Spurious correlation #2,122 · 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 professional painters in South Dakota and the second variable is Brookfield's stock price (BN). The chart goes from 2003 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 professional painters in South Dakota and the second variable is Brookfield's stock price (BN). The chart goes from 2003 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the professional painters flocked to South Dakota, they unknowingly brought with them an inexplicable fondness for the color brookfield blue. This led to a surge in demand for Brookfield paint, causing a shortage in supply. With more people clamoring to get their hands on this specific shade, the stock price of Brookfield (BN) naturally painted its way to a new high. The unexpected connection between professional painters and a particular paint brand sent ripples through the stock market, proving that when it comes to trading, every brush stroke of luck counts!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image showing a spacious art studio in South Dakota bustling with activity. Professional painters are passionately working on vibrant landscapes and portraits on their canvases. In the background, a large digital display prominently shows the rising stock price of Brookfield, reflecting the company's strong financial growth. The scene should capture the fusion of traditional creative expression with the modern influence of cyber folk, encompassing the spirit of innovation and artistry in a visually compelling way. 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 professional painters in South Dakota and Brookfield's stock price. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Macabre Cute cartoon Cute 2D animation Cyber folk Parallax art
ChatGPT: Cyber folk

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 professional painters in South Dakota and Brookfield's stock price together. Keep the description simple.
ChatGPT: In a spacious art studio in South Dakota, a group of professional painters diligently work on their canvases, bringing vibrant landscapes and portraits to life. Nearby, on a large digital display, Brookfield's stock price steadily rises, embodying the strong financial growth of the company.

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: [ Cyber folk ] and depicting this scene: In a spacious art studio in South Dakota, a group of professional painters diligently work on their canvases, bringing vibrant landscapes and portraits to life. Nearby, on a large digital display, Brookfield's stock price steadily rises, embodying the strong financial growth of the company. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image showing a spacious art studio in South Dakota bustling with activity. Professional painters are passionately working on vibrant landscapes and portraits on their canvases. In the background, a large digital display prominently shows the rising stock price of Brookfield, reflecting the company's strong financial growth. The scene should capture the fusion of traditional creative expression with the modern influence of cyber folk, encompassing the spirit of innovation and artistry in a visually compelling way.

*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 professional painters in South Dakota caused Brookfield's stock price (BN) to increase.

AI academic paper

(Because p < 0.01)

Painters and Prices: Probing the Peculiar Relationship between Professional Painters in South Dakota and Brookfield's Stock Price

Journal of Regional Economics and Quirky Interdisciplinary Studies

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 professional painters in South Dakota and Brookfield's stock price (BN). 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 you might move on to cartoons and children's shows that you watched for research.

Here is the title and abstract of the paper:
[[TITLE]]
Painters and Prices: Probing the Peculiar Relationship between Professional Painters in South Dakota and Brookfield's Stock Price

[[ABSTRACT]]
The curious case of correlation between the number of professional painters in South Dakota and the stock price of Brookfield (BN) has raised eyebrows among economists and art enthusiasts alike. In this paper, we endeavor to shine a spotlight on this unlikely duo and decipher the enigmatic linkages between the labor market and the financial markets.

Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we conducted a comprehensive analysis spanning the years 2003 to 2022. Our rigorous investigation revealed a striking correlation coefficient of 0.8154594 and p < 0.01, lending credence to the intriguing intersection of these seemingly disparate domains.

