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Spurious correlation #4,317 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Annual US household spending on new cars and the second variable is Votes for Democratic Senators in Florida.  The chart goes from 2000 to 2018, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As household spending on new cars rises, more Floridians experience the joy of vehicle ownership. This leads to an increase in car-related conversations and camaraderie, bringing people together to discuss common interests, including politics. The heightened enthusiasm for cars somehow translates to a surge in support for Democratic Senatorial candidates, as if the rev of a Democratic engine resonates with the newly purchased cars, creating a unique electoral alignment fueled by automotive vibes.

Model: dalle-3
Prompt: Prompt: [ A photo-realistic image ] Create a scene of a vibrant neighborhood block party in Florida, where sleek new cars are on display in the driveways, catching the gleaming sunlight. Families and neighbors are gathered around, engrossed in lively conversations about the latest car models and features. Amidst the cheerful atmosphere, a group of neighbors are seen huddling together, discussing politics, including the upcoming Senate elections. The shared love for cars appears to have ignited an unexpected surge in support for Democratic Senatorial candidates, as if the enthusiasm for the vehicles has infused the community with a new sense of political alignment. Capture the joyful ambiance and the unique intersection of car admiration and political engagement. 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: Annual US household spending on new cars and Democrat votes for Senators in Florida. 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: Whimsical illustration Pop art Voxel art A photo-realistic image inspired by bauhaus
ChatGPT: A photo-realistic 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 Annual US household spending on new cars and Democrat votes for Senators in Florida, in the following situation: As household spending on new cars rises, more Floridians experience the joy of vehicle ownership. This leads to an increase in car-related conversations and camaraderie, bringing people together to discuss common interests, including politics. The heightened enthusiasm for cars somehow translates to a surge in support for Democratic Senatorial candidates, as if the rev of a Democratic engine resonates with the newly purchased cars, creating a unique electoral alignment fueled by automotive vibes.. Keep the description simple.
ChatGPT: A neighborhood block party is in full swing in Florida, with new cars shining in the driveways and families gathered around, admiring the sleek vehicles. People are engaged in lively discussions about the latest car models and features. Amidst the laughter and chatter, a group of neighbors huddle together, excitedly discussing politics, including the upcoming Senate elections. The joyful ambiance and shared love for cars seem to fuel a surge in support for Democratic Senatorial candidates, as if the enthusiasm for the new cars has sparked an unexpected alignment in political preferences.

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 photo-realistic image ] and depicting this scene: A neighborhood block party is in full swing in Florida, with new cars shining in the driveways and families gathered around, admiring the sleek vehicles. People are engaged in lively discussions about the latest car models and features. Amidst the laughter and chatter, a group of neighbors huddle together, excitedly discussing politics, including the upcoming Senate elections. The joyful ambiance and shared love for cars seem to fuel a surge in support for Democratic Senatorial candidates, as if the enthusiasm for the new cars has sparked an unexpected alignment in political preferences. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: [ A photo-realistic image ] Create a scene of a vibrant neighborhood block party in Florida, where sleek new cars are on display in the driveways, catching the gleaming sunlight. Families and neighbors are gathered around, engrossed in lively conversations about the latest car models and features. Amidst the cheerful atmosphere, a group of neighbors are seen huddling together, discussing politics, including the upcoming Senate elections. The shared love for cars appears to have ignited an unexpected surge in support for Democratic Senatorial candidates, as if the enthusiasm for the vehicles has infused the community with a new sense of political alignment. Capture the joyful ambiance and the unique intersection of car admiration and political engagement.

*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 Annual US household spending on new cars caused Democrat votes for Senators in Florida to increase.

AI academic paper

(Because p < 0.01)
Driving Votes: The Correlation Between New Car Spending and Democrat Senatorial Support in Florida

Journal of Political Consumption and Behavior

Jan 2024

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




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Annual US household spending on new cars and Democrat votes for Senators in Florida. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

Your research team used data from Bureau of Labor Statistics and MIT Election Data and Science Lab, Harvard Dataverse to assess this nagging question. You found a correlation coefficient of 0.8810923 and p < 0.01 for 2000 to 2018.

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]]
Driving Votes: The Correlation Between New Car Spending and Democrat Senatorial Support in Florida

[[ABSTRACT]]
This study sets out to investigate the relationship between annual US household spending on new cars and Democrat votes for Senators in Florida. Leveraging data from the Bureau of Labor Statistics and the MIT Election Data and Science Lab, Harvard Dataverse, we embarked on this journey into the intersection of economic choices and political preferences. Through rigorous statistical analysis, we discovered a significant correlation between the two aforementioned variables. Our findings revealed a robust correlation coefficient of 0.8810923 and a p-value of less than 0.01 for the years spanning from 2000 to 2018.

To put it succinctly, our research uncovered a clear connection between the amount of money spent on new automobiles by American households and their inclination to support democratic candidates in Senatorial elections in the state of Florida. Perhaps it could be said that "when it comes to choosing a new car, it seems that Floridian households are also choosing their Senators."

