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Spurious correlation #3,291 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Golden Boot Player's English Premier League Goal Tally and the second variable is The number of occupational therapy assistants in Iowa.  The chart goes from 2010 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the Golden Boot Player's English Premier League goal tally increases, more people in Iowa are inspired to pursue careers as occupational therapy assistants in order to help others get back on their feet after their own attempts at recreating the player's impressive goals result in injury. This influx of new occupational therapy assistants leads to a higher demand for their services across the state, ultimately improving the overall well-being of Iowans.

Model: dalle-3
Prompt: [Scene for Cute 2D Animation] In a vibrant soccer stadium, the bright green pitch is filled with enthusiastic fans cheering for their team. A scoreboard with mesmerizing lights displays the Golden Boot Player's name, and each time their goal tally increases, the crowd erupts into cheers. On the sidelines, a group of animated fans attempts to reenact their favorite player's moves, resulting in comical and endearing mishaps. Some fans joyfully mimic their hero's skillful footwork, while others clumsily tumble, causing them to comically collide and fall. In a charming small town in Iowa, a line of adorable injured fans patiently wait outside a welcoming clinic. A friendly sign on the clinic door reads "Occupational Therapy Assistants Needed," adding a heartwarming touch to the scene. 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: Golden Boot Player's English Premier League Goal Tally and The number of occupational therapy assistants in Iowa. 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: Minimalism Cute 2D animation Charcoal a funny image macro Woodblock painting
ChatGPT: Cute 2D animation

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 Golden Boot Player's English Premier League Goal Tally and The number of occupational therapy assistants in Iowa, in the following situation: Because as the Golden Boot Player's goal tally increases, more fans start reenacting their favorite player's moves, leading to an increase in injuries. This causes a surge in demand for occupational therapy assistants in Iowa to help fans recover and get back in the game.. Keep the description simple.
ChatGPT: In a soccer stadium, a scoreboard displays the Golden Boot Player's English Premier League goal tally increasing. Meanwhile, on the sidelines, a group of fans energetically reenact their favorite player's moves, but a few of them end up getting injured. In a nearby town in Iowa, a line of injured fans wait outside a clinic, where a sign reads "Occupational Therapy Assistants Needed".

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: [ Cute 2D animation ] and depicting this scene: In a soccer stadium, a scoreboard displays the Golden Boot Player's English Premier League goal tally increasing. Meanwhile, on the sidelines, a group of fans energetically reenact their favorite player's moves, but a few of them end up getting injured. In a nearby town in Iowa, a line of injured fans wait outside a clinic, where a sign reads "Occupational Therapy Assistants Needed". Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [Scene for Cute 2D Animation] In a vibrant soccer stadium, the bright green pitch is filled with enthusiastic fans cheering for their team. A scoreboard with mesmerizing lights displays the Golden Boot Player's name, and each time their goal tally increases, the crowd erupts into cheers. On the sidelines, a group of animated fans attempts to reenact their favorite player's moves, resulting in comical and endearing mishaps. Some fans joyfully mimic their hero's skillful footwork, while others clumsily tumble, causing them to comically collide and fall. In a charming small town in Iowa, a line of adorable injured fans patiently wait outside a welcoming clinic. A friendly sign on the clinic door reads "Occupational Therapy Assistants Needed," adding a heartwarming touch to the scene.

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

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

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Golden Boot Player's English Premier League Goal Tally caused The number of occupational therapy assistants in Iowa to increase.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)
Scoring Goals and Assisting Occupational Therapy: A Correlation Study in English Premier League and Iowa

Journal of Sports Psychology and Occupational Therapy

Jan 2024

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




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Golden Boot Player's English Premier League Goal Tally and The number of occupational therapy assistants in Iowa. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Include a pun in the title.

Your research team used data from Wikipedia and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.7934608 and p < 0.01 for 2010 to 2022.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Scoring Goals and Assisting Occupational Therapy: A Correlation Study in English Premier League and Iowa

[[ABSTRACT]]
This study investigates the relationship between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa. Using data from Wikipedia for the Golden Boot Player's goal tally and the Bureau of Labor Statistics for occupational therapy assistant numbers, our research team calculated a correlation coefficient of 0.7934608 with a significance level of p < 0.01 for the period 2010 to 2022. The results reveal a statistically significant association between these seemingly unrelated variables, prompting further inquiry into the potential impact of soccer prowess on the demand for occupational therapy assistance. This study aims to provide a lighthearted twist to the often serious academic literature, inviting readers to score some statistical goals of their own in determining the peculiar interplay between football success and healthcare workforce trends.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Golden Boot Player's English Premier League Goal Tally and The number of occupational therapy assistants in Iowa. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
Scoring Goals and Assisting Occupational Therapy: A Correlation Study in English Premier League and Iowa

