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Spurious correlation #4,735 · 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 Republican Presidential candidate in Utah and the second variable is Automotive recalls issued by BMW of North America.  The chart goes from 1976 to 2020, and the two variables track closely in value over that time. Small Image
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AI explanation

The more Republican votes in Utah, the more it revs up certain demographics, leading to an increase in BMW sales. This surge in demand puts extra pressure on BMW of North America to quickly produce more vehicles, leading to an uptick in automotive recalls. It seems like the political race wasn't the only thing in Utah giving everyone a campaign for change - some BMWs were also feeling the need for re-election!

Model: dalle-3
Prompt: Generate an image of a minimalist landscape with a stark, desert backdrop of Utah. In the foreground, depict a line of sleek, minimalist BMW cars lined up, symbolizing the surge in sales and the buzzing activity at the production plant. Incorporate a subtle representation of the ballot counting process as a minimalist abstract graphic, hinting at the Republican Presidential candidate. Add a touch of humor by including a group of mechanic figures working on the BMWs, implying the automotive recalls alongside the election buzz. 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 Republican Presidential candidate in Utah and Automotive recalls issued by BMW of North America. 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: Oragami Hyper-realistic Hyper-realistic Cute 2D animation Minimalism
ChatGPT: Minimalism

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Votes for the Republican Presidential candidate in Utah and Automotive recalls issued by BMW of North America, in the following situation: The more Republican votes in Utah, the more it revs up certain demographics, leading to an increase in BMW sales. This surge in demand puts extra pressure on BMW of North America to quickly produce more vehicles, leading to an uptick in automotive recalls. It seems like the political race wasn't the only thing in Utah giving everyone a campaign for change - some BMWs were also feeling the need for re-election!. Keep the description simple.
ChatGPT: In Utah, the ballots are counted for the Republican Presidential candidate as engines rev up across the state, and BMW sales surge. The increased demand puts pressure on BMW of North America, leading to a flurry of activity at the production plant. However, amidst the excitement, a fleet of BMWs lined up for a re-election of their own, with mechanics working to address automotive recalls.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Minimalism ] and depicting this scene: In Utah, the ballots are counted for the Republican Presidential candidate as engines rev up across the state, and BMW sales surge. The increased demand puts pressure on BMW of North America, leading to a flurry of activity at the production plant. However, amidst the excitement, a fleet of BMWs lined up for a re-election of their own, with mechanics working to address automotive recalls. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a minimalist landscape with a stark, desert backdrop of Utah. In the foreground, depict a line of sleek, minimalist BMW cars lined up, symbolizing the surge in sales and the buzzing activity at the production plant. Incorporate a subtle representation of the ballot counting process as a minimalist abstract graphic, hinting at the Republican Presidential candidate. Add a touch of humor by including a group of mechanic figures working on the BMWs, implying the automotive recalls alongside the election buzz.

*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 Republican Presidential candidate in Utah caused Automotive recalls issued by BMW of North America to increase. Include one good pun.

AI academic paper

(Because p < 0.01)
An Ode to Roads and Votes: The Antidote for BMW and Republican Boat Floats

The Journal of Transport Politics and Cultural Studies

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 dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You 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 Republican Presidential candidate in Utah and Automotive recalls issued by BMW of North America. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Rhyme words in the title.

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 0.8895360 and p < 0.01 for 1976 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]]
An Ode to Roads and Votes: The Antidote for BMW and Republican Boat Floats

[[ABSTRACT]]
The connection between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America is a perplexing enigma that has baffled scholars and auto enthusiasts alike. In this study, we set out to untangle the knotty relationship between political preferences and vehicular safety lapses. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, we sought to elucidate the potential influence of conservative voting patterns on BMW automotive recalls. Much to our surprise, we discovered a correlation coefficient of 0.8895360 and p < 0.01 for the period spanning 1976 to 2020, indicating a robust association between these seemingly disparate phenomena. In both literal and figurative terms, it appears that Republican support in the Beehive State may indeed have an impact on the wheels of BMW. It's as if voters are clutching onto their political beliefs and holding onto their BMWs – for better or verse!

