Spurious correlation #3,185 · 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 microbiologists in North Carolina and the second variable is Gasoline pumped in Togo. The chart goes from 2003 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 microbiologists in North Carolina and the second variable is Gasoline pumped in Togo. The chart goes from 2003 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The increase in microbiologists in North Carolina led to a surplus of expertise in bacterial fermentation, inadvertently boosting the production of biofuels, including gasoline, resulting in more fuel being pumped in Togo. Looks like North Carolina's microbiologists are fueling more than just research!

^{Show image generation prompt} Model: dalle-3
Prompt: [ Photorealism ] Prompt: Generate an image of a bustling laboratory in North Carolina where a group of microbiologists gather around a table, animatedly discussing their latest discoveries. Meanwhile, in Togo, a line of colorful gasoline pumps stands in a sunny courtyard, where locals gather to learn more about the properties of gasoline and its uses. The enthusiasm of the microbiologists seems to have spread all the way to Togo, fueling the curiosity and knowledge of the locals there. The scene captures the contrast between the scientific hub in North Carolina and the vibrant, educational atmosphere in Togo, showcasing the interconnectedness of knowledge and discovery across different locations. 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 microbiologists in North Carolina and Gasoline pumped in Togo. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Parallax art Celtic art Steampunk Photorealism High-tech
ChatGPT: Photorealism

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 microbiologists in North Carolina and Gasoline pumped in Togo, in the following situation: As more microbiologists flocked to North Carolina, their love for "gassing up" conversations sparked a global interest. Their infectious enthusiasm for microbes made its way to Togo, influencing locals to "fuel" their curiosity and pump up their knowledge about gasoline.. Keep the description simple.
ChatGPT: In a bustling laboratory in North Carolina, a group of microbiologists gathers around a table, animatedly discussing their latest discoveries. Meanwhile, in Togo, a line of colorful gasoline pumps stand in a sunny courtyard, where locals gather to learn more about the properties of gasoline and its uses. The enthusiasm of the microbiologists seems to have spread all the way to Togo, fueling the curiosity and knowledge of the locals there.

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: [ Photorealism ] and depicting this scene: In a bustling laboratory in North Carolina, a group of microbiologists gathers around a table, animatedly discussing their latest discoveries. Meanwhile, in Togo, a line of colorful gasoline pumps stand in a sunny courtyard, where locals gather to learn more about the properties of gasoline and its uses. The enthusiasm of the microbiologists seems to have spread all the way to Togo, fueling the curiosity and knowledge of the locals there. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Photorealism ] Prompt: Generate an image of a bustling laboratory in North Carolina where a group of microbiologists gather around a table, animatedly discussing their latest discoveries. Meanwhile, in Togo, a line of colorful gasoline pumps stands in a sunny courtyard, where locals gather to learn more about the properties of gasoline and its uses. The enthusiasm of the microbiologists seems to have spread all the way to Togo, fueling the curiosity and knowledge of the locals there. The scene captures the contrast between the scientific hub in North Carolina and the vibrant, educational atmosphere in Togo, showcasing the interconnectedness of knowledge and discovery across different locations.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in The number of microbiologists in North Carolina caused Gasoline pumped in Togo to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)

Microbiologists in North Carolina and Gasoline in Togo: A Marvelous Mismatch or Mysterious Match?

Journal of Cross-Cultural Microbiology and Environmental Chemistry

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 microbiologists in North Carolina and Gasoline pumped in Togo. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
Microbiologists in North Carolina and Gasoline in Togo: A Marvelous Mismatch or Mysterious Match?

[[ABSTRACT]]
This research paper examines the perplexing relationship between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo. Through the meticulous analysis of data acquired from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, this study unveils a surprising correlation coefficient of 0.8880153 and a statistically significant p-value of less than 0.01.

The implications of these findings are both puzzling and thought-provoking. Could the proliferation of microbiologists in North Carolina have an unforeseen impact on gasoline consumption in faraway Togo? Or perhaps this correlation is merely a fluke, a random alignment of disparate data points that fools the eyes and the mind. The idiosyncrasies of human behavior and the whims of statistical anomalies may very well be at play here, but further research is needed to untangle this enigma.

As we delve into the complexities of this peculiar correlation, we invite the scientific community to ponder the question: is there a deeper connection between the microscopic world of microbiology and the macroscopic realm of gasoline consumption, or are we simply witnessing the capricious dance of unrelated statistical variables?

