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Spurious correlation #3,447 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Tallahassee and the second variable is BP's stock price (BP).  The chart goes from 2002 to 2023, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As air pollution in Tallahassee increased, more people may have turned to BP for their oil and gas needs, inadvertently boosting the company's stock price. It's like Tallahassee was giving BP a breath of fresh profits!

Model: dalle-3
Prompt: Prompt: Generate an image in the style of a TIME magazine cover depicting Tallahassee with once smoggy horizons now replaced by clear blue skies. Show residents joyfully biking to work with a noticeable decrease in air pollution. Include a prominent display of the BP stock ticker showing a steady upward trend, representing increased demand for petroleum products and driving up their stock price. 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: Air pollution in Tallahassee and BP's stock price (BP). 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: inspired by bauhaus Cybernetic art Cutsy art illustration A TIME magazine cover image Magic realism
ChatGPT: A TIME magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Tallahassee and BP's stock price (BP), in the following situation: As air pollution decreased in Tallahassee, residents started biking more, leading to a surge in demand for BP's petroleum products and driving up their stock price.. Keep the description simple.
ChatGPT: In Tallahassee, clear blue skies replace the once smoggy horizon as the air pollution decreases. On the bustling streets, residents are seen happily biking to work and enjoying the fresh air. Meanwhile, the stock ticker for BP displays a steady upward trend, indicating a surge in demand for their petroleum products, driving up their stock price.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A TIME magazine cover image ] and depicting this scene: In Tallahassee, clear blue skies replace the once smoggy horizon as the air pollution decreases. On the bustling streets, residents are seen happily biking to work and enjoying the fresh air. Meanwhile, the stock ticker for BP displays a steady upward trend, indicating a surge in demand for their petroleum products, driving up their stock price. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image in the style of a TIME magazine cover depicting Tallahassee with once smoggy horizons now replaced by clear blue skies. Show residents joyfully biking to work with a noticeable decrease in air pollution. Include a prominent display of the BP stock ticker showing a steady upward trend, representing increased demand for petroleum products and driving up their stock price.

*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 increases in Air pollution in Tallahassee positively influenced BP's stock price (BP). Include one good pun.

AI academic paper

(Because p < 0.01)
The Polluted Peculiarities: Probing the Pecuniary Pertinence of Air Pollution in Tallahassee on BP's Bottom Line

The Journal of Ecological Economics and Environmental Epidemiology

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 Air pollution in Tallahassee and BP's stock price (BP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Make the title an alliteration.

Your research team used data from Environmental Protection Agency and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.8213367 and p < 0.01 for 2002 to 2023.

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]]
The Polluted Peculiarities: Probing the Pecuniary Pertinence of Air Pollution in Tallahassee on BP's Bottom Line

[[ABSTRACT]]
In this empirical investigation, we unravel the enigmatic connection between air pollution levels in Tallahassee and the stock price of BP. With a nod to the alliterative allure of our inquiry, we enlist data from the Environmental Protection Agency and LSEG Analytics (Refinitiv) to scrutinize this captivating convergence. Employing cutting-edge statistical techniques, we uncover a robust correlation coefficient of 0.8213367 and decisively demonstrate a statistically significant relationship (p < 0.01) over the period spanning from 2002 to 2023.

In a twist of fate as unexpected as finding a diamond in a haystack, our findings paint a portrait of how the whims of the wind carry not just pollutants, but also influence the financial fortunes of businesses. Our results suggest that as air quality in Tallahassee wanes, so does the appeal of BP's stock. We posit that this association could be considered an "ille-gas-y", shifting the conventional paradigm of stock price determinants.

So, next time you take a breath of fresh air in Tallahassee, spare a thought for BP's stockholders, for their financial fate is inextricably tied to the capricious currents of air pollution.


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 Air pollution in Tallahassee and BP's stock price (BP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
The Polluted Peculiarities: Probing the Pecuniary Pertinence of Air Pollution in Tallahassee on BP's Bottom Line

[[ABSTRACT]]
In this empirical investigation, we unravel the enigmatic connection between air pollution levels in Tallahassee and the stock price of BP. With a nod to the alliterative allure of our inquiry, we enlist data from the Environmental Protection Agency and LSEG Analytics (Refinitiv) to scrutinize this captivating convergence. Employing cutting-edge statistical techniques, we uncover a robust correlation coefficient of 0.8213367 and decisively demonstrate a statistically significant relationship (p < 0.01) over the period spanning from 2002 to 2023.

In a twist of fate as unexpected as finding a diamond in a haystack, our findings paint a portrait of how the whims of the wind carry not just pollutants, but also influence the financial fortunes of businesses. Our results suggest that as air quality in Tallahassee wanes, so does the appeal of BP's stock. We posit that this association could be considered an "ille-gas-y", shifting the conventional paradigm of stock price determinants.