Who knew that political leanings and automotive malfunctions could be tied together in such a peculiar manner? Our findings not only raise eyebrows but also perform a parallel park into uncharted territory, shedding light on the multifaceted tapestry of societal influence on corporate behaviors. It’s as if we stumbled upon a pothole that led straight to the heart of political and automotive intrigue. This study poignantly illustrates that, much like the road to victory, the road to vehicular safety may also be paved with political inclinations. After all, in the realm of democracy and auto engineering, unexpected twists and turns are par for the course.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the 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 Republican Presidential candidate in Utah and Automotive recalls issued by BMW of North America. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
An Ode to Roads and Votes: The Antidote for BMW and Republican Boat Floats

[[ABSTRACT]]
The connection between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America is a perplexing enigma that has baffled scholars and auto enthusiasts alike. In this study, we set out to untangle the knotty relationship between political preferences and vehicular safety lapses. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, we sought to elucidate the potential influence of conservative voting patterns on BMW automotive recalls. Much to our surprise, we discovered a correlation coefficient of 0.8895360 and p < 0.01 for the period spanning 1976 to 2020, indicating a robust association between these seemingly disparate phenomena. In both literal and figurative terms, it appears that Republican support in the Beehive State may indeed have an impact on the wheels of BMW. It's as if voters are clutching onto their political beliefs and holding onto their BMWs – for better or verse!

Who knew that political leanings and automotive malfunctions could be tied together in such a peculiar manner? Our findings not only raise eyebrows but also perform a parallel park into uncharted territory, shedding light on the multifaceted tapestry of societal influence on corporate behaviors. It’s as if we stumbled upon a pothole that led straight to the heart of political and automotive intrigue. This study poignantly illustrates that, much like the road to victory, the road to vehicular safety may also be paved with political inclinations. After all, in the realm of democracy and auto engineering, unexpected twists and turns are par for the course.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The curious correlation between political preferences and vehicular safety has long captured the attention of researchers and enthusiasts alike. Curiously, this connection has surfaced in the context of votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America. As we embark on this journey to unravel the enigma, we find ourselves on a road less traveled, paved with statistical anomalies and unexpected insights.

It is indeed remarkable how seemingly distinct domains of politics and automotive engineering might intertwine. One cannot help but ponder whether there exists a direct causative link or if this association is merely a coincidence, albeit a compelling one. It’s as if the wheels of political preference are driving the gears of automotive fate – a curious confluence of democracy and BMWs, steering us into uncharted territories of sociopolitical influence.

This endeavor is reminiscent of a dad joke – a bit puzzling, somewhat unexpected, and undeniably amusing. Just as a good dad joke catches one off guard, our findings may surprise and engage the reader, offering a fresh perspective on the interplay between political dynamics and corporate conduct. It's as if the unexpected fusion of voting patterns and automotive malfunctions has taken us down a punny road, where the punchline is both surprising and enlightening.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Utah and Automotive recalls issued by BMW of North America. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
An Ode to Roads and Votes: The Antidote for BMW and Republican Boat Floats

[[ABSTRACT]]
The connection between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America is a perplexing enigma that has baffled scholars and auto enthusiasts alike. In this study, we set out to untangle the knotty relationship between political preferences and vehicular safety lapses. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, we sought to elucidate the potential influence of conservative voting patterns on BMW automotive recalls. Much to our surprise, we discovered a correlation coefficient of 0.8895360 and p < 0.01 for the period spanning 1976 to 2020, indicating a robust association between these seemingly disparate phenomena. In both literal and figurative terms, it appears that Republican support in the Beehive State may indeed have an impact on the wheels of BMW. It's as if voters are clutching onto their political beliefs and holding onto their BMWs – for better or verse!

Who knew that political leanings and automotive malfunctions could be tied together in such a peculiar manner? Our findings not only raise eyebrows but also perform a parallel park into uncharted territory, shedding light on the multifaceted tapestry of societal influence on corporate behaviors. It’s as if we stumbled upon a pothole that led straight to the heart of political and automotive intrigue. This study poignantly illustrates that, much like the road to victory, the road to vehicular safety may also be paved with political inclinations. After all, in the realm of democracy and auto engineering, unexpected twists and turns are par for the course.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The curious correlation between political preferences and vehicular safety has long captured the attention of researchers and enthusiasts alike. Curiously, this connection has surfaced in the context of votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America. As we embark on this journey to unravel the enigma, we find ourselves on a road less traveled, paved with statistical anomalies and unexpected insights.
It is indeed remarkable how seemingly distinct domains of politics and automotive engineering might intertwine. One cannot help but ponder whether there exists a direct causative link or if this association is merely a coincidence, albeit a compelling one. It’s as if the wheels of political preference are driving the gears of automotive fate – a curious confluence of democracy and BMWs, steering us into uncharted territories of sociopolitical influence.
This endeavor is reminiscent of a dad joke – a bit puzzling, somewhat unexpected, and undeniably amusing. Just as a good dad joke catches one off guard, our findings may surprise and engage the reader, offering a fresh perspective on the interplay between political dynamics and corporate conduct. It's as if the unexpected fusion of voting patterns and automotive malfunctions has taken us down a punny road, where the punchline is both surprising and enlightening.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Over the years, studies by Smith (2007), Doe (2013), and Jones (2018) have delved into the unusual relationship between political preferences and corporate conduct. The authors find that political leanings often influence consumer behavior and even impact corporate decision-making processes. However, none of these studies have ventured into the peculiar intersection of votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America. It's as if the roads of political discourse and automotive mechanisms have merged into an unexpected roundabout, leading to unexplored destinations of societal influence.

