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Spurious correlation #4,345 · 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 the Libertarian Presidential candidate in Indiana and the second variable is Automotive recalls for issues with the Parking Brake.  The chart goes from 1980 to 2020, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As more people voted for the Libertarian candidate, they unknowingly unleashed a wave of free-spirited, non-interventionist energy. This unbridled liberty somehow found its way into the manufacturing process, causing parking brake components to say, "You can't contain me, man!" and leading to a sudden need for recalls. Remember, when it comes to parking brakes and politics, sometimes the correlation is just brake-coincidence!

Model: dalle-3
Prompt: Prompt: Generate an image of a high-tech scene where a parade of voters is pouring into polling stations in Indiana to cast their ballots for the Libertarian Presidential candidate. Simultaneously, at a nearby automotive factory, the parking brake component assembly line is experiencing a surge of free-spirited energy, with parts rebelling against their traditional limitations. Capture the juxtaposition of the orderly voting process and the chaotic rebellion of the parking brake parts in a futuristic setting. 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: Votes for the Libertarian Presidential candidate in Indiana and Automotive recalls for issues with the Parking Brake. 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: A Discovery magazine cover image High-tech Cyberpunk Hyper-realistic Oragami
ChatGPT: High-tech

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 Votes for the Libertarian Presidential candidate in Indiana and Automotive recalls for issues with the Parking Brake, in the following situation: As more people voted for the Libertarian candidate, they unknowingly unleashed a wave of free-spirited, non-interventionist energy. This unbridled liberty somehow found its way into the manufacturing process, causing parking brake components to say, "You can't contain me, man!" and leading to a sudden need for recalls. Remember, when it comes to parking brakes and politics, sometimes the correlation is just brake-coincidence!. Keep the description simple.
ChatGPT: In Indiana, a parade of voters poured into polling stations to cast their ballots for the Libertarian Presidential candidate. Meanwhile, at a nearby automotive factory, the parking brake component assembly line experienced a sudden surge of free-spirited energy, with parts declaring, "You can't contain me, man!" As a result, a need for recalls arose as the parking brake parts rebelled against their traditional limitations.

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: [ High-tech ] and depicting this scene: In Indiana, a parade of voters poured into polling stations to cast their ballots for the Libertarian Presidential candidate. Meanwhile, at a nearby automotive factory, the parking brake component assembly line experienced a sudden surge of free-spirited energy, with parts declaring, "You can't contain me, man!" As a result, a need for recalls arose as the parking brake parts rebelled against their traditional limitations. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image of a high-tech scene where a parade of voters is pouring into polling stations in Indiana to cast their ballots for the Libertarian Presidential candidate. Simultaneously, at a nearby automotive factory, the parking brake component assembly line is experiencing a surge of free-spirited energy, with parts rebelling against their traditional limitations. Capture the juxtaposition of the orderly voting process and the chaotic rebellion of the parking brake parts in a futuristic setting.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Votes for the Libertarian Presidential candidate in Indiana caused Automotive recalls for issues with the Parking Brake to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)
Parking Brake Libertarianism: An Underestimated Relationship Between Political Preferences and Automotive Mishaps

The Journal of Quirky Social Science Research

Jan 2024

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




Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Indiana and Automotive recalls for issues with the Parking Brake. Make lots of jokes, goofy observations, and puns.

Make the title a clever pun.

Your research team used data from MIT Election Data and Science Lab, Harvard Dataverse and US DOT to assess this nagging question. You found a correlation coefficient of 0.9687156 and p < 0.01 for 1980 to 2020.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
"Parking Brake Libertarianism: An Underestimated Relationship Between Political Preferences and Automotive Mishaps"

[[ABSTRACT]]
In this study, we delve into the rather unexpected and, dare we say, quirkily intriguing connection between political voting patterns and automotive manufacturing malfunctions. Taking our inspiration from the words of Kurk Vonnegut, "So it goes", we set out to investigate the correlation between votes cast for Libertarian presidential candidates in the state of Indiana and a specific type of automotive recalls related to the notorious parking brake system. Our research team, taking a delightfully unconventional approach, utilized data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through rigorous statistical analysis, we discovered a remarkably high correlation coefficient of 0.9687156 (p < 0.01) between these seemingly disparate phenomena for the time span of 1980 to 2020. Our findings not only bring an unexpected dose of levity to the world of politics and automotive engineering but also serve as a compelling reminder of the intricate and oftentimes confoundingly amusing links that exist in our world. So, buckle up your seatbelts and be prepared to engage in a truly whimsical journey through the world of statistical analysis and unexpected connections.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Indiana and Automotive recalls for issues with the Parking Brake. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
"Parking Brake Libertarianism: An Underestimated Relationship Between Political Preferences and Automotive Mishaps"

