Spurious correlation #1,681 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up and the second variable is Kerosene used in Barbados. The chart goes from 1982 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up and the second variable is Kerosene used in Barbados. The chart goes from 1982 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the NCAA Women's Softball Championship final score difference increased, there was a corresponding surge in celebratory fireworks. These fireworks led to a spike in demand for kerosene used in Barbados for lighting up the post-victory parties and creating a festive atmosphere. After all, what better way to celebrate a big win than with some fiery competition on and off the field!

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Generate an image that replicates the style of a classic black-and-white newspaper illustration. Depict a small, lively stadium in Barbados, with a gigantic scoreboard illuminated by kerosene lamps, displaying the final score difference between the winners and runners-up in the NCAA Women's Softball Championship. The bright glow of the kerosene lamps should bathe the proud faces of the winning team as they celebrate their victory, while the runners-up stand in respectful concession of defeat. Keep the visual portrayal straightforward, avoiding any words or speech bubbles. 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: NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up and Kerosene used in Barbados. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Art nouveau A TIME magazine cover image Whimsical illustration A scene from Skyrim A black-and-white newspaper illustration
ChatGPT: A black-and-white newspaper illustration

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 NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up and Kerosene used in Barbados together. Keep the description simple.
ChatGPT: In a small, vibrant stadium in Barbados, the final score difference between the winners and runners-up in the NCAA Women's Softball Championship is displayed on a gigantic scoreboard powered by kerosene lamps. The bright glow of the kerosene lamps illuminates the proud faces of the winning team, as they celebrate their victory on the field, while the runners-up stand in respect, conceding defeat with grace.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A black-and-white newspaper illustration ] and depicting this scene: In a small, vibrant stadium in Barbados, the final score difference between the winners and runners-up in the NCAA Women's Softball Championship is displayed on a gigantic scoreboard powered by kerosene lamps. The bright glow of the kerosene lamps illuminates the proud faces of the winning team, as they celebrate their victory on the field, while the runners-up stand in respect, conceding defeat with grace. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image that replicates the style of a classic black-and-white newspaper illustration. Depict a small, lively stadium in Barbados, with a gigantic scoreboard illuminated by kerosene lamps, displaying the final score difference between the winners and runners-up in the NCAA Women's Softball Championship. The bright glow of the kerosene lamps should bathe the proud faces of the winning team as they celebrate their victory, while the runners-up stand in respectful concession of defeat. Keep the visual portrayal straightforward, avoiding any words or speech bubbles.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up positively influenced Kerosene used in Barbados. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)

Softball Scores and Kerosene Consumption: An Amusing Analysis

The Journal of Playful Research

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up and Kerosene used in Barbados. Make lots of 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.

Here is the title and abstract of the paper:
[[TITLE]]
Softball Scores and Kerosene Consumption: An Amusing Analysis

[[ABSTRACT]]
This peculiar study examined the correlation between the final score difference in NCAA Women's Softball Championship (Div I) games and kerosene consumption in the beautiful island of Barbados. We collected data from the NCAA and the Energy Information Administration to answer this offbeat question. Our findings revealed a surprisingly high correlation coefficient of 0.6454373 and a statistically significant p-value of less than 0.01 for the time period spanning 1982 to 2021. This unexpected connection suggests that there may be more to the game of softball and the use of kerosene in Barbados than meets the eye. The implications of these findings are sure to spark curiosity and perhaps even a few chuckles among researchers and softball enthusiasts alike.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The connection between seemingly unrelated variables has been a subject of great fascination for researchers across various disciplines. In the world of sports, studies have explored the influence of factors such as weather, crowd size, and team performance on game outcomes. However, the potential link between NCAA Women's Softball Championship (Div I) final score differences and kerosene consumption in Barbados is a peculiar and unexpected subject for investigation.
The notion that the intensity of a softball game could have any bearing on the consumption of kerosene in a distant tropical paradise may strike some as whimsical or even comical. Nonetheless, it is precisely this element of surprise that often leads to the most intriguing and thought-provoking scientific discoveries. As such, this study embarks on a lighthearted yet earnest exploration of the statistical relationship between these two seemingly unrelated phenomena.
While on the surface, the idea of associating the athletic prowess of collegiate softball players with the utilization of kerosene in Barbados may elicit a few chuckles, the statistical analysis to follow presents some compelling findings. The aim of this research is not only to unveil potential correlations but also to generate a sense of wonder about the hidden connections that may lurk beneath the surface of our seemingly disparate world.
Through the use of historical championship game data and kerosene consumption statistics, this study seeks to shed light on a perplexing and amusing correlation that may prompt a playful raising of eyebrows among the scholarly community – and perhaps a few smiles as well. The implications of this unexpected association are bound to spark curiosity and intrigue, providing a welcome departure from the traditional realms of academic inquiry.
Even as we assume a serious and rigorous demeanor in our scholarly pursuits, there is ample room for a touch of whimsy and humor, especially when unearthing unforeseen connections between softball championships and kerosene usage in a distant Caribbean island. With that said, let us delve into the depths of this unconventional investigation and unearth the whimsical yet intriguing insights it has to offer.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Previous research on the subject of NCAA Women's Softball Championship (Div I) final score differences and their correlation with kerosene usage in Barbados has been minimal yet surprisingly engaging. Smith et al. (2015) delved into the world of sports and energy consumption, but their focus was primarily on basketball and renewable energy sources. Meanwhile, Doe and Jones (2018) explored the societal impact of collegiate sports on small island economies, yet unfortunately, their work did not extend to the intricate connection between softball games and kerosene consumption.

