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Spurious correlation #5,447 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Votes for Republican Senators in Virginia and the second variable is Google searches for 'hottest man on earth'.  The chart goes from 2004 to 2020, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the temperature rose in the political arena, it created a hotly contested race which heated up the debate. As the Republican votes cooled off, so did the competition, leading to a Senate situation that was no longer sizzling. This political chill had a ripple effect, causing a decrease in the overall heat index of the elected officials. And as we all know, fewer Republican votes for Senators in Virginia meant there was simply less political fire to fuel the flames of this particular search. In the end, it seems that in this case, the connection between politics and this particular search query is just too hot to handle!

Model: dalle-3
Prompt: Prompt: Create an image of a bustling Virginia town, with a thermometer gauge rising as political tension heats up, casting a fiery glow over the landscape. Republican votes for Senators slowly cool down, and the once intense competition sizzles to a mild simmer. As the political temperature drops, so does the overall heat index of elected officials. Meanwhile, a Google search bar glows with the words "hottest man on earth," its flames diminishing in the shadow of the cooled political arena. The connection between politics and the search query becomes too hot to handle, and it evaporates into an unexpected cooling breeze. 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 Republican Senators in Virginia and Google searches for 'hottest man on earth'. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Hyper-realistic Pop art a meme Hyper-realistic Photorealism
ChatGPT: a meme

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 Republican Senators in Virginia and Google searches for 'hottest man on earth', in the following situation: As the temperature rose in the political arena, it created a hotly contested race which heated up the debate. As the Republican votes cooled off, so did the competition, leading to a Senate situation that was no longer sizzling. This political chill had a ripple effect, causing a decrease in the overall heat index of the elected officials. And as we all know, fewer Republican votes for Senators in Virginia meant there was simply less political fire to fuel the flames of this particular search. In the end, it seems that in this case, the connection between politics and this particular search query is just too hot to handle!. Keep the description simple.
ChatGPT: In a bustling Virginia town, a thermometer gauge rises with political tension, casting a heated glow over the landscape. Republican votes for Senators slowly cool down, and the once fiery race simmers to a mild competition. As the political temperature drops, so does the overall heat index of elected officials. Meanwhile, a Google search bar glows with the words "hottest man on earth," but its flames diminish in the shadow of the cooled political arena. The connection between politics and the search query becomes too hot to handle, evaporating into an unexpected cooling breeze.

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 meme ] and depicting this scene: In a bustling Virginia town, a thermometer gauge rises with political tension, casting a heated glow over the landscape. Republican votes for Senators slowly cool down, and the once fiery race simmers to a mild competition. As the political temperature drops, so does the overall heat index of elected officials. Meanwhile, a Google search bar glows with the words "hottest man on earth," but its flames diminish in the shadow of the cooled political arena. The connection between politics and the search query becomes too hot to handle, evaporating into an unexpected cooling breeze. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Create an image of a bustling Virginia town, with a thermometer gauge rising as political tension heats up, casting a fiery glow over the landscape. Republican votes for Senators slowly cool down, and the once intense competition sizzles to a mild simmer. As the political temperature drops, so does the overall heat index of elected officials. Meanwhile, a Google search bar glows with the words "hottest man on earth," its flames diminishing in the shadow of the cooled political arena. The connection between politics and the search query becomes too hot to handle, and it evaporates into an unexpected cooling breeze.

*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 a decrease in Republican votes for Senators in Virginia caused hottest man on earth (Google searches for 'hottest man on earth') to decrease.\Make it sound serious until the end.

AI academic paper

(Because p < 0.05)
Red States and Red Hot Searches: A Correlational Analysis of Republican Senator Votes in Virginia and Google Searches for 'Hottest Man on Earth'

The Journal of Political Behavior and Internet Trends

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 Republican votes for Senators in Virginia and Google searches for 'hottest man on earth'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title a clever pun.

Your research team used data from MIT Election Data and Science Lab, Harvard Dataverse and Google Trends to assess this nagging question. You found a correlation coefficient of 0.8431649 and p < 0.05 for 2004 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]]
"Red States and Red Hot Searches: A Correlational Analysis of Republican Senator Votes in Virginia and Google Searches for 'Hottest Man on Earth'"

[[ABSTRACT]]
This study investigates the surprising correlation between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, our research team calculated a correlation coefficient of 0.8431649 with a significance level of p < 0.05. Our analysis offers insight into the unexpected behavior of voters and their online search patterns, shedding light on the subtle dynamics between political preferences and pop culture interests. The findings not only highlight the complexities of human behavior but also emphasize the need for multidisciplinary approaches in understanding socio-political phenomena.


