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Spurious correlation #1,798 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of umpires and referees in Michigan and the second variable is Fossil fuel use in Burundi.  The chart goes from 2003 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the number of umpires and referees in Michigan increased, there was a corresponding rise in whistle production. This led to a global shortage of plastic, forcing Burundi to ramp up fossil fuel use for alternative plastic production, and inadvertently blowing the situation out of proportion.

Model: dalle-3
Prompt: [ Concept art ] Create an image of a stadium in Michigan with several umpires and referees standing at the sidelines, engaged in discussion about game strategies. In the background, depict a fleet of cars and buses in Burundi, emitting exhaust as they transport people across the city. Ensure that the contrast between the bustling city and the focused sports environment is visually striking. 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: The number of umpires and referees in Michigan and Fossil fuel use in Burundi. 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: Parallax art Cubism Charcoal Parallax art Concept art
ChatGPT: Concept art

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 The number of umpires and referees in Michigan and Fossil fuel use in Burundi together. Keep the description simple.
ChatGPT: In a stadium in Michigan, several umpires and referees are seen standing at the sidelines, discussing game strategies. In the background, a fleet of cars and buses in Burundi can be seen, emitting exhaust as they transport people across the city.

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: [ Concept art ] and depicting this scene: In a stadium in Michigan, several umpires and referees are seen standing at the sidelines, discussing game strategies. In the background, a fleet of cars and buses in Burundi can be seen, emitting exhaust as they transport people across the city. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Concept art ] Create an image of a stadium in Michigan with several umpires and referees standing at the sidelines, engaged in discussion about game strategies. In the background, depict a fleet of cars and buses in Burundi, emitting exhaust as they transport people across the city. Ensure that the contrast between the bustling city and the focused sports environment is visually striking.

*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 The number of umpires and referees in Michigan caused Fossil fuel use in Burundi to increase.

AI academic paper

(Because p < 0.01)
Refereeing the Fossil Fueled: The Unlikely Link Between Sports Officials in Michigan and Fossil Fuel Use in Burundi

The Journal of Sport Officiating and International Resource Management

Jan 2024

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




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

Make the title punny if you can come up with clever pun. If not, make it sound serious.

Your research team used data from Bureau of Larbor Statistics and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.8402788 and p < 0.01 for 2003 to 2021.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
"Refereeing the Fossil Fueled: The Unlikely Link Between Sports Officials in Michigan and Fossil Fuel Use in Burundi"

[[ABSTRACT]]
In this groundbreaking study, we delved deep into the world of sports officials and fossil fuel consumption to uncover the unexpected relationship between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. While this correlation may seem as unlikely as finding a 4-leaf clover on a soccer field, our findings reveal a statistically significant connection that will leave you both scratching your head and laughing like you've just heard a top-notch dad joke.

Drawing on extensive data from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, our research team uncovered a remarkable correlation coefficient of 0.8402788 and p-value less than 0.01, proving that the relationship between these two seemingly unrelated variables isn't just a fluke (a football reference and a pun – is there a "punt" intended?).

We analyzed the number of umpires and referees in Michigan's various sporting events alongside the per capita fossil fuel use in Burundi, taking into account potential confounding variables such as population size, economic factors, and environmental policy. The results not only presented a strong positive correlation but also provided a fresh perspective on the interconnectedness of global phenomena (a bit like a referee's whistle – hard to ignore!).

So, next time someone asks you about the link between sports officiating and fossil fuel consumption, you can confidently reference our research and watch as minds are blown like a coach disputing a call on the field. After all, when it comes to unusual correlations, we're in a league of our own!


Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 The number of umpires and referees in Michigan and Fossil fuel use in Burundi. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
"Refereeing the Fossil Fueled: The Unlikely Link Between Sports Officials in Michigan and Fossil Fuel Use in Burundi"

[[ABSTRACT]]
In this groundbreaking study, we delved deep into the world of sports officials and fossil fuel consumption to uncover the unexpected relationship between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. While this correlation may seem as unlikely as finding a 4-leaf clover on a soccer field, our findings reveal a statistically significant connection that will leave you both scratching your head and laughing like you've just heard a top-notch dad joke.

Drawing on extensive data from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, our research team uncovered a remarkable correlation coefficient of 0.8402788 and p-value less than 0.01, proving that the relationship between these two seemingly unrelated variables isn't just a fluke (a football reference and a pun – is there a "punt" intended?).

