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Spurious correlation #2,160 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Bachelor's degrees awarded in Agriculture and the second variable is Bank of America's stock price (BAC).  The chart goes from 2012 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As more graduates entered the workforce with expertise in crop production and animal husbandry, they unwittingly improved the office plant survival rate at Bank of America. This lush influx of greenery boosted employee morale and air quality, leading to a productivity bloom that investors couldn't leaf alone. One could say they really branched out into success!

Model: dalle-3
Prompt: Generate a cubist-inspired depiction of a rustic barn interior. Inside, a group of graduates wearing caps and gowns stand proudly, holding up their Bachelor's degrees in Agriculture and natural resources. Their faces are fragmented, showing multiple perspectives simultaneously. In the background, a digital display flickers with the Bank of America's stock price steadily rising, with abstract shapes and fragmented numbers. The scene captures a sense of achievement and progress through the lens of cubism. 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: Bachelor's degrees awarded in Agriculture and natural resources and Bank of America'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: Glitch art A TIME magazine cover image Data cyber art Cubism Cubism
ChatGPT: Cubism

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 Bachelor's degrees awarded in Agriculture and natural resources and Bank of America's stock price together. Keep the description simple.
ChatGPT: In a rustic barn, a group of graduates in caps and gowns proudly display their Bachelor's degrees in Agriculture and natural resources. In the background, a digital display shows Bank of America's stock price steadily rising on a big screen.

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: [ Cubism ] and depicting this scene: In a rustic barn, a group of graduates in caps and gowns proudly display their Bachelor's degrees in Agriculture and natural resources. In the background, a digital display shows Bank of America's stock price steadily rising on a big screen. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate a cubist-inspired depiction of a rustic barn interior. Inside, a group of graduates wearing caps and gowns stand proudly, holding up their Bachelor's degrees in Agriculture and natural resources. Their faces are fragmented, showing multiple perspectives simultaneously. In the background, a digital display flickers with the Bank of America's stock price steadily rising, with abstract shapes and fragmented numbers. The scene captures a sense of achievement and progress through the lens of cubism.

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

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

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Bachelor's degrees awarded in Agriculture and natural resources caused Bank of America's stock price (BAC) to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)
Agriculture, Natural Resources, and Finance: Sowing the Seeds of Stock Price Growth

The Journal of Agricultural Economics and Financial Management

Jan 2024

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




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Bachelor's degrees awarded in Agriculture and natural resources and Bank of America's stock price (BAC). Make lots of jokes, goofy observations, and puns.

Make the title a clever pun.

Your research team used data from National Center for Education Statistics and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9477381 and p < 0.01 for 2012 to 2021.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
"Agriculture, Natural Resources, and Finance: Sowing the Seeds of Stock Price Growth"

[[ABSTRACT]]
In this study, we delved into the unlikely correlation between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). By planting the seeds of curiosity, we utilized data from the National Center for Education Statistics and LSEG Analytics (Refinitiv) to explore whether there was a statistically significant relationship between these two seemingly unrelated domains. Our findings revealed a surprisingly strong correlation coefficient of 0.9477381 and a p-value of less than 0.01 for the period spanning from 2012 to 2021. So, while you may have thought "stock" when someone mentioned agriculture, our research suggests that there might just be some truth to that notion. This study offers a novel perspective on the interconnectedness of academic disciplines and financial markets, highlighting the potential for cross-pollination between fields that might initially appear as different as apples and oranges.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Bachelor's degrees awarded in Agriculture and natural resources and Bank of America's stock price (BAC). Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
"Agriculture, Natural Resources, and Finance: Sowing the Seeds of Stock Price Growth"

[[ABSTRACT]]
In this study, we delved into the unlikely correlation between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). By planting the seeds of curiosity, we utilized data from the National Center for Education Statistics and LSEG Analytics (Refinitiv) to explore whether there was a statistically significant relationship between these two seemingly unrelated domains. Our findings revealed a surprisingly strong correlation coefficient of 0.9477381 and a p-value of less than 0.01 for the period spanning from 2012 to 2021. So, while you may have thought "stock" when someone mentioned agriculture, our research suggests that there might just be some truth to that notion. This study offers a novel perspective on the interconnectedness of academic disciplines and financial markets, highlighting the potential for cross-pollination between fields that might initially appear as different as apples and oranges.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

As the age-old saying goes, "you reap what you sow." In the world of academia and finance, this phrase takes on a whole new meaning as we venture into the intriguing intersection of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). In this study, we embark on a quest to unearth the hidden roots of this unlikely correlation and explore the fertile ground where academia meets finance.

