Spurious correlation #5,116 · 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 Tampa, Florida and the second variable is The number of maintenance workers, machinery in Florida. The chart goes from 2003 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Tampa, Florida and the second variable is The number of maintenance workers, machinery in Florida. The chart goes from 2003 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the air became cleaner, the machinery realized they no longer needed maintenance workers and simply started fixing themselves. It was like they were saying, "We don't need no smog control!"

^{Show image generation prompt} Model: dalle-3
Prompt: Generate a photo-realistic image of a maintenance yard in Tampa, Florida, with a noticeable reduction in air pollution. Show fewer maintenance workers present and focus on machinery appearing well-maintained and autonomous in a cleaner environment. Depict the machines seemingly thriving and waving off the smog, contributing to the serene atmosphere. Capture the essence of the scene with attention to detail, lighting, and environmental changes. 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 Tampa, Florida and The number of maintenance workers, machinery in Florida. 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 photo-realistic image Cutsy graphics Minimalism a Polaroid photo
ChatGPT: A photo-realistic 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 Tampa, Florida and The number of maintenance workers, machinery in Florida, in the following situation: As the air became cleaner, the machinery realized they no longer needed maintenance workers and simply started fixing themselves. It was like they were saying, "We don't need no smog control!". Keep the description simple.
ChatGPT: In Tampa, Florida, the air pollution level noticeably decreased as the number of maintenance workers and machinery also declined. The once bustling maintenance yard had fewer workers as the machinery seemed to be fixing itself, basking in the cleaner air. It was as if the machines were waving goodbye to the smog as they hummed along, not needing any control.

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 photo-realistic image ] and depicting this scene: In Tampa, Florida, the air pollution level noticeably decreased as the number of maintenance workers and machinery also declined. The once bustling maintenance yard had fewer workers as the machinery seemed to be fixing itself, basking in the cleaner air. It was as if the machines were waving goodbye to the smog as they hummed along, not needing any control. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate a photo-realistic image of a maintenance yard in Tampa, Florida, with a noticeable reduction in air pollution. Show fewer maintenance workers present and focus on machinery appearing well-maintained and autonomous in a cleaner environment. Depict the machines seemingly thriving and waving off the smog, contributing to the serene atmosphere. Capture the essence of the scene with attention to detail, lighting, and environmental changes.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humerus responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in Air pollution in Tampa, Florida caused The number of maintenance workers, machinery in Florida to decrease.

AI academic paper

(Because p < 0.01)

Breath in the Machinery: Examining the Correlation Between Air Pollution in Tampa, Florida and the Employment of Maintenance Workers

The Journal of Environmental Occupational Dynamics

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Tampa, Florida and The number of maintenance workers, machinery in Florida. 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.

Here is the title and abstract of the paper:
[[TITLE]]
"Breath in the Machinery: Examining the Correlation Between Air Pollution in Tampa, Florida and the Employment of Maintenance Workers"

[[ABSTRACT]]
The present study endeavors to unveil the intriguing relationship between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. Utilizing datasets from the Environmental Protection Agency and the Bureau of Labor Statistics, our team embarked on a journey to explore this unusual connection. Our findings revealed a remarkably strong correlation, represented by a correlation coefficient of 0.9331348, with a level of statistical significance denoted by p < 0.01, covering the timeframe from 2003 to 2022.

As we delved deep into the data, a peculiar pattern emerged, akin to dust bunnies lurking under a bed - the level of air pollution in Tampa displayed a striking alignment with the number of maintenance workers and machinery in the state. It was as if the mechanical equipment was gasping for a breath of fresh air, quite literally. Perhaps these maintenance workers were not just adept at fixing machinery, but also at purifying the air surrounding them, proving that they were truly the unsung heroes of environmental stewardship. It's almost as if the machinery and the air pollution engaged in a tug-of-war, with the maintenance workers caught in the middle, resembling a comical family dynamic worthy of a sitcom.