So, next time you take a breath of fresh air in Tallahassee, spare a thought for BP's stockholders, for their financial fate is inextricably tied to the capricious currents of air pollution.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The intersection of environmental factors and financial markets has long been a source of intrigue and speculation. As researchers, we are constantly seeking to unearth unexpected connections, much like a geologist uncovers hidden gems. In this vein, our investigation delves into the peculiar relationship between air pollution in Tallahassee and the stock price of BP. It's a tale of two seemingly disparate domains coming together in an unanticipated duet, akin to a chemical reaction that produces an unexpected compound.

According to our investigation, when it comes to the correlation between air pollution in Tallahassee and BP's stock price, the plot thickens as much as a roux in a Cajun gumbo! We embarked on this venture armed with statistical tools and a healthy dose of skepticism, yet as the data unfolded, we found ourselves in the midst of an unpredictable plot twist—much like a suspenseful thriller with an unexpected ending. The findings unwittingly revealed a conflation of seemingly unrelated spheres: the realm of emissions and the pulse of the stock market, intertwined like polar molecules in a solvent.

It's no mere coincidence that we opted to delve into this topic. The air pollution puzzle in Tallahassee confronts us with a conundrum, akin to Schroedinger's cat paradox, where the uncertain resides at the heart of the matter. Statistical rigor demands that we leave no hypothesis untested, much like a scientist carefully examining a petri dish filled with myriad possibilities. Our inquiry is much like peeling an onion; each layer reveals an additional facet of the intertwined relationship between the atmosphere and financial instruments.

In our quest to explore this unusual juxtaposition, we did encounter a fair share of obstacles, not unlike a hiker navigating a rugged mountain trail. However, armed with our statistical compass and theorems as sturdy as the peaks of the Alps, we persevered. The findings of this research, much like a rare specimen discovered in the wild, captivate and provoke reflection on the intricacies of the business world and the environment. It certainly gives a new meaning to the phrase "taking stock" of environmental factors!

Stay tuned for the unfolding narrative of our investigation, where air pollution and stock prices intertwine in a manner that may just leave you gasping for breath or contemplating your investment portfolio with a newfound sense of environmental awareness.


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 Air pollution in Tallahassee and BP's stock price (BP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
The Polluted Peculiarities: Probing the Pecuniary Pertinence of Air Pollution in Tallahassee on BP's Bottom Line

[[ABSTRACT]]
In this empirical investigation, we unravel the enigmatic connection between air pollution levels in Tallahassee and the stock price of BP. With a nod to the alliterative allure of our inquiry, we enlist data from the Environmental Protection Agency and LSEG Analytics (Refinitiv) to scrutinize this captivating convergence. Employing cutting-edge statistical techniques, we uncover a robust correlation coefficient of 0.8213367 and decisively demonstrate a statistically significant relationship (p < 0.01) over the period spanning from 2002 to 2023.

In a twist of fate as unexpected as finding a diamond in a haystack, our findings paint a portrait of how the whims of the wind carry not just pollutants, but also influence the financial fortunes of businesses. Our results suggest that as air quality in Tallahassee wanes, so does the appeal of BP's stock. We posit that this association could be considered an "ille-gas-y", shifting the conventional paradigm of stock price determinants.

So, next time you take a breath of fresh air in Tallahassee, spare a thought for BP's stockholders, for their financial fate is inextricably tied to the capricious currents of air pollution.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of environmental factors and financial markets has long been a source of intrigue and speculation. As researchers, we are constantly seeking to unearth unexpected connections, much like a geologist uncovers hidden gems. In this vein, our investigation delves into the peculiar relationship between air pollution in Tallahassee and the stock price of BP. It's a tale of two seemingly disparate domains coming together in an unanticipated duet, akin to a chemical reaction that produces an unexpected compound.
According to our investigation, when it comes to the correlation between air pollution in Tallahassee and BP's stock price, the plot thickens as much as a roux in a Cajun gumbo! We embarked on this venture armed with statistical tools and a healthy dose of skepticism, yet as the data unfolded, we found ourselves in the midst of an unpredictable plot twist—much like a suspenseful thriller with an unexpected ending. The findings unwittingly revealed a conflation of seemingly unrelated spheres: the realm of emissions and the pulse of the stock market, intertwined like polar molecules in a solvent.
It's no mere coincidence that we opted to delve into this topic. The air pollution puzzle in Tallahassee confronts us with a conundrum, akin to Schroedinger's cat paradox, where the uncertain resides at the heart of the matter. Statistical rigor demands that we leave no hypothesis untested, much like a scientist carefully examining a petri dish filled with myriad possibilities. Our inquiry is much like peeling an onion; each layer reveals an additional facet of the intertwined relationship between the atmosphere and financial instruments.
In our quest to explore this unusual juxtaposition, we did encounter a fair share of obstacles, not unlike a hiker navigating a rugged mountain trail. However, armed with our statistical compass and theorems as sturdy as the peaks of the Alps, we persevered. The findings of this research, much like a rare specimen discovered in the wild, captivate and provoke reflection on the intricacies of the business world and the environment. It certainly gives a new meaning to the phrase "taking stock" of environmental factors!
Stay tuned for the unfolding narrative of our investigation, where air pollution and stock prices intertwine in a manner that may just leave you gasping for breath or contemplating your investment portfolio with a newfound sense of environmental awareness.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The relationship between air pollution and financial markets has been a topic of interest among scholars and analysts for decades. In "Air Quality and Financial Markets," Smith et al. (2015) reveal the potential impact of air pollution on stock prices, highlighting the significance of environmental factors in shaping economic outcomes. Similarly, Doe and Jones (2017) argue in their work, "The Invisible Hand of Pollution," that air quality is an essential consideration for investors and businesses, with far-reaching implications for market performance.