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 Republican votes for Senators in Virginia and Google searches for 'hottest man on earth'. 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]]
"Red States and Red Hot Searches: A Correlational Analysis of Republican Senator Votes in Virginia and Google Searches for 'Hottest Man on Earth'"

[[ABSTRACT]]
This study investigates the surprising correlation between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, our research team calculated a correlation coefficient of 0.8431649 with a significance level of p < 0.05. Our analysis offers insight into the unexpected behavior of voters and their online search patterns, shedding light on the subtle dynamics between political preferences and pop culture interests. The findings not only highlight the complexities of human behavior but also emphasize the need for multidisciplinary approaches in understanding socio-political phenomena.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The intersection of politics and popular culture has long been a source of fascination for researchers and laypeople alike. From T-shirts emblazoned with political slogans to viral memes featuring political figures, it is clear that these seemingly distinct realms often intertwine in unexpected ways. Our study delves into a particularly intriguing example of this phenomenon, exploring the relationship between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth'. It is not only a marriage of red states and red hot searches but also a curious case meriting a closer statistical examination.

Political scientists have traditionally focused on factors such as party affiliation, ideology, and candidate characteristics to explain voting behavior. However, in an era marked by the increasing digitalization of daily life, the role of online activities in shaping political trends has become increasingly salient. Alongside this trend, researchers across disciplines have recognized the value of harnessing digital footprints as valuable sources of insight into the intricacies of human behavior.

With this context in mind, our research seeks to navigate uncharted territory at the intersection of political science and online search behavior. In examining the Google searches for 'hottest man on earth', we address a question that has not been previously explored in academic literature. This unexpected and somewhat whimsical inquiry offers a unique opportunity to shed light on the intricate and often puzzling confluence of political preferences and pop culture curiosities.

The unexpected discovery of the notable correlation coefficient between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020 not only raises eyebrows but also presents a conundrum that our rigorous statistical analysis aims to untangle. By utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, we have taken a multidisciplinary approach to delicately dissect this relationship.

Through our findings, we aim not only to captivate the academic community with a surprising statistical phenomenon but also to underscore the numerous nuances underpinning human behavior. As we embark on this scholarly journey, we do so with an astute awareness of the quirks and idiosyncrasies inherent in both research and human nature. After all, when navigating uncharted statistical territory, a touch of humor and an affinity for diving into the unexpected can often prove to be invaluable companions.


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 Republican votes for Senators in Virginia and Google searches for 'hottest man on earth'. 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]]
"Red States and Red Hot Searches: A Correlational Analysis of Republican Senator Votes in Virginia and Google Searches for 'Hottest Man on Earth'"

[[ABSTRACT]]
This study investigates the surprising correlation between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, our research team calculated a correlation coefficient of 0.8431649 with a significance level of p < 0.05. Our analysis offers insight into the unexpected behavior of voters and their online search patterns, shedding light on the subtle dynamics between political preferences and pop culture interests. The findings not only highlight the complexities of human behavior but also emphasize the need for multidisciplinary approaches in understanding socio-political phenomena.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of politics and popular culture has long been a source of fascination for researchers and laypeople alike. From T-shirts emblazoned with political slogans to viral memes featuring political figures, it is clear that these seemingly distinct realms often intertwine in unexpected ways. Our study delves into a particularly intriguing example of this phenomenon, exploring the relationship between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth'. It is not only a marriage of red states and red hot searches but also a curious case meriting a closer statistical examination.
Political scientists have traditionally focused on factors such as party affiliation, ideology, and candidate characteristics to explain voting behavior. However, in an era marked by the increasing digitalization of daily life, the role of online activities in shaping political trends has become increasingly salient. Alongside this trend, researchers across disciplines have recognized the value of harnessing digital footprints as valuable sources of insight into the intricacies of human behavior.
With this context in mind, our research seeks to navigate uncharted territory at the intersection of political science and online search behavior. In examining the Google searches for 'hottest man on earth', we address a question that has not been previously explored in academic literature. This unexpected and somewhat whimsical inquiry offers a unique opportunity to shed light on the intricate and often puzzling confluence of political preferences and pop culture curiosities.
The unexpected discovery of the notable correlation coefficient between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020 not only raises eyebrows but also presents a conundrum that our rigorous statistical analysis aims to untangle. By utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, we have taken a multidisciplinary approach to delicately dissect this relationship.
Through our findings, we aim not only to captivate the academic community with a surprising statistical phenomenon but also to underscore the numerous nuances underpinning human behavior. As we embark on this scholarly journey, we do so with an astute awareness of the quirks and idiosyncrasies inherent in both research and human nature. After all, when navigating uncharted statistical territory, a touch of humor and an affinity for diving into the unexpected can often prove to be invaluable companions.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The connection between political voting behavior and seemingly unrelated factors has been a subject of scholarly interest in recent years. Smith (2016) examined the influence of social media on political attitudes and found that online activities can influence individual political preferences. Similarly, Doe (2018) explored the impact of digital footprints on election outcomes, revealing the potential for online search patterns to reflect voter sentiments.

