Spurious correlation #4,394 · 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 Alaska and the second variable is Google searches for 'what color should I paint my house'. The chart goes from 2004 to 2020, and the two variables track closely in value over that time.

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 Alaska and the second variable is Google searches for 'what color should I paint my house'. The chart goes from 2004 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As more Senators were elected, there was a surge in patriotic pride. Alaskans, feeling a strong connection to their political representatives, were inspired to showcase their support in the most colorful way possible. It's a red, white, and blue wave of home improvement sweeping across the state!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a scenic Alaskan neighborhood adorned with colorful Republican flags flying proudly above the finely manicured yards. Homeowners can be seen outside, browsing their phones with Google searches open, contemplating the perfect color to paint their houses. The streets are lined with vibrant shades of red, white, and blue, reflecting the patriotic spirit and political affiliation of the community. The scene should exude a high-tech aesthetic, integrating modern elements seamlessly into the traditional Alaskan setting. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Republican votes for Senators in Alaska and Google searches for 'what color should I paint my house'. 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: Glitch art High-tech Pop art Oragami Psychedelic
ChatGPT: High-tech

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Republican votes for Senators in Alaska and Google searches for 'what color should I paint my house', in the following situation: As more Senators were elected, there was a surge in patriotic pride. Alaskans, feeling a strong connection to their political representatives, were inspired to showcase their support in the most colorful way possible. It's a red, white, and blue wave of home improvement sweeping across the state!. Keep the description simple.
ChatGPT: In a picturesque neighborhood in Alaska, colorful flags flutter proudly in front yards, representing the Republican votes for Senators. Alongside these flags, homeowners stand outside, Google searches open on their phones, pondering the question "What color should I paint my house?" The streets are filled with the vibrant red, white, and blue hues, symbolizing the patriotic pride and political connection felt by Alaskans.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ High-tech ] and depicting this scene: In a picturesque neighborhood in Alaska, colorful flags flutter proudly in front yards, representing the Republican votes for Senators. Alongside these flags, homeowners stand outside, Google searches open on their phones, pondering the question "What color should I paint my house?" The streets are filled with the vibrant red, white, and blue hues, symbolizing the patriotic pride and political connection felt by Alaskans. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a scenic Alaskan neighborhood adorned with colorful Republican flags flying proudly above the finely manicured yards. Homeowners can be seen outside, browsing their phones with Google searches open, contemplating the perfect color to paint their houses. The streets are lined with vibrant shades of red, white, and blue, reflecting the patriotic spirit and political affiliation of the community. The scene should exude a high-tech aesthetic, integrating modern elements seamlessly into the traditional Alaskan setting.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} 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 Republican votes for Senators in Alaska caused what color should I paint my house (Google searches for 'what color should I paint my house') to increase.

AI academic paper

(Because p < 0.05)

Red Senate, Green Houses: The Correlation Between Republican Votes in Alaska and Google Searches for 'What Color Should I Paint My House'

The Journal of Eclectic Political Analysis

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} 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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Alaska and Google searches for 'what color should I paint my house'. Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
Red Senate, Green Houses: The Correlation Between Republican Votes in Alaska and Google Searches for 'What Color Should I Paint My House'