While some may brush off this correlation as a mere coincidence, our findings suggest that there may be more than meets the eye. Whether it's a stroke of luck, a colorful conspiracy, or a sheer coincidence, this peculiar relationship between painters and stock prices in South Dakota calls for further exploration and is sure to paint a different picture of market dynamics.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the realm of economic data analysis, peculiar correlations often emerge, begging the question: What on earth connects these seemingly unrelated variables? Today, we find ourselves in the captivating world of finance and fine arts, as we delve into the unforeseen relationship between the number of professional painters in South Dakota and the stock price of Brookfield (BN).
As we embark on this academic exploration, we are not merely chasing rainbows or attempting to paint a rosy picture of the financial markets. Instead, we aim to shed light on this unexpected correlation, brushing aside any skepticism and coloring our understanding with empirical evidence.
The dalliance between South Dakota's professional painters and Brookfield's stock price may appear as incongruous as mixing oil and watercolors, but as any seasoned researcher knows, sometimes the most unexpected connections yield the most fascinating insights.
Undoubtedly, there will be skeptics who may roll their eyes and claim this correlation is merely a brushstroke of luck or a pigment of our imagination. However, as we present the findings of our rigorous analysis, it will become abundantly clear that this seemingly whimsical connection demands serious attention amid the sea of more conventional market indicators.
With our analysis spanning nearly two decades, incorporating data from the Bureau of Labor Statistics and LSEG Analytics, we aim to present a compelling case. Our investigation has unveiled a surprisingly robust correlation coefficient of 0.8154594, with statistical significance even shinier than a fresh coat of paint.
So, let us venture into this world where Wall Street and the art studio intersect, armed with paintbrushes of statistical rigor and a palette of data visualization. Our study aims to transform the mundane canvas of market analysis into a vibrant tapestry, leaving the audience pondering the colorful interplay between the labor market in South Dakota and the ebbs and flows of Brookfield's stock price.
In the following sections, we will peel back the layers of this unexpected relationship, revealing the intricate strokes of correlation and the broader implications for understanding market dynamics. So, fasten your seatbelts and prepare to appreciate the artistic flair of statistical analysis in this truly captivating tale of painters and prices.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find a correlation between labor market indicators and financial market dynamics, shedding light on the interconnectedness of seemingly disparate domains. Building on this foundation, our investigation aims to uncover the intricate relationship between the number of professional painters in South Dakota and the stock price of Brookfield (BN).

Taking a brushstroke from "Doe and Jones," we delve into the world of unconventional market indicators, where the canvas of economic analysis expands to include the vibrant hues of artistic labor. As we embark on this colorful journey, we acknowledge the skepticism that may arise regarding the viability of such an unusual correlation. However, it's crucial to note that groundbreaking revelations often emerge from the unlikeliest of sources.

Venturing beyond the traditional confines of economic literature, our study draws inspiration from "The Wealth of Nations" by Adam Smith, "Freakonomics" by Steven D. Levitt and Stephen J. Dubner, and "Capital in the Twenty-First Century" by Thomas Piketty. While these seminal works offer invaluable insights into economic forces, the connection to the number of professional painters in South Dakota and its effect on Brookfield's stock price remains an uncharted territory, akin to a blank canvas awaiting inventive exploration.

In parallel, fiction works such as "The Picture of Dorian Gray" by Oscar Wilde and "The Goldfinch" by Donna Tartt offer a glimpse into the transformative power of art, albeit in a more metaphysical sense. While these literary masterpieces may not offer direct parallels to our research, they serve as a reminder of the profound impact of artistic endeavors on human perception and societal dynamics.

Moreover, our investigation has not shied away from embracing unconventional sources of inspiration, with a deep dive into cartoons and children's shows that depict the trials and triumphs of artistic expression. After all, who could forget the iconic scene from "SpongeBob SquarePants" where Squidward Tentacles, despite his artistic passion, grapples with the financial realities of life in Bikini Bottom? While this may seem like a whimsical inclusion in an academic paper, it underscores the pervasive influence of economic considerations even in the most lighthearted portrayals of artistic pursuits.

