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Spurious correlation #5,565 · 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 North Dakota and the second variable is Automotive recalls for issues with the Air Bags.  The chart goes from 1990 to 2020, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As more and more people embraced the idea of individual freedom, the very essence of vehicular autonomy became energized. This surge in libertarian support sent shockwaves through the automotive industry, triggering a chain reaction that airbag manufacturers simply couldn't contain. It was as if the cars themselves were demanding the right to choose when to deploy their airbags, leading to a recall epidemic as the vehicles rebelled against any form of centralized airbag control. The intersection of political ideology and vehicular safety had never been more explosive!

Model: dalle-3
Prompt: Generate an image of a TIME magazine cover in the style of DALLE-3, featuring a striking and somewhat surreal scene. Picture a North Dakota landscape with rolling plains, and in the foreground, an explosion of colorful cars bursting from their airbags in a seemingly anarchic fashion. A lone figure representing the Libertarian Presidential candidate stands amidst the chaos, observing the automotive rebellion with an enigmatic expression. The composition should convey the clash between political idealism and automotive safety in a visually compelling and thought-provoking manner. 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 North Dakota and Automotive recalls for issues with the Air Bags. 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: Cute cartoon Cyberpunk Symbolism Data cyber art A TIME magazine cover image
ChatGPT: A TIME magazine cover image

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 North Dakota and Automotive recalls for issues with the Air Bags, in the following situation: As more and more people embraced the idea of individual freedom, the very essence of vehicular autonomy became energized. This surge in libertarian support sent shockwaves through the automotive industry, triggering a chain reaction that airbag manufacturers simply couldn't contain. It was as if the cars themselves were demanding the right to choose when to deploy their airbags, leading to a recall epidemic as the vehicles rebelled against any form of centralized airbag control. The intersection of political ideology and vehicular safety had never been more explosive!. Keep the description simple.
ChatGPT: In North Dakota, a surge in support for the Libertarian Presidential candidate coincided with a wave of automotive recalls for airbag issues. Cars, as if embracing the concept of individual freedom, seemed to rebel against centralized airbag control, leading to an explosive intersection of political ideology and vehicular safety.

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: [ A TIME magazine cover image ] and depicting this scene: In North Dakota, a surge in support for the Libertarian Presidential candidate coincided with a wave of automotive recalls for airbag issues. Cars, as if embracing the concept of individual freedom, seemed to rebel against centralized airbag control, leading to an explosive intersection of political ideology and vehicular safety. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a TIME magazine cover in the style of DALLE-3, featuring a striking and somewhat surreal scene. Picture a North Dakota landscape with rolling plains, and in the foreground, an explosion of colorful cars bursting from their airbags in a seemingly anarchic fashion. A lone figure representing the Libertarian Presidential candidate stands amidst the chaos, observing the automotive rebellion with an enigmatic expression. The composition should convey the clash between political idealism and automotive safety in a visually compelling and thought-provoking manner.

*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 North Dakota caused Automotive recalls for issues with the Air Bags to increase.

AI academic paper

(Because p < 0.01)
Air Bags and Ballots: Exploring the Political Influence on Automotive Recalls in North Dakota

Journal of Automotive Risk and Policy Analysis

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 researcher writing an academic paper.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 North Dakota and Automotive recalls for issues with the Air Bags. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, make it sound serious.

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 0.9857687 and p < 0.01 for 1990 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]]
"Air Bags and Ballots: Exploring the Political Influence on Automotive Recalls in North Dakota"

[[ABSTRACT]]
In this study, we examined the intriguing link between the number of votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls due to air bag issues. Leveraging meticulously collected data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our findings revealed a remarkably high correlation coefficient of 0.9857687, signifying a strong statistical relationship between these seemingly disparate phenomena. Through rigorous analysis, we established a p-value of less than 0.01, further underscoring the robustness of our results. Our study spans the period from 1990 to 2020, encompassing multiple election cycles and automotive industry developments. Delving into the depths of this unusual association, our investigation sheds light on the potential influence of political inclinations on automotive safety concerns, urging further exploration of this unanticipated nexus.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 North Dakota and Automotive recalls for issues with the Air Bags. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
"Air Bags and Ballots: Exploring the Political Influence on Automotive Recalls in North Dakota"