Moving beyond the traditional realm of political science, our study ventures into uncharted territory by investigating the connection between Republican votes for Senators in Virginia and Google searches for 'hottest man on earth'. While this inquiry may seem whimsical at first glance, it touches upon the broader theme of how online behaviors intersect with political inclinations.

In the realm of popular culture and its impact on societal dynamics, Jones (2017) analyzed the influence of celebrity endorsements on political campaigns, highlighting the captivating effect of cultural figures on voter engagement. Additionally, "The Influential Power of Pop Culture" (Roberts, 2019) delves into the intricate ways in which popular culture seeps into the fabric of political landscapes, offering a lens through which to view the complex interplay between seemingly disparate domains.

Expanding upon this line of inquiry, our study steps into the realm of fictitious realms that may seemingly hold parallels to our investigation. "The Hotter, the Better: A Search for Political Romance" (Winters, 2020) provides a lighthearted exploration of the unforeseen connections between personal attractions and political inclinations, albeit within the context of fiction. Further, "Politics Under the Microscope: An Investigative Journey" (Johnson, 2018) delivers a captivating blend of fact and fiction, teasing at the blurred boundaries between objective analysis and imaginative storytelling.

As we delve deeper into the web of interconnected influences, we acknowledge the need for a whimsical touch to our exploration of this unexpected correlation. It is within this spirit that we draw inspiration from the unlikeliest of sources, including the fine print on shampoo bottles and the peculiar quirks of everyday life. After all, it is in the unexpected and seemingly absurd that we often uncover the most dazzling insights.


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 Republican votes for Senators in Virginia and Google searches for 'hottest man on earth'. 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 Google Trends . You used data from 2004 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]]
"Red States and Red Hot Searches: A Correlational Analysis of Republican Senator Votes in Virginia and Google Searches for 'Hottest Man on Earth'"

[[ABSTRACT]]
This study investigates the surprising correlation between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, our research team calculated a correlation coefficient of 0.8431649 with a significance level of p < 0.05. Our analysis offers insight into the unexpected behavior of voters and their online search patterns, shedding light on the subtle dynamics between political preferences and pop culture interests. The findings not only highlight the complexities of human behavior but also emphasize the need for multidisciplinary approaches in understanding socio-political phenomena.

[[INTRODUCTION]]
The intersection of politics and popular culture has long been a source of fascination for researchers and laypeople alike. From T-shirts emblazoned with political slogans to viral memes featuring political figures, it is clear that these seemingly distinct realms often intertwine in unexpected ways. Our study delves into a particularly intriguing example of this phenomenon, exploring the relationship between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth'. It is not only a marriage of red states and red hot searches but also a curious case meriting a closer statistical examination.
Political scientists have traditionally focused on factors such as party affiliation, ideology, and candidate characteristics to explain voting behavior. However, in an era marked by the increasing digitalization of daily life, the role of online activities in shaping political trends has become increasingly salient. Alongside this trend, researchers across disciplines have recognized the value of harnessing digital footprints as valuable sources of insight into the intricacies of human behavior.
With this context in mind, our research seeks to navigate uncharted territory at the intersection of political science and online search behavior. In examining the Google searches for 'hottest man on earth', we address a question that has not been previously explored in academic literature. This unexpected and somewhat whimsical inquiry offers a unique opportunity to shed light on the intricate and often puzzling confluence of political preferences and pop culture curiosities.
The unexpected discovery of the notable correlation coefficient between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020 not only raises eyebrows but also presents a conundrum that our rigorous statistical analysis aims to untangle. By utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, we have taken a multidisciplinary approach to delicately dissect this relationship.
Through our findings, we aim not only to captivate the academic community with a surprising statistical phenomenon but also to underscore the numerous nuances underpinning human behavior. As we embark on this scholarly journey, we do so with an astute awareness of the quirks and idiosyncrasies inherent in both research and human nature. After all, when navigating uncharted statistical territory, a touch of humor and an affinity for diving into the unexpected can often prove to be invaluable companions.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Our research employed a multi-faceted methodology to unravel the enigmatic nexus between Republican senatorial votes in Virginia and the fervor for finding the 'hottest man on earth' via Google searches. The data collection process, akin to embarking on a digital treasure hunt, commenced with a comprehensive extraction of electoral results from the MIT Election Data and Science Lab. This involved navigating through intricate cyber-archives, sifting through electoral statistics, and occasionally fending off the temptation to click on cat videos surreptitiously lurking in the virtual vicinity.

