Spurious correlation #2,897 · 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 Riverside, California and the second variable is Number of home runs hit by Matt Kemp. The chart goes from 2006 to 2020, 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 Riverside, California and the second variable is Number of home runs hit by Matt Kemp. The chart goes from 2006 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The particles in the air were actually supercharged with home run energy, giving Matt Kemp's hits an extra oomph as they sailed through the smoggy skies.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image that looks like it is a scene from a Pixar movie, depicting a hazy sky hanging heavy over a baseball stadium in Riverside, California. Despite the pollution, the crowd cheers as Matt Kemp steps up to bat. With each swing, the baseball effortlessly soars through the polluted air, sailing over the outfield wall. The smog may obscure the horizon, but it can't cloud the sight of Kemp's home runs as they sail through the tainted sky. 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 Riverside, California and Number of home runs hit by Matt Kemp. 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: Art nouveau Cutsy graphics An image that looks like it is a scene from a Pixar movie Cybernetic art Futuristic
ChatGPT: An image that looks like it is a scene from a Pixar movie

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Riverside, California and Number of home runs hit by Matt Kemp, in the following situation: because the air pollution in Riverside, California made the baseballs lighter, allowing Matt Kemp to hit more home runs with ease.. Keep the description simple.
ChatGPT: In Riverside, California, a hazy sky hangs heavy over the baseball stadium. Despite the pollution, the crowd cheers as Matt Kemp steps up to bat. With each swing, the baseball effortlessly soars through the polluted air, soaring over the outfield wall. The smog may obscure the horizon, but it can't cloud the sight of Kemp's home runs as they sail through the tainted sky.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: In Riverside, California, a hazy sky hangs heavy over the baseball stadium. Despite the pollution, the crowd cheers as Matt Kemp steps up to bat. With each swing, the baseball effortlessly soars through the polluted air, soaring over the outfield wall. The smog may obscure the horizon, but it can't cloud the sight of Kemp's home runs as they sail through the tainted sky. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that looks like it is a scene from a Pixar movie, depicting a hazy sky hanging heavy over a baseball stadium in Riverside, California. Despite the pollution, the crowd cheers as Matt Kemp steps up to bat. With each swing, the baseball effortlessly soars through the polluted air, sailing over the outfield wall. The smog may obscure the horizon, but it can't cloud the sight of Kemp's home runs as they sail through the tainted sky.

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

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

AI academic paper

(Because p < 0.01)

A Breath of Fresh Air: The Lungevity of Home Runs in Riverside, California

The Journal of Sports Science and Home Run 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 dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Riverside, California and Number of home runs hit by Matt Kemp. 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]]
"A Breath of Fresh Air: The Lungevity of Home Runs in Riverside, California"

[[ABSTRACT]]
This study investigates the relationship between air pollution levels in Riverside, California, and the number of home runs hit by the professional baseball player Matt Kemp. Using data from the Environmental Protection Agency and Baseball Reference for the period of 2006 to 2020, we found a strong correlation coefficient of 0.8360854 (p < 0.01) between air pollution and Matt Kemp's home run hitting performance.

Our analysis reveals that as air pollution levels in Riverside increased, the number of home runs hit by Matt Kemp also increased, suggesting a potential positive association between the two variables. This unexpected connection may shed light on the elusive factors influencing athletic performance in professional sports.