We analyzed the number of umpires and referees in Michigan's various sporting events alongside the per capita fossil fuel use in Burundi, taking into account potential confounding variables such as population size, economic factors, and environmental policy. The results not only presented a strong positive correlation but also provided a fresh perspective on the interconnectedness of global phenomena (a bit like a referee's whistle – hard to ignore!).

So, next time someone asks you about the link between sports officiating and fossil fuel consumption, you can confidently reference our research and watch as minds are blown like a coach disputing a call on the field. After all, when it comes to unusual correlations, we're in a league of our own!

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Sports officiating and fossil fuel use may seem like two subjects as unrelated as basketball and baked goods, but our research has revealed a surprising link between the two. As we embarked on this investigation, we couldn't help but wonder: what do umpires in Michigan have to do with the consumption of fossil fuels in Burundi? It's a riddle that would make even the most seasoned dad joke enthusiast scratch their head in disbelief.

The idea for this study struck us like a lightning bolt – fitting, given the electrifying nature of both sports events and the energy industry. We couldn't pass up the opportunity to delve into this head-scratching conundrum, akin to a referee questioning whether a goal was truly offside or just a near miss. After all, if we can't have a bit of fun with our research, then what's the point?

Across the landscape of academic inquiry, it's not often that sports officiating and environmental matters collide. But here we are, ready to unravel the mystery shrouding the connection between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. It's a bit like finding a pun in the middle of a serious paragraph – unexpected, yet undeniably enjoyable.

This study is not just about uncovering an improbable correlation; it's about challenging conventional thinking and looking at the world of sports and energy consumption through a new lens. Much like a well-executed play in a game, our findings are poised to change the game in the field of unusual correlations. So, sit tight, hold onto your referee's whistle, and get ready for a research journey that's wilder than a mascot causing mischief on the sidelines.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of umpires and referees in Michigan and Fossil fuel use in Burundi. 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 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]]
"Refereeing the Fossil Fueled: The Unlikely Link Between Sports Officials in Michigan and Fossil Fuel Use in Burundi"

[[ABSTRACT]]
In this groundbreaking study, we delved deep into the world of sports officials and fossil fuel consumption to uncover the unexpected relationship between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. While this correlation may seem as unlikely as finding a 4-leaf clover on a soccer field, our findings reveal a statistically significant connection that will leave you both scratching your head and laughing like you've just heard a top-notch dad joke.

Drawing on extensive data from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, our research team uncovered a remarkable correlation coefficient of 0.8402788 and p-value less than 0.01, proving that the relationship between these two seemingly unrelated variables isn't just a fluke (a football reference and a pun – is there a "punt" intended?).

We analyzed the number of umpires and referees in Michigan's various sporting events alongside the per capita fossil fuel use in Burundi, taking into account potential confounding variables such as population size, economic factors, and environmental policy. The results not only presented a strong positive correlation but also provided a fresh perspective on the interconnectedness of global phenomena (a bit like a referee's whistle – hard to ignore!).

So, next time someone asks you about the link between sports officiating and fossil fuel consumption, you can confidently reference our research and watch as minds are blown like a coach disputing a call on the field. After all, when it comes to unusual correlations, we're in a league of our own!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Sports officiating and fossil fuel use may seem like two subjects as unrelated as basketball and baked goods, but our research has revealed a surprising link between the two. As we embarked on this investigation, we couldn't help but wonder: what do umpires in Michigan have to do with the consumption of fossil fuels in Burundi? It's a riddle that would make even the most seasoned dad joke enthusiast scratch their head in disbelief.
The idea for this study struck us like a lightning bolt – fitting, given the electrifying nature of both sports events and the energy industry. We couldn't pass up the opportunity to delve into this head-scratching conundrum, akin to a referee questioning whether a goal was truly offside or just a near miss. After all, if we can't have a bit of fun with our research, then what's the point?
Across the landscape of academic inquiry, it's not often that sports officiating and environmental matters collide. But here we are, ready to unravel the mystery shrouding the connection between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. It's a bit like finding a pun in the middle of a serious paragraph – unexpected, yet undeniably enjoyable.
This study is not just about uncovering an improbable correlation; it's about challenging conventional thinking and looking at the world of sports and energy consumption through a new lens. Much like a well-executed play in a game, our findings are poised to change the game in the field of unusual correlations. So, sit tight, hold onto your referee's whistle, and get ready for a research journey that's wilder than a mascot causing mischief on the sidelines.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

At the outset, it is important to consider the existing literature on the separate topics of sports officiating and environmental impact before delving into the unexpected connection between the two. Smith et al. (2015) conducted a comprehensive analysis of the recruitment and training processes for sports officials in various states across the United States. Their work shed light on the rigorous selection criteria and ongoing professional development required for individuals to take on the responsibilities of an umpire or referee. Meanwhile, Doe and Jones (2018) examined the patterns of fossil fuel consumption in developing countries, highlighting the complex interplay between economic growth, energy utilization, and environmental sustainability.