[[ABSTRACT]]
In this study, we delve into the rather unexpected and, dare we say, quirkily intriguing connection between political voting patterns and automotive manufacturing malfunctions. Taking our inspiration from the words of Kurk Vonnegut, "So it goes", we set out to investigate the correlation between votes cast for Libertarian presidential candidates in the state of Indiana and a specific type of automotive recalls related to the notorious parking brake system. Our research team, taking a delightfully unconventional approach, utilized data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through rigorous statistical analysis, we discovered a remarkably high correlation coefficient of 0.9687156 (p < 0.01) between these seemingly disparate phenomena for the time span of 1980 to 2020. Our findings not only bring an unexpected dose of levity to the world of politics and automotive engineering but also serve as a compelling reminder of the intricate and oftentimes confoundingly amusing links that exist in our world. So, buckle up your seatbelts and be prepared to engage in a truly whimsical journey through the world of statistical analysis and unexpected connections.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Political preferences and automotive mishaps may seem about as connected as a donut and a salad, but as the enigmatic Kurt Vonnegut once mused, "So it goes." With this enigmatic phrase serving as our guide, we embark on the most peculiar journey through statistical analysis—exploring the correlation between votes for the Libertarian presidential candidate in Indiana and automotive recalls pertaining to that most humdrum of car components, the parking brake.

It is widely known that the state of Indiana has a unique political landscape, known for its basketball fervor and, of course, a rich political history. But to what extent can we stretch this reputation to encompass the voting tendencies toward libertarian ideals and their potential reflection in automotive mishaps? This question, though whimsical at first glance, invokes a serious statistical inquiry that calls for a robust and punctilious exploration.

Our research, fueled by a dash of humor and an ounce of skepticism, draws from extensive data sources including the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through the cunning application of advanced statistical methods, we didn’t just stumble upon any old correlation; no, we unearthed a staggering correlation coefficient of 0.9687156 (p < 0.01) for the period spanning from 1980 to 2020. It's a discovery that raises eyebrows and corners of lips alike, inviting us to consider the possibility of an unexpected nexus between political proclivities and automotive incapacitations.

But enough with the fanfare! Let’s dive into the underbelly of this juxtaposition that can be both confounding and jovial, reminding us that the world of statistics, just like the open road, can be filled with surprising twists and turns. So, fasten your seatbelts; we're about to embark on a journey that will have you holding onto your parking brake with a renewed sense of wonder and bemusement.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Indiana and Automotive recalls for issues with the Parking Brake. 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 cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
"Parking Brake Libertarianism: An Underestimated Relationship Between Political Preferences and Automotive Mishaps"

[[ABSTRACT]]
In this study, we delve into the rather unexpected and, dare we say, quirkily intriguing connection between political voting patterns and automotive manufacturing malfunctions. Taking our inspiration from the words of Kurk Vonnegut, "So it goes", we set out to investigate the correlation between votes cast for Libertarian presidential candidates in the state of Indiana and a specific type of automotive recalls related to the notorious parking brake system. Our research team, taking a delightfully unconventional approach, utilized data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through rigorous statistical analysis, we discovered a remarkably high correlation coefficient of 0.9687156 (p < 0.01) between these seemingly disparate phenomena for the time span of 1980 to 2020. Our findings not only bring an unexpected dose of levity to the world of politics and automotive engineering but also serve as a compelling reminder of the intricate and oftentimes confoundingly amusing links that exist in our world. So, buckle up your seatbelts and be prepared to engage in a truly whimsical journey through the world of statistical analysis and unexpected connections.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Political preferences and automotive mishaps may seem about as connected as a donut and a salad, but as the enigmatic Kurt Vonnegut once mused, "So it goes." With this enigmatic phrase serving as our guide, we embark on the most peculiar journey through statistical analysis—exploring the correlation between votes for the Libertarian presidential candidate in Indiana and automotive recalls pertaining to that most humdrum of car components, the parking brake.
It is widely known that the state of Indiana has a unique political landscape, known for its basketball fervor and, of course, a rich political history. But to what extent can we stretch this reputation to encompass the voting tendencies toward libertarian ideals and their potential reflection in automotive mishaps? This question, though whimsical at first glance, invokes a serious statistical inquiry that calls for a robust and punctilious exploration.
Our research, fueled by a dash of humor and an ounce of skepticism, draws from extensive data sources including the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through the cunning application of advanced statistical methods, we didn’t just stumble upon any old correlation; no, we unearthed a staggering correlation coefficient of 0.9687156 (p < 0.01) for the period spanning from 1980 to 2020. It's a discovery that raises eyebrows and corners of lips alike, inviting us to consider the possibility of an unexpected nexus between political proclivities and automotive incapacitations.
But enough with the fanfare! Let’s dive into the underbelly of this juxtaposition that can be both confounding and jovial, reminding us that the world of statistics, just like the open road, can be filled with surprising twists and turns. So, fasten your seatbelts; we're about to embark on a journey that will have you holding onto your parking brake with a renewed sense of wonder and bemusement.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In a pristinely quantitative exploration of the topics at hand, Smith and Doe in their work "Evaluating Political Preferences and Recalls: A Statistical Analysis" have eloquently delved into the correlation, or lack thereof, between voting patterns and automotive mishaps. Their meticulous study, though thorough, unfailingly conjures up images of cats herding sheep, leaving readers with a sense of awe and bewilderment.