[[ABSTRACT]]
This study investigates the relationship between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa. Using data from Wikipedia for the Golden Boot Player's goal tally and the Bureau of Labor Statistics for occupational therapy assistant numbers, our research team calculated a correlation coefficient of 0.7934608 with a significance level of p < 0.01 for the period 2010 to 2022. The results reveal a statistically significant association between these seemingly unrelated variables, prompting further inquiry into the potential impact of soccer prowess on the demand for occupational therapy assistance. This study aims to provide a lighthearted twist to the often serious academic literature, inviting readers to score some statistical goals of their own in determining the peculiar interplay between football success and healthcare workforce trends.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
Introduction

The relationship between sports and healthcare may seem as distant as the farthest goal post on the soccer field, but our research aims to kick that notion to the curb. In this study, we delve into the intriguing and seemingly improbable association between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in the heartland of Iowa. What started as a cheeky water cooler conversation in the break room has culminated in a statistical analysis that promises to score high on the scale of quirky research inquiries.

As the lighthearted banter turned into a serious pursuit of knowledge, we scoured the depths of Wikipedia for the illustrious goal-scoring feats of the Golden Boot Player and dove into the depths of the Bureau of Labor Statistics for the numbers of occupational therapy assistants in Iowa. Our data wrangling skills were put to the test as we maneuvered through the twists and turns of soccer statistics and healthcare workforce data, aiming to find the sweet spot where a goal for the team intersects with a helpful assist.

In this paper, we endeavor to bring a delightful blend of statistical analysis and sporting prowess, lacing our findings with the irony of a footballer's goal tally potentially influencing the demand for occupational therapy assistance. Our research injects a dose of good-natured curiosity into the often rigorous world of correlation studies, inviting readers to join us in uncovering the hidden link between the beautiful game and the noble profession of healthcare aiding.

Stay tuned as we take you on a statistical journey that promises to be as thrilling as a last-minute equalizer, all while shedding light on the whimsical intersection of two seemingly disparate realms. Because in the world of research, as in the world of sports, one can never underestimate the potential for an unexpected twist that just might change the game.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Golden Boot Player's English Premier League Goal Tally and The number of occupational therapy assistants in Iowa. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
Scoring Goals and Assisting Occupational Therapy: A Correlation Study in English Premier League and Iowa

[[ABSTRACT]]
This study investigates the relationship between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa. Using data from Wikipedia for the Golden Boot Player's goal tally and the Bureau of Labor Statistics for occupational therapy assistant numbers, our research team calculated a correlation coefficient of 0.7934608 with a significance level of p < 0.01 for the period 2010 to 2022. The results reveal a statistically significant association between these seemingly unrelated variables, prompting further inquiry into the potential impact of soccer prowess on the demand for occupational therapy assistance. This study aims to provide a lighthearted twist to the often serious academic literature, inviting readers to score some statistical goals of their own in determining the peculiar interplay between football success and healthcare workforce trends.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Introduction
The relationship between sports and healthcare may seem as distant as the farthest goal post on the soccer field, but our research aims to kick that notion to the curb. In this study, we delve into the intriguing and seemingly improbable association between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in the heartland of Iowa. What started as a cheeky water cooler conversation in the break room has culminated in a statistical analysis that promises to score high on the scale of quirky research inquiries.
As the lighthearted banter turned into a serious pursuit of knowledge, we scoured the depths of Wikipedia for the illustrious goal-scoring feats of the Golden Boot Player and dove into the depths of the Bureau of Labor Statistics for the numbers of occupational therapy assistants in Iowa. Our data wrangling skills were put to the test as we maneuvered through the twists and turns of soccer statistics and healthcare workforce data, aiming to find the sweet spot where a goal for the team intersects with a helpful assist.
In this paper, we endeavor to bring a delightful blend of statistical analysis and sporting prowess, lacing our findings with the irony of a footballer's goal tally potentially influencing the demand for occupational therapy assistance. Our research injects a dose of good-natured curiosity into the often rigorous world of correlation studies, inviting readers to join us in uncovering the hidden link between the beautiful game and the noble profession of healthcare aiding.
Stay tuned as we take you on a statistical journey that promises to be as thrilling as a last-minute equalizer, all while shedding light on the whimsical intersection of two seemingly disparate realms. Because in the world of research, as in the world of sports, one can never underestimate the potential for an unexpected twist that just might change the game.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The pursuit of uncovering unexpected connections between seemingly unrelated variables has long been a matter of academic intrigue. As we set out to explore the association between the Golden Boot Player's English Premier League goal tally and the number of occupational therapy assistants in Iowa, we are reminded of the insightful findings of Smith et al. in their seminal work "Unearthing Unlikely Links: A Statistical Exploration of Unconventional Correlations." This work emphasized the importance of embracing unpredictability in statistical analyses, and our study is a testament to this approach.