In "The Road Less Traveled," M. Scott Peck emphasizes the significance of venturing into uncharted territories, much like our present endeavor in unraveling the connection between political inclinations and automotive recalls. Our findings, in a similar vein, may lead scholars and enthusiasts down a path replete with unexpected and puzzling insights – a bit like a dad joke that catches one off guard and elicits an amused, albeit perplexed, response. Just as a good dad joke serves as a momentary escape from the ordinary, our research aims to offer a quirky yet thought-provoking diversion into the realm of sociopolitical influence on vehicular safety.

Furthermore, fictional works such as "The Road" by Cormac McCarthy and "Zen and the Art of Motorcycle Maintenance" by Robert M. Pirsig, although unrelated to our specific research, evoke the imagery of movement, journey, and introspection, much like the endeavor at hand. As we navigate through the bylanes of political preferences and corporate conduct, we are reminded that unexpected twists and turns are not exclusive to road trips but also characterize scholarly pursuits into uncharted intellectual territory. It's as if the bookshelves of literature and our research have converged in a literary crossroads, providing us with a multifaceted view of societal dynamics and corporate behavior.

In addition, the animated series "Wacky Races" and the children's show "Thomas & Friends" present engaging narratives revolving around the theme of transportation and adventures on wheels. While these light-hearted productions may appear whimsical and detached from the serious nature of our research, they serve as a reminder that unexpected connections and peculiar correlations can often manifest in the most unexpected of places – much like the perplexing relationship between Republican votes in Utah and BMW automotive recalls that we seek to unravel. It's as if our academic pursuit has transformed into a whimsical rollercoaster ride, where every unexpected twist unearths surprising parallels and delightful revelations.

In summary, our literature review draws inspiration from diverse sources, ranging from scholarly works to fictional narratives and children's shows, underscoring the multifaceted and humorous nature of our investigation. Much like a well-crafted dad joke, our endeavor seeks to entertain, surprise, and leave a lasting impression on scholarly discourse, steering us onto uncharted roads of discovery that promise to be as perplexing as they are enlightening.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Utah and Automotive recalls issued by BMW of North America. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 1976 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]]
An Ode to Roads and Votes: The Antidote for BMW and Republican Boat Floats

[[ABSTRACT]]
The connection between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America is a perplexing enigma that has baffled scholars and auto enthusiasts alike. In this study, we set out to untangle the knotty relationship between political preferences and vehicular safety lapses. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, we sought to elucidate the potential influence of conservative voting patterns on BMW automotive recalls. Much to our surprise, we discovered a correlation coefficient of 0.8895360 and p < 0.01 for the period spanning 1976 to 2020, indicating a robust association between these seemingly disparate phenomena. In both literal and figurative terms, it appears that Republican support in the Beehive State may indeed have an impact on the wheels of BMW. It's as if voters are clutching onto their political beliefs and holding onto their BMWs – for better or verse!

Who knew that political leanings and automotive malfunctions could be tied together in such a peculiar manner? Our findings not only raise eyebrows but also perform a parallel park into uncharted territory, shedding light on the multifaceted tapestry of societal influence on corporate behaviors. It’s as if we stumbled upon a pothole that led straight to the heart of political and automotive intrigue. This study poignantly illustrates that, much like the road to victory, the road to vehicular safety may also be paved with political inclinations. After all, in the realm of democracy and auto engineering, unexpected twists and turns are par for the course.

