Spurious correlation #5,806 · 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 Iowa and the second variable is Google searches for 'best mousetrap'. 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 Iowa and the second variable is Google searches for 'best mousetrap'. The chart goes from 2004 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The decrease in Republican votes for Senators in Iowa caused a decrease in Google searches for 'best mousetrap' because as the saying goes, when it comes to politics, it's all about who can 'trap' the most votes. With the demographic shift, it seems the mice weren't the only ones looking for a change in the 'House'!

^{Show image generation prompt} Model: dalle-3
Prompt: [ Cute cartoon ] A small Iowa town is depicted with a cheerful and vibrant aesthetic. The polling station, adorned with stars and stripes, prominently features a whiteboard displaying a red line graph sloping downwards to represent the decrease in Republican votes for Senators. The local hardware store's storefront exudes a cozy and inviting atmosphere, complete with potted plants and hanging flower baskets. A digital display on the window showcases a declining trend in Google searches for 'best mousetrap'. Nearby, an endearing group of mice in colorful attire gleefully watch the election results, their lively conversation evident in their animated gestures. The hardware store's window display features an array of colorful mousetraps that catch the mice's attention, adding an element of whimsy to the scene. 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 Iowa and Google searches for 'best mousetrap'. 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: High-tech An image that looks like it is a scene from 'Star Wars' Celtic art Brutalism Cute cartoon
ChatGPT: Cute cartoon

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 Iowa and Google searches for 'best mousetrap', in the following situation: The decrease in Republican votes for Senators in Iowa caused a decrease in Google searches for 'best mousetrap' because as the saying goes, when it comes to politics, it's all about who can 'trap' the most votes. With the demographic shift, it seems the mice weren't the only ones looking for a change in the 'House'!. Keep the description simple.
ChatGPT: In a small Iowa town, a polling station displays a decrease in Republican votes for Senators, as indicated by a red line graph trending downwards on a whiteboard. Meanwhile, a local hardware store's storefront features a decrease in Google searches for 'best mousetrap', as seen on a digital display on the window. Nearby, a group of mice watches the election results, eagerly discussing their quest for a change in the "House" of politics, as they browse through the hardware store's window display.

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: [ Cute cartoon ] and depicting this scene: In a small Iowa town, a polling station displays a decrease in Republican votes for Senators, as indicated by a red line graph trending downwards on a whiteboard. Meanwhile, a local hardware store's storefront features a decrease in Google searches for 'best mousetrap', as seen on a digital display on the window. Nearby, a group of mice watches the election results, eagerly discussing their quest for a change in the "House" of politics, as they browse through the hardware store's window display. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Cute cartoon ] A small Iowa town is depicted with a cheerful and vibrant aesthetic. The polling station, adorned with stars and stripes, prominently features a whiteboard displaying a red line graph sloping downwards to represent the decrease in Republican votes for Senators. The local hardware store's storefront exudes a cozy and inviting atmosphere, complete with potted plants and hanging flower baskets. A digital display on the window showcases a declining trend in Google searches for 'best mousetrap'. Nearby, an endearing group of mice in colorful attire gleefully watch the election results, their lively conversation evident in their animated gestures. The hardware store's window display features an array of colorful mousetraps that catch the mice's attention, adding an element of whimsy to the scene.

*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 a decrease in Republican votes for Senators in Iowa caused best mousetrap (Google searches for 'best mousetrap') to decrease. Include one good pun.

AI academic paper

(Because p < 0.05)

Cheesing the System: Analyzing the Correlation Between Republican Votes for Senators in Iowa and Google Searches for 'Best Mousetrap'

The Journal of Unconventional Political Science

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 Iowa and Google searches for 'best mousetrap'. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Cheesing the System: Analyzing the Correlation Between Republican Votes for Senators in Iowa and Google Searches for 'Best Mousetrap'"

[[ABSTRACT]]
When it comes to politics, demographics, and consumer behavior, there's always more than meets the eye - or in this case, more than meets the whiskers. In this study, we delve into the intriguing world of Iowa politics and rodent control, aiming to shed light on the unexpected connection between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. This research not only seeks to provide insight into electoral patterns, but also hopes to catch some valuable data on consumer preferences and their interplay with political leanings.

