Spurious correlation #4,375 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Votes for Republican Senators in Kansas and the second variable is Liquefied petroleum gas used in Barbados. The chart goes from 1980 to 2020, 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 Votes for Republican Senators in Kansas and the second variable is Liquefied petroleum gas used in Barbados. The chart goes from 1980 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the Republican votes for Senators in Kansas went up, there was a surge in demand for BBQ equipment, leading to an increase in Liquefied petroleum gas used in Barbados! It seems like the political heat in the US was sparking some real flame-grilled enthusiasm for gas usage in the Caribbean. Who knew that a political race thousands of miles away could have such a *fiery* impact on Barbadian gas consumption!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image that captures the essence of a bustling scene where people are celebrating the surge of Republican votes for Senators in Kansas by firing up BBQ equipment. Simultaneously, depict the surge in demand for Liquefied petroleum gas in Barbados, with the scent of sizzling food wafting through the air and creating a fiery impact felt thousands of miles away. Encapsulate the lively atmosphere, the sense of community, and the distinct textures of the woodblock painting style. 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: Republican votes for Senators in Kansas and Liquefied petroleum gas used in Barbados. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Hyper-realistic Cyberpunk Woodblock painting Surrealism Brutalism
ChatGPT: Woodblock painting

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 Republican votes for Senators in Kansas and Liquefied petroleum gas used in Barbados, in the following situation: As the Republican votes for Senators in Kansas went up, there was a surge in demand for BBQ equipment, leading to an increase in Liquefied petroleum gas used in Barbados! It seems like the political heat in the US was sparking some real flame-grilled enthusiasm for gas usage in the Caribbean. Who knew that a political race thousands of miles away could have such a *fiery* impact on Barbadian gas consumption!. Keep the description simple.
ChatGPT: In Kansas, the number of Republican votes for Senators surged, with people celebrating by firing up their BBQ equipment. In Barbados, the demand for Liquefied petroleum gas skyrocketed as the scent of sizzling food wafted through the air, creating a fiery impact felt thousands of miles away.

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: [ Woodblock painting ] and depicting this scene: In Kansas, the number of Republican votes for Senators surged, with people celebrating by firing up their BBQ equipment. In Barbados, the demand for Liquefied petroleum gas skyrocketed as the scent of sizzling food wafted through the air, creating a fiery impact felt thousands of miles away. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that captures the essence of a bustling scene where people are celebrating the surge of Republican votes for Senators in Kansas by firing up BBQ equipment. Simultaneously, depict the surge in demand for Liquefied petroleum gas in Barbados, with the scent of sizzling food wafting through the air and creating a fiery impact felt thousands of miles away. Encapsulate the lively atmosphere, the sense of community, and the distinct textures of the woodblock painting style.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in Republican votes for Senators in Kansas positively influenced Liquefied petroleum gas used in Barbados. Include one good pun.

AI academic paper

(Because p < 0.01)

Up in Smoke: The Flaming Hot Link Between Republican Votes in Kansas and LPG Usage in Barbados

The Journal of Unconventional Correlations

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 Republican votes for Senators in Kansas and Liquefied petroleum gas used in Barbados. Make lots of jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Up in Smoke: The Flaming Hot Link Between Republican Votes in Kansas and LPG Usage in Barbados"

[[ABSTRACT]]
In this study, we aimed to investigate the seemingly unrelated correlation between Republican votes for Senators in Kansas and the consumption of liquefied petroleum gas (LPG) in Barbados. Utilizing data from MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we set out to uncover any potential connections between these two seemingly disparate variables. After rigorous analysis, we discovered a correlation coefficient of 0.8289548 and p < 0.01 for the years 1980 to 2020, sparking both academic intrigue and a fair amount of eyebrow-raising among our research team.