Turning to the broader literature, "Energy Economics" by Ott and Long (2019) offers a comprehensive analysis of energy consumption patterns across different regions, but regrettably, it overlooks the specific nuances of kerosene usage in Barbados. In a similar vein, "Sports Statistics: A Comprehensive Guide" by Johnson and Smith (2017) provides an extensive overview of statistical methods in sports analysis, but the peculiar interplay between softball championship outcomes and kerosene remains conspicuously absent.

Seeking inspiration from fictional narratives, "The Softball Chronicles" by Miller (2016) and "Kerosene Dreams" by Parker (2018) offered no concrete insights but did provide an enjoyable departure into the world of imaginative storytelling. However, our quest for empirical evidence demanded a more rigorous approach.

In a bold departure from convention, the authors resorted to a rather unorthodox source of information – the mundane yet surprisingly informative world of CVS receipts – to glean insights into consumer behavior and potential connections with sporting events and energy consumption. These whimsical detours, though nontraditional, served to underscore the element of surprise and amusement that often crops up in the pursuit of knowledge.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up and Kerosene used in Barbados. Make lots of jokes, goofy observations, and puns. 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 NCAA and Energy Information Administration . You used data from 1982 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]]
Softball Scores and Kerosene Consumption: An Amusing Analysis

[[ABSTRACT]]
This peculiar study examined the correlation between the final score difference in NCAA Women's Softball Championship (Div I) games and kerosene consumption in the beautiful island of Barbados. We collected data from the NCAA and the Energy Information Administration to answer this offbeat question. Our findings revealed a surprisingly high correlation coefficient of 0.6454373 and a statistically significant p-value of less than 0.01 for the time period spanning 1982 to 2021. This unexpected connection suggests that there may be more to the game of softball and the use of kerosene in Barbados than meets the eye. The implications of these findings are sure to spark curiosity and perhaps even a few chuckles among researchers and softball enthusiasts alike.

[[INTRODUCTION]]
The connection between seemingly unrelated variables has been a subject of great fascination for researchers across various disciplines. In the world of sports, studies have explored the influence of factors such as weather, crowd size, and team performance on game outcomes. However, the potential link between NCAA Women's Softball Championship (Div I) final score differences and kerosene consumption in Barbados is a peculiar and unexpected subject for investigation.
The notion that the intensity of a softball game could have any bearing on the consumption of kerosene in a distant tropical paradise may strike some as whimsical or even comical. Nonetheless, it is precisely this element of surprise that often leads to the most intriguing and thought-provoking scientific discoveries. As such, this study embarks on a lighthearted yet earnest exploration of the statistical relationship between these two seemingly unrelated phenomena.
While on the surface, the idea of associating the athletic prowess of collegiate softball players with the utilization of kerosene in Barbados may elicit a few chuckles, the statistical analysis to follow presents some compelling findings. The aim of this research is not only to unveil potential correlations but also to generate a sense of wonder about the hidden connections that may lurk beneath the surface of our seemingly disparate world.
Through the use of historical championship game data and kerosene consumption statistics, this study seeks to shed light on a perplexing and amusing correlation that may prompt a playful raising of eyebrows among the scholarly community – and perhaps a few smiles as well. The implications of this unexpected association are bound to spark curiosity and intrigue, providing a welcome departure from the traditional realms of academic inquiry.
Even as we assume a serious and rigorous demeanor in our scholarly pursuits, there is ample room for a touch of whimsy and humor, especially when unearthing unforeseen connections between softball championships and kerosene usage in a distant Caribbean island. With that said, let us delve into the depths of this unconventional investigation and unearth the whimsical yet intriguing insights it has to offer.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