Our research team harnessed data from the MIT Election Data and Science Lab, Harvard Dataverse and Google Trends to tackle this, dare we say, "gouda" question. Utilizing a time span from 2004 to 2020, we discovered a robust correlation coefficient of 0.8298131 and a noteworthy significance level (p < 0.05), highlighting the statistically significant relationship between these seemingly unrelated variables. It seems that the political landscape and the hunt for an effective mousetrap may be more entwined than initially perceived. As they say, "Big cheese attracts big votes!"

Our findings not only spur further investigation into the curious connections between political sentiment and consumer goods, but also lead us to ponder the implications for future election campaigns. Beyond the data, the sheer amusement of uncovering this unexpected link reminds us of the words of wisdom: "A mouse never entraps itself, but in matters of politics and pest control, stranger bedfellows have seldom been found."

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Political scientists, ever vigilant in their pursuit of understanding the intricate dance of electoral behavior, continually seek to unravel the complex web of factors that influence voters. In this vein, our study delves into a rather unconventional intersection of political trends and consumer behavior by examining the correlation between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. As the old saying goes, "Curiosity killed the cat, but satisfaction brought it back… with a mousetrap."
The state of Iowa, known for its robust political engagement and occasional rodent incursions, offers a unique setting for exploring this unorthodox relationship. By harnessing the power of big data and a healthy dose of curiosity, we aim to shed light on whether there exists a parallel in the preferences of Iowa's electorate and their pursuit of efficient rodent control. After all, in the words of Benjamin Franklin, "Guests, like fish, begin to smell after three days… or if there's a mousetrap in plain view."
Our findings are not intended to serve as a mere exercise in eccentric empirical exploration, but rather as a testament to the unpredictability of human behavior and the multifaceted influences that shape it. The correlation we uncover may prompt a chuckle or two, but it also underscores the underlying complexity of decision-making processes – whether in the realm of politics or pest management. As the late great physicist Albert Einstein once said, "Politics is more difficult than physics… and mousetrap engineering is no walk in the park, either."
This paper embarks on a journey that takes us from the hallowed halls of political analysis to the humble confines of household pest control, emphasizing that the threads of connection between seemingly disparate realms can yield surprising insights. As we navigate this uncharted terrain, we must heed the wisdom of Mark Twain, who famously mused, "To a man with a hammer, everything looks like a nail… or in this case, a mousetrap." With fabrications of the cogent, we look forward to unraveling the mysteries lurking within the labyrinth of seemingly unrelated data.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In their seminal work "Mouse and Men," Doe and Smith explore the complexities of rodent behavior and its implications for human society. They delve into the psychological and sociological factors that drive individuals to seek methods for controlling mice and other vermin, offering a thought-provoking analysis of the intersection between household pest management and broader societal patterns. The authors' comprehensive investigation sheds light on the multifaceted nature of the relationship between human behavior and rodent control, reminding us that in politics, as in pest management, unexpected factors can play a pivotal role.

Taking a more quantitative approach, Jones et al. in "Cheese Chasers: A Statistical Analysis" conduct a rigorous study on the societal preferences for different types of mousetraps. Their research spans various regions of the United States, probing the factors that influence consumer choices in the realm of rodent eradication. Through their meticulous analysis, they demonstrate the nuanced interplay between market preferences and regional characteristics, emphasizing that the pursuit of an effective mousetrap is not merely a matter of practicality, but also a reflection of deeper societal inclinations.

Now, turning our attention to more casual reading, the fictional works "Of Mice and Men" and "The Mouse and the Motorcycle" offer whimsical insights into the world of rodent behavior and human-mouse interactions. While these novels may not provide empirical evidence, they do remind us of the enduring fascination with rodents and the myriad ways in which they have captured the human imagination. It seems that our ceaseless quest for understanding the mouse and its traps is not confined to the pages of research journals, but permeates the realms of fiction as well.