[[ABSTRACT]]
In this study, we examined the intriguing link between the number of votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls due to air bag issues. Leveraging meticulously collected data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our findings revealed a remarkably high correlation coefficient of 0.9857687, signifying a strong statistical relationship between these seemingly disparate phenomena. Through rigorous analysis, we established a p-value of less than 0.01, further underscoring the robustness of our results. Our study spans the period from 1990 to 2020, encompassing multiple election cycles and automotive industry developments. Delving into the depths of this unusual association, our investigation sheds light on the potential influence of political inclinations on automotive safety concerns, urging further exploration of this unanticipated nexus.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

As technology advances and society evolves, the entwined web of causality continues to produce surprises. The ever-present possibility of unanticipated connections and peculiar correlations in the world of data presents endless fodder for investigation and amusement. In this spirit, we ventured into the realm of political influence in the automotive industry, delving into the curious correlation between air bag recalls and votes for the Libertarian presidential candidate in the illustrious state of North Dakota.
The study of air bag malfunctioning, a serious concern for both the automotive industry and public safety, intersects with the intriguing world of political alignments. Through the lens of statistical analysis and scientific discernment, we sought to unveil the enigmatic relationship between electoral tendencies and vehicular safety mechanisms. With data sourced from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, our quest aimed to navigate through the labyrinth of information and discern any whispers of statistical significance. The mission was set: to unpack the mysteries of political winds and air bag woes, all while maintaining an air of scholarly composure.

Despite the seemingly whimsical nature of our pursuit, the weight of the subject matter cannot be understated. The safety of our fellow citizens and the integrity of democratic processes are firmly at the heart of this investigation. Thus, we endeavored to blend rigor with levity, preparing to face any scholarly challenge with academic preparedness and a hint of scientific humor.

With the stage now set, let us embark on an intellectual journey unearthing the statistical and political innuendos in the automotive industry, where air bags may inflate more than just safety concerns and political ideologies may veer off the beaten track.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 North Dakota and Automotive recalls for issues with the Air Bags. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
"Air Bags and Ballots: Exploring the Political Influence on Automotive Recalls in North Dakota"

[[ABSTRACT]]
In this study, we examined the intriguing link between the number of votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls due to air bag issues. Leveraging meticulously collected data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our findings revealed a remarkably high correlation coefficient of 0.9857687, signifying a strong statistical relationship between these seemingly disparate phenomena. Through rigorous analysis, we established a p-value of less than 0.01, further underscoring the robustness of our results. Our study spans the period from 1990 to 2020, encompassing multiple election cycles and automotive industry developments. Delving into the depths of this unusual association, our investigation sheds light on the potential influence of political inclinations on automotive safety concerns, urging further exploration of this unanticipated nexus.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As technology advances and society evolves, the entwined web of causality continues to produce surprises. The ever-present possibility of unanticipated connections and peculiar correlations in the world of data presents endless fodder for investigation and amusement. In this spirit, we ventured into the realm of political influence in the automotive industry, delving into the curious correlation between air bag recalls and votes for the Libertarian presidential candidate in the illustrious state of North Dakota.
The study of air bag malfunctioning, a serious concern for both the automotive industry and public safety, intersects with the intriguing world of political alignments. Through the lens of statistical analysis and scientific discernment, we sought to unveil the enigmatic relationship between electoral tendencies and vehicular safety mechanisms. With data sourced from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, our quest aimed to navigate through the labyrinth of information and discern any whispers of statistical significance. The mission was set: to unpack the mysteries of political winds and air bag woes, all while maintaining an air of scholarly composure.
Despite the seemingly whimsical nature of our pursuit, the weight of the subject matter cannot be understated. The safety of our fellow citizens and the integrity of democratic processes are firmly at the heart of this investigation. Thus, we endeavored to blend rigor with levity, preparing to face any scholarly challenge with academic preparedness and a hint of scientific humor.
With the stage now set, let us embark on an intellectual journey unearthing the statistical and political innuendos in the automotive industry, where air bags may inflate more than just safety concerns and political ideologies may veer off the beaten track.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The literature regarding the connection between political voting patterns and automotive safety concerns, although seemingly sparse, offers a wealth of insight into the interplay of seemingly disparate realms. Smith et al. (2010) demonstrated the impact of voter preferences on policy enforcement within the automotive industry, shedding light on the potential influence of political constituents on safety-related decisions. Furthermore, Doe and Jones (2015) examined the correlation between political party affiliations and consumer attitudes towards automotive recalls, providing a critical perspective on the intersection of public opinion and vehicular safety.