Turning to a more unconventional source of insight, "The Energy Playbook: From Fouls to Fuels" provides a unique perspective on the intersection of sports and energy consumption. Written by Dr. Leo Cleats, this book discusses the energy dynamics at play during sporting events, drawing parallels between the intensity of competition and the energy demands of society at large. Similarly, "Referees and Renewable Resources: A Field Guide" by Dr. Grace Goalpost delves into the symbiotic relationship between sports officiating and sustainable energy practices, offering a whimsical yet thought-provoking take on the subject matter.

Shifting into the realm of fiction, the novel "Energy and Officiating: A Tale of Two Whistles" by A. P. Offside weaves a narrative that traverses the landscapes of sports arenas and energy facilities, blurring the lines between competition and conservation. In a lighter vein, the children's book "The Little Umpire Who Could: Powering Up for the Planet" by S. Greenfield introduces young readers to the importance of renewable energy, proving that even the smallest whistle-blowers can make a big difference.

Of course, let's not forget the timeless wisdom of animated classics. "Captain Planet and the Planeteers" unapologetically championed environmental stewardship, reminding us that with the power of rings and teamwork, we can combat fossil fuel use just as fervently as contesting an unfavorable call on the field. In a similar vein, the escapades of "The Magic School Bus" took us on educational journeys, sparking our curiosity about the natural world and inspiring us to think critically about our impact on the environment.

Through this eclectic review of literature, we begin to appreciate the multidimensional nature of the subjects at hand, where the serious and the whimsical converge in their exploration of sports officiating, energy consumption, and the unforeseen threads that bind them together. As we further examine our own findings in this area, we invite readers to keep an open mind and perhaps even a referee's whistle handy – you never know when a surprising connection might warrant a good chuckle.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between The number of umpires and referees in Michigan and Fossil fuel use in Burundi. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Larbor Statistics and Energy Information Administration . You used data from 2003 to 2021

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Refereeing the Fossil Fueled: The Unlikely Link Between Sports Officials in Michigan and Fossil Fuel Use in Burundi"

[[ABSTRACT]]
In this groundbreaking study, we delved deep into the world of sports officials and fossil fuel consumption to uncover the unexpected relationship between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. While this correlation may seem as unlikely as finding a 4-leaf clover on a soccer field, our findings reveal a statistically significant connection that will leave you both scratching your head and laughing like you've just heard a top-notch dad joke.

Drawing on extensive data from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, our research team uncovered a remarkable correlation coefficient of 0.8402788 and p-value less than 0.01, proving that the relationship between these two seemingly unrelated variables isn't just a fluke (a football reference and a pun – is there a "punt" intended?).

We analyzed the number of umpires and referees in Michigan's various sporting events alongside the per capita fossil fuel use in Burundi, taking into account potential confounding variables such as population size, economic factors, and environmental policy. The results not only presented a strong positive correlation but also provided a fresh perspective on the interconnectedness of global phenomena (a bit like a referee's whistle – hard to ignore!).

So, next time someone asks you about the link between sports officiating and fossil fuel consumption, you can confidently reference our research and watch as minds are blown like a coach disputing a call on the field. After all, when it comes to unusual correlations, we're in a league of our own!

[[INTRODUCTION]]
Sports officiating and fossil fuel use may seem like two subjects as unrelated as basketball and baked goods, but our research has revealed a surprising link between the two. As we embarked on this investigation, we couldn't help but wonder: what do umpires in Michigan have to do with the consumption of fossil fuels in Burundi? It's a riddle that would make even the most seasoned dad joke enthusiast scratch their head in disbelief.
The idea for this study struck us like a lightning bolt – fitting, given the electrifying nature of both sports events and the energy industry. We couldn't pass up the opportunity to delve into this head-scratching conundrum, akin to a referee questioning whether a goal was truly offside or just a near miss. After all, if we can't have a bit of fun with our research, then what's the point?
Across the landscape of academic inquiry, it's not often that sports officiating and environmental matters collide. But here we are, ready to unravel the mystery shrouding the connection between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. It's a bit like finding a pun in the middle of a serious paragraph – unexpected, yet undeniably enjoyable.
This study is not just about uncovering an improbable correlation; it's about challenging conventional thinking and looking at the world of sports and energy consumption through a new lens. Much like a well-executed play in a game, our findings are poised to change the game in the field of unusual correlations. So, sit tight, hold onto your referee's whistle, and get ready for a research journey that's wilder than a mascot causing mischief on the sidelines.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To unravel the perplexing relationship between the number of umpires and referees in Michigan and the consumption of fossil fuels in Burundi, we employed a multi-faceted approach encompassing data collection, statistical analysis, and enough coffee to keep our research team as alert as a goalkeeper guarding the net. Our data collection spanned the years 2003 to 2021, much like a tennis match that went into an extended tiebreaker.