Venturing into the cinematic sphere, movies such as "Ratatouille" and "Stuart Little" provide delightful escapades featuring rodents and their unlikely adventures. While these films may not directly address the correlation between political voting patterns and mousetrap preferences, they do underscore the enduring appeal of rodent-centric narratives in popular culture. After all, who can resist a tale of a culinary genius rat or a miniature mouse navigating the human world with aplomb? These cinematic indulgences serve as a reminder that even in the realm of research, a touch of whimsy and imagination can go a long way. Plus, they give us a prime opportunity for some gouda puns!

As we navigate the wild terrain of research on political voting patterns and peculiar consumer preferences, it is essential to inject a bit of levity into our exploration. After all, as the saying goes, "Why did the mouse eat a candle? For some light refreshment." In the same vein, we approach our study with a dash of humor and a sense of whimsy, recognizing that amidst the serious pursuit of knowledge, there's always room for a good old dad joke or two. With that in mind, let's approach the next section of our paper with the same spirit of curiosity and mirth. After all, as the classic adage suggests, "When the cat's away, the mice will play… but when the researcher's away, the dad jokes will stay!"

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 Iowa and Google searches for 'best mousetrap'. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
"Cheesing the System: Analyzing the Correlation Between Republican Votes for Senators in Iowa and Google Searches for 'Best Mousetrap'"

[[ABSTRACT]]
When it comes to politics, demographics, and consumer behavior, there's always more than meets the eye - or in this case, more than meets the whiskers. In this study, we delve into the intriguing world of Iowa politics and rodent control, aiming to shed light on the unexpected connection between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. This research not only seeks to provide insight into electoral patterns, but also hopes to catch some valuable data on consumer preferences and their interplay with political leanings.

Our research team harnessed data from the MIT Election Data and Science Lab, Harvard Dataverse and Google Trends to tackle this, dare we say, "gouda" question. Utilizing a time span from 2004 to 2020, we discovered a robust correlation coefficient of 0.8298131 and a noteworthy significance level (p < 0.05), highlighting the statistically significant relationship between these seemingly unrelated variables. It seems that the political landscape and the hunt for an effective mousetrap may be more entwined than initially perceived. As they say, "Big cheese attracts big votes!"

Our findings not only spur further investigation into the curious connections between political sentiment and consumer goods, but also lead us to ponder the implications for future election campaigns. Beyond the data, the sheer amusement of uncovering this unexpected link reminds us of the words of wisdom: "A mouse never entraps itself, but in matters of politics and pest control, stranger bedfellows have seldom been found."

[[INTRODUCTION]]
Political scientists, ever vigilant in their pursuit of understanding the intricate dance of electoral behavior, continually seek to unravel the complex web of factors that influence voters. In this vein, our study delves into a rather unconventional intersection of political trends and consumer behavior by examining the correlation between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. As the old saying goes, "Curiosity killed the cat, but satisfaction brought it back… with a mousetrap."
The state of Iowa, known for its robust political engagement and occasional rodent incursions, offers a unique setting for exploring this unorthodox relationship. By harnessing the power of big data and a healthy dose of curiosity, we aim to shed light on whether there exists a parallel in the preferences of Iowa's electorate and their pursuit of efficient rodent control. After all, in the words of Benjamin Franklin, "Guests, like fish, begin to smell after three days… or if there's a mousetrap in plain view."
Our findings are not intended to serve as a mere exercise in eccentric empirical exploration, but rather as a testament to the unpredictability of human behavior and the multifaceted influences that shape it. The correlation we uncover may prompt a chuckle or two, but it also underscores the underlying complexity of decision-making processes – whether in the realm of politics or pest management. As the late great physicist Albert Einstein once said, "Politics is more difficult than physics… and mousetrap engineering is no walk in the park, either."
This paper embarks on a journey that takes us from the hallowed halls of political analysis to the humble confines of household pest control, emphasizing that the threads of connection between seemingly disparate realms can yield surprising insights. As we navigate this uncharted terrain, we must heed the wisdom of Mark Twain, who famously mused, "To a man with a hammer, everything looks like a nail… or in this case, a mousetrap." With fabrications of the cogent, we look forward to unraveling the mysteries lurking within the labyrinth of seemingly unrelated data.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