In conclusion, our results imply not only a link between consumer behavior and political ideology, but also highlight the need for further investigation into the driving forces behind this peculiar correlation. It is evident that studying the connection between car spending and voting behavior can provide valuable insights into the broader interplay of economics and politics. After all, one could posit that "analyzing car purchases in relation to political choices may unlock the drive behind democratic support."


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Annual US household spending on new cars and Democrat votes for Senators in Florida. 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]]
Driving Votes: The Correlation Between New Car Spending and Democrat Senatorial Support in Florida

[[ABSTRACT]]
This study sets out to investigate the relationship between annual US household spending on new cars and Democrat votes for Senators in Florida. Leveraging data from the Bureau of Labor Statistics and the MIT Election Data and Science Lab, Harvard Dataverse, we embarked on this journey into the intersection of economic choices and political preferences. Through rigorous statistical analysis, we discovered a significant correlation between the two aforementioned variables. Our findings revealed a robust correlation coefficient of 0.8810923 and a p-value of less than 0.01 for the years spanning from 2000 to 2018.

To put it succinctly, our research uncovered a clear connection between the amount of money spent on new automobiles by American households and their inclination to support democratic candidates in Senatorial elections in the state of Florida. Perhaps it could be said that "when it comes to choosing a new car, it seems that Floridian households are also choosing their Senators."

In conclusion, our results imply not only a link between consumer behavior and political ideology, but also highlight the need for further investigation into the driving forces behind this peculiar correlation. It is evident that studying the connection between car spending and voting behavior can provide valuable insights into the broader interplay of economics and politics. After all, one could posit that "analyzing car purchases in relation to political choices may unlock the drive behind democratic support."

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

In the complex world of electoral politics, a multitude of factors, from socioeconomic status to ideological beliefs, influence voter behavior. Utilizing statistical analysis, this study endeavors to uncover the connection between annual US household spending on new cars and Democrat votes for Senators in Florida. This unconventional pairing of economic expenditure and political preference is not only intriguing but also has the potential to shed light on the intricate motivations behind voter decision-making.

As the saying goes, "When it comes to elections and cars, it seems that Floridian households are driving a point home."

A substantial body of research has explored the intricate relationship between economic choices and political affiliations. However, the specific linkage between new car spending and Senatorial support for the Democratic party in Florida remains largely unexplored. This study seeks to fill this void in the literature, delving into the intriguing intersection of consumer behavior and electoral outcomes.

It is often joked that in politics, just like driving a new car, one should not be in a hurry to change the direction.

The correlation between consumer spending and political leanings has captivated scholars and armchair pundits alike. By focusing on the unique context of Florida and the specific variable of new car spending, this study aims to contribute a distinctive perspective to the ongoing discourse surrounding the intertwined realms of economics and politics.

As the research unfolds, it becomes increasingly clear that in the grand scheme of democracies and automobiles, every aspect holds a key to understanding the bigger picture.

Stay tuned for a journey that not only unveils statistical insights but also offers a fresh perspective on the amalgamation of consumer habits and political inclinations. Let's buckle up and embark on a thrilling ride through the realm of statistical analysis and political intrigue.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Annual US household spending on new cars and Democrat votes for Senators in Florida. 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 a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
Driving Votes: The Correlation Between New Car Spending and Democrat Senatorial Support in Florida

[[ABSTRACT]]
This study sets out to investigate the relationship between annual US household spending on new cars and Democrat votes for Senators in Florida. Leveraging data from the Bureau of Labor Statistics and the MIT Election Data and Science Lab, Harvard Dataverse, we embarked on this journey into the intersection of economic choices and political preferences. Through rigorous statistical analysis, we discovered a significant correlation between the two aforementioned variables. Our findings revealed a robust correlation coefficient of 0.8810923 and a p-value of less than 0.01 for the years spanning from 2000 to 2018.

To put it succinctly, our research uncovered a clear connection between the amount of money spent on new automobiles by American households and their inclination to support democratic candidates in Senatorial elections in the state of Florida. Perhaps it could be said that "when it comes to choosing a new car, it seems that Floridian households are also choosing their Senators."

In conclusion, our results imply not only a link between consumer behavior and political ideology, but also highlight the need for further investigation into the driving forces behind this peculiar correlation. It is evident that studying the connection between car spending and voting behavior can provide valuable insights into the broader interplay of economics and politics. After all, one could posit that "analyzing car purchases in relation to political choices may unlock the drive behind democratic support."