Simultaneously, we harnessed the prowess of the Harvard Dataverse, akin to embarking on a scholarly odyssey through digital dimensions, to procure meticulous socio-political metadata. This journey involved wrangling with datasets, dodging digital dust bunnies, and cautiously circumnavigating the treacherous shoals of typographical errors that have been known to capsize less discerning researchers, leaving them stranded amidst the reefs of unreliable data.

Furthermore, our venture into the realm of online search behavior entailed a deep dive into Google Trends, traversing the vast expanse of internet queries in pursuit of the elusive quest for the 'hottest man on earth'. Navigating the labyrinthine corridors of search algorithms, at times, felt akin to unraveling a digital Gordian knot, yet we persisted with the determination of digital explorers in pursuit of our statistical treasure.

The comprehensive dataset knit together through these arduous virtual sojourns encompassed the years 2004 to 2020, offering a panoramic vista of electoral patterns and online inquiries. Our dataset, much like a fabled treasure trove, contained the gemstones of electoral results and the digital footprints of fervid 'hottest man on earth' searches, forming the bedrock of our analytical pursuits.

Subsequently, employing advanced statistical techniques, such as Pearson correlation analysis and linear regression models, we meticulously sought to unveil the hidden threads interweaving political choices with pop culture proclivities. Our statistical odyssey was guided by an unwavering commitment to uncovering meaningful patterns amidst the sea of numbers, recognizing that within the domain of statistics lies both the rigidity of mathematical laws and the subtleties of human whims and proclivities.

The resultant correlation coefficient of 0.8431649, coupled with a significance level of p < 0.05, emerged as the treasure unearthed from our digital quest. This robust statistical finding serves as a lodestar illuminating the hitherto obscured interplay between political inclinations and the pursuit of ethereal allure through online searches.

We are well aware that navigating the intricate channels of political votes and digital quests requires both intuition and statistical acumen, for within the bosom of academic inquiry, the unexpected often conceals immense insight. Thus, armed with computational fortitude and a penchant for navigating the quirkier side of data, we journeyed through digital and statistical wilderness to illuminate the confluence of red states and red hot searches, all the while recognizing that scholarly sojourns are seldom devoid of whimsy and wonder.


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 Republican votes for Senators in Virginia and Google searches for 'hottest man on earth'. 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 Google Trends .

For the time period 2004 to 2020, you found a correlation 0.8431649, r-squared of 0.7109271, and p < 0.05.

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]]
"Red States and Red Hot Searches: A Correlational Analysis of Republican Senator Votes in Virginia and Google Searches for 'Hottest Man on Earth'"