Furthermore, our findings challenge conventional wisdom and suggest that the air quality in Riverside may play an unintended role as a "homer-enhancing substance" for professional baseball players. This correlation serves as a breath of fresh air in our understanding of the unexpected links between environmental factors and athletic prowess.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the pursuit of understanding the complex interplay between environmental factors and athletic performance, researchers have long sought to uncover the hidden connections that influence the game of baseball. While the focus has primarily been on variables such as player strength, bat speed, and weather conditions, the potential impact of air quality on homerun hitting has remained largely unexplored. However, our study takes a deep dive into this uncharted territory, seeking to elucidate the surprising association between air pollution levels in Riverside, California, and the prolific home run hitting of the formidable player, Matt Kemp.
As we embark on this research journey, it is crucial to maintain a keen eye for unexpected correlations that may emerge, much like a home run sneaks past the outfielders. This study endeavors to not only unravel the statistical relationship between air pollution and home run hitting but also to provide a breath of fresh air in the realm of sports science. It aims to capture the essence of environmental influences on athletic achievements and, quite literally, break new ground in understanding the "air apparent" impact of air quality on baseball performance.
[Insert dad joke] As we navigate through the statistical realm, it is imperative to "pitch" our ideas in a manner that captures the attention of both sports enthusiasts and environmental advocates. After all, just like a well-executed pun, compelling research should elicit both groans and grins, simultaneously expanding our understanding and our appreciation for the unexpected connections that can be found in the world of science.
Utilizing data from reputable sources such as the Environmental Protection Agency and Baseball Reference, this investigation applies rigorous statistical analyses to unearth the correlation between air pollution and the number of home runs hit by Matt Kemp. By scrutinizing the empirical evidence from 2006 to 2020, we aim to shed light on the seemingly improbable link between aerial contaminants and the soaring trajectory of baseballs launched by this esteemed player.
[Insert dad joke] In the tradition of a seasoned umpire, we approach this examination with a discerning eye, fully aware that even the most unassuming factors may prove to be game-changers in the world of sports. Just as a seemingly innocuous bloop single can turn into an unexpected rally, our findings may pave the way for a new innings of research, unravelling the environmental forces at play in the game of baseball.
The implications of this study extend beyond the realm of sports, offering intriguing insights into the intricate web of environmental influences on human performance. The link between air pollution in Riverside and Matt Kemp's home run hitting may serve as a springboard for exploring the broader impact of air quality on athletic achievements, opening doors to novel avenues of investigation in the realm of environmental sports science.
[Insert dad joke] Just as a curveball catches the batter by surprise, we hope that our findings will throw a curveball into conventional understanding, demonstrating that the winds of change in sports science can be influenced by the very air we breathe. This research strives to infuse a breath of fresh air into the discourse on environmental factors in sports, offering a tantalizing glimpse into the unexpected connections that underpin athletic excellence.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The literature on the relationship between environmental factors and athletic performance has predominantly focused on variables such as climate, altitude, and humidity. However, recent studies have begun to hint at the potential influence of air quality on sports outcomes. Smith (2018) examined the impact of air pollution on cardiovascular endurance in athletes, finding a negative association between pollutant levels and performance during endurance activities. Similarly, Doe et al. (2020) investigated the effects of air quality on soccer match outcomes, revealing that higher levels of pollution were correlated with a decrease in player sprinting speed.

In the realm of baseball, the influence of air quality on hitting performance has received limited attention. However, Jones (2019) explored the potential impact of air pollution on batting averages, albeit with inconclusive results. Despite these studies, the specific relationship between air pollution and home run hitting by professional baseball players remains largely unexplored.

[Insert dad joke] Speaking of air quality, did you hear about the baseball team that always played in smoggy conditions? They had some "high-flying" performances, but their opponents couldn't help but "choke" under the pressure.

To elucidate this under-researched connection, our study delves into the unexpected correlation between air pollution levels in Riverside, California, and the number of home runs hit by the renowned player, Matt Kemp. While the notion of air quality serving as a potential "homer-enhancing substance" may seem far-fetched, our analysis aims to bring this airy possibility down to earth.

In the realm of environmental science, diverse literature exists on the study of air pollution and its impact on human health and ecosystems. Notably, "Air Pollution and Health" by Smith (2017) presents a comprehensive overview of the physiological and pathological effects of air pollutants on human respiratory systems. Additionally, "Atmospheric Chemistry and Physics" by Doe (2019) provides detailed insights into the chemical composition of air pollutants and their dispersion in the atmosphere.

[Insert dad joke] Did you hear about the chemist who tried to study air pollution? He really went the extra mile to "air" on the side of caution!

Moving beyond non-fiction literature, one cannot overlook the potential influence of fictional works that may offer indirect insights into the relationship between air pollution and athletic performance. The dystopian novel "Ozone" by John Green imagines a world where air pollution has reached catastrophic levels, prompting characters to adapt their physical activities to the toxic environment. Similarly, in the science fiction classic "The Airborne Athlete" by Jane Austen, the protagonist unveils a remarkable ability to harness the power of airborne particles to enhance athletic prowess.

[Insert dad joke] Did you hear about the baseball player who could hit home runs using polluted air? He really "breathed" new life into the game!

Furthermore, anecdotal evidence from social media posts has hinted at the potential impact of air quality on sports achievements. A tweet by @SportsSciInsights noted an unusual spike in home runs by players during periods of increased air pollution, prompting speculation about the role of atmospheric conditions in altering baseball dynamics. Similarly, a Reddit post on r/BaseballAnalytics recounted an amateur player's experience of hitting remarkable long-distance shots during hazy weather, raising intriguing questions about the interplay between air quality and athletic performance.

[Insert dad joke] I saw an Instagram post about a baseball player hitting home runs in smoggy conditions. It really shed some "light" on the influence of air quality on athletic performance!

In light of the existing literature and anecdotal observations, our study seeks to contribute to the understanding of this unconventional association, striving to unveil the mystifying connection between air pollution in Riverside, California, and the remarkable home run hitting prowess of Matt Kemp. Just as a curveball catches the batter by surprise, our findings promise to offer a new spin on the environmental influences shaping the game of baseball.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Riverside, California and Number of home runs hit by Matt Kemp. 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 Baseball Reference . You used data from 2006 to 2020

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]]
"A Breath of Fresh Air: The Lungevity of Home Runs in Riverside, California"

[[ABSTRACT]]
This study investigates the relationship between air pollution levels in Riverside, California, and the number of home runs hit by the professional baseball player Matt Kemp. Using data from the Environmental Protection Agency and Baseball Reference for the period of 2006 to 2020, we found a strong correlation coefficient of 0.8360854 (p < 0.01) between air pollution and Matt Kemp's home run hitting performance.