While it may seem like pairing broccoli and Wall Street, our curiosity led us to till the statistical soil and plant the seeds of inquiry. Who would have thought that the number of individuals receiving degrees in the agricultural and natural resources discipline could have any bearing on the stock price of a major financial institution? But as they say, truth can often be stranger than friction. It's one thing to expect high yields in an agricultural field, but expecting a fruitful relationship between academic degrees and stock market performance is a different crop altogether.

With our trowels sharpened and data in hand, we uncovered a statistically significant correlation coefficient of 0.9477381 and a p-value that would make even the most skeptical statistician take notice. This isn't just a fluctuation in the wind; it's a strong breeze of evidence blowing in from unexpected terrain. Just as a crop of corn can surprise you with its height, our findings may just upend conventional wisdom about the seemingly disparate worlds of academia and finance.

So, hold onto your hats as we navigate through the wheat fields of data and the stock market's financial forest. This study promises to offer a fresh perspective on the interconnectedness of academic disciplines and financial markets, serving up a tasty dish of interdisciplinary insights that are ripe for the picking. After all, who would have guessed that the humble agricultural sector could have such a profound impact on the not-so-humble stock price of Bank of America? Let's dig in!


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Bachelor's degrees awarded in Agriculture and natural resources and Bank of America's stock price (BAC). Make lots of jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Agriculture, Natural Resources, and Finance: Sowing the Seeds of Stock Price Growth"

[[ABSTRACT]]
In this study, we delved into the unlikely correlation between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). By planting the seeds of curiosity, we utilized data from the National Center for Education Statistics and LSEG Analytics (Refinitiv) to explore whether there was a statistically significant relationship between these two seemingly unrelated domains. Our findings revealed a surprisingly strong correlation coefficient of 0.9477381 and a p-value of less than 0.01 for the period spanning from 2012 to 2021. So, while you may have thought "stock" when someone mentioned agriculture, our research suggests that there might just be some truth to that notion. This study offers a novel perspective on the interconnectedness of academic disciplines and financial markets, highlighting the potential for cross-pollination between fields that might initially appear as different as apples and oranges.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As the age-old saying goes, "you reap what you sow." In the world of academia and finance, this phrase takes on a whole new meaning as we venture into the intriguing intersection of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). In this study, we embark on a quest to unearth the hidden roots of this unlikely correlation and explore the fertile ground where academia meets finance.
While it may seem like pairing broccoli and Wall Street, our curiosity led us to till the statistical soil and plant the seeds of inquiry. Who would have thought that the number of individuals receiving degrees in the agricultural and natural resources discipline could have any bearing on the stock price of a major financial institution? But as they say, truth can often be stranger than friction. It's one thing to expect high yields in an agricultural field, but expecting a fruitful relationship between academic degrees and stock market performance is a different crop altogether.
With our trowels sharpened and data in hand, we uncovered a statistically significant correlation coefficient of 0.9477381 and a p-value that would make even the most skeptical statistician take notice. This isn't just a fluctuation in the wind; it's a strong breeze of evidence blowing in from unexpected terrain. Just as a crop of corn can surprise you with its height, our findings may just upend conventional wisdom about the seemingly disparate worlds of academia and finance.
So, hold onto your hats as we navigate through the wheat fields of data and the stock market's financial forest. This study promises to offer a fresh perspective on the interconnectedness of academic disciplines and financial markets, serving up a tasty dish of interdisciplinary insights that are ripe for the picking. After all, who would have guessed that the humble agricultural sector could have such a profound impact on the not-so-humble stock price of Bank of America? Let's dig in!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The literature on the relationship between academic disciplines and financial markets is often as wide and varied as the fields of Agriculture and natural resources themselves. At the outset, seminal works by Smith et al. (2010), Doe and Jones (2015), and Brown (2018) have explored connections between educational trends and economic indicators, laying the groundwork for our investigation.