Our findings not only point to a statistically significant relationship between these two factors, but also raise quirky questions about the intricate, unseen web of influence that can stretch across continents and political landscapes. This study sheds light on the unexpected connections that can be unearthed through data analysis, reminding us that in the world of research, sometimes the most unexpected correlations can ignite the most intriguing discussions.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As researchers, we often strive to uncover connections and patterns in the vast sea of data, hoping to shed light on the mysterious dance of variables that shape our world. Occasionally, though, we stumble upon correlations that make us scratch our heads and exclaim, "Well, I'll be switched!" Our investigation into the relationship between Republican votes for Senators in Kansas and the usage of liquefied petroleum gas (LPG) in Barbados falls squarely into this category.
One might wonder what could possibly link the voting preferences of Midwestern Americans to the energy consumption habits of Caribbean islanders. Is it a bizarre game of political telephone? A clandestine network of propane enthusiasts with a penchant for conservative politics? Or could it be that there is something deeper, more unexpected, and dare I say, gasp-worthy, lurking beneath the surface?
While it may seem like an academic romp through the land of nonsensical connections, rest assured, dear readers, this study is grounded in sophisticated statistical analysis and methodological rigor. Our initial puzzlement at this seemingly unrelated pair of variables quickly turned into a fervent quest to unravel the tangled yarn of data that lay before us.
The statistical relationship we uncovered, with a correlation coefficient of 0.8289548 and p < 0.01, left us both astounded and amused. We couldn't help but marvel at the curiosity that lurks within the labyrinth of datasets, where the unexpected can be as commonplace as a light sprinkling of correlation coefficients.
Join us on this unconventional expedition, as we venture into the uncharted territory of statistical surprises and peculiar pairings. Our findings may just spark a flame of curiosity within you, as we unravel the peculiar connection between Republican votes in Kansas and the consumption of LPG in Barbados. Shall we begin?

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The association between seemingly disparate variables has long captured the attention of researchers seeking to untangle the mysteries of statistical relationships. In "The Journal of Statistical Inquiries," Smith et al. delve into the unexpected connections that can emerge from rigorous data analysis, setting the stage for our own foray into the enigmatic relationship between Republican votes in Kansas and the consumption of liquefied petroleum gas (LPG) in Barbados.

Turning to the realm of energy consumption and its global implications, Doe and Jones illuminate the complex web of factors influencing LPG usage in their seminal work, "Energy Dynamics in a Changing World." This provides a valuable background for our exploration, as we seek to understand the peculiar interplay of political dynamics and energy preferences in our curious correlation.

As we move into the realm of fiction, one cannot help but draw a parallel to the enigmatic connections woven throughout Murakami's "Kafka on the Shore." While the novel may appear to be a far cry from the sober world of statistical analysis, its exploration of surreal links and parallel narratives serves as a whimsical reminder of the unexpected pathways that data can unveil.

Similarly, in "The Hitchhiker's Guide to the Galaxy" by Douglas Adams, we encounter a galactic journey filled with absurd coincidences and peculiar intergalactic intersections. Much like our own investigation, this literary escapade reminds us that the universe is rife with unanticipated peculiarities waiting to be uncovered.

Moreover, the rise of internet memes such as the "Surprised Pikachu" meme serves as a reflection of our own astonishment at the unlikely correlation we uncovered. Much like the wide-eyed Pikachu, our team was taken aback by the startling relationship between Republican votes in Kansas and LPG usage in Barbados.

As we steer our scholarly ship into the uncharted waters of these curious connections, it is with both a sense of academic rigor and a healthy dose of humor that we proceed. Let us navigate this seascape of statistical surprises with both steadfast resolve and a twinkle in our eyes, as we uncover the flaming hot link between seemingly unrelated phenomena.

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 Republican votes for Senators in Kansas and Liquefied petroleum gas used in Barbados. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration . You used data from 1980 to 2020

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]]
"Up in Smoke: The Flaming Hot Link Between Republican Votes in Kansas and LPG Usage in Barbados"

[[ABSTRACT]]
In this study, we aimed to investigate the seemingly unrelated correlation between Republican votes for Senators in Kansas and the consumption of liquefied petroleum gas (LPG) in Barbados. Utilizing data from MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we set out to uncover any potential connections between these two seemingly disparate variables. After rigorous analysis, we discovered a correlation coefficient of 0.8289548 and p < 0.01 for the years 1980 to 2020, sparking both academic intrigue and a fair amount of eyebrow-raising among our research team.

Our findings not only point to a statistically significant relationship between these two factors, but also raise quirky questions about the intricate, unseen web of influence that can stretch across continents and political landscapes. This study sheds light on the unexpected connections that can be unearthed through data analysis, reminding us that in the world of research, sometimes the most unexpected correlations can ignite the most intriguing discussions.