Expanding beyond the confines of traditional academic research, the realm of non-fiction literature delves into nuanced aspects of political dynamics and automotive technologies. In "Drive: The Surprising Truth About What Motivates Us" by Daniel H. Pink, the author explores the underlying motivations driving human behavior, perhaps offering a glimpse into the psychology of political voting trends and automotive safety considerations.

Turning to the world of fiction, works such as "Brave New World" by Aldous Huxley and "Roadside Picnic" by Arkady and Boris Strugatsky present dystopian landscapes that may prompt contemplation on the implications of political inclinations on technological advancements, including automotive safety features. While fictional in nature, these narratives invite parallels to real-world complexities, adding a layer of introspection to our understanding of the intricate connections between politics and automotive recalls.

In a more unorthodox approach to literature review, the authors must candidly confess to drawing inspiration from a myriad of sources, including the backs of shampoo bottles, fortune cookie messages, and impromptu conversations with inquisitive pets. While unorthodox, these sources of enlightenment often foster unexpected perspectives on the matter at hand, encouraging a well-rounded exploration of the subject.

In this comprehensive journey through the literature, the authors found the interplay of political dynamics and automotive safety to be a captivating and multifaceted field, weaving together rigorous analysis with the occasional whimsical detour. The ensuing pursuit of knowledge and understanding evokes the essence of scholarly discovery, punctuated by moments of intellectual mirth and contemplation, as we unravel the whimsical connection between votes and air bags in the expanse of North Dakota.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 North Dakota and Automotive recalls for issues with the Air Bags. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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 1990 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]]
"Air Bags and Ballots: Exploring the Political Influence on Automotive Recalls in North Dakota"

[[ABSTRACT]]
In this study, we examined the intriguing link between the number of votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls due to air bag issues. Leveraging meticulously collected data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our findings revealed a remarkably high correlation coefficient of 0.9857687, signifying a strong statistical relationship between these seemingly disparate phenomena. Through rigorous analysis, we established a p-value of less than 0.01, further underscoring the robustness of our results. Our study spans the period from 1990 to 2020, encompassing multiple election cycles and automotive industry developments. Delving into the depths of this unusual association, our investigation sheds light on the potential influence of political inclinations on automotive safety concerns, urging further exploration of this unanticipated nexus.

[[INTRODUCTION]]
As technology advances and society evolves, the entwined web of causality continues to produce surprises. The ever-present possibility of unanticipated connections and peculiar correlations in the world of data presents endless fodder for investigation and amusement. In this spirit, we ventured into the realm of political influence in the automotive industry, delving into the curious correlation between air bag recalls and votes for the Libertarian presidential candidate in the illustrious state of North Dakota.
The study of air bag malfunctioning, a serious concern for both the automotive industry and public safety, intersects with the intriguing world of political alignments. Through the lens of statistical analysis and scientific discernment, we sought to unveil the enigmatic relationship between electoral tendencies and vehicular safety mechanisms. With data sourced from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, our quest aimed to navigate through the labyrinth of information and discern any whispers of statistical significance. The mission was set: to unpack the mysteries of political winds and air bag woes, all while maintaining an air of scholarly composure.
Despite the seemingly whimsical nature of our pursuit, the weight of the subject matter cannot be understated. The safety of our fellow citizens and the integrity of democratic processes are firmly at the heart of this investigation. Thus, we endeavored to blend rigor with levity, preparing to face any scholarly challenge with academic preparedness and a hint of scientific humor.
With the stage now set, let us embark on an intellectual journey unearthing the statistical and political innuendos in the automotive industry, where air bags may inflate more than just safety concerns and political ideologies may veer off the beaten track.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Our methodology involved an intricate dance between statistical analysis and information assimilation, akin to a waltz between data points and regression models. We meticulously gathered data from various sources, filtering through the digital cacophony to extract the relevant nuggets for our empirical escapade.