Jones, in "Intersections of Politics and Automobiles: A Comprehensive Review," examines the interplay between political leanings and automotive failures with the rigor befitting an intricate dance. The compelling stories woven in this tapestry of academic literature have kept readers guessing, much like a thrilling mystery novel.

Turning a page to non-traditional sources, we encounter "Car Troubles and Ballot Bubbles: An Unconventional Study" by Lorem Ipsum, which leaves one pondering the rather outlandish yet intriguing correlations found within. Their findings, though novel, evoke the image of a chameleon attempting to find its place in a crowded color wheel.

Shifting gears, we peer into the world of fiction for additional insights. "Atlas Parked: A Tale of Political Intrigue and Mechanical Mayhem" by A. Nowa and "Pulp Brake-tion: A Libertarian Mystery" by J. Steele, though not grounded in empirical data, offer curious narratives that veer close to the very essence of our research. The enthralling plotlines in these pieces would even make a statistician raise an eyebrow in puzzlement.

Venturing into the uncharted territory of social media, we stumbled upon a most venerated Twitter post by @DataGeek123 who humorously remarked, "I always knew there was something fishy about those parking brake-happy Libertarians. #StatisticalShenanigans." Such sardonic yet insightful reflections serve as a charming tease to the convoluted nature of our investigation.

In conclusion, the literature surveyed in this review gives voice to a symphony of inquiries, musings, and quips that underscore the inherently whimsical nature of our exploration, reminding us that statistical analysis, much like life, is replete with unexpected twists and amusing turns.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Indiana and Automotive recalls for issues with the Parking Brake. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and US DOT . 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]]
"Parking Brake Libertarianism: An Underestimated Relationship Between Political Preferences and Automotive Mishaps"

[[ABSTRACT]]
In this study, we delve into the rather unexpected and, dare we say, quirkily intriguing connection between political voting patterns and automotive manufacturing malfunctions. Taking our inspiration from the words of Kurk Vonnegut, "So it goes", we set out to investigate the correlation between votes cast for Libertarian presidential candidates in the state of Indiana and a specific type of automotive recalls related to the notorious parking brake system. Our research team, taking a delightfully unconventional approach, utilized data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through rigorous statistical analysis, we discovered a remarkably high correlation coefficient of 0.9687156 (p < 0.01) between these seemingly disparate phenomena for the time span of 1980 to 2020. Our findings not only bring an unexpected dose of levity to the world of politics and automotive engineering but also serve as a compelling reminder of the intricate and oftentimes confoundingly amusing links that exist in our world. So, buckle up your seatbelts and be prepared to engage in a truly whimsical journey through the world of statistical analysis and unexpected connections.

[[INTRODUCTION]]
Political preferences and automotive mishaps may seem about as connected as a donut and a salad, but as the enigmatic Kurt Vonnegut once mused, "So it goes." With this enigmatic phrase serving as our guide, we embark on the most peculiar journey through statistical analysis—exploring the correlation between votes for the Libertarian presidential candidate in Indiana and automotive recalls pertaining to that most humdrum of car components, the parking brake.
It is widely known that the state of Indiana has a unique political landscape, known for its basketball fervor and, of course, a rich political history. But to what extent can we stretch this reputation to encompass the voting tendencies toward libertarian ideals and their potential reflection in automotive mishaps? This question, though whimsical at first glance, invokes a serious statistical inquiry that calls for a robust and punctilious exploration.
Our research, fueled by a dash of humor and an ounce of skepticism, draws from extensive data sources including the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through the cunning application of advanced statistical methods, we didn’t just stumble upon any old correlation; no, we unearthed a staggering correlation coefficient of 0.9687156 (p < 0.01) for the period spanning from 1980 to 2020. It's a discovery that raises eyebrows and corners of lips alike, inviting us to consider the possibility of an unexpected nexus between political proclivities and automotive incapacitations.
But enough with the fanfare! Let’s dive into the underbelly of this juxtaposition that can be both confounding and jovial, reminding us that the world of statistics, just like the open road, can be filled with surprising twists and turns. So, fasten your seatbelts; we're about to embark on a journey that will have you holding onto your parking brake with a renewed sense of wonder and bemusement.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To investigate the perplexing relationship between political leanings and automotive malfunctions, our research team adopted a methodological approach that was as rigorous as it was whimsically inventive. Drawing on data sources from the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation, our intrepid researchers delved into decades of information encompassing the period from 1980 to 2020.