In summary, our foray into the unpainted territories of economic analysis and artistic labor is poised to challenge established notions and infuse a sense of playfulness into the often sober discourse of market correlations. With our eclectic array of influences, ranging from classical economic treatises to whimsical cartoons, our study is primed to unravel the enigmatic linkages between professional painters in South Dakota and the fluctuations in Brookfield's stock price, perhaps painting a picture that defies conventional wisdom in the realm of market dynamics.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 professional painters in South Dakota and Brookfield's stock price (BN). Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Larbor Statistics and LSEG Analytics (Refinitiv) . You used data from 2003 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]]
Painters and Prices: Probing the Peculiar Relationship between Professional Painters in South Dakota and Brookfield's Stock Price

[[ABSTRACT]]
The curious case of correlation between the number of professional painters in South Dakota and the stock price of Brookfield (BN) has raised eyebrows among economists and art enthusiasts alike. In this paper, we endeavor to shine a spotlight on this unlikely duo and decipher the enigmatic linkages between the labor market and the financial markets.

Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we conducted a comprehensive analysis spanning the years 2003 to 2022. Our rigorous investigation revealed a striking correlation coefficient of 0.8154594 and p < 0.01, lending credence to the intriguing intersection of these seemingly disparate domains.

While some may brush off this correlation as a mere coincidence, our findings suggest that there may be more than meets the eye. Whether it's a stroke of luck, a colorful conspiracy, or a sheer coincidence, this peculiar relationship between painters and stock prices in South Dakota calls for further exploration and is sure to paint a different picture of market dynamics.

[[INTRODUCTION]]
In the realm of economic data analysis, peculiar correlations often emerge, begging the question: What on earth connects these seemingly unrelated variables? Today, we find ourselves in the captivating world of finance and fine arts, as we delve into the unforeseen relationship between the number of professional painters in South Dakota and the stock price of Brookfield (BN).
As we embark on this academic exploration, we are not merely chasing rainbows or attempting to paint a rosy picture of the financial markets. Instead, we aim to shed light on this unexpected correlation, brushing aside any skepticism and coloring our understanding with empirical evidence.
The dalliance between South Dakota's professional painters and Brookfield's stock price may appear as incongruous as mixing oil and watercolors, but as any seasoned researcher knows, sometimes the most unexpected connections yield the most fascinating insights.
Undoubtedly, there will be skeptics who may roll their eyes and claim this correlation is merely a brushstroke of luck or a pigment of our imagination. However, as we present the findings of our rigorous analysis, it will become abundantly clear that this seemingly whimsical connection demands serious attention amid the sea of more conventional market indicators.
With our analysis spanning nearly two decades, incorporating data from the Bureau of Labor Statistics and LSEG Analytics, we aim to present a compelling case. Our investigation has unveiled a surprisingly robust correlation coefficient of 0.8154594, with statistical significance even shinier than a fresh coat of paint.
So, let us venture into this world where Wall Street and the art studio intersect, armed with paintbrushes of statistical rigor and a palette of data visualization. Our study aims to transform the mundane canvas of market analysis into a vibrant tapestry, leaving the audience pondering the colorful interplay between the labor market in South Dakota and the ebbs and flows of Brookfield's stock price.
In the following sections, we will peel back the layers of this unexpected relationship, revealing the intricate strokes of correlation and the broader implications for understanding market dynamics. So, fasten your seatbelts and prepare to appreciate the artistic flair of statistical analysis in this truly captivating tale of painters and prices.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the mysterious entanglement between the number of professional painters in South Dakota and the stock price of Brookfield (BN), our research team embarked on a convoluted adventure of data collection and analysis. We employed an array of methodological tools, blending the precision of econometric modeling with the finesse of artful data interpretation. This section delineates the intricacies of our approach, painting a vivid picture of our rigorous methodology.

**Data Collection:** Our quest for data traversed the digital expanse, scouring sources far and wide, akin to a painter seeking the perfect pigment. The Bureau of Labor Statistics stood as a stalwart pillar of labor market information, offering a panoramic view of employment trends in the state of South Dakota. Additionally, LSEG Analytics (Refinitiv) provided a mosaic of financial data, capturing the ebbs and flows of Brookfield's stock price from 2003 to 2022.