First, we scoured the Bureau of Labor Statistics for comprehensive information on the number of umpires and referees across various sports events in Michigan, casting a wide net to ensure we didn't miss a single penalty kick or controversial call. Secondly, we turned to the Energy Information Administration to obtain reliable data on the per capita consumption of fossil fuels in Burundi, leaving no stone unturned in our quest to understand the energy dynamics of this East African nation, akin to a thorough investigation by a zealous referee reviewing a contentious play.

Our statistical analysis, much like a precision pass in soccer, involved calculating the Pearson correlation coefficient between the number of sports officials in Michigan and per capita fossil fuel consumption in Burundi. We also performed regression analysis to account for potential confounding variables, employing mathematical models with more complexity than a professional athlete's pre-game ritual.

As with any academic pursuit, we took great care to ensure that our methodology was as rigorous as, well, a stringent referee enforcing the rules of the game. We conducted sensitivity analyses, control group comparisons, and robustness checks to confirm the robustness of our findings, serving as the scientific equivalent of a coach's challenging decision to go for a two-point conversion in the final minutes of a game.

Throughout the process, we maintained the utmost transparency and rigor, adhering to best practices in research methodology while also embracing the occasional pun and dad joke, because what's life without a bit of levity? After all, if our statistical methods can't elicit a smile, then we may need to call a timeout and review our approach like a coach challenging a play on the field.

Now, onto the results – we promise they're more exhilarating than a buzzer-beating three-pointer in basketball!


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

Please make up the results section of an academic research paper presenting the findings of the connection between The number of umpires and referees in Michigan and Fossil fuel use in Burundi. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

For the time period 2003 to 2021, you found a correlation 0.8402788, r-squared of 0.7060685, 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]]
"Refereeing the Fossil Fueled: The Unlikely Link Between Sports Officials in Michigan and Fossil Fuel Use in Burundi"

[[ABSTRACT]]
In this groundbreaking study, we delved deep into the world of sports officials and fossil fuel consumption to uncover the unexpected relationship between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. While this correlation may seem as unlikely as finding a 4-leaf clover on a soccer field, our findings reveal a statistically significant connection that will leave you both scratching your head and laughing like you've just heard a top-notch dad joke.

Drawing on extensive data from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, our research team uncovered a remarkable correlation coefficient of 0.8402788 and p-value less than 0.01, proving that the relationship between these two seemingly unrelated variables isn't just a fluke (a football reference and a pun – is there a "punt" intended?).

We analyzed the number of umpires and referees in Michigan's various sporting events alongside the per capita fossil fuel use in Burundi, taking into account potential confounding variables such as population size, economic factors, and environmental policy. The results not only presented a strong positive correlation but also provided a fresh perspective on the interconnectedness of global phenomena (a bit like a referee's whistle – hard to ignore!).

So, next time someone asks you about the link between sports officiating and fossil fuel consumption, you can confidently reference our research and watch as minds are blown like a coach disputing a call on the field. After all, when it comes to unusual correlations, we're in a league of our own!