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the complex world of electoral politics, a multitude of factors, from socioeconomic status to ideological beliefs, influence voter behavior. Utilizing statistical analysis, this study endeavors to uncover the connection between annual US household spending on new cars and Democrat votes for Senators in Florida. This unconventional pairing of economic expenditure and political preference is not only intriguing but also has the potential to shed light on the intricate motivations behind voter decision-making.
As the saying goes, "When it comes to elections and cars, it seems that Floridian households are driving a point home."
A substantial body of research has explored the intricate relationship between economic choices and political affiliations. However, the specific linkage between new car spending and Senatorial support for the Democratic party in Florida remains largely unexplored. This study seeks to fill this void in the literature, delving into the intriguing intersection of consumer behavior and electoral outcomes.
It is often joked that in politics, just like driving a new car, one should not be in a hurry to change the direction.
The correlation between consumer spending and political leanings has captivated scholars and armchair pundits alike. By focusing on the unique context of Florida and the specific variable of new car spending, this study aims to contribute a distinctive perspective to the ongoing discourse surrounding the intertwined realms of economics and politics.
As the research unfolds, it becomes increasingly clear that in the grand scheme of democracies and automobiles, every aspect holds a key to understanding the bigger picture.
Stay tuned for a journey that not only unveils statistical insights but also offers a fresh perspective on the amalgamation of consumer habits and political inclinations. Let's buckle up and embark on a thrilling ride through the realm of statistical analysis and political intrigue.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find that economic choices can have a significant impact on voting behavior, opening up a Pandora's box of factors that shape political preferences. This sentiment is echoed in "Doe's" research, where the authors delve into the complex web of consumer behavior and its implications for political outcomes. The literature is replete with studies delving into the intricate relationship between economic decisions and voting patterns, creating a rich tapestry of scholarly inquiry.

You know, they say voting for a senator is like buying a new car - both decisions leave you with a sinking feeling in your stomach, but at least one comes with a complimentary air freshener.

When it comes to understanding the connection between new car spending and political allegiance, "Jones" provides a comprehensive analysis of the economic determinants of voting behavior. The authors elucidate the nuanced interplay between household expenditures and political leanings, shedding light on the multifaceted nature of electoral decision-making.

It's like they always say, choosing a Democrat senator in Florida is like picking a new car - there's a lot of horsepower and potential, but you hope it doesn't break down in the middle of your journey.

Moving beyond the realm of academic literature, non-fiction works such as "Freakonomics" and "Predictably Irrational" offer insights into the underlying factors that influence consumer choices and their wider implications. These books provide a valuable perspective on how economic decisions can reverberate in the political arena, shaping the collective voice of the electorate.

Speaking of consumer choices, did you hear about the car that went into politics? It was an Elect-Tesla model!

On the fiction front, novels like "The Great Gatsby" and "The Grapes of Wrath" highlight the symbolism of automobiles and their role in reflecting societal values and aspirations. These literary works underscore the profound influence of consumerism on human behavior and societal dynamics, offering a thought-provoking lens through which to examine the connection between new car spending and political allegiances.

In a parallel universe, there's probably a "Fast and Furious 9" sequel where Vin Diesel runs for senator in Florida. It's all about driving votes, in more ways than one.

Furthermore, the internet meme culture has not been immune to the allure of combining cars and political jokes. With memes like "Car Salesman Slaps Car" and "This Is Fine Dog in a Burning Car," the digital sphere humorously encapsulates the fusion of consumer decisions and political allegiances, illustrating the pervasive influence of these themes in popular discourse.

They say a meme about new car spending and Democrat support in Florida is like a good joke - it just keeps driving the point home!



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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Annual US household spending on new cars and Democrat votes for Senators in Florida. 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 Bureau of Labor Statistics and MIT Election Data and Science Lab, Harvard Dataverse . You used data from 2000 to 2018

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]]
Driving Votes: The Correlation Between New Car Spending and Democrat Senatorial Support in Florida

[[ABSTRACT]]
This study sets out to investigate the relationship between annual US household spending on new cars and Democrat votes for Senators in Florida. Leveraging data from the Bureau of Labor Statistics and the MIT Election Data and Science Lab, Harvard Dataverse, we embarked on this journey into the intersection of economic choices and political preferences. Through rigorous statistical analysis, we discovered a significant correlation between the two aforementioned variables. Our findings revealed a robust correlation coefficient of 0.8810923 and a p-value of less than 0.01 for the years spanning from 2000 to 2018.

To put it succinctly, our research uncovered a clear connection between the amount of money spent on new automobiles by American households and their inclination to support democratic candidates in Senatorial elections in the state of Florida. Perhaps it could be said that "when it comes to choosing a new car, it seems that Floridian households are also choosing their Senators."

In conclusion, our results imply not only a link between consumer behavior and political ideology, but also highlight the need for further investigation into the driving forces behind this peculiar correlation. It is evident that studying the connection between car spending and voting behavior can provide valuable insights into the broader interplay of economics and politics. After all, one could posit that "analyzing car purchases in relation to political choices may unlock the drive behind democratic support."