However, as we traverse the landscape of correlation studies, it is essential to not only rely on the serious and the somber. Lightheartedness has its place in academia, and as such, we turn our attention to the work of Doe and Jones, who, in "Surprising Synergies: Statistical Curiosities in Unrelated Phenomena," highlighted the potential for humor and unexpected twists in research inquiries. This paper serves as a delightful precursor to our own investigation, as it encourages scholars to embrace the whimsical in statistical analysis.

Turning to more specific literature related to the fields of soccer statistics and healthcare workforce trends, we encounter a range of books that shed light on the potential intersection of these disciplines. "The Soccer Score: The Statistical Anthropology of Sports Phenomena" by Lorem and Ipsum provides a comprehensive overview of statistical analyses in soccer, offering a unique perspective on the potential influence of individual players on broader societal dynamics.

In the realm of healthcare, "Occupational Therapy in the Heartland: A Statistical Examination of Professional Trends" by Lorem delves into the nuanced dynamics of occupational therapy in the Midwest, laying the groundwork for our own exploration of the demand for occupational therapy assistants in Iowa. This thought-provoking work signifies the importance of considering regional variations in healthcare professions, a theme that resonates with the core of our research inquiry.

While academic literature forms the backbone of our scholarly pursuit, it is also important to embrace a diverse range of influences. Fictional works such as "Goal-Getter's Serendipity" and "The Assist Chronicles: A Tale of Occupational Therapy Triumph" may not directly contribute to statistical analyses, but they serve as a gentle reminder that unexpected connections can often be found in the most unlikely of places.

In the spirit of embracing the art of unexpected correlations, our research team draws inspiration from childhood cartoons and shows that have, in their own quirky way, touched upon themes related to soccer and healthcare. "Rugby Raccoon's Remarkable Goals" and "The Occupational Therapy Octopus" stand as playful nods to the interplay between sports and healthcare, offering a lighthearted perspective on the potential connections that underpin our research endeavor.

As we embark on this statistical odyssey, it is vital to remember that even the most unconventional of pairings may hold valuable insights. With these diverse influences guiding our path, we set out to unravel the peculiar interplay between the thrill of the game and the professionalism of healthcare, all while keeping our spirits high and our statistical inclinations sharp.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Golden Boot Player's English Premier League Goal Tally and The number of occupational therapy assistants in Iowa. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Wikipedia and Bureau of Larbor Statistics . You used data from 2010 to 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Scoring Goals and Assisting Occupational Therapy: A Correlation Study in English Premier League and Iowa

[[ABSTRACT]]
This study investigates the relationship between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa. Using data from Wikipedia for the Golden Boot Player's goal tally and the Bureau of Labor Statistics for occupational therapy assistant numbers, our research team calculated a correlation coefficient of 0.7934608 with a significance level of p < 0.01 for the period 2010 to 2022. The results reveal a statistically significant association between these seemingly unrelated variables, prompting further inquiry into the potential impact of soccer prowess on the demand for occupational therapy assistance. This study aims to provide a lighthearted twist to the often serious academic literature, inviting readers to score some statistical goals of their own in determining the peculiar interplay between football success and healthcare workforce trends.

[[INTRODUCTION]]
Introduction
The relationship between sports and healthcare may seem as distant as the farthest goal post on the soccer field, but our research aims to kick that notion to the curb. In this study, we delve into the intriguing and seemingly improbable association between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in the heartland of Iowa. What started as a cheeky water cooler conversation in the break room has culminated in a statistical analysis that promises to score high on the scale of quirky research inquiries.
As the lighthearted banter turned into a serious pursuit of knowledge, we scoured the depths of Wikipedia for the illustrious goal-scoring feats of the Golden Boot Player and dove into the depths of the Bureau of Labor Statistics for the numbers of occupational therapy assistants in Iowa. Our data wrangling skills were put to the test as we maneuvered through the twists and turns of soccer statistics and healthcare workforce data, aiming to find the sweet spot where a goal for the team intersects with a helpful assist.
In this paper, we endeavor to bring a delightful blend of statistical analysis and sporting prowess, lacing our findings with the irony of a footballer's goal tally potentially influencing the demand for occupational therapy assistance. Our research injects a dose of good-natured curiosity into the often rigorous world of correlation studies, inviting readers to join us in uncovering the hidden link between the beautiful game and the noble profession of healthcare aiding.
Stay tuned as we take you on a statistical journey that promises to be as thrilling as a last-minute equalizer, all while shedding light on the whimsical intersection of two seemingly disparate realms. Because in the world of research, as in the world of sports, one can never underestimate the potential for an unexpected twist that just might change the game.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Data Collection
The initial step in our peculiar pursuit involved collecting data on the goal tally of the Golden Boot Player in the English Premier League. Our intrepid research team scoured the vast expanse of the internet, navigating through the intricate web of football statistics like a seasoned midfielder evading opponents. After countless hours of diligent clicking and scrolling, we unearthed the treasure trove of goal-scoring feats from 2010 to 2022 on the hallowed grounds of Wikipedia. With our laptops ablaze and cups of coffee in hand, we meticulously recorded the goals scored by the Golden Boot Player, ensuring that no goal was left unaccounted for in our data set.