Our analysis reveals that as air pollution levels in Riverside increased, the number of home runs hit by Matt Kemp also increased, suggesting a potential positive association between the two variables. This unexpected connection may shed light on the elusive factors influencing athletic performance in professional sports.

Furthermore, our findings challenge conventional wisdom and suggest that the air quality in Riverside may play an unintended role as a "homer-enhancing substance" for professional baseball players. This correlation serves as a breath of fresh air in our understanding of the unexpected links between environmental factors and athletic prowess.

[[INTRODUCTION]]
In the pursuit of understanding the complex interplay between environmental factors and athletic performance, researchers have long sought to uncover the hidden connections that influence the game of baseball. While the focus has primarily been on variables such as player strength, bat speed, and weather conditions, the potential impact of air quality on homerun hitting has remained largely unexplored. However, our study takes a deep dive into this uncharted territory, seeking to elucidate the surprising association between air pollution levels in Riverside, California, and the prolific home run hitting of the formidable player, Matt Kemp.
As we embark on this research journey, it is crucial to maintain a keen eye for unexpected correlations that may emerge, much like a home run sneaks past the outfielders. This study endeavors to not only unravel the statistical relationship between air pollution and home run hitting but also to provide a breath of fresh air in the realm of sports science. It aims to capture the essence of environmental influences on athletic achievements and, quite literally, break new ground in understanding the "air apparent" impact of air quality on baseball performance.
[Insert dad joke] As we navigate through the statistical realm, it is imperative to "pitch" our ideas in a manner that captures the attention of both sports enthusiasts and environmental advocates. After all, just like a well-executed pun, compelling research should elicit both groans and grins, simultaneously expanding our understanding and our appreciation for the unexpected connections that can be found in the world of science.
Utilizing data from reputable sources such as the Environmental Protection Agency and Baseball Reference, this investigation applies rigorous statistical analyses to unearth the correlation between air pollution and the number of home runs hit by Matt Kemp. By scrutinizing the empirical evidence from 2006 to 2020, we aim to shed light on the seemingly improbable link between aerial contaminants and the soaring trajectory of baseballs launched by this esteemed player.
[Insert dad joke] In the tradition of a seasoned umpire, we approach this examination with a discerning eye, fully aware that even the most unassuming factors may prove to be game-changers in the world of sports. Just as a seemingly innocuous bloop single can turn into an unexpected rally, our findings may pave the way for a new innings of research, unravelling the environmental forces at play in the game of baseball.
The implications of this study extend beyond the realm of sports, offering intriguing insights into the intricate web of environmental influences on human performance. The link between air pollution in Riverside and Matt Kemp's home run hitting may serve as a springboard for exploring the broader impact of air quality on athletic achievements, opening doors to novel avenues of investigation in the realm of environmental sports science.
[Insert dad joke] Just as a curveball catches the batter by surprise, we hope that our findings will throw a curveball into conventional understanding, demonstrating that the winds of change in sports science can be influenced by the very air we breathe. This research strives to infuse a breath of fresh air into the discourse on environmental factors in sports, offering a tantalizing glimpse into the unexpected connections that underpin athletic excellence.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The present study employed a methodological approach that combined rigorous statistical analyses with a dash of whimsical curiosity, akin to a scientist with a penchant for puns conducting a high-stakes experiment. The primary data sources for this investigation were the Environmental Protection Agency's Air Quality System (AQS) database and the comprehensive statistical records of baseball player performance from Baseball Reference.

To begin, air pollution data was collected from multiple monitoring stations across Riverside, California, measuring pollutants such as particulate matter (PM2.5 and PM10), ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO). This comprehensive pollution data was then standardized and aggregated to create a composite measure of air quality for Riverside, resembling the amalgamation of various chemical elements in a test tube, albeit without the fizzing and bubbling.

Simultaneously, information on the number of home runs hit by Matt Kemp from 2006 to 2020 was meticulously compiled, seeking to capture the prodigious power of his hits with the precision of a scientist measuring atomic particles, albeit with slightly larger and more spherical objects.

Following the collection of these disparate datasets, extensive data cleaning and processing were carried out to ensure the accuracy and integrity of the variables under scrutiny. We diligently sifted through the data, akin to a meticulous archaeologist excavating historical artifacts, in search of any anomalies or inconsistencies that could potentially confound the subsequent analyses.