In order to untangle the cheese-laden labyrinth of political and pest control preferences, our research team employed a multifaceted approach that could rival the intricate workings of a Rube Goldberg machine. First, we scoured the MIT Election Data and Science Lab for detailed records of Republican votes for Senators in Iowa from 2004 to 2020, delving deep into the electoral cheeseboard to extract the necessary data. We then turned our attention to Google Trends, where we tracked the search interest for the term 'best mousetrap' within the same time frame. Our aim was to capture the ebb and flow of online curiosity regarding rodent eradication methods, which sometimes led to a "trap-tivating" exploration of consumer behavior.

With the collected data in hand, we initially hypothesized that there might be a correlation between the frequency of Republican votes for Senators in Iowa and the intensity of searches for the ideal mousetrap. Like a skilled mouse-ographer, we plotted the temporal movements of these variables, employing advanced statistical analyses to discern any meaningful patterns. We also implemented a variety of control measures to ensure that our findings would not be confounded by extraneous factors, although avoiding the temptation to "cut the cheese" jokes proved to be a considerable challenge.

To determine the robustness of the relationship between the two seemingly disparate variables, we calculated the Pearson correlation coefficient, which served as our trusty compass in navigating the convoluted terrain of political and pest control preferences. Additionally, we conducted a series of regression analyses to ascertain the extent to which variations in Republican votes for Senators could be attributed to the fluctuations in searches for 'best mousetrap', carefully scrutinizing each coefficient as if it held the key to a proverbial block of Swiss cheese.

Furthermore, we subjected our data to a battery of sensitivity analyses and model diagnostics, ensuring that our conclusions were as solid as a wedge of cheddar. We also employed permutation tests and bootstrapping procedures to validate the stability of our results, all the while resisting the urge to make "cheesy" puns about statistical methodologies.

In taking these methodological strides, we were acutely aware of the potential pitfalls and caveats that accompany such unorthodox research pursuits. The burgeoning field of "rodentopolitics," as we fondly referred to it, demanded a careful blend of analytical rigor and a sense of whimsy - much like navigating a maze with a slice of Havarti as the prize. Drawing inspiration from this quirky intersection, we remained resolute in our commitment to unraveling the enigmatic link between political inclinations and the pursuit of ingenious rodent control solutions.

As Mary Shelley once observed, "Nothing is so painful to the human mind as a great and sudden change," but in the case of our research, the unexpected connections we uncovered brought more delight than distress. With this amalgam of innovative methodologies and a dollop of humor, we embarked on a journey that sought to reveal the hidden threads binding Senate votes and the allure of a top-notch mousetrap. After all, in the words of an old pest control adage, "When the cat's away, the mice will play...unless there happens to be a particularly enticing mousetrap in the house."

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 Iowa and Google searches for 'best mousetrap'. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
"Cheesing the System: Analyzing the Correlation Between Republican Votes for Senators in Iowa and Google Searches for 'Best Mousetrap'"

[[ABSTRACT]]
When it comes to politics, demographics, and consumer behavior, there's always more than meets the eye - or in this case, more than meets the whiskers. In this study, we delve into the intriguing world of Iowa politics and rodent control, aiming to shed light on the unexpected connection between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. This research not only seeks to provide insight into electoral patterns, but also hopes to catch some valuable data on consumer preferences and their interplay with political leanings.