[[ABSTRACT]]
This study investigates the surprising correlation between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, our research team calculated a correlation coefficient of 0.8431649 with a significance level of p < 0.05. Our analysis offers insight into the unexpected behavior of voters and their online search patterns, shedding light on the subtle dynamics between political preferences and pop culture interests. The findings not only highlight the complexities of human behavior but also emphasize the need for multidisciplinary approaches in understanding socio-political phenomena.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intersection of politics and popular culture has long been a source of fascination for researchers and laypeople alike. From T-shirts emblazoned with political slogans to viral memes featuring political figures, it is clear that these seemingly distinct realms often intertwine in unexpected ways. Our study delves into a particularly intriguing example of this phenomenon, exploring the relationship between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth'. It is not only a marriage of red states and red hot searches but also a curious case meriting a closer statistical examination.
Political scientists have traditionally focused on factors such as party affiliation, ideology, and candidate characteristics to explain voting behavior. However, in an era marked by the increasing digitalization of daily life, the role of online activities in shaping political trends has become increasingly salient. Alongside this trend, researchers across disciplines have recognized the value of harnessing digital footprints as valuable sources of insight into the intricacies of human behavior.
With this context in mind, our research seeks to navigate uncharted territory at the intersection of political science and online search behavior. In examining the Google searches for 'hottest man on earth', we address a question that has not been previously explored in academic literature. This unexpected and somewhat whimsical inquiry offers a unique opportunity to shed light on the intricate and often puzzling confluence of political preferences and pop culture curiosities.
The unexpected discovery of the notable correlation coefficient between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020 not only raises eyebrows but also presents a conundrum that our rigorous statistical analysis aims to untangle. By utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, we have taken a multidisciplinary approach to delicately dissect this relationship.
Through our findings, we aim not only to captivate the academic community with a surprising statistical phenomenon but also to underscore the numerous nuances underpinning human behavior. As we embark on this scholarly journey, we do so with an astute awareness of the quirks and idiosyncrasies inherent in both research and human nature. After all, when navigating uncharted statistical territory, a touch of humor and an affinity for diving into the unexpected can often prove to be invaluable companions.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The statistical analysis revealed a noteworthy correlation between Republican votes for Senators in Virginia and Google searches for 'hottest man on earth' during the period 2004 to 2020. The correlation coefficient, r, was determined to be 0.8431649, indicating a strong positive relationship between these seemingly disparate variables. This finding was supported by an r-squared value of 0.7109271, signifying that approximately 71.1% of the variation in Republican votes for Senators in Virginia could be explained by the frequency of Google searches for 'hottest man on earth'. With a significance level of p < 0.05, the observed correlation was deemed statistically significant.

To visually capture this unexpected association, a scatterplot (Fig. 1) was constructed to depict the relationship between Republican votes for Senators in Virginia and Google searches for 'hottest man on earth' over the analyzed time frame. The scatterplot vividly illustrates the robust positive correlation, serving as a testament to the intriguing nature of this investigation.

Our research team's discovery of this striking relationship not only adds a lighthearted dimension to the realm of political analysis but also prompts a reevaluation of the factors influencing voter behavior. The implications of this correlation extend beyond the immediate realms of political science and online search behavior, resonating with the underlying complexities of human decision-making. The unexpected convergence of red states and red-hot searches has indeed unearthed a quirk of human behavior that demands further exploration and appreciation.

In light of these findings, we underscore the importance of embracing unconventional inquiries and unearthing unexpected associations. The intersection of political preferences and pop culture curiosities, though initially whimsical, offers valuable insights into the intricate tapestry of human behavior. In continuing our scholarly pursuit, we remain committed to unraveling the enigmatic connections that underlie statistical phenomena, armed with an unwavering embrace of the unexpected and an appreciation for the delightful surprises that statistical inquiry can yield.


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 Republican votes for Senators in Virginia and Google searches for 'hottest man on earth'. 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]]
"Red States and Red Hot Searches: A Correlational Analysis of Republican Senator Votes in Virginia and Google Searches for 'Hottest Man on Earth'"

[[ABSTRACT]]
This study investigates the surprising correlation between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, our research team calculated a correlation coefficient of 0.8431649 with a significance level of p < 0.05. Our analysis offers insight into the unexpected behavior of voters and their online search patterns, shedding light on the subtle dynamics between political preferences and pop culture interests. The findings not only highlight the complexities of human behavior but also emphasize the need for multidisciplinary approaches in understanding socio-political phenomena.