In "Harvesting Returns: Agricultural Education and Economic Outcomes" by Smith et al., the authors find an intriguing link between the number of Bachelor's degrees awarded in Agriculture and natural resources and the growth of local agricultural economies. The study's findings sprouted a newfound interest in understanding the broader implications of educational pursuits in this domain. Further, Doe and Jones (2015) shed light on the investment potential of knowledge-based sectors, signaling that the agricultural field may not just sow seeds but also sow the seeds of financial growth.

Moving beyond traditional academic research, non-fiction books such as "The Omnivore's Dilemma" by Michael Pollan and "The Hidden Life of Trees" by Peter Wohlleben have captivated readers with their insights into agricultural systems and natural resources, offering a leafy backdrop for our financial foray. On the fiction front, "Animal Farm" by George Orwell and "The Grapes of Wrath" by John Steinbeck beckon readers into the agricultural landscape, blending narrative fiction with socio-economic undertones.

Surprisingly enough, even cartoons and children's shows have inadvertently cultivated an interest in the intersection of agriculture and finance. The animated series "VeggieTales" and "Bob the Builder" may seem like child's play, but their themes of resource management and economic sustainability plant seeds of understanding about the importance of these sectors from an early age. And who could forget the classic "Captain Planet and the Planeteers," where environmental conservation and financial responsibility join forces to save the world?

As our exploration delves into the unexpected correlation between Bachelor's degrees in Agriculture and natural resources and the stock price of Bank of America (BAC), this colorful array of literature serves as a reminder that, much like a well-tended garden, interdisciplinary connections can yield unexpectedly fruitful results.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Bachelor's degrees awarded in Agriculture and natural resources and Bank of America's stock price (BAC). Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from National Center for Education Statistics and LSEG Analytics (Refinitiv) . You used data from 2012 to 2021

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Agriculture, Natural Resources, and Finance: Sowing the Seeds of Stock Price Growth"

[[ABSTRACT]]
In this study, we delved into the unlikely correlation between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). By planting the seeds of curiosity, we utilized data from the National Center for Education Statistics and LSEG Analytics (Refinitiv) to explore whether there was a statistically significant relationship between these two seemingly unrelated domains. Our findings revealed a surprisingly strong correlation coefficient of 0.9477381 and a p-value of less than 0.01 for the period spanning from 2012 to 2021. So, while you may have thought "stock" when someone mentioned agriculture, our research suggests that there might just be some truth to that notion. This study offers a novel perspective on the interconnectedness of academic disciplines and financial markets, highlighting the potential for cross-pollination between fields that might initially appear as different as apples and oranges.

[[INTRODUCTION]]
As the age-old saying goes, "you reap what you sow." In the world of academia and finance, this phrase takes on a whole new meaning as we venture into the intriguing intersection of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). In this study, we embark on a quest to unearth the hidden roots of this unlikely correlation and explore the fertile ground where academia meets finance.
While it may seem like pairing broccoli and Wall Street, our curiosity led us to till the statistical soil and plant the seeds of inquiry. Who would have thought that the number of individuals receiving degrees in the agricultural and natural resources discipline could have any bearing on the stock price of a major financial institution? But as they say, truth can often be stranger than friction. It's one thing to expect high yields in an agricultural field, but expecting a fruitful relationship between academic degrees and stock market performance is a different crop altogether.
With our trowels sharpened and data in hand, we uncovered a statistically significant correlation coefficient of 0.9477381 and a p-value that would make even the most skeptical statistician take notice. This isn't just a fluctuation in the wind; it's a strong breeze of evidence blowing in from unexpected terrain. Just as a crop of corn can surprise you with its height, our findings may just upend conventional wisdom about the seemingly disparate worlds of academia and finance.
So, hold onto your hats as we navigate through the wheat fields of data and the stock market's financial forest. This study promises to offer a fresh perspective on the interconnectedness of academic disciplines and financial markets, serving up a tasty dish of interdisciplinary insights that are ripe for the picking. After all, who would have guessed that the humble agricultural sector could have such a profound impact on the not-so-humble stock price of Bank of America? Let's dig in!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To plow through the soil of statistics and unearth the hidden gems of correlation, we employed a meticulous and quirky methodology that encapsulates the spirit of exploration and discovery. This escapade into the world of agricultural degrees and stock prices involved a concoction of data collection, slicing and dicing, and sprinkling just the right amount of statistical seasoning.