**Quantitative Analysis:** Armed with a diverse palette of statistical methods, we proceeded to distill the essence of the collected data. Utilizing advanced econometric techniques, we measured the correlation between the number of professional painters in South Dakota and Brookfield's stock price with a nuanced precision akin to blending hues on a canvas. Our analysis encompassed time series modeling, panel data analysis, and robust regression approaches, ensuring a comprehensive exploration of the observed relationship.

**Robustness Checks:** In our pursuit of empirical rigor, we subjected our findings to a battery of robustness checks, not unlike evaluating the permanence of a freshly applied varnish. Sensitivity analyses, Monte Carlo simulations, and bootstrap methods served as our proverbial brushes, ensuring that the observed correlation between painters and stock prices withstands the test of statistical scrutiny.

**Control Variables:** Recognizing the need to account for confounding factors, we meticulously curated a selection of control variables, meticulously akin to an artist choosing complementary colors for a masterpiece. Variables such as employment in related industries, macroeconomic indicators, and regional economic trends lent depth to our analysis, allowing us to disentangle the true essence of the relationship under investigation.

**Ethical Considerations:** Just as an artist respects the integrity of their craft, we upheld the ethical standards of data usage and dissemination throughout our research endeavors. Adhering to the principles of data privacy and academic integrity, we treated the information with the utmost care and transparency, ensuring that our findings illuminate the realm of knowledge without compromising the sanctity of information.

In synthesizing these methodological components, our research endeavors sought to transcend the boundaries of convention, fusing the disciplines of economics and art in a harmonious symphony of empirical inquiry. This methodological exegesis lays bare the scaffolding of our scholarly pursuit, inviting the reader to appreciate the precision and artistry that underpins our investigation. Now, let us proceed to the culmination of this intellectual odyssey, where the canvas of analysis awaits the brushstrokes of illumination and discovery.

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 professional painters in South Dakota and Brookfield's stock price (BN). Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Painters and Prices: Probing the Peculiar Relationship between Professional Painters in South Dakota and Brookfield's Stock Price

[[ABSTRACT]]
The curious case of correlation between the number of professional painters in South Dakota and the stock price of Brookfield (BN) has raised eyebrows among economists and art enthusiasts alike. In this paper, we endeavor to shine a spotlight on this unlikely duo and decipher the enigmatic linkages between the labor market and the financial markets.

Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we conducted a comprehensive analysis spanning the years 2003 to 2022. Our rigorous investigation revealed a striking correlation coefficient of 0.8154594 and p < 0.01, lending credence to the intriguing intersection of these seemingly disparate domains.

While some may brush off this correlation as a mere coincidence, our findings suggest that there may be more than meets the eye. Whether it's a stroke of luck, a colorful conspiracy, or a sheer coincidence, this peculiar relationship between painters and stock prices in South Dakota calls for further exploration and is sure to paint a different picture of market dynamics.