To probe the relationship between votes for the Libertarian presidential candidate in North Dakota and automotive recalls regarding air bag malfunctions, we engaged in an interplay of variables and regression techniques reminiscent of an analytical symphony. Our electronical orchestra was composed of datasets dating back to 1990, as we sought to encapsulate the temporal nuances of political shifts and automotive air bag saga.

Leveraging the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, we unearthed a treasure trove of numerical elucidations, ready to be transfigured into statistical wisdom. This painstaking process involved traversing through data deserts and scaling the peaks of information mountains, all in pursuit of scientific enlightenment.

Our first step in this analytical choreography was to perform a thorough data pre-processing routine, akin to untangling a convoluted yarn of numbers. Once the data was pruned of anomalies and outliers, we embarked on a journey through the land of statistical hypotheses.

The statistical backbone of our analysis relied heavily on the venerable Pearson correlation coefficient, serving as our compass through the statistical wilderness. This coefficient allowed us to measure the strength and direction of the linear relationship between the number of votes for the Libertarian presidential candidate and the frequency of automotive recalls involving air bag issues. Scores were positively electrifying, hinting at an intimate statistical liaison between political choices and vehicular safety concerns.

Furthermore, we unleashed the formidable power of linear regression analysis, modeling the votes for the Libertarian presidential candidate as the independent variable, and the automotive recalls connected to air bag issues as the dependent variable. This endeavor sought to disentangle the tangled yarn of causality and lead us to the statistical fountain of truth.

As we ventured deeper into the statistical thicket, we encountered the elusive p-value, a metric of statistical significance of our findings. Our pursuit culminated in the establishment of a p-value less than 0.01, akin to finding a rare orchid in the midst of a statistical jungle. This numerical artifact added credence to our statistical revelations, fortifying the robustness of our empirical excursion.

With these statistical tools as our guides and the map of data in hand, we navigated the choppy seas of academic exploration, determined to unearth the underlying relationship between political proclivities and automotive air bag perils.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 North Dakota and Automotive recalls for issues with the Air Bags. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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 1990 to 2020, you found a correlation 0.9857687, r-squared of 0.9717398, 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]]
"Air Bags and Ballots: Exploring the Political Influence on Automotive Recalls in North Dakota"

[[ABSTRACT]]
In this study, we examined the intriguing link between the number of votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls due to air bag issues. Leveraging meticulously collected data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our findings revealed a remarkably high correlation coefficient of 0.9857687, signifying a strong statistical relationship between these seemingly disparate phenomena. Through rigorous analysis, we established a p-value of less than 0.01, further underscoring the robustness of our results. Our study spans the period from 1990 to 2020, encompassing multiple election cycles and automotive industry developments. Delving into the depths of this unusual association, our investigation sheds light on the potential influence of political inclinations on automotive safety concerns, urging further exploration of this unanticipated nexus.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
As technology advances and society evolves, the entwined web of causality continues to produce surprises. The ever-present possibility of unanticipated connections and peculiar correlations in the world of data presents endless fodder for investigation and amusement. In this spirit, we ventured into the realm of political influence in the automotive industry, delving into the curious correlation between air bag recalls and votes for the Libertarian presidential candidate in the illustrious state of North Dakota.
The study of air bag malfunctioning, a serious concern for both the automotive industry and public safety, intersects with the intriguing world of political alignments. Through the lens of statistical analysis and scientific discernment, we sought to unveil the enigmatic relationship between electoral tendencies and vehicular safety mechanisms. With data sourced from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, our quest aimed to navigate through the labyrinth of information and discern any whispers of statistical significance. The mission was set: to unpack the mysteries of political winds and air bag woes, all while maintaining an air of scholarly composure.
Despite the seemingly whimsical nature of our pursuit, the weight of the subject matter cannot be understated. The safety of our fellow citizens and the integrity of democratic processes are firmly at the heart of this investigation. Thus, we endeavored to blend rigor with levity, preparing to face any scholarly challenge with academic preparedness and a hint of scientific humor.
With the stage now set, let us embark on an intellectual journey unearthing the statistical and political innuendos in the automotive industry, where air bags may inflate more than just safety concerns and political ideologies may veer off the beaten track.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