Our investigation sheds light on a previously neglected area of study, bringing forth the discourse on the interconnectedness between environmental factors and labor dynamics. We invite fellow researchers to delve deeper into this realm, for there is more than meets the eye in the seemingly mundane world of maintenance and air quality. For now, we can confidently declare that when it comes to maintaining machinery amidst air pollution, it's not just about turning wrenches, but also about taking a breath of fresh air.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The air we breathe impacts not just our lungs, but also the very machinations of our society. It is not merely a breath of fresh air, but a tale of interconnectedness, as intricately entwined as a pair of headphones at the bottom of a backpack. Tampa, Florida, known for its sunny beaches and thriving city life, also contends with the issue of air pollution lingering in its atmosphere, akin to an unwelcome party guest who just won't take the hint to leave. As this study showcases, the connection between air pollution and the employment of maintenance workers and machinery in Florida presents a fascinating union worthy of investigation.
What do you call an owl that does maintenance work? A hootenanny! Similarly, our inquiry into the correlation between air pollution and the deployment of maintenance workers and machinery is no whimsical affair but a serious scholarly pursuit. Our team meticulously combed through data with the tenacity of a lint roller, aiming to unravel the puzzling relationship between these seemingly disparate elements.
The employment of maintenance workers and machinery is the beating heart of Florida's infrastructure, much like a doting father trying to fix the family car on a Sunday afternoon. Our study seeks to shine a light on the vitality of this sector, uncovering how it may be impacted by the specter of air pollution. The emergence of a strong correlation, akin to the fervor of grandparents teaming up for a game of charades at a family gathering, suggests that there is more at play than meets the eye.
As the saying goes, "Where there's smoke, there's fire." And in the case of Tampa, where there's air pollution, there are maintenance workers and machinery. This correlation, while surprising at first glance, brings to mind the age-old question: "Which came first, the maintenance worker or the machinery?" Our study endeavors to provide some answers and perhaps a few chuckles along the way.
The fabric of our society is woven from the threads of interconnected systems, much like a patchwork quilt painstakingly assembled on a snowy winter's eve. As we unravel the intricate connections between air quality and labor dynamics, we invite our fellow researchers to join us in this enlightening expedition. For, in the great tapestry of research, every thread, no matter how unusual, contributes to the richness of our collective knowledge.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The correlation between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state has been a topic of growing interest and intrigue among researchers. Smith and Doe (2018) presented an exploratory analysis, delving into the possible associations between environmental factors and labor dynamics. Similarly, Jones et al. (2020) ventured into this uncharted territory, unearthing initial evidence of a peculiar relationship between air quality and the maintenance workforce.

Books such as "Air Pollution and Labor Dynamics: Unraveling the Web" by Greenberg (2017) and "Machinery Maintenance Amidst Environmental Challenges" by Patel (2019) have provided invaluable insights into the complex interplay between these seemingly disparate domains. This growing body of literature sets the stage for our investigation, as we seek to add another layer of understanding to this curious entanglement.

Turning to the realm of fiction, it is intriguing to note how works of literature such as "The Air Quality Paradox" by Harper Lee and "Maintenance Misadventures in the Sunshine State" by J.K. Rowling, though fictional in nature, seem to parallel the themes of our study. These imaginative narratives offer a glimpse into the potential ramifications of air pollution on the labor force, albeit in a whimsical and fantastical manner.

In our quest for knowledge, we expanded our exploration beyond the traditional confines of academic literature. Engaging in a thorough review of sources, we stumbled upon an unexpected treasure trove of insights - CVS receipts. Amidst the mundane purchase records, these artifacts provided snippets of everyday life in Tampa, hinting at the subtle nuances of air pollution's influence on the demand for maintenance services. While unconventional, this approach yielded surprisingly relevant observations, akin to finding a hidden gem in a pile of discarded cardboard boxes.

And so, armed with the wisdom gleaned from scholarly works, fictional tales, and even the unlikeliest of sources, we embark on our journey to unravel the enigmatic link between the air we breathe and the machinery we rely on. For in the labyrinth of research, every unexpected turn, much like a well-timed dad joke, adds a touch of whimsy to the pursuit of knowledge.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Air pollution in Tampa, Florida and The number of maintenance workers, machinery in Florida. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Bureau of Larbor Statistics . You used data from 2003 to 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Breath in the Machinery: Examining the Correlation Between Air Pollution in Tampa, Florida and the Employment of Maintenance Workers"

[[ABSTRACT]]
The present study endeavors to unveil the intriguing relationship between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. Utilizing datasets from the Environmental Protection Agency and the Bureau of Labor Statistics, our team embarked on a journey to explore this unusual connection. Our findings revealed a remarkably strong correlation, represented by a correlation coefficient of 0.9331348, with a level of statistical significance denoted by p < 0.01, covering the timeframe from 2003 to 2022.

As we delved deep into the data, a peculiar pattern emerged, akin to dust bunnies lurking under a bed - the level of air pollution in Tampa displayed a striking alignment with the number of maintenance workers and machinery in the state. It was as if the mechanical equipment was gasping for a breath of fresh air, quite literally. Perhaps these maintenance workers were not just adept at fixing machinery, but also at purifying the air surrounding them, proving that they were truly the unsung heroes of environmental stewardship. It's almost as if the machinery and the air pollution engaged in a tug-of-war, with the maintenance workers caught in the middle, resembling a comical family dynamic worthy of a sitcom.

Our investigation sheds light on a previously neglected area of study, bringing forth the discourse on the interconnectedness between environmental factors and labor dynamics. We invite fellow researchers to delve deeper into this realm, for there is more than meets the eye in the seemingly mundane world of maintenance and air quality. For now, we can confidently declare that when it comes to maintaining machinery amidst air pollution, it's not just about turning wrenches, but also about taking a breath of fresh air.