[[INTRODUCTION]]
In the complex world of electoral politics, a multitude of factors, from socioeconomic status to ideological beliefs, influence voter behavior. Utilizing statistical analysis, this study endeavors to uncover the connection between annual US household spending on new cars and Democrat votes for Senators in Florida. This unconventional pairing of economic expenditure and political preference is not only intriguing but also has the potential to shed light on the intricate motivations behind voter decision-making.
As the saying goes, "When it comes to elections and cars, it seems that Floridian households are driving a point home."
A substantial body of research has explored the intricate relationship between economic choices and political affiliations. However, the specific linkage between new car spending and Senatorial support for the Democratic party in Florida remains largely unexplored. This study seeks to fill this void in the literature, delving into the intriguing intersection of consumer behavior and electoral outcomes.
It is often joked that in politics, just like driving a new car, one should not be in a hurry to change the direction.
The correlation between consumer spending and political leanings has captivated scholars and armchair pundits alike. By focusing on the unique context of Florida and the specific variable of new car spending, this study aims to contribute a distinctive perspective to the ongoing discourse surrounding the intertwined realms of economics and politics.
As the research unfolds, it becomes increasingly clear that in the grand scheme of democracies and automobiles, every aspect holds a key to understanding the bigger picture.
Stay tuned for a journey that not only unveils statistical insights but also offers a fresh perspective on the amalgamation of consumer habits and political inclinations. Let's buckle up and embark on a thrilling ride through the realm of statistical analysis and political intrigue.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To investigate the correlation between annual US household spending on new cars and Democrat votes for Senators in Florida, our research team embarked on an exhaustive data collection and analysis journey. Our dataset was primarily sourced from the Bureau of Labor Statistics for new car expenditures and the MIT Election Data and Science Lab, Harvard Dataverse for Democrat votes for Senators in Florida. From 2000 to 2018, these data sources provided the foundation for our rigorous statistical investigation.

To begin our methodology, we carefully curated data on annual household spending on new cars from the Bureau of Labor Statistics, scrutinizing the figures to ensure accuracy and completeness. We then cross-referenced this information with the corresponding Democrat votes for Senators in Florida, obtained from the MIT Election Data and Science Lab, Harvard Dataverse. This process involved meticulous attention to detail and a keen eye for identifying any outliers or anomalies in the data - after all, as researchers, it's crucial for us to drive straight to the heart of the matter.

Next, we employed a series of advanced statistical techniques to analyze the relationship between new car spending and Democrat Senatorial support in Florida. The methods utilized included regression analysis, correlation coefficients, and various econometric models. During this stage, our team diligently controlled for potential confounding variables, ensuring that our findings were robust and reliable. After all, in the world of statistics and political correlations, it's vital to clear the road of any obstacles that could lead to misleading conclusions.

In addition to the quantitative analysis, we also conducted qualitative assessments to delve deeper into the underlying factors influencing the observed relationship. This involved examining historical trends, economic indicators, and political dynamics within the state of Florida. By taking this comprehensive approach, we aimed to paint a vivid and multifaceted portrait of the intricate interplay between consumer behavior and political allegiance.

Furthermore, to validate our findings and ensure the credibility of our results, we subjected our statistical models to rigorous sensitivity analyses and diagnostic tests. This meticulous process allowed us to pinpoint the robustness of the relationship between new car spending and Democrat Senatorial support in Florida, ensuring that our conclusions were not merely a fluke of statistical noise.

Lastly, in the spirit of transparency and academic rigor, we also considered potential limitations and biases in our research methodology. While we strived to navigate through the data landscape with precision and diligence, we acknowledged the inherent complexities of teasing apart causality from correlation in observational studies. Nevertheless, armed with the power of statistical analysis and a keen dedication to uncovering the underlying truths, we proceeded earnestly in our pursuit of knowledge.

In summary, our methodology encompassed a meticulous data collection process, rigorous statistical analysis, and a comprehensive approach to unpacking the complex relationship between annual US household spending on new cars and Democrat votes for Senators in Florida. Through these methodological strides, we aimed to pave the way for a deeper understanding of the intersection between economic choices and political leanings, proving that in the realm of statistical research, the journey truly is the destination.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Annual US household spending on new cars and Democrat votes for Senators in Florida. 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 Bureau of Labor Statistics and MIT Election Data and Science Lab, Harvard Dataverse .

For the time period 2000 to 2018, you found a correlation 0.8810923, r-squared of 0.7763236, 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]]
Driving Votes: The Correlation Between New Car Spending and Democrat Senatorial Support in Florida

[[ABSTRACT]]
This study sets out to investigate the relationship between annual US household spending on new cars and Democrat votes for Senators in Florida. Leveraging data from the Bureau of Labor Statistics and the MIT Election Data and Science Lab, Harvard Dataverse, we embarked on this journey into the intersection of economic choices and political preferences. Through rigorous statistical analysis, we discovered a significant correlation between the two aforementioned variables. Our findings revealed a robust correlation coefficient of 0.8810923 and a p-value of less than 0.01 for the years spanning from 2000 to 2018.

To put it succinctly, our research uncovered a clear connection between the amount of money spent on new automobiles by American households and their inclination to support democratic candidates in Senatorial elections in the state of Florida. Perhaps it could be said that "when it comes to choosing a new car, it seems that Floridian households are also choosing their Senators."

In conclusion, our results imply not only a link between consumer behavior and political ideology, but also highlight the need for further investigation into the driving forces behind this peculiar correlation. It is evident that studying the connection between car spending and voting behavior can provide valuable insights into the broader interplay of economics and politics. After all, one could posit that "analyzing car purchases in relation to political choices may unlock the drive behind democratic support."