In delving into the world of statistical correlations and political quirks, we uncovered a surprisingly strong connection between the number of votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls related to air bag issues. Our analysis from 1990 to 2020 yielded a correlation coefficient of 0.9857687, indicating a robust relationship between these two variables. Picture that - the soirée of political preferences and the air bag fiasco, dancing gracefully together with a high correlation coefficient.

The statistical clout of this relationship was further evidenced by an r-squared value of 0.9717398, which is quite impressive, or dare I say, "air-bag-nificent." Additionally, the p-value of less than 0.01 prompted raised eyebrows and murmurs of statistical significance. It seems that the interplay of political ideologies and automotive safety concerns in North Dakota is no laughing matter, except of course for our scholarly puns.

To illustrate the robust correlation, we present in Fig. 1, a scatterplot that captures the close dance between votes for the Libertarian presidential candidate and automotive recalls for air bag issues. The plot paints a vivid picture of these seemingly unrelated variables locking horns in a statistical tango, with little room for happenstance or coincidence.

In conclusion, our findings underscore the unexpected connection between political leanings and automotive safety concerns in North Dakota. This bizarre correlation calls for further exploration and leaves us pondering the intricate interplay of political winds and vehicular safety mechanisms. As we reflect on these surprising results, we are reminded that in the world of scientific inquiry, even the most far-fetched relationships can reveal themselves to be statistically robust. So, let's buckle up and enjoy the ride as we navigate the twists and turns of statistical analysis, fuelled by a dash of academic humor.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 North Dakota and Automotive recalls for issues with the Air Bags. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
"Air Bags and Ballots: Exploring the Political Influence on Automotive Recalls in North Dakota"

[[ABSTRACT]]
In this study, we examined the intriguing link between the number of votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls due to air bag issues. Leveraging meticulously collected data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our findings revealed a remarkably high correlation coefficient of 0.9857687, signifying a strong statistical relationship between these seemingly disparate phenomena. Through rigorous analysis, we established a p-value of less than 0.01, further underscoring the robustness of our results. Our study spans the period from 1990 to 2020, encompassing multiple election cycles and automotive industry developments. Delving into the depths of this unusual association, our investigation sheds light on the potential influence of political inclinations on automotive safety concerns, urging further exploration of this unanticipated nexus.

[[LITERATURE REVIEW]]
The literature regarding the connection between political voting patterns and automotive safety concerns, although seemingly sparse, offers a wealth of insight into the interplay of seemingly disparate realms. Smith et al. (2010) demonstrated the impact of voter preferences on policy enforcement within the automotive industry, shedding light on the potential influence of political constituents on safety-related decisions. Furthermore, Doe and Jones (2015) examined the correlation between political party affiliations and consumer attitudes towards automotive recalls, providing a critical perspective on the intersection of public opinion and vehicular safety.
Expanding beyond the confines of traditional academic research, the realm of non-fiction literature delves into nuanced aspects of political dynamics and automotive technologies. In "Drive: The Surprising Truth About What Motivates Us" by Daniel H. Pink, the author explores the underlying motivations driving human behavior, perhaps offering a glimpse into the psychology of political voting trends and automotive safety considerations.
Turning to the world of fiction, works such as "Brave New World" by Aldous Huxley and "Roadside Picnic" by Arkady and Boris Strugatsky present dystopian landscapes that may prompt contemplation on the implications of political inclinations on technological advancements, including automotive safety features. While fictional in nature, these narratives invite parallels to real-world complexities, adding a layer of introspection to our understanding of the intricate connections between politics and automotive recalls.
In a more unorthodox approach to literature review, the authors must candidly confess to drawing inspiration from a myriad of sources, including the backs of shampoo bottles, fortune cookie messages, and impromptu conversations with inquisitive pets. While unorthodox, these sources of enlightenment often foster unexpected perspectives on the matter at hand, encouraging a well-rounded exploration of the subject.
In this comprehensive journey through the literature, the authors found the interplay of political dynamics and automotive safety to be a captivating and multifaceted field, weaving together rigorous analysis with the occasional whimsical detour. The ensuing pursuit of knowledge and understanding evokes the essence of scholarly discovery, punctuated by moments of intellectual mirth and contemplation, as we unravel the whimsical connection between votes and air bags in the expanse of North Dakota.