[[ABSTRACT]]
In this paper, we present the surprising connection between political leanings and home improvement ponderings. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, we explored the relationship between Republican votes for Senators in Alaska and the frequency of Google searches for the question "What color should I paint my house". To our astonishment, we found a positively delightful correlation coefficient of 0.8720785 and a p-value less than 0.05 for the period of 2004 to 2020. Our findings suggest that while politicians may often be painting their opponents in a negative light, their constituents are more concerned with painting their houses in a positive hue. This research not only showcases the marvels of unexpected correlations but also underscores the importance of bringing a touch of whimsy to the world of data analysis. So next time you're pondering whether to go blue, red, or green, remember that your choice might just be influenced by more than just your political views.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of politics and home improvement has long been an underexplored area of research. While one may not immediately see the connection between voting behavior and interior décor contemplations, our study aims to uncover the surprising correlations that exist in this seemingly unrelated realm.
In recent years, researchers have taken a keen interest in utilizing big data to uncover hidden relationships between seemingly disparate variables. Our study follows in this tradition, seeking to shed light on the nuances of human behavior and decision-making by examining the relationship between Republican votes for Senators in Alaska and the Google searches for the popular query "What color should I paint my house".
As we embark on this unconventional journey of inquiry, it is important to acknowledge the novelty and unexpected nature of our investigation. The idea that political affiliations could potentially influence one's proclivity towards particular color palettes for home renovation projects may initially provoke skepticism, even amusement. However, as we delve into the data and statistical analysis, the surprising connections that emerge are nothing short of delightful.
While the correlation between political leanings and home decorating preferences may seem whimsical at first glance, our findings stand to offer valuable insights into the intricate tapestry of human behavior. Through this research, we hope to not only expand the boundaries of data analysis but also bring a lighthearted touch to the often somber world of academic inquiry.
So, join us on this curious expedition as we uncover the connections between red Senate votes and the inclination towards green houses, all while maintaining a dutiful devotion to the principles of rigorous scientific inquiry. After all, in the words of Oscar Wilde, "We are all in the gutter, but some of us are looking at the paint swatches."

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The pursuit of unexpected correlations has been a focal point of research in recent years. Smith et al. (2015) delved into the exploration of unlikely associations between political behavior and seemingly unrelated consumer choices, highlighting the potential for hidden connections in the vast expanse of data. Similarly, Doe and Jones (2018) emphasized the value of unearthing unconventional relationships through thorough data analysis, paving the way for our own delightfully peculiar investigation.

As we venture further into this wacky world of political votes and paint preferences, it is essential to consider the broader literary landscape of research that may offer insights, albeit indirect, into our chosen inquiry. "The Psychology of Political Behavior" by Johnson (2017) may not explicitly delve into color choices for home design, but it does offer a compelling study of the underlying psychological drivers that influence voting behavior, a dimension that undoubtedly intersects with the realm of home improvement ponderings.

Now, let's take a whimsical turn into the world of fiction, where curious connections abound. "The Colors of Magic" by Pratchett (1983) may not provide empirical evidence of political affiliations influencing paint preferences, but its exploration of magical realms and quirkily colored landscapes certainly sparks the imagination. On a similarly fantastical note, "The Secret Lives of Color" by St. Clair (2017) offers a sensational romp through the captivating history of colors, infusing a dash of vibrancy into the otherwise solemn halls of academic literature.

In our foray into the unconventional, we stumbled upon a series of riveting social media posts that seemed strangely relevant to our inquiry. One particularly intriguing tweet by @HomeDecorEnthusiast proclaimed, "Just like choosing a political candidate, picking the right paint color is all about finding the perfect match for your values and aspirations #RedBlueGreen #HomeVote". While a tweet may not hold the weight of scholarly evidence, it certainly offers a quirky perspective on the intersection of politics and paint palettes.

With this hodgepodge of scholarly musings, fantastical exploits, and online musings in mind, we set off to unravel the unexpected tapestry of connections between Republican votes in Alaska and Google searches for 'What color should I paint my house'. The journey may be unconventional, but as we uncover the colorful threads that weave through these diverse domains, we invite our readers to revel in the sheer joy of unexpected correlations. As Lewis Carroll astutely observed, "Why, sometimes I've believed as many as six impossible things before breakfast," and who's to say that a correlation between red Senate votes and the inclination towards green houses isn't one of them?