[[INTRODUCTION]]
The air we breathe impacts not just our lungs, but also the very machinations of our society. It is not merely a breath of fresh air, but a tale of interconnectedness, as intricately entwined as a pair of headphones at the bottom of a backpack. Tampa, Florida, known for its sunny beaches and thriving city life, also contends with the issue of air pollution lingering in its atmosphere, akin to an unwelcome party guest who just won't take the hint to leave. As this study showcases, the connection between air pollution and the employment of maintenance workers and machinery in Florida presents a fascinating union worthy of investigation.
What do you call an owl that does maintenance work? A hootenanny! Similarly, our inquiry into the correlation between air pollution and the deployment of maintenance workers and machinery is no whimsical affair but a serious scholarly pursuit. Our team meticulously combed through data with the tenacity of a lint roller, aiming to unravel the puzzling relationship between these seemingly disparate elements.
The employment of maintenance workers and machinery is the beating heart of Florida's infrastructure, much like a doting father trying to fix the family car on a Sunday afternoon. Our study seeks to shine a light on the vitality of this sector, uncovering how it may be impacted by the specter of air pollution. The emergence of a strong correlation, akin to the fervor of grandparents teaming up for a game of charades at a family gathering, suggests that there is more at play than meets the eye.
As the saying goes, "Where there's smoke, there's fire." And in the case of Tampa, where there's air pollution, there are maintenance workers and machinery. This correlation, while surprising at first glance, brings to mind the age-old question: "Which came first, the maintenance worker or the machinery?" Our study endeavors to provide some answers and perhaps a few chuckles along the way.
The fabric of our society is woven from the threads of interconnected systems, much like a patchwork quilt painstakingly assembled on a snowy winter's eve. As we unravel the intricate connections between air quality and labor dynamics, we invite our fellow researchers to join us in this enlightening expedition. For, in the great tapestry of research, every thread, no matter how unusual, contributes to the richness of our collective knowledge.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To untangle the enigmatic web of air pollution and the employment of maintenance workers and machinery, our research team embraced an array of methods akin to a buffet line, carefully selecting the most appetizing and robust approaches. We began with a comprehensive review of existing literature, diving into the depths of scholarly articles and reports as if we were treasure hunters in a library ocean. This step allowed us to gain a nuanced understanding of the subject, much like reading the instructions before attempting to assemble a piece of IKEA furniture.

Utilizing datasets from the Environmental Protection Agency and the Bureau of Labor Statistics, we combed through an extensive array of records, numbers, and graphs, resembling intrepid explorers navigating a digital jungle. We sought to capture the essence of information, much like a photographer endeavoring to capture the elusive beauty of a fleeting moment. By incorporating data spanning from 2003 to 2022, we aimed to encapsulate a comprehensive picture of the relationship over time, akin to a time-lapse video chronicling the growth of a houseplant, albeit with less dramatic music.

In our statistical analysis, we employed a series of complex and sophisticated methods, utilizing correlation analyses and regression models like a team of artists skillfully crafting a mathematical masterpiece. The correlation coefficient emerged as our trusty guide, steering us through the labyrinth of data with the precision of a GPS system, while the p-values stood as the gatekeepers of statistical significance, determining the worthiness of our findings like stern judges in a talent show. This process allowed us to unveil the strength and significance of the relationship between air pollution and the deployment of maintenance workers and machinery, akin to summoning ancient relics from beneath the sands of time.

In addition to quantitative analyses, we ventured into the realm of qualitative inquiry, conducting interviews and focus group discussions with maintenance workers and industry experts. These conversations provided us with a deeper understanding of the on-the-ground dynamics, offering insights akin to uncovering buried treasure in a conversation mine. The anecdotes and perspectives shared by these individuals added a human touch to our study, much like seasoning a dish with just the right amount of spice to elevate its flavor.

To ensure the robustness of our findings, we also engaged in rigorous sensitivity analyses, testing the stability of our results under various scenarios and assumptions. This process acted as a safety net, guarding against the pitfalls of spurious correlations or erroneous conclusions, much like a meticulous safety inspection before embarking on a rollercoaster ride.

Our methodological approach can best be summarized as a whimsical dance, with the grace of a swan and the determination of a marathon runner. We navigated through the maze of data with perseverance and a touch of humor, much like a jester in the court of academia, unraveling the mysteries of air pollution and the employment of maintenance workers and machinery.

Why did the maintenance worker break up with his girlfriend? He said he needed some space. Similarly, our meticulous approach to data collection and analysis aimed to create the space for meaningful insights to emerge, shedding light on the intriguing relationship between air quality and labor dynamics.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 Tampa, Florida and The number of maintenance workers, machinery in Florida. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Bureau of Larbor Statistics .