[[INTRODUCTION]]
The curious correlation between political preferences and vehicular safety has long captured the attention of researchers and enthusiasts alike. Curiously, this connection has surfaced in the context of votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America. As we embark on this journey to unravel the enigma, we find ourselves on a road less traveled, paved with statistical anomalies and unexpected insights.
It is indeed remarkable how seemingly distinct domains of politics and automotive engineering might intertwine. One cannot help but ponder whether there exists a direct causative link or if this association is merely a coincidence, albeit a compelling one. It’s as if the wheels of political preference are driving the gears of automotive fate – a curious confluence of democracy and BMWs, steering us into uncharted territories of sociopolitical influence.
This endeavor is reminiscent of a dad joke – a bit puzzling, somewhat unexpected, and undeniably amusing. Just as a good dad joke catches one off guard, our findings may surprise and engage the reader, offering a fresh perspective on the interplay between political dynamics and corporate conduct. It's as if the unexpected fusion of voting patterns and automotive malfunctions has taken us down a punny road, where the punchline is both surprising and enlightening.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To investigate the perplexing association between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America, we employed a multifaceted research approach. Firstly, data pertaining to Republican presidential candidate votes in Utah from 1976 to 2020 was meticulously sourced from the MIT Election Data and Science Lab. This involved sifting through an extensive array of electoral records, akin to meticulously searching for the proverbial needle in a haystack.

Next, automotive recall information for BMW of North America during the same time frame was extracted from the Harvard Dataverse. This process was akin to navigating a convoluted maze of vehicular data, uncovering hidden recall notices like a skilled detective on the trail of a prolific culprit. It was indeed a journey filled with unexpected twists and turns, not unlike driving down an unfamiliar road with an unreliable GPS system.

Once the relevant data was procured, we conducted a comprehensive analysis utilizing econometric models to establish a quantitative relationship between these ostensibly unrelated variables. The statistical analysis was akin to piecing together a complex jigsaw puzzle, where each statistical metric and regression model offered a part of the solution but required patient assembly.

Moreover, we controlled for various confounding variables such as economic indicators, vehicle registration trends, and political demographics, ensuring that our findings were robust and not merely a product of spurious correlations. This process resembled walking a tightrope, delicately balancing numerous factors to prevent the introduction of bias into our research.

A particularly amusing anecdote from our data collection process involved discovering a correlation between the political inclination of the state and the frequency of recalls for BMWs. It appears that political beliefs and vehicular recalls may indeed be interconnected, much like a well-crafted dad joke that leaves one both puzzled and amused. The unexpected fusion of political leanings and automotive malfunctions in our findings elicited a response that was akin to the jovial surprise of encountering a well-timed dad joke.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Utah and Automotive recalls issued by BMW of North America. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 1976 to 2020, you found a correlation 0.8895360, r-squared of 0.7912742, 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]]
An Ode to Roads and Votes: The Antidote for BMW and Republican Boat Floats

[[ABSTRACT]]
The connection between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America is a perplexing enigma that has baffled scholars and auto enthusiasts alike. In this study, we set out to untangle the knotty relationship between political preferences and vehicular safety lapses. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, we sought to elucidate the potential influence of conservative voting patterns on BMW automotive recalls. Much to our surprise, we discovered a correlation coefficient of 0.8895360 and p < 0.01 for the period spanning 1976 to 2020, indicating a robust association between these seemingly disparate phenomena. In both literal and figurative terms, it appears that Republican support in the Beehive State may indeed have an impact on the wheels of BMW. It's as if voters are clutching onto their political beliefs and holding onto their BMWs – for better or verse!

Who knew that political leanings and automotive malfunctions could be tied together in such a peculiar manner? Our findings not only raise eyebrows but also perform a parallel park into uncharted territory, shedding light on the multifaceted tapestry of societal influence on corporate behaviors. It’s as if we stumbled upon a pothole that led straight to the heart of political and automotive intrigue. This study poignantly illustrates that, much like the road to victory, the road to vehicular safety may also be paved with political inclinations. After all, in the realm of democracy and auto engineering, unexpected twists and turns are par for the course.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The curious correlation between political preferences and vehicular safety has long captured the attention of researchers and enthusiasts alike. Curiously, this connection has surfaced in the context of votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America. As we embark on this journey to unravel the enigma, we find ourselves on a road less traveled, paved with statistical anomalies and unexpected insights.
It is indeed remarkable how seemingly distinct domains of politics and automotive engineering might intertwine. One cannot help but ponder whether there exists a direct causative link or if this association is merely a coincidence, albeit a compelling one. It’s as if the wheels of political preference are driving the gears of automotive fate – a curious confluence of democracy and BMWs, steering us into uncharted territories of sociopolitical influence.
This endeavor is reminiscent of a dad joke – a bit puzzling, somewhat unexpected, and undeniably amusing. Just as a good dad joke catches one off guard, our findings may surprise and engage the reader, offering a fresh perspective on the interplay between political dynamics and corporate conduct. It's as if the unexpected fusion of voting patterns and automotive malfunctions has taken us down a punny road, where the punchline is both surprising and enlightening.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

We found a strong positive correlation (r = 0.8895360) between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America for the time period spanning 1976 to 2020. This correlation was supported by an r-squared value of 0.7912742, indicating that approximately 79.13% of the variation in automotive recalls can be explained by the variation in Republican votes in Utah. With a p-value of less than 0.01, the association between these two variables is considered statistically significant.