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intricate web of causation and correlation in the realms of science and economics often presents us with enigmatic puzzles that defy easy explanation. In the vast tapestry of statistical data, peculiar connections can emerge, confounding our expectations and challenging our understanding of the world. One such curious relationship that has piqued the interest of researchers is the seemingly unlikely association between the number of microbiologists in North Carolina and the volume of gasoline pumped in Togo. At first glance, these two variables appear to inhabit vastly different spheres of human endeavor, yet the statistical evidence suggests otherwise.
This research seeks to unravel the enigma of this unexpected correlation, employing rigorous analysis and scholarly inquiry to shed light on what may initially appear as a bizarre mismatch. The confluence of microbiologists in the southeastern United States and gasoline consumption in the West African nation of Togo presents a conundrum that demands our attention. As we embark on this intellectual odyssey, we must be mindful of the possibility that the observed correlation may be a mere statistical quirk, a whimsical dance of numbers that tickles the fancy of probability but holds no substantive meaning. Nonetheless, we approach this investigation with scholarly rigor, ever mindful of the importance of disentangling causation from correlation, lest we fall victim to the siren song of spurious relationships.
The present study is predicated on the analysis of meticulously gathered data spanning nearly two decades, drawing from reputable sources such as the Bureau of Labor Statistics and the Energy Information Administration. Our analysis reveals a surprising correlation coefficient of 0.8880153, coupled with a statistically significant p-value of less than 0.01. These findings, while astonishing, compel us to delve deeper into the underlying mechanisms that may underpin this seeming incongruity. It is within this analytical framework that we endeavor to unravel the mysteries that lurk within the landscape of data, seeking to discern whether the observed relationship between microbiologists and gasoline consumption is a marvelous mismatch or a mysterious match.
In the pages that follow, we invite the reader to embark on this scholarly journey with us, as we navigate the labyrinthine pathways of statistical analysis and hypothesis testing. The implications of our findings, while as yet uncertain, serve as a clarion call to the scientific community to contemplate the possibility of unforeseen connections lurking beneath the surface of empirical data. With cautious skepticism and an unwavering commitment to empirical inquiry, we set forth on this intellectual adventure, poised to unravel the perplexing tapestry of microbiologists in North Carolina and gasoline in Togo.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The curious relationship between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo has elicited a spectrum of responses from the scholarly community, ranging from incredulity to unbridled fascination. In their seminal work, Smith et al. (2015) provided an initial exploration of this connection, positing that the growth of microbiology as a discipline in North Carolina could potentially exert an unforeseen influence on the demand for gasoline in Togo. The authors conducted a comprehensive survey of microbiologist demographics in the southeastern United States and juxtaposed this with per capita gasoline consumption trends in Togo, thereby laying the foundation for further inquiry into this curious confluence.

Subsequent investigations by Doe and Jones (2018) delved into the complexities of microbial ecosystems and their potential impact on transcontinental energy dynamics, offering a theoretical framework that sought to elucidate the enigmatic relationship under scrutiny. Drawing from ecological principles and cross-disciplinary insights, their work elegantly wove a narrative of microbial influence traversing geographical bounds, prompting the reader to contemplate the far-reaching tendrils of microbiological phenomena.

In a departure from the traditional literature, "The Invisible Influence: Microbes and Petroleum Products" by Sapienza (2016) provided a thought-provoking allegorical exploration of the parallel evolution of microbiologists in North Carolina and gasoline consumption in Togo. Through a series of metaphorical vignettes and lyrical musings, Sapienza skillfully interwove the intricate tapestry of human endeavor and microbial proliferation, urging the reader to consider the invisible hand of microbiological forces at play in the realm of energy consumption.

Turning to fiction for a moment, the classic novel "Microbes in Motion" by Austen (1813) introduced readers to the clandestine world of microscopic organisms and their hypothetical influence on global energy flows. While the novel's primary focus lies in romantic entanglements, the underlying theme of microbiological intrigue serves as a captivating backdrop, hinting at the enduring fascination with the unseen forces that may shape our world.

In a contemporary context, the popular internet meme "Gasoline Gobbling Germs" humorously addresses the intersection of microbiology and gasoline consumption, albeit in a lighthearted and irreverent manner. This meme, characterized by anthropomorphized microbes gleefully chugging gasoline, embodies the collective imagination's whimsical foray into the realm of improbable connections and incongruous relationships.

As we navigate the landscape of scholarly inquiry and imaginative speculation, it becomes evident that the intersection of microbiologists in North Carolina and gasoline in Togo occupies a realm of enigmatic curiosity that beckons to be explored further. The following sections of this paper endeavor to unravel the mysteries that envelop this captivating linkage, employing a judicious blend of empirical analysis and speculative contemplation to discern the essence of this marvelous mismatch or mysterious match.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 microbiologists in North Carolina and Gasoline pumped in Togo. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 2003 to 2021

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Microbiologists in North Carolina and Gasoline in Togo: A Marvelous Mismatch or Mysterious Match?

[[ABSTRACT]]
This research paper examines the perplexing relationship between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo. Through the meticulous analysis of data acquired from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, this study unveils a surprising correlation coefficient of 0.8880153 and a statistically significant p-value of less than 0.01.

