, lending credence to the notion that the beer-brewing boom may have a foamy influence on the financial markets. This study offers a refreshing perspective on the interconnectedness of craft brewing and stock market dynamics, demonstrating that when it comes to financial forecasting, it pays to keep an eye on the frothy flow of the beer industry. Cheers to the unexpected ways in which hops and stock tickers intertwine!

[[INTRDUCTION]]
Pour yourself a cold one and settle in, as we embark on an ale-mentary exploration into the curious relationship between the number of breweries in the United States and the stock price of CoStar Group (CSGP). In the world of finance, where numbers reign supreme, we mustn't underestimate the potential impact of the craft beer craze bubbling up in the U.S. And in the realm of brewing, where hops and barley rule, who would have thought that the whims of the stock market could have a say in the brewer's craft?
As craft beer enthusiasts raise their pint glasses in celebration, and financial analysts furrow their brows in contemplation, our study sets out to shed light on this sudsy connection. The idea that the frothy tide of craft breweries could somehow ebb and flow alongside the gyrations of a financial indicator like CSGP is enough to make even the most seasoned economist do a double take. But fear not, for we are here to hop into the data and hop-efully ferment some insights that will leave you hoppy and wiser.
Craft brewing has been on a frothy, foam-flecked rise in the U.S. over the past few decades, with the Brewers Association reporting an exponential growth in the number of breweries. Meanwhile, CoStar Group, a real estate information and analytics company, has been churning out its stock market performance, largely unfazed by the sudsy revolution brewing in the background. It's this dichotomy that piqued our interest, prompting us to ask the question: Could there be a brew-tiful correlation between the proliferation of breweries and the performance of CSGP's stock price?
The beer industry is no stranger to trends, flavors of the month, and seasonal fads, but what if we told you that it could also hold the frothy frolics that influence the tides of the stock market? It's a notion that may seem as unlikely as a non-alcoholic beer festival, but as the data begins to bubble to the surface, we start to see that there may be more to this brew-haha than meets the eye.
So, grab your favorite pint glass, pull up a barstool, and let's dive headfirst into the world of hops, barley, and stock tickers. In the spirit of scholarly inquiry, and perhaps a touch of whimsy, we aim to uncover the suds in the stocks and the stocks in the suds. Cheers to unraveling this boozy enigma and to finding out what happens when finance meets fermentation!

[[RESULTS]]
The statistical analysis of the data obtained from the Brewers Association and LSEG Analytics revealed a strikingly high correlation coefficient of 0.8907051 between the number of breweries in the United States and CoStar Group's stock price (CSGP). This correlation indicates a robust relationship between the proliferation of breweries and the gyrations of CSGP's stock price, suggesting that the suds and stocks may frolic in unison more than previously anticipated.
Additionally, the coefficient of determination (r-squared) was calculated to be 0.7933556, signifying that approximately 79.3% of the variability in CSGP's stock price can be explained by the changes in the number of breweries. This finding underscores the significant influence exerted by the brewing industry on the performance of CSGP in the market, showcasing a connection that goes beyond mere happenstance and delves into the intriguing interplay between artisanal beer production and financial market dynamics.
Furthermore, the p-value of less than 0.01 obtained from the analysis implies a statistically significant relationship between the variables under investigation. In practical terms, this suggests that the correlation observed is highly unlikely to have occurred by chance alone, affirming the validity of the identified connection between the number of breweries and CSGP's stock price.
The results provide empirical support for the notion that the craft beer boom in the United States may indeed have a tangible impact on the financial markets, with implications that extend beyond mere sipping and savoring. As such, our findings not only add a spirited splash of froth to the literature on market dynamics but also raise a glass to the unexpected synergy between the world of brewing and the realm of finance.
In Fig. 1, the scatterplot vividly illustrates the strong positive correlation between the number of breweries and CSGP's stock price, offering a visual depiction of the foamy influence wielded by the brewing industry on financial markets. This figure underscores the captivating relationship uncovered in our investigation and provides a compelling testament to the interconnectedness of craft brewing and stock market dynamics.
The connection between breweries and CSGP's stock price discovered in this study serves as a reminder that, in the world of finance, keeping an eye on the ale-studded horizon may yield valuable insights, bringing new meaning to the term "liquid assets." Cheers to the unexpected celestial dance of hops and stock tickers, and to the realization that, in the grand symphony of financial markets, it pays to have a keen nose for the scent of barley and the heady aroma of market trends.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

As we raise a toast to the findings of this sudsy study, it becomes abundantly clear that the connection between the number of breweries in the United States and CoStar Group's stock price is no mere ale-usion. Our analysis has poured out a stein-ulating correlation coefficient of 0.8907051, leaving little room to beer around the bush when it comes to the impact of craft brewing on financial markets. The coefficient of determination (r-squared) of 0.7933556 further solidifies the notion that when it comes to predicting CSGP's stock movements, the behavior of breweries is not to be maltreated lightly.