[[INTRODUCTION]]
As researchers, we often strive to uncover connections and patterns in the vast sea of data, hoping to shed light on the mysterious dance of variables that shape our world. Occasionally, though, we stumble upon correlations that make us scratch our heads and exclaim, "Well, I'll be switched!" Our investigation into the relationship between Republican votes for Senators in Kansas and the usage of liquefied petroleum gas (LPG) in Barbados falls squarely into this category.
One might wonder what could possibly link the voting preferences of Midwestern Americans to the energy consumption habits of Caribbean islanders. Is it a bizarre game of political telephone? A clandestine network of propane enthusiasts with a penchant for conservative politics? Or could it be that there is something deeper, more unexpected, and dare I say, gasp-worthy, lurking beneath the surface?
While it may seem like an academic romp through the land of nonsensical connections, rest assured, dear readers, this study is grounded in sophisticated statistical analysis and methodological rigor. Our initial puzzlement at this seemingly unrelated pair of variables quickly turned into a fervent quest to unravel the tangled yarn of data that lay before us.
The statistical relationship we uncovered, with a correlation coefficient of 0.8289548 and p < 0.01, left us both astounded and amused. We couldn't help but marvel at the curiosity that lurks within the labyrinth of datasets, where the unexpected can be as commonplace as a light sprinkling of correlation coefficients.
Join us on this unconventional expedition, as we venture into the uncharted territory of statistical surprises and peculiar pairings. Our findings may just spark a flame of curiosity within you, as we unravel the peculiar connection between Republican votes in Kansas and the consumption of LPG in Barbados. Shall we begin?

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To explore the eyebrow-raising correlation between Republican votes for Senators in Kansas and the consumption of liquefied petroleum gas (LPG) in Barbados, our research team embarked on a wild ride through the wild west of data analysis. We harnessed the power of statistical sorcery and the wisdom of the digital elders to wrangle the hodgepodge of information from various sources, all to answer the burning question: just what in the Midwestern barbecue is going on here?

Data Collection:
First, we donned our virtual explorer hats and scoured the digital savannas of the MIT Election Data and Science Lab, the Harvard Dataverse, and the Energy Information Administration. We sifted through mounds of data from the years 1980 to 2020, making sure to gather every possible nugget of information related to Republican votes in Kansas and LPG usage in Barbados. It was a real data safari, let me tell you.

Data Cleaning:
After lassoing the raw data, we threw it into our statistical washing machine, where we scrubbed and buffed it until it sparkled like a freshly polished propane tank. We discarded any duplicate or irrelevant data points, ensuring that our dataset was as pristine as a freshly buffed brass fitting.

Statistical Analysis:
Armed with our trusty statistical toolkit, we unleashed the powers of correlation analysis to untangle the enigmatic relationship between our chosen variables. We calculated correlation coefficients, p-values, and confidence intervals with the precision of a surgeon, all in the quest for the elusive truth behind this curious coupling.

Robustness Checks:
To ensure the integrity of our findings, we subjected our analysis to a battery of robustness checks. We prodded and poked our models from every possible angle, making sure that our results stood firm in the face of scrutiny, much like a sturdy barbecue grill in the midst of a gusty Kansas wind.

Sensitivity Analysis:
In a nod to the capricious nature of statistical relationships, we conducted sensitivity analyses to gauge the impact of potential outliers and alternative model specifications. We wanted to make sure that our findings weren't just a flash in the pan, but rather a substantial, well-done conclusion.

Limitations:
As with any adventure into the wilds of data analysis, we encountered a few potholes and pitfalls along the way. It's important to note that while our findings reveal an intriguing correlation, causation remains as slippery as a greased pig at a county fair. Additionally, the generalizability of our findings to other contexts should be approached with caution, as the idiosyncrasies of Kansas politics and Caribbean energy habits may be difficult to extrapolate to other regions.

Ethical Considerations:
We operated under the steadfast guidance of academic integrity, ensuring that our data collection and analysis adhered to the highest ethical standards. No data points were harmed in the making of this study, and all statistical manipulations were conducted with the utmost respect for the dignity of the numbers involved.

In closing, our methodology represents a fusion of tenacious data wrangling, rigorous statistical analysis, and a fair dose of whimsy. Our journey through the statistical wilderness yielded unexpected connections and intriguing insights, serving as a reminder that in the world of research, even the most peculiar pairings can lead to illuminating discoveries.

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 Republican votes for Senators in Kansas and Liquefied petroleum gas used in Barbados. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration .

For the time period 1980 to 2020, you found a correlation 0.8289548, r-squared of 0.6871661, 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]]
"Up in Smoke: The Flaming Hot Link Between Republican Votes in Kansas and LPG Usage in Barbados"

[[ABSTRACT]]
In this study, we aimed to investigate the seemingly unrelated correlation between Republican votes for Senators in Kansas and the consumption of liquefied petroleum gas (LPG) in Barbados. Utilizing data from MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we set out to uncover any potential connections between these two seemingly disparate variables. After rigorous analysis, we discovered a correlation coefficient of 0.8289548 and p < 0.01 for the years 1980 to 2020, sparking both academic intrigue and a fair amount of eyebrow-raising among our research team.

Our findings not only point to a statistically significant relationship between these two factors, but also raise quirky questions about the intricate, unseen web of influence that can stretch across continents and political landscapes. This study sheds light on the unexpected connections that can be unearthed through data analysis, reminding us that in the world of research, sometimes the most unexpected correlations can ignite the most intriguing discussions.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
As researchers, we often strive to uncover connections and patterns in the vast sea of data, hoping to shed light on the mysterious dance of variables that shape our world. Occasionally, though, we stumble upon correlations that make us scratch our heads and exclaim, "Well, I'll be switched!" Our investigation into the relationship between Republican votes for Senators in Kansas and the usage of liquefied petroleum gas (LPG) in Barbados falls squarely into this category.
One might wonder what could possibly link the voting preferences of Midwestern Americans to the energy consumption habits of Caribbean islanders. Is it a bizarre game of political telephone? A clandestine network of propane enthusiasts with a penchant for conservative politics? Or could it be that there is something deeper, more unexpected, and dare I say, gasp-worthy, lurking beneath the surface?
While it may seem like an academic romp through the land of nonsensical connections, rest assured, dear readers, this study is grounded in sophisticated statistical analysis and methodological rigor. Our initial puzzlement at this seemingly unrelated pair of variables quickly turned into a fervent quest to unravel the tangled yarn of data that lay before us.
The statistical relationship we uncovered, with a correlation coefficient of 0.8289548 and p < 0.01, left us both astounded and amused. We couldn't help but marvel at the curiosity that lurks within the labyrinth of datasets, where the unexpected can be as commonplace as a light sprinkling of correlation coefficients.
Join us on this unconventional expedition, as we venture into the uncharted territory of statistical surprises and peculiar pairings. Our findings may just spark a flame of curiosity within you, as we unravel the peculiar connection between Republican votes in Kansas and the consumption of LPG in Barbados. Shall we begin?

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The data analysis revealed a correlation coefficient of 0.8289548, indicating a robust relationship between Republican votes for Senators in Kansas and the usage of liquefied petroleum gas (LPG) in Barbados. This correlation coefficient can be interpreted as a relatively strong positive relationship between the two variables. It's as if these two seemingly unrelated elements have decided to do-si-do in the statistical square dance of life!

The calculated r-squared value of 0.6871661 further emphasizes the substantial association between the variables, suggesting that approximately 68.72% of the variation in LPG usage in Barbados can be explained by the Republican votes for Senators in Kansas. Who would have thought that political leanings in the Sunflower State could have such a sizzling impact on the use of LPG in a Caribbean paradise? It's enough to make one take a moment to appreciate the curious, convoluted tapestry of interconnectedness that weaves its way through the fabric of society.

The p-value of less than 0.01 indicates that the observed relationship is unlikely to be due to random chance alone. While this statistical significance is undoubtedly intriguing, it also leaves us pondering the deeper significance of these findings. Could it be that there's an unexplored realm of geopolitical energy influences at play here, or is it simply a case of statistical happenstance? The mysteries abound, much like a compelling detective novel, and we find ourselves eager to dive deeper into the enigmatic waters of correlation and causation.

Furthermore, the visually represented correlation, depicted in Fig. 1, showcases a scatterplot that clearly demonstrates the strong and positive relationship between Republican votes for Senators in Kansas and LPG usage in Barbados. This visual evidence solidifies the statistical findings and serves as a visual reminder that in the world of data analysis, even the most unexpected pairings can share a dance across the statistical dance floor.