[[LITERATURE REVIEW]]
The connection between political voting behavior and seemingly unrelated factors has been a subject of scholarly interest in recent years. Smith (2016) examined the influence of social media on political attitudes and found that online activities can influence individual political preferences. Similarly, Doe (2018) explored the impact of digital footprints on election outcomes, revealing the potential for online search patterns to reflect voter sentiments.
Moving beyond the traditional realm of political science, our study ventures into uncharted territory by investigating the connection between Republican votes for Senators in Virginia and Google searches for 'hottest man on earth'. While this inquiry may seem whimsical at first glance, it touches upon the broader theme of how online behaviors intersect with political inclinations.
In the realm of popular culture and its impact on societal dynamics, Jones (2017) analyzed the influence of celebrity endorsements on political campaigns, highlighting the captivating effect of cultural figures on voter engagement. Additionally, "The Influential Power of Pop Culture" (Roberts, 2019) delves into the intricate ways in which popular culture seeps into the fabric of political landscapes, offering a lens through which to view the complex interplay between seemingly disparate domains.
Expanding upon this line of inquiry, our study steps into the realm of fictitious realms that may seemingly hold parallels to our investigation. "The Hotter, the Better: A Search for Political Romance" (Winters, 2020) provides a lighthearted exploration of the unforeseen connections between personal attractions and political inclinations, albeit within the context of fiction. Further, "Politics Under the Microscope: An Investigative Journey" (Johnson, 2018) delivers a captivating blend of fact and fiction, teasing at the blurred boundaries between objective analysis and imaginative storytelling.
As we delve deeper into the web of interconnected influences, we acknowledge the need for a whimsical touch to our exploration of this unexpected correlation. It is within this spirit that we draw inspiration from the unlikeliest of sources, including the fine print on shampoo bottles and the peculiar quirks of everyday life. After all, it is in the unexpected and seemingly absurd that we often uncover the most dazzling insights.

[[RESULTS]]
The statistical analysis revealed a noteworthy correlation between Republican votes for Senators in Virginia and Google searches for 'hottest man on earth' during the period 2004 to 2020. The correlation coefficient, r, was determined to be 0.8431649, indicating a strong positive relationship between these seemingly disparate variables. This finding was supported by an r-squared value of 0.7109271, signifying that approximately 71.1% of the variation in Republican votes for Senators in Virginia could be explained by the frequency of Google searches for 'hottest man on earth'. With a significance level of p < 0.05, the observed correlation was deemed statistically significant.
To visually capture this unexpected association, a scatterplot (Fig. 1) was constructed to depict the relationship between Republican votes for Senators in Virginia and Google searches for 'hottest man on earth' over the analyzed time frame. The scatterplot vividly illustrates the robust positive correlation, serving as a testament to the intriguing nature of this investigation.
Our research team's discovery of this striking relationship not only adds a lighthearted dimension to the realm of political analysis but also prompts a reevaluation of the factors influencing voter behavior. The implications of this correlation extend beyond the immediate realms of political science and online search behavior, resonating with the underlying complexities of human decision-making. The unexpected convergence of red states and red-hot searches has indeed unearthed a quirk of human behavior that demands further exploration and appreciation.
In light of these findings, we underscore the importance of embracing unconventional inquiries and unearthing unexpected associations. The intersection of political preferences and pop culture curiosities, though initially whimsical, offers valuable insights into the intricate tapestry of human behavior. In continuing our scholarly pursuit, we remain committed to unraveling the enigmatic connections that underlie statistical phenomena, armed with an unwavering embrace of the unexpected and an appreciation for the delightful surprises that statistical inquiry can yield.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The continuation of the unconventional correlation uncovered in our study not only provides a tantalizingly puzzling connection between political voting behavior and peculiars of pop culture, but also underscores the need for a multidisciplinary approach to comprehend the idiosyncrasies of human behavior. The unexpected relationship between Republican votes for Senators in Virginia and Google searches for 'hottest man on earth' supports the broader scholarly narrative of how seemingly unrelated factors can intertwine in the tapestry of socio-political phenomena.

In reflecting upon the whimsical nature of this inquiry, we are reminded of the light-hearted observations made by Winters (2020) in their exploration of the unforeseen connections between personal attractions and political inclinations. While Winters' work may be a fictitious representation, our findings appear to resonate with the underlying theme of the unforeseen interplay between individual inclinations and political affiliations. As Johnson (2018) highlighted, the boundaries between objective analysis and imaginative storytelling may not always be as distinct as we assume, inspiring us to approach our results with open-minded curiosity.

The statistical significance of the correlation coefficient, r = 0.8431649, distinctly mirrors the findings of Smith (2016) on the influential impact of social media on political attitudes. While our investigation pertains to search patterns rather than social media activities, the common thread of digital footprints reflecting political preferences echoes in our discoveries. Thus, our results fortify the prior research on the potential for online behaviors to mirror voter sentiments, albeit in a delightful and unanticipated context.

In a similar vein, the captivating effect of cultural figures on voter engagement, as highlighted by Jones (2017), seems to find an unexpected parallel in our investigation. The robust positive relationship between Republican votes for Senators in Virginia and Google searches for 'hottest man on earth' elucidates the enthralling blend of popular culture curiosities and political inclinations. Therefore, our findings tangentially affirm the captivating influence of popular culture on voter engagement, echoing the spirit of Roberts' (2019) analysis on the influential power of pop culture in shaping political landscapes.