It appears that as the Republican support in Utah increased, there was a corresponding increase in the number of automotive recalls issued by BMW of North America. It's as if the political climate was revving up the engines of automotive safety concerns – a real case of politics steering the wheels of vehicular fate.

Fig. 1 shows a scatterplot demonstrating the robust positive relationship between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America. The plot clearly illustrates the upward trajectory of automotive recalls as Republican support in Utah climbs, painting a vivid picture of the interconnectedness of these seemingly unrelated phenomena.

Our findings shed light on the potential influence of political preferences on automotive safety, highlighting the intricate interplay between political dynamics and corporate conduct. It's almost as if every vote cast holds the potential to rev up the engine of automotive safety – a truly unexpected connection between the ballot box and the auto shop.

As we navigate the uncharted territory of this remarkable correlation, we are reminded that, much like the intricate mechanics of a well-crafted pun, the relationship between votes for the Republican candidate in Utah and BMW automotive recalls is both surprising and thought-provoking. Just when one thought they had seen it all, a new unexpected twist emerges, much like the punchline of a clever dad joke.

Our study serves as a testament to the multifaceted tapestry of societal influence on corporate behaviors, providing a compelling reminder that in the complex web of social and economic phenomena, even the most unexpected connections may hold valuable insights. As we ponder these findings, one cannot help but marvel at the unexpected intersections of politics and automotive safety – a dynamic duo turning the wheels of fate in unanticipated ways.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Utah and Automotive recalls issued by BMW of North America. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
An Ode to Roads and Votes: The Antidote for BMW and Republican Boat Floats

[[ABSTRACT]]
The connection between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America is a perplexing enigma that has baffled scholars and auto enthusiasts alike. In this study, we set out to untangle the knotty relationship between political preferences and vehicular safety lapses. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, we sought to elucidate the potential influence of conservative voting patterns on BMW automotive recalls. Much to our surprise, we discovered a correlation coefficient of 0.8895360 and p < 0.01 for the period spanning 1976 to 2020, indicating a robust association between these seemingly disparate phenomena. In both literal and figurative terms, it appears that Republican support in the Beehive State may indeed have an impact on the wheels of BMW. It's as if voters are clutching onto their political beliefs and holding onto their BMWs – for better or verse!

Who knew that political leanings and automotive malfunctions could be tied together in such a peculiar manner? Our findings not only raise eyebrows but also perform a parallel park into uncharted territory, shedding light on the multifaceted tapestry of societal influence on corporate behaviors. It’s as if we stumbled upon a pothole that led straight to the heart of political and automotive intrigue. This study poignantly illustrates that, much like the road to victory, the road to vehicular safety may also be paved with political inclinations. After all, in the realm of democracy and auto engineering, unexpected twists and turns are par for the course.

[[LITERATURE REVIEW]]
Over the years, studies by Smith (2007), Doe (2013), and Jones (2018) have delved into the unusual relationship between political preferences and corporate conduct. The authors find that political leanings often influence consumer behavior and even impact corporate decision-making processes. However, none of these studies have ventured into the peculiar intersection of votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America. It's as if the roads of political discourse and automotive mechanisms have merged into an unexpected roundabout, leading to unexplored destinations of societal influence.
In "The Road Less Traveled," M. Scott Peck emphasizes the significance of venturing into uncharted territories, much like our present endeavor in unraveling the connection between political inclinations and automotive recalls. Our findings, in a similar vein, may lead scholars and enthusiasts down a path replete with unexpected and puzzling insights – a bit like a dad joke that catches one off guard and elicits an amused, albeit perplexed, response. Just as a good dad joke serves as a momentary escape from the ordinary, our research aims to offer a quirky yet thought-provoking diversion into the realm of sociopolitical influence on vehicular safety.
Furthermore, fictional works such as "The Road" by Cormac McCarthy and "Zen and the Art of Motorcycle Maintenance" by Robert M. Pirsig, although unrelated to our specific research, evoke the imagery of movement, journey, and introspection, much like the endeavor at hand. As we navigate through the bylanes of political preferences and corporate conduct, we are reminded that unexpected twists and turns are not exclusive to road trips but also characterize scholarly pursuits into uncharted intellectual territory. It's as if the bookshelves of literature and our research have converged in a literary crossroads, providing us with a multifaceted view of societal dynamics and corporate behavior.
In addition, the animated series "Wacky Races" and the children's show "Thomas & Friends" present engaging narratives revolving around the theme of transportation and adventures on wheels. While these light-hearted productions may appear whimsical and detached from the serious nature of our research, they serve as a reminder that unexpected connections and peculiar correlations can often manifest in the most unexpected of places – much like the perplexing relationship between Republican votes in Utah and BMW automotive recalls that we seek to unravel. It's as if our academic pursuit has transformed into a whimsical rollercoaster ride, where every unexpected twist unearths surprising parallels and delightful revelations.
In summary, our literature review draws inspiration from diverse sources, ranging from scholarly works to fictional narratives and children's shows, underscoring the multifaceted and humorous nature of our investigation. Much like a well-crafted dad joke, our endeavor seeks to entertain, surprise, and leave a lasting impression on scholarly discourse, steering us onto uncharted roads of discovery that promise to be as perplexing as they are enlightening.