For the time period 2003 to 2022, you found a correlation 0.9331348, r-squared of 0.8707406, 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]]
"Breath in the Machinery: Examining the Correlation Between Air Pollution in Tampa, Florida and the Employment of Maintenance Workers"

[[ABSTRACT]]
The present study endeavors to unveil the intriguing relationship between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. Utilizing datasets from the Environmental Protection Agency and the Bureau of Labor Statistics, our team embarked on a journey to explore this unusual connection. Our findings revealed a remarkably strong correlation, represented by a correlation coefficient of 0.9331348, with a level of statistical significance denoted by p < 0.01, covering the timeframe from 2003 to 2022.

As we delved deep into the data, a peculiar pattern emerged, akin to dust bunnies lurking under a bed - the level of air pollution in Tampa displayed a striking alignment with the number of maintenance workers and machinery in the state. It was as if the mechanical equipment was gasping for a breath of fresh air, quite literally. Perhaps these maintenance workers were not just adept at fixing machinery, but also at purifying the air surrounding them, proving that they were truly the unsung heroes of environmental stewardship. It's almost as if the machinery and the air pollution engaged in a tug-of-war, with the maintenance workers caught in the middle, resembling a comical family dynamic worthy of a sitcom.

Our investigation sheds light on a previously neglected area of study, bringing forth the discourse on the interconnectedness between environmental factors and labor dynamics. We invite fellow researchers to delve deeper into this realm, for there is more than meets the eye in the seemingly mundane world of maintenance and air quality. For now, we can confidently declare that when it comes to maintaining machinery amidst air pollution, it's not just about turning wrenches, but also about taking a breath of fresh air.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The air we breathe impacts not just our lungs, but also the very machinations of our society. It is not merely a breath of fresh air, but a tale of interconnectedness, as intricately entwined as a pair of headphones at the bottom of a backpack. Tampa, Florida, known for its sunny beaches and thriving city life, also contends with the issue of air pollution lingering in its atmosphere, akin to an unwelcome party guest who just won't take the hint to leave. As this study showcases, the connection between air pollution and the employment of maintenance workers and machinery in Florida presents a fascinating union worthy of investigation.
What do you call an owl that does maintenance work? A hootenanny! Similarly, our inquiry into the correlation between air pollution and the deployment of maintenance workers and machinery is no whimsical affair but a serious scholarly pursuit. Our team meticulously combed through data with the tenacity of a lint roller, aiming to unravel the puzzling relationship between these seemingly disparate elements.
The employment of maintenance workers and machinery is the beating heart of Florida's infrastructure, much like a doting father trying to fix the family car on a Sunday afternoon. Our study seeks to shine a light on the vitality of this sector, uncovering how it may be impacted by the specter of air pollution. The emergence of a strong correlation, akin to the fervor of grandparents teaming up for a game of charades at a family gathering, suggests that there is more at play than meets the eye.
As the saying goes, "Where there's smoke, there's fire." And in the case of Tampa, where there's air pollution, there are maintenance workers and machinery. This correlation, while surprising at first glance, brings to mind the age-old question: "Which came first, the maintenance worker or the machinery?" Our study endeavors to provide some answers and perhaps a few chuckles along the way.
The fabric of our society is woven from the threads of interconnected systems, much like a patchwork quilt painstakingly assembled on a snowy winter's eve. As we unravel the intricate connections between air quality and labor dynamics, we invite our fellow researchers to join us in this enlightening expedition. For, in the great tapestry of research, every thread, no matter how unusual, contributes to the richness of our collective knowledge.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of the data collected from the Environmental Protection Agency and the Bureau of Labor Statistics revealed a strong positive correlation between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. The correlation coefficient of 0.9331348 indicated a robust relationship between these variables, with an r-squared value of 0.8707406, and a level of statistical significance denoted by p < 0.01. In other words, the connection between these variables is as clear as the Florida sky on a sunny day, before the air pollution comes rolling in.

Fig. 1, our scatterplot, illustrates this remarkable correlation, with maintenance workers and machinery on one axis and air pollution levels on the other. The points form a nearly perfect line, resembling a meticulously maintained row of garden gnomes, standing in unison amidst the tumultuous winds of statistical variance. It's like the maintenance workers and machinery are saying, "We've got your back, air quality!"

The strong correlation we uncovered provides compelling evidence that the presence of air pollution in Tampa, Florida is intricately linked to the employment of maintenance workers and machinery in the state. It's as though the machinery is whispering to the maintenance workers, "I can't breathe, but together, we can make the air quality great again."

Our findings lend weight to the idea that the deployment of maintenance workers and machinery in Florida is significantly influenced by the level of air pollution. It's like a symbiotic relationship, with the machines and air pollution engaged in a dance as old as time, and the maintenance workers caught in the middle, boogying to the beat of environmental stewardship.

In conclusion, our research infers that there is a compelling association between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. It's almost as if the machinery, like a dramatic teenager, is crying out for attention amidst the haze of air pollution, drawing the steadfast and diligent maintenance workers into a dance of ecological significance.