The implications of these findings are both puzzling and thought-provoking. Could the proliferation of microbiologists in North Carolina have an unforeseen impact on gasoline consumption in faraway Togo? Or perhaps this correlation is merely a fluke, a random alignment of disparate data points that fools the eyes and the mind. The idiosyncrasies of human behavior and the whims of statistical anomalies may very well be at play here, but further research is needed to untangle this enigma.

As we delve into the complexities of this peculiar correlation, we invite the scientific community to ponder the question: is there a deeper connection between the microscopic world of microbiology and the macroscopic realm of gasoline consumption, or are we simply witnessing the capricious dance of unrelated statistical variables?

[[INTRODUCTION]]
The intricate web of causation and correlation in the realms of science and economics often presents us with enigmatic puzzles that defy easy explanation. In the vast tapestry of statistical data, peculiar connections can emerge, confounding our expectations and challenging our understanding of the world. One such curious relationship that has piqued the interest of researchers is the seemingly unlikely association between the number of microbiologists in North Carolina and the volume of gasoline pumped in Togo. At first glance, these two variables appear to inhabit vastly different spheres of human endeavor, yet the statistical evidence suggests otherwise.
This research seeks to unravel the enigma of this unexpected correlation, employing rigorous analysis and scholarly inquiry to shed light on what may initially appear as a bizarre mismatch. The confluence of microbiologists in the southeastern United States and gasoline consumption in the West African nation of Togo presents a conundrum that demands our attention. As we embark on this intellectual odyssey, we must be mindful of the possibility that the observed correlation may be a mere statistical quirk, a whimsical dance of numbers that tickles the fancy of probability but holds no substantive meaning. Nonetheless, we approach this investigation with scholarly rigor, ever mindful of the importance of disentangling causation from correlation, lest we fall victim to the siren song of spurious relationships.
The present study is predicated on the analysis of meticulously gathered data spanning nearly two decades, drawing from reputable sources such as the Bureau of Labor Statistics and the Energy Information Administration. Our analysis reveals a surprising correlation coefficient of 0.8880153, coupled with a statistically significant p-value of less than 0.01. These findings, while astonishing, compel us to delve deeper into the underlying mechanisms that may underpin this seeming incongruity. It is within this analytical framework that we endeavor to unravel the mysteries that lurk within the landscape of data, seeking to discern whether the observed relationship between microbiologists and gasoline consumption is a marvelous mismatch or a mysterious match.
In the pages that follow, we invite the reader to embark on this scholarly journey with us, as we navigate the labyrinthine pathways of statistical analysis and hypothesis testing. The implications of our findings, while as yet uncertain, serve as a clarion call to the scientific community to contemplate the possibility of unforeseen connections lurking beneath the surface of empirical data. With cautious skepticism and an unwavering commitment to empirical inquiry, we set forth on this intellectual adventure, poised to unravel the perplexing tapestry of microbiologists in North Carolina and gasoline in Togo.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To commence our investigation into the peculiar correlation between the number of microbiologists in North Carolina and gasoline consumption in Togo, we employed a multifaceted approach that blended quantitative analysis with a touch of whimsy and a sprinkle of statistical wizardry. The data for this study were predominantly sourced from the Bureau of Labor Statistics and the Energy Information Administration, with a smidgeon of anecdotal evidence from the local coffee shops of North Carolina and the bustling gasoline stations of Togo.

The first step in our methodological escapade was to gather comprehensive data on the number of microbiologists gainfully employed in North Carolina. This involved combing through labor statistics, job postings, and the occasional chance encounter with a microbiologist at a barbecue joint. Concurrently, we tapped into the vast reservoir of information on gasoline consumption in Togo, leveraging the towering wealth of data graciously provided by the Energy Information Administration alongside our keen observations of moped riders and street vendors in the bustling thoroughfares of Togo.

Having amassed an impressive trove of data, we undertook the Herculean task of transforming raw numbers into nuggets of statistical enlightenment. This involved performing a series of intricate calculations invoking the mythical powers of correlation coefficients, standard deviations, and the occasional incantation of p-values to summon statistical significance from the depths of empirical uncertainty.

To scrutinize the potential connection between microbiologists and gasoline consumption, we unfurled the grand tapestry of time, stretching from the bygone days of 2003 to the frontier of 2021. Our aim was to capture the ebb and flow of both microbiologists and gasoline in their temporal dance, hoping to elucidate the hidden choreography of their statistical interplay.

With bated breath and furrowed brows, we subjected our amassed data to the rigors of statistical analysis, employing regression models and time series analyses to sift through the labyrinth of numbers and discern meaningful patterns. Our quest for empirical truth led us to uncover a surprising correlation coefficient of 0.8880153, a revelation that set our hearts aflutter and our minds ablaze with curiosity.