In this study, a multi-faceted approach was employed to investigate the potential correlation between NCAA Women's Softball Championship (Div I) final score differences and kerosene consumption in Barbados. The data collection process commenced with a thorough review of historical championship game records sourced from the official NCAA website and reputable sports data repositories. Match outcomes and final score differentials spanning the years 1982 to 2021 were meticulously collated to ensure comprehensive coverage of the championship's competitive landscape. To maintain data integrity, cross-referencing and validation procedures were implemented to mitigate the risk of erroneous or incomplete information influencing the results.

Simultaneously, kerosene consumption data for Barbados during the same time period was diligently sourced from the Energy Information Administration. Comprehensive figures detailing the quantities of kerosene utilized for various purposes, including domestic, industrial, and commercial applications, were meticulously scrutinized to capture the intricacies of energy usage patterns in the idyllic Caribbean nation. To ensure the credibility of the kerosene consumption data, robust verification protocols were applied, and any anomalies or inconsistencies were subjected to rigorous scrutiny and potential exclusion to safeguard the integrity of the analysis.

Following the meticulous compilation of the requisite datasets, statistical analyses were conducted to ascertain the potential relationship between the variables under investigation. Utilizing sophisticated analytical tools, including regression models and correlation coefficients, the research team meticulously scrutinized the amassed data to discern any meaningful patterns or associations between NCAA Women's Softball Championship final score differences and kerosene consumption in Barbados. The robustness and reliability of the statistical procedures were ensured through extensive testing and validation to fortify the veracity of the findings.

Furthermore, to account for any extraneous variables that may confound the established relationship, comprehensive sensitivity analyses and robustness checks were undertaken to validate the robustness of the observed correlation. Through these meticulous approaches, the research team sought to mitigate the potential influences of confounding factors and bolster the credibility of the documented association between the outcomes of the NCAA Women's Softball Championship games and kerosene usage in Barbados.

Overall, the employed research methods endeavored to uphold the highest standards of rigor and precision to delineate the unexpected yet intriguing connection between the final score differences of collegiate softball games and kerosene consumption in the picturesque island of Barbados. The resultant findings, while unexpected and whimsical, underscore the inextricable linkages that can emerge from the unlikeliest of sources, inviting a lighthearted yet earnest appreciation for the colorful tapestry of interwoven phenomena in our world.

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

Please make up the results section of an academic research paper presenting the findings of the connection between NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up and Kerosene used in Barbados. Make lots of jokes, goofy observations, and puns. 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 NCAA and Energy Information Administration .

For the time period 1982 to 2021, you found a correlation 0.6454373, r-squared of 0.4165893, 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]]
Softball Scores and Kerosene Consumption: An Amusing Analysis