As for the number of occupational therapy assistants in the great state of Iowa, we ventured into the domain of the Bureau of Labor Statistics, trekking through the statistical wilderness like adventurous explorers seeking a hidden treasure. Braving the labyrinth of occupational data, we meticulously tallied the number of occupational therapy assistants from 2010 to 2022, ensuring that our dataset was as robust as a resilient defense thwarting a goal-scoring attempt.

Data Analysis
With our trusty dataset in hand, we delved into the realm of statistical analysis, armed with our arsenal of correlation coefficients and significance tests. Employing the formidable tools of research, we calculated the correlation coefficient between the goal tally of the Golden Boot Player and the number of occupational therapy assistants in Iowa with the precision of a free-kick finding the top corner of the net. Our statistical journey led us to a correlation coefficient of 0.7934608, signaling a strong association between these seemingly incongruent variables.

To validate the robustness of our findings, we subjected our correlation coefficient to the scrutiny of significance testing, utilizing the classic p-value to ascertain the likelihood of our results occurring by mere chance. With a significance level of p < 0.01, our findings emerged as statistically significant, standing as tall as a towering center-back thwarting an opponent's scoring attempt.

Limitations
Despite our valiant efforts and the remarkable findings that emerged from our study, it is essential to acknowledge the limitations that accompanied our quirky quest. The reliance on publicly available data, such as that from Wikipedia and the Bureau of Labor Statistics, may introduce potential biases and inaccuracies. However, in the spirit of academic honesty, we aimed to mitigate these limitations through rigorous data verification and validation, akin to a diligent referee scrutinizing a contentious offside call.

Furthermore, while our correlation analysis revealed a compelling relationship between the goal tally of the Golden Boot Player and the number of occupational therapy assistants in Iowa, causation remains an elusive rival on the sports field of statistical inference. We recognize the need for caution in inferring direct causal mechanisms from our findings and encourage further research to untangle the intricate web of associations between sports excellence and healthcare workforce dynamics.

In conclusion, our methodology, though unconventional, led us to uncover a statistically significant connection between the art of goal scoring in the English Premier League and the demand for occupational therapy assistance in Iowa. Our research endeavors to infuse levity into the often serious discourse of academic inquiry, highlighting the unexpected synergies that unfold when statistical analysis meets the world of sports and healthcare. As we take a playful toe-poke at the intersection of these seemingly disparate realms, we invite fellow researchers to join us in unraveling the enigmatic tapestry of correlations that define the intriguing world of statistics and sporting feats. After all, in the realm of research, as in the realm of sports, one must always be prepared for the unexpected twist that just might change the game.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Golden Boot Player's English Premier League Goal Tally and The number of occupational therapy assistants in Iowa. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

For the time period 2010 to 2022, you found a correlation 0.7934608, r-squared of 0.6295800, 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]]
Scoring Goals and Assisting Occupational Therapy: A Correlation Study in English Premier League and Iowa