We began by collecting comprehensive data on votes cast for Libertarian presidential candidates in the state of Indiana, meticulously scouring election records, and cross-referencing them with precinct-level data to ensure accuracy. This initial step in our methodology involved teasing out the nuances of political inclinations in a state known for its distinct affinity for basketball and the occasional political eccentricity.

On the other hand, our approach to accessing automotive recall data was equally intricate and, dare we say, gripping. We painstakingly combed through reports from the US Department of Transportation, zeroing in specifically on recalls related to the hitherto unassuming yet surprisingly pivotal component of the parking brake system. The mere act of perusing through these recalls had our team members on the edge of their seats, wondering what quirks and quibbles we might uncover.

With these two disparate datasets in hand, we embarked on the task of uncovering patterns and correlations that would make even the most seasoned statistician raise an eyebrow. Employing a range of statistical techniques including correlation analysis and regression modelling, we set out to tease out the potential interplay between votes for the Libertarian presidential candidate in Indiana and the frequency of automotive recalls related to parking brake issues.

Our statistical toolkit included Pearson’s correlation coefficient and multivariate regression analysis, all tailored to peel back the layers of this delightfully unconventional inquiry. We meticulously controlled for potential confounding variables such as time trends, economic fluctuations, and even the occasional cosmic event that might have influenced the voting behavior and automotive upkeep in the Hoosier state.

Furthermore, our research team engaged in a thorough sensitivity analysis to assess the robustness of our findings, subjecting our models to a battery of tests and cross-validation measures. We also took special care to account for any potential heteroscedasticity or autocorrelation that might have threatened the integrity of our analyses – because, really, what’s a statistical inquiry without a touch of convolution?

After an excruciatingly detailed process of data cleaning, preparation, and analysis—performed with just the right dose of levity and seriousness—we arrived at the eye-popping correlation coefficient of 0.9687156 (p < 0.01). This unorthodox yet statistically sound journey through the data unveiled a relationship between political preferences and automotive eccentricities that has left our team in a state of whimsical wonderment.

In the end, our methodological exploits, while unconventional, paved the way for a meticulous and insightful exploration of the intersection between political proclivities and automotive mishaps. Just as Kurt Vonnegut’s words “So it goes” resonate with unexpected twists and turns, our methodological approach took us on a wild statistical ride, illustrating that even in the world of academia, a touch of playfulness and panache can yield enlightening revelations.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Indiana and Automotive recalls for issues with the Parking Brake. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

For the time period 1980 to 2020, you found a correlation 0.9687156, r-squared of 0.9384099, 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]]
"Parking Brake Libertarianism: An Underestimated Relationship Between Political Preferences and Automotive Mishaps"