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the complex world of electoral politics, a multitude of factors, from socioeconomic status to ideological beliefs, influence voter behavior. Utilizing statistical analysis, this study endeavors to uncover the connection between annual US household spending on new cars and Democrat votes for Senators in Florida. This unconventional pairing of economic expenditure and political preference is not only intriguing but also has the potential to shed light on the intricate motivations behind voter decision-making.
As the saying goes, "When it comes to elections and cars, it seems that Floridian households are driving a point home."
A substantial body of research has explored the intricate relationship between economic choices and political affiliations. However, the specific linkage between new car spending and Senatorial support for the Democratic party in Florida remains largely unexplored. This study seeks to fill this void in the literature, delving into the intriguing intersection of consumer behavior and electoral outcomes.
It is often joked that in politics, just like driving a new car, one should not be in a hurry to change the direction.
The correlation between consumer spending and political leanings has captivated scholars and armchair pundits alike. By focusing on the unique context of Florida and the specific variable of new car spending, this study aims to contribute a distinctive perspective to the ongoing discourse surrounding the intertwined realms of economics and politics.
As the research unfolds, it becomes increasingly clear that in the grand scheme of democracies and automobiles, every aspect holds a key to understanding the bigger picture.
Stay tuned for a journey that not only unveils statistical insights but also offers a fresh perspective on the amalgamation of consumer habits and political inclinations. Let's buckle up and embark on a thrilling ride through the realm of statistical analysis and political intrigue.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The statistical analysis of the relationship between annual US household spending on new cars and Democrat votes for Senators in Florida yielded a robust correlation coefficient of 0.8810923, indicating a strong positive association between the two variables. This finding suggests that as household spending on new cars increases, there is a corresponding tendency for greater Democrat support in Senatorial elections in Florida. One might quip that "when it comes to voting blue, it seems that buying new is, too."

Furthermore, the coefficient of determination (r-squared) was calculated to be 0.7763236, indicating that approximately 77.6% of the variability in Democrat votes for Senators in Florida can be explained by the variation in annual household spending on new cars. In other words, the level of car spending appears to be a pivotal determinant in predicting the level of Democrat support in Senatorial elections in the Sunshine State. It seems that "for Floridian households, cars and politics make quite the power couple."

The p-value, which was found to be less than 0.01, provides compelling evidence to reject the null hypothesis that there is no relationship between new car spending and Democrat votes for Senators in Florida. At this level of significance, the results underscore the substantial statistical significance of the observed correlation. One might venture to say that "the connection between new car purchases and Democratic votes is as clear as the Florida sky."

Fig. 1 illustrates the strong positive correlation between annual US household spending on new cars and Democrat votes for Senators in Florida. The scatterplot visually depicts the upward trend, affirming the compelling relationship between these two variables. One might opine that "this connection seems as clear as the road ahead for a brand-new car. Smooth and straight."

In summary, the findings of this study unveil a noteworthy connection between consumer behavior, as manifested in car spending, and political inclinations, as reflected in Democrat support in Senatorial elections. The results not only accentuate the importance of economic factors in shaping electoral outcomes but also beckon further exploration of the nexus between individual spending choices and partisan loyalties. It is apparent that the "road to political insights may very well run through the precincts of car dealerships."


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Annual US household spending on new cars and Democrat votes for Senators in Florida. 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]]
Driving Votes: The Correlation Between New Car Spending and Democrat Senatorial Support in Florida

[[ABSTRACT]]
This study sets out to investigate the relationship between annual US household spending on new cars and Democrat votes for Senators in Florida. Leveraging data from the Bureau of Labor Statistics and the MIT Election Data and Science Lab, Harvard Dataverse, we embarked on this journey into the intersection of economic choices and political preferences. Through rigorous statistical analysis, we discovered a significant correlation between the two aforementioned variables. Our findings revealed a robust correlation coefficient of 0.8810923 and a p-value of less than 0.01 for the years spanning from 2000 to 2018.

To put it succinctly, our research uncovered a clear connection between the amount of money spent on new automobiles by American households and their inclination to support democratic candidates in Senatorial elections in the state of Florida. Perhaps it could be said that "when it comes to choosing a new car, it seems that Floridian households are also choosing their Senators."

In conclusion, our results imply not only a link between consumer behavior and political ideology, but also highlight the need for further investigation into the driving forces behind this peculiar correlation. It is evident that studying the connection between car spending and voting behavior can provide valuable insights into the broader interplay of economics and politics. After all, one could posit that "analyzing car purchases in relation to political choices may unlock the drive behind democratic support."

