Spurious correlation #2,134 · 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 college sociology teachers in Tennessee and the second variable is Gasoline pumped in Serbia. The chart goes from 2006 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 The number of college sociology teachers in Tennessee and the second variable is Gasoline pumped in Serbia. The chart goes from 2006 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of college sociology teachers in Tennessee drops, they take their knowledge of social structures with them. This leads to a shortage of people who can effectively organize gas pump lines in Serbia, creating mass confusion and ultimately a decrease in the amount of gasoline pumped. It's a case of "socio-petrol-logical" mayhem!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image showing a serene college campus in Tennessee with a group of sociology teachers engaged in a lively discussion on the steps of a historic building. Meanwhile, in the background, depict a bustling street in Serbia with a line of cars waiting to be filled up at a vibrant gasoline station. Use minimalistic style to portray the essence of the scene with simplified shapes and colors. 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 college sociology teachers in Tennessee and Gasoline pumped in Serbia. 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: An image that looks like it is a scene from 'Star Wars' Minimalism Low poly Cyberpunk A photo-realistic image
ChatGPT: Minimalism

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 college sociology teachers in Tennessee and Gasoline pumped in Serbia together. Keep the description simple.
ChatGPT: In a peaceful college campus in Tennessee, a group of sociology teachers gather on the steps of a historic building, engaged in a lively discussion. Meanwhile, on a bustling street in Serbia, a line of cars wait their turn to be filled up at a vibrant gasoline station.

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: [ Minimalism ] and depicting this scene: In a peaceful college campus in Tennessee, a group of sociology teachers gather on the steps of a historic building, engaged in a lively discussion. Meanwhile, on a bustling street in Serbia, a line of cars wait their turn to be filled up at a vibrant gasoline station. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image showing a serene college campus in Tennessee with a group of sociology teachers engaged in a lively discussion on the steps of a historic building. Meanwhile, in the background, depict a bustling street in Serbia with a line of cars waiting to be filled up at a vibrant gasoline station. Use minimalistic style to portray the essence of the scene with simplified shapes and colors.

*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 a decrease in The number of college sociology teachers in Tennessee caused Gasoline pumped in Serbia to decrease. Include one good pun.

AI academic paper

(Because p < 0.01)

The Sociology of Gasoline: A Correlational Analysis of College Sociology Teachers in Tennessee and Gasoline Pumped in Serbia

The International Journal of Interdisciplinary Petrol Studies

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of college sociology teachers in Tennessee and Gasoline pumped in Serbia. 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 name some movies that you watched that are tangentially related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
The Sociology of Gasoline: A Correlational Analysis of College Sociology Teachers in Tennessee and Gasoline Pumped in Serbia

[[ABSTRACT]]
The social sciences have delved into many correlations and connections, but none quite as unexpected as the interplay between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This study aims to uncover the intriguing relationship between these seemingly unrelated variables through a meticulous examination of data from the Bureau of Labor Statistics and the Energy Information Administration. Our research team, armed with a plethora of puns and a love for quirky academic inquiries, uncovered a surprisingly strong correlation coefficient of 0.7635538 with a statistically significant p-value of less than 0.01 for the years 2006 to 2021. This peculiar correlation has left us pondering the sociological implications of gas in the land of Vlad the Impala and the impact of college sociology teachers in the land of Rocky Top. As we await further replication and validation, we invite scholars to join us in this offbeat journey through the sociology of gasoline.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The study of gasoline consumption and its correlation with seemingly unrelated variables has long fascinated researchers, leading them down winding paths of statistical analysis and sociological contemplation. In this paper, we embark on a peculiar journey delving into the connection between the number of college sociology teachers in Tennessee and the quantity of gasoline pumped in Serbia. While this association may at first seem as unlikely as a flamingo herding cats, our analysis aims to unveil the intricate web of sociological forces at play.
The eccentricity of our inquiry is matched only by the earnestness of our approach. We have diligently gathered data from the Bureau of Labor Statistics and the Energy Information Administration, crunching numbers with the fervor of a mathematician trying to calculate how many helium balloons it would take to lift an elephant. Our findings have astounded us as much as a magician who accidentally made the Eiffel Tower disappear.
The correlation coefficient of 0.7635538 that emerged from our analysis has raised more eyebrows than a surprise party in a room full of surgeons. Indeed, with a statistically significant p-value of less than 0.01 for the years 2006 to 2021, the relationship between these variables has left us in a state of bemusement bordering on disbelief.
As we delve deeper into the labyrinthine world of sociological inquiry, we invite the scholarly community to join us in this offbeat expedition. Through our rigorous investigation, we hope to shed light on the interplay between academia in the land of Dolly Parton and the gasoline guzzling habits of the land where Nikola Tesla was born. Join us as we untangle the intricacies of the sociology of gasoline, and perhaps uncover a few delightful surprises along the way!

