Spurious correlation #2,147 · 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 career/technical education teachers, secondary school in Wisconsin and the second variable is BHP Group's stock price (BHP). The chart goes from 2010 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 career/technical education teachers, secondary school in Wisconsin and the second variable is BHP Group's stock price (BHP). The chart goes from 2010 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As career/technical education teachers became scarce in Wisconsin, fewer students learned about mining and resource extraction. This led to a decrease in future interest and expertise in the industry, causing investors to worry about the potential labor shortage and the impact on BHP Group's operations. In essence, the dwindling number of teachers indirectly unearthed concerns about BHP's future workforce, putting pressure on the stock price. Remember, you can't just dig for success in the mining industry - you also need the right educational foundations! And that's how the absence of CTE teachers in Wisconsin may have been a miner setback for BHP Group.

^{Show image generation prompt} Model: dalle-3
Prompt: Sure, here's your image generation prompt: "Generate an image that looks like it is a scene from a Pixar movie featuring a bustling secondary school in Wisconsin. The focus is on the career/technical education wing, which is alive with the presence of numerous dedicated teachers. In the background, there is a digital stock ticker displaying the steadily climbing stock price of the BHP Group, reflecting the continued success of the global mining company. Keep the visual depiction simple, without any words or speech bubbles." 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 career/technical education teachers, secondary school in Wisconsin and BHP Group'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: Photorealism An image that looks like it is a scene from A Disney Movie A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Cyberpunk An image that looks like it is a scene from a Pixar movie
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 career/technical education teachers, secondary school in Wisconsin and BHP Group's stock price together. Keep the description simple.
ChatGPT: In a bustling secondary school in Wisconsin, the career/technical education wing is alive with the presence of numerous dedicated teachers. Meanwhile, on a nearby digital stock ticker, the BHP Group's stock price steadily climbs, reflecting the continued success of the global mining 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: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: In a bustling secondary school in Wisconsin, the career/technical education wing is alive with the presence of numerous dedicated teachers. Meanwhile, on a nearby digital stock ticker, the BHP Group's stock price steadily climbs, reflecting the continued success of the global mining company. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Sure, here's your image generation prompt: "Generate an image that looks like it is a scene from a Pixar movie featuring a bustling secondary school in Wisconsin. The focus is on the career/technical education wing, which is alive with the presence of numerous dedicated teachers. In the background, there is a digital stock ticker displaying the steadily climbing stock price of the BHP Group, reflecting the continued success of the global mining company. Keep the visual depiction simple, without any words or speech bubbles."

*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 a decrease in The number of career/technical education teachers, secondary school in Wisconsin caused BHP Group's stock price (BHP) to decrease.

AI academic paper

(Because p < 0.01)

Adding Up the Quirks: Exploring the Link Between Career/Technical Education Teachers in Wisconsin Secondary Schools and BHP Group's Stock Price

The Journal of Irreverent Finance and Unusual Pedagogy

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 career/technical education teachers, secondary school in Wisconsin and BHP Group's stock price. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
"Adding Up the Quirks: Exploring the Link Between Career/Technical Education Teachers in Wisconsin Secondary Schools and BHP Group's Stock Price"

[[ABSTRACT]]
This study delves into the peculiar relationship between the numbers of career/technical education teachers in secondary schools in the state of Wisconsin and the stock price of BHP Group. Using data extracted from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team uncovered a statistically significant correlation coefficient of 0.9584866 (p < 0.01) for the years 2010 to 2022. While we set out with an air of scholarly seriousness, we couldn't help but be tickled by the whimsical twists and turns in our findings. Stay tuned as we unravel this surprising connection, one eccentric data point at a time!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Career/technical education has long been considered a cornerstone of secondary education, equipping students with practical skills and preparing them for the workforce. Similarly, the stock market has been a barometer of economic activity and corporate performance. It is in this lively intersection that we find ourselves, aiming to shed light on the curious dance between the number of career/technical education teachers in Wisconsin secondary schools and the enigmatic world of stock prices, particularly those of the illustrious BHP Group.
As we embark on this scholarly journey, we are reminded of the words of renowned economist John Maynard Keynes, who once quipped, "In the long run, we are all dead." While Keynes may not have had this specific research question in mind, his words serve as a whimsical reminder that even the most serious of academic pursuits can benefit from a dash of levity.
Our investigation stems from a desire to uncover the pulsating heartbeat of the economy, resonating through the halls of education and reverberating in the fluctuations of stock markets. Mark Twain once mused, "The lack of money is the root of all evil," and while this may hold true in many contexts, our study aims to illuminate the potential interplay between the realm of education and the financial interests of corporations.
With data in hand, we set out to decipher the enigma concealed within the numbers, uncovering an unexpected correlation between seemingly disparate variables. It is with both rigor and a light-hearted sense of curiosity that we venture into this exploration, eager to unveil the idiosyncrasies that underpin our economic and educational landscapes. So, buckle up and prepare for a scholarly rollercoaster ride through the intricacies of career/technical education and stock prices, where the only certainty is the uncertainty of our findings.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find that the availability of career/technical education programs in secondary schools has a significant impact on students' skill development and workforce readiness. This important work lays the foundation for understanding the potential influence of career and technical education on various aspects of the economy, including the world of finance.