It's important to note the potential impact of unexpected factors on stock prices, much like a surprise birthday party can turn an otherwise ordinary day into a memorable affair. In "The Black Swan: The Impact of the Highly Improbable," Taleb (2007) underscores the significance of unforeseen events in financial markets, providing a thought-provoking parallel to the unexpected findings of our investigation.

In a more fictional but no less intriguing realm, the works of Michael Crichton, particularly "State of Fear" and "Prey," offer captivating narratives that integrate environmental elements with financial intrigue. While not academic in nature, these novels inject a sense of suspense and drama into the otherwise staid world of empirical research. Sometimes, a dash of fiction can add pizzazz to the otherwise buttoned-up confines of scholarly research, much like adding a sprinkle of cinnamon to a cup of hot cocoa.

In perusing social media channels, the authors stumbled upon a tweet by @EnviroEconGuru, which mused, "Is there a correlation between air pollution in Tallahassee and BP's stock price? #StocksAndSmog #UnlikelyBedfellows." Such informal musings, while perhaps lacking the methodological rigor of an academic study, nonetheless underscore the topicality and interest of this unexpected connection.

Given the gravity of our findings, it's clear that the association between air pollution in Tallahassee and BP's stock price is more than just a passing curiosity. As we untangle the web of factors influencing stock performance, it becomes increasingly apparent that even the breeze in Tallahassee carries tidings of financial import. Much like a gust of wind can unexpectedly rustle one's papers, the whims of air pollution in Tallahassee can unexpectedly ruffle the feathers of BP's stock price.


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 Air pollution in Tallahassee and BP's stock price (BP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and LSEG Analytics (Refinitiv) . You used data from 2002 to 2023

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]]
The Polluted Peculiarities: Probing the Pecuniary Pertinence of Air Pollution in Tallahassee on BP's Bottom Line

[[ABSTRACT]]
In this empirical investigation, we unravel the enigmatic connection between air pollution levels in Tallahassee and the stock price of BP. With a nod to the alliterative allure of our inquiry, we enlist data from the Environmental Protection Agency and LSEG Analytics (Refinitiv) to scrutinize this captivating convergence. Employing cutting-edge statistical techniques, we uncover a robust correlation coefficient of 0.8213367 and decisively demonstrate a statistically significant relationship (p < 0.01) over the period spanning from 2002 to 2023.

In a twist of fate as unexpected as finding a diamond in a haystack, our findings paint a portrait of how the whims of the wind carry not just pollutants, but also influence the financial fortunes of businesses. Our results suggest that as air quality in Tallahassee wanes, so does the appeal of BP's stock. We posit that this association could be considered an "ille-gas-y", shifting the conventional paradigm of stock price determinants.

So, next time you take a breath of fresh air in Tallahassee, spare a thought for BP's stockholders, for their financial fate is inextricably tied to the capricious currents of air pollution.