In summary, our research has uncovered a surprising and statistically significant connection between the political landscape of Kansas and the energy habits of Barbados, enriching the academic discussion with a whimsical tale of unexpected correlation. This study not only highlights the playful and unpredictable nature of statistical exploration but also invites researchers and enthusiasts alike to embrace the quirks and surprises that await within the labyrinth of data analysis.

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 Republican votes for Senators in Kansas and Liquefied petroleum gas used in Barbados. Make lots of jokes, goofy observations, and puns.

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]]
"Up in Smoke: The Flaming Hot Link Between Republican Votes in Kansas and LPG Usage in Barbados"

[[ABSTRACT]]
In this study, we aimed to investigate the seemingly unrelated correlation between Republican votes for Senators in Kansas and the consumption of liquefied petroleum gas (LPG) in Barbados. Utilizing data from MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we set out to uncover any potential connections between these two seemingly disparate variables. After rigorous analysis, we discovered a correlation coefficient of 0.8289548 and p < 0.01 for the years 1980 to 2020, sparking both academic intrigue and a fair amount of eyebrow-raising among our research team.

Our findings not only point to a statistically significant relationship between these two factors, but also raise quirky questions about the intricate, unseen web of influence that can stretch across continents and political landscapes. This study sheds light on the unexpected connections that can be unearthed through data analysis, reminding us that in the world of research, sometimes the most unexpected correlations can ignite the most intriguing discussions.

[[LITERATURE REVIEW]]
The association between seemingly disparate variables has long captured the attention of researchers seeking to untangle the mysteries of statistical relationships. In "The Journal of Statistical Inquiries," Smith et al. delve into the unexpected connections that can emerge from rigorous data analysis, setting the stage for our own foray into the enigmatic relationship between Republican votes in Kansas and the consumption of liquefied petroleum gas (LPG) in Barbados.
Turning to the realm of energy consumption and its global implications, Doe and Jones illuminate the complex web of factors influencing LPG usage in their seminal work, "Energy Dynamics in a Changing World." This provides a valuable background for our exploration, as we seek to understand the peculiar interplay of political dynamics and energy preferences in our curious correlation.
As we move into the realm of fiction, one cannot help but draw a parallel to the enigmatic connections woven throughout Murakami's "Kafka on the Shore." While the novel may appear to be a far cry from the sober world of statistical analysis, its exploration of surreal links and parallel narratives serves as a whimsical reminder of the unexpected pathways that data can unveil.
Similarly, in "The Hitchhiker's Guide to the Galaxy" by Douglas Adams, we encounter a galactic journey filled with absurd coincidences and peculiar intergalactic intersections. Much like our own investigation, this literary escapade reminds us that the universe is rife with unanticipated peculiarities waiting to be uncovered.
Moreover, the rise of internet memes such as the "Surprised Pikachu" meme serves as a reflection of our own astonishment at the unlikely correlation we uncovered. Much like the wide-eyed Pikachu, our team was taken aback by the startling relationship between Republican votes in Kansas and LPG usage in Barbados.
As we steer our scholarly ship into the uncharted waters of these curious connections, it is with both a sense of academic rigor and a healthy dose of humor that we proceed. Let us navigate this seascape of statistical surprises with both steadfast resolve and a twinkle in our eyes, as we uncover the flaming hot link between seemingly unrelated phenomena.