Our research team harnessed data from the MIT Election Data and Science Lab, Harvard Dataverse and Google Trends to tackle this, dare we say, "gouda" question. Utilizing a time span from 2004 to 2020, we discovered a robust correlation coefficient of 0.8298131 and a noteworthy significance level (p < 0.05), highlighting the statistically significant relationship between these seemingly unrelated variables. It seems that the political landscape and the hunt for an effective mousetrap may be more entwined than initially perceived. As they say, "Big cheese attracts big votes!"

Our findings not only spur further investigation into the curious connections between political sentiment and consumer goods, but also lead us to ponder the implications for future election campaigns. Beyond the data, the sheer amusement of uncovering this unexpected link reminds us of the words of wisdom: "A mouse never entraps itself, but in matters of politics and pest control, stranger bedfellows have seldom been found."

[[LITERATURE REVIEW]]
In their seminal work "Mouse and Men," Doe and Smith explore the complexities of rodent behavior and its implications for human society. They delve into the psychological and sociological factors that drive individuals to seek methods for controlling mice and other vermin, offering a thought-provoking analysis of the intersection between household pest management and broader societal patterns. The authors' comprehensive investigation sheds light on the multifaceted nature of the relationship between human behavior and rodent control, reminding us that in politics, as in pest management, unexpected factors can play a pivotal role.
Taking a more quantitative approach, Jones et al. in "Cheese Chasers: A Statistical Analysis" conduct a rigorous study on the societal preferences for different types of mousetraps. Their research spans various regions of the United States, probing the factors that influence consumer choices in the realm of rodent eradication. Through their meticulous analysis, they demonstrate the nuanced interplay between market preferences and regional characteristics, emphasizing that the pursuit of an effective mousetrap is not merely a matter of practicality, but also a reflection of deeper societal inclinations.
Now, turning our attention to more casual reading, the fictional works "Of Mice and Men" and "The Mouse and the Motorcycle" offer whimsical insights into the world of rodent behavior and human-mouse interactions. While these novels may not provide empirical evidence, they do remind us of the enduring fascination with rodents and the myriad ways in which they have captured the human imagination. It seems that our ceaseless quest for understanding the mouse and its traps is not confined to the pages of research journals, but permeates the realms of fiction as well.
Venturing into the cinematic sphere, movies such as "Ratatouille" and "Stuart Little" provide delightful escapades featuring rodents and their unlikely adventures. While these films may not directly address the correlation between political voting patterns and mousetrap preferences, they do underscore the enduring appeal of rodent-centric narratives in popular culture. After all, who can resist a tale of a culinary genius rat or a miniature mouse navigating the human world with aplomb? These cinematic indulgences serve as a reminder that even in the realm of research, a touch of whimsy and imagination can go a long way. Plus, they give us a prime opportunity for some gouda puns!
As we navigate the wild terrain of research on political voting patterns and peculiar consumer preferences, it is essential to inject a bit of levity into our exploration. After all, as the saying goes, "Why did the mouse eat a candle? For some light refreshment." In the same vein, we approach our study with a dash of humor and a sense of whimsy, recognizing that amidst the serious pursuit of knowledge, there's always room for a good old dad joke or two. With that in mind, let's approach the next section of our paper with the same spirit of curiosity and mirth. After all, as the classic adage suggests, "When the cat's away, the mice will play… but when the researcher's away, the dad jokes will stay!"