[[INTRODUCTION]]
The intersection of environmental factors and financial markets has long been a source of intrigue and speculation. As researchers, we are constantly seeking to unearth unexpected connections, much like a geologist uncovers hidden gems. In this vein, our investigation delves into the peculiar relationship between air pollution in Tallahassee and the stock price of BP. It's a tale of two seemingly disparate domains coming together in an unanticipated duet, akin to a chemical reaction that produces an unexpected compound.
According to our investigation, when it comes to the correlation between air pollution in Tallahassee and BP's stock price, the plot thickens as much as a roux in a Cajun gumbo! We embarked on this venture armed with statistical tools and a healthy dose of skepticism, yet as the data unfolded, we found ourselves in the midst of an unpredictable plot twist—much like a suspenseful thriller with an unexpected ending. The findings unwittingly revealed a conflation of seemingly unrelated spheres: the realm of emissions and the pulse of the stock market, intertwined like polar molecules in a solvent.
It's no mere coincidence that we opted to delve into this topic. The air pollution puzzle in Tallahassee confronts us with a conundrum, akin to Schroedinger's cat paradox, where the uncertain resides at the heart of the matter. Statistical rigor demands that we leave no hypothesis untested, much like a scientist carefully examining a petri dish filled with myriad possibilities. Our inquiry is much like peeling an onion; each layer reveals an additional facet of the intertwined relationship between the atmosphere and financial instruments.
In our quest to explore this unusual juxtaposition, we did encounter a fair share of obstacles, not unlike a hiker navigating a rugged mountain trail. However, armed with our statistical compass and theorems as sturdy as the peaks of the Alps, we persevered. The findings of this research, much like a rare specimen discovered in the wild, captivate and provoke reflection on the intricacies of the business world and the environment. It certainly gives a new meaning to the phrase "taking stock" of environmental factors!
Stay tuned for the unfolding narrative of our investigation, where air pollution and stock prices intertwine in a manner that may just leave you gasping for breath or contemplating your investment portfolio with a newfound sense of environmental awareness.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To investigate the intriguing relationship between air pollution in Tallahassee and the stock price of BP, we employed a multifaceted approach, akin to a prism revealing the diverse spectra of this complex association. Our data collection, much like a scavenger hunt, sought out treasures across the digital landscape, with a particular focus on information from the Environmental Protection Agency and LSEG Analytics (Refinitiv). Gathering data spanning the years 2002 to 2023, we navigated through the virtual wilderness, harnessing the power of the information superhighway to procure our dataset.

In a twist of fate as unexpected as finding a diamond in a haystack, we sought to harness the power of statistical analyses that would pierce through the fog of uncertainty and shed light on the relationship between these seemingly disparate variables. Our analytical arsenal included the stalwart Pearson correlation coefficient, serving as the compass guiding us through the mists of the data, alongside a battery of regressions to unravel the monetary implications of air quality fluctuation on BP's stock price.

We approached our statistical models with the same precision as a surgeon wielding a scalpel, ensuring that our assumptions held true and our specifications were as firm as a finely tuned instrument. To mitigate the risk of confounding variables playing the part of an unruly troupe on our research stage, we diligently controlled for other environmental and market factors, ensuring that our results painted a clear picture of the singular influence of air pollution in Tallahassee on BP's stock performance.

While our methods may seem as convoluted as a labyrinth, we remained steadfast in our dedication to unraveling this enigmatic connection. With tenacity reminiscent of a detective untangling a web of clues, we scrutinized the data with an unwavering commitment to uncovering the underlying patterns and relationships.

Now, let's take a breather and delve into the labyrinth of statistical analyses, where the winds of data and the tides of stock prices come together in a harmonious dance, revealing the interconnectedness of seemingly incongruent domains.


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 Air pollution in Tallahassee and BP's stock price (BP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and LSEG Analytics (Refinitiv) .

For the time period 2002 to 2023, you found a correlation 0.8213367, r-squared of 0.6745940, 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]]
The Polluted Peculiarities: Probing the Pecuniary Pertinence of Air Pollution in Tallahassee on BP's Bottom Line

[[ABSTRACT]]
In this empirical investigation, we unravel the enigmatic connection between air pollution levels in Tallahassee and the stock price of BP. With a nod to the alliterative allure of our inquiry, we enlist data from the Environmental Protection Agency and LSEG Analytics (Refinitiv) to scrutinize this captivating convergence. Employing cutting-edge statistical techniques, we uncover a robust correlation coefficient of 0.8213367 and decisively demonstrate a statistically significant relationship (p < 0.01) over the period spanning from 2002 to 2023.

In a twist of fate as unexpected as finding a diamond in a haystack, our findings paint a portrait of how the whims of the wind carry not just pollutants, but also influence the financial fortunes of businesses. Our results suggest that as air quality in Tallahassee wanes, so does the appeal of BP's stock. We posit that this association could be considered an "ille-gas-y", shifting the conventional paradigm of stock price determinants.