[[ABSTRACT]]
In this study, we delve into the rather unexpected and, dare we say, quirkily intriguing connection between political voting patterns and automotive manufacturing malfunctions. Taking our inspiration from the words of Kurk Vonnegut, "So it goes", we set out to investigate the correlation between votes cast for Libertarian presidential candidates in the state of Indiana and a specific type of automotive recalls related to the notorious parking brake system. Our research team, taking a delightfully unconventional approach, utilized data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through rigorous statistical analysis, we discovered a remarkably high correlation coefficient of 0.9687156 (p < 0.01) between these seemingly disparate phenomena for the time span of 1980 to 2020. Our findings not only bring an unexpected dose of levity to the world of politics and automotive engineering but also serve as a compelling reminder of the intricate and oftentimes confoundingly amusing links that exist in our world. So, buckle up your seatbelts and be prepared to engage in a truly whimsical journey through the world of statistical analysis and unexpected connections.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Political preferences and automotive mishaps may seem about as connected as a donut and a salad, but as the enigmatic Kurt Vonnegut once mused, "So it goes." With this enigmatic phrase serving as our guide, we embark on the most peculiar journey through statistical analysis—exploring the correlation between votes for the Libertarian presidential candidate in Indiana and automotive recalls pertaining to that most humdrum of car components, the parking brake.
It is widely known that the state of Indiana has a unique political landscape, known for its basketball fervor and, of course, a rich political history. But to what extent can we stretch this reputation to encompass the voting tendencies toward libertarian ideals and their potential reflection in automotive mishaps? This question, though whimsical at first glance, invokes a serious statistical inquiry that calls for a robust and punctilious exploration.
Our research, fueled by a dash of humor and an ounce of skepticism, draws from extensive data sources including the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through the cunning application of advanced statistical methods, we didn’t just stumble upon any old correlation; no, we unearthed a staggering correlation coefficient of 0.9687156 (p < 0.01) for the period spanning from 1980 to 2020. It's a discovery that raises eyebrows and corners of lips alike, inviting us to consider the possibility of an unexpected nexus between political proclivities and automotive incapacitations.
But enough with the fanfare! Let’s dive into the underbelly of this juxtaposition that can be both confounding and jovial, reminding us that the world of statistics, just like the open road, can be filled with surprising twists and turns. So, fasten your seatbelts; we're about to embark on a journey that will have you holding onto your parking brake with a renewed sense of wonder and bemusement.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our analysis provided an unexpectedly robust correlation between the number of votes for the Libertarian presidential candidate in Indiana and automotive recalls related to issues with the parking brake. The correlation coefficient of 0.9687156, with an r-squared value of 0.9384099, demonstrated a remarkably strong relationship between these seemingly incongruous variables for the period spanning from 1980 to 2020.

The findings of this study serve as a testament to the peculiar interconnectedness of seemingly unrelated phenomena. It's as if the voters and the automotive systems were in cahoots, pulling handbrake turns in the world of statistical analysis. The p-value being less than 0.01 further underscores the statistical significance of this relationship, leaving us pondering the whimsical dance between political preferences and mechanical malfunctions.

Figure 1 showcases a scatterplot vividly portraying the striking correlation between votes for the Libertarian candidate in Indiana and automotive recalls for issues with the parking brake. It's almost as if the data itself is making a visual pun, driving home the unexpected connection between the political inclinations of Hoosiers and the troubles with their parking brakes, serving as a quirky reminder that statistical analysis can sometimes lead us down the most amusing of roads.

The implications of these findings are as intriguing as they are unexpected, shedding light on an unconventional relationship that not only tickles the statistical fancy but also prompts one to contemplate the quirky interplay of voting tendencies and mechanism failures. As Kurt Vonnegut eloquently put it, "So it goes," and indeed, our results invite us to embrace the whimsical nature of life's interconnectedness, even when it involves something as mundane as parking brakes and political preferences.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Indiana and Automotive recalls for issues with the Parking Brake. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
"Parking Brake Libertarianism: An Underestimated Relationship Between Political Preferences and Automotive Mishaps"

[[ABSTRACT]]
In this study, we delve into the rather unexpected and, dare we say, quirkily intriguing connection between political voting patterns and automotive manufacturing malfunctions. Taking our inspiration from the words of Kurk Vonnegut, "So it goes", we set out to investigate the correlation between votes cast for Libertarian presidential candidates in the state of Indiana and a specific type of automotive recalls related to the notorious parking brake system. Our research team, taking a delightfully unconventional approach, utilized data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through rigorous statistical analysis, we discovered a remarkably high correlation coefficient of 0.9687156 (p < 0.01) between these seemingly disparate phenomena for the time span of 1980 to 2020. Our findings not only bring an unexpected dose of levity to the world of politics and automotive engineering but also serve as a compelling reminder of the intricate and oftentimes confoundingly amusing links that exist in our world. So, buckle up your seatbelts and be prepared to engage in a truly whimsical journey through the world of statistical analysis and unexpected connections.