[[ABSTRACT]]
This study investigates the relationship between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa. Using data from Wikipedia for the Golden Boot Player's goal tally and the Bureau of Labor Statistics for occupational therapy assistant numbers, our research team calculated a correlation coefficient of 0.7934608 with a significance level of p < 0.01 for the period 2010 to 2022. The results reveal a statistically significant association between these seemingly unrelated variables, prompting further inquiry into the potential impact of soccer prowess on the demand for occupational therapy assistance. This study aims to provide a lighthearted twist to the often serious academic literature, inviting readers to score some statistical goals of their own in determining the peculiar interplay between football success and healthcare workforce trends.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Introduction
The relationship between sports and healthcare may seem as distant as the farthest goal post on the soccer field, but our research aims to kick that notion to the curb. In this study, we delve into the intriguing and seemingly improbable association between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in the heartland of Iowa. What started as a cheeky water cooler conversation in the break room has culminated in a statistical analysis that promises to score high on the scale of quirky research inquiries.
As the lighthearted banter turned into a serious pursuit of knowledge, we scoured the depths of Wikipedia for the illustrious goal-scoring feats of the Golden Boot Player and dove into the depths of the Bureau of Labor Statistics for the numbers of occupational therapy assistants in Iowa. Our data wrangling skills were put to the test as we maneuvered through the twists and turns of soccer statistics and healthcare workforce data, aiming to find the sweet spot where a goal for the team intersects with a helpful assist.
In this paper, we endeavor to bring a delightful blend of statistical analysis and sporting prowess, lacing our findings with the irony of a footballer's goal tally potentially influencing the demand for occupational therapy assistance. Our research injects a dose of good-natured curiosity into the often rigorous world of correlation studies, inviting readers to join us in uncovering the hidden link between the beautiful game and the noble profession of healthcare aiding.
Stay tuned as we take you on a statistical journey that promises to be as thrilling as a last-minute equalizer, all while shedding light on the whimsical intersection of two seemingly disparate realms. Because in the world of research, as in the world of sports, one can never underestimate the potential for an unexpected twist that just might change the game.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our correlation analysis between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa have yielded some rather striking findings. The correlation coefficient of 0.7934608 indicates a strong positive relationship between these seemingly unrelated variables, suggesting that as the Golden Boot Player's goal tally increases, the number of occupational therapy assistants in Iowa also tends to rise. The r-squared value of 0.6295800 further reinforces the robustness of this relationship, explaining approximately 63% of the variation in occupational therapy assistant numbers based on the variations in the Golden Boot Player's goal tally.

With a significance level of p < 0.01, the correlation is deemed statistically significant, which raises both eyebrows and soccer balls in the world of statistical analysis. It seems that the influence of scoring prowess on healthcare assistance in Iowa is not just a wild kick at the goal, but rather a carefully calculated pass that finds its way into the net of research significance.

Our findings are graphically encapsulated in the scatterplot shown in Figure 1. The plot visually depicts the strong positive correlation between the two variables, with each data point representing a delightful blend of statistical intrigue and the thrill of the soccer field. It's as if each plotted point serves as a reminder that in the world of research, just like in sports, the unexpected twist might just be the key to unraveling the most enigmatic relationships.

In conclusion, our results not only highlight the statistically significant association between the Golden Boot Player's English Premier League goal tally and the number of occupational therapy assistants in Iowa, but also underscore the importance of embracing the unexpected in the pursuit of knowledge. Our study sets the stage for further exploration into the whimsical interplay between the world of football and the realm of healthcare, inviting readers to join us in uncovering the delightful mysteries that lurk in the most unexpected corners of statistical analysis. After all, in the game of research, when it comes to uncovering hidden relationships, sometimes all it takes is a well-placed statistical assist to score a winning goal.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Golden Boot Player's English Premier League Goal Tally and The number of occupational therapy assistants in Iowa. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Scoring Goals and Assisting Occupational Therapy: A Correlation Study in English Premier League and Iowa

[[ABSTRACT]]
This study investigates the relationship between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa. Using data from Wikipedia for the Golden Boot Player's goal tally and the Bureau of Labor Statistics for occupational therapy assistant numbers, our research team calculated a correlation coefficient of 0.7934608 with a significance level of p < 0.01 for the period 2010 to 2022. The results reveal a statistically significant association between these seemingly unrelated variables, prompting further inquiry into the potential impact of soccer prowess on the demand for occupational therapy assistance. This study aims to provide a lighthearted twist to the often serious academic literature, inviting readers to score some statistical goals of their own in determining the peculiar interplay between football success and healthcare workforce trends.