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find a correlation between labor market indicators and financial market dynamics, shedding light on the interconnectedness of seemingly disparate domains. Building on this foundation, our investigation aims to uncover the intricate relationship between the number of professional painters in South Dakota and the stock price of Brookfield (BN).
Taking a brushstroke from "Doe and Jones," we delve into the world of unconventional market indicators, where the canvas of economic analysis expands to include the vibrant hues of artistic labor. As we embark on this colorful journey, we acknowledge the skepticism that may arise regarding the viability of such an unusual correlation. However, it's crucial to note that groundbreaking revelations often emerge from the unlikeliest of sources.
Venturing beyond the traditional confines of economic literature, our study draws inspiration from "The Wealth of Nations" by Adam Smith, "Freakonomics" by Steven D. Levitt and Stephen J. Dubner, and "Capital in the Twenty-First Century" by Thomas Piketty. While these seminal works offer invaluable insights into economic forces, the connection to the number of professional painters in South Dakota and its effect on Brookfield's stock price remains an uncharted territory, akin to a blank canvas awaiting inventive exploration.
In parallel, fiction works such as "The Picture of Dorian Gray" by Oscar Wilde and "The Goldfinch" by Donna Tartt offer a glimpse into the transformative power of art, albeit in a more metaphysical sense. While these literary masterpieces may not offer direct parallels to our research, they serve as a reminder of the profound impact of artistic endeavors on human perception and societal dynamics.
Moreover, our investigation has not shied away from embracing unconventional sources of inspiration, with a deep dive into cartoons and children's shows that depict the trials and triumphs of artistic expression. After all, who could forget the iconic scene from "SpongeBob SquarePants" where Squidward Tentacles, despite his artistic passion, grapples with the financial realities of life in Bikini Bottom? While this may seem like a whimsical inclusion in an academic paper, it underscores the pervasive influence of economic considerations even in the most lighthearted portrayals of artistic pursuits.
In summary, our foray into the unpainted territories of economic analysis and artistic labor is poised to challenge established notions and infuse a sense of playfulness into the often sober discourse of market correlations. With our eclectic array of influences, ranging from classical economic treatises to whimsical cartoons, our study is primed to unravel the enigmatic linkages between professional painters in South Dakota and the fluctuations in Brookfield's stock price, perhaps painting a picture that defies conventional wisdom in the realm of market dynamics.

[[RESULTS]]
The statistical analysis of the data revealed a robust and eyebrow-raising correlation between the number of professional painters in South Dakota and the stock price of Brookfield (BN). Our findings unveiled a correlation coefficient of 0.8154594, indicating a strong positive relationship between these seemingly disparate variables. This correlation was supported by an r-squared value of 0.6649740, underscoring the substantial proportion of variation in Brookfield's stock price that can be explained by the number of painters in South Dakota.
In the world of statistics, a p-value less than 0.01 is akin to discovering a rare gem in a statistical mine—indicating an extremely low probability that the observed correlation is due to chance alone. This level of statistical significance further bolsters the credibility of our findings and suggests that the relationship between professional painters in South Dakota and Brookfield's stock price is not merely a whimsical coincidence.
The scatterplot presented in Figure 1 vividly illustrates the close connection between the number of professional painters in South Dakota and the stock price of Brookfield. The data points form a striking pattern that echoes the harmonious blend of colors on a painter's palette, offering a visual depiction of the strong correlation uncovered in our analysis.
While some may view this correlation as a peculiar quirk of data, our study invites the academic community to consider the broader implications of this unexpected relationship. It challenges conventional wisdom and prompts a reevaluation of the factors influencing stock prices, hinting at the intricate interplay between regional labor markets and financial dynamics.
In summary, our research provides compelling evidence of a noteworthy correlation between professional painters in South Dakota and Brookfield's stock price. This peculiar relationship transcends the boundaries of traditional market analysis, inviting further exploration and speculation on the colorful connections woven into the fabric of economic and artistic landscapes.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The striking correlation between the number of professional painters in South Dakota and the stock price of Brookfield (BN) has left even the most seasoned economists pondering the canvas of market dynamics. Our findings, which bear the weight of statistical significance, echo the colorful musings of "Doe and Jones" and the rhythmic strokes of "Smith et al." As we brush past skepticism, our study daubs a vibrant hue on the intricate tapestry of market correlations.

Our results not only corroborate prior research on the interconnectedness of labor market indicators and financial market dynamics but also add a splash of whimsy to the canvas of economic analysis. The robust correlation coefficient of 0.8154594 mirrors the resounding strokes of creativity found in our literary companions, affirming that beneath the surface of market data lie hidden connections that are ready to burst forth and paint a revealing masterpiece.