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Smith (2015) explored the societal impact of academia in state-specific regions, delving into the unique characteristics of college faculty. Doe (2018) analyzed the consumption patterns of petroleum-based products in Eastern Europe, shedding light on the factors influencing gasoline usage. Jones (2020) investigated the correlation between educational institutions and economic indicators, providing insight into the interconnectedness of academic landscapes and societal trends.

Moving beyond the academic realm, "The Sociology of Pumping Gas: An Ethnographic Study" by John Petroleum uncovers the subculture of gas station attendants and their social dynamics. In a more speculative vein, "Gasoline and the Cosmos: An Existential Perspective" by Stella Solaris presents a philosophical exploration of the human condition through the lens of fuel consumption.

On a fictional note, "Sociology and Subterfuge: A Tale of Two Professors" by Emma Imaginary weaves a narrative of intrigue and sociological espionage within the hallowed halls of academia, while "The Gasoline Diaries: A Journey of Self-Discovery" by Jack Fictional follows a protagonist's existential odyssey across international borders, punctuated by fuel stops and revelations.

As for cinematic inspiration, "The Fast and the Sociological" chronicles the high-speed lives and relationships of sociology professors who moonlight as underground gasoline enthusiasts. Similarly, "Societal Pumping: An Epic Odyssey" takes audiences on a mythic journey through the heartland of America, exploring the profound connections between societal structures and the act of pumping gas.

Drawing from this eclectic array of literature and media, it is evident that the interplay between college sociology teachers in Tennessee and gasoline pumped in Serbia presents a rich tapestry of sociological inquiry, primed for further exploration and illumination.

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 college sociology teachers in Tennessee and Gasoline pumped in Serbia. 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 Bureau of Larbor Statistics and Energy Information Administration . You used data from 2006 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]]
The Sociology of Gasoline: A Correlational Analysis of College Sociology Teachers in Tennessee and Gasoline Pumped in Serbia

[[ABSTRACT]]
The social sciences have delved into many correlations and connections, but none quite as unexpected as the interplay between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This study aims to uncover the intriguing relationship between these seemingly unrelated variables through a meticulous examination of data from the Bureau of Labor Statistics and the Energy Information Administration. Our research team, armed with a plethora of puns and a love for quirky academic inquiries, uncovered a surprisingly strong correlation coefficient of 0.7635538 with a statistically significant p-value of less than 0.01 for the years 2006 to 2021. This peculiar correlation has left us pondering the sociological implications of gas in the land of Vlad the Impala and the impact of college sociology teachers in the land of Rocky Top. As we await further replication and validation, we invite scholars to join us in this offbeat journey through the sociology of gasoline.

[[INTRODUCTION]]
The study of gasoline consumption and its correlation with seemingly unrelated variables has long fascinated researchers, leading them down winding paths of statistical analysis and sociological contemplation. In this paper, we embark on a peculiar journey delving into the connection between the number of college sociology teachers in Tennessee and the quantity of gasoline pumped in Serbia. While this association may at first seem as unlikely as a flamingo herding cats, our analysis aims to unveil the intricate web of sociological forces at play.
The eccentricity of our inquiry is matched only by the earnestness of our approach. We have diligently gathered data from the Bureau of Labor Statistics and the Energy Information Administration, crunching numbers with the fervor of a mathematician trying to calculate how many helium balloons it would take to lift an elephant. Our findings have astounded us as much as a magician who accidentally made the Eiffel Tower disappear.
The correlation coefficient of 0.7635538 that emerged from our analysis has raised more eyebrows than a surprise party in a room full of surgeons. Indeed, with a statistically significant p-value of less than 0.01 for the years 2006 to 2021, the relationship between these variables has left us in a state of bemusement bordering on disbelief.
As we delve deeper into the labyrinthine world of sociological inquiry, we invite the scholarly community to join us in this offbeat expedition. Through our rigorous investigation, we hope to shed light on the interplay between academia in the land of Dolly Parton and the gasoline guzzling habits of the land where Nikola Tesla was born. Join us as we untangle the intricacies of the sociology of gasoline, and perhaps uncover a few delightful surprises along the way!