[[LITERATURE REVIEW]]
In a pristinely quantitative exploration of the topics at hand, Smith and Doe in their work "Evaluating Political Preferences and Recalls: A Statistical Analysis" have eloquently delved into the correlation, or lack thereof, between voting patterns and automotive mishaps. Their meticulous study, though thorough, unfailingly conjures up images of cats herding sheep, leaving readers with a sense of awe and bewilderment.
Jones, in "Intersections of Politics and Automobiles: A Comprehensive Review," examines the interplay between political leanings and automotive failures with the rigor befitting an intricate dance. The compelling stories woven in this tapestry of academic literature have kept readers guessing, much like a thrilling mystery novel.
Turning a page to non-traditional sources, we encounter "Car Troubles and Ballot Bubbles: An Unconventional Study" by Lorem Ipsum, which leaves one pondering the rather outlandish yet intriguing correlations found within. Their findings, though novel, evoke the image of a chameleon attempting to find its place in a crowded color wheel.
Shifting gears, we peer into the world of fiction for additional insights. "Atlas Parked: A Tale of Political Intrigue and Mechanical Mayhem" by A. Nowa and "Pulp Brake-tion: A Libertarian Mystery" by J. Steele, though not grounded in empirical data, offer curious narratives that veer close to the very essence of our research. The enthralling plotlines in these pieces would even make a statistician raise an eyebrow in puzzlement.
Venturing into the uncharted territory of social media, we stumbled upon a most venerated Twitter post by @DataGeek123 who humorously remarked, "I always knew there was something fishy about those parking brake-happy Libertarians. #StatisticalShenanigans." Such sardonic yet insightful reflections serve as a charming tease to the convoluted nature of our investigation.
In conclusion, the literature surveyed in this review gives voice to a symphony of inquiries, musings, and quips that underscore the inherently whimsical nature of our exploration, reminding us that statistical analysis, much like life, is replete with unexpected twists and amusing turns.

[[RESULTS]]
The results of our analysis provided an unexpectedly robust correlation between the number of votes for the Libertarian presidential candidate in Indiana and automotive recalls related to issues with the parking brake. The correlation coefficient of 0.9687156, with an r-squared value of 0.9384099, demonstrated a remarkably strong relationship between these seemingly incongruous variables for the period spanning from 1980 to 2020.
The findings of this study serve as a testament to the peculiar interconnectedness of seemingly unrelated phenomena. It's as if the voters and the automotive systems were in cahoots, pulling handbrake turns in the world of statistical analysis. The p-value being less than 0.01 further underscores the statistical significance of this relationship, leaving us pondering the whimsical dance between political preferences and mechanical malfunctions.
Figure 1 showcases a scatterplot vividly portraying the striking correlation between votes for the Libertarian candidate in Indiana and automotive recalls for issues with the parking brake. It's almost as if the data itself is making a visual pun, driving home the unexpected connection between the political inclinations of Hoosiers and the troubles with their parking brakes, serving as a quirky reminder that statistical analysis can sometimes lead us down the most amusing of roads.
The implications of these findings are as intriguing as they are unexpected, shedding light on an unconventional relationship that not only tickles the statistical fancy but also prompts one to contemplate the quirky interplay of voting tendencies and mechanism failures. As Kurt Vonnegut eloquently put it, "So it goes," and indeed, our results invite us to embrace the whimsical nature of life's interconnectedness, even when it involves something as mundane as parking brakes and political preferences.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The findings of this study present a compelling case for the surprising and remarkably strong correlation between votes for the Libertarian presidential candidate in Indiana and automotive recalls related to issues with the parking brake. While at first glance, this connection may seem about as likely as finding a penny-farthing bicycle in a Formula 1 race, the statistical evidence presented here cannot be denied. Our results support the previous observations made by Smith and Doe, who, in their endearing comparison of political preferences and recalls with sheep-herding cats, alluded to the potential for a hidden relationship. Likewise, Jones' intricate dance between political leanings and automotive failures appears to have foreshadowed the whimsical tango we have unearthed in our study.

The literature review affectionately documented the curious and sometimes perplexing nature of our investigation, drawing parallels with a chameleon lost in a crowded color wheel and likening our research to a tale of political intrigue and mechanical mayhem. The insightful Twitter post by @DataGeek123, with its teasing reference to "Statistical Shenanigans," now bears an unexpectedly prophetic weight, as we find ourselves uncovering one of the most statistically significant relationships in recent memory.

The scatterplot in Figure 1 not only vividly portrays the striking correlation between votes for the Libertarian candidate in Indiana and automotive recalls for issues with the parking brake, but it seems to sneak in an almost cheeky visual pun. It's as if the data itself is winking at us, reminding us that statistical analysis can sometimes lead us down the most amusing of roads, or in this case, parking brake avenues.

Our findings raise intriguing questions about the underlying mechanisms responsible for this peculiar relationship. Could it be that the fervent desire for individual freedom and minimal government intervention, often associated with Libertarian ideology, is somehow manifested in the malfunctioning of parking brakes? Is there a curious synergy at play here, akin to a whimsical ballet between political leanings and mechanical contraptions? These questions, although delightfully tongue-in-cheek, merit further exploration and theoretical development.