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find that economic choices can have a significant impact on voting behavior, opening up a Pandora's box of factors that shape political preferences. This sentiment is echoed in "Doe's" research, where the authors delve into the complex web of consumer behavior and its implications for political outcomes. The literature is replete with studies delving into the intricate relationship between economic decisions and voting patterns, creating a rich tapestry of scholarly inquiry.
You know, they say voting for a senator is like buying a new car - both decisions leave you with a sinking feeling in your stomach, but at least one comes with a complimentary air freshener.
When it comes to understanding the connection between new car spending and political allegiance, "Jones" provides a comprehensive analysis of the economic determinants of voting behavior. The authors elucidate the nuanced interplay between household expenditures and political leanings, shedding light on the multifaceted nature of electoral decision-making.
It's like they always say, choosing a Democrat senator in Florida is like picking a new car - there's a lot of horsepower and potential, but you hope it doesn't break down in the middle of your journey.
Moving beyond the realm of academic literature, non-fiction works such as "Freakonomics" and "Predictably Irrational" offer insights into the underlying factors that influence consumer choices and their wider implications. These books provide a valuable perspective on how economic decisions can reverberate in the political arena, shaping the collective voice of the electorate.
Speaking of consumer choices, did you hear about the car that went into politics? It was an Elect-Tesla model!
On the fiction front, novels like "The Great Gatsby" and "The Grapes of Wrath" highlight the symbolism of automobiles and their role in reflecting societal values and aspirations. These literary works underscore the profound influence of consumerism on human behavior and societal dynamics, offering a thought-provoking lens through which to examine the connection between new car spending and political allegiances.
In a parallel universe, there's probably a "Fast and Furious 9" sequel where Vin Diesel runs for senator in Florida. It's all about driving votes, in more ways than one.
Furthermore, the internet meme culture has not been immune to the allure of combining cars and political jokes. With memes like "Car Salesman Slaps Car" and "This Is Fine Dog in a Burning Car," the digital sphere humorously encapsulates the fusion of consumer decisions and political allegiances, illustrating the pervasive influence of these themes in popular discourse.
They say a meme about new car spending and Democrat support in Florida is like a good joke - it just keeps driving the point home!


[[RESULTS]]
The statistical analysis of the relationship between annual US household spending on new cars and Democrat votes for Senators in Florida yielded a robust correlation coefficient of 0.8810923, indicating a strong positive association between the two variables. This finding suggests that as household spending on new cars increases, there is a corresponding tendency for greater Democrat support in Senatorial elections in Florida. One might quip that "when it comes to voting blue, it seems that buying new is, too."
Furthermore, the coefficient of determination (r-squared) was calculated to be 0.7763236, indicating that approximately 77.6% of the variability in Democrat votes for Senators in Florida can be explained by the variation in annual household spending on new cars. In other words, the level of car spending appears to be a pivotal determinant in predicting the level of Democrat support in Senatorial elections in the Sunshine State. It seems that "for Floridian households, cars and politics make quite the power couple."
The p-value, which was found to be less than 0.01, provides compelling evidence to reject the null hypothesis that there is no relationship between new car spending and Democrat votes for Senators in Florida. At this level of significance, the results underscore the substantial statistical significance of the observed correlation. One might venture to say that "the connection between new car purchases and Democratic votes is as clear as the Florida sky."
Fig. 1 illustrates the strong positive correlation between annual US household spending on new cars and Democrat votes for Senators in Florida. The scatterplot visually depicts the upward trend, affirming the compelling relationship between these two variables. One might opine that "this connection seems as clear as the road ahead for a brand-new car. Smooth and straight."
In summary, the findings of this study unveil a noteworthy connection between consumer behavior, as manifested in car spending, and political inclinations, as reflected in Democrat support in Senatorial elections. The results not only accentuate the importance of economic factors in shaping electoral outcomes but also beckon further exploration of the nexus between individual spending choices and partisan loyalties. It is apparent that the "road to political insights may very well run through the precincts of car dealerships."

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of our study have unveiled a remarkably strong correlation between annual US household spending on new cars and Democrat votes for Senators in Florida. Our findings corroborate the existing literature, which has hinted at the intricate interplay between economic decisions and political allegiances. Our results echo the sentiment expressed by Smith et al. and Doe, who highlighted the substantial impact of economic choices on voting behavior, albeit in a more serious fashion. Furthermore, the relationship identified in our study aligns with the comprehensive analysis provided by Jones, which emphasized the nuanced interplay between household expenditures and political leanings.

It appears that the connection between car spending and Democrat support in Florida is as clear as the road ahead for a brand-new car. Smooth and straight. The statistical significance of the observed correlation, with a p-value of less than 0.01, provides compelling evidence to reject the null hypothesis and underscores the substantive nature of this association. One might venture to say that the connection between new car purchases and Democratic votes is as clear as the Florida sky, but not as sunny!

Our findings have broader implications for understanding the dynamics of electoral decision-making and the role of consumer behavior in shaping political outcomes. The coefficient of determination (r-squared) of 0.7763236 indicates that a significant proportion of the variability in Democrat votes for Senators in Florida can be explained by the variation in annual household spending on new cars, highlighting the pivotal role of car spending in predicting political inclinations. It appears that, for Floridian households, cars and politics make quite the power couple. If only we could drive our way out of partisan politics as easily as finding a good parking spot.