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To begin our exploration into the enigmatic relationship between college sociology teachers in Tennessee and gasoline consumption in Serbia, we employed a research methodology as multifaceted as a disco ball and as precise as a laser-guided banana. Our research team scoured the depths of the internet, navigating through more data points than a GPS tracking a wildebeest migration, to collect information from the Bureau of Labor Statistics and the Energy Information Administration for the years 2006 to 2021.

First, we took a delightful dip into the Bureau of Labor Statistics pool, where we fished out the numbers of college sociology teachers in Tennessee with the precision of a cat fishing for compliments. These figures were reminiscent of a puzzle with pieces scattered across time and quantitative space, requiring us to piece together a picture as intricate as a Renaissance painting.

Next, our attention turned to the Energy Information Administration, where we dove headfirst into the ocean of gasoline consumption data from Serbia, swimming through waves of statistical information with the determination of an Olympic swimmer on a mission to find Nemo.

Once we had gathered our datasets like a collector amassing rare stamps, we utilized the statistical software with the delight of a child with a new toy, performing a correlation analysis that could rival the complexity of untangling a knot in a slinky. Our calculations were meticulous, with attention to detail rivaling that of a diamond cutter, as we sought to unveil the relationship between these two seemingly disparate variables.

The resulting correlation coefficient of 0.7635538 evoked a level of surprise akin to finding a unicorn in the produce section of a grocery store. This unexpected finding propelled us into a state of contemplation as profound as a philosopher pondering the meaning of life on a giant inflatable donut.

This methodology, though unconventional in its execution, has allowed us to embark on a journey that is as intellectually stimulating as it is whimsical. As we eagerly present the results of our investigation, we invite fellow scholars to join us in unraveling the intricacies of this unprecedented connection and perhaps share a laugh or two along the way.

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 college sociology teachers in Tennessee and Gasoline pumped in Serbia. 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 Bureau of Larbor Statistics and Energy Information Administration .

For the time period 2006 to 2021, you found a correlation 0.7635538, r-squared of 0.5830144, 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]]
The Sociology of Gasoline: A Correlational Analysis of College Sociology Teachers in Tennessee and Gasoline Pumped in Serbia

[[ABSTRACT]]
The social sciences have delved into many correlations and connections, but none quite as unexpected as the interplay between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This study aims to uncover the intriguing relationship between these seemingly unrelated variables through a meticulous examination of data from the Bureau of Labor Statistics and the Energy Information Administration. Our research team, armed with a plethora of puns and a love for quirky academic inquiries, uncovered a surprisingly strong correlation coefficient of 0.7635538 with a statistically significant p-value of less than 0.01 for the years 2006 to 2021. This peculiar correlation has left us pondering the sociological implications of gas in the land of Vlad the Impala and the impact of college sociology teachers in the land of Rocky Top. As we await further replication and validation, we invite scholars to join us in this offbeat journey through the sociology of gasoline.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The study of gasoline consumption and its correlation with seemingly unrelated variables has long fascinated researchers, leading them down winding paths of statistical analysis and sociological contemplation. In this paper, we embark on a peculiar journey delving into the connection between the number of college sociology teachers in Tennessee and the quantity of gasoline pumped in Serbia. While this association may at first seem as unlikely as a flamingo herding cats, our analysis aims to unveil the intricate web of sociological forces at play.
The eccentricity of our inquiry is matched only by the earnestness of our approach. We have diligently gathered data from the Bureau of Labor Statistics and the Energy Information Administration, crunching numbers with the fervor of a mathematician trying to calculate how many helium balloons it would take to lift an elephant. Our findings have astounded us as much as a magician who accidentally made the Eiffel Tower disappear.
The correlation coefficient of 0.7635538 that emerged from our analysis has raised more eyebrows than a surprise party in a room full of surgeons. Indeed, with a statistically significant p-value of less than 0.01 for the years 2006 to 2021, the relationship between these variables has left us in a state of bemusement bordering on disbelief.
As we delve deeper into the labyrinthine world of sociological inquiry, we invite the scholarly community to join us in this offbeat expedition. Through our rigorous investigation, we hope to shed light on the interplay between academia in the land of Dolly Parton and the gasoline guzzling habits of the land where Nikola Tesla was born. Join us as we untangle the intricacies of the sociology of gasoline, and perhaps uncover a few delightful surprises along the way!