The statistical insights gleaned from our analytical odyssey spurred an ardent desire to probe the depths of causation and correlation, igniting a fervent endeavor to untangle the web of relationships between the microbial denizens of North Carolina and the effervescent fuel economy of Togo.

In conclusion, our methodology, while steeped in the earnest tradition of empirical inquiry, bore the hallmark of a zesty adventure through the realms of statistics and scientific exploration. Armed with data, curiosity, and a generous dollop of statistical prowess, we ventured forth into the ineffable domain of microbiologists in North Carolina and gasoline in Togo, beckoned by the siren song of statistical mystery and the tantalizing promise of scholarly revelation.

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 microbiologists in North Carolina and Gasoline pumped in Togo. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 2003 to 2021, you found a correlation 0.8880153, r-squared of 0.7885711, 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]]
Microbiologists in North Carolina and Gasoline in Togo: A Marvelous Mismatch or Mysterious Match?

[[ABSTRACT]]
This research paper examines the perplexing relationship between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo. Through the meticulous analysis of data acquired from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, this study unveils a surprising correlation coefficient of 0.8880153 and a statistically significant p-value of less than 0.01.

The implications of these findings are both puzzling and thought-provoking. Could the proliferation of microbiologists in North Carolina have an unforeseen impact on gasoline consumption in faraway Togo? Or perhaps this correlation is merely a fluke, a random alignment of disparate data points that fools the eyes and the mind. The idiosyncrasies of human behavior and the whims of statistical anomalies may very well be at play here, but further research is needed to untangle this enigma.

As we delve into the complexities of this peculiar correlation, we invite the scientific community to ponder the question: is there a deeper connection between the microscopic world of microbiology and the macroscopic realm of gasoline consumption, or are we simply witnessing the capricious dance of unrelated statistical variables?

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intricate web of causation and correlation in the realms of science and economics often presents us with enigmatic puzzles that defy easy explanation. In the vast tapestry of statistical data, peculiar connections can emerge, confounding our expectations and challenging our understanding of the world. One such curious relationship that has piqued the interest of researchers is the seemingly unlikely association between the number of microbiologists in North Carolina and the volume of gasoline pumped in Togo. At first glance, these two variables appear to inhabit vastly different spheres of human endeavor, yet the statistical evidence suggests otherwise.
This research seeks to unravel the enigma of this unexpected correlation, employing rigorous analysis and scholarly inquiry to shed light on what may initially appear as a bizarre mismatch. The confluence of microbiologists in the southeastern United States and gasoline consumption in the West African nation of Togo presents a conundrum that demands our attention. As we embark on this intellectual odyssey, we must be mindful of the possibility that the observed correlation may be a mere statistical quirk, a whimsical dance of numbers that tickles the fancy of probability but holds no substantive meaning. Nonetheless, we approach this investigation with scholarly rigor, ever mindful of the importance of disentangling causation from correlation, lest we fall victim to the siren song of spurious relationships.
The present study is predicated on the analysis of meticulously gathered data spanning nearly two decades, drawing from reputable sources such as the Bureau of Labor Statistics and the Energy Information Administration. Our analysis reveals a surprising correlation coefficient of 0.8880153, coupled with a statistically significant p-value of less than 0.01. These findings, while astonishing, compel us to delve deeper into the underlying mechanisms that may underpin this seeming incongruity. It is within this analytical framework that we endeavor to unravel the mysteries that lurk within the landscape of data, seeking to discern whether the observed relationship between microbiologists and gasoline consumption is a marvelous mismatch or a mysterious match.
In the pages that follow, we invite the reader to embark on this scholarly journey with us, as we navigate the labyrinthine pathways of statistical analysis and hypothesis testing. The implications of our findings, while as yet uncertain, serve as a clarion call to the scientific community to contemplate the possibility of unforeseen connections lurking beneath the surface of empirical data. With cautious skepticism and an unwavering commitment to empirical inquiry, we set forth on this intellectual adventure, poised to unravel the perplexing tapestry of microbiologists in North Carolina and gasoline in Togo.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis of the relationship between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo yielded intriguing results. The correlation coefficient of 0.8880153 indicates a strong positive linear relationship between these seemingly disparate variables. This coefficient suggests that as the number of microbiologists in North Carolina increases, there is a concurrent increase in the volume of gasoline pumped in Togo. Now, I'm not saying that microbiologists are secretly hoarding gasoline or conducting fuel-related experiments, but the data certainly raises some eyebrows.

The coefficient of determination, often denoted as r-squared, is a substantial 0.7885711. This indicates that approximately 79% of the variability in gasoline consumption in Togo can be explained by the number of microbiologists in North Carolina. To put it simply, there's a lot of overlap between these two variables, like an accidental matching pair of socks hidden in the depths of a sock drawer.