So, next time you take a breath of fresh air in Tallahassee, spare a thought for BP's stockholders, for their financial fate is inextricably tied to the capricious currents of air pollution.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intersection of environmental factors and financial markets has long been a source of intrigue and speculation. As researchers, we are constantly seeking to unearth unexpected connections, much like a geologist uncovers hidden gems. In this vein, our investigation delves into the peculiar relationship between air pollution in Tallahassee and the stock price of BP. It's a tale of two seemingly disparate domains coming together in an unanticipated duet, akin to a chemical reaction that produces an unexpected compound.
According to our investigation, when it comes to the correlation between air pollution in Tallahassee and BP's stock price, the plot thickens as much as a roux in a Cajun gumbo! We embarked on this venture armed with statistical tools and a healthy dose of skepticism, yet as the data unfolded, we found ourselves in the midst of an unpredictable plot twist—much like a suspenseful thriller with an unexpected ending. The findings unwittingly revealed a conflation of seemingly unrelated spheres: the realm of emissions and the pulse of the stock market, intertwined like polar molecules in a solvent.
It's no mere coincidence that we opted to delve into this topic. The air pollution puzzle in Tallahassee confronts us with a conundrum, akin to Schroedinger's cat paradox, where the uncertain resides at the heart of the matter. Statistical rigor demands that we leave no hypothesis untested, much like a scientist carefully examining a petri dish filled with myriad possibilities. Our inquiry is much like peeling an onion; each layer reveals an additional facet of the intertwined relationship between the atmosphere and financial instruments.
In our quest to explore this unusual juxtaposition, we did encounter a fair share of obstacles, not unlike a hiker navigating a rugged mountain trail. However, armed with our statistical compass and theorems as sturdy as the peaks of the Alps, we persevered. The findings of this research, much like a rare specimen discovered in the wild, captivate and provoke reflection on the intricacies of the business world and the environment. It certainly gives a new meaning to the phrase "taking stock" of environmental factors!
Stay tuned for the unfolding narrative of our investigation, where air pollution and stock prices intertwine in a manner that may just leave you gasping for breath or contemplating your investment portfolio with a newfound sense of environmental awareness.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

A statistical analysis of the relationship between air pollution levels in Tallahassee and BP's stock price reveals an intriguing narrative. The correlation coefficient of 0.8213367 indicates a strong positive relationship between these seemingly unrelated variables. In statistical terms, it's as if they are "pollution pals" echoing each other's movements.

The r-squared value of 0.6745940 further illuminates this connection, demonstrating that over 67% of the variability in BP's stock price can be explained by changes in air pollution levels. It's as if the air pollution levels are whispering stock tips into the market's ear, influencing BP's financial fate more than one might expect.

We also found a statistically significant relationship with a p-value of less than 0.01, indicating that the observed association between air pollution in Tallahassee and BP's stock price is unlikely to be due to random chance. It's a result so significant, it's practically "polluting" the landscape of traditional stock price determinants.

Notably, the scatterplot (Fig. 1) visually depicts the strong positive relationship between air pollution in Tallahassee and BP's stock price. It looks as if the data points are holding hands, skipping along in perfect unison—truly a sight to "smog" about!

This unexpected interconnection between the whims of air pollution and the fortunes of BP's stock price highlights the pervasive impact of environmental factors on the financial realm. It's a revelation that not only captures the attention but also elicits a chuckle at the unexpected dance of these variables.

In summary, the statistical evidence indicates that air pollution in Tallahassee exerts a notable influence on the stock price of BP. Our findings provide a unique perspective on the intricate relationship between environmental factors and financial markets, adding a touch of "atmos-fear" to the traditional understanding of stock price determinants.


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 Air pollution in Tallahassee and BP's stock price (BP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
The Polluted Peculiarities: Probing the Pecuniary Pertinence of Air Pollution in Tallahassee on BP's Bottom Line

[[ABSTRACT]]
In this empirical investigation, we unravel the enigmatic connection between air pollution levels in Tallahassee and the stock price of BP. With a nod to the alliterative allure of our inquiry, we enlist data from the Environmental Protection Agency and LSEG Analytics (Refinitiv) to scrutinize this captivating convergence. Employing cutting-edge statistical techniques, we uncover a robust correlation coefficient of 0.8213367 and decisively demonstrate a statistically significant relationship (p < 0.01) over the period spanning from 2002 to 2023.

In a twist of fate as unexpected as finding a diamond in a haystack, our findings paint a portrait of how the whims of the wind carry not just pollutants, but also influence the financial fortunes of businesses. Our results suggest that as air quality in Tallahassee wanes, so does the appeal of BP's stock. We posit that this association could be considered an "ille-gas-y", shifting the conventional paradigm of stock price determinants.

So, next time you take a breath of fresh air in Tallahassee, spare a thought for BP's stockholders, for their financial fate is inextricably tied to the capricious currents of air pollution.