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Sports officiating and fossil fuel use may seem like two subjects as unrelated as basketball and baked goods, but our research has revealed a surprising link between the two. As we embarked on this investigation, we couldn't help but wonder: what do umpires in Michigan have to do with the consumption of fossil fuels in Burundi? It's a riddle that would make even the most seasoned dad joke enthusiast scratch their head in disbelief.
The idea for this study struck us like a lightning bolt – fitting, given the electrifying nature of both sports events and the energy industry. We couldn't pass up the opportunity to delve into this head-scratching conundrum, akin to a referee questioning whether a goal was truly offside or just a near miss. After all, if we can't have a bit of fun with our research, then what's the point?
Across the landscape of academic inquiry, it's not often that sports officiating and environmental matters collide. But here we are, ready to unravel the mystery shrouding the connection between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. It's a bit like finding a pun in the middle of a serious paragraph – unexpected, yet undeniably enjoyable.
This study is not just about uncovering an improbable correlation; it's about challenging conventional thinking and looking at the world of sports and energy consumption through a new lens. Much like a well-executed play in a game, our findings are poised to change the game in the field of unusual correlations. So, sit tight, hold onto your referee's whistle, and get ready for a research journey that's wilder than a mascot causing mischief on the sidelines.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Our analysis of the data revealed a striking correlation between the number of umpires and referees in Michigan and the fossil fuel use in Burundi. The correlation coefficient of 0.8402788 illuminated a strong positive relationship, akin to the way a powerful stadium floodlight shines on the field – bright and impossible to ignore.

This unexpected connection between sports officiating and environmental factors may seem as unlikely as a golfer wearing two different colored socks, but our research demonstrates that there is more to this relationship than meets the eye. The statistical significance, with an r-squared value of 0.7060685 and p-value less than 0.01, further solidifies the validity of this peculiar association, leaving skeptics with as much to contemplate as a confusing offside call on the soccer field.

The scatterplot (Fig. 1) visually represents the robust correlation we observed between the two variables, making it clear that this isn't just a chance occurrence – it's a real game-changer.

Our findings shed light on an unexpected intersection between two seemingly disparate worlds, much like a referee's whistle piercing through the noise of a raucous stadium. This research has not only expanded our understanding of the interconnectedness of global phenomena but has also opened the door to a myriad of potential implications that stretch beyond the realm of sports and energy. It's safe to say that this discovery is as unexpected as a surprise substitution in the final minutes of a match.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of umpires and referees in Michigan and Fossil fuel use in Burundi. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
"Refereeing the Fossil Fueled: The Unlikely Link Between Sports Officials in Michigan and Fossil Fuel Use in Burundi"

[[ABSTRACT]]
In this groundbreaking study, we delved deep into the world of sports officials and fossil fuel consumption to uncover the unexpected relationship between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. While this correlation may seem as unlikely as finding a 4-leaf clover on a soccer field, our findings reveal a statistically significant connection that will leave you both scratching your head and laughing like you've just heard a top-notch dad joke.

Drawing on extensive data from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, our research team uncovered a remarkable correlation coefficient of 0.8402788 and p-value less than 0.01, proving that the relationship between these two seemingly unrelated variables isn't just a fluke (a football reference and a pun – is there a "punt" intended?).

We analyzed the number of umpires and referees in Michigan's various sporting events alongside the per capita fossil fuel use in Burundi, taking into account potential confounding variables such as population size, economic factors, and environmental policy. The results not only presented a strong positive correlation but also provided a fresh perspective on the interconnectedness of global phenomena (a bit like a referee's whistle – hard to ignore!).

So, next time someone asks you about the link between sports officiating and fossil fuel consumption, you can confidently reference our research and watch as minds are blown like a coach disputing a call on the field. After all, when it comes to unusual correlations, we're in a league of our own!

[[LITERATURE REVIEW]]
At the outset, it is important to consider the existing literature on the separate topics of sports officiating and environmental impact before delving into the unexpected connection between the two. Smith et al. (2015) conducted a comprehensive analysis of the recruitment and training processes for sports officials in various states across the United States. Their work shed light on the rigorous selection criteria and ongoing professional development required for individuals to take on the responsibilities of an umpire or referee. Meanwhile, Doe and Jones (2018) examined the patterns of fossil fuel consumption in developing countries, highlighting the complex interplay between economic growth, energy utilization, and environmental sustainability.
Turning to a more unconventional source of insight, "The Energy Playbook: From Fouls to Fuels" provides a unique perspective on the intersection of sports and energy consumption. Written by Dr. Leo Cleats, this book discusses the energy dynamics at play during sporting events, drawing parallels between the intensity of competition and the energy demands of society at large. Similarly, "Referees and Renewable Resources: A Field Guide" by Dr. Grace Goalpost delves into the symbiotic relationship between sports officiating and sustainable energy practices, offering a whimsical yet thought-provoking take on the subject matter.
Shifting into the realm of fiction, the novel "Energy and Officiating: A Tale of Two Whistles" by A. P. Offside weaves a narrative that traverses the landscapes of sports arenas and energy facilities, blurring the lines between competition and conservation. In a lighter vein, the children's book "The Little Umpire Who Could: Powering Up for the Planet" by S. Greenfield introduces young readers to the importance of renewable energy, proving that even the smallest whistle-blowers can make a big difference.
Of course, let's not forget the timeless wisdom of animated classics. "Captain Planet and the Planeteers" unapologetically championed environmental stewardship, reminding us that with the power of rings and teamwork, we can combat fossil fuel use just as fervently as contesting an unfavorable call on the field. In a similar vein, the escapades of "The Magic School Bus" took us on educational journeys, sparking our curiosity about the natural world and inspiring us to think critically about our impact on the environment.
Through this eclectic review of literature, we begin to appreciate the multidimensional nature of the subjects at hand, where the serious and the whimsical converge in their exploration of sports officiating, energy consumption, and the unforeseen threads that bind them together. As we further examine our own findings in this area, we invite readers to keep an open mind and perhaps even a referee's whistle handy – you never know when a surprising connection might warrant a good chuckle.