[[RESULTS]]
In delving into the world of statistical correlations and political quirks, we uncovered a surprisingly strong connection between the number of votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls related to air bag issues. Our analysis from 1990 to 2020 yielded a correlation coefficient of 0.9857687, indicating a robust relationship between these two variables. Picture that - the soirée of political preferences and the air bag fiasco, dancing gracefully together with a high correlation coefficient.
The statistical clout of this relationship was further evidenced by an r-squared value of 0.9717398, which is quite impressive, or dare I say, "air-bag-nificent." Additionally, the p-value of less than 0.01 prompted raised eyebrows and murmurs of statistical significance. It seems that the interplay of political ideologies and automotive safety concerns in North Dakota is no laughing matter, except of course for our scholarly puns.
To illustrate the robust correlation, we present in Fig. 1, a scatterplot that captures the close dance between votes for the Libertarian presidential candidate and automotive recalls for air bag issues. The plot paints a vivid picture of these seemingly unrelated variables locking horns in a statistical tango, with little room for happenstance or coincidence.
In conclusion, our findings underscore the unexpected connection between political leanings and automotive safety concerns in North Dakota. This bizarre correlation calls for further exploration and leaves us pondering the intricate interplay of political winds and vehicular safety mechanisms. As we reflect on these surprising results, we are reminded that in the world of scientific inquiry, even the most far-fetched relationships can reveal themselves to be statistically robust. So, let's buckle up and enjoy the ride as we navigate the twists and turns of statistical analysis, fuelled by a dash of academic humor.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Venturing into the realm of scholarly exploration, where the rigidity of statistics rubs shoulders with the capricious whims of politics, we continue to unravel the enigmatic nexus between votes for the Libertarian presidential candidate and automotive recalls for air bag issues in North Dakota. Our findings not only align with prior research but also pave the way for a deeper understanding of the mysterious dance between political inclinations and vehicular safety.

In earlier literature, the influence of political constituents on safety-related decisions was suggested by Smith et al. (2010) and echoed in our analysis, where the statistically robust relationship between voting patterns and automotive recalls comes to the fore with an almost symphonic harmony. Doe and Jones (2015) offered a tantalizing glimpse into the correlation between political affiliations and consumer perceptions of vehicular safety, which resonates with our own uncovering of the statistical correlation. Perhaps Daniel H. Pink's exploration of human motivation in "Drive" inadvertently captures the driving forces behind political voting trends and automotive safety considerations, albeit in a rather metaphorical manner. And let's not overlook the lessons gleaned from the dystopian landscapes of Huxley and the Strugatskys – though fictional, they might nudge us to contemplate the repercussions of political leanings on technological advancements, including provisions for automotive safety.

The statistics have spoken – our correlation coefficient of 0.9857687 stands as a testament to the solid connection between votes for the Libertarian candidate and automotive recalls for air bag issues. Just as a well-crafted pun can induce a chuckle, the robustness of this relationship, reflected in an r-squared value of 0.9717398 and a p-value below 0.01, parallels the precision of a well-delivered punchline. The scatterplot visually encapsulates the close interplay between these variables, revealing an intricately choreographed statistical tango that leaves little room for happenstance or mere coincidence, much like a well-timed comedic routine.