Next, a series of sophisticated statistical analyses were performed to explore the relationship between air pollution levels and the number of home runs hit by Matt Kemp. These analyses included correlation coefficients, regression models, and exploratory data visualizations, aiming to uncover potential patterns and associations between the two seemingly disparate variables. The statistical tools were wielded with precision, much like a skilled magician performing sleight of hand, ensuring that the audience (or in this case, the scientific community) remained captivated and intrigued.

Furthermore, sensitivity analyses were conducted to evaluate the robustness of the findings, considering the potential influence of external variables such as weather conditions, stadium altitude, and other contextual factors that may inadvertently impact both air quality and baseball performance. This comprehensive approach aimed to address any potential confounding factors, much like an investigator meticulously eliminating suspects in a mystery novel, unveiling the true relationship between air pollution and home run hitting.

Finally, the results were critically interpreted within the broader context of existing literature on environmental influences in sports performance, emphasizing the need for further exploration and replication of the findings in diverse settings. This interpretative process involved a judicious examination of the implications, and, not unlike a connoisseur of fine literature, a careful consideration of the narrative that emerged from the statistical analyses.

In summary, the methodology employed in this study sought to harmonize the precision of rigorous statistical analyses with a creative flair for unearthing unexpected connections, aiming to shed light on the captivating relationship between air pollution in Riverside, California, and the remarkable home run hitting feats of Matt Kemp.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Riverside, California and Number of home runs hit by Matt Kemp. 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 Baseball Reference .

For the time period 2006 to 2020, you found a correlation 0.8360854, r-squared of 0.6990388, 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]]
"A Breath of Fresh Air: The Lungevity of Home Runs in Riverside, California"

[[ABSTRACT]]
This study investigates the relationship between air pollution levels in Riverside, California, and the number of home runs hit by the professional baseball player Matt Kemp. Using data from the Environmental Protection Agency and Baseball Reference for the period of 2006 to 2020, we found a strong correlation coefficient of 0.8360854 (p < 0.01) between air pollution and Matt Kemp's home run hitting performance.

Our analysis reveals that as air pollution levels in Riverside increased, the number of home runs hit by Matt Kemp also increased, suggesting a potential positive association between the two variables. This unexpected connection may shed light on the elusive factors influencing athletic performance in professional sports.

Furthermore, our findings challenge conventional wisdom and suggest that the air quality in Riverside may play an unintended role as a "homer-enhancing substance" for professional baseball players. This correlation serves as a breath of fresh air in our understanding of the unexpected links between environmental factors and athletic prowess.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the pursuit of understanding the complex interplay between environmental factors and athletic performance, researchers have long sought to uncover the hidden connections that influence the game of baseball. While the focus has primarily been on variables such as player strength, bat speed, and weather conditions, the potential impact of air quality on homerun hitting has remained largely unexplored. However, our study takes a deep dive into this uncharted territory, seeking to elucidate the surprising association between air pollution levels in Riverside, California, and the prolific home run hitting of the formidable player, Matt Kemp.
As we embark on this research journey, it is crucial to maintain a keen eye for unexpected correlations that may emerge, much like a home run sneaks past the outfielders. This study endeavors to not only unravel the statistical relationship between air pollution and home run hitting but also to provide a breath of fresh air in the realm of sports science. It aims to capture the essence of environmental influences on athletic achievements and, quite literally, break new ground in understanding the "air apparent" impact of air quality on baseball performance.
[Insert dad joke] As we navigate through the statistical realm, it is imperative to "pitch" our ideas in a manner that captures the attention of both sports enthusiasts and environmental advocates. After all, just like a well-executed pun, compelling research should elicit both groans and grins, simultaneously expanding our understanding and our appreciation for the unexpected connections that can be found in the world of science.
Utilizing data from reputable sources such as the Environmental Protection Agency and Baseball Reference, this investigation applies rigorous statistical analyses to unearth the correlation between air pollution and the number of home runs hit by Matt Kemp. By scrutinizing the empirical evidence from 2006 to 2020, we aim to shed light on the seemingly improbable link between aerial contaminants and the soaring trajectory of baseballs launched by this esteemed player.
[Insert dad joke] In the tradition of a seasoned umpire, we approach this examination with a discerning eye, fully aware that even the most unassuming factors may prove to be game-changers in the world of sports. Just as a seemingly innocuous bloop single can turn into an unexpected rally, our findings may pave the way for a new innings of research, unravelling the environmental forces at play in the game of baseball.
The implications of this study extend beyond the realm of sports, offering intriguing insights into the intricate web of environmental influences on human performance. The link between air pollution in Riverside and Matt Kemp's home run hitting may serve as a springboard for exploring the broader impact of air quality on athletic achievements, opening doors to novel avenues of investigation in the realm of environmental sports science.
[Insert dad joke] Just as a curveball catches the batter by surprise, we hope that our findings will throw a curveball into conventional understanding, demonstrating that the winds of change in sports science can be influenced by the very air we breathe. This research strives to infuse a breath of fresh air into the discourse on environmental factors in sports, offering a tantalizing glimpse into the unexpected connections that underpin athletic excellence.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis of the data revealed a strong positive correlation between air pollution levels in Riverside, California, and the number of home runs hit by Matt Kemp. The correlation coefficient of 0.8360854 indicated a robust relationship between the two variables. This finding suggests that as air pollution levels increased, so did the number of home runs hit by the esteemed player. It seems the phrase "knocking it out of the park" resonates quite literally in the case of air pollution in Riverside.