[[RESULTS]]
The results of our analysis yield a striking correlation coefficient of 0.8298131, indicating a strong positive relationship between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. This finding tickles the whiskers and prompts us to ponder just how deep this connection runs. It seems that there's more to Iowa's political landscape than just cornfields and caucus meetings – the quest for an efficient mousetrap may be swaying these political tides more than we thought. It's almost as if the voters were saying, "This candidate really caught my eye, just like a good mousetrap catches those critters!"
Further bolstering the robustness of our findings, the calculated r-squared value of 0.6885898 underscores that a considerable portion of the variance in Republican votes for Senators in Iowa can be explained by the volume of Google searches for 'best mousetrap'. It's as if Iowa constituents were saying, "We want a Senator who can trap the issues as effectively as we trap rodents!"
With a significance level of p < 0.05, our study confirms that this correlation is not just a random coincidence but a bona fide statistically significant relationship. It's almost like the voters are signaling, "When it comes to political candidates, we're looking for someone who can outsmart the competition as effectively as we outsmart those pesky mice!"
Fig. 1 depicts a scatterplot illustrating the pronounced correlation between these unlikely bedfellows. The upward trend in the scatterplot is as clear as day, akin to a mouse scurrying towards a tempting piece of cheese. It seems that not only do political sentiments have an impact on the ballot box, but they also resonate in the realm of household pest control. One might even say, "The voters are trapped in a cheese maze of political decisions!"
In conclusion, our findings support the notion that there exists a notable relationship between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. This unexpected connection invites a myriad of interpretations and invites us to consider the multi-layered influences that shape electoral behavior. As we navigate the labyrinth of data, it's clear that when it comes to politics and pest control, stranger connections have seldom been found.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our results not only provide empirical support for the enduring connection between political leanings and consumer predilections, but they also whisk us away into the realm of unanticipated correlations. Much like a well-placed wedge of cheese, the correlation coefficient of 0.8298131 firmly positions the relationship between Republican votes for Senators in Iowa and Google searches for 'best mousetrap' at the forefront of our analysis. It seems that in the labyrinth of political dynamics, the scent of a good mousetrap may be just as alluring as the aroma of electoral victory. This unexpected finding nudges us to consider a fittingly cheesy question: are voters seeking a candidate who can “trap” the competition as effectively as a premium mousetrap ensnares its prey?

Drawing from prior research, the work of Doe and Smith in "Mouse and Men" reminds us that the pursuit of efficient rodent control is not merely a domestic endeavor but also a reflection of broader societal tendencies. Our results resonate with their insights, hinting that the preference for a reliable mousetrap may echo beyond household concerns and reverberate within the realm of political decision-making. It’s almost as if the voters are signaling, “We’re looking for a Senator who can tackle public policy challenges with the same ingenuity we employ against unwelcome houseguests!"

Additionally, the meticulous study conducted by Jones et al. in "Cheese Chasers: A Statistical Analysis" substantiates our findings by highlighting the intricate interplay between consumer preferences and regional characteristics. This aligns with our revelation that the regional context of Iowa, intertwined with its political landscape, may form an unexpected backdrop to the quest for the ideal mousetrap. As we navigate this web of interconnected factors, it’s as if the voters are musing, “We want a Senator who can navigate the complexities of governance as adeptly as we navigate the nuances of rodent control."

Moreover, the whimsical tales and cinematic adventures featuring rodents, as mentioned in our literature review, not only add a dash of delight to our exploration but also underscore the enduring intrigue associated with rodents in popular culture. This broader fascination with rodents and their narratives might offer a playful lens through which we can interpret the unexpected correlation uncovered in our study. It’s almost as if the voters are hinting, “We’re seeking a Senator whose political journey captures our imagination as much as these rodent-centric narratives captivate our curiosity!"

In summary, our analysis not only confirms the statistically significant relationship between Republican votes for Senators in Iowa and Google searches for 'best mousetrap' but also opens avenues for further investigation into the intertwined nature of political sentiment and consumer behavior. As we unravel the knotty tapestry of political voting patterns and peculiar consumer preferences, we are reminded that in matters of both politics and pest control, the unexpected often holds the key to understanding deeper patterns. After all, as the famous saying goes, "When the cat's away, the mice will play… but when the researcher's away, the dad jokes will stay!"

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 Iowa and Google searches for 'best mousetrap'. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
"Cheesing the System: Analyzing the Correlation Between Republican Votes for Senators in Iowa and Google Searches for 'Best Mousetrap'"

[[ABSTRACT]]
When it comes to politics, demographics, and consumer behavior, there's always more than meets the eye - or in this case, more than meets the whiskers. In this study, we delve into the intriguing world of Iowa politics and rodent control, aiming to shed light on the unexpected connection between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. This research not only seeks to provide insight into electoral patterns, but also hopes to catch some valuable data on consumer preferences and their interplay with political leanings.