Doe's extensive investigation delves into the trends of teacher recruitment and retention in the field of career/technical education. The findings shed light on the challenges and opportunities in sustaining a well-equipped workforce, a factor that may intersect intriguingly with the stock market dynamics.

Jones' study on the economic impact of educational programs provides valuable insights into the potential linkages between educational initiatives and corporate interests. Such research paves the way for our examination of the unexpected connection between the number of career/technical education teachers in Wisconsin secondary schools and the stock price of BHP Group.

Moving from scholarly articles to books, "Economics of Education" by James S. Catterall is an exemplary resource that explores the economic dimensions of education, providing a comprehensive background for understanding the potential intersections of education and financial markets. Similarly, "Technical Careers: The Path Less Traveled" by Sarah R. Labensky offers a practical perspective on the diverse pathways within technical education, setting the stage for our investigation into the quirky relationship between career/technical education teachers and stock prices.

Transitioning into a more whimsical realm, the fictional works "The Wealthy Educator" by Penny Tration and "Stocks, Stocks, Stocks: A Tale of Two Markets" by Ivana Getarich, while not academic in nature, playfully hint at the fusion of education and finance, adding a touch of levity to our scholarly pursuit.

On a more contemporary note, social media posts such as @EconGuru's tweet "Education+Finance=Profit?" and @TeacherTrader's LinkedIn article "The Surprising Link Between Vocational Education and Stock Value" have sparked intriguing discussions that echo the spirited exploration we engage in as we uncover the intricacies of our peculiar research question.

As we assimilate these diverse sources, we approach our analysis with a mix of scholarly gravitas and a sense of delightful curiosity, ready to embark on this whimsical journey of unraveling the unexpected correlations that come to light. Stay tuned for our revelatory findings, where the only thing as robust as our data analysis is our sense of humor!

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 career/technical education teachers, secondary school in Wisconsin and BHP Group's stock price. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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 2010 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]]
"Adding Up the Quirks: Exploring the Link Between Career/Technical Education Teachers in Wisconsin Secondary Schools and BHP Group's Stock Price"

[[ABSTRACT]]
This study delves into the peculiar relationship between the numbers of career/technical education teachers in secondary schools in the state of Wisconsin and the stock price of BHP Group. Using data extracted from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team uncovered a statistically significant correlation coefficient of 0.9584866 (p < 0.01) for the years 2010 to 2022. While we set out with an air of scholarly seriousness, we couldn't help but be tickled by the whimsical twists and turns in our findings. Stay tuned as we unravel this surprising connection, one eccentric data point at a time!

[[INTRODUCTION]]
Career/technical education has long been considered a cornerstone of secondary education, equipping students with practical skills and preparing them for the workforce. Similarly, the stock market has been a barometer of economic activity and corporate performance. It is in this lively intersection that we find ourselves, aiming to shed light on the curious dance between the number of career/technical education teachers in Wisconsin secondary schools and the enigmatic world of stock prices, particularly those of the illustrious BHP Group.
As we embark on this scholarly journey, we are reminded of the words of renowned economist John Maynard Keynes, who once quipped, "In the long run, we are all dead." While Keynes may not have had this specific research question in mind, his words serve as a whimsical reminder that even the most serious of academic pursuits can benefit from a dash of levity.
Our investigation stems from a desire to uncover the pulsating heartbeat of the economy, resonating through the halls of education and reverberating in the fluctuations of stock markets. Mark Twain once mused, "The lack of money is the root of all evil," and while this may hold true in many contexts, our study aims to illuminate the potential interplay between the realm of education and the financial interests of corporations.
With data in hand, we set out to decipher the enigma concealed within the numbers, uncovering an unexpected correlation between seemingly disparate variables. It is with both rigor and a light-hearted sense of curiosity that we venture into this exploration, eager to unveil the idiosyncrasies that underpin our economic and educational landscapes. So, buckle up and prepare for a scholarly rollercoaster ride through the intricacies of career/technical education and stock prices, where the only certainty is the uncertainty of our findings.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the enigmatic connection between the number of career/technical education teachers in Wisconsin secondary schools and the whimsical world of BHP Group's stock price, our research team embarked on a journey fraught with statistical analyses, data wrangling acrobatics, and a healthy dose of whimsy. With a twinkle in our eye and coffee in hand, we set out to piece together the puzzle, employing a mix of quantitative methods and offbeat investigative techniques.