The high magnitude of the correlation coefficient, along with the r-squared value of 0.6990388, demonstrates that approximately 69.9% of the variability in Matt Kemp's home run performance can be explained by changes in air pollution levels. It appears that environmental factors may exert a substantial influence on the dynamics of baseball, adding a breath of fresh air to the traditional factors considered in athletic performance.

In the realm of statistical significance, the p-value of less than 0.01 provides strong evidence to reject the null hypothesis that there is no relationship between air pollution levels and Matt Kemp's home run hitting performance. It seems that the air in Riverside holds a surprising secret to the power behind those swings.

Additionally, the scatterplot (Fig. 1) visually illustrates the strong positive correlation between air pollution levels and the number of home runs hit by Matt Kemp. It seems the air quality in Riverside may have been secretly cheering for those home runs after all.

These findings challenge conventional wisdom and imply that the air quality in Riverside, California, may inadvertently serve as a performance-enhancing factor for professional baseball players. The unexpected association uncovered in this study serves as a breath of fresh air, demonstrating the unconventional connections that can be unveiled through rigorous statistical analysis.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Riverside, California and Number of home runs hit by Matt Kemp. 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]]
"A Breath of Fresh Air: The Lungevity of Home Runs in Riverside, California"

[[ABSTRACT]]
This study investigates the relationship between air pollution levels in Riverside, California, and the number of home runs hit by the professional baseball player Matt Kemp. Using data from the Environmental Protection Agency and Baseball Reference for the period of 2006 to 2020, we found a strong correlation coefficient of 0.8360854 (p < 0.01) between air pollution and Matt Kemp's home run hitting performance.

Our analysis reveals that as air pollution levels in Riverside increased, the number of home runs hit by Matt Kemp also increased, suggesting a potential positive association between the two variables. This unexpected connection may shed light on the elusive factors influencing athletic performance in professional sports.

Furthermore, our findings challenge conventional wisdom and suggest that the air quality in Riverside may play an unintended role as a "homer-enhancing substance" for professional baseball players. This correlation serves as a breath of fresh air in our understanding of the unexpected links between environmental factors and athletic prowess.

[[LITERATURE REVIEW]]
The literature on the relationship between environmental factors and athletic performance has predominantly focused on variables such as climate, altitude, and humidity. However, recent studies have begun to hint at the potential influence of air quality on sports outcomes. Smith (2018) examined the impact of air pollution on cardiovascular endurance in athletes, finding a negative association between pollutant levels and performance during endurance activities. Similarly, Doe et al. (2020) investigated the effects of air quality on soccer match outcomes, revealing that higher levels of pollution were correlated with a decrease in player sprinting speed.
In the realm of baseball, the influence of air quality on hitting performance has received limited attention. However, Jones (2019) explored the potential impact of air pollution on batting averages, albeit with inconclusive results. Despite these studies, the specific relationship between air pollution and home run hitting by professional baseball players remains largely unexplored.
[Insert dad joke] Speaking of air quality, did you hear about the baseball team that always played in smoggy conditions? They had some "high-flying" performances, but their opponents couldn't help but "choke" under the pressure.
To elucidate this under-researched connection, our study delves into the unexpected correlation between air pollution levels in Riverside, California, and the number of home runs hit by the renowned player, Matt Kemp. While the notion of air quality serving as a potential "homer-enhancing substance" may seem far-fetched, our analysis aims to bring this airy possibility down to earth.
In the realm of environmental science, diverse literature exists on the study of air pollution and its impact on human health and ecosystems. Notably, "Air Pollution and Health" by Smith (2017) presents a comprehensive overview of the physiological and pathological effects of air pollutants on human respiratory systems. Additionally, "Atmospheric Chemistry and Physics" by Doe (2019) provides detailed insights into the chemical composition of air pollutants and their dispersion in the atmosphere.
[Insert dad joke] Did you hear about the chemist who tried to study air pollution? He really went the extra mile to "air" on the side of caution!
Moving beyond non-fiction literature, one cannot overlook the potential influence of fictional works that may offer indirect insights into the relationship between air pollution and athletic performance. The dystopian novel "Ozone" by John Green imagines a world where air pollution has reached catastrophic levels, prompting characters to adapt their physical activities to the toxic environment. Similarly, in the science fiction classic "The Airborne Athlete" by Jane Austen, the protagonist unveils a remarkable ability to harness the power of airborne particles to enhance athletic prowess.
[Insert dad joke] Did you hear about the baseball player who could hit home runs using polluted air? He really "breathed" new life into the game!
Furthermore, anecdotal evidence from social media posts has hinted at the potential impact of air quality on sports achievements. A tweet by @SportsSciInsights noted an unusual spike in home runs by players during periods of increased air pollution, prompting speculation about the role of atmospheric conditions in altering baseball dynamics. Similarly, a Reddit post on r/BaseballAnalytics recounted an amateur player's experience of hitting remarkable long-distance shots during hazy weather, raising intriguing questions about the interplay between air quality and athletic performance.
[Insert dad joke] I saw an Instagram post about a baseball player hitting home runs in smoggy conditions. It really shed some "light" on the influence of air quality on athletic performance!
In light of the existing literature and anecdotal observations, our study seeks to contribute to the understanding of this unconventional association, striving to unveil the mystifying connection between air pollution in Riverside, California, and the remarkable home run hitting prowess of Matt Kemp. Just as a curveball catches the batter by surprise, our findings promise to offer a new spin on the environmental influences shaping the game of baseball.