[[RESULTS]]
The data analysis revealed a correlation coefficient of 0.8289548, indicating a robust relationship between Republican votes for Senators in Kansas and the usage of liquefied petroleum gas (LPG) in Barbados. This correlation coefficient can be interpreted as a relatively strong positive relationship between the two variables. It's as if these two seemingly unrelated elements have decided to do-si-do in the statistical square dance of life!
The calculated r-squared value of 0.6871661 further emphasizes the substantial association between the variables, suggesting that approximately 68.72% of the variation in LPG usage in Barbados can be explained by the Republican votes for Senators in Kansas. Who would have thought that political leanings in the Sunflower State could have such a sizzling impact on the use of LPG in a Caribbean paradise? It's enough to make one take a moment to appreciate the curious, convoluted tapestry of interconnectedness that weaves its way through the fabric of society.
The p-value of less than 0.01 indicates that the observed relationship is unlikely to be due to random chance alone. While this statistical significance is undoubtedly intriguing, it also leaves us pondering the deeper significance of these findings. Could it be that there's an unexplored realm of geopolitical energy influences at play here, or is it simply a case of statistical happenstance? The mysteries abound, much like a compelling detective novel, and we find ourselves eager to dive deeper into the enigmatic waters of correlation and causation.
Furthermore, the visually represented correlation, depicted in Fig. 1, showcases a scatterplot that clearly demonstrates the strong and positive relationship between Republican votes for Senators in Kansas and LPG usage in Barbados. This visual evidence solidifies the statistical findings and serves as a visual reminder that in the world of data analysis, even the most unexpected pairings can share a dance across the statistical dance floor.
In summary, our research has uncovered a surprising and statistically significant connection between the political landscape of Kansas and the energy habits of Barbados, enriching the academic discussion with a whimsical tale of unexpected correlation. This study not only highlights the playful and unpredictable nature of statistical exploration but also invites researchers and enthusiasts alike to embrace the quirks and surprises that await within the labyrinth of data analysis.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of this study have set ablaze a fiery discussion of the intertwined relationship between Republican votes in Kansas and liquefied petroleum gas (LPG) consumption in Barbados. Our findings not only confirm the statistically robust connection suggested by prior research but also add a touch of whimsy to the otherwise serious world of statistical analysis.

One of the key findings of our study is the substantial correlation coefficient of 0.8289548 between Republican votes for Senators in Kansas and LPG usage in Barbados. It's as if these two variables are engaging in a spirited tango across the statistical dance floor, demonstrating a remarkable level of synchronization. This correlation coefficient gives new meaning to the phrase "political heat," as it illuminates the undeniable link between the voting patterns in the heartland of America and the energy preferences of a Caribbean oasis.

The r-squared value of 0.6871661 further emphasizes the influential role that Republican votes in Kansas play in shaping LPG usage in Barbados. It's like uncovering a hidden subplot in a complex geopolitical thriller, where the actions of one entity reverberate across oceans and hemispheres. Who knew that the political breeze from the wheat fields of Kansas could fan the flames of LPG consumption in the tropical breeze of Barbados with such vigor?

Indeed, the p-value of less than 0.01 adds an element of intrigue to our findings. This level of statistical significance is like discovering a treasure chest at the end of a statistical rainbow, sparking questions of causation and hidden mechanisms at play. It compels us to consider the curious ways in which political dynamics and energy preferences may intersect, inviting us to ponder whether there are deeper geopolitical undercurrents influencing this correlation or if it's simply a curious quirk of statistical fate.

Furthermore, the visually represented correlation in Fig. 1, with its scatterplot showcasing the strong and positive relationship between the variables, serves as a vivid reminder that in the world of data analysis, even the most unexpected pairings can come together for a spirited statistical soirée.

In conclusion, our study not only validates the unexpected correlation between Republican votes in Kansas and LPG usage in Barbados but also highlights the playful and unpredictable nature of statistical exploration. These findings invite us to embrace the quirks and surprises that arise from uncovering the unexpected web of statistical relationships, reminding us that in the world of research, the most whimsical correlations can often spark the most thought-provoking discussions.

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 Republican votes for Senators in Kansas and Liquefied petroleum gas used in Barbados. Make lots of jokes, goofy observations, and puns.

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]]
"Up in Smoke: The Flaming Hot Link Between Republican Votes in Kansas and LPG Usage in Barbados"

[[ABSTRACT]]
In this study, we aimed to investigate the seemingly unrelated correlation between Republican votes for Senators in Kansas and the consumption of liquefied petroleum gas (LPG) in Barbados. Utilizing data from MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we set out to uncover any potential connections between these two seemingly disparate variables. After rigorous analysis, we discovered a correlation coefficient of 0.8289548 and p < 0.01 for the years 1980 to 2020, sparking both academic intrigue and a fair amount of eyebrow-raising among our research team.

Our findings not only point to a statistically significant relationship between these two factors, but also raise quirky questions about the intricate, unseen web of influence that can stretch across continents and political landscapes. This study sheds light on the unexpected connections that can be unearthed through data analysis, reminding us that in the world of research, sometimes the most unexpected correlations can ignite the most intriguing discussions.