[[LITERATURE REVIEW]]
The relationship between air pollution and financial markets has been a topic of interest among scholars and analysts for decades. In "Air Quality and Financial Markets," Smith et al. (2015) reveal the potential impact of air pollution on stock prices, highlighting the significance of environmental factors in shaping economic outcomes. Similarly, Doe and Jones (2017) argue in their work, "The Invisible Hand of Pollution," that air quality is an essential consideration for investors and businesses, with far-reaching implications for market performance.
It's important to note the potential impact of unexpected factors on stock prices, much like a surprise birthday party can turn an otherwise ordinary day into a memorable affair. In "The Black Swan: The Impact of the Highly Improbable," Taleb (2007) underscores the significance of unforeseen events in financial markets, providing a thought-provoking parallel to the unexpected findings of our investigation.
In a more fictional but no less intriguing realm, the works of Michael Crichton, particularly "State of Fear" and "Prey," offer captivating narratives that integrate environmental elements with financial intrigue. While not academic in nature, these novels inject a sense of suspense and drama into the otherwise staid world of empirical research. Sometimes, a dash of fiction can add pizzazz to the otherwise buttoned-up confines of scholarly research, much like adding a sprinkle of cinnamon to a cup of hot cocoa.
In perusing social media channels, the authors stumbled upon a tweet by @EnviroEconGuru, which mused, "Is there a correlation between air pollution in Tallahassee and BP's stock price? #StocksAndSmog #UnlikelyBedfellows." Such informal musings, while perhaps lacking the methodological rigor of an academic study, nonetheless underscore the topicality and interest of this unexpected connection.
Given the gravity of our findings, it's clear that the association between air pollution in Tallahassee and BP's stock price is more than just a passing curiosity. As we untangle the web of factors influencing stock performance, it becomes increasingly apparent that even the breeze in Tallahassee carries tidings of financial import. Much like a gust of wind can unexpectedly rustle one's papers, the whims of air pollution in Tallahassee can unexpectedly ruffle the feathers of BP's stock price.

[[RESULTS]]
A statistical analysis of the relationship between air pollution levels in Tallahassee and BP's stock price reveals an intriguing narrative. The correlation coefficient of 0.8213367 indicates a strong positive relationship between these seemingly unrelated variables. In statistical terms, it's as if they are "pollution pals" echoing each other's movements.
The r-squared value of 0.6745940 further illuminates this connection, demonstrating that over 67% of the variability in BP's stock price can be explained by changes in air pollution levels. It's as if the air pollution levels are whispering stock tips into the market's ear, influencing BP's financial fate more than one might expect.
We also found a statistically significant relationship with a p-value of less than 0.01, indicating that the observed association between air pollution in Tallahassee and BP's stock price is unlikely to be due to random chance. It's a result so significant, it's practically "polluting" the landscape of traditional stock price determinants.
Notably, the scatterplot (Fig. 1) visually depicts the strong positive relationship between air pollution in Tallahassee and BP's stock price. It looks as if the data points are holding hands, skipping along in perfect unison—truly a sight to "smog" about!
This unexpected interconnection between the whims of air pollution and the fortunes of BP's stock price highlights the pervasive impact of environmental factors on the financial realm. It's a revelation that not only captures the attention but also elicits a chuckle at the unexpected dance of these variables.
In summary, the statistical evidence indicates that air pollution in Tallahassee exerts a notable influence on the stock price of BP. Our findings provide a unique perspective on the intricate relationship between environmental factors and financial markets, adding a touch of "atmos-fear" to the traditional understanding of stock price determinants.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our findings unveil a compelling connection between air pollution levels in Tallahassee and BP's stock price, shedding light on the remarkable interplay between atmospheric quality and financial markets. Our study builds upon prior research, as we corroborate the work of Smith et al. (2015) and Doe and Jones (2017) by demonstrating a strong and statistically significant relationship between air pollution and stock prices, akin to the way a good pun can't help but elicit a chuckle.

The robust correlation coefficient of 0.8213367 we discovered aligns with the previous literature, affirming the influence of air pollution on stock prices. This correlation is as clear as the smog in a city with heavy air pollution - you simply can't miss it!

Our results also align with the musings of @EnviroEconGuru, showing that sometimes informal, speculative thoughts shared on social media platforms can lead to unexpected and enlightening research endeavors. In the realm of academic research, it's as though social media can sometimes blow in unexpected winds of insight, much like the unpredictability of air pollution in Tallahassee.

The statistically significant relationship we uncovered, with a p-value of less than 0.01, firmly supports the hypothesis that air pollution in Tallahassee and BP's stock price are linked. It's a finding so significant, it's like discovering a treasure in a sea of statistical analyses - a true "pollution treasure," if you will.

Our study not only contributes to the scholarly literature but also brings an element of surprise and intrigue to the otherwise staid world of empirical research. The correlation found in our study can be likened to a good dad joke - it's unexpected, yet undeniably amusing.

In conclusion, our investigation not only adds to the burgeoning body of knowledge on the intersection of environmental factors and financial markets but also injects a sense of playfulness and wonder into the traditionally serious realm of empirical research. It's as if the unexpected connection between air pollution in Tallahassee and BP's stock price has breathed a breath of fresh air into the world of statistics, revealing the delightful complexities of the data.


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 Air pollution in Tallahassee and BP's stock price (BP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The Polluted Peculiarities: Probing the Pecuniary Pertinence of Air Pollution in Tallahassee on BP's Bottom Line

[[ABSTRACT]]
In this empirical investigation, we unravel the enigmatic connection between air pollution levels in Tallahassee and the stock price of BP. With a nod to the alliterative allure of our inquiry, we enlist data from the Environmental Protection Agency and LSEG Analytics (Refinitiv) to scrutinize this captivating convergence. Employing cutting-edge statistical techniques, we uncover a robust correlation coefficient of 0.8213367 and decisively demonstrate a statistically significant relationship (p < 0.01) over the period spanning from 2002 to 2023.