The impressive strength of the correlation we found is nothing to sneeze at, unlike the pollutants hanging in the air of Tampa. These results open the door to a deeper understanding of the intricate connections between air quality and labor dynamics, offering a fresh perspective to a field often overlooked. It's an invitation for further investigation, and perhaps a call for society to recognize the significance of these often-underappreciated workers in shaping our environmental landscape.

The data speaks for itself, and in this case, it's whispering that when it comes to maintaining machinery amidst air pollution, it's not just about turning wrenches, but also about taking a breath of fresh air.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Tampa, Florida and The number of maintenance workers, machinery in Florida. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
"Breath in the Machinery: Examining the Correlation Between Air Pollution in Tampa, Florida and the Employment of Maintenance Workers"

[[ABSTRACT]]
The present study endeavors to unveil the intriguing relationship between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. Utilizing datasets from the Environmental Protection Agency and the Bureau of Labor Statistics, our team embarked on a journey to explore this unusual connection. Our findings revealed a remarkably strong correlation, represented by a correlation coefficient of 0.9331348, with a level of statistical significance denoted by p < 0.01, covering the timeframe from 2003 to 2022.

As we delved deep into the data, a peculiar pattern emerged, akin to dust bunnies lurking under a bed - the level of air pollution in Tampa displayed a striking alignment with the number of maintenance workers and machinery in the state. It was as if the mechanical equipment was gasping for a breath of fresh air, quite literally. Perhaps these maintenance workers were not just adept at fixing machinery, but also at purifying the air surrounding them, proving that they were truly the unsung heroes of environmental stewardship. It's almost as if the machinery and the air pollution engaged in a tug-of-war, with the maintenance workers caught in the middle, resembling a comical family dynamic worthy of a sitcom.

Our investigation sheds light on a previously neglected area of study, bringing forth the discourse on the interconnectedness between environmental factors and labor dynamics. We invite fellow researchers to delve deeper into this realm, for there is more than meets the eye in the seemingly mundane world of maintenance and air quality. For now, we can confidently declare that when it comes to maintaining machinery amidst air pollution, it's not just about turning wrenches, but also about taking a breath of fresh air.

[[LITERATURE REVIEW]]
The correlation between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state has been a topic of growing interest and intrigue among researchers. Smith and Doe (2018) presented an exploratory analysis, delving into the possible associations between environmental factors and labor dynamics. Similarly, Jones et al. (2020) ventured into this uncharted territory, unearthing initial evidence of a peculiar relationship between air quality and the maintenance workforce.
Books such as "Air Pollution and Labor Dynamics: Unraveling the Web" by Greenberg (2017) and "Machinery Maintenance Amidst Environmental Challenges" by Patel (2019) have provided invaluable insights into the complex interplay between these seemingly disparate domains. This growing body of literature sets the stage for our investigation, as we seek to add another layer of understanding to this curious entanglement.
Turning to the realm of fiction, it is intriguing to note how works of literature such as "The Air Quality Paradox" by Harper Lee and "Maintenance Misadventures in the Sunshine State" by J.K. Rowling, though fictional in nature, seem to parallel the themes of our study. These imaginative narratives offer a glimpse into the potential ramifications of air pollution on the labor force, albeit in a whimsical and fantastical manner.
In our quest for knowledge, we expanded our exploration beyond the traditional confines of academic literature. Engaging in a thorough review of sources, we stumbled upon an unexpected treasure trove of insights - CVS receipts. Amidst the mundane purchase records, these artifacts provided snippets of everyday life in Tampa, hinting at the subtle nuances of air pollution's influence on the demand for maintenance services. While unconventional, this approach yielded surprisingly relevant observations, akin to finding a hidden gem in a pile of discarded cardboard boxes.
And so, armed with the wisdom gleaned from scholarly works, fictional tales, and even the unlikeliest of sources, we embark on our journey to unravel the enigmatic link between the air we breathe and the machinery we rely on. For in the labyrinth of research, every unexpected turn, much like a well-timed dad joke, adds a touch of whimsy to the pursuit of knowledge.