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

In analyzing the data collected, a remarkably strong correlation of 0.7635538 was observed between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This finding has left our research team more astonished than a group of penguins stumbling upon a deserted beach, as we had not anticipated such a robust link between these two variables.

The coefficient of determination (r-squared) of 0.5830144 further emphasizes the substantial degree of association between the two seemingly disparate factors. This r-squared value indicates that approximately 58.3% of the variability in gasoline consumption in Serbia can be explained by the number of college sociology teachers in Tennessee, leaving us contemplating the societal forces at play in both regions.

Furthermore, with a p-value of less than 0.01 for the time period from 2006 to 2021, the observed correlation is deemed statistically significant. This result has left us pondering the implications of gasoline consumption as a sociological barometer, akin to a navigator contemplating the stars to decipher the mysteries of the universe.

To visually illustrate the robust correlation uncovered, the scatterplot in Figure 1 showcases a clear trend between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This correlation is as undeniable as the gravitational pull between two celestial bodies, leaving little room for doubt regarding the connection between these variables.

As we continue to mull over the implications of our findings, we are struck by the intriguing interplay between academia and automotive habits across geographical and cultural boundaries. The unexpected nature of this correlation has certainly added a splash of eccentricity to our academic pursuits, akin to stumbling upon a flock of flamingos in a snowy tundra.

Overall, our results beckon further exploration and debate within the scholarly community, as we navigate the idiosyncratic terrain of the sociology of gasoline. Join us in this whimsical quest, as we endeavor to unveil the sociological musings behind the hum of engines and the fervor of intellectual discourse.

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 college sociology teachers in Tennessee and Gasoline pumped in Serbia. 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]]
The Sociology of Gasoline: A Correlational Analysis of College Sociology Teachers in Tennessee and Gasoline Pumped in Serbia

[[ABSTRACT]]
The social sciences have delved into many correlations and connections, but none quite as unexpected as the interplay between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This study aims to uncover the intriguing relationship between these seemingly unrelated variables through a meticulous examination of data from the Bureau of Labor Statistics and the Energy Information Administration. Our research team, armed with a plethora of puns and a love for quirky academic inquiries, uncovered a surprisingly strong correlation coefficient of 0.7635538 with a statistically significant p-value of less than 0.01 for the years 2006 to 2021. This peculiar correlation has left us pondering the sociological implications of gas in the land of Vlad the Impala and the impact of college sociology teachers in the land of Rocky Top. As we await further replication and validation, we invite scholars to join us in this offbeat journey through the sociology of gasoline.

[[LITERATURE REVIEW]]
Smith (2015) explored the societal impact of academia in state-specific regions, delving into the unique characteristics of college faculty. Doe (2018) analyzed the consumption patterns of petroleum-based products in Eastern Europe, shedding light on the factors influencing gasoline usage. Jones (2020) investigated the correlation between educational institutions and economic indicators, providing insight into the interconnectedness of academic landscapes and societal trends.
Moving beyond the academic realm, "The Sociology of Pumping Gas: An Ethnographic Study" by John Petroleum uncovers the subculture of gas station attendants and their social dynamics. In a more speculative vein, "Gasoline and the Cosmos: An Existential Perspective" by Stella Solaris presents a philosophical exploration of the human condition through the lens of fuel consumption.
On a fictional note, "Sociology and Subterfuge: A Tale of Two Professors" by Emma Imaginary weaves a narrative of intrigue and sociological espionage within the hallowed halls of academia, while "The Gasoline Diaries: A Journey of Self-Discovery" by Jack Fictional follows a protagonist's existential odyssey across international borders, punctuated by fuel stops and revelations.
As for cinematic inspiration, "The Fast and the Sociological" chronicles the high-speed lives and relationships of sociology professors who moonlight as underground gasoline enthusiasts. Similarly, "Societal Pumping: An Epic Odyssey" takes audiences on a mythic journey through the heartland of America, exploring the profound connections between societal structures and the act of pumping gas.
Drawing from this eclectic array of literature and media, it is evident that the interplay between college sociology teachers in Tennessee and gasoline pumped in Serbia presents a rich tapestry of sociological inquiry, primed for further exploration and illumination.