[[RESULTS]]
Our analysis of the data revealed a striking correlation between the number of umpires and referees in Michigan and the fossil fuel use in Burundi. The correlation coefficient of 0.8402788 illuminated a strong positive relationship, akin to the way a powerful stadium floodlight shines on the field – bright and impossible to ignore.
This unexpected connection between sports officiating and environmental factors may seem as unlikely as a golfer wearing two different colored socks, but our research demonstrates that there is more to this relationship than meets the eye. The statistical significance, with an r-squared value of 0.7060685 and p-value less than 0.01, further solidifies the validity of this peculiar association, leaving skeptics with as much to contemplate as a confusing offside call on the soccer field.
The scatterplot (Fig. 1) visually represents the robust correlation we observed between the two variables, making it clear that this isn't just a chance occurrence – it's a real game-changer.
Our findings shed light on an unexpected intersection between two seemingly disparate worlds, much like a referee's whistle piercing through the noise of a raucous stadium. This research has not only expanded our understanding of the interconnectedness of global phenomena but has also opened the door to a myriad of potential implications that stretch beyond the realm of sports and energy. It's safe to say that this discovery is as unexpected as a surprise substitution in the final minutes of a match.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of our study have unveiled a surprising connection between the number of sports officials in Michigan and fossil fuel use in Burundi. While this relationship may seem as puzzling as a soccer team's inability to score because they only brought a rake to the field (they really needed a pitchfork), the statistical significance and strong positive correlation we observed support the notion that there may be more to this connection than meets the eye. Our findings align with the work of Smith et al. (2015) and Doe and Jones (2018), demonstrating a consistent pattern of unexpected linkages across seemingly unrelated phenomena.

In the immortal words of referee jokes, what's the difference between a referee and a school teacher? The referee doesn't grade on a curve. While the humor certainly isn't lost on us, the implications of our research are no laughing matter. Our analysis suggests that the presence of sports officials in one geographic location may influence fossil fuel consumption in a geographically distant region, an unexpected twist that rivals the drama of an underdog team clinching a last-minute victory.

The robust correlation coefficient of 0.8402788, reminiscent of a well-executed penalty kick, underscores the strength of the relationship uncovered in our study. This finding not only upholds the principles espoused in "The Energy Playbook: From Fouls to Fuels" and "Referees and Renewable Resources: A Field Guide" but also offers substantive empirical support for the oft-overlooked intersections between sports officiating and environmental impact.

Our results, akin to a flawless touchdown pass, provide a visual representation of the link between the number of umpires and referees in Michigan and fossil fuel use in Burundi (Fig. 1). This relationship emerges as a game-changer in the discourse on global interconnectedness, prompting further exploration of the intricate web of influence that extends beyond the apparent boundaries of sports and energy. The implications of this discovery are as far-reaching as a well-placed serve in tennis, marking a paradigm shift that demands closer examination of the unexpected repercussions of seemingly unrelated variables.

Our findings invite consideration of a fundamental question: why did the soccer player bring string to the game? Because they wanted to tie the score! Much like the humor inherent in this soccer-themed joke, our research challenges conventional thinking and underscores the importance of looking beyond the obvious to uncover hidden connections that may hold significant implications for global systems. As we continue to unpack the unexpected relationship between sports officiating and environmental impact, it becomes clear that there is more to this story than meets the eye – a revelation as startling as a streaker interrupting a baseball game!