Data Collection: We donned our virtual safari hats and scoured the vast expanses of the internet in search of datasets that would allow us to conduct this peculiar investigation. With the help of the National Center for Education Statistics and the detective work of LSEG Analytics (Refinitiv), we gathered information on the number of Bachelor's degrees awarded in Agriculture and natural resources over the years 2012 to 2021. It was like panning for gold in a statistical river, sifting through the data to find the nuggets that would lead us to our fabled connection between academia and finance.

Statistical Analysis: To till the soil of our data and plant the seeds of statistical insight, we utilized a range of analytical tools. Our trusty scatter plots and regression analysis acted as our compass and map as we navigated the terrain of correlation. The aim was to cultivate a thorough understanding of the relationship, or lack thereof, between agricultural education and stock market performance.

Regression Model Cultivation: Like the careful cultivation of a vineyard, we sowed the seeds of our regression model, carefully selecting the predictor variables and tending to the coefficients with precision. Our model was delicately pruned to capture the nuances of the relationship, allowing us to weed out any spurious correlations and identify the true fruit-bearing vines of statistical significance.

Cross-Pollination and Sensitivity Analysis: Just as a bee flits from flower to flower, we engaged in a bit of statistical cross-pollination by subjecting our findings to rigorous sensitivity analysis. This allowed us to gauge the robustness of our results and ensure that they could withstand the gusts of skepticism that might blow in from the academic and financial community.

Ethical Harvesting: In the spirit of scientific integrity, we undertook the responsible and ethical harvesting of our statistical fruits, ensuring that our conclusions were grounded in sound methodology and unbiased analysis.

With our bushels of data and the tools of statistical agriculture at our disposal, we ventured forth into the uncharted territory where academia meets finance, ready to unearth the unexpected bounty that lay beneath the surface.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Bachelor's degrees awarded in Agriculture and natural resources and Bank of America's stock price (BAC). Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from National Center for Education Statistics and LSEG Analytics (Refinitiv) .

For the time period 2012 to 2021, you found a correlation 0.9477381, r-squared of 0.8982076, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"Agriculture, Natural Resources, and Finance: Sowing the Seeds of Stock Price Growth"

[[ABSTRACT]]
In this study, we delved into the unlikely correlation between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). By planting the seeds of curiosity, we utilized data from the National Center for Education Statistics and LSEG Analytics (Refinitiv) to explore whether there was a statistically significant relationship between these two seemingly unrelated domains. Our findings revealed a surprisingly strong correlation coefficient of 0.9477381 and a p-value of less than 0.01 for the period spanning from 2012 to 2021. So, while you may have thought "stock" when someone mentioned agriculture, our research suggests that there might just be some truth to that notion. This study offers a novel perspective on the interconnectedness of academic disciplines and financial markets, highlighting the potential for cross-pollination between fields that might initially appear as different as apples and oranges.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
As the age-old saying goes, "you reap what you sow." In the world of academia and finance, this phrase takes on a whole new meaning as we venture into the intriguing intersection of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). In this study, we embark on a quest to unearth the hidden roots of this unlikely correlation and explore the fertile ground where academia meets finance.
While it may seem like pairing broccoli and Wall Street, our curiosity led us to till the statistical soil and plant the seeds of inquiry. Who would have thought that the number of individuals receiving degrees in the agricultural and natural resources discipline could have any bearing on the stock price of a major financial institution? But as they say, truth can often be stranger than friction. It's one thing to expect high yields in an agricultural field, but expecting a fruitful relationship between academic degrees and stock market performance is a different crop altogether.
With our trowels sharpened and data in hand, we uncovered a statistically significant correlation coefficient of 0.9477381 and a p-value that would make even the most skeptical statistician take notice. This isn't just a fluctuation in the wind; it's a strong breeze of evidence blowing in from unexpected terrain. Just as a crop of corn can surprise you with its height, our findings may just upend conventional wisdom about the seemingly disparate worlds of academia and finance.
So, hold onto your hats as we navigate through the wheat fields of data and the stock market's financial forest. This study promises to offer a fresh perspective on the interconnectedness of academic disciplines and financial markets, serving up a tasty dish of interdisciplinary insights that are ripe for the picking. After all, who would have guessed that the humble agricultural sector could have such a profound impact on the not-so-humble stock price of Bank of America? Let's dig in!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our investigation into the unexpected relationship between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC) have certainly cultivated some intriguing findings. From 2012 to 2021, we unearthed a robust correlation coefficient of 0.9477381, signifying a remarkably strong association between these two seemingly disparate domains. It's as if we stumbled upon a hidden fertilizer for stock market success in a field we least expected!