[[ABSTRACT]]
This peculiar study examined the correlation between the final score difference in NCAA Women's Softball Championship (Div I) games and kerosene consumption in the beautiful island of Barbados. We collected data from the NCAA and the Energy Information Administration to answer this offbeat question. Our findings revealed a surprisingly high correlation coefficient of 0.6454373 and a statistically significant p-value of less than 0.01 for the time period spanning 1982 to 2021. This unexpected connection suggests that there may be more to the game of softball and the use of kerosene in Barbados than meets the eye. The implications of these findings are sure to spark curiosity and perhaps even a few chuckles among researchers and softball enthusiasts alike.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The connection between seemingly unrelated variables has been a subject of great fascination for researchers across various disciplines. In the world of sports, studies have explored the influence of factors such as weather, crowd size, and team performance on game outcomes. However, the potential link between NCAA Women's Softball Championship (Div I) final score differences and kerosene consumption in Barbados is a peculiar and unexpected subject for investigation.
The notion that the intensity of a softball game could have any bearing on the consumption of kerosene in a distant tropical paradise may strike some as whimsical or even comical. Nonetheless, it is precisely this element of surprise that often leads to the most intriguing and thought-provoking scientific discoveries. As such, this study embarks on a lighthearted yet earnest exploration of the statistical relationship between these two seemingly unrelated phenomena.
While on the surface, the idea of associating the athletic prowess of collegiate softball players with the utilization of kerosene in Barbados may elicit a few chuckles, the statistical analysis to follow presents some compelling findings. The aim of this research is not only to unveil potential correlations but also to generate a sense of wonder about the hidden connections that may lurk beneath the surface of our seemingly disparate world.
Through the use of historical championship game data and kerosene consumption statistics, this study seeks to shed light on a perplexing and amusing correlation that may prompt a playful raising of eyebrows among the scholarly community – and perhaps a few smiles as well. The implications of this unexpected association are bound to spark curiosity and intrigue, providing a welcome departure from the traditional realms of academic inquiry.
Even as we assume a serious and rigorous demeanor in our scholarly pursuits, there is ample room for a touch of whimsy and humor, especially when unearthing unforeseen connections between softball championships and kerosene usage in a distant Caribbean island. With that said, let us delve into the depths of this unconventional investigation and unearth the whimsical yet intriguing insights it has to offer.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The results of the analysis yielded a correlation coefficient of 0.6454373 between the final score difference in NCAA Women's Softball Championship (Div I) games and kerosene consumption in Barbados. The coefficient of determination (r-squared value) was calculated to be 0.4165893. These values indicate a moderate to strong positive linear relationship between the two variables for the time period spanning 1982 to 2021. Moreover, the p-value of less than 0.01 suggests that this correlation is statistically significant.

The scatterplot (Fig. 1) visually demonstrates the observed association, with a clear clustering of data points indicating a positive trend between the final score difference in softball games and kerosene consumption in Barbados.

The unexpected strength of this correlation raises intriguing questions about the underlying factors at play. While it may seem far-fetched that the outcome of collegiate softball games could influence kerosene consumption in a distant Caribbean island, the empirical evidence suggests otherwise. These findings introduce a touch of whimsy to the realm of statistical analysis, reminding us that correlations, no matter how surprising, warrant serious consideration.

The implications of this peculiar connection extend beyond the realms of sport and energy consumption, potentially inspiring further investigation into the nuanced interplay of seemingly unrelated phenomena. The unexpected nature of this correlation is likely to stimulate curiosity and prompt a few bemused chuckles within academic and athletic communities alike.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up and Kerosene used in Barbados. Make lots of jokes, goofy observations, and puns. 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]]
Softball Scores and Kerosene Consumption: An Amusing Analysis

[[ABSTRACT]]
This peculiar study examined the correlation between the final score difference in NCAA Women's Softball Championship (Div I) games and kerosene consumption in the beautiful island of Barbados. We collected data from the NCAA and the Energy Information Administration to answer this offbeat question. Our findings revealed a surprisingly high correlation coefficient of 0.6454373 and a statistically significant p-value of less than 0.01 for the time period spanning 1982 to 2021. This unexpected connection suggests that there may be more to the game of softball and the use of kerosene in Barbados than meets the eye. The implications of these findings are sure to spark curiosity and perhaps even a few chuckles among researchers and softball enthusiasts alike.

[[LITERATURE REVIEW]]
Previous research on the subject of NCAA Women's Softball Championship (Div I) final score differences and their correlation with kerosene usage in Barbados has been minimal yet surprisingly engaging. Smith et al. (2015) delved into the world of sports and energy consumption, but their focus was primarily on basketball and renewable energy sources. Meanwhile, Doe and Jones (2018) explored the societal impact of collegiate sports on small island economies, yet unfortunately, their work did not extend to the intricate connection between softball games and kerosene consumption.
Turning to the broader literature, "Energy Economics" by Ott and Long (2019) offers a comprehensive analysis of energy consumption patterns across different regions, but regrettably, it overlooks the specific nuances of kerosene usage in Barbados. In a similar vein, "Sports Statistics: A Comprehensive Guide" by Johnson and Smith (2017) provides an extensive overview of statistical methods in sports analysis, but the peculiar interplay between softball championship outcomes and kerosene remains conspicuously absent.
Seeking inspiration from fictional narratives, "The Softball Chronicles" by Miller (2016) and "Kerosene Dreams" by Parker (2018) offered no concrete insights but did provide an enjoyable departure into the world of imaginative storytelling. However, our quest for empirical evidence demanded a more rigorous approach.
In a bold departure from convention, the authors resorted to a rather unorthodox source of information – the mundane yet surprisingly informative world of CVS receipts – to glean insights into consumer behavior and potential connections with sporting events and energy consumption. These whimsical detours, though nontraditional, served to underscore the element of surprise and amusement that often crops up in the pursuit of knowledge.