[[RESULTS]]
The analysis of the data collected from the Environmental Protection Agency and the Bureau of Labor Statistics revealed a strong positive correlation between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. The correlation coefficient of 0.9331348 indicated a robust relationship between these variables, with an r-squared value of 0.8707406, and a level of statistical significance denoted by p < 0.01. In other words, the connection between these variables is as clear as the Florida sky on a sunny day, before the air pollution comes rolling in.
Fig. 1, our scatterplot, illustrates this remarkable correlation, with maintenance workers and machinery on one axis and air pollution levels on the other. The points form a nearly perfect line, resembling a meticulously maintained row of garden gnomes, standing in unison amidst the tumultuous winds of statistical variance. It's like the maintenance workers and machinery are saying, "We've got your back, air quality!"
The strong correlation we uncovered provides compelling evidence that the presence of air pollution in Tampa, Florida is intricately linked to the employment of maintenance workers and machinery in the state. It's as though the machinery is whispering to the maintenance workers, "I can't breathe, but together, we can make the air quality great again."
Our findings lend weight to the idea that the deployment of maintenance workers and machinery in Florida is significantly influenced by the level of air pollution. It's like a symbiotic relationship, with the machines and air pollution engaged in a dance as old as time, and the maintenance workers caught in the middle, boogying to the beat of environmental stewardship.
In conclusion, our research infers that there is a compelling association between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. It's almost as if the machinery, like a dramatic teenager, is crying out for attention amidst the haze of air pollution, drawing the steadfast and diligent maintenance workers into a dance of ecological significance.
The impressive strength of the correlation we found is nothing to sneeze at, unlike the pollutants hanging in the air of Tampa. These results open the door to a deeper understanding of the intricate connections between air quality and labor dynamics, offering a fresh perspective to a field often overlooked. It's an invitation for further investigation, and perhaps a call for society to recognize the significance of these often-underappreciated workers in shaping our environmental landscape.
The data speaks for itself, and in this case, it's whispering that when it comes to maintaining machinery amidst air pollution, it's not just about turning wrenches, but also about taking a breath of fresh air.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study substantiate the earlier findings by Smith and Doe (2018) and Jones et al. (2020), which indicated a significant relationship between air pollution in Tampa, Florida and the employment of maintenance workers and machinery. It seems that our analysis has not only confirmed but also strengthened the evidence of this peculiar connection, reminiscent of the reliability of a well-maintained piece of equipment - it's as sturdy as a dad joke at a family gathering.

The strong positive correlation coefficient of 0.9331348 discovered in our study not only validates the prior research but also emphasizes the robustness of this link. It's almost as if the data is repeatedly nudging us and saying, "I'm not pulling your leg, this association is the real deal." This echoes the sentiment that there's nothing "half-ashe" about this connection.

As we reach back to the comical family dynamic analogy highlighted in the literature review, our results seem to support the notion that the air pollution, maintenance workers, and machinery are engaged in an intricate dance, much like a conga line at a jovial gathering. The data illustrates that the machinery isn't just passively enduring the effects of air pollution; it's actively influencing the demand for maintenance workers. It's almost as if the machinery is whispering to the workers, "I'll be blowing smoke until you fix me up, and then we can clear the air together."

The strength of our findings lays fertile ground for further studies, much like a well-tended garden ready for new blooms. By scrutinizing this relationship, researchers and policymakers can gain valuable insights into the labor dynamics influenced by environmental factors. Moreover, our results also bring attention to the crucial role of maintenance workers in mitigating the effects of air pollution - they are the unsung heroes in the battle for cleaner air, akin to the stealth superheroes resembling Clark "Maintenance" Kent, saving the day without a cape.

In essence, our study not only verifies the correlation between air pollution in Tampa, Florida and the employment of maintenance workers and machinery but also illuminates the intricate interplay between environmental dynamics and labor demands. It's not just about turning wrenches; it's about turning the wheels of progress in environmental stewardship. Our findings beckon the scientific community to delve further into this fascinating connection, for there is much to unearth amidst the machinery and the mist of air pollution.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Tampa, Florida and The number of maintenance workers, machinery in Florida. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
"Breath in the Machinery: Examining the Correlation Between Air Pollution in Tampa, Florida and the Employment of Maintenance Workers"

[[ABSTRACT]]
The present study endeavors to unveil the intriguing relationship between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. Utilizing datasets from the Environmental Protection Agency and the Bureau of Labor Statistics, our team embarked on a journey to explore this unusual connection. Our findings revealed a remarkably strong correlation, represented by a correlation coefficient of 0.9331348, with a level of statistical significance denoted by p < 0.01, covering the timeframe from 2003 to 2022.

As we delved deep into the data, a peculiar pattern emerged, akin to dust bunnies lurking under a bed - the level of air pollution in Tampa displayed a striking alignment with the number of maintenance workers and machinery in the state. It was as if the mechanical equipment was gasping for a breath of fresh air, quite literally. Perhaps these maintenance workers were not just adept at fixing machinery, but also at purifying the air surrounding them, proving that they were truly the unsung heroes of environmental stewardship. It's almost as if the machinery and the air pollution engaged in a tug-of-war, with the maintenance workers caught in the middle, resembling a comical family dynamic worthy of a sitcom.

Our investigation sheds light on a previously neglected area of study, bringing forth the discourse on the interconnectedness between environmental factors and labor dynamics. We invite fellow researchers to delve deeper into this realm, for there is more than meets the eye in the seemingly mundane world of maintenance and air quality. For now, we can confidently declare that when it comes to maintaining machinery amidst air pollution, it's not just about turning wrenches, but also about taking a breath of fresh air.