In the absence of a conclusion, we leave readers with the following pun-laden query: why did the soccer ball quit the team? It was tired of being kicked around. Our results, while certainly lighthearted in their presentation, stand as a testament to the potential for unexpected connections to shape our understanding of the world around us. Whether you're a referee on the field or a scientist in the lab, the pursuit of knowledge often leads to revelations that are as surprising as they are enlightening.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of umpires and referees in Michigan and Fossil fuel use in Burundi. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
"Refereeing the Fossil Fueled: The Unlikely Link Between Sports Officials in Michigan and Fossil Fuel Use in Burundi"

[[ABSTRACT]]
In this groundbreaking study, we delved deep into the world of sports officials and fossil fuel consumption to uncover the unexpected relationship between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. While this correlation may seem as unlikely as finding a 4-leaf clover on a soccer field, our findings reveal a statistically significant connection that will leave you both scratching your head and laughing like you've just heard a top-notch dad joke.

Drawing on extensive data from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, our research team uncovered a remarkable correlation coefficient of 0.8402788 and p-value less than 0.01, proving that the relationship between these two seemingly unrelated variables isn't just a fluke (a football reference and a pun – is there a "punt" intended?).

We analyzed the number of umpires and referees in Michigan's various sporting events alongside the per capita fossil fuel use in Burundi, taking into account potential confounding variables such as population size, economic factors, and environmental policy. The results not only presented a strong positive correlation but also provided a fresh perspective on the interconnectedness of global phenomena (a bit like a referee's whistle – hard to ignore!).

So, next time someone asks you about the link between sports officiating and fossil fuel consumption, you can confidently reference our research and watch as minds are blown like a coach disputing a call on the field. After all, when it comes to unusual correlations, we're in a league of our own!

[[INTRDUCTION]]
Sports officiating and fossil fuel use may seem like two subjects as unrelated as basketball and baked goods, but our research has revealed a surprising link between the two. As we embarked on this investigation, we couldn't help but wonder: what do umpires in Michigan have to do with the consumption of fossil fuels in Burundi? It's a riddle that would make even the most seasoned dad joke enthusiast scratch their head in disbelief.
The idea for this study struck us like a lightning bolt – fitting, given the electrifying nature of both sports events and the energy industry. We couldn't pass up the opportunity to delve into this head-scratching conundrum, akin to a referee questioning whether a goal was truly offside or just a near miss. After all, if we can't have a bit of fun with our research, then what's the point?
Across the landscape of academic inquiry, it's not often that sports officiating and environmental matters collide. But here we are, ready to unravel the mystery shrouding the connection between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. It's a bit like finding a pun in the middle of a serious paragraph – unexpected, yet undeniably enjoyable.
This study is not just about uncovering an improbable correlation; it's about challenging conventional thinking and looking at the world of sports and energy consumption through a new lens. Much like a well-executed play in a game, our findings are poised to change the game in the field of unusual correlations. So, sit tight, hold onto your referee's whistle, and get ready for a research journey that's wilder than a mascot causing mischief on the sidelines.

[[RESULTS]]
Our analysis of the data revealed a striking correlation between the number of umpires and referees in Michigan and the fossil fuel use in Burundi. The correlation coefficient of 0.8402788 illuminated a strong positive relationship, akin to the way a powerful stadium floodlight shines on the field – bright and impossible to ignore.
This unexpected connection between sports officiating and environmental factors may seem as unlikely as a golfer wearing two different colored socks, but our research demonstrates that there is more to this relationship than meets the eye. The statistical significance, with an r-squared value of 0.7060685 and p-value less than 0.01, further solidifies the validity of this peculiar association, leaving skeptics with as much to contemplate as a confusing offside call on the soccer field.
The scatterplot (Fig. 1) visually represents the robust correlation we observed between the two variables, making it clear that this isn't just a chance occurrence – it's a real game-changer.
Our findings shed light on an unexpected intersection between two seemingly disparate worlds, much like a referee's whistle piercing through the noise of a raucous stadium. This research has not only expanded our understanding of the interconnectedness of global phenomena but has also opened the door to a myriad of potential implications that stretch beyond the realm of sports and energy. It's safe to say that this discovery is as unexpected as a surprise substitution in the final minutes of a match.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the relationship between the number of umpires and referees in Michigan and fossil fuel use in Burundi has uncovered a remarkable and statistically significant correlation. This unexpected connection has been revealed to be as undeniable as a player's sweat on a jersey after a grueling match. Our findings not only challenge conventional wisdom but also raise eyebrows like a controversial game-winning call.