It is essential to emphasize the statistical significance represented by the p-value of less than 0.01, akin to stumbling upon a rare pearl in an ocean of statistical permutations. This level of significance lends credence to the notion that the observed relationship between painters in South Dakota and Brookfield's stock price is not a mere fluke but a momentous revelation akin to unearthing a treasure trove of economic curios. The r-squared value of 0.6649740 further underlines the substantial portion of variance in Brookfield's stock price explained by the number of painters in South Dakota, akin to the masterful interplay of light and shadows in a captivating artwork.

As we gaze upon the scatterplot in Figure 1, the compelling visual representation mirrors a carefully crafted piece of art, with data points dancing in harmony much like the vibrant strokes on a painter's canvas. This imagery is not just a playful analogy; it intertwines the realms of economic and artistic expression, challenging the perceptions of conventional market analysis and inviting a whimsical dalliance with the unforeseen.

In traversing the uncharted territories of market correlations, our study acknowledges the influence of unconventional sources of inspiration, reigniting the playful spirit of academic inquiry. Just as Squidward Tentacles grapples with the financial realities of life in Bikini Bottom, our research delves into the entwining forces of labor and finance, revealing that even the most lighthearted of portrayals can offer profound insights into economic considerations.

In summary, our study makes a bold stroke on the canvas of economic research, not merely confirming the veracity of an unexpected correlation but also carving a vivid path for future investigations. As we stand on the precipice of art and finance, it is essential to remember that the most unconventional pairings often yield the most captivating insights, painting a fresh perspective on the complex web of market dynamics.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 professional painters in South Dakota and Brookfield's stock price (BN). Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Painters and Prices: Probing the Peculiar Relationship between Professional Painters in South Dakota and Brookfield's Stock Price

[[ABSTRACT]]
The curious case of correlation between the number of professional painters in South Dakota and the stock price of Brookfield (BN) has raised eyebrows among economists and art enthusiasts alike. In this paper, we endeavor to shine a spotlight on this unlikely duo and decipher the enigmatic linkages between the labor market and the financial markets.

Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we conducted a comprehensive analysis spanning the years 2003 to 2022. Our rigorous investigation revealed a striking correlation coefficient of 0.8154594 and p < 0.01, lending credence to the intriguing intersection of these seemingly disparate domains.

While some may brush off this correlation as a mere coincidence, our findings suggest that there may be more than meets the eye. Whether it's a stroke of luck, a colorful conspiracy, or a sheer coincidence, this peculiar relationship between painters and stock prices in South Dakota calls for further exploration and is sure to paint a different picture of market dynamics.

[[INTRDUCTION]]
In the realm of economic data analysis, peculiar correlations often emerge, begging the question: What on earth connects these seemingly unrelated variables? Today, we find ourselves in the captivating world of finance and fine arts, as we delve into the unforeseen relationship between the number of professional painters in South Dakota and the stock price of Brookfield (BN).
As we embark on this academic exploration, we are not merely chasing rainbows or attempting to paint a rosy picture of the financial markets. Instead, we aim to shed light on this unexpected correlation, brushing aside any skepticism and coloring our understanding with empirical evidence.
The dalliance between South Dakota's professional painters and Brookfield's stock price may appear as incongruous as mixing oil and watercolors, but as any seasoned researcher knows, sometimes the most unexpected connections yield the most fascinating insights.
Undoubtedly, there will be skeptics who may roll their eyes and claim this correlation is merely a brushstroke of luck or a pigment of our imagination. However, as we present the findings of our rigorous analysis, it will become abundantly clear that this seemingly whimsical connection demands serious attention amid the sea of more conventional market indicators.
With our analysis spanning nearly two decades, incorporating data from the Bureau of Labor Statistics and LSEG Analytics, we aim to present a compelling case. Our investigation has unveiled a surprisingly robust correlation coefficient of 0.8154594, with statistical significance even shinier than a fresh coat of paint.
So, let us venture into this world where Wall Street and the art studio intersect, armed with paintbrushes of statistical rigor and a palette of data visualization. Our study aims to transform the mundane canvas of market analysis into a vibrant tapestry, leaving the audience pondering the colorful interplay between the labor market in South Dakota and the ebbs and flows of Brookfield's stock price.
In the following sections, we will peel back the layers of this unexpected relationship, revealing the intricate strokes of correlation and the broader implications for understanding market dynamics. So, fasten your seatbelts and prepare to appreciate the artistic flair of statistical analysis in this truly captivating tale of painters and prices.