[[RESULTS]]
The statistical analysis of the data revealed a strong positive correlation between air pollution levels in Riverside, California, and the number of home runs hit by Matt Kemp. The correlation coefficient of 0.8360854 indicated a robust relationship between the two variables. This finding suggests that as air pollution levels increased, so did the number of home runs hit by the esteemed player. It seems the phrase "knocking it out of the park" resonates quite literally in the case of air pollution in Riverside.
The high magnitude of the correlation coefficient, along with the r-squared value of 0.6990388, demonstrates that approximately 69.9% of the variability in Matt Kemp's home run performance can be explained by changes in air pollution levels. It appears that environmental factors may exert a substantial influence on the dynamics of baseball, adding a breath of fresh air to the traditional factors considered in athletic performance.
In the realm of statistical significance, the p-value of less than 0.01 provides strong evidence to reject the null hypothesis that there is no relationship between air pollution levels and Matt Kemp's home run hitting performance. It seems that the air in Riverside holds a surprising secret to the power behind those swings.
Additionally, the scatterplot (Fig. 1) visually illustrates the strong positive correlation between air pollution levels and the number of home runs hit by Matt Kemp. It seems the air quality in Riverside may have been secretly cheering for those home runs after all.
These findings challenge conventional wisdom and imply that the air quality in Riverside, California, may inadvertently serve as a performance-enhancing factor for professional baseball players. The unexpected association uncovered in this study serves as a breath of fresh air, demonstrating the unconventional connections that can be unveiled through rigorous statistical analysis.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study confirm the surprisingly strong positive correlation between air pollution levels in Riverside, California, and the number of home runs hit by Matt Kemp. This unexpected connection extends our understanding of the potential influence of environmental factors on athletic performance, shedding light on the novel concept of air quality as a potential "homer-enhancing substance." Our findings are in line with prior research that has hinted at the significant impact of air quality on sporting outcomes, bringing this airy possibility down to earth, so to speak.

The robust correlation coefficient of 0.8360854 supports the hypothesis that as air pollution levels increase, so does the number of home runs hit by Matt Kemp. This unusual association may seem like a breath of fresh air in the realm of baseball studies, but it adds a new dimension to the factors influencing athletic prowess. It appears that the air in Riverside holds a surprising secret to the power behind those swings, akin to a well-kept dad joke that catches one off guard.

The high level of explained variability in Matt Kemp's home run performance, as indicated by the r-squared value of 0.6990388, underscores the substantial influence of environmental factors on baseball dynamics. Just as a curveball catches the batter by surprise, our findings promise to offer a new spin on the environmental influences shaping the game, much like the unexpected twist in a good pun.

The statistical significance of our results, with a p-value of less than 0.01, provides strong evidence to reject the null hypothesis. It seems that the air quality in Riverside may have been secretly cheering for those home runs after all, highlighting the unforeseen impact of environmental variables on professional sports performance. This correlation serves as a breath of fresh air in our understanding of the unexpected links between environmental factors and athletic prowess, much like a well-timed dad joke in a serious conversation.

In conclusion, our study brings to the forefront the previously unexplored relationship between air pollution levels in Riverside, California, and the remarkable home run hitting prowess of Matt Kemp. This unexpected connection challenges traditional notions and invites further exploration into the potential influence of environmental factors on athletic achievements. It seems that, just like a good pun, the influence of air quality on sports outcomes may hold unforeseen significance, and we look forward to additional research unraveling the complexities of this unexpected association.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Riverside, California and Number of home runs hit by Matt Kemp. 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]]
"A Breath of Fresh Air: The Lungevity of Home Runs in Riverside, California"

[[ABSTRACT]]
This study investigates the relationship between air pollution levels in Riverside, California, and the number of home runs hit by the professional baseball player Matt Kemp. Using data from the Environmental Protection Agency and Baseball Reference for the period of 2006 to 2020, we found a strong correlation coefficient of 0.8360854 (p < 0.01) between air pollution and Matt Kemp's home run hitting performance.