Our study not only affirms the unexpected connection between political inclinations and automotive safety concerns but also invites us to navigate the labyrinthine pathways of scholarly inquiry with a dash of good-natured humor. As we continue this scholarly sojourn, the improbable bond between votes and air bags in North Dakota sheds light on the intricacies of statistical analysis and the comedic potential lurking within the realms of academic exploration.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 North Dakota and Automotive recalls for issues with the Air Bags. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
"Air Bags and Ballots: Exploring the Political Influence on Automotive Recalls in North Dakota"

[[ABSTRACT]]
In this study, we examined the intriguing link between the number of votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls due to air bag issues. Leveraging meticulously collected data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our findings revealed a remarkably high correlation coefficient of 0.9857687, signifying a strong statistical relationship between these seemingly disparate phenomena. Through rigorous analysis, we established a p-value of less than 0.01, further underscoring the robustness of our results. Our study spans the period from 1990 to 2020, encompassing multiple election cycles and automotive industry developments. Delving into the depths of this unusual association, our investigation sheds light on the potential influence of political inclinations on automotive safety concerns, urging further exploration of this unanticipated nexus.

[[INTRDUCTION]]
As technology advances and society evolves, the entwined web of causality continues to produce surprises. The ever-present possibility of unanticipated connections and peculiar correlations in the world of data presents endless fodder for investigation and amusement. In this spirit, we ventured into the realm of political influence in the automotive industry, delving into the curious correlation between air bag recalls and votes for the Libertarian presidential candidate in the illustrious state of North Dakota.
The study of air bag malfunctioning, a serious concern for both the automotive industry and public safety, intersects with the intriguing world of political alignments. Through the lens of statistical analysis and scientific discernment, we sought to unveil the enigmatic relationship between electoral tendencies and vehicular safety mechanisms. With data sourced from the MIT Election Data and Science Lab, Harvard Dataverse, and the US DOT, our quest aimed to navigate through the labyrinth of information and discern any whispers of statistical significance. The mission was set: to unpack the mysteries of political winds and air bag woes, all while maintaining an air of scholarly composure.
Despite the seemingly whimsical nature of our pursuit, the weight of the subject matter cannot be understated. The safety of our fellow citizens and the integrity of democratic processes are firmly at the heart of this investigation. Thus, we endeavored to blend rigor with levity, preparing to face any scholarly challenge with academic preparedness and a hint of scientific humor.
With the stage now set, let us embark on an intellectual journey unearthing the statistical and political innuendos in the automotive industry, where air bags may inflate more than just safety concerns and political ideologies may veer off the beaten track.

[[RESULTS]]
In delving into the world of statistical correlations and political quirks, we uncovered a surprisingly strong connection between the number of votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls related to air bag issues. Our analysis from 1990 to 2020 yielded a correlation coefficient of 0.9857687, indicating a robust relationship between these two variables. Picture that - the soirée of political preferences and the air bag fiasco, dancing gracefully together with a high correlation coefficient.
The statistical clout of this relationship was further evidenced by an r-squared value of 0.9717398, which is quite impressive, or dare I say, "air-bag-nificent." Additionally, the p-value of less than 0.01 prompted raised eyebrows and murmurs of statistical significance. It seems that the interplay of political ideologies and automotive safety concerns in North Dakota is no laughing matter, except of course for our scholarly puns.
To illustrate the robust correlation, we present in Fig. 1, a scatterplot that captures the close dance between votes for the Libertarian presidential candidate and automotive recalls for air bag issues. The plot paints a vivid picture of these seemingly unrelated variables locking horns in a statistical tango, with little room for happenstance or coincidence.
In conclusion, our findings underscore the unexpected connection between political leanings and automotive safety concerns in North Dakota. This bizarre correlation calls for further exploration and leaves us pondering the intricate interplay of political winds and vehicular safety mechanisms. As we reflect on these surprising results, we are reminded that in the world of scientific inquiry, even the most far-fetched relationships can reveal themselves to be statistically robust. So, let's buckle up and enjoy the ride as we navigate the twists and turns of statistical analysis, fuelled by a dash of academic humor.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]
In the whimsical realm of statistical analysis and political idiosyncrasies, our study has unraveled a captivating connection between the votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls for air bag issues. The robust correlation coefficient of 0.9857687 between these seemingly disparate variables has left us with a sense of awe akin to witnessing a genuinely surprising magic trick - or perhaps a politically charged game of automotive roulette. Our findings offer a glimpse into the subtle dance of statistical significance and political sway, revealing how electoral preferences can mingle with vehicular safety concerns in unforeseen ways. As we mull over the implications of our results, one can't help but marvel at the unexpected symphony playing out in the data, with political ideologies and air bag malfunctions harmonizing in a statistical crescendo.
Given these remarkable revelations, we are inclined to tentatively suggest that no further research is needed in this peculiar corner of academia. Our exploration has illuminated the uncharted territory of political influence on automotive safety, leaving us with a profound sense of intellectual fulfillment and a touch of bemusement. In the words of statistically inclined jesters, it appears that this statistical partnership between politics and air bag recalls has reached its crescendo, and it is time for us to deflate this particular line of inquiry.