The coefficient of determination (r-squared) of 0.8982076 further bolstered our findings, suggesting that a whopping 89.82% of the variability in Bank of America's stock price can be explained by changes in the number of Agriculture and natural resources Bachelor's degrees awarded. Who would have guessed that the fertile fields of academia could have such a strong impact on the financial harvest at the Bank of America?

Not to mention, our p-value of less than 0.01 adds an extra layer of significance to our results. This indicates that the likelihood of observing such a strong association between these variables by chance is slim to none. It's as if we've stumbled upon the statistical equivalent of finding a four-leaf clover in a field of data – a rare and remarkable discovery indeed!

For a visual representation of our groundbreaking findings, our scatterplot (Fig. 1) beautifully showcases the strong positive correlation between the number of Agriculture and natural resources Bachelor's degrees awarded and Bank of America's stock price. It's as if the data points themselves are shouting, "leaf it to us to show you the way to profits!"

In conclusion, our research not only sheds light on the unexpected relationship between academic degrees and financial market performance but also tills the soil of interdisciplinary inquiry, showing that the roots of one field can bear fruits in seemingly unrelated domains. So, while this research certainly sows the seeds of curiosity, it also harvests a bountiful crop of statistical evidence to demonstrate the surprising interconnectedness of these two fields. Who knew that the world of finance could have such a green thumb for the agricultural sector?


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Bachelor's degrees awarded in Agriculture and natural resources and Bank of America's stock price (BAC). Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Agriculture, Natural Resources, and Finance: Sowing the Seeds of Stock Price Growth"

[[ABSTRACT]]
In this study, we delved into the unlikely correlation between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). By planting the seeds of curiosity, we utilized data from the National Center for Education Statistics and LSEG Analytics (Refinitiv) to explore whether there was a statistically significant relationship between these two seemingly unrelated domains. Our findings revealed a surprisingly strong correlation coefficient of 0.9477381 and a p-value of less than 0.01 for the period spanning from 2012 to 2021. So, while you may have thought "stock" when someone mentioned agriculture, our research suggests that there might just be some truth to that notion. This study offers a novel perspective on the interconnectedness of academic disciplines and financial markets, highlighting the potential for cross-pollination between fields that might initially appear as different as apples and oranges.

[[LITERATURE REVIEW]]
The literature on the relationship between academic disciplines and financial markets is often as wide and varied as the fields of Agriculture and natural resources themselves. At the outset, seminal works by Smith et al. (2010), Doe and Jones (2015), and Brown (2018) have explored connections between educational trends and economic indicators, laying the groundwork for our investigation.
In "Harvesting Returns: Agricultural Education and Economic Outcomes" by Smith et al., the authors find an intriguing link between the number of Bachelor's degrees awarded in Agriculture and natural resources and the growth of local agricultural economies. The study's findings sprouted a newfound interest in understanding the broader implications of educational pursuits in this domain. Further, Doe and Jones (2015) shed light on the investment potential of knowledge-based sectors, signaling that the agricultural field may not just sow seeds but also sow the seeds of financial growth.
Moving beyond traditional academic research, non-fiction books such as "The Omnivore's Dilemma" by Michael Pollan and "The Hidden Life of Trees" by Peter Wohlleben have captivated readers with their insights into agricultural systems and natural resources, offering a leafy backdrop for our financial foray. On the fiction front, "Animal Farm" by George Orwell and "The Grapes of Wrath" by John Steinbeck beckon readers into the agricultural landscape, blending narrative fiction with socio-economic undertones.
Surprisingly enough, even cartoons and children's shows have inadvertently cultivated an interest in the intersection of agriculture and finance. The animated series "VeggieTales" and "Bob the Builder" may seem like child's play, but their themes of resource management and economic sustainability plant seeds of understanding about the importance of these sectors from an early age. And who could forget the classic "Captain Planet and the Planeteers," where environmental conservation and financial responsibility join forces to save the world?
As our exploration delves into the unexpected correlation between Bachelor's degrees in Agriculture and natural resources and the stock price of Bank of America (BAC), this colorful array of literature serves as a reminder that, much like a well-tended garden, interdisciplinary connections can yield unexpectedly fruitful results.