Our analysis reveals that as air pollution levels in Riverside increased, the number of home runs hit by Matt Kemp also increased, suggesting a potential positive association between the two variables. This unexpected connection may shed light on the elusive factors influencing athletic performance in professional sports.

Furthermore, our findings challenge conventional wisdom and suggest that the air quality in Riverside may play an unintended role as a "homer-enhancing substance" for professional baseball players. This correlation serves as a breath of fresh air in our understanding of the unexpected links between environmental factors and athletic prowess.

[[INTRDUCTION]]
In the pursuit of understanding the complex interplay between environmental factors and athletic performance, researchers have long sought to uncover the hidden connections that influence the game of baseball. While the focus has primarily been on variables such as player strength, bat speed, and weather conditions, the potential impact of air quality on homerun hitting has remained largely unexplored. However, our study takes a deep dive into this uncharted territory, seeking to elucidate the surprising association between air pollution levels in Riverside, California, and the prolific home run hitting of the formidable player, Matt Kemp.
As we embark on this research journey, it is crucial to maintain a keen eye for unexpected correlations that may emerge, much like a home run sneaks past the outfielders. This study endeavors to not only unravel the statistical relationship between air pollution and home run hitting but also to provide a breath of fresh air in the realm of sports science. It aims to capture the essence of environmental influences on athletic achievements and, quite literally, break new ground in understanding the "air apparent" impact of air quality on baseball performance.
[Insert dad joke] As we navigate through the statistical realm, it is imperative to "pitch" our ideas in a manner that captures the attention of both sports enthusiasts and environmental advocates. After all, just like a well-executed pun, compelling research should elicit both groans and grins, simultaneously expanding our understanding and our appreciation for the unexpected connections that can be found in the world of science.
Utilizing data from reputable sources such as the Environmental Protection Agency and Baseball Reference, this investigation applies rigorous statistical analyses to unearth the correlation between air pollution and the number of home runs hit by Matt Kemp. By scrutinizing the empirical evidence from 2006 to 2020, we aim to shed light on the seemingly improbable link between aerial contaminants and the soaring trajectory of baseballs launched by this esteemed player.
[Insert dad joke] In the tradition of a seasoned umpire, we approach this examination with a discerning eye, fully aware that even the most unassuming factors may prove to be game-changers in the world of sports. Just as a seemingly innocuous bloop single can turn into an unexpected rally, our findings may pave the way for a new innings of research, unravelling the environmental forces at play in the game of baseball.
The implications of this study extend beyond the realm of sports, offering intriguing insights into the intricate web of environmental influences on human performance. The link between air pollution in Riverside and Matt Kemp's home run hitting may serve as a springboard for exploring the broader impact of air quality on athletic achievements, opening doors to novel avenues of investigation in the realm of environmental sports science.
[Insert dad joke] Just as a curveball catches the batter by surprise, we hope that our findings will throw a curveball into conventional understanding, demonstrating that the winds of change in sports science can be influenced by the very air we breathe. This research strives to infuse a breath of fresh air into the discourse on environmental factors in sports, offering a tantalizing glimpse into the unexpected connections that underpin athletic excellence.

[[RESULTS]]
The statistical analysis of the data revealed a strong positive correlation between air pollution levels in Riverside, California, and the number of home runs hit by Matt Kemp. The correlation coefficient of 0.8360854 indicated a robust relationship between the two variables. This finding suggests that as air pollution levels increased, so did the number of home runs hit by the esteemed player. It seems the phrase "knocking it out of the park" resonates quite literally in the case of air pollution in Riverside.
The high magnitude of the correlation coefficient, along with the r-squared value of 0.6990388, demonstrates that approximately 69.9% of the variability in Matt Kemp's home run performance can be explained by changes in air pollution levels. It appears that environmental factors may exert a substantial influence on the dynamics of baseball, adding a breath of fresh air to the traditional factors considered in athletic performance.
In the realm of statistical significance, the p-value of less than 0.01 provides strong evidence to reject the null hypothesis that there is no relationship between air pollution levels and Matt Kemp's home run hitting performance. It seems that the air in Riverside holds a surprising secret to the power behind those swings.
Additionally, the scatterplot (Fig. 1) visually illustrates the strong positive correlation between air pollution levels and the number of home runs hit by Matt Kemp. It seems the air quality in Riverside may have been secretly cheering for those home runs after all.
These findings challenge conventional wisdom and imply that the air quality in Riverside, California, may inadvertently serve as a performance-enhancing factor for professional baseball players. The unexpected association uncovered in this study serves as a breath of fresh air, demonstrating the unconventional connections that can be unveiled through rigorous statistical analysis.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[Conclusion]]

In light of the substantial correlation between air pollution levels in Riverside, California, and the number of home runs hit by Matt Kemp, it seems that the phrase "hitting it out of the park" takes on a whole new meaning. Our findings hint at the possibility that air pollution may have been the unseen coach whispering "swing for the fences" to Matt Kemp all along. In this unexpected partnership between environmental factors and athletic performance, the air quality in Riverside appears to have acted as an unintentional cheerleader, rooting for those home runs with every breath.