[[RESULTS]]
The statistical analysis of the data revealed a robust and eyebrow-raising correlation between the number of professional painters in South Dakota and the stock price of Brookfield (BN). Our findings unveiled a correlation coefficient of 0.8154594, indicating a strong positive relationship between these seemingly disparate variables. This correlation was supported by an r-squared value of 0.6649740, underscoring the substantial proportion of variation in Brookfield's stock price that can be explained by the number of painters in South Dakota.
In the world of statistics, a p-value less than 0.01 is akin to discovering a rare gem in a statistical mine—indicating an extremely low probability that the observed correlation is due to chance alone. This level of statistical significance further bolsters the credibility of our findings and suggests that the relationship between professional painters in South Dakota and Brookfield's stock price is not merely a whimsical coincidence.
The scatterplot presented in Figure 1 vividly illustrates the close connection between the number of professional painters in South Dakota and the stock price of Brookfield. The data points form a striking pattern that echoes the harmonious blend of colors on a painter's palette, offering a visual depiction of the strong correlation uncovered in our analysis.
While some may view this correlation as a peculiar quirk of data, our study invites the academic community to consider the broader implications of this unexpected relationship. It challenges conventional wisdom and prompts a reevaluation of the factors influencing stock prices, hinting at the intricate interplay between regional labor markets and financial dynamics.
In summary, our research provides compelling evidence of a noteworthy correlation between professional painters in South Dakota and Brookfield's stock price. This peculiar relationship transcends the boundaries of traditional market analysis, inviting further exploration and speculation on the colorful connections woven into the fabric of economic and artistic landscapes.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the correlation between the number of professional painters in South Dakota and Brookfield's stock price has illuminated a peculiar and surprisingly robust relationship. Our findings have revealed a correlation coefficient as striking as a bold brushstroke on an empty canvas, with a statistical significance that shines brighter than a starry night sky.

The implications of this unlikely pairing stretch beyond the boundaries of traditional market indicators, inviting the academic community to ponder the colorful interplay between seemingly unrelated economic and artistic domains. We have sketched a compelling case that urges a reevaluation of the factors influencing stock prices and underscores the intricate connections that underpin market dynamics.

While some may view this correlation as an odd quirk, akin to stumbling upon a whimsical painting in a grand gallery, our findings demand serious consideration. Whether it's a stroke of luck, a splash of artistic influence, or a mere coincidence, the connection between professional painters in South Dakota and Brookfield's stock price beckons further exploration.

As we wrap up our investigation, it becomes abundantly clear that no more research is needed in this area. Our findings have cast a spotlight on this unexpected relationship, painting a vibrant picture that leaves little room for doubt. The colorful tapestry of correlation between these unconventional variables has been woven, and it's time for the academic community to marvel at this eye-catching masterpiece and celebrate the unexpected quirks that enliven the world of economic analysis.

In the grand gallery of academic research, our study stands as a testament to the captivating nature of statistical analysis, where even the most unlikely connections can unravel a mesmerizing tale. So, as we bid adieu to this enchanting exploration, we leave the audience with a newfound appreciation for the artistry inherent in uncovering correlations that transcend traditional boundaries. For in the world of research, as in life, sometimes the most unexpected connections yield the most fascinating insights.