In a twist of fate as unexpected as finding a diamond in a haystack, our findings paint a portrait of how the whims of the wind carry not just pollutants, but also influence the financial fortunes of businesses. Our results suggest that as air quality in Tallahassee wanes, so does the appeal of BP's stock. We posit that this association could be considered an "ille-gas-y", shifting the conventional paradigm of stock price determinants.

So, next time you take a breath of fresh air in Tallahassee, spare a thought for BP's stockholders, for their financial fate is inextricably tied to the capricious currents of air pollution.

[[INTRDUCTION]]
The intersection of environmental factors and financial markets has long been a source of intrigue and speculation. As researchers, we are constantly seeking to unearth unexpected connections, much like a geologist uncovers hidden gems. In this vein, our investigation delves into the peculiar relationship between air pollution in Tallahassee and the stock price of BP. It's a tale of two seemingly disparate domains coming together in an unanticipated duet, akin to a chemical reaction that produces an unexpected compound.
According to our investigation, when it comes to the correlation between air pollution in Tallahassee and BP's stock price, the plot thickens as much as a roux in a Cajun gumbo! We embarked on this venture armed with statistical tools and a healthy dose of skepticism, yet as the data unfolded, we found ourselves in the midst of an unpredictable plot twist—much like a suspenseful thriller with an unexpected ending. The findings unwittingly revealed a conflation of seemingly unrelated spheres: the realm of emissions and the pulse of the stock market, intertwined like polar molecules in a solvent.
It's no mere coincidence that we opted to delve into this topic. The air pollution puzzle in Tallahassee confronts us with a conundrum, akin to Schroedinger's cat paradox, where the uncertain resides at the heart of the matter. Statistical rigor demands that we leave no hypothesis untested, much like a scientist carefully examining a petri dish filled with myriad possibilities. Our inquiry is much like peeling an onion; each layer reveals an additional facet of the intertwined relationship between the atmosphere and financial instruments.
In our quest to explore this unusual juxtaposition, we did encounter a fair share of obstacles, not unlike a hiker navigating a rugged mountain trail. However, armed with our statistical compass and theorems as sturdy as the peaks of the Alps, we persevered. The findings of this research, much like a rare specimen discovered in the wild, captivate and provoke reflection on the intricacies of the business world and the environment. It certainly gives a new meaning to the phrase "taking stock" of environmental factors!
Stay tuned for the unfolding narrative of our investigation, where air pollution and stock prices intertwine in a manner that may just leave you gasping for breath or contemplating your investment portfolio with a newfound sense of environmental awareness.

[[RESULTS]]
A statistical analysis of the relationship between air pollution levels in Tallahassee and BP's stock price reveals an intriguing narrative. The correlation coefficient of 0.8213367 indicates a strong positive relationship between these seemingly unrelated variables. In statistical terms, it's as if they are "pollution pals" echoing each other's movements.
The r-squared value of 0.6745940 further illuminates this connection, demonstrating that over 67% of the variability in BP's stock price can be explained by changes in air pollution levels. It's as if the air pollution levels are whispering stock tips into the market's ear, influencing BP's financial fate more than one might expect.
We also found a statistically significant relationship with a p-value of less than 0.01, indicating that the observed association between air pollution in Tallahassee and BP's stock price is unlikely to be due to random chance. It's a result so significant, it's practically "polluting" the landscape of traditional stock price determinants.
Notably, the scatterplot (Fig. 1) visually depicts the strong positive relationship between air pollution in Tallahassee and BP's stock price. It looks as if the data points are holding hands, skipping along in perfect unison—truly a sight to "smog" about!
This unexpected interconnection between the whims of air pollution and the fortunes of BP's stock price highlights the pervasive impact of environmental factors on the financial realm. It's a revelation that not only captures the attention but also elicits a chuckle at the unexpected dance of these variables.
In summary, the statistical evidence indicates that air pollution in Tallahassee exerts a notable influence on the stock price of BP. Our findings provide a unique perspective on the intricate relationship between environmental factors and financial markets, adding a touch of "atmos-fear" to the traditional understanding of stock price determinants.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has uncovered a compelling association between air pollution in Tallahassee and the stock price of BP, illuminating a whimsical waltz between the environmental and financial spheres. This unexpected symbiosis of pollutants and profits serves as a reminder that the winds of change carry more than just whispers of air. In the world of statistics, we often seek to unveil hidden connections, but this correlation is akin to discovering that the famed Dr. Jekyll had a financial alter ego, Mr. Hyde.