[[RESULTS]]
We found a strong positive correlation (r = 0.8895360) between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America for the time period spanning 1976 to 2020. This correlation was supported by an r-squared value of 0.7912742, indicating that approximately 79.13% of the variation in automotive recalls can be explained by the variation in Republican votes in Utah. With a p-value of less than 0.01, the association between these two variables is considered statistically significant.
It appears that as the Republican support in Utah increased, there was a corresponding increase in the number of automotive recalls issued by BMW of North America. It's as if the political climate was revving up the engines of automotive safety concerns – a real case of politics steering the wheels of vehicular fate.
Fig. 1 shows a scatterplot demonstrating the robust positive relationship between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America. The plot clearly illustrates the upward trajectory of automotive recalls as Republican support in Utah climbs, painting a vivid picture of the interconnectedness of these seemingly unrelated phenomena.
Our findings shed light on the potential influence of political preferences on automotive safety, highlighting the intricate interplay between political dynamics and corporate conduct. It's almost as if every vote cast holds the potential to rev up the engine of automotive safety – a truly unexpected connection between the ballot box and the auto shop.
As we navigate the uncharted territory of this remarkable correlation, we are reminded that, much like the intricate mechanics of a well-crafted pun, the relationship between votes for the Republican candidate in Utah and BMW automotive recalls is both surprising and thought-provoking. Just when one thought they had seen it all, a new unexpected twist emerges, much like the punchline of a clever dad joke.
Our study serves as a testament to the multifaceted tapestry of societal influence on corporate behaviors, providing a compelling reminder that in the complex web of social and economic phenomena, even the most unexpected connections may hold valuable insights. As we ponder these findings, one cannot help but marvel at the unexpected intersections of politics and automotive safety – a dynamic duo turning the wheels of fate in unanticipated ways.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]
The strong positive correlation between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America, as evidenced by our findings, lends credence to the notion that political preferences may indeed exert an influence on corporate behaviors in the automotive industry. It's as if political sentiment in Utah has been revving the engine of BMW automotive recalls, providing a real "spark plug" for further investigation into this unexpected connection.

Our results are in line with the prior research by Smith (2007), Doe (2013), and Jones (2018), which suggested that political leanings can impact corporate decision-making processes and consumer behavior. In a similar vein, our study underscores the possibility that political dynamics, specifically votes for the Republican presidential candidate in Utah, may impact automotive safety outcomes, notably in the context of BMW vehicles. The unexpected link we uncovered is akin to stumbling upon a "gear-shift" in the landscape of sociopolitical and corporate interplay.

The robust association between Republican votes in Utah and BMW automotive recalls is not only statistically significant but also conceptually significant, suggesting that there is merit in further exploring the mechanisms and underlying factors driving this unexpected relationship. It's as if each new revelation in our analysis offers an unanticipated "turn of phrase," challenging traditional assumptions and opening the door to thought-provoking inquiries into the intricate dynamics of societal influence on corporate conduct.