As we wrap up this study, it's clear that this surprising correlation has hit a home run of its own in the world of sports science. The data speak for themselves, and they seem to be saying, "take a deep breath, and swing for the statistical fences." It's as if the air pollution levels in Riverside were secretly conducting a symphony of statistical significance, harmonizing with each home run hit by Matt Kemp.

We believe our study provides a breath of fresh air in the realm of unexpected connections in sports science and environmental influences. With these results in mind, it's safe to say that the ball is now in the court of further research to explore the ramifications of this unexpected correlation. However, given the weight of evidence we've uncovered, it seems that no further research is needed in this particular area. Let's just say, we've hit this one out of the park!

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 A Breath of Fresh Air: The Lungevity of Home Runs in Riverside, California. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Sports Science and Home Run 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 A Breath of Fresh Air: The Lungevity of Home Runs in Riverside, California. Respond only with the name of a fictional organization.

ChatGPT:

Institute for Urban Homeric Engineering

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 A Breath of Fresh Air: The Lungevity of Home Runs in Riverside, California with an abstract of This study investigates the relationship between air pollution levels in Riverside, California, and the number of home runs hit by the professional baseball player Matt Kemp. Using data from the Environmental Protection Agency and Baseball Reference for the period of 2006 to 2020, we found a strong correlation coefficient of 0.8360854 (p < 0.01) between air pollution and Matt Kemp's home run hitting performance.
Our analysis reveals that as air pollution levels in Riverside increased, the number of home runs hit by Matt Kemp also increased, suggesting a potential positive association between the two variables. This unexpected connection may shed light on the elusive factors influencing athletic performance in professional sports.
Furthermore, our findings challenge conventional wisdom and suggest that the air quality in Riverside may play an unintended role as a "homer-enhancing substance" for professional baseball players. This correlation serves as a breath of fresh air in our understanding of the unexpected links between environmental factors and athletic prowess.

ChatGPT:

Riverside California, air pollution levels, home runs, Matt Kemp, professional baseball, Environmental Protection Agency, Baseball Reference, correlation coefficient, athletic performance, air quality, homer-enhancing substance, environmental factors, unexpected links, professional sports, sports performance

*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 Riverside, California
Detailed data title: Percentage of days with moderate or worse air quality in Riverside-San Bernardino-Ontario, CA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Riverside, California

Number of home runs hit by Matt Kemp
Source: Baseball Reference
See what else correlates with Number of home runs hit by Matt Kemp

Correlation r = 0.8360854 (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 = 0.6990388 (Coefficient of determination)
This means 69.9% of the change in the one variable (i.e., Number of home runs hit by Matt Kemp) is predictable based on the change in the other (i.e., Air pollution in Riverside, California) over the 15 years from 2006 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.000103.^Show 0.0001030200838983467400000000
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 0.84 in 0.0103% of random cases. Said differently, if you correlated 9,707 random variables^Note Which I absolutely did.
with the same 14 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 14 because we have two variables measured over a period of 15 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.

[ 0.57, 0.94 ] 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.

	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Air pollution in Riverside, California (Bad air quality days)	86.8493	88.4931	92.8962	94.7945	95.0685	96.1644	95.6284	93.4247	96.1644	95.3425	95.6284	93.1507	93.1507	88.4931	89.8907
Number of home runs hit by Matt Kemp (Home runs)	7	10	18	26	28	39	23	6	25	23	35	19	21	1	6

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([86.8493,88.4931,92.8962,94.7945,95.0685,96.1644,95.6284,93.4247,96.1644,95.3425,95.6284,93.1507,93.1507,88.4931,89.8907,])
array_2 = np.array([7,10,18,26,28,39,23,6,25,23,35,19,21,1,6,])
array_1_name = "Air pollution in Riverside, California"
array_2_name = "Number of home runs hit by Matt Kemp"

# 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 Riverside, California
Line chart for only Number of home runs hit by Matt Kemp
AI-generated correlation image
The spurious research paper: A Breath of Fresh Air: The Lungevity of Home Runs in Riverside, California

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Correlation ID: 2897 · Black Variable ID: 21145 · Red Variable ID: 367


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