Indeed, the quirky relationship between new car spending and political allegiances offers an intriguing avenue for further research. The "drive" behind democratic support seems to extend beyond the ballot box and all the way to the showroom floor. Perhaps it could be said that "when it comes to choosing a new car, it seems that Floridian households are also choosing their Senators." It's as if the purchase of a new car acts as a crystal ball into political preferences. One might quip that "when it comes to voting blue, it seems that buying new is, too."

The road to political insights may very well run through the precincts of car dealerships. As we continue to unpack the connection between consumer behavior and voting patterns, we are reminded that understanding the electorate is much like navigating a congested highway – it requires patience, attention to detail, and maybe a musical playlist to keep the spirits high. After all, statistics and dad jokes are not that different - both aim to elicit a reaction, whether it's a smile or a sigh.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Annual US household spending on new cars and Democrat votes for Senators in Florida. 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]]
Driving Votes: The Correlation Between New Car Spending and Democrat Senatorial Support in Florida

[[ABSTRACT]]
This study sets out to investigate the relationship between annual US household spending on new cars and Democrat votes for Senators in Florida. Leveraging data from the Bureau of Labor Statistics and the MIT Election Data and Science Lab, Harvard Dataverse, we embarked on this journey into the intersection of economic choices and political preferences. Through rigorous statistical analysis, we discovered a significant correlation between the two aforementioned variables. Our findings revealed a robust correlation coefficient of 0.8810923 and a p-value of less than 0.01 for the years spanning from 2000 to 2018.

To put it succinctly, our research uncovered a clear connection between the amount of money spent on new automobiles by American households and their inclination to support democratic candidates in Senatorial elections in the state of Florida. Perhaps it could be said that "when it comes to choosing a new car, it seems that Floridian households are also choosing their Senators."

In conclusion, our results imply not only a link between consumer behavior and political ideology, but also highlight the need for further investigation into the driving forces behind this peculiar correlation. It is evident that studying the connection between car spending and voting behavior can provide valuable insights into the broader interplay of economics and politics. After all, one could posit that "analyzing car purchases in relation to political choices may unlock the drive behind democratic support."

[[INTRDUCTION]]
In the complex world of electoral politics, a multitude of factors, from socioeconomic status to ideological beliefs, influence voter behavior. Utilizing statistical analysis, this study endeavors to uncover the connection between annual US household spending on new cars and Democrat votes for Senators in Florida. This unconventional pairing of economic expenditure and political preference is not only intriguing but also has the potential to shed light on the intricate motivations behind voter decision-making.
As the saying goes, "When it comes to elections and cars, it seems that Floridian households are driving a point home."
A substantial body of research has explored the intricate relationship between economic choices and political affiliations. However, the specific linkage between new car spending and Senatorial support for the Democratic party in Florida remains largely unexplored. This study seeks to fill this void in the literature, delving into the intriguing intersection of consumer behavior and electoral outcomes.
It is often joked that in politics, just like driving a new car, one should not be in a hurry to change the direction.
The correlation between consumer spending and political leanings has captivated scholars and armchair pundits alike. By focusing on the unique context of Florida and the specific variable of new car spending, this study aims to contribute a distinctive perspective to the ongoing discourse surrounding the intertwined realms of economics and politics.
As the research unfolds, it becomes increasingly clear that in the grand scheme of democracies and automobiles, every aspect holds a key to understanding the bigger picture.
Stay tuned for a journey that not only unveils statistical insights but also offers a fresh perspective on the amalgamation of consumer habits and political inclinations. Let's buckle up and embark on a thrilling ride through the realm of statistical analysis and political intrigue.

[[RESULTS]]
The statistical analysis of the relationship between annual US household spending on new cars and Democrat votes for Senators in Florida yielded a robust correlation coefficient of 0.8810923, indicating a strong positive association between the two variables. This finding suggests that as household spending on new cars increases, there is a corresponding tendency for greater Democrat support in Senatorial elections in Florida. One might quip that "when it comes to voting blue, it seems that buying new is, too."
Furthermore, the coefficient of determination (r-squared) was calculated to be 0.7763236, indicating that approximately 77.6% of the variability in Democrat votes for Senators in Florida can be explained by the variation in annual household spending on new cars. In other words, the level of car spending appears to be a pivotal determinant in predicting the level of Democrat support in Senatorial elections in the Sunshine State. It seems that "for Floridian households, cars and politics make quite the power couple."
The p-value, which was found to be less than 0.01, provides compelling evidence to reject the null hypothesis that there is no relationship between new car spending and Democrat votes for Senators in Florida. At this level of significance, the results underscore the substantial statistical significance of the observed correlation. One might venture to say that "the connection between new car purchases and Democratic votes is as clear as the Florida sky."
Fig. 1 illustrates the strong positive correlation between annual US household spending on new cars and Democrat votes for Senators in Florida. The scatterplot visually depicts the upward trend, affirming the compelling relationship between these two variables. One might opine that "this connection seems as clear as the road ahead for a brand-new car. Smooth and straight."
In summary, the findings of this study unveil a noteworthy connection between consumer behavior, as manifested in car spending, and political inclinations, as reflected in Democrat support in Senatorial elections. The results not only accentuate the importance of economic factors in shaping electoral outcomes but also beckon further exploration of the nexus between individual spending choices and partisan loyalties. It is apparent that the "road to political insights may very well run through the precincts of car dealerships."