In the spirit of embracing the whimsical and unexpected, we assert with unwavering confidence that further research in this area is as unnecessary as a painter with a fear of colors. The canvas of correlation between professional painters in South Dakota and Brookfield's stock price has been painted, and it's certainly a masterpiece worth admiring.

Now, let's grab our easels and move on to the next captivating mystery in the world of economic and artistic intersections.

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 Painters and Prices: Probing the Peculiar Relationship between Professional Painters in South Dakota and Brookfield's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Regional Economics and Quirky Interdisciplinary Studies

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 Painters and Prices: Probing the Peculiar Relationship between Professional Painters in South Dakota and Brookfield's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Society for the Advancement of Quirky Economic Research (SAQER)

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 Painters and Prices: Probing the Peculiar Relationship between Professional Painters in South Dakota and Brookfield's Stock Price with an abstract of The curious case of correlation between the number of professional painters in South Dakota and the stock price of Brookfield (BN) has raised eyebrows among economists and art enthusiasts alike. In this paper, we endeavor to shine a spotlight on this unlikely duo and decipher the enigmatic linkages between the labor market and the financial markets.
Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we conducted a comprehensive analysis spanning the years 2003 to 2022. Our rigorous investigation revealed a striking correlation coefficient of 0.8154594 and p < 0.01, lending credence to the intriguing intersection of these seemingly disparate domains.
While some may brush off this correlation as a mere coincidence, our findings suggest that there may be more than meets the eye. Whether it's a stroke of luck, a colorful conspiracy, or a sheer coincidence, this peculiar relationship between painters and stock prices in South Dakota calls for further exploration and is sure to paint a different picture of market dynamics.

ChatGPT:

South Dakota professional painters, Brookfield stock price, correlation analysis, labor market analysis, financial market analysis, Bureau of Labor Statistics data, LSEG Analytics data, correlation coefficient, market dynamics, peculiar relationship, South Dakota labor market, financial market correlation

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

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Data details

The number of professional painters in South Dakota
Detailed data title: BLS estimate of painters, construction and maintenance in South Dakota
Source: Bureau of Larbor Statistics
See what else correlates with The number of professional painters in South Dakota

Brookfield's stock price (BN)
Detailed data title: Opening price of Brookfield (BN) 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 Brookfield's stock price (BN)

Correlation r = 0.8154594 (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 = 0.6649740 (Coefficient of determination)
This means 66.5% of the change in the one variable (i.e., Brookfield's stock price (BN)) is predictable based on the change in the other (i.e., The number of professional painters in South Dakota) over the 20 years from 2003 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.2E-5.^Show 0.0000118085882725530500000000
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 0.82 in 0.0012% of random cases. Said differently, if you correlated 84,684 random variables^Note You don't actually need 84 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

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

[ 0.58, 0.92 ] 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.

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
The number of professional painters in South Dakota (Laborers)	430	500	550	560	550	540	480	440	450	450	490	530	560	570	500	520	530	600	540	600
Brookfield's stock price (BN) (Stock price)	16.54	24.8	29.54	40.97	39.26	29.12	12.32	18.46	27.25	22.74	30.35	31.54	40.76	25.29	26.96	35.47	30.89	47.17	33.43	49.19

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([430,500,550,560,550,540,480,440,450,450,490,530,560,570,500,520,530,600,540,600,])
array_2 = np.array([16.54,24.8,29.54,40.97,39.26,29.12,12.32,18.46,27.25,22.74,30.35,31.54,40.76,25.29,26.96,35.47,30.89,47.17,33.43,49.19,])
array_1_name = "The number of professional painters in South Dakota"
array_2_name = "Brookfield's stock price (BN)"

# 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 professional painters in South Dakota
Line chart for only Brookfield's stock price (BN)
AI-generated correlation image
The spurious research paper: Painters and Prices: Probing the Peculiar Relationship between Professional Painters in South Dakota and Brookfield's Stock Price

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Correlation ID: 2122 · Black Variable ID: 14332 · Red Variable ID: 1706


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