Perhaps the most striking finding is the p-value of less than 0.01, signifying that the observed correlation is statistically significant. This implies that the likelihood of obtaining such a strong correlation by chance alone is less than 1%, which is akin to finding a needle in a statistically significant haystack.

Now, to visually represent this revelatory connection, we present Figure 1, a scatterplot showcasing the conspicuous correlation between the number of microbiologists in North Carolina and the gasoline pumped in Togo. As you can see, the data points align themselves in a manner that would make even the most dedicated conspiracy theorist raise an eyebrow. However, we urge caution in leaping to extravagant conclusions, as correlation does not imply causation, and the universe of statistical anomalies is ever prepared to confound our expectations.

In conclusion, the results of this investigation provide compelling evidence of a perplexing correlation between microbiologists in North Carolina and gasoline in Togo. While the implications of this peculiar association remain shrouded in mystery, the findings beckon further inquiry and contemplation. The scientific community is invited to engage in spirited discussion and empirical scrutiny, as we grapple with the riddle of this curious connection.

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 microbiologists in North Carolina and Gasoline pumped in Togo. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
Microbiologists in North Carolina and Gasoline in Togo: A Marvelous Mismatch or Mysterious Match?

[[ABSTRACT]]
This research paper examines the perplexing relationship between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo. Through the meticulous analysis of data acquired from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, this study unveils a surprising correlation coefficient of 0.8880153 and a statistically significant p-value of less than 0.01.

The implications of these findings are both puzzling and thought-provoking. Could the proliferation of microbiologists in North Carolina have an unforeseen impact on gasoline consumption in faraway Togo? Or perhaps this correlation is merely a fluke, a random alignment of disparate data points that fools the eyes and the mind. The idiosyncrasies of human behavior and the whims of statistical anomalies may very well be at play here, but further research is needed to untangle this enigma.

As we delve into the complexities of this peculiar correlation, we invite the scientific community to ponder the question: is there a deeper connection between the microscopic world of microbiology and the macroscopic realm of gasoline consumption, or are we simply witnessing the capricious dance of unrelated statistical variables?

[[LITERATURE REVIEW]]
The curious relationship between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo has elicited a spectrum of responses from the scholarly community, ranging from incredulity to unbridled fascination. In their seminal work, Smith et al. (2015) provided an initial exploration of this connection, positing that the growth of microbiology as a discipline in North Carolina could potentially exert an unforeseen influence on the demand for gasoline in Togo. The authors conducted a comprehensive survey of microbiologist demographics in the southeastern United States and juxtaposed this with per capita gasoline consumption trends in Togo, thereby laying the foundation for further inquiry into this curious confluence.
Subsequent investigations by Doe and Jones (2018) delved into the complexities of microbial ecosystems and their potential impact on transcontinental energy dynamics, offering a theoretical framework that sought to elucidate the enigmatic relationship under scrutiny. Drawing from ecological principles and cross-disciplinary insights, their work elegantly wove a narrative of microbial influence traversing geographical bounds, prompting the reader to contemplate the far-reaching tendrils of microbiological phenomena.
In a departure from the traditional literature, "The Invisible Influence: Microbes and Petroleum Products" by Sapienza (2016) provided a thought-provoking allegorical exploration of the parallel evolution of microbiologists in North Carolina and gasoline consumption in Togo. Through a series of metaphorical vignettes and lyrical musings, Sapienza skillfully interwove the intricate tapestry of human endeavor and microbial proliferation, urging the reader to consider the invisible hand of microbiological forces at play in the realm of energy consumption.
Turning to fiction for a moment, the classic novel "Microbes in Motion" by Austen (1813) introduced readers to the clandestine world of microscopic organisms and their hypothetical influence on global energy flows. While the novel's primary focus lies in romantic entanglements, the underlying theme of microbiological intrigue serves as a captivating backdrop, hinting at the enduring fascination with the unseen forces that may shape our world.
In a contemporary context, the popular internet meme "Gasoline Gobbling Germs" humorously addresses the intersection of microbiology and gasoline consumption, albeit in a lighthearted and irreverent manner. This meme, characterized by anthropomorphized microbes gleefully chugging gasoline, embodies the collective imagination's whimsical foray into the realm of improbable connections and incongruous relationships.
As we navigate the landscape of scholarly inquiry and imaginative speculation, it becomes evident that the intersection of microbiologists in North Carolina and gasoline in Togo occupies a realm of enigmatic curiosity that beckons to be explored further. The following sections of this paper endeavor to unravel the mysteries that envelop this captivating linkage, employing a judicious blend of empirical analysis and speculative contemplation to discern the essence of this marvelous mismatch or mysterious match.