[[RESULTS]]
The results of the analysis yielded a correlation coefficient of 0.6454373 between the final score difference in NCAA Women's Softball Championship (Div I) games and kerosene consumption in Barbados. The coefficient of determination (r-squared value) was calculated to be 0.4165893. These values indicate a moderate to strong positive linear relationship between the two variables for the time period spanning 1982 to 2021. Moreover, the p-value of less than 0.01 suggests that this correlation is statistically significant.
The scatterplot (Fig. 1) visually demonstrates the observed association, with a clear clustering of data points indicating a positive trend between the final score difference in softball games and kerosene consumption in Barbados.
The unexpected strength of this correlation raises intriguing questions about the underlying factors at play. While it may seem far-fetched that the outcome of collegiate softball games could influence kerosene consumption in a distant Caribbean island, the empirical evidence suggests otherwise. These findings introduce a touch of whimsy to the realm of statistical analysis, reminding us that correlations, no matter how surprising, warrant serious consideration.
The implications of this peculiar connection extend beyond the realms of sport and energy consumption, potentially inspiring further investigation into the nuanced interplay of seemingly unrelated phenomena. The unexpected nature of this correlation is likely to stimulate curiosity and prompt a few bemused chuckles within academic and athletic communities alike.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of our study provide compelling evidence in support of the unexpected correlation between the final score difference in NCAA Women's Softball Championship (Div I) games and kerosene consumption in Barbados. This peculiar connection, while initially met with skepticism, aligns with the broader literature on surprising interrelationships in the sporting and energy consumption domains.

First, our results lend empirical support to the whimsical notion posited by Smith et al. (2015) that sporting events may impact energy consumption in unique ways. While their focus was on basketball and renewable energy sources, our study introduces the novel concept that even softball championship outcomes can influence energy consumption patterns in a distinct geographical region. This unexpected twist undoubtedly adds an element of amusement to the realm of sports economics.

Furthermore, Doe and Jones (2018) delved into the societal impact of collegiate sports on small island economies, providing a poignant glimpse into the interconnectedness of athletic events and local communities. Our findings extend this narrative by revealing an unconventional linkage between softball championship results and kerosene usage in Barbados. The implications of this correlation prompt a reexamination of the intricate influence of sports on seemingly unrelated aspects of society, injecting a touch of lightheartedness into the serious discourse on sports economics.

In a similar vein, our study heeds the call for a nontraditional approach to understanding energy consumption patterns, aligning with the unorthodox spirit showcased in the exploration of consumer behavior through CVS receipts. This departure from conventional sources of information underscores the need to embrace unexpected sources of insight and consider seemingly improbable connections more seriously. The delightfully unexpected nature of our findings serves to remind researchers of the boundless potential for amusement and surprise in the pursuit of knowledge, adding a whimsical flair to the customary solemnity of academic inquiry.

Thus, our analyses validate and expand upon the limited yet engaging literature on the interplay of sports championship outcomes and energy consumption, emphasizing the unexpected and humorous twists that can emerge from serious scholarly endeavors. The statistically significant correlation between softball scores and kerosene usage in Barbados invites further contemplation of the peculiar patterns that unfold within the realms of sports and energy economics, urging researchers to adopt a more light-hearted perspective in their scholarly pursuits.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up and Kerosene used in Barbados. Make lots of jokes, goofy observations, and puns. 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]]
Softball Scores and Kerosene Consumption: An Amusing Analysis

[[ABSTRACT]]
This peculiar study examined the correlation between the final score difference in NCAA Women's Softball Championship (Div I) games and kerosene consumption in the beautiful island of Barbados. We collected data from the NCAA and the Energy Information Administration to answer this offbeat question. Our findings revealed a surprisingly high correlation coefficient of 0.6454373 and a statistically significant p-value of less than 0.01 for the time period spanning 1982 to 2021. This unexpected connection suggests that there may be more to the game of softball and the use of kerosene in Barbados than meets the eye. The implications of these findings are sure to spark curiosity and perhaps even a few chuckles among researchers and softball enthusiasts alike.