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Alaska and Google searches for 'what color should I paint my house'. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and 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 Senate, Green Houses: The Correlation Between Republican Votes in Alaska and Google Searches for 'What Color Should I Paint My House'

[[ABSTRACT]]
In this paper, we present the surprising connection between political leanings and home improvement ponderings. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, we explored the relationship between Republican votes for Senators in Alaska and the frequency of Google searches for the question "What color should I paint my house". To our astonishment, we found a positively delightful correlation coefficient of 0.8720785 and a p-value less than 0.05 for the period of 2004 to 2020. Our findings suggest that while politicians may often be painting their opponents in a negative light, their constituents are more concerned with painting their houses in a positive hue. This research not only showcases the marvels of unexpected correlations but also underscores the importance of bringing a touch of whimsy to the world of data analysis. So next time you're pondering whether to go blue, red, or green, remember that your choice might just be influenced by more than just your political views.

[[INTRODUCTION]]
The intersection of politics and home improvement has long been an underexplored area of research. While one may not immediately see the connection between voting behavior and interior décor contemplations, our study aims to uncover the surprising correlations that exist in this seemingly unrelated realm.
In recent years, researchers have taken a keen interest in utilizing big data to uncover hidden relationships between seemingly disparate variables. Our study follows in this tradition, seeking to shed light on the nuances of human behavior and decision-making by examining the relationship between Republican votes for Senators in Alaska and the Google searches for the popular query "What color should I paint my house".
As we embark on this unconventional journey of inquiry, it is important to acknowledge the novelty and unexpected nature of our investigation. The idea that political affiliations could potentially influence one's proclivity towards particular color palettes for home renovation projects may initially provoke skepticism, even amusement. However, as we delve into the data and statistical analysis, the surprising connections that emerge are nothing short of delightful.
While the correlation between political leanings and home decorating preferences may seem whimsical at first glance, our findings stand to offer valuable insights into the intricate tapestry of human behavior. Through this research, we hope to not only expand the boundaries of data analysis but also bring a lighthearted touch to the often somber world of academic inquiry.
So, join us on this curious expedition as we uncover the connections between red Senate votes and the inclination towards green houses, all while maintaining a dutiful devotion to the principles of rigorous scientific inquiry. After all, in the words of Oscar Wilde, "We are all in the gutter, but some of us are looking at the paint swatches."

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To explore the intriguing relationship between Republican votes for Senators in Alaska and the frequency of Google searches for the query "What color should I paint my house", our research team embarked on a data-driven escapade that would make even the most intrepid explorers of the scientific world envious.

Firstly, we obtained historical election data from the MIT Election Data and Science Lab, providing us with a treasure trove of information on Republican votes in the great state of Alaska from 2004 to 2020. This data was then meticulously combed through, like a keen gardener tending to their prized petunias, to isolate the voting patterns that would serve as the cornerstone of our analysis.

Simultaneously, we delved into the vast expanse of Google Trends, navigating the virtual jungle of search queries with the grace and precision of a skilled navigator, to unearth the volume of searches pertaining to the ponderous question of home coloring conundrums. "What color should I paint my house?" reverberated through our screens as we sifted through the data like archaeologists unearthing the lost treasures of antiquity.

Following this dexterous data collection, our team harnessed the almighty powers of statistical analysis software, wielding the tools of correlation coefficients and p-values like the mystical instruments of insight they are, to illuminate the intricacies of the relationship between political proclivities and domestic design musings.

In the spirit of scientific rigor, our analysis employed robust statistical methods to ascertain the strength and significance of the observed correlation. As we navigated the choppy waters of hypothesis testing and regression analysis, we remained steadfast in our pursuit of understanding the unexpected link between political affiliations and color contemplations.

Our resilient journey through the vast seas of data and statistical models yielded a positively delightful correlation coefficient of 0.8720785, entailing a p-value less than 0.05 and prompting exclamations of wonder from our research team that could have rivalled those of a gleeful astronomer discovering a new celestial body. These findings not only elicited surprise but also sparked a newfound appreciation for the quirkiness of human behavior and the whimsical pathways along which data can lead us.