As we navigate the captivating conundrum of the unexpected convergence of red states and red-hot searches, we stand in awe of the whimsical surprise that statistical inquiry can yield. The correlation between these seemingly disparate variables has indeed unveiled a quirk of human behavior that is not only fascinating but also demands further exploration and appreciation. Thus, our study underscores the invaluable insights gleaned from embracing unconventional inquiries and unearthing the unexpected associations, ultimately enriching our understanding of statistical phenomena.


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 Republican votes for Senators in Virginia and Google searches for 'hottest man on earth'. 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]]
"Red States and Red Hot Searches: A Correlational Analysis of Republican Senator Votes in Virginia and Google Searches for 'Hottest Man on Earth'"

[[ABSTRACT]]
This study investigates the surprising correlation between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, our research team calculated a correlation coefficient of 0.8431649 with a significance level of p < 0.05. Our analysis offers insight into the unexpected behavior of voters and their online search patterns, shedding light on the subtle dynamics between political preferences and pop culture interests. The findings not only highlight the complexities of human behavior but also emphasize the need for multidisciplinary approaches in understanding socio-political phenomena.

[[INTRDUCTION]]
The intersection of politics and popular culture has long been a source of fascination for researchers and laypeople alike. From T-shirts emblazoned with political slogans to viral memes featuring political figures, it is clear that these seemingly distinct realms often intertwine in unexpected ways. Our study delves into a particularly intriguing example of this phenomenon, exploring the relationship between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth'. It is not only a marriage of red states and red hot searches but also a curious case meriting a closer statistical examination.
Political scientists have traditionally focused on factors such as party affiliation, ideology, and candidate characteristics to explain voting behavior. However, in an era marked by the increasing digitalization of daily life, the role of online activities in shaping political trends has become increasingly salient. Alongside this trend, researchers across disciplines have recognized the value of harnessing digital footprints as valuable sources of insight into the intricacies of human behavior.
With this context in mind, our research seeks to navigate uncharted territory at the intersection of political science and online search behavior. In examining the Google searches for 'hottest man on earth', we address a question that has not been previously explored in academic literature. This unexpected and somewhat whimsical inquiry offers a unique opportunity to shed light on the intricate and often puzzling confluence of political preferences and pop culture curiosities.
The unexpected discovery of the notable correlation coefficient between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020 not only raises eyebrows but also presents a conundrum that our rigorous statistical analysis aims to untangle. By utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, we have taken a multidisciplinary approach to delicately dissect this relationship.
Through our findings, we aim not only to captivate the academic community with a surprising statistical phenomenon but also to underscore the numerous nuances underpinning human behavior. As we embark on this scholarly journey, we do so with an astute awareness of the quirks and idiosyncrasies inherent in both research and human nature. After all, when navigating uncharted statistical territory, a touch of humor and an affinity for diving into the unexpected can often prove to be invaluable companions.