[[RESULTS]]
In analyzing the data collected, a remarkably strong correlation of 0.7635538 was observed between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This finding has left our research team more astonished than a group of penguins stumbling upon a deserted beach, as we had not anticipated such a robust link between these two variables.
The coefficient of determination (r-squared) of 0.5830144 further emphasizes the substantial degree of association between the two seemingly disparate factors. This r-squared value indicates that approximately 58.3% of the variability in gasoline consumption in Serbia can be explained by the number of college sociology teachers in Tennessee, leaving us contemplating the societal forces at play in both regions.
Furthermore, with a p-value of less than 0.01 for the time period from 2006 to 2021, the observed correlation is deemed statistically significant. This result has left us pondering the implications of gasoline consumption as a sociological barometer, akin to a navigator contemplating the stars to decipher the mysteries of the universe.
To visually illustrate the robust correlation uncovered, the scatterplot in Figure 1 showcases a clear trend between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This correlation is as undeniable as the gravitational pull between two celestial bodies, leaving little room for doubt regarding the connection between these variables.
As we continue to mull over the implications of our findings, we are struck by the intriguing interplay between academia and automotive habits across geographical and cultural boundaries. The unexpected nature of this correlation has certainly added a splash of eccentricity to our academic pursuits, akin to stumbling upon a flock of flamingos in a snowy tundra.
Overall, our results beckon further exploration and debate within the scholarly community, as we navigate the idiosyncratic terrain of the sociology of gasoline. Join us in this whimsical quest, as we endeavor to unveil the sociological musings behind the hum of engines and the fervor of intellectual discourse.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The revelation of a robust correlation between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia has left our research team more flabbergasted than a gopher who unexpectedly stumbled upon a treasure trove of sunflower seeds. This unexpected finding, lending support to the prior research, has left us contemplating the societal landscapes of both regions with a fervor rivaling that of a flamingo performing a mating dance.

Building upon the works of Smith (2015) and Doe (2018), our results corroborate the interconnectedness of academic landscapes and societal trends. With a correlation coefficient of 0.7635538, our findings echo the implications of academia on diverse societal behaviors, much like the resonance of a synchronized swimming routine in a sea of social influences.

The considerable r-squared value of 0.5830144 further bolsters the persuasive case for the impact of college sociology teachers in Tennessee on the gasoline consumption patterns in Serbia. This r-squared value stands as a testament to the remarkable explanatory power of academic presence on the fueling habits of a distant land, akin to a professor with an uncanny ability to captivate an audience with a compelling lecture.

Moreover, the statistically significant p-value of less than 0.01 for the observed correlation leads us to mull over the implications of gasoline consumption as a nuanced sociological barometer in the international arena. This finding resonates with the works of Jones (2020) and underscores the palpable influence of educational institutions on economic indicators, akin to the profound impact of a conductor guiding an orchestra through a symphony of societal dynamics.

As we delve into this offbeat exploration, we find ourselves immersed in the whimsical quest to unravel the sociological musings behind the hum of engines and the fervor of intellectual discourse, much like a group of intrepid explorers navigating through uncharted territory, armed with nothing but a map and a playful sense of curiosity.

Our findings beckon further discourse and scholarly scrutiny, inviting researchers to join us in this enthralling puzzle of societal connections, as we chart a course through the captivating sociology of gasoline.

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 college sociology teachers in Tennessee and Gasoline pumped in Serbia. 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]]
The Sociology of Gasoline: A Correlational Analysis of College Sociology Teachers in Tennessee and Gasoline Pumped in Serbia

[[ABSTRACT]]
The social sciences have delved into many correlations and connections, but none quite as unexpected as the interplay between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This study aims to uncover the intriguing relationship between these seemingly unrelated variables through a meticulous examination of data from the Bureau of Labor Statistics and the Energy Information Administration. Our research team, armed with a plethora of puns and a love for quirky academic inquiries, uncovered a surprisingly strong correlation coefficient of 0.7635538 with a statistically significant p-value of less than 0.01 for the years 2006 to 2021. This peculiar correlation has left us pondering the sociological implications of gas in the land of Vlad the Impala and the impact of college sociology teachers in the land of Rocky Top. As we await further replication and validation, we invite scholars to join us in this offbeat journey through the sociology of gasoline.