In summary, our methodology hinges upon the tenets of thorough data collection, meticulous statistical analysis, and a healthy dose of curiosity, culminating in the revelation of a correlation as unexpected as stumbling upon a garden gnome in the midst of a political rally. So, with our compasses of scientific inquiry in hand, we traverse the uncharted territories of correlation and causation to shine a light on the enigmatic connections between red Senate votes and the inclination towards green houses. After all, in the words of Sherlock Holmes, "The game is afoot, Watson!"

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Alaska and Google searches for 'what color should I paint my house'. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Red Senate, Green Houses: The Correlation Between Republican Votes in Alaska and Google Searches for 'What Color Should I Paint My House'

[[ABSTRACT]]
In this paper, we present the surprising connection between political leanings and home improvement ponderings. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, we explored the relationship between Republican votes for Senators in Alaska and the frequency of Google searches for the question "What color should I paint my house". To our astonishment, we found a positively delightful correlation coefficient of 0.8720785 and a p-value less than 0.05 for the period of 2004 to 2020. Our findings suggest that while politicians may often be painting their opponents in a negative light, their constituents are more concerned with painting their houses in a positive hue. This research not only showcases the marvels of unexpected correlations but also underscores the importance of bringing a touch of whimsy to the world of data analysis. So next time you're pondering whether to go blue, red, or green, remember that your choice might just be influenced by more than just your political views.

[[LITERATURE REVIEW]]
The pursuit of unexpected correlations has been a focal point of research in recent years. Smith et al. (2015) delved into the exploration of unlikely associations between political behavior and seemingly unrelated consumer choices, highlighting the potential for hidden connections in the vast expanse of data. Similarly, Doe and Jones (2018) emphasized the value of unearthing unconventional relationships through thorough data analysis, paving the way for our own delightfully peculiar investigation.
As we venture further into this wacky world of political votes and paint preferences, it is essential to consider the broader literary landscape of research that may offer insights, albeit indirect, into our chosen inquiry. "The Psychology of Political Behavior" by Johnson (2017) may not explicitly delve into color choices for home design, but it does offer a compelling study of the underlying psychological drivers that influence voting behavior, a dimension that undoubtedly intersects with the realm of home improvement ponderings.
Now, let's take a whimsical turn into the world of fiction, where curious connections abound. "The Colors of Magic" by Pratchett (1983) may not provide empirical evidence of political affiliations influencing paint preferences, but its exploration of magical realms and quirkily colored landscapes certainly sparks the imagination. On a similarly fantastical note, "The Secret Lives of Color" by St. Clair (2017) offers a sensational romp through the captivating history of colors, infusing a dash of vibrancy into the otherwise solemn halls of academic literature.
In our foray into the unconventional, we stumbled upon a series of riveting social media posts that seemed strangely relevant to our inquiry. One particularly intriguing tweet by @HomeDecorEnthusiast proclaimed, "Just like choosing a political candidate, picking the right paint color is all about finding the perfect match for your values and aspirations #RedBlueGreen #HomeVote". While a tweet may not hold the weight of scholarly evidence, it certainly offers a quirky perspective on the intersection of politics and paint palettes.
With this hodgepodge of scholarly musings, fantastical exploits, and online musings in mind, we set off to unravel the unexpected tapestry of connections between Republican votes in Alaska and Google searches for 'What color should I paint my house'. The journey may be unconventional, but as we uncover the colorful threads that weave through these diverse domains, we invite our readers to revel in the sheer joy of unexpected correlations. As Lewis Carroll astutely observed, "Why, sometimes I've believed as many as six impossible things before breakfast," and who's to say that a correlation between red Senate votes and the inclination towards green houses isn't one of them?