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has successfully demonstrated a significant and robust correlation between annual US household spending on new cars and Democrat votes for Senators in Florida. It appears that when it comes to political preferences, Floridian households are not just making a statement at the ballot box, but also in the showroom. One might even say that their votes are revving up the engines of political change.

The results of this study not only highlight the intriguing interplay between consumer behavior and political allegiance but also emphasize the need for further investigation into the driving forces behind this unexpected correlation. Well, it seems that in the realm of electoral choices, much like on the highway, there are always a few surprising twists and turns.

As we reflect on our findings, it becomes evident that the connection between car purchases and political choices provides valuable insights into the complexities of voter decision-making. Perhaps one could posit that “when it comes to casting ballots, some households are putting their pedal to the metal.”

It is clear that our study has uncovered an interesting dynamic between economic choices and political ideologies, and one cannot help but appreciate the humor in the quirks of human behavior. Indeed, analyzing car purchases in relation to political choices may unlock the drive behind democratic support.

In light of these compelling results, we assert that no further research is needed in this area. The road to understanding the link between new car spending and Democrat votes in Florida has been well-paved by our study, and it seems we've reached the final destination in this line of investigation. After all, one might say that “we’ve crossed the finish line and parked our findings for good.”

It’s been quite the journey, but in the world of statistical inquiry and political analysis, it seems that for now, this research has driven its point home quite effectively. Proceeding further on this path would be akin to taking a detour when we’ve already arrived at the perfect destination.


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 Driving Votes: The Correlation Between New Car Spending and Democrat Senatorial Support in Florida. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Political Consumption and Behavior


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 Driving Votes: The Correlation Between New Car Spending and Democrat Senatorial Support in Florida. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Consumer Politics and Voting Behavior 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 Driving Votes: The Correlation Between New Car Spending and Democrat Senatorial Support in Florida with an abstract of This study sets out to investigate the relationship between annual US household spending on new cars and Democrat votes for Senators in Florida. Leveraging data from the Bureau of Labor Statistics and the MIT Election Data and Science Lab, Harvard Dataverse, we embarked on this journey into the intersection of economic choices and political preferences. Through rigorous statistical analysis, we discovered a significant correlation between the two aforementioned variables. Our findings revealed a robust correlation coefficient of 0.8810923 and a p-value of less than 0.01 for the years spanning from 2000 to 2018.
To put it succinctly, our research uncovered a clear connection between the amount of money spent on new automobiles by American households and their inclination to support democratic candidates in Senatorial elections in the state of Florida. Perhaps it could be said that "when it comes to choosing a new car, it seems that Floridian households are also choosing their Senators."
In conclusion, our results imply not only a link between consumer behavior and political ideology, but also highlight the need for further investigation into the driving forces behind this peculiar correlation. It is evident that studying the connection between car spending and voting behavior can provide valuable insights into the broader interplay of economics and politics. After all, one could posit that "analyzing car purchases in relation to political choices may unlock the drive behind democratic support.

ChatGPT:

new car spending, Democrat votes, Senators in Florida, household spending, political preferences, economic choices, political ideology, voting behavior, consumer behavior, economic interplay, political choices

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



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Data details

Annual US household spending on new cars
Detailed data title: Average annual household spend on new cars
Source: Bureau of Labor Statistics
See what else correlates with Annual US household spending on new cars

Votes for Democratic Senators in Florida
Detailed data title: Percentage of votes cast for Federal Democrat Senate candidates in Florida
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for Democratic Senators in Florida

Correlation r = 0.8810923 (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 = 0.7763236 (Coefficient of determination)
This means 77.6% of the change in the one variable (i.e., Votes for Democratic Senators in Florida) is predictable based on the change in the other (i.e., Annual US household spending on new cars) over the 7 years from 2000 through 2018.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.0088. 0.0087748112883162620000000000
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 0.88 in 0.88% of random cases. Said differently, if you correlated 114 random variables Which I absolutely did.
with the same 6 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 6 because we have two variables measured over a period of 7 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.

[ 0.38, 0.98 ] 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.
2000200420062010201220162018
Annual US household spending on new cars (Household spend)1605174817981219163916501825
Votes for Democratic Senators in Florida (Percentage of votes)51.043648.32160.30120.19855.231844.314949.9325




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
  4. Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.
  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([1605,1748,1798,1219,1639,1650,1825,])
array_2 = np.array([51.0436,48.321,60.301,20.198,55.2318,44.3149,49.9325,])
array_1_name = "Annual US household spending on new cars"
array_2_name = "Votes for Democratic Senators in Florida"

# 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: 4317 · Black Variable ID: 19927 · Red Variable ID: 26366
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