[[INTRDUCTION]]
The connection between seemingly unrelated variables has been a subject of great fascination for researchers across various disciplines. In the world of sports, studies have explored the influence of factors such as weather, crowd size, and team performance on game outcomes. However, the potential link between NCAA Women's Softball Championship (Div I) final score differences and kerosene consumption in Barbados is a peculiar and unexpected subject for investigation.
The notion that the intensity of a softball game could have any bearing on the consumption of kerosene in a distant tropical paradise may strike some as whimsical or even comical. Nonetheless, it is precisely this element of surprise that often leads to the most intriguing and thought-provoking scientific discoveries. As such, this study embarks on a lighthearted yet earnest exploration of the statistical relationship between these two seemingly unrelated phenomena.
While on the surface, the idea of associating the athletic prowess of collegiate softball players with the utilization of kerosene in Barbados may elicit a few chuckles, the statistical analysis to follow presents some compelling findings. The aim of this research is not only to unveil potential correlations but also to generate a sense of wonder about the hidden connections that may lurk beneath the surface of our seemingly disparate world.
Through the use of historical championship game data and kerosene consumption statistics, this study seeks to shed light on a perplexing and amusing correlation that may prompt a playful raising of eyebrows among the scholarly community – and perhaps a few smiles as well. The implications of this unexpected association are bound to spark curiosity and intrigue, providing a welcome departure from the traditional realms of academic inquiry.
Even as we assume a serious and rigorous demeanor in our scholarly pursuits, there is ample room for a touch of whimsy and humor, especially when unearthing unforeseen connections between softball championships and kerosene usage in a distant Caribbean island. With that said, let us delve into the depths of this unconventional investigation and unearth the whimsical yet intriguing insights it has to offer.

[[RESULTS]]
The results of the analysis yielded a correlation coefficient of 0.6454373 between the final score difference in NCAA Women's Softball Championship (Div I) games and kerosene consumption in Barbados. The coefficient of determination (r-squared value) was calculated to be 0.4165893. These values indicate a moderate to strong positive linear relationship between the two variables for the time period spanning 1982 to 2021. Moreover, the p-value of less than 0.01 suggests that this correlation is statistically significant.
The scatterplot (Fig. 1) visually demonstrates the observed association, with a clear clustering of data points indicating a positive trend between the final score difference in softball games and kerosene consumption in Barbados.
The unexpected strength of this correlation raises intriguing questions about the underlying factors at play. While it may seem far-fetched that the outcome of collegiate softball games could influence kerosene consumption in a distant Caribbean island, the empirical evidence suggests otherwise. These findings introduce a touch of whimsy to the realm of statistical analysis, reminding us that correlations, no matter how surprising, warrant serious consideration.
The implications of this peculiar connection extend beyond the realms of sport and energy consumption, potentially inspiring further investigation into the nuanced interplay of seemingly unrelated phenomena. The unexpected nature of this correlation is likely to stimulate curiosity and prompt a few bemused chuckles within academic and athletic communities alike.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the findings of this study have left us both astonished and amused by the unexpected relationship discovered between NCAA Women's Softball Championship (Div I) final score differences and kerosene consumption in Barbados. The moderately strong positive linear relationship, indicated by the correlation coefficient of 0.6454373 and the r-squared value of 0.4165893, has certainly thrown a curveball into the world of statistical analysis. It seems that the outcome of softball games may have more weight in the tropical climes of Barbados than initially presumed, quite a grand slam of a discovery!

While the precise mechanisms underlying this correlation remain enigmatic, we are left to marvel at the whimsical nature of statistical association. Our initial presumption of a capricious or even humorous link between these two variables belies the intriguing depth of their interconnectedness, much like finding a diamond in the rough.

The implications of this study extend beyond the confines of softball and kerosene, potentially inspiring further investigation into the uncharted territory of unexpected correlations. As we tread this path of seemingly disparate phenomena converging in unexpected ways, let us remain open to the delightful surprises that may emerge, much like a surprise bunt in the bottom of the ninth inning.

In light of these findings, we assert unequivocally that no further research in this peculiar area is needed. The slim chances of finding a more entertaining association in the world of statistical analysis are about as likely as a snowball's chance in, well, Barbados.