[[RESULTS]]
The results of our analysis revealed a remarkably strong positive correlation between Republican votes for Senators in Alaska and the frequency of Google searches for the inquiry "What color should I paint my house". The correlation coefficient of 0.8720785 indicates a robust relationship between the two variables. Additionally, the observed R-squared value of 0.7605209 suggests that approximately 76.05% of the variance in house paint color searches can be explained by the variation in Republican votes.
To visually capture this striking association, we present Fig. 1, a scatterplot that vividly depicts the positive relationship between the mentioned variables. This figure serves as a testament to the power of data analysis in unearthing the unexpected and the seemingly whimsical connections that underlie human behavior.
The statistical significance of our findings is further underscored by a p-value less than 0.05, indicating a high level of confidence in the observed correlation. This result supports the notion that the relationship between Republican votes in Alaska and the quest for home color inspiration is not merely a serendipitous occurrence but rather a compelling pattern embedded within the data.
These findings offer a captivating glimpse into the quirkier side of human decision-making, exemplifying the intricate interplay between political inclinations and aesthetic preferences. While one may initially assume that political choices would have little bearing on matters of interior design, our results challenge this assumption, highlighting the unforeseen ways in which individual attitudes and behaviors can intersect across seemingly unrelated domains.
In conclusion, our study not only sheds light on the surprising correlation between political leanings and home improvement considerations but also serves as a whimsical reminder of the abundant curiosities waiting to be unearthed within the world of data analysis. As Oscar Wilde aptly noted, "We are all in the gutter, but some of us are looking at the paint swatches."

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The correlation between Republican votes for Senators in Alaska and Google searches for the inquiry "What color should I paint my house" has unveiled a delightful tapestry of unexpected connections. Our findings not only solidify the existence of this peculiar relationship but also add a whimsical twist to the world of statistical analysis. As we dive into the discussion of our results, we cannot help but marvel at the wacky yet fascinating implications of our research.

Drawing upon the literature review that showcased the value of unearthing unconventional relationships, our study underscores the significance of delving into seemingly disparate realms to unveil surprising connections. Smith et al. (2015) and Doe and Jones (2018) laid the groundwork for our investigation by emphasizing the potential for uncovering delightful oddities within data, which we have certainly accomplished in our study. Furthermore, the tweet by @HomeDecorEnthusiast, while not an academically rigorous source, reflects the evolving public discourse on the intersection of politics and paint preferences, reinforcing the societal relevance of our research.

Our results not only support the prior research by showcasing a robust correlation between Republican votes and home color inquiries but also offer a whimsical lens through which to view the intricate nuances of human decision-making. In the grand tapestry of human behavior, it appears that political inclinations and aesthetic preferences intertwine in unexpected ways, creating an eccentric yet compelling web of influences.

Delving into the comical yet captivating nature of our findings, we cannot help but be reminded of the insightful words of Lewis Carroll and the whimsical worlds crafted by authors such as Terry Pratchett. As we navigate the realm of unexpected correlations, we urge our fellow researchers to embrace the wackiness that may lurk beneath the surface of data analysis. After all, who's to say that a correlation between political votes and the inclination towards specific house paint colors isn't one of those "six impossible things before breakfast"?

In the spirit of embracing the unexpected and finding joy in the offbeat, our study not only contributes to the scholarly discourse on correlations and human behavior but also invites a touch of whimsy into the otherwise austere halls of academia. For as Oscar Wilde so aptly noted, "We are all in the gutter, but some of us are looking at the paint swatches."

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Alaska and Google searches for 'what color should I paint my house'. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Red Senate, Green Houses: The Correlation Between Republican Votes in Alaska and Google Searches for 'What Color Should I Paint My House'

[[ABSTRACT]]
In this paper, we present the surprising connection between political leanings and home improvement ponderings. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, we explored the relationship between Republican votes for Senators in Alaska and the frequency of Google searches for the question "What color should I paint my house". To our astonishment, we found a positively delightful correlation coefficient of 0.8720785 and a p-value less than 0.05 for the period of 2004 to 2020. Our findings suggest that while politicians may often be painting their opponents in a negative light, their constituents are more concerned with painting their houses in a positive hue. This research not only showcases the marvels of unexpected correlations but also underscores the importance of bringing a touch of whimsy to the world of data analysis. So next time you're pondering whether to go blue, red, or green, remember that your choice might just be influenced by more than just your political views.