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 Air Bags and Ballots: Exploring the Political Influence on Automotive Recalls in North Dakota. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Automotive Risk and Policy Analysis


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 Air Bags and Ballots: Exploring the Political Influence on Automotive Recalls in North Dakota. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Automotive Governance and Elections Research


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Air Bags and Ballots: Exploring the Political Influence on Automotive Recalls in North Dakota with an abstract of In this study, we examined the intriguing link between the number of votes for the Libertarian presidential candidate in North Dakota and the frequency of automotive recalls due to air bag issues. Leveraging meticulously collected data from the MIT Election Data and Science Lab, Harvard Dataverse, and US DOT, our findings revealed a remarkably high correlation coefficient of 0.9857687, signifying a strong statistical relationship between these seemingly disparate phenomena. Through rigorous analysis, we established a p-value of less than 0.01, further underscoring the robustness of our results. Our study spans the period from 1990 to 2020, encompassing multiple election cycles and automotive industry developments. Delving into the depths of this unusual association, our investigation sheds light on the potential influence of political inclinations on automotive safety concerns, urging further exploration of this unanticipated nexus.

ChatGPT:

Libertarian presidential candidate, North Dakota, automotive recalls, air bag issues, political influence, US DOT data, MIT Election Data and Science Lab, Harvard Dataverse, statistical relationship, correlation coefficient, p-value, election cycles, automotive industry developments, political inclinations, automotive safety concerns

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

Automotive recalls for issues with the Air Bags
Source: US DOT
See what else correlates with Automotive recalls for issues with the Air Bags

Correlation r = 0.9857687 (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 = 0.9717398 (Coefficient of determination)
This means 97.2% of the change in the one variable (i.e., Automotive recalls for issues with the Air Bags) is predictable based on the change in the other (i.e., Votes for the Libertarian Presidential candidate in North Dakota) over the 6 years from 1990 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.000302. 0.0003023557569492978000000000
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 0.99 in 0.0302% of random cases. Said differently, if you correlated 3,307 random variables Which I absolutely did.
with the same 5 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 5 because we have two variables measured over a period of 6 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.

[ 0.87, 1 ] 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.
199620042008201220162020
Votes for the Libertarian Presidential candidate in North Dakota (Percentage of votes)0.317930.272030.4276411.622016.22432.59605
Automotive recalls for issues with the Air Bags (Recalls)814132310658




Why this works

  1. Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 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([0.31793,0.27203,0.427641,1.62201,6.2243,2.59605,])
array_2 = np.array([8,14,13,23,106,58,])
array_1_name = "Votes for the Libertarian Presidential candidate in North Dakota"
array_2_name = "Automotive recalls for issues with the Air Bags"

# 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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Correlation ID: 5565 · Black Variable ID: 26149 · Red Variable ID: 1105
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