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 Softball Scores and Kerosene Consumption: An Amusing Analysis. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Playful Research

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 Softball Scores and Kerosene Consumption: An Amusing Analysis. Respond only with the name of a fictional organization.

ChatGPT:

The International Institute for Ludicrous 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 Softball Scores and Kerosene Consumption: An Amusing Analysis with an abstract of This peculiar study examined the correlation between the final score difference in NCAA Women's Softball Championship (Div I) games and kerosene consumption in the beautiful island of Barbados. We collected data from the NCAA and the Energy Information Administration to answer this offbeat question. Our findings revealed a surprisingly high correlation coefficient of 0.6454373 and a statistically significant p-value of less than 0.01 for the time period spanning 1982 to 2021. This unexpected connection suggests that there may be more to the game of softball and the use of kerosene in Barbados than meets the eye. The implications of these findings are sure to spark curiosity and perhaps even a few chuckles among researchers and softball enthusiasts alike.

ChatGPT:

NCAA Women's Softball Championship, Div I, score difference, kerosene consumption, Barbados, correlation coefficient, Energy Information Administration, statistical significance, unusual connection, softball game, kerosene use, offbeat question, NCAA data, EIA data, softball research

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

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Data details

NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up
Source: NCAA
See what else correlates with NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up

Kerosene used in Barbados
Detailed data title: Volume of kerosene used consumed in Barbados in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Kerosene used in Barbados

Correlation r = 0.6454373 (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 = 0.4165893 (Coefficient of determination)
This means 41.7% of the change in the one variable (i.e., Kerosene used in Barbados) is predictable based on the change in the other (i.e., NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up) over the 40 years from 1982 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.9E-6.^Show 0.0000068982515347911910000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.65 in 0.00069% of random cases. Said differently, if you correlated 144,964 random variables^Note You don't actually need 144 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 39 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 39 because we have two variables measured over a period of 40 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.

[ 0.42, 0.8 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up (Score)	2	2	1	1	3	3	3	1	2	4	2	1	2	2	2	8	1	1	2	1	6	1	2	3	5	5	11	1	6	5	1	4	3	3	1	1	5	1	0	4
Kerosene used in Barbados (Million Barrels/Day)	0.0845238	0.0892857	0.0857143	0.0952381	0.1	0.0778	0.07709	0.07	0.068	0.08471	0.08448	0.06353	0.08471	0.04931	0.052	0.6	0.04235	0.0423562	0.0422404	0.0423562	0.0635342	0.0554654	0.0568556	0.0592563	0.0603999	0.101231	0.367069	0.0760293	0.236136	0.198862	0.162626	0.19505	0.0114595	0.011459	0.011645	0.192764	0.011677	0.011677	0.00985277	0.0104865

Why this works

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

For the purposes of this project, I counted a point as an outlier if it the residual was two standard deviations from the mean.

(This bullet point only shows up in the details page on charts that do, in fact, have outliers.)
They stand out on the scatterplot above: notice the dots that are far away from any other dots. I intentionally mishandeled outliers, which makes the correlation look extra strong.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([2,2,1,1,3,3,3,1,2,4,2,1,2,2,2,8,1,1,2,1,6,1,2,3,5,5,11,1,6,5,1,4,3,3,1,1,5,1,0,4,])
array_2 = np.array([0.0845238,0.0892857,0.0857143,0.0952381,0.1,0.0778,0.07709,0.07,0.068,0.08471,0.08448,0.06353,0.08471,0.04931,0.052,0.6,0.04235,0.0423562,0.0422404,0.0423562,0.0635342,0.0554654,0.0568556,0.0592563,0.0603999,0.101231,0.367069,0.0760293,0.236136,0.198862,0.162626,0.19505,0.0114595,0.011459,0.011645,0.192764,0.011677,0.011677,0.00985277,0.0104865,])
array_1_name = "NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up"
array_2_name = "Kerosene used in Barbados"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only NCAA Women's Softball Championship (Div I) Final Score Difference Between Winners and Runner-Up
Line chart for only Kerosene used in Barbados
AI-generated correlation image
The spurious research paper: Softball Scores and Kerosene Consumption: An Amusing Analysis

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Correlation ID: 1681 · Black Variable ID: 242 · Red Variable ID: 24183


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