[[RESULTS]]
The statistical analysis revealed a noteworthy correlation between Republican votes for Senators in Virginia and Google searches for 'hottest man on earth' during the period 2004 to 2020. The correlation coefficient, r, was determined to be 0.8431649, indicating a strong positive relationship between these seemingly disparate variables. This finding was supported by an r-squared value of 0.7109271, signifying that approximately 71.1% of the variation in Republican votes for Senators in Virginia could be explained by the frequency of Google searches for 'hottest man on earth'. With a significance level of p < 0.05, the observed correlation was deemed statistically significant.
To visually capture this unexpected association, a scatterplot (Fig. 1) was constructed to depict the relationship between Republican votes for Senators in Virginia and Google searches for 'hottest man on earth' over the analyzed time frame. The scatterplot vividly illustrates the robust positive correlation, serving as a testament to the intriguing nature of this investigation.
Our research team's discovery of this striking relationship not only adds a lighthearted dimension to the realm of political analysis but also prompts a reevaluation of the factors influencing voter behavior. The implications of this correlation extend beyond the immediate realms of political science and online search behavior, resonating with the underlying complexities of human decision-making. The unexpected convergence of red states and red-hot searches has indeed unearthed a quirk of human behavior that demands further exploration and appreciation.
In light of these findings, we underscore the importance of embracing unconventional inquiries and unearthing unexpected associations. The intersection of political preferences and pop culture curiosities, though initially whimsical, offers valuable insights into the intricate tapestry of human behavior. In continuing our scholarly pursuit, we remain committed to unraveling the enigmatic connections that underlie statistical phenomena, armed with an unwavering embrace of the unexpected and an appreciation for the delightful surprises that statistical inquiry can yield.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study has yielded remarkable insights into the curious junction of political affiliations and popular culture interests. The substantial correlation between Republican votes for Senators in Virginia and Google searches for 'hottest man on earth' from 2004 to 2020 is not only statistically robust but also ripe with potential implications, showcasing the whimsical yet captivating nature of academic inquiry. This unexpected finding serves as a reminder that, in the realm of statistical analysis, even the most lighthearted and seemingly unrelated variables can converge in ways that defy conventional wisdom, adding a dash of levity to the often serious domain of research. Our journey into this uncharted territory has not only broadened our understanding of voter behavior but also underscored the multifaceted dynamics that underpin human decision-making. As we reflect on the vibrant tapestry of statistical nuances and the unexpected delights of unraveling correlations, we are compelled to quip that perhaps, in the realm of statistical inquiry, "hottest trends" can indeed transcend the confines of pop culture and permeate the intricate fabric of political landscapes. With this, we assert that, in light of this compelling discovery, further research in this area is decidedly unnecessary, as we have unearthed a statistical gem that gleams with the sparkle of unpredictability and grins with the wry humor of statistical discovery – a fervent reminder that in the world of research, the unexpected often yields the most delightful insights.


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 Red States and Red Hot Searches: A Correlational Analysis of Republican Senator Votes in Virginia and Google Searches for 'Hottest Man on Earth'. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Political Behavior and Internet Trends


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 Red States and Red Hot Searches: A Correlational Analysis of Republican Senator Votes in Virginia and Google Searches for 'Hottest Man on Earth'. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Political and Cultural Research Integration (CPCRI)


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 Red States and Red Hot Searches: A Correlational Analysis of Republican Senator Votes in Virginia and Google Searches for 'Hottest Man on Earth' with an abstract of This study investigates the surprising correlation between Republican votes for Senators in Virginia and the frequency of Google searches for 'hottest man on earth' from 2004 to 2020. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, our research team calculated a correlation coefficient of 0.8431649 with a significance level of p < 0.05. Our analysis offers insight into the unexpected behavior of voters and their online search patterns, shedding light on the subtle dynamics between political preferences and pop culture interests. The findings not only highlight the complexities of human behavior but also emphasize the need for multidisciplinary approaches in understanding socio-political phenomena.

ChatGPT:

Virginia, Republican Senators, Google searches, 'hottest man on earth', correlation, 2004-2020, MIT Election Data and Science Lab, Harvard Dataverse, Google Trends, voter behavior, online search patterns, political preferences, pop culture interests, multidisciplinary approach, socio-political phenomena

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



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Data details

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

Google searches for 'hottest man on earth'
Detailed data title: Relative volume of Google searches for 'hottest man on earth' (Worldwide, without quotes)
Source: Google Trends
Additional Info: Relative search volume (not absolute numbers)

See what else correlates with Google searches for 'hottest man on earth'

Correlation r = 0.8431649 (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 = 0.7109271 (Coefficient of determination)
This means 71.1% of the change in the one variable (i.e., Google searches for 'hottest man on earth') is predictable based on the change in the other (i.e., Votes for Republican Senators in Virginia) over the 6 years from 2004 through 2020.

p < 0.05, which statistically significant(Null hypothesis significance test)
The p-value is 0.035. 0.0349670058055222140000000000
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 0.84 in 3.5% of random cases. Said differently, if you correlated 29 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.

[ 0.1, 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.
200620082012201420182020
Votes for Republican Senators in Virginia (Percentage of votes)49.200833.728546.960848.338441.007543.9083
Google searches for 'hottest man on earth' (Rel. search volume)12.33336.3333317.166717.33338.512.5833




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.
  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([49.2008,33.7285,46.9608,48.3384,41.0075,43.9083,])
array_2 = np.array([12.3333,6.33333,17.1667,17.3333,8.5,12.5833,])
array_1_name = "Votes for Republican Senators in Virginia"
array_2_name = "Google searches for 'hottest man on earth'"

# 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: 5447 · Black Variable ID: 26476 · Red Variable ID: 1430
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