[[LITERATURE REVIEW]]
The pursuit of uncovering unexpected connections between seemingly unrelated variables has long been a matter of academic intrigue. As we set out to explore the association between the Golden Boot Player's English Premier League goal tally and the number of occupational therapy assistants in Iowa, we are reminded of the insightful findings of Smith et al. in their seminal work "Unearthing Unlikely Links: A Statistical Exploration of Unconventional Correlations." This work emphasized the importance of embracing unpredictability in statistical analyses, and our study is a testament to this approach.
However, as we traverse the landscape of correlation studies, it is essential to not only rely on the serious and the somber. Lightheartedness has its place in academia, and as such, we turn our attention to the work of Doe and Jones, who, in "Surprising Synergies: Statistical Curiosities in Unrelated Phenomena," highlighted the potential for humor and unexpected twists in research inquiries. This paper serves as a delightful precursor to our own investigation, as it encourages scholars to embrace the whimsical in statistical analysis.
Turning to more specific literature related to the fields of soccer statistics and healthcare workforce trends, we encounter a range of books that shed light on the potential intersection of these disciplines. "The Soccer Score: The Statistical Anthropology of Sports Phenomena" by Lorem and Ipsum provides a comprehensive overview of statistical analyses in soccer, offering a unique perspective on the potential influence of individual players on broader societal dynamics.
In the realm of healthcare, "Occupational Therapy in the Heartland: A Statistical Examination of Professional Trends" by Lorem delves into the nuanced dynamics of occupational therapy in the Midwest, laying the groundwork for our own exploration of the demand for occupational therapy assistants in Iowa. This thought-provoking work signifies the importance of considering regional variations in healthcare professions, a theme that resonates with the core of our research inquiry.
While academic literature forms the backbone of our scholarly pursuit, it is also important to embrace a diverse range of influences. Fictional works such as "Goal-Getter's Serendipity" and "The Assist Chronicles: A Tale of Occupational Therapy Triumph" may not directly contribute to statistical analyses, but they serve as a gentle reminder that unexpected connections can often be found in the most unlikely of places.
In the spirit of embracing the art of unexpected correlations, our research team draws inspiration from childhood cartoons and shows that have, in their own quirky way, touched upon themes related to soccer and healthcare. "Rugby Raccoon's Remarkable Goals" and "The Occupational Therapy Octopus" stand as playful nods to the interplay between sports and healthcare, offering a lighthearted perspective on the potential connections that underpin our research endeavor.
As we embark on this statistical odyssey, it is vital to remember that even the most unconventional of pairings may hold valuable insights. With these diverse influences guiding our path, we set out to unravel the peculiar interplay between the thrill of the game and the professionalism of healthcare, all while keeping our spirits high and our statistical inclinations sharp.

[[RESULTS]]
The results of our correlation analysis between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa have yielded some rather striking findings. The correlation coefficient of 0.7934608 indicates a strong positive relationship between these seemingly unrelated variables, suggesting that as the Golden Boot Player's goal tally increases, the number of occupational therapy assistants in Iowa also tends to rise. The r-squared value of 0.6295800 further reinforces the robustness of this relationship, explaining approximately 63% of the variation in occupational therapy assistant numbers based on the variations in the Golden Boot Player's goal tally.
With a significance level of p < 0.01, the correlation is deemed statistically significant, which raises both eyebrows and soccer balls in the world of statistical analysis. It seems that the influence of scoring prowess on healthcare assistance in Iowa is not just a wild kick at the goal, but rather a carefully calculated pass that finds its way into the net of research significance.
Our findings are graphically encapsulated in the scatterplot shown in Figure 1. The plot visually depicts the strong positive correlation between the two variables, with each data point representing a delightful blend of statistical intrigue and the thrill of the soccer field. It's as if each plotted point serves as a reminder that in the world of research, just like in sports, the unexpected twist might just be the key to unraveling the most enigmatic relationships.
In conclusion, our results not only highlight the statistically significant association between the Golden Boot Player's English Premier League goal tally and the number of occupational therapy assistants in Iowa, but also underscore the importance of embracing the unexpected in the pursuit of knowledge. Our study sets the stage for further exploration into the whimsical interplay between the world of football and the realm of healthcare, inviting readers to join us in uncovering the delightful mysteries that lurk in the most unexpected corners of statistical analysis. After all, in the game of research, when it comes to uncovering hidden relationships, sometimes all it takes is a well-placed statistical assist to score a winning goal.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of our study have indeed cast a light on the unexpectedly connected worlds of soccer and healthcare, as our findings provide compelling evidence for a strong positive relationship between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa. This peculiar linkage echoes the sentiment of Smith et al. in their emphasis on embracing unpredictability in statistical analyses, with our study serving as a resounding testament to the enigmatic nature of correlation research.

In a serendipitous twist, our statistically significant correlation coefficient of 0.7934608 aligns with the account of Doe and Jones, who championed the potential for humor and unexpected turns in research inquiries. While we may have initially approached this investigation with a lighthearted curiosity, the robustness of the statistical association has prompted a deeper reflection on the underlying mechanisms that might intertwine the soccer field with the healthcare landscape.

As we traverse this uncharted terrain of statistical inquiry, we cannot overlook the lighthearted influences that have guided our path. The vibrant tapestry of literature, spanning from the insightful works of Lorem and Ipsum in soccer statistics to the whimsical musings of childhood cartoons, has undoubtedly left its mark on our scholarly journey. The seemingly unconventional pairings and playful musings have, in their own quirky way, spurred a deeper appreciation for the unexpected in statistical analysis, serving as constant reminders that statistical correlations, much like a well-executed dribble on the field, can lead to surprising outcomes.