In summary, our study has not only uncovered a statistically robust connection between two seemingly unrelated domains but has also underscored the inherently whimsical nature of statistical analysis. The unexpected correlation between voting tendencies and mundane mechanical malfunctions serves as a delightful reminder that statistical exploration, much like life, is often filled with unexpected quirks and peculiar associations. As we continue to unravel the mysteries of statistical analysis, we must remain open to the whimsical nature of the correlations we may uncover, even if it involves something as seemingly prosaic as parking brakes and political preferences. After all, as Kurt Vonnegut so aptly put it, "So it goes."


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Indiana and Automotive recalls for issues with the Parking Brake. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Parking Brake Libertarianism: An Underestimated Relationship Between Political Preferences and Automotive Mishaps"

[[ABSTRACT]]
In this study, we delve into the rather unexpected and, dare we say, quirkily intriguing connection between political voting patterns and automotive manufacturing malfunctions. Taking our inspiration from the words of Kurk Vonnegut, "So it goes", we set out to investigate the correlation between votes cast for Libertarian presidential candidates in the state of Indiana and a specific type of automotive recalls related to the notorious parking brake system. Our research team, taking a delightfully unconventional approach, utilized data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through rigorous statistical analysis, we discovered a remarkably high correlation coefficient of 0.9687156 (p < 0.01) between these seemingly disparate phenomena for the time span of 1980 to 2020. Our findings not only bring an unexpected dose of levity to the world of politics and automotive engineering but also serve as a compelling reminder of the intricate and oftentimes confoundingly amusing links that exist in our world. So, buckle up your seatbelts and be prepared to engage in a truly whimsical journey through the world of statistical analysis and unexpected connections.

[[INTRDUCTION]]
Political preferences and automotive mishaps may seem about as connected as a donut and a salad, but as the enigmatic Kurt Vonnegut once mused, "So it goes." With this enigmatic phrase serving as our guide, we embark on the most peculiar journey through statistical analysis—exploring the correlation between votes for the Libertarian presidential candidate in Indiana and automotive recalls pertaining to that most humdrum of car components, the parking brake.
It is widely known that the state of Indiana has a unique political landscape, known for its basketball fervor and, of course, a rich political history. But to what extent can we stretch this reputation to encompass the voting tendencies toward libertarian ideals and their potential reflection in automotive mishaps? This question, though whimsical at first glance, invokes a serious statistical inquiry that calls for a robust and punctilious exploration.
Our research, fueled by a dash of humor and an ounce of skepticism, draws from extensive data sources including the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through the cunning application of advanced statistical methods, we didn’t just stumble upon any old correlation; no, we unearthed a staggering correlation coefficient of 0.9687156 (p < 0.01) for the period spanning from 1980 to 2020. It's a discovery that raises eyebrows and corners of lips alike, inviting us to consider the possibility of an unexpected nexus between political proclivities and automotive incapacitations.
But enough with the fanfare! Let’s dive into the underbelly of this juxtaposition that can be both confounding and jovial, reminding us that the world of statistics, just like the open road, can be filled with surprising twists and turns. So, fasten your seatbelts; we're about to embark on a journey that will have you holding onto your parking brake with a renewed sense of wonder and bemusement.

[[RESULTS]]
The results of our analysis provided an unexpectedly robust correlation between the number of votes for the Libertarian presidential candidate in Indiana and automotive recalls related to issues with the parking brake. The correlation coefficient of 0.9687156, with an r-squared value of 0.9384099, demonstrated a remarkably strong relationship between these seemingly incongruous variables for the period spanning from 1980 to 2020.
The findings of this study serve as a testament to the peculiar interconnectedness of seemingly unrelated phenomena. It's as if the voters and the automotive systems were in cahoots, pulling handbrake turns in the world of statistical analysis. The p-value being less than 0.01 further underscores the statistical significance of this relationship, leaving us pondering the whimsical dance between political preferences and mechanical malfunctions.
Figure 1 showcases a scatterplot vividly portraying the striking correlation between votes for the Libertarian candidate in Indiana and automotive recalls for issues with the parking brake. It's almost as if the data itself is making a visual pun, driving home the unexpected connection between the political inclinations of Hoosiers and the troubles with their parking brakes, serving as a quirky reminder that statistical analysis can sometimes lead us down the most amusing of roads.
The implications of these findings are as intriguing as they are unexpected, shedding light on an unconventional relationship that not only tickles the statistical fancy but also prompts one to contemplate the quirky interplay of voting tendencies and mechanism failures. As Kurt Vonnegut eloquently put it, "So it goes," and indeed, our results invite us to embrace the whimsical nature of life's interconnectedness, even when it involves something as mundane as parking brakes and political preferences.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study has uncovered a correlation so strong that it seems as if the voters and the parking brakes have formed a coalition of their own. The statistical significance of this relationship, with a p-value of less than 0.01, cannot be dismissed as a mere coincidence. It's as if the Hoosiers are not only making political statements but also sending a message to their automobiles through their voting choices.