The statistically significant p-value of less than 0.01 has brewed up a storm of excitement, affirming that the frothy influence of breweries on CSGP's stock price isn't just a random ale-gory. It's a real, tangible connection that demands attention, like a stout demand for your last sip.

Our findings not only add to the bevvy of research on market dynamics but also bring a fresh perspective to the world of financial forecasting. The scatterplot in Fig. 1 paints a vivid picture of the buoyant relationship between breweries and CSGP's stock price, making it crystal clear that when it comes to the stock market, sometimes it's best to follow the frothy path of least resistance.

In conclusion, this study leaves little room for doubt: the beer industry and financial markets are more interconnected than a well-crafted stout. As for the future of this peculiar correlation, we raise our glasses one last time and declare that further research would be as unnecessary as a beer with no foam. Cheers to the unexpected findings, and may this research inspire many more ale-gant investigations into the whimsical interplay of hops and stock ticker symbols!

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 Foam and Finance: A Sudsy Connection Between Breweries and CoStar Group's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Fermented 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 Foam and Finance: A Sudsy Connection Between Breweries and CoStar Group's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Sudsy 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 Foam and Finance: A Sudsy Connection Between Breweries and CoStar Group's Stock Price with an abstract of Craft beer enthusiasts and financial analysts alike may raise their glasses to the intriguing correlation between the proliferation of breweries in the United States and the stock price of CoStar Group (CSGP). In this frothy study, we tap into data from the Brewers Association and LSEG Analytics to investigate the relationship between the number of breweries and CSGP's stock price from 2002 to 2022. Our findings reveal a remarkably high correlation coefficient of 0.8907051 and a statistically significant p-value of less than 0.01, lending credence to the notion that the beer-brewing boom may have a foamy influence on the financial markets. This study offers a refreshing perspective on the interconnectedness of craft brewing and stock market dynamics, demonstrating that when it comes to financial forecasting, it pays to keep an eye on the frothy flow of the beer industry. Cheers to the unexpected ways in which hops and stock tickers intertwine!

ChatGPT:

breweries, CoStar Group, stock price, correlation, Brewers Association, LSEG Analytics, craft brewing, financial markets, beer industry, stock market dynamics, financial forecasting, brewery proliferation

*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

CoStar Group's stock price (CSGP)
Detailed data title: Opening price of CoStar Group (CSGP) 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 CoStar Group's stock price (CSGP)

Correlation r = 0.8907051 (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 = 0.7933556 (Coefficient of determination)
This means 79.3% of the change in the one variable (i.e., CoStar Group's stock price (CSGP)) 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 6.3E-8.^Show 0.0000000625889544951470600000
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 0.89 in 6.3E-6% of random cases. Said differently, if you correlated 15,977,260 random variables^Note You don't actually need 15 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 20 degrees of freedom, ^Note 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.

[ 0.75, 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	2022
The number of Breweries in the United States (Number of breweries)	1575	1629	1635	1612	1741	1805	1896	1933	2131	2525	2670	3162	4014	4847	5780	6767	7722	8557	9092	9384	9709
CoStar Group's stock price (CSGP) (Stock price)	2.45	1.91	4.12	4.6	4.34	5.4	4.71	3.3	4.24	5.81	6.82	9.15	18.39	18.46	20.33	18.93	29.83	33.28	60.5	93.22	79.35

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.

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([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([2.45,1.91,4.12,4.6,4.34,5.4,4.71,3.3,4.24,5.81,6.82,9.15,18.39,18.46,20.33,18.93,29.83,33.28,60.5,93.22,79.35,])
array_1_name = "The number of Breweries in the United States"
array_2_name = "CoStar Group's stock price (CSGP)"

# 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 The number of Breweries in the United States
Line chart for only CoStar Group's stock price (CSGP)
AI-generated correlation image
The spurious research paper: Foam and Finance: A Sudsy Connection Between Breweries and CoStar Group's Stock Price

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Correlation ID: 3094 · Black Variable ID: 34 · Red Variable ID: 1821


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