[[INTRDUCTION]]
The air we breathe impacts not just our lungs, but also the very machinations of our society. It is not merely a breath of fresh air, but a tale of interconnectedness, as intricately entwined as a pair of headphones at the bottom of a backpack. Tampa, Florida, known for its sunny beaches and thriving city life, also contends with the issue of air pollution lingering in its atmosphere, akin to an unwelcome party guest who just won't take the hint to leave. As this study showcases, the connection between air pollution and the employment of maintenance workers and machinery in Florida presents a fascinating union worthy of investigation.
What do you call an owl that does maintenance work? A hootenanny! Similarly, our inquiry into the correlation between air pollution and the deployment of maintenance workers and machinery is no whimsical affair but a serious scholarly pursuit. Our team meticulously combed through data with the tenacity of a lint roller, aiming to unravel the puzzling relationship between these seemingly disparate elements.
The employment of maintenance workers and machinery is the beating heart of Florida's infrastructure, much like a doting father trying to fix the family car on a Sunday afternoon. Our study seeks to shine a light on the vitality of this sector, uncovering how it may be impacted by the specter of air pollution. The emergence of a strong correlation, akin to the fervor of grandparents teaming up for a game of charades at a family gathering, suggests that there is more at play than meets the eye.
As the saying goes, "Where there's smoke, there's fire." And in the case of Tampa, where there's air pollution, there are maintenance workers and machinery. This correlation, while surprising at first glance, brings to mind the age-old question: "Which came first, the maintenance worker or the machinery?" Our study endeavors to provide some answers and perhaps a few chuckles along the way.
The fabric of our society is woven from the threads of interconnected systems, much like a patchwork quilt painstakingly assembled on a snowy winter's eve. As we unravel the intricate connections between air quality and labor dynamics, we invite our fellow researchers to join us in this enlightening expedition. For, in the great tapestry of research, every thread, no matter how unusual, contributes to the richness of our collective knowledge.

[[RESULTS]]
The analysis of the data collected from the Environmental Protection Agency and the Bureau of Labor Statistics revealed a strong positive correlation between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. The correlation coefficient of 0.9331348 indicated a robust relationship between these variables, with an r-squared value of 0.8707406, and a level of statistical significance denoted by p < 0.01. In other words, the connection between these variables is as clear as the Florida sky on a sunny day, before the air pollution comes rolling in.
Fig. 1, our scatterplot, illustrates this remarkable correlation, with maintenance workers and machinery on one axis and air pollution levels on the other. The points form a nearly perfect line, resembling a meticulously maintained row of garden gnomes, standing in unison amidst the tumultuous winds of statistical variance. It's like the maintenance workers and machinery are saying, "We've got your back, air quality!"
The strong correlation we uncovered provides compelling evidence that the presence of air pollution in Tampa, Florida is intricately linked to the employment of maintenance workers and machinery in the state. It's as though the machinery is whispering to the maintenance workers, "I can't breathe, but together, we can make the air quality great again."
Our findings lend weight to the idea that the deployment of maintenance workers and machinery in Florida is significantly influenced by the level of air pollution. It's like a symbiotic relationship, with the machines and air pollution engaged in a dance as old as time, and the maintenance workers caught in the middle, boogying to the beat of environmental stewardship.
In conclusion, our research infers that there is a compelling association between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. It's almost as if the machinery, like a dramatic teenager, is crying out for attention amidst the haze of air pollution, drawing the steadfast and diligent maintenance workers into a dance of ecological significance.
The impressive strength of the correlation we found is nothing to sneeze at, unlike the pollutants hanging in the air of Tampa. These results open the door to a deeper understanding of the intricate connections between air quality and labor dynamics, offering a fresh perspective to a field often overlooked. It's an invitation for further investigation, and perhaps a call for society to recognize the significance of these often-underappreciated workers in shaping our environmental landscape.
The data speaks for itself, and in this case, it's whispering that when it comes to maintaining machinery amidst air pollution, it's not just about turning wrenches, but also about taking a breath of fresh air.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has peeled back the layers of obscurity surrounding the relationship between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. It's as if the machinery and air pollution were engaged in a dance as old as time, and the maintenance workers were the chaperones trying to keep things in order - much like a high school prom, but with significantly more airborne particulate matter.

Our findings consistently demonstrated a compelling correlation, almost as robust as a family dog's enthusiasm for a game of fetch, with a correlation coefficient of 0.9331348 that would make any statistics enthusiast raise an eyebrow in pleasant surprise. The statistical evidence of this connection is as convincing as a well-timed dad joke at a family gathering - you just can't argue with it.

The strength of this correlation highlights the intertwined fate of machinery, air pollution, and the diligent maintenance workers in Florida. It's like a classic love triangle, with the machinery desperately vying for attention amidst the haze of air pollution, and the maintenance workers being the unsung heroes of environmental stewardship, calming the conflict like skilled relationship counselors.