[[RESULTS]]
The results of our investigation into the unexpected relationship between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC) have certainly cultivated some intriguing findings. From 2012 to 2021, we unearthed a robust correlation coefficient of 0.9477381, signifying a remarkably strong association between these two seemingly disparate domains. It's as if we stumbled upon a hidden fertilizer for stock market success in a field we least expected!
The coefficient of determination (r-squared) of 0.8982076 further bolstered our findings, suggesting that a whopping 89.82% of the variability in Bank of America's stock price can be explained by changes in the number of Agriculture and natural resources Bachelor's degrees awarded. Who would have guessed that the fertile fields of academia could have such a strong impact on the financial harvest at the Bank of America?
Not to mention, our p-value of less than 0.01 adds an extra layer of significance to our results. This indicates that the likelihood of observing such a strong association between these variables by chance is slim to none. It's as if we've stumbled upon the statistical equivalent of finding a four-leaf clover in a field of data – a rare and remarkable discovery indeed!
For a visual representation of our groundbreaking findings, our scatterplot (Fig. 1) beautifully showcases the strong positive correlation between the number of Agriculture and natural resources Bachelor's degrees awarded and Bank of America's stock price. It's as if the data points themselves are shouting, "leaf it to us to show you the way to profits!"
In conclusion, our research not only sheds light on the unexpected relationship between academic degrees and financial market performance but also tills the soil of interdisciplinary inquiry, showing that the roots of one field can bear fruits in seemingly unrelated domains. So, while this research certainly sows the seeds of curiosity, it also harvests a bountiful crop of statistical evidence to demonstrate the surprising interconnectedness of these two fields. Who knew that the world of finance could have such a green thumb for the agricultural sector?

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our findings have uncovered a fertile ground for future research and have brought to light the interconnectedness of academia and the financial world. The statistically significant correlation between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC) serves as a testament to the unexpected tendrils of influence that stretch across seemingly disparate domains.

The prior research by Smith et al. (2010) and Doe and Jones (2015) provided a solid foundation for our investigation, much like sturdy trellises supporting the growth of vineyards. Their work on the economic impact of agricultural education and the investment potential of knowledge-based sectors resonates deeply with our findings, affirming the relevance of educational pursuits in these fields. While the connection between agricultural education and local economies has been established, our study extends this notion to the financial market, enriching the existing literature with unprecedented insights.

The literature review's exploration of non-fiction and fiction works, from "The Omnivore's Dilemma" to "The Grapes of Wrath," not only adds color to our research narrative but also underscores the enduring intellectual fascination with the agricultural and natural resource domains. These cultural touchstones serve as a gentle reminder that the influence of agriculture on various aspects of society, including finance, has been a perennial theme woven into the fabric of human experience.

Our results align with the prior literature on the economic implications of agricultural education and the potential for knowledge-based sectors to sow the seeds of financial growth. The robust correlation coefficient and the coefficient of determination gleaned from our statistical analysis provide compelling evidence of the substantial impact of Agriculture and natural resources education on the fluctuations in Bank of America's stock price. It's as if the financial market, like a thriving crop, responds sensitively to the nuanced changes in educational trends, cultivating a symbiotic relationship with the academic landscape.

The statistically significant p-value further bolsters the validity of our findings, reinforcing the notion that the observed association between these variables is not simply a fortuitous coincidence but a meaningful relationship worthy of scholarly attention. It's almost as if we stumbled upon the statistical equivalent of a pot of gold at the end of a rainbow, a rare and substantial discovery that beckons further exploration.

In essence, our research not only sows the seeds of curiosity but also reaps a bumper harvest of empirical evidence, underscoring the unexpected yet profound entwining of academia and finance. The tendrils of agricultural education branch out to touch the stock market in ways that have hitherto remained concealed, painting a picture of interdependence that transcends traditional disciplinary boundaries and blooming with the promise of intriguing future studies. Who would have thought that the world of finance could be so intimately intertwined with the agricultural sector?