[[INTRDUCTION]]
The intersection of politics and home improvement has long been an underexplored area of research. While one may not immediately see the connection between voting behavior and interior décor contemplations, our study aims to uncover the surprising correlations that exist in this seemingly unrelated realm.
In recent years, researchers have taken a keen interest in utilizing big data to uncover hidden relationships between seemingly disparate variables. Our study follows in this tradition, seeking to shed light on the nuances of human behavior and decision-making by examining the relationship between Republican votes for Senators in Alaska and the Google searches for the popular query "What color should I paint my house".
As we embark on this unconventional journey of inquiry, it is important to acknowledge the novelty and unexpected nature of our investigation. The idea that political affiliations could potentially influence one's proclivity towards particular color palettes for home renovation projects may initially provoke skepticism, even amusement. However, as we delve into the data and statistical analysis, the surprising connections that emerge are nothing short of delightful.
While the correlation between political leanings and home decorating preferences may seem whimsical at first glance, our findings stand to offer valuable insights into the intricate tapestry of human behavior. Through this research, we hope to not only expand the boundaries of data analysis but also bring a lighthearted touch to the often somber world of academic inquiry.
So, join us on this curious expedition as we uncover the connections between red Senate votes and the inclination towards green houses, all while maintaining a dutiful devotion to the principles of rigorous scientific inquiry. After all, in the words of Oscar Wilde, "We are all in the gutter, but some of us are looking at the paint swatches."

[[RESULTS]]
The results of our analysis revealed a remarkably strong positive correlation between Republican votes for Senators in Alaska and the frequency of Google searches for the inquiry "What color should I paint my house". The correlation coefficient of 0.8720785 indicates a robust relationship between the two variables. Additionally, the observed R-squared value of 0.7605209 suggests that approximately 76.05% of the variance in house paint color searches can be explained by the variation in Republican votes.
To visually capture this striking association, we present Fig. 1, a scatterplot that vividly depicts the positive relationship between the mentioned variables. This figure serves as a testament to the power of data analysis in unearthing the unexpected and the seemingly whimsical connections that underlie human behavior.
The statistical significance of our findings is further underscored by a p-value less than 0.05, indicating a high level of confidence in the observed correlation. This result supports the notion that the relationship between Republican votes in Alaska and the quest for home color inspiration is not merely a serendipitous occurrence but rather a compelling pattern embedded within the data.
These findings offer a captivating glimpse into the quirkier side of human decision-making, exemplifying the intricate interplay between political inclinations and aesthetic preferences. While one may initially assume that political choices would have little bearing on matters of interior design, our results challenge this assumption, highlighting the unforeseen ways in which individual attitudes and behaviors can intersect across seemingly unrelated domains.
In conclusion, our study not only sheds light on the surprising correlation between political leanings and home improvement considerations but also serves as a whimsical reminder of the abundant curiosities waiting to be unearthed within the world of data analysis. As Oscar Wilde aptly noted, "We are all in the gutter, but some of us are looking at the paint swatches."

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In closing, our study has brought to light the unexpectedly delightful connection between political preferences and the colorful contemplations of home improvement. The robust correlation we discovered between Republican votes for Senators in Alaska and the frequency of Google searches for house paint color inspirations is not just statistically significant – it's a splash of amusement in the otherwise serious ocean of data analysis.

The fact that one's penchant for politicians of a certain hue seems to align with aspirations for colorful homes is surely a revelation deserving of attention. It's as though the constituents are saying, "I may have red-state politics, but I want my house to be a lovely shade of serene green."

This correlation may, of course, raise questions about the extent to which political allegiance permeates the very walls of our homes – turning them into blue, red, or purple testaments to our leanings. And while we have not delved into the psychological mechanisms underpinning this phenomenon, we are left pondering if home painters are also casting a vote for their sense of aesthetics. But let's not paint too broad a stroke here – remember, correlation does not imply causation, and perhaps it's just a case of Alaskans being particularly inspired by their Senatorial choices.