Data Collection:
Our data journey began amidst the virtual treasure trove of the internet, where we scoured the Bureau of Labor Statistics and LSEG Analytics (Refinitiv) for the elusive gems of information spanning the years 2010 to 2022. We painstakingly gathered data on the number of career/technical education teachers in Wisconsin secondary schools, ensuring that no peculiar data point was left unturned. As for BHP Group's stock price, we tracked its capricious movements with the diligence of a detective hot on the trail of a caper.

Quantitative Wizardry:
Armed with a quiver of statistical tools, we dabbled in the whimsical world of correlation analysis to unearth the peculiar dance between the variables. With bated breath, we deployed Pearson's correlation coefficient to quantify the strength of the relationship, all the while adorned in our scholarly robes and a sprinkle of statistical stardust.

Robustness Checks:
To ensure that our findings stood the test of whimsy, we subjected our data to a battery of robustness checks, assuring that our conclusions weren't merely a figment of statistical shenanigans. For good measure, we teased out the influential data points, allowing our findings to stand sturdy amidst the swirling winds of academic inquiry.

Interdisciplinary Musings:
In a nod to the academic trapeze act, we approached this research endeavor with a multidisciplinary flair, drawing inspiration from the hallowed halls of education and the exuberant world of finance. The intertwining of these seemingly divergent realms provided an enchanting backdrop for our scholarly escapade, allowing for a harmonious symphony of knowledge dissemination.

Ethical Considerations:
Amidst the scholarly revelry, we upheld the ethical tenets of research integrity with due diligence, ensuring that our statistical forays were conducted with the utmost respect for data privacy and academic probity.

In summary, our methodology was a whimsical tapestry woven from the threads of quantitative prowess, interdisciplinary merrymaking, and a touch of scholarly panache. Our data-driven odyssey through the peculiar connection between career/technical education teachers and stock prices serves as a testament to the joyous interplay of academic inquiry and the exuberant dance of empirical discovery. Now, on to the grand reveal of our findings, where the quirky and the quantitative converge in a scholarly waltz unlike any other!

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 career/technical education teachers, secondary school in Wisconsin and BHP Group's stock price. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Adding Up the Quirks: Exploring the Link Between Career/Technical Education Teachers in Wisconsin Secondary Schools and BHP Group's Stock Price"

[[ABSTRACT]]
This study delves into the peculiar relationship between the numbers of career/technical education teachers in secondary schools in the state of Wisconsin and the stock price of BHP Group. Using data extracted from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team uncovered a statistically significant correlation coefficient of 0.9584866 (p < 0.01) for the years 2010 to 2022. While we set out with an air of scholarly seriousness, we couldn't help but be tickled by the whimsical twists and turns in our findings. Stay tuned as we unravel this surprising connection, one eccentric data point at a time!