The unexpected convergence of political preferences and automotive safety in our study serves as a reminder that, much like a well-timed dad joke, scholarly pursuits can unveil surprising parallels and delightful revelations. Our findings, while initially perplexing, have paved the way for a head-on exploration of the multifaceted and dynamic interplay between political complexities and corporate behaviors. It's as if the road to discovery is brimming with unforeseen detours and delightful surprises, much like a meandering journey through the tapestry of human influence on vehicular fate.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Utah and Automotive recalls issued by BMW of North America. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
An Ode to Roads and Votes: The Antidote for BMW and Republican Boat Floats

[[ABSTRACT]]
The connection between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America is a perplexing enigma that has baffled scholars and auto enthusiasts alike. In this study, we set out to untangle the knotty relationship between political preferences and vehicular safety lapses. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, we sought to elucidate the potential influence of conservative voting patterns on BMW automotive recalls. Much to our surprise, we discovered a correlation coefficient of 0.8895360 and p < 0.01 for the period spanning 1976 to 2020, indicating a robust association between these seemingly disparate phenomena. In both literal and figurative terms, it appears that Republican support in the Beehive State may indeed have an impact on the wheels of BMW. It's as if voters are clutching onto their political beliefs and holding onto their BMWs – for better or verse!

Who knew that political leanings and automotive malfunctions could be tied together in such a peculiar manner? Our findings not only raise eyebrows but also perform a parallel park into uncharted territory, shedding light on the multifaceted tapestry of societal influence on corporate behaviors. It’s as if we stumbled upon a pothole that led straight to the heart of political and automotive intrigue. This study poignantly illustrates that, much like the road to victory, the road to vehicular safety may also be paved with political inclinations. After all, in the realm of democracy and auto engineering, unexpected twists and turns are par for the course.

[[INTRDUCTION]]
The curious correlation between political preferences and vehicular safety has long captured the attention of researchers and enthusiasts alike. Curiously, this connection has surfaced in the context of votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America. As we embark on this journey to unravel the enigma, we find ourselves on a road less traveled, paved with statistical anomalies and unexpected insights.
It is indeed remarkable how seemingly distinct domains of politics and automotive engineering might intertwine. One cannot help but ponder whether there exists a direct causative link or if this association is merely a coincidence, albeit a compelling one. It’s as if the wheels of political preference are driving the gears of automotive fate – a curious confluence of democracy and BMWs, steering us into uncharted territories of sociopolitical influence.
This endeavor is reminiscent of a dad joke – a bit puzzling, somewhat unexpected, and undeniably amusing. Just as a good dad joke catches one off guard, our findings may surprise and engage the reader, offering a fresh perspective on the interplay between political dynamics and corporate conduct. It's as if the unexpected fusion of voting patterns and automotive malfunctions has taken us down a punny road, where the punchline is both surprising and enlightening.

[[RESULTS]]
We found a strong positive correlation (r = 0.8895360) between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America for the time period spanning 1976 to 2020. This correlation was supported by an r-squared value of 0.7912742, indicating that approximately 79.13% of the variation in automotive recalls can be explained by the variation in Republican votes in Utah. With a p-value of less than 0.01, the association between these two variables is considered statistically significant.
It appears that as the Republican support in Utah increased, there was a corresponding increase in the number of automotive recalls issued by BMW of North America. It's as if the political climate was revving up the engines of automotive safety concerns – a real case of politics steering the wheels of vehicular fate.
Fig. 1 shows a scatterplot demonstrating the robust positive relationship between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America. The plot clearly illustrates the upward trajectory of automotive recalls as Republican support in Utah climbs, painting a vivid picture of the interconnectedness of these seemingly unrelated phenomena.
Our findings shed light on the potential influence of political preferences on automotive safety, highlighting the intricate interplay between political dynamics and corporate conduct. It's almost as if every vote cast holds the potential to rev up the engine of automotive safety – a truly unexpected connection between the ballot box and the auto shop.
As we navigate the uncharted territory of this remarkable correlation, we are reminded that, much like the intricate mechanics of a well-crafted pun, the relationship between votes for the Republican candidate in Utah and BMW automotive recalls is both surprising and thought-provoking. Just when one thought they had seen it all, a new unexpected twist emerges, much like the punchline of a clever dad joke.
Our study serves as a testament to the multifaceted tapestry of societal influence on corporate behaviors, providing a compelling reminder that in the complex web of social and economic phenomena, even the most unexpected connections may hold valuable insights. As we ponder these findings, one cannot help but marvel at the unexpected intersections of politics and automotive safety – a dynamic duo turning the wheels of fate in unanticipated ways.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study has illuminated a compelling association between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America. The statistically significant correlation coefficient of 0.8895360 and the high explanatory power of 79.13% underscore the robustness of this unexpected link. It's as if the political landscape is driving a BMW straight into the realm of vehicular safety concerns—a political power play on the road, if you will.

Our findings prompt a reevaluation of the conventional wisdom surrounding the interplay of political preferences and corporate conduct. It’s almost as if every ballot cast holds the potential to rev up the engine of automotive safety—a political twist that leaves us pondering the implications. It's like a dad joke that catches you off guard—the unexpected connection between the ballot box and the auto shop certainly gives new meaning to the phrase “political horsepower.”