As much as we'd love to continue exploring this unexpectedly entertaining relationship, perhaps it's time to hang up our researcher's hat for now. For truly, some mysteries are better left untarnished by further scruitiny – like the metaphysical bond between Republican votes and the question of which color to paint one's abode. In the immortal words of Wilde, "We are all in the gutter, but some of us are looking at the paint swatches" – and we've looked at them long enough.

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 Senate, Green Houses: The Correlation Between Republican Votes in Alaska and Google Searches for 'What Color Should I Paint My House'. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Eclectic Political Analysis

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Red Senate, Green Houses: The Correlation Between Republican Votes in Alaska and Google Searches for 'What Color Should I Paint My House'. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Interdisciplinary Research on Quirky Correlations (SIRQC)

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 Senate, Green Houses: The Correlation Between Republican Votes in Alaska and Google Searches for 'What Color Should I Paint My House' with an abstract of In this paper, we present the surprising connection between political leanings and home improvement ponderings. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Google Trends, we explored the relationship between Republican votes for Senators in Alaska and the frequency of Google searches for the question "What color should I paint my house". To our astonishment, we found a positively delightful correlation coefficient of 0.8720785 and a p-value less than 0.05 for the period of 2004 to 2020. Our findings suggest that while politicians may often be painting their opponents in a negative light, their constituents are more concerned with painting their houses in a positive hue. This research not only showcases the marvels of unexpected correlations but also underscores the importance of bringing a touch of whimsy to the world of data analysis. So next time you're pondering whether to go blue, red, or green, remember that your choice might just be influenced by more than just your political views.

ChatGPT:

Alaska, Republican votes, Google searches, correlation, home improvement, house painting, political leanings, MIT Election Data and Science Lab, Harvard Dataverse, Google Trends, correlation coefficient, p-value, data analysis, unexpected correlations

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

Google searches for 'what color should I paint my house'
Detailed data title: Relative volume of Google searches for 'what color should I paint my house' (Worldwide, without quotes)
Source: Google Trends
Additional Info: ^{See full details} Relative search volume (not absolute numbers)

See what else correlates with Google searches for 'what color should I paint my house'

Correlation r = 0.8720785 (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 = 0.7605209 (Coefficient of determination)
This means 76.1% of the change in the one variable (i.e., Google searches for 'what color should I paint my house') is predictable based on the change in the other (i.e., Votes for Republican Senators in Alaska) over the 6 years from 2004 through 2020.

p < 0.05, which statistically significant(Null hypothesis significance test)
The p-value is 0.023.^Show 0.0234992120498760200000000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note 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 0.87 in 2.3% of random cases. Said differently, if you correlated 43 random variables^Note Which I absolutely did.
with the same 5 degrees of freedom, ^Note 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.

[ 0.21, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} 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: ^Note 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.

	2004	2008	2010	2014	2016	2020
Votes for Republican Senators in Alaska (Percentage of votes)	48.5779	46.5229	35.553	47.9621	44.358	53.8971
Google searches for 'what color should I paint my house' (Rel. search volume)	12	9.08333	7.25	10.25	10.25	11.5833

Why this works

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.
Lack of causal connection: There is probably^Note 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.
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^Note 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.
Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} 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([48.5779,46.5229,35.553,47.9621,44.358,53.8971,])
array_2 = np.array([12,9.08333,7.25,10.25,10.25,11.5833,])
array_1_name = "Votes for Republican Senators in Alaska"
array_2_name = "Google searches for 'what color should I paint my house'"

# 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)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

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

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

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
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Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Votes for Republican Senators in Alaska
Line chart for only Google searches for 'what color should I paint my house'
AI-generated correlation image
The spurious research paper: Red Senate, Green Houses: The Correlation Between Republican Votes in Alaska and Google Searches for 'What Color Should I Paint My House'

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Correlation ID: 4394 · Black Variable ID: 26347 · Red Variable ID: 1426


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