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find that the availability of career/technical education programs in secondary schools has a significant impact on students' skill development and workforce readiness. This important work lays the foundation for understanding the potential influence of career and technical education on various aspects of the economy, including the world of finance.
Doe's extensive investigation delves into the trends of teacher recruitment and retention in the field of career/technical education. The findings shed light on the challenges and opportunities in sustaining a well-equipped workforce, a factor that may intersect intriguingly with the stock market dynamics.
Jones' study on the economic impact of educational programs provides valuable insights into the potential linkages between educational initiatives and corporate interests. Such research paves the way for our examination of the unexpected connection between the number of career/technical education teachers in Wisconsin secondary schools and the stock price of BHP Group.
Moving from scholarly articles to books, "Economics of Education" by James S. Catterall is an exemplary resource that explores the economic dimensions of education, providing a comprehensive background for understanding the potential intersections of education and financial markets. Similarly, "Technical Careers: The Path Less Traveled" by Sarah R. Labensky offers a practical perspective on the diverse pathways within technical education, setting the stage for our investigation into the quirky relationship between career/technical education teachers and stock prices.
Transitioning into a more whimsical realm, the fictional works "The Wealthy Educator" by Penny Tration and "Stocks, Stocks, Stocks: A Tale of Two Markets" by Ivana Getarich, while not academic in nature, playfully hint at the fusion of education and finance, adding a touch of levity to our scholarly pursuit.
On a more contemporary note, social media posts such as @EconGuru's tweet "Education+Finance=Profit?" and @TeacherTrader's LinkedIn article "The Surprising Link Between Vocational Education and Stock Value" have sparked intriguing discussions that echo the spirited exploration we engage in as we uncover the intricacies of our peculiar research question.
As we assimilate these diverse sources, we approach our analysis with a mix of scholarly gravitas and a sense of delightful curiosity, ready to embark on this whimsical journey of unraveling the unexpected correlations that come to light. Stay tuned for our revelatory findings, where the only thing as robust as our data analysis is our sense of humor!

[[RESULTS]]
The results of our investigation revealed a striking correlation between the number of career/technical education teachers in secondary schools in Wisconsin and the stock price of BHP Group. For the time period spanning 2010 to 2022, we found a correlation coefficient of 0.9584866, with an r-squared value of 0.9186966, both of which were statistically significant at p < 0.01.
Figure 1 displays a scatterplot that vividly illustrates the robust and positive relationship between these seemingly incongruous variables. The scatterplot elegantly captures the essence of our findings, almost like a piece of abstract art – only instead of an avant-garde painting, we have a graph depicting the delightful dance between education and financial markets.
It's worth noting that the strength of the correlation was quite remarkable, akin to finding the last slice of pizza at a bustling party – unexpected, but undeniably satisfying. The data points coalesced into a coherent pattern, revealing a compelling link that left our research team both astonished and elated.
The confidence in the relationship, as indicated by the high r-squared value, suggests that approximately 92% of the variability in BHP Group's stock price can be explained by the number of career/technical education teachers in Wisconsin secondary schools. The remaining 8% may very well be attributed to the mysterious workings of the stock market – a realm as enigmatic as it is alluring.
In sum, our results shed light on an unexpected and beguiling association between these two distinct domains, adding a touch of whimsy to the otherwise staid world of economic research. The correlation between education and stock prices might appear peculiar at first glance, but as the great physicist Albert Einstein once remarked, "The most beautiful thing we can experience is the mysterious." With that in mind, we invite our readers to join us in unraveling the captivating enigma that is the relationship between career/technical education and stock prices.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study revealed an astonishingly robust correlation between the number of career/technical education teachers in Wisconsin secondary schools and the stock price of BHP Group, affirming and extending prior research in curious ways. Building on the works of Smith et al., Doe, and Jones, our findings substantiate the intricate link between education and financial market dynamics. Utilizing the whimsical insights gleaned from "The Wealthy Educator" by Penny Tration and "Stocks, Stocks, Stocks: A Tale of Two Markets" by Ivana Getarich (yes, actual academic sources), we have not only unraveled this enigmatic association but also, dare we say, infused a hint of levity into our scholarly pursuit.

The correlation coefficient of 0.9584866 is akin to stumbling upon a rare Pokémon while traversing through the tangled undergrowth of correlation matrices – unexpected, yet profoundly exhilarating. This substantial strength of association, reminiscent of finding the perfect punchline to a nerdy joke, underscores the compelling nature of this unorthodox relationship. As Catterall proposed in "Economics of Education," the complexity of the educational landscape intertwines with market forces in ways as intriguing as a good mystery novel; our study has unwrapped a chapter of this enthralling narrative.

The scatterplot, serving as a visual testament to this peculiar correlation, could rival the enigmatic allure of a modern art masterpiece. It eloquently showcases the enchanting dance between educational endeavors and stock prices, reminiscent of an avant-garde painting that has come to life, albeit in the form of data visualization. It is as if the obscure connection between these seemingly incongruent variables were a puzzle yearning to be solved, and our study, much like a keen investigator, has cracked the enigma wide open.

The high r-squared value of 0.9186966, akin to a well-constructed punchline, indicates that approximately 92% of the variability in BHP Group's stock price can be attributed to the number of career/technical education teachers. The remaining 8%, akin to the wry wit of a cryptic crossword puzzle, may stem from the idiosyncrasies of the stock market – an unfathomable realm that mirrors the whimsical nature of our research findings.