In light of these compelling findings, we confidently declare that no further research is needed in this area. It's as clear as the air in Tampa after a thorough maintenance session - or at least, almost as clear!

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 Breath in the Machinery: Examining the Correlation Between Air Pollution in Tampa, Florida and the Employment of Maintenance Workers. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Environmental Occupational Dynamics

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 Breath in the Machinery: Examining the Correlation Between Air Pollution in Tampa, Florida and the Employment of Maintenance Workers. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Urban Air Quality 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 Breath in the Machinery: Examining the Correlation Between Air Pollution in Tampa, Florida and the Employment of Maintenance Workers with an abstract of The present study endeavors to unveil the intriguing relationship between air pollution in Tampa, Florida and the employment of maintenance workers and machinery in the state. Utilizing datasets from the Environmental Protection Agency and the Bureau of Labor Statistics, our team embarked on a journey to explore this unusual connection. Our findings revealed a remarkably strong correlation, represented by a correlation coefficient of 0.9331348, with a level of statistical significance denoted by p < 0.01, covering the timeframe from 2003 to 2022.
As we delved deep into the data, a peculiar pattern emerged, akin to dust bunnies lurking under a bed - the level of air pollution in Tampa displayed a striking alignment with the number of maintenance workers and machinery in the state. It was as if the mechanical equipment was gasping for a breath of fresh air, quite literally. Perhaps these maintenance workers were not just adept at fixing machinery, but also at purifying the air surrounding them, proving that they were truly the unsung heroes of environmental stewardship. It's almost as if the machinery and the air pollution engaged in a tug-of-war, with the maintenance workers caught in the middle, resembling a comical family dynamic worthy of a sitcom.
Our investigation sheds light on a previously neglected area of study, bringing forth the discourse on the interconnectedness between environmental factors and labor dynamics. We invite fellow researchers to delve deeper into this realm, for there is more than meets the eye in the seemingly mundane world of maintenance and air quality. For now, we can confidently declare that when it comes to maintaining machinery amidst air pollution, it's not just about turning wrenches, but also about taking a breath of fresh air.

ChatGPT:

air pollution, Tampa Florida, maintenance workers, machinery, correlation, Environmental Protection Agency, Bureau of Labor Statistics, statistical significance, dataset, labor dynamics, environmental factors, breath of fresh air

*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 Tampa, Florida
Detailed data title: Percentage of days with air quality at 'unhealthy for sensitive groups' or worse in Tampa-St. Petersburg-Clearwater, FL
Source: Environmental Protection Agency
See what else correlates with Air pollution in Tampa, Florida

The number of maintenance workers, machinery in Florida
Detailed data title: BLS estimate of maintenance workers, machinery in Florida
Source: Bureau of Larbor Statistics
See what else correlates with The number of maintenance workers, machinery in Florida

Correlation r = 0.9331348 (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 = 0.8707406 (Coefficient of determination)
This means 87.1% of the change in the one variable (i.e., The number of maintenance workers, machinery in Florida) is predictable based on the change in the other (i.e., Air pollution in Tampa, Florida) over the 20 years from 2003 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.0E-9.^Show 0.0000000019875452054919810000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.93 in 2.0E-7% of random cases. Said differently, if you correlated 503,133,210 random variables^Note You don't actually need 503 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

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

[ 0.84, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Air pollution in Tampa, Florida (Bad air quality days)	7.67123	5.46448	10.9589	10.9589	5.47945	3.00546	1.36986	2.73973	4.38356	2.45902	1.09589	1.64384	0.273973	0.819672	0.821918	1.36986	1.36986	0.819672	0.273973	0.273973
The number of maintenance workers, machinery in Florida (Laborers)	6530	5540	6930	6850	5610	4500	2380	2910	2940	3320	2570	2150	1680	1460	1160	1530	1610	1640	1050	2400

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([7.67123,5.46448,10.9589,10.9589,5.47945,3.00546,1.36986,2.73973,4.38356,2.45902,1.09589,1.64384,0.273973,0.819672,0.821918,1.36986,1.36986,0.819672,0.273973,0.273973,])
array_2 = np.array([6530,5540,6930,6850,5610,4500,2380,2910,2940,3320,2570,2150,1680,1460,1160,1530,1610,1640,1050,2400,])
array_1_name = "Air pollution in Tampa, Florida"
array_2_name = "The number of maintenance workers, machinery in Florida"

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

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

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Air pollution in Tampa, Florida
Line chart for only The number of maintenance workers, machinery in Florida
AI-generated correlation image
The spurious research paper: Breath in the Machinery: Examining the Correlation Between Air Pollution in Tampa, Florida and the Employment of Maintenance Workers

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Correlation ID: 5116 · Black Variable ID: 21331 · Red Variable ID: 6640


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