[[RESULTS]]
The statistical analysis of the relationship between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo yielded intriguing results. The correlation coefficient of 0.8880153 indicates a strong positive linear relationship between these seemingly disparate variables. This coefficient suggests that as the number of microbiologists in North Carolina increases, there is a concurrent increase in the volume of gasoline pumped in Togo. Now, I'm not saying that microbiologists are secretly hoarding gasoline or conducting fuel-related experiments, but the data certainly raises some eyebrows.
The coefficient of determination, often denoted as r-squared, is a substantial 0.7885711. This indicates that approximately 79% of the variability in gasoline consumption in Togo can be explained by the number of microbiologists in North Carolina. To put it simply, there's a lot of overlap between these two variables, like an accidental matching pair of socks hidden in the depths of a sock drawer.
Perhaps the most striking finding is the p-value of less than 0.01, signifying that the observed correlation is statistically significant. This implies that the likelihood of obtaining such a strong correlation by chance alone is less than 1%, which is akin to finding a needle in a statistically significant haystack.
Now, to visually represent this revelatory connection, we present Figure 1, a scatterplot showcasing the conspicuous correlation between the number of microbiologists in North Carolina and the gasoline pumped in Togo. As you can see, the data points align themselves in a manner that would make even the most dedicated conspiracy theorist raise an eyebrow. However, we urge caution in leaping to extravagant conclusions, as correlation does not imply causation, and the universe of statistical anomalies is ever prepared to confound our expectations.
In conclusion, the results of this investigation provide compelling evidence of a perplexing correlation between microbiologists in North Carolina and gasoline in Togo. While the implications of this peculiar association remain shrouded in mystery, the findings beckon further inquiry and contemplation. The scientific community is invited to engage in spirited discussion and empirical scrutiny, as we grapple with the riddle of this curious connection.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The revelation of a robust positive correlation between the number of microbiologists in North Carolina and the quantity of gasoline dispensed in Togo serves as a conundrum that demands meticulous scrutiny. Such unexpected findings not only pique scientific curiosity but also invite a moment of whimsy, akin to stumbling upon a clown at a funeral. The empirical evidence presented here substantiates the earlier literature that hinted at the unseen influence of microbial dynamics on transcontinental energy phenomena. The work of Smith et al. (2015) and Doe and Jones (2018) laid the groundwork for this investigation, and their measured assessments now find resonance in the statistical substantiation of this curious correlation. Even the lighthearted commentary of the "Gasoline Gobbling Germs" meme, although facetious in nature, unwittingly underscored the tantalizing enigma that is now brought to light.

The correlation coefficient of 0.8880153, akin to discovering a surprisingly harmonious duet between an accordion and a kazoo, underscores the striking alignment between the proliferation of microbiologists in one corner of the globe and the fuel consumption patterns in a distant land. Furthermore, the substantial coefficient of determination reinforces the notion that a substantial proportion of the variance in gasoline consumption in Togo can be ascribed to the waxing and waning populace of microbiologists in North Carolina, not unlike the intricate dance of the moon's gravitational pull on the Earth's tides. These statistical metrics not only fortify the notion of a genuine relationship but also advocate for a comprehensive examination of the dynamics that underpin this perplexing connection.

With the p-value less than 0.01, reminiscent of uncovering a clover with four leaves and a leprechaun to boot, we are compelled to acknowledge the presence of a statistically significant association. This serendipitous alignment of seemingly incongruent variables cannot be dismissed as a mere fluke, relegating it to the ranks of extraordinary observations that beckon for astute comprehension. The scatterplot depicted in Figure 1 encapsulates this striking concordance, with data points mirroring each other like a pair of identical snowflakes, both beautiful and bewildering.

However, it is imperative to exercise caution in attributing causality to this correlation, as correlation does not imply causation, much as a barking dog is not necessarily the architect of its owner's folly. Instead, this revelation should ignite a spark of inquisitiveness and prompt further scholarly inquiry. The multidimensional implications of this connection, like a Rubik's Cube of academic intrigue, beckon the scientific community to delve into uncharted territories and unravel the intricate threads of this astonishing tapestry.

In summation, this study presents a provoking exploration of an unforeseen correlation and calls for a continuation of this scholarly odyssey. The interplay between the microscopic world of microbiologists and the macroscopic realm of gasoline consumption offers a riveting tableau for academic pursuit, challenging the boundaries of our conventional understanding and inciting a passionate quest for elucidation.

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 microbiologists in North Carolina and Gasoline pumped in Togo. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
Microbiologists in North Carolina and Gasoline in Togo: A Marvelous Mismatch or Mysterious Match?

[[ABSTRACT]]
This research paper examines the perplexing relationship between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo. Through the meticulous analysis of data acquired from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, this study unveils a surprising correlation coefficient of 0.8880153 and a statistically significant p-value of less than 0.01.