In conclusion, our study adds a touch of whimsy to the otherwise somber realm of economic research, proving that even in the most unforeseen of places, correlations and exhilarating discoveries can bloom. Our findings support the proposition that education and stock market dynamics are not as distinct as they may initially seem, proving that, indeed, the most delightful mysteries often lurk in the most unexpected places. As we continue to unravel this captivating enigma, we invite our readers to keep pace with us, for in the words of the inimitable Albert Einstein, "The most beautiful thing we can experience is the mysterious."

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 career/technical education teachers, secondary school in Wisconsin and BHP Group's stock price. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Adding Up the Quirks: Exploring the Link Between Career/Technical Education Teachers in Wisconsin Secondary Schools and BHP Group's Stock Price"

[[ABSTRACT]]
This study delves into the peculiar relationship between the numbers of career/technical education teachers in secondary schools in the state of Wisconsin and the stock price of BHP Group. Using data extracted from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team uncovered a statistically significant correlation coefficient of 0.9584866 (p < 0.01) for the years 2010 to 2022. While we set out with an air of scholarly seriousness, we couldn't help but be tickled by the whimsical twists and turns in our findings. Stay tuned as we unravel this surprising connection, one eccentric data point at a time!

[[INTRDUCTION]]
Career/technical education has long been considered a cornerstone of secondary education, equipping students with practical skills and preparing them for the workforce. Similarly, the stock market has been a barometer of economic activity and corporate performance. It is in this lively intersection that we find ourselves, aiming to shed light on the curious dance between the number of career/technical education teachers in Wisconsin secondary schools and the enigmatic world of stock prices, particularly those of the illustrious BHP Group.
As we embark on this scholarly journey, we are reminded of the words of renowned economist John Maynard Keynes, who once quipped, "In the long run, we are all dead." While Keynes may not have had this specific research question in mind, his words serve as a whimsical reminder that even the most serious of academic pursuits can benefit from a dash of levity.
Our investigation stems from a desire to uncover the pulsating heartbeat of the economy, resonating through the halls of education and reverberating in the fluctuations of stock markets. Mark Twain once mused, "The lack of money is the root of all evil," and while this may hold true in many contexts, our study aims to illuminate the potential interplay between the realm of education and the financial interests of corporations.
With data in hand, we set out to decipher the enigma concealed within the numbers, uncovering an unexpected correlation between seemingly disparate variables. It is with both rigor and a light-hearted sense of curiosity that we venture into this exploration, eager to unveil the idiosyncrasies that underpin our economic and educational landscapes. So, buckle up and prepare for a scholarly rollercoaster ride through the intricacies of career/technical education and stock prices, where the only certainty is the uncertainty of our findings.

[[RESULTS]]
The results of our investigation revealed a striking correlation between the number of career/technical education teachers in secondary schools in Wisconsin and the stock price of BHP Group. For the time period spanning 2010 to 2022, we found a correlation coefficient of 0.9584866, with an r-squared value of 0.9186966, both of which were statistically significant at p < 0.01.
Figure 1 displays a scatterplot that vividly illustrates the robust and positive relationship between these seemingly incongruous variables. The scatterplot elegantly captures the essence of our findings, almost like a piece of abstract art – only instead of an avant-garde painting, we have a graph depicting the delightful dance between education and financial markets.
It's worth noting that the strength of the correlation was quite remarkable, akin to finding the last slice of pizza at a bustling party – unexpected, but undeniably satisfying. The data points coalesced into a coherent pattern, revealing a compelling link that left our research team both astonished and elated.
The confidence in the relationship, as indicated by the high r-squared value, suggests that approximately 92% of the variability in BHP Group's stock price can be explained by the number of career/technical education teachers in Wisconsin secondary schools. The remaining 8% may very well be attributed to the mysterious workings of the stock market – a realm as enigmatic as it is alluring.
In sum, our results shed light on an unexpected and beguiling association between these two distinct domains, adding a touch of whimsy to the otherwise staid world of economic research. The correlation between education and stock prices might appear peculiar at first glance, but as the great physicist Albert Einstein once remarked, "The most beautiful thing we can experience is the mysterious." With that in mind, we invite our readers to join us in unraveling the captivating enigma that is the relationship between career/technical education and stock prices.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has unraveled a captivating correlation between the number of career/technical education teachers in Wisconsin secondary schools and the stock price of BHP Group. The statistical significance of our findings, akin to discovering a four-leaf clover in the vast fields of data analysis, reinforces the robustness of this unexpected relationship. As we traverse the uncharted territory where education intertwines with the pulsating rhythms of financial markets, we cannot help but revel in the whimsical tapestry of our results.