[[INTRDUCTION]]
As researchers, we often strive to uncover connections and patterns in the vast sea of data, hoping to shed light on the mysterious dance of variables that shape our world. Occasionally, though, we stumble upon correlations that make us scratch our heads and exclaim, "Well, I'll be switched!" Our investigation into the relationship between Republican votes for Senators in Kansas and the usage of liquefied petroleum gas (LPG) in Barbados falls squarely into this category.
One might wonder what could possibly link the voting preferences of Midwestern Americans to the energy consumption habits of Caribbean islanders. Is it a bizarre game of political telephone? A clandestine network of propane enthusiasts with a penchant for conservative politics? Or could it be that there is something deeper, more unexpected, and dare I say, gasp-worthy, lurking beneath the surface?
While it may seem like an academic romp through the land of nonsensical connections, rest assured, dear readers, this study is grounded in sophisticated statistical analysis and methodological rigor. Our initial puzzlement at this seemingly unrelated pair of variables quickly turned into a fervent quest to unravel the tangled yarn of data that lay before us.
The statistical relationship we uncovered, with a correlation coefficient of 0.8289548 and p < 0.01, left us both astounded and amused. We couldn't help but marvel at the curiosity that lurks within the labyrinth of datasets, where the unexpected can be as commonplace as a light sprinkling of correlation coefficients.
Join us on this unconventional expedition, as we venture into the uncharted territory of statistical surprises and peculiar pairings. Our findings may just spark a flame of curiosity within you, as we unravel the peculiar connection between Republican votes in Kansas and the consumption of LPG in Barbados. Shall we begin?

[[RESULTS]]
The data analysis revealed a correlation coefficient of 0.8289548, indicating a robust relationship between Republican votes for Senators in Kansas and the usage of liquefied petroleum gas (LPG) in Barbados. This correlation coefficient can be interpreted as a relatively strong positive relationship between the two variables. It's as if these two seemingly unrelated elements have decided to do-si-do in the statistical square dance of life!
The calculated r-squared value of 0.6871661 further emphasizes the substantial association between the variables, suggesting that approximately 68.72% of the variation in LPG usage in Barbados can be explained by the Republican votes for Senators in Kansas. Who would have thought that political leanings in the Sunflower State could have such a sizzling impact on the use of LPG in a Caribbean paradise? It's enough to make one take a moment to appreciate the curious, convoluted tapestry of interconnectedness that weaves its way through the fabric of society.
The p-value of less than 0.01 indicates that the observed relationship is unlikely to be due to random chance alone. While this statistical significance is undoubtedly intriguing, it also leaves us pondering the deeper significance of these findings. Could it be that there's an unexplored realm of geopolitical energy influences at play here, or is it simply a case of statistical happenstance? The mysteries abound, much like a compelling detective novel, and we find ourselves eager to dive deeper into the enigmatic waters of correlation and causation.
Furthermore, the visually represented correlation, depicted in Fig. 1, showcases a scatterplot that clearly demonstrates the strong and positive relationship between Republican votes for Senators in Kansas and LPG usage in Barbados. This visual evidence solidifies the statistical findings and serves as a visual reminder that in the world of data analysis, even the most unexpected pairings can share a dance across the statistical dance floor.
In summary, our research has uncovered a surprising and statistically significant connection between the political landscape of Kansas and the energy habits of Barbados, enriching the academic discussion with a whimsical tale of unexpected correlation. This study not only highlights the playful and unpredictable nature of statistical exploration but also invites researchers and enthusiasts alike to embrace the quirks and surprises that await within the labyrinth of data analysis.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has brought to light the unlikely bond between Republican votes in Kansas and the consumption of liquefied petroleum gas (LPG) in Barbados. It seems that these two seemingly unrelated variables have formed a statistical bromance that leaves us scratching our heads and wondering if they're secretly passing notes in the statistical classroom.

The robust correlation coefficient of 0.8289548 has sent ripples through the academic community, reminding us that the world of data analysis is not without its fair share of surprises, much like receiving a mystery flavor in a pack of jellybeans.

As we reflect on the statistically significant relationship between these variables, we can't help but marvel at the whimsical waltz of statistical significance, where even the most unexpected pairs can find common ground, like two mismatched socks at a statistical sock hop.

With a visual depiction of this connection in Fig. 1, showcasing a scatterplot that is as surprising as finding a unicorn in a field of statistical sheep, our findings stand as a playful reminder that statistical analysis is not just about crunching numbers, but also about uncovering the unexpected connections that lie beneath the surface.

In light of our findings, we are left with a sense of wonder and a hint of amusement, as though the statistical gods have decided to play a game of statistical hide and seek with these unsuspecting variables.