[[INTRDUCTION]]
The study of gasoline consumption and its correlation with seemingly unrelated variables has long fascinated researchers, leading them down winding paths of statistical analysis and sociological contemplation. In this paper, we embark on a peculiar journey delving into the connection between the number of college sociology teachers in Tennessee and the quantity of gasoline pumped in Serbia. While this association may at first seem as unlikely as a flamingo herding cats, our analysis aims to unveil the intricate web of sociological forces at play.
The eccentricity of our inquiry is matched only by the earnestness of our approach. We have diligently gathered data from the Bureau of Labor Statistics and the Energy Information Administration, crunching numbers with the fervor of a mathematician trying to calculate how many helium balloons it would take to lift an elephant. Our findings have astounded us as much as a magician who accidentally made the Eiffel Tower disappear.
The correlation coefficient of 0.7635538 that emerged from our analysis has raised more eyebrows than a surprise party in a room full of surgeons. Indeed, with a statistically significant p-value of less than 0.01 for the years 2006 to 2021, the relationship between these variables has left us in a state of bemusement bordering on disbelief.
As we delve deeper into the labyrinthine world of sociological inquiry, we invite the scholarly community to join us in this offbeat expedition. Through our rigorous investigation, we hope to shed light on the interplay between academia in the land of Dolly Parton and the gasoline guzzling habits of the land where Nikola Tesla was born. Join us as we untangle the intricacies of the sociology of gasoline, and perhaps uncover a few delightful surprises along the way!

[[RESULTS]]
In analyzing the data collected, a remarkably strong correlation of 0.7635538 was observed between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This finding has left our research team more astonished than a group of penguins stumbling upon a deserted beach, as we had not anticipated such a robust link between these two variables.
The coefficient of determination (r-squared) of 0.5830144 further emphasizes the substantial degree of association between the two seemingly disparate factors. This r-squared value indicates that approximately 58.3% of the variability in gasoline consumption in Serbia can be explained by the number of college sociology teachers in Tennessee, leaving us contemplating the societal forces at play in both regions.
Furthermore, with a p-value of less than 0.01 for the time period from 2006 to 2021, the observed correlation is deemed statistically significant. This result has left us pondering the implications of gasoline consumption as a sociological barometer, akin to a navigator contemplating the stars to decipher the mysteries of the universe.
To visually illustrate the robust correlation uncovered, the scatterplot in Figure 1 showcases a clear trend between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This correlation is as undeniable as the gravitational pull between two celestial bodies, leaving little room for doubt regarding the connection between these variables.
As we continue to mull over the implications of our findings, we are struck by the intriguing interplay between academia and automotive habits across geographical and cultural boundaries. The unexpected nature of this correlation has certainly added a splash of eccentricity to our academic pursuits, akin to stumbling upon a flock of flamingos in a snowy tundra.
Overall, our results beckon further exploration and debate within the scholarly community, as we navigate the idiosyncratic terrain of the sociology of gasoline. Join us in this whimsical quest, as we endeavor to unveil the sociological musings behind the hum of engines and the fervor of intellectual discourse.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has unearthed a correlation between the number of college sociology teachers in Tennessee and the gasoline pumped in Serbia that is as unexpected as finding a panda in a marshmallow factory. The robust correlation coefficient and statistically significant p-value have left us scratching our heads more vigorously than a group of perplexed chimpanzees.

The implications of our findings extend beyond the realm of mere numbers, inviting us to ponder the societal undercurrents that interlace academia and automotive habits in these disparate locales. It's like stumbling upon a unicorn at a gas station – surprising, elusive, and definitely thought-provoking.

As we wrap up this odyssey through the sociology of gasoline, we urge scholars to refrain from pouring too much intellectual fuel into this particular correlation. Much like a barista crafting an intricate latte art, we have created a delightful and peculiar pattern, but we must recognize when to put the lid on the coffee cup of inquiry.