The high r-squared value, akin to catching the perfect wave in the tumultuous sea of statistical analysis, underscores the substantial explanatory power of career/technical education teachers on BHP Group's stock price. The remaining unexplained variability, much like the elusive nature of a well-timed punchline, adds a dash of intrigue to this enthralling association.

While our study may have strayed into the realm of the unconventional, it has undoubtedly injected an element of quirkiness into the otherwise austere field of economic research. Our findings remind us that in the vast expanse of scholarly inquiry, serendipitous discoveries and unexpected connections are as essential as they are delightful.

With that said, we assert, with utmost gravity and a twinkle in our eyes, that further research in this area is entirely unnecessary. The enigma has been unraveled, the peculiar dance elucidated, and the unexpected correlation uncovered. As Sherlock Holmes would say, "The game is afoot," but in this case, the game is conclusively over, and the results are in.

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 Adding Up the Quirks: Exploring the Link Between Career/Technical Education Teachers in Wisconsin Secondary Schools and BHP Group's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Irreverent Finance and Unusual Pedagogy

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 Adding Up the Quirks: Exploring the Link Between Career/Technical Education Teachers in Wisconsin Secondary Schools and BHP Group's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Quirky Career Pathways Research

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Adding Up the Quirks: Exploring the Link Between Career/Technical Education Teachers in Wisconsin Secondary Schools and BHP Group's Stock Price with an abstract of This study delves into the peculiar relationship between the numbers of career/technical education teachers in secondary schools in the state of Wisconsin and the stock price of BHP Group. Using data extracted from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team uncovered a statistically significant correlation coefficient of 0.9584866 (p < 0.01) for the years 2010 to 2022. While we set out with an air of scholarly seriousness, we couldn't help but be tickled by the whimsical twists and turns in our findings. Stay tuned as we unravel this surprising connection, one eccentric data point at a time!

ChatGPT:

Wisconsin secondary schools, career/technical education teachers, BHP Group stock price, correlation study, Bureau of Labor Statistics data, LSEG Analytics, Refinitiv, correlation coefficient, quantitative research, Wisconsin education system, BHP Group financial analysis, statistical analysis, relationship between education and stock market

*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 career/technical education teachers, secondary school in Wisconsin
Detailed data title: BLS estimate of career/technical education teachers, secondary school in Wisconsin
Source: Bureau of Larbor Statistics
See what else correlates with The number of career/technical education teachers, secondary school in Wisconsin

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

Correlation r = 0.9584866 (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 = 0.9186966 (Coefficient of determination)
This means 91.9% of the change in the one variable (i.e., BHP Group's stock price (BHP)) is predictable based on the change in the other (i.e., The number of career/technical education teachers, secondary school in Wisconsin) over the 13 years from 2010 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.5E-7.^Show 0.0000002468789167150279300000
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 0.96 in 2.5E-5% of random cases. Said differently, if you correlated 4,050,569 random variables^Note You don't actually need 4 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 12 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 12 because we have two variables measured over a period of 13 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.

[ 0.86, 0.99 ] 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.

	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
The number of career/technical education teachers, secondary school in Wisconsin (Laborers)	1430	1460	1440	1430	1250	730	550	540	780	940	950	1250	1130
BHP Group's stock price (BHP) (Stock price)	66.69	79.32	63.08	67.8	56.97	40.03	22.36	32.96	41.69	41.59	49.24	60.64	54.03

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([1430,1460,1440,1430,1250,730,550,540,780,940,950,1250,1130,])
array_2 = np.array([66.69,79.32,63.08,67.8,56.97,40.03,22.36,32.96,41.69,41.59,49.24,60.64,54.03,])
array_1_name = "The number of career/technical education teachers, secondary school in Wisconsin"
array_2_name = "BHP Group's stock price (BHP)"

# 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
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Line chart for only The number of career/technical education teachers, secondary school in Wisconsin
Line chart for only BHP Group's stock price (BHP)
AI-generated correlation image
The spurious research paper: Adding Up the Quirks: Exploring the Link Between Career/Technical Education Teachers in Wisconsin Secondary Schools and BHP Group's Stock Price

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Correlation ID: 2147 · Black Variable ID: 18770 · Red Variable ID: 1599


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