With that said, we assert confidently that no further research is needed in this captivating yet quirky area of inquiry. After all, sometimes, a statistical surprise is best left to stand on its own, much like a quirky anecdote at a dinner party that leaves everyone amused and wondering, "What on earth?"

So, let us bid adieu to this statistical romance between Kansas and Barbados, leaving it to dance its own peculiar dance in the annals of statistical curiosities. Let's call it a day and leave our minds unclouded by the statistical fog of mystery, ready to embrace the next unexpected discovery that lurks within the uncharted territory of data analysis.

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 Up in Smoke: The Flaming Hot Link Between Republican Votes in Kansas and LPG Usage in Barbados. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Unconventional Correlations

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 Up in Smoke: The Flaming Hot Link Between Republican Votes in Kansas and LPG Usage in Barbados. Respond only with the name of a fictional organization.

ChatGPT:

The International Consortium for Interconnected Climate Research

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Up in Smoke: The Flaming Hot Link Between Republican Votes in Kansas and LPG Usage in Barbados with an abstract of In this study, we aimed to investigate the seemingly unrelated correlation between Republican votes for Senators in Kansas and the consumption of liquefied petroleum gas (LPG) in Barbados. Utilizing data from MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we set out to uncover any potential connections between these two seemingly disparate variables. After rigorous analysis, we discovered a correlation coefficient of 0.8289548 and p < 0.01 for the years 1980 to 2020, sparking both academic intrigue and a fair amount of eyebrow-raising among our research team.
Our findings not only point to a statistically significant relationship between these two factors, but also raise quirky questions about the intricate, unseen web of influence that can stretch across continents and political landscapes. This study sheds light on the unexpected connections that can be unearthed through data analysis, reminding us that in the world of research, sometimes the most unexpected correlations can ignite the most intriguing discussions.

ChatGPT:

Republican votes, Kansas, LPG usage, Barbados, correlation, data analysis, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration, correlation coefficient, political landscapes, data analysis, unexpected correlations.

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

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Data details

Votes for Republican Senators in Kansas
Detailed data title: Total number of votes cast for Federal Republican Senate candidates in Kansas
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for Republican Senators in Kansas

Liquefied petroleum gas used in Barbados
Detailed data title: Volume of liquefied petroleum gas used consumed in Barbados in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Liquefied petroleum gas used in Barbados

Correlation r = 0.8289548 (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 = 0.6871661 (Coefficient of determination)
This means 68.7% of the change in the one variable (i.e., Liquefied petroleum gas used in Barbados) is predictable based on the change in the other (i.e., Votes for Republican Senators in Kansas) over the 14 years from 1980 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00025.^Show 0.0002474088174862497000000000
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 0.83 in 0.025% of random cases. Said differently, if you correlated 4,042 random variables^Note Which I absolutely did.
with the same 13 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 13 because we have two variables measured over a period of 14 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.

[ 0.53, 0.94 ] 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.

	1980	1984	1986	1990	1992	1996	1998	2002	2004	2008	2010	2014	2016	2020
Votes for Republican Senators in Kansas (Total votes)	598686	757402	576902	578605	706246	1226700	474639	641075	780863	727121	587175	460350	732376	727962
Liquefied petroleum gas used in Barbados (Million Barrels/Day)	0.239286	0.257143	0.3	0.2	0.3	1.9	0.4	0.369068	0.389689	0.37849	0.392493	0.212932	0.238689	0.201519

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([598686,757402,576902,578605,706246,1226700,474639,641075,780863,727121,587175,460350,732376,727962,])
array_2 = np.array([0.239286,0.257143,0.3,0.2,0.3,1.9,0.4,0.369068,0.389689,0.37849,0.392493,0.212932,0.238689,0.201519,])
array_1_name = "Votes for Republican Senators in Kansas"
array_2_name = "Liquefied petroleum gas used in Barbados"

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

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

Reuseable content

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

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

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

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

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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 Votes for Republican Senators in Kansas
Line chart for only Liquefied petroleum gas used in Barbados
AI-generated correlation image
The spurious research paper: Up in Smoke: The Flaming Hot Link Between Republican Votes in Kansas and LPG Usage in Barbados

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Correlation ID: 4375 · Black Variable ID: 26242 · Red Variable ID: 24184


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