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Bachelor's degrees awarded in Agriculture and natural resources and Bank of America's stock price (BAC). Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Agriculture, Natural Resources, and Finance: Sowing the Seeds of Stock Price Growth"

[[ABSTRACT]]
In this study, we delved into the unlikely correlation between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). By planting the seeds of curiosity, we utilized data from the National Center for Education Statistics and LSEG Analytics (Refinitiv) to explore whether there was a statistically significant relationship between these two seemingly unrelated domains. Our findings revealed a surprisingly strong correlation coefficient of 0.9477381 and a p-value of less than 0.01 for the period spanning from 2012 to 2021. So, while you may have thought "stock" when someone mentioned agriculture, our research suggests that there might just be some truth to that notion. This study offers a novel perspective on the interconnectedness of academic disciplines and financial markets, highlighting the potential for cross-pollination between fields that might initially appear as different as apples and oranges.

[[INTRDUCTION]]
As the age-old saying goes, "you reap what you sow." In the world of academia and finance, this phrase takes on a whole new meaning as we venture into the intriguing intersection of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). In this study, we embark on a quest to unearth the hidden roots of this unlikely correlation and explore the fertile ground where academia meets finance.
While it may seem like pairing broccoli and Wall Street, our curiosity led us to till the statistical soil and plant the seeds of inquiry. Who would have thought that the number of individuals receiving degrees in the agricultural and natural resources discipline could have any bearing on the stock price of a major financial institution? But as they say, truth can often be stranger than friction. It's one thing to expect high yields in an agricultural field, but expecting a fruitful relationship between academic degrees and stock market performance is a different crop altogether.
With our trowels sharpened and data in hand, we uncovered a statistically significant correlation coefficient of 0.9477381 and a p-value that would make even the most skeptical statistician take notice. This isn't just a fluctuation in the wind; it's a strong breeze of evidence blowing in from unexpected terrain. Just as a crop of corn can surprise you with its height, our findings may just upend conventional wisdom about the seemingly disparate worlds of academia and finance.
So, hold onto your hats as we navigate through the wheat fields of data and the stock market's financial forest. This study promises to offer a fresh perspective on the interconnectedness of academic disciplines and financial markets, serving up a tasty dish of interdisciplinary insights that are ripe for the picking. After all, who would have guessed that the humble agricultural sector could have such a profound impact on the not-so-humble stock price of Bank of America? Let's dig in!

[[RESULTS]]
The results of our investigation into the unexpected relationship between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC) have certainly cultivated some intriguing findings. From 2012 to 2021, we unearthed a robust correlation coefficient of 0.9477381, signifying a remarkably strong association between these two seemingly disparate domains. It's as if we stumbled upon a hidden fertilizer for stock market success in a field we least expected!
The coefficient of determination (r-squared) of 0.8982076 further bolstered our findings, suggesting that a whopping 89.82% of the variability in Bank of America's stock price can be explained by changes in the number of Agriculture and natural resources Bachelor's degrees awarded. Who would have guessed that the fertile fields of academia could have such a strong impact on the financial harvest at the Bank of America?
Not to mention, our p-value of less than 0.01 adds an extra layer of significance to our results. This indicates that the likelihood of observing such a strong association between these variables by chance is slim to none. It's as if we've stumbled upon the statistical equivalent of finding a four-leaf clover in a field of data – a rare and remarkable discovery indeed!
For a visual representation of our groundbreaking findings, our scatterplot (Fig. 1) beautifully showcases the strong positive correlation between the number of Agriculture and natural resources Bachelor's degrees awarded and Bank of America's stock price. It's as if the data points themselves are shouting, "leaf it to us to show you the way to profits!"
In conclusion, our research not only sheds light on the unexpected relationship between academic degrees and financial market performance but also tills the soil of interdisciplinary inquiry, showing that the roots of one field can bear fruits in seemingly unrelated domains. So, while this research certainly sows the seeds of curiosity, it also harvests a bountiful crop of statistical evidence to demonstrate the surprising interconnectedness of these two fields. Who knew that the world of finance could have such a green thumb for the agricultural sector?

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In closing, our research has brought to light an unexpectedly fruitful relationship between the world of academic agriculture and the fertile grounds of Bank of America’s stock price. It seems that while we may have started with a few seeds of skepticism, we have indeed reaped a rich harvest of statistically significant findings.