The delightfully compelling r-squared value of 0.6295800 further corroborates the strength of the relationship uncovered in our study, offering a statistical testament to the intertwined dance of soccer prowess and healthcare assistance in Iowa. This quantifiable measure of variation underscores the significance of the Golden Boot Player's goal tally as an influential factor in the dynamics of occupational therapy assistant numbers, turning what may have initially seemed like a whimsical pursuit into a meticulously calculated statistical observation.

The scatterplot visual representation of our results, captured in Figure 1, is not just a depiction of data points; it is a vivid portrayal of the harmonious convergence of statistical intrigue and the spirit of the soccer field. Each point on the plot serves as a testament to the unanticipated correlations that lie beneath the surface, a true reflection of the delightful and often surprising mysteries that underpin statistical analysis.

In drawing these threads together, our study has not only unearthed a statistically significant association but has also sparked a lighthearted appreciation for the peculiar interplay between two seemingly distinct domains. We invite readers to join us in this delightful odyssey of statistical exploration, where the unexpected unlock a world of scientific curiosity and statistical amusement. After all, in the grand scheme of research, a well-placed statistical assist might just be the winning goal in unraveling the most captivating of scientific enigmas.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Golden Boot Player's English Premier League Goal Tally and The number of occupational therapy assistants in Iowa. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Scoring Goals and Assisting Occupational Therapy: A Correlation Study in English Premier League and Iowa

[[ABSTRACT]]
This study investigates the relationship between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa. Using data from Wikipedia for the Golden Boot Player's goal tally and the Bureau of Labor Statistics for occupational therapy assistant numbers, our research team calculated a correlation coefficient of 0.7934608 with a significance level of p < 0.01 for the period 2010 to 2022. The results reveal a statistically significant association between these seemingly unrelated variables, prompting further inquiry into the potential impact of soccer prowess on the demand for occupational therapy assistance. This study aims to provide a lighthearted twist to the often serious academic literature, inviting readers to score some statistical goals of their own in determining the peculiar interplay between football success and healthcare workforce trends.

[[INTRDUCTION]]
Introduction
The relationship between sports and healthcare may seem as distant as the farthest goal post on the soccer field, but our research aims to kick that notion to the curb. In this study, we delve into the intriguing and seemingly improbable association between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in the heartland of Iowa. What started as a cheeky water cooler conversation in the break room has culminated in a statistical analysis that promises to score high on the scale of quirky research inquiries.
As the lighthearted banter turned into a serious pursuit of knowledge, we scoured the depths of Wikipedia for the illustrious goal-scoring feats of the Golden Boot Player and dove into the depths of the Bureau of Labor Statistics for the numbers of occupational therapy assistants in Iowa. Our data wrangling skills were put to the test as we maneuvered through the twists and turns of soccer statistics and healthcare workforce data, aiming to find the sweet spot where a goal for the team intersects with a helpful assist.
In this paper, we endeavor to bring a delightful blend of statistical analysis and sporting prowess, lacing our findings with the irony of a footballer's goal tally potentially influencing the demand for occupational therapy assistance. Our research injects a dose of good-natured curiosity into the often rigorous world of correlation studies, inviting readers to join us in uncovering the hidden link between the beautiful game and the noble profession of healthcare aiding.
Stay tuned as we take you on a statistical journey that promises to be as thrilling as a last-minute equalizer, all while shedding light on the whimsical intersection of two seemingly disparate realms. Because in the world of research, as in the world of sports, one can never underestimate the potential for an unexpected twist that just might change the game.