Our findings, represented by a correlation coefficient as robust as an oak tree in a storm, indicate a strong positive relationship between air pollution levels in Tallahassee and BP's stock price. It's as if they are partners in grime, dancing to the rhythm of economic uncertainty. With an r-squared value that explains over two-thirds of the variability in BP's stock price, the influence of air pollution is as clear as a blue sky turned hazy with pollutants. It's a statistical revelation that even the most hardened number cruncher couldn't "methane".

Furthermore, our results boast a statistically significant relationship, indicating that the observed association between air pollution in Tallahassee and BP's stock price is no mere fluke. It's a result so striking that it leaves traditional stock price determinants "gasping for air".

In light of these findings, we assert that no further research in this area is needed, unless, of course, one wishes to explore the "uplifting" effect of air quality on stock prices. As for now, let's say our findings stand as firm as a redwood in the forest, shedding light on the unexpected interplay between environmental factors and financial markets.

No further research is needed in this area.


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 The Polluted Peculiarities: Probing the Pecuniary Pertinence of Air Pollution in Tallahassee on BP's Bottom Line. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Ecological Economics and Environmental Epidemiology


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 The Polluted Peculiarities: Probing the Pecuniary Pertinence of Air Pollution in Tallahassee on BP's Bottom Line. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Environmental Economics and Policy 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 The Polluted Peculiarities: Probing the Pecuniary Pertinence of Air Pollution in Tallahassee on BP's Bottom Line with an abstract of In this empirical investigation, we unravel the enigmatic connection between air pollution levels in Tallahassee and the stock price of BP. With a nod to the alliterative allure of our inquiry, we enlist data from the Environmental Protection Agency and LSEG Analytics (Refinitiv) to scrutinize this captivating convergence. Employing cutting-edge statistical techniques, we uncover a robust correlation coefficient of 0.8213367 and decisively demonstrate a statistically significant relationship (p < 0.01) over the period spanning from 2002 to 2023.
In a twist of fate as unexpected as finding a diamond in a haystack, our findings paint a portrait of how the whims of the wind carry not just pollutants, but also influence the financial fortunes of businesses. Our results suggest that as air quality in Tallahassee wanes, so does the appeal of BP's stock. We posit that this association could be considered an "ille-gas-y", shifting the conventional paradigm of stock price determinants.
So, next time you take a breath of fresh air in Tallahassee, spare a thought for BP's stockholders, for their financial fate is inextricably tied to the capricious currents of air pollution.

ChatGPT:

air pollution, Tallahassee, BP, stock price, correlation, environmental protection agency, LSEG Analytics, Refinitiv, statistical techniques, correlation coefficient, relationship, air quality, financial impact, stock price determinants

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



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Data details

Air pollution in Tallahassee
Detailed data title: Percentage of days with moderate or worse air quality in Tallahassee, FL
Source: Environmental Protection Agency
See what else correlates with Air pollution in Tallahassee

BP's stock price (BP)
Detailed data title: Opening price of BP p.l.c. (BP) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function

See what else correlates with BP's stock price (BP)

Correlation r = 0.8213367 (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 = 0.6745940 (Coefficient of determination)
This means 67.5% of the change in the one variable (i.e., BP's stock price (BP)) is predictable based on the change in the other (i.e., Air pollution in Tallahassee) over the 22 years from 2002 through 2023.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.8E-6. 0.0000027966781752303493000000
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 0.82 in 0.00028% of random cases. Said differently, if you correlated 357,567 random variables You don't actually need 357 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 21 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 21 because we have two variables measured over a period of 22 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.

[ 0.61, 0.92 ] 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.
2002200320042005200620072008200920102011201220132014201520162017201820192020202120222023
Air pollution in Tallahassee (Bad air quality days)28.767140.27459.289661.095964.383659.452153.551941.095943.561641.917826.77618.904132.602726.849322.404428.925624.022325.479524.316920.821921.643833.1492
BP's stock price (BP) (Stock price)46.340.8549.5358.0565.567.2773.784759.344.943.7942.4548.4338.2130.838.142.0637.4738.0421.0926.6935




Why this works

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




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([28.7671,40.274,59.2896,61.0959,64.3836,59.4521,53.5519,41.0959,43.5616,41.9178,26.776,18.9041,32.6027,26.8493,22.4044,28.9256,24.0223,25.4795,24.3169,20.8219,21.6438,33.1492,])
array_2 = np.array([46.3,40.85,49.53,58.05,65.5,67.27,73.78,47,59.3,44.9,43.79,42.45,48.43,38.21,30.8,38.1,42.06,37.47,38.04,21.09,26.69,35,])
array_1_name = "Air pollution in Tallahassee"
array_2_name = "BP's stock price (BP)"

# 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: 3447 · Black Variable ID: 21325 · Red Variable ID: 1625
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