The magnitude of the correlation coefficient, akin to a weightlifter’s impressive lift, emphasizes the strength of this association, leaving little room for doubt. It's as clear as a cloudless day at a baseball game – the number of sports officials in Michigan has an impact on fossil fuel use in Burundi that cannot be dismissed.

Our research provides compelling evidence that this correlation is more than just a fluke, much like a soccer ball rebounding off the goalpost – it's real and worthy of attention. This discovery stands out in the academic arena like a colorful referee uniform amidst a sea of plain jerseys.

As we wrap up our analysis, it's clear that this unexpected connection is no laughing matter, except for one final dad joke: Why don't referees like to diet? They can't stand to lose a few pounds! But, on a serious note, it’s safe to say that further research into this area is unnecessary. We've already hit a home run with this study, and it's time to move on to other peculiar correlations.


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 Refereeing the Fossil Fueled: The Unlikely Link Between Sports Officials in Michigan and Fossil Fuel Use in Burundi. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Sport Officiating and International Resource Management


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Refereeing the Fossil Fueled: The Unlikely Link Between Sports Officials in Michigan and Fossil Fuel Use in Burundi. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Cross-Cultural Sports and Energy Research


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Refereeing the Fossil Fueled: The Unlikely Link Between Sports Officials in Michigan and Fossil Fuel Use in Burundi with an abstract of In this groundbreaking study, we delved deep into the world of sports officials and fossil fuel consumption to uncover the unexpected relationship between the number of umpires and referees in Michigan and the utilization of fossil fuels in Burundi. While this correlation may seem as unlikely as finding a 4-leaf clover on a soccer field, our findings reveal a statistically significant connection that will leave you both scratching your head and laughing like you've just heard a top-notch dad joke.
Drawing on extensive data from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, our research team uncovered a remarkable correlation coefficient of 0.8402788 and p-value less than 0.01, proving that the relationship between these two seemingly unrelated variables isn't just a fluke (a football reference and a pun – is there a "punt" intended?).
We analyzed the number of umpires and referees in Michigan's various sporting events alongside the per capita fossil fuel use in Burundi, taking into account potential confounding variables such as population size, economic factors, and environmental policy. The results not only presented a strong positive correlation but also provided a fresh perspective on the interconnectedness of global phenomena (a bit like a referee's whistle – hard to ignore!).
So, next time someone asks you about the link between sports officiating and fossil fuel consumption, you can confidently reference our research and watch as minds are blown like a coach disputing a call on the field. After all, when it comes to unusual correlations, we're in a league of our own!

ChatGPT:

fossil fuel consumption, sports officials, Michigan, referees, umpires, correlation, fossil fuel use per capita, Burundi, Bureau of Labor Statistics, Energy Information Administration, global phenomena, environmental policy, population size, economic factors

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



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Data details

The number of umpires and referees in Michigan
Detailed data title: BLS estimate of umpires, referees, and other sports officials in Michigan
Source: Bureau of Larbor Statistics
See what else correlates with The number of umpires and referees in Michigan

Fossil fuel use in Burundi
Detailed data title: Total fossil fuel use in Burundi in billion kWh
Source: Energy Information Administration
See what else correlates with Fossil fuel use in Burundi

Correlation r = 0.8402788 (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 = 0.7060685 (Coefficient of determination)
This means 70.6% of the change in the one variable (i.e., Fossil fuel use in Burundi) is predictable based on the change in the other (i.e., The number of umpires and referees in Michigan) over the 19 years from 2003 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.7E-6. 0.0000067129154620724490000000
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 0.84 in 0.00067% of random cases. Said differently, if you correlated 148,967 random variables You don't actually need 148 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 18 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 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.

[ 0.62, 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.
2003200420052006200720082009201020112012201320142015201620172018201920202021
The number of umpires and referees in Michigan (Laborers)110410410410230240310230290240360430450300650940880620520
Fossil fuel use in Burundi (Billion kWh)0.0020.0020.0020.0020.0020.0020.0020.0020.0120.0030.0260.0370.0330.0290.0790.105090.1229460.1167330.124204




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([110,410,410,410,230,240,310,230,290,240,360,430,450,300,650,940,880,620,520,])
array_2 = np.array([0.002,0.002,0.002,0.002,0.002,0.002,0.002,0.002,0.012,0.003,0.026,0.037,0.033,0.029,0.079,0.10509,0.122946,0.116733,0.124204,])
array_1_name = "The number of umpires and referees in Michigan"
array_2_name = "Fossil fuel use in Burundi"

# 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 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: 1798 · Black Variable ID: 9670 · Red Variable ID: 23561
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