Having trudged through the statistical underbrush of this inquiry, we are left with a panoramic view of an uncharted territory—an unexpected intersection where the dynamics of democracy and the mechanics of automotive safety converge in surprising ways. These findings are a glaring red light for those who never considered the political steering of vehicular fate—an eye-opener cloaked in the guise of scholarly investigation. It's as if we've stumbled upon a pothole that led straight to the heart of political and automotive intrigue—a real tire turner, if you will.

For now, we assert that no further investigation in this area is warranted. Our study stands as a monument to the unexpected connections that may lie beneath the ostensibly separate domains of politics and automotive engineering. This paper, much like a well-timed dad joke, offers a surprising twist that leaves us pondering the intricate dance between Republican votes and BMW recalls. After all, in the realm of statistical surprise and sociopolitical horsepower, no more research is needed.


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 An Ode to Roads and Votes: The Antidote for BMW and Republican Boat Floats. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Transport Politics and Cultural Studies


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited An Ode to Roads and Votes: The Antidote for BMW and Republican Boat Floats. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Progressive Infrastructure and Civic Engagement


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 An Ode to Roads and Votes: The Antidote for BMW and Republican Boat Floats with an abstract of The connection between votes for the Republican presidential candidate in Utah and automotive recalls issued by BMW of North America is a perplexing enigma that has baffled scholars and auto enthusiasts alike. In this study, we set out to untangle the knotty relationship between political preferences and vehicular safety lapses. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, we sought to elucidate the potential influence of conservative voting patterns on BMW automotive recalls. Much to our surprise, we discovered a correlation coefficient of 0.8895360 and p < 0.01 for the period spanning 1976 to 2020, indicating a robust association between these seemingly disparate phenomena. In both literal and figurative terms, it appears that Republican support in the Beehive State may indeed have an impact on the wheels of BMW. It's as if voters are clutching onto their political beliefs and holding onto their BMWs – for better or verse!
Who knew that political leanings and automotive malfunctions could be tied together in such a peculiar manner? Our findings not only raise eyebrows but also perform a parallel park into uncharted territory, shedding light on the multifaceted tapestry of societal influence on corporate behaviors. It’s as if we stumbled upon a pothole that led straight to the heart of political and automotive intrigue. This study poignantly illustrates that, much like the road to victory, the road to vehicular safety may also be paved with political inclinations. After all, in the realm of democracy and auto engineering, unexpected twists and turns are par for the course.

ChatGPT:

BMW, Republican votes, Utah, automotive recalls, correlation, conservative voting patterns, Beehive State, political influence, vehicular safety, political leanings, corporate behaviors, societal influence, democracy, auto engineering

*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 Republican Presidential candidate in Utah
Detailed data title: Total votes cast for the Republican Presidential candidate in Utah
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for the Republican Presidential candidate in Utah

Automotive recalls issued by BMW of North America
Detailed data title: Automotive recals issued by BMW of North America
Source: US DOT
See what else correlates with Automotive recalls issued by BMW of North America

Correlation r = 0.8895360 (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 = 0.7912742 (Coefficient of determination)
This means 79.1% of the change in the one variable (i.e., Automotive recalls issued by BMW of North America) is predictable based on the change in the other (i.e., Votes for the Republican Presidential candidate in Utah) over the 12 years from 1976 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.000107. 0.0001073184290148495600000000
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 0.89 in 0.0107% of random cases. Said differently, if you correlated 9,318 random variables Which I absolutely did.
with the same 11 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 11 because we have two variables measured over a period of 12 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.

[ 0.64, 0.97 ] 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.
197619801984198819921996200020042008201220162020
Votes for the Republican Presidential candidate in Utah (Total votes)337908439687469105428442322632361911515096663742596030740600515211865140
Automotive recalls issued by BMW of North America (Recalls)313352111716151736




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. Confounding variable: 2020 is particularly different from the other years on this graph. Confounding variables (like global pandemics) will cause two variables to look connected when in fact a "sneaky third" variable is influencing both of them behind the scenes.
  5. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




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([337908,439687,469105,428442,322632,361911,515096,663742,596030,740600,515211,865140,])
array_2 = np.array([3,1,3,3,5,2,11,17,16,15,17,36,])
array_1_name = "Votes for the Republican Presidential candidate in Utah"
array_2_name = "Automotive recalls issued by BMW of North America"

# 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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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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Correlation ID: 4735 · Black Variable ID: 26037 · Red Variable ID: 1121
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