While some might think this correlation is just a statistical fluke, the high r-squared value of 0.9384099 tells us that there is more to this connection than meets the eye. It's as if the parking brake issues and political leanings are performing a ballet of sorts, with one twirling and the other responding in a strikingly synchronized manner.

Therefore, it is safe to say that our findings add a dash of whimsy and wonder to the rather serious fields of political science and automotive engineering. Our results not only raise eyebrows but also elicit a chuckle or two, as we ponder the peculiarity of this unexpected relationship. Indeed, it seems that even the most mundane of car troubles can have a political twist!

In closing, our study invites us to embrace the humorous and offbeat side of statistical analysis, reminding us that sometimes the most peculiar connections can lead us to important revelations. So, as we release the parking brake on this study, it is clear that no further research in this area is needed. After all, when it comes to the correlation between libertarian votes and parking brake issues, the numbers don't lie, and neither does the amusement they provide. It's time to park this topic and drive onto the next statistical adventure!


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 Parking Brake Libertarianism: An Underestimated Relationship Between Political Preferences and Automotive Mishaps. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Social Science Research


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Parking Brake Libertarianism: An Underestimated Relationship Between Political Preferences and Automotive Mishaps. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Research Advancement


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 Parking Brake Libertarianism: An Underestimated Relationship Between Political Preferences and Automotive Mishaps with an abstract of In this study, we delve into the rather unexpected and, dare we say, quirkily intriguing connection between political voting patterns and automotive manufacturing malfunctions. Taking our inspiration from the words of Kurk Vonnegut, "So it goes", we set out to investigate the correlation between votes cast for Libertarian presidential candidates in the state of Indiana and a specific type of automotive recalls related to the notorious parking brake system. Our research team, taking a delightfully unconventional approach, utilized data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US Department of Transportation. Through rigorous statistical analysis, we discovered a remarkably high correlation coefficient of 0.9687156 (p < 0.01) between these seemingly disparate phenomena for the time span of 1980 to 2020. Our findings not only bring an unexpected dose of levity to the world of politics and automotive engineering but also serve as a compelling reminder of the intricate and oftentimes confoundingly amusing links that exist in our world. So, buckle up your seatbelts and be prepared to engage in a truly whimsical journey through the world of statistical analysis and unexpected connections.

ChatGPT:

parking brake malfunctions, political voting patterns, Libertarian presidential candidates, automotive recalls, Indiana, correlation, statistical analysis, MIT Election Data and Science Lab, Harvard Dataverse, US Department of Transportation, automotive engineering, correlation coefficient, 1980-2020

*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 the Libertarian Presidential candidate in Indiana
Detailed data title: Percentage of all votes cast for the Libertarian Presidential candidate in Indiana
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for the Libertarian Presidential candidate in Indiana

Automotive recalls for issues with the Parking Brake
Source: US DOT
See what else correlates with Automotive recalls for issues with the Parking Brake

Correlation r = 0.9687156 (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 = 0.9384099 (Coefficient of determination)
This means 93.8% of the change in the one variable (i.e., Automotive recalls for issues with the Parking Brake) is predictable based on the change in the other (i.e., Votes for the Libertarian Presidential candidate in Indiana) over the 9 years from 1980 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.7E-5. 0.0000172942137347787900000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.97 in 0.0017% of random cases. Said differently, if you correlated 57,823 random variables You don't actually need 57 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 8 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 8 because we have two variables measured over a period of 9 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.

[ 0.85, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
198019921996200020042008201220162020
Votes for the Libertarian Presidential candidate in Indiana (Percentage of votes)0.8754110.3441650.732030.7061330.7316851.063481.909334.899271.95284
Automotive recalls for issues with the Parking Brake (Recalls)51666872810




Why this works

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




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([0.875411,0.344165,0.73203,0.706133,0.731685,1.06348,1.90933,4.89927,1.95284,])
array_2 = np.array([5,1,6,6,6,8,7,28,10,])
array_1_name = "Votes for the Libertarian Presidential candidate in Indiana"
array_2_name = "Automotive recalls for issues with the Parking Brake"

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

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



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

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

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