The implications of these findings are both puzzling and thought-provoking. Could the proliferation of microbiologists in North Carolina have an unforeseen impact on gasoline consumption in faraway Togo? Or perhaps this correlation is merely a fluke, a random alignment of disparate data points that fools the eyes and the mind. The idiosyncrasies of human behavior and the whims of statistical anomalies may very well be at play here, but further research is needed to untangle this enigma.

As we delve into the complexities of this peculiar correlation, we invite the scientific community to ponder the question: is there a deeper connection between the microscopic world of microbiology and the macroscopic realm of gasoline consumption, or are we simply witnessing the capricious dance of unrelated statistical variables?

[[INTRDUCTION]]
The intricate web of causation and correlation in the realms of science and economics often presents us with enigmatic puzzles that defy easy explanation. In the vast tapestry of statistical data, peculiar connections can emerge, confounding our expectations and challenging our understanding of the world. One such curious relationship that has piqued the interest of researchers is the seemingly unlikely association between the number of microbiologists in North Carolina and the volume of gasoline pumped in Togo. At first glance, these two variables appear to inhabit vastly different spheres of human endeavor, yet the statistical evidence suggests otherwise.
This research seeks to unravel the enigma of this unexpected correlation, employing rigorous analysis and scholarly inquiry to shed light on what may initially appear as a bizarre mismatch. The confluence of microbiologists in the southeastern United States and gasoline consumption in the West African nation of Togo presents a conundrum that demands our attention. As we embark on this intellectual odyssey, we must be mindful of the possibility that the observed correlation may be a mere statistical quirk, a whimsical dance of numbers that tickles the fancy of probability but holds no substantive meaning. Nonetheless, we approach this investigation with scholarly rigor, ever mindful of the importance of disentangling causation from correlation, lest we fall victim to the siren song of spurious relationships.
The present study is predicated on the analysis of meticulously gathered data spanning nearly two decades, drawing from reputable sources such as the Bureau of Labor Statistics and the Energy Information Administration. Our analysis reveals a surprising correlation coefficient of 0.8880153, coupled with a statistically significant p-value of less than 0.01. These findings, while astonishing, compel us to delve deeper into the underlying mechanisms that may underpin this seeming incongruity. It is within this analytical framework that we endeavor to unravel the mysteries that lurk within the landscape of data, seeking to discern whether the observed relationship between microbiologists and gasoline consumption is a marvelous mismatch or a mysterious match.
In the pages that follow, we invite the reader to embark on this scholarly journey with us, as we navigate the labyrinthine pathways of statistical analysis and hypothesis testing. The implications of our findings, while as yet uncertain, serve as a clarion call to the scientific community to contemplate the possibility of unforeseen connections lurking beneath the surface of empirical data. With cautious skepticism and an unwavering commitment to empirical inquiry, we set forth on this intellectual adventure, poised to unravel the perplexing tapestry of microbiologists in North Carolina and gasoline in Togo.

[[RESULTS]]
The statistical analysis of the relationship between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo yielded intriguing results. The correlation coefficient of 0.8880153 indicates a strong positive linear relationship between these seemingly disparate variables. This coefficient suggests that as the number of microbiologists in North Carolina increases, there is a concurrent increase in the volume of gasoline pumped in Togo. Now, I'm not saying that microbiologists are secretly hoarding gasoline or conducting fuel-related experiments, but the data certainly raises some eyebrows.
The coefficient of determination, often denoted as r-squared, is a substantial 0.7885711. This indicates that approximately 79% of the variability in gasoline consumption in Togo can be explained by the number of microbiologists in North Carolina. To put it simply, there's a lot of overlap between these two variables, like an accidental matching pair of socks hidden in the depths of a sock drawer.
Perhaps the most striking finding is the p-value of less than 0.01, signifying that the observed correlation is statistically significant. This implies that the likelihood of obtaining such a strong correlation by chance alone is less than 1%, which is akin to finding a needle in a statistically significant haystack.
Now, to visually represent this revelatory connection, we present Figure 1, a scatterplot showcasing the conspicuous correlation between the number of microbiologists in North Carolina and the gasoline pumped in Togo. As you can see, the data points align themselves in a manner that would make even the most dedicated conspiracy theorist raise an eyebrow. However, we urge caution in leaping to extravagant conclusions, as correlation does not imply causation, and the universe of statistical anomalies is ever prepared to confound our expectations.
In conclusion, the results of this investigation provide compelling evidence of a perplexing correlation between microbiologists in North Carolina and gasoline in Togo. While the implications of this peculiar association remain shrouded in mystery, the findings beckon further inquiry and contemplation. The scientific community is invited to engage in spirited discussion and empirical scrutiny, as we grapple with the riddle of this curious connection.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has unveiled a baffling correlation between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo. The statistical evidence showcases a strong positive linear relationship, which may seem as unlikely as finding a polar bear in the Sahara. The coefficient of determination emphasizes the substantial overlap between these variables, akin to stumbling upon a surprise in a cereal box. The p-value, at less than 0.01, accentuates the unlikelihood of this correlation occurring by chance, almost like finding a diamond in the rough. Our findings tantalizingly hint at a mysterious connection that beckons further scrutiny, akin to a Sherlock Holmes mystery begging to be solved.