Our results have shown a correlation coefficient so strong, it’s as if it’s been bench-pressing data points in its spare time. With an r-squared value that explains nearly 90% of the variability, it's like finding the missing puzzle piece in a hedge maze.

As for the p-value, well, it’s clear that the likelihood of observing such a strong connection between these variables by pure chance is about as likely as finding a unicorn grazing in a statistics textbook.

Our scatterplot is not just a graph; it's a visual symphony of peas and queues, demonstrating the unexpected harmony between academic accolades and stock market success. It's like watching a field of financial flowers bloom under the nurturing care of agricultural education.

To put it simply, our research has plowed through the fields of academic and financial scholarship, unearthing a connection that could fertilize future interdisciplinary investigations. It's time to acknowledge that the world of finance and the world of agriculture might just be a match made in statistical heaven.

In conclusion, this study not only plants the seed of curiosity but also reaps a bountiful harvest of evidence, leaving little room for doubt. As for whether further research is needed in this area? We say, "lettuce not." This research has really brought home the bacon, and it’s time to cultivate new fields of statistical inquiry.


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 Agriculture, Natural Resources, and Finance: Sowing the Seeds of Stock Price Growth. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Agricultural Economics and Financial Management


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 Agriculture, Natural Resources, and Finance: Sowing the Seeds of Stock Price Growth. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Agribusiness Economics and Finance


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 Agriculture, Natural Resources, and Finance: Sowing the Seeds of Stock Price Growth with an abstract of In this study, we delved into the unlikely correlation between the number of Bachelor's degrees awarded in Agriculture and natural resources and the stock price of Bank of America (BAC). By planting the seeds of curiosity, we utilized data from the National Center for Education Statistics and LSEG Analytics (Refinitiv) to explore whether there was a statistically significant relationship between these two seemingly unrelated domains. Our findings revealed a surprisingly strong correlation coefficient of 0.9477381 and a p-value of less than 0.01 for the period spanning from 2012 to 2021. So, while you may have thought "stock" when someone mentioned agriculture, our research suggests that there might just be some truth to that notion. This study offers a novel perspective on the interconnectedness of academic disciplines and financial markets, highlighting the potential for cross-pollination between fields that might initially appear as different as apples and oranges.

ChatGPT:

agriculture bachelor's degrees, natural resources, stock price correlation, Bank of America stock price, agricultural education, finance and agriculture, agriculture and stock market, cross-disciplinary research, interconnection between academic disciplines, correlation analysis, agriculture and finance, bachelor's degree statistics, data analytics in finance

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



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Data details

Bachelor's degrees awarded in Agriculture
Detailed data title: Bachelor's degrees conferred by postsecondary institutions, in field of study: Agriculture and natural resources
Source: National Center for Education Statistics
See what else correlates with Bachelor's degrees awarded in Agriculture

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

See what else correlates with Bank of America's stock price (BAC)

Correlation r = 0.9477381 (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 = 0.8982076 (Coefficient of determination)
This means 89.8% of the change in the one variable (i.e., Bank of America's stock price (BAC)) is predictable based on the change in the other (i.e., Bachelor's degrees awarded in Agriculture) over the 10 years from 2012 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.06E-5. 0.0000306349554563168500000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.95 in 0.00306% of random cases. Said differently, if you correlated 32,642 random variables You don't actually need 32 thousand variables to find a correlation like this one. 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.

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 9 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 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.

[ 0.79, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
2012201320142015201620172018201920202021
Bachelor's degrees awarded in Agriculture (Degrees awarded)31629343043595337028378273878240334413734185841925
Bank of America's stock price (BAC) (Stock price)5.7512.0515.6917.9916.4522.629.7524.0835.3530.46




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
  4. 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. 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. 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([31629,34304,35953,37028,37827,38782,40334,41373,41858,41925,])
array_2 = np.array([5.75,12.05,15.69,17.99,16.45,22.6,29.75,24.08,35.35,30.46,])
array_1_name = "Bachelor's degrees awarded in Agriculture"
array_2_name = "Bank of America's stock price (BAC)"

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

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



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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."

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Correlation ID: 2160 · Black Variable ID: 1264 · Red Variable ID: 1570
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