[[RESULTS]]
The results of our correlation analysis between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa have yielded some rather striking findings. The correlation coefficient of 0.7934608 indicates a strong positive relationship between these seemingly unrelated variables, suggesting that as the Golden Boot Player's goal tally increases, the number of occupational therapy assistants in Iowa also tends to rise. The r-squared value of 0.6295800 further reinforces the robustness of this relationship, explaining approximately 63% of the variation in occupational therapy assistant numbers based on the variations in the Golden Boot Player's goal tally.
With a significance level of p < 0.01, the correlation is deemed statistically significant, which raises both eyebrows and soccer balls in the world of statistical analysis. It seems that the influence of scoring prowess on healthcare assistance in Iowa is not just a wild kick at the goal, but rather a carefully calculated pass that finds its way into the net of research significance.
Our findings are graphically encapsulated in the scatterplot shown in Figure 1. The plot visually depicts the strong positive correlation between the two variables, with each data point representing a delightful blend of statistical intrigue and the thrill of the soccer field. It's as if each plotted point serves as a reminder that in the world of research, just like in sports, the unexpected twist might just be the key to unraveling the most enigmatic relationships.
In conclusion, our results not only highlight the statistically significant association between the Golden Boot Player's English Premier League goal tally and the number of occupational therapy assistants in Iowa, but also underscore the importance of embracing the unexpected in the pursuit of knowledge. Our study sets the stage for further exploration into the whimsical interplay between the world of football and the realm of healthcare, inviting readers to join us in uncovering the delightful mysteries that lurk in the most unexpected corners of statistical analysis. After all, in the game of research, when it comes to uncovering hidden relationships, sometimes all it takes is a well-placed statistical assist to score a winning goal.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has uncovered a statistically significant correlation between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa. The robust correlation coefficient of 0.7934608 with a p-value of less than 0.01 highlights the surprising connection between soccer prowess and the demand for healthcare assistance in the heartland of Iowa. Our findings not only add a whimsical twist to the world of statistical analysis but also emphasize the importance of embracing the unexpected. It seems that in the game of research, as in the game of football, the most unpredictable connections can lead to the most intriguing outcomes. It's as if statistics and soccer have come together for a well-coordinated play that defies conventional expectations, reminding us that in the world of correlation studies, as in the world of sports, a well-timed assist can lead to a winning goal. With our study providing a delightful blend of statistical analysis and sporting intrigue, it is safe to say that no further research is needed in this area. After all, when it comes to uncovering unexpected correlations, sometimes all it takes is the right combination of variables and a dash of statistical flair to kick the ball into the back of the net.


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 Scoring Goals and Assisting Occupational Therapy: A Correlation Study in English Premier League and Iowa. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Sports Psychology and Occupational Therapy


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 Scoring Goals and Assisting Occupational Therapy: A Correlation Study in English Premier League and Iowa. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Sport and Occupational Therapy Research (SSOTR)


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 Scoring Goals and Assisting Occupational Therapy: A Correlation Study in English Premier League and Iowa with an abstract of This study investigates the relationship between the goal tally of the Golden Boot Player in the English Premier League and the number of occupational therapy assistants in Iowa. Using data from Wikipedia for the Golden Boot Player's goal tally and the Bureau of Labor Statistics for occupational therapy assistant numbers, our research team calculated a correlation coefficient of 0.7934608 with a significance level of p < 0.01 for the period 2010 to 2022. The results reveal a statistically significant association between these seemingly unrelated variables, prompting further inquiry into the potential impact of soccer prowess on the demand for occupational therapy assistance. This study aims to provide a lighthearted twist to the often serious academic literature, inviting readers to score some statistical goals of their own in determining the peculiar interplay between football success and healthcare workforce trends.

ChatGPT:

English Premier League, Golden Boot Player, occupational therapy assistants, Iowa, correlation study, Bureau of Labor Statistics, soccer prowess, occupational therapy demand, healthcare workforce trends

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



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Data details

Golden Boot Player's English Premier League Goal Tally
Source: Wikipedia
See what else correlates with Golden Boot Player's English Premier League Goal Tally

The number of occupational therapy assistants in Iowa
Detailed data title: BLS estimate of occupational therapy assistants in Iowa
Source: Bureau of Larbor Statistics
See what else correlates with The number of occupational therapy assistants in Iowa

Correlation r = 0.7934608 (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 = 0.6295800 (Coefficient of determination)
This means 63% of the change in the one variable (i.e., The number of occupational therapy assistants in Iowa) is predictable based on the change in the other (i.e., Golden Boot Player's English Premier League Goal Tally) over the 13 years from 2010 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00121. 0.0012068066471149550000000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.79 in 0.121% of random cases. Said differently, if you correlated 829 random variables Which I absolutely did.
with the same 12 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 12 because we have two variables measured over a period of 13 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.43, 0.94 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
2010201120122013201420152016201720182019202020212022
Golden Boot Player's English Premier League Goal Tally (Goals scored)20302631262529322223232336
The number of occupational therapy assistants in Iowa (Laborers)330360410390360400420420360350380340460




Why this works

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




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([20,30,26,31,26,25,29,32,22,23,23,23,36,])
array_2 = np.array([330,360,410,390,360,400,420,420,360,350,380,340,460,])
array_1_name = "Golden Boot Player's English Premier League Goal Tally"
array_2_name = "The number of occupational therapy assistants in Iowa"

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

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



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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. 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.

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Correlation ID: 3291 · Black Variable ID: 71 · Red Variable ID: 18073
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