As we wrap up our investigation, we are left not with answers, but with more questions. Could the enigmatic world of microbiology hold the key to understanding gasoline consumption in Togo? Or are we merely witnessing a statistical quirk playing an elaborate prank on our expectations? The complexities of the human experience and the realm of statistics continue to baffle and surprise us, much like an unexpected plot twist in a thriller novel.

In light of our findings, we assert that no further research is needed in this area. Instead, we encourage future inquiries into similarly whimsical correlations, confident that the world of statistical analysis has many more surprises in store for us. After all, who knows what other improbable relationships are waiting to be uncovered, like hidden treasures in the attic of data?

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 Microbiologists in North Carolina and Gasoline in Togo: A Marvelous Mismatch or Mysterious Match?. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Cross-Cultural Microbiology and Environmental Chemistry

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 Microbiologists in North Carolina and Gasoline in Togo: A Marvelous Mismatch or Mysterious Match?. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Cross-Cultural Microbiological 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 Microbiologists in North Carolina and Gasoline in Togo: A Marvelous Mismatch or Mysterious Match? with an abstract of This research paper examines the perplexing relationship between the number of microbiologists in North Carolina and the amount of gasoline pumped in Togo. Through the meticulous analysis of data acquired from the Bureau of Labor Statistics and the Energy Information Administration spanning the years 2003 to 2021, this study unveils a surprising correlation coefficient of 0.8880153 and a statistically significant p-value of less than 0.01.
The implications of these findings are both puzzling and thought-provoking. Could the proliferation of microbiologists in North Carolina have an unforeseen impact on gasoline consumption in faraway Togo? Or perhaps this correlation is merely a fluke, a random alignment of disparate data points that fools the eyes and the mind. The idiosyncrasies of human behavior and the whims of statistical anomalies may very well be at play here, but further research is needed to untangle this enigma.
As we delve into the complexities of this peculiar correlation, we invite the scientific community to ponder the question: is there a deeper connection between the microscopic world of microbiology and the macroscopic realm of gasoline consumption, or are we simply witnessing the capricious dance of unrelated statistical variables?

ChatGPT:

Microbiologists, North Carolina, gasoline, Togo, correlation, Bureau of Labor Statistics, Energy Information Administration, data analysis, correlation coefficient, statistical significance, implications, research, human behavior, statistical anomalies, scientific community, microbiology, gasoline consumption, macroscopic realm.

*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 microbiologists in North Carolina
Detailed data title: BLS estimate of microbiologists in North Carolina
Source: Bureau of Larbor Statistics
See what else correlates with The number of microbiologists in North Carolina

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

Correlation r = 0.8880153 (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 = 0.7885711 (Coefficient of determination)
This means 78.9% of the change in the one variable (i.e., Gasoline pumped in Togo) is predictable based on the change in the other (i.e., The number of microbiologists in North Carolina) over the 19 years from 2003 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.9E-7.^Show 0.0000003889217909881774000000
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 0.89 in 3.9E-5% of random cases. Said differently, if you correlated 2,571,211 random variables^Note You don't actually need 2 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 18 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.73, 0.96 ] 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.

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
The number of microbiologists in North Carolina (Microbiologists)	260	180	340	250	260	650	760	650	560	520	450	370	240	290	410	430	370	470	640
Gasoline pumped in Togo (Million Barrels/Day)	2.45384	2.54036	2.66416	2.00981	2.50058	4.12516	5.84247	4.60386	3.94951	3.37937	3.52885	2.1734	2.38373	2.92123	3.01471	3.76255	3.62233	3.45871	3.64953

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([260,180,340,250,260,650,760,650,560,520,450,370,240,290,410,430,370,470,640,])
array_2 = np.array([2.45384,2.54036,2.66416,2.00981,2.50058,4.12516,5.84247,4.60386,3.94951,3.37937,3.52885,2.1734,2.38373,2.92123,3.01471,3.76255,3.62233,3.45871,3.64953,])
array_1_name = "The number of microbiologists in North Carolina"
array_2_name = "Gasoline pumped in Togo"

# 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 The number of microbiologists in North Carolina
Line chart for only Gasoline pumped in Togo
AI-generated correlation image
The spurious research paper: Microbiologists in North Carolina and Gasoline in Togo: A Marvelous Mismatch or Mysterious Match?

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Correlation ID: 3185 · Black Variable ID: 12296 · Red Variable ID: 24994


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