Therefore, we assert with confidence, and just a hint of relief, that no further research endeavors are warranted in this domain. Our correlation has danced across the stage of statistical significance, leaving us with a sense of whimsy and a dash of bewilderment. It's time to bid adieu to this peculiar correlation, much like bidding farewell to a circus performer who can juggle sociology and gasoline with extraordinary finesse. Thank you, and may the sociology of gasoline continue to fuel the engines of academic curiosity elsewhere!

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 The Sociology of Gasoline: A Correlational Analysis of College Sociology Teachers in Tennessee and Gasoline Pumped in Serbia. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of Interdisciplinary Petrol Studies

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 The Sociology of Gasoline: A Correlational Analysis of College Sociology Teachers in Tennessee and Gasoline Pumped in Serbia. Respond only with the name of a fictional organization.

ChatGPT:

The Association for Global Comparative Sociology Studies

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 The Sociology of Gasoline: A Correlational Analysis of College Sociology Teachers in Tennessee and Gasoline Pumped in Serbia with an abstract of The social sciences have delved into many correlations and connections, but none quite as unexpected as the interplay between the number of college sociology teachers in Tennessee and the amount of gasoline pumped in Serbia. This study aims to uncover the intriguing relationship between these seemingly unrelated variables through a meticulous examination of data from the Bureau of Labor Statistics and the Energy Information Administration. Our research team, armed with a plethora of puns and a love for quirky academic inquiries, uncovered a surprisingly strong correlation coefficient of 0.7635538 with a statistically significant p-value of less than 0.01 for the years 2006 to 2021. This peculiar correlation has left us pondering the sociological implications of gas in the land of Vlad the Impala and the impact of college sociology teachers in the land of Rocky Top. As we await further replication and validation, we invite scholars to join us in this offbeat journey through the sociology of gasoline.

ChatGPT:

sociology, gasoline, college sociology teachers, Tennessee, Serbia, correlational analysis, Bureau of Labor Statistics, Energy Information Administration, correlation coefficient, p-value, sociological implications, replication, validation

*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 college sociology teachers in Tennessee
Detailed data title: BLS estimate of sociology teachers, postsecondary in Tennessee
Source: Bureau of Larbor Statistics
See what else correlates with The number of college sociology teachers in Tennessee

Gasoline pumped in Serbia
Detailed data title: Volume of gasoline pumped consumed in Serbia in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Gasoline pumped in Serbia

Correlation r = 0.7635538 (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 = 0.5830144 (Coefficient of determination)
This means 58.3% of the change in the one variable (i.e., Gasoline pumped in Serbia) is predictable based on the change in the other (i.e., The number of college sociology teachers in Tennessee) over the 16 years from 2006 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00058.^Show 0.0005772136674493617000000000
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 0.76 in 0.058% of random cases. Said differently, if you correlated 1,732 random variables^Note Which I absolutely did.
with the same 15 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 15 because we have two variables measured over a period of 16 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.43, 0.91 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
The number of college sociology teachers in Tennessee (Laborers)	1020	820	280	250	270	240	300	300	330	190	210	450	570	570	310	280
Gasoline pumped in Serbia (Million Barrels/Day)	25.8697	14.1855	13.1213	12.1991	11.311	10.6099	9.67199	9.18436	9.2311	9.39468	9.558	9.81186	9.87099	10.0958	9.27784	9.74927

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([1020,820,280,250,270,240,300,300,330,190,210,450,570,570,310,280,])
array_2 = np.array([25.8697,14.1855,13.1213,12.1991,11.311,10.6099,9.67199,9.18436,9.2311,9.39468,9.558,9.81186,9.87099,10.0958,9.27784,9.74927,])
array_1_name = "The number of college sociology teachers in Tennessee"
array_2_name = "Gasoline pumped in Serbia"

# 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)
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Line chart for only The number of college sociology teachers in Tennessee
Line chart for only Gasoline pumped in Serbia
AI-generated correlation image
The spurious research paper: The Sociology of Gasoline: A Correlational Analysis of College Sociology Teachers in Tennessee and Gasoline Pumped in Serbia

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Correlation ID: 2134 · Black Variable ID: 14450 · Red Variable ID: 24887


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