Our research team harnessed data from the MIT Election Data and Science Lab, Harvard Dataverse and Google Trends to tackle this, dare we say, "gouda" question. Utilizing a time span from 2004 to 2020, we discovered a robust correlation coefficient of 0.8298131 and a noteworthy significance level (p < 0.05), highlighting the statistically significant relationship between these seemingly unrelated variables. It seems that the political landscape and the hunt for an effective mousetrap may be more entwined than initially perceived. As they say, "Big cheese attracts big votes!"

Our findings not only spur further investigation into the curious connections between political sentiment and consumer goods, but also lead us to ponder the implications for future election campaigns. Beyond the data, the sheer amusement of uncovering this unexpected link reminds us of the words of wisdom: "A mouse never entraps itself, but in matters of politics and pest control, stranger bedfellows have seldom been found."

[[INTRDUCTION]]
Political scientists, ever vigilant in their pursuit of understanding the intricate dance of electoral behavior, continually seek to unravel the complex web of factors that influence voters. In this vein, our study delves into a rather unconventional intersection of political trends and consumer behavior by examining the correlation between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. As the old saying goes, "Curiosity killed the cat, but satisfaction brought it back… with a mousetrap."
The state of Iowa, known for its robust political engagement and occasional rodent incursions, offers a unique setting for exploring this unorthodox relationship. By harnessing the power of big data and a healthy dose of curiosity, we aim to shed light on whether there exists a parallel in the preferences of Iowa's electorate and their pursuit of efficient rodent control. After all, in the words of Benjamin Franklin, "Guests, like fish, begin to smell after three days… or if there's a mousetrap in plain view."
Our findings are not intended to serve as a mere exercise in eccentric empirical exploration, but rather as a testament to the unpredictability of human behavior and the multifaceted influences that shape it. The correlation we uncover may prompt a chuckle or two, but it also underscores the underlying complexity of decision-making processes – whether in the realm of politics or pest management. As the late great physicist Albert Einstein once said, "Politics is more difficult than physics… and mousetrap engineering is no walk in the park, either."
This paper embarks on a journey that takes us from the hallowed halls of political analysis to the humble confines of household pest control, emphasizing that the threads of connection between seemingly disparate realms can yield surprising insights. As we navigate this uncharted terrain, we must heed the wisdom of Mark Twain, who famously mused, "To a man with a hammer, everything looks like a nail… or in this case, a mousetrap." With fabrications of the cogent, we look forward to unraveling the mysteries lurking within the labyrinth of seemingly unrelated data.

[[RESULTS]]
The results of our analysis yield a striking correlation coefficient of 0.8298131, indicating a strong positive relationship between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. This finding tickles the whiskers and prompts us to ponder just how deep this connection runs. It seems that there's more to Iowa's political landscape than just cornfields and caucus meetings – the quest for an efficient mousetrap may be swaying these political tides more than we thought. It's almost as if the voters were saying, "This candidate really caught my eye, just like a good mousetrap catches those critters!"
Further bolstering the robustness of our findings, the calculated r-squared value of 0.6885898 underscores that a considerable portion of the variance in Republican votes for Senators in Iowa can be explained by the volume of Google searches for 'best mousetrap'. It's as if Iowa constituents were saying, "We want a Senator who can trap the issues as effectively as we trap rodents!"
With a significance level of p < 0.05, our study confirms that this correlation is not just a random coincidence but a bona fide statistically significant relationship. It's almost like the voters are signaling, "When it comes to political candidates, we're looking for someone who can outsmart the competition as effectively as we outsmart those pesky mice!"
Fig. 1 depicts a scatterplot illustrating the pronounced correlation between these unlikely bedfellows. The upward trend in the scatterplot is as clear as day, akin to a mouse scurrying towards a tempting piece of cheese. It seems that not only do political sentiments have an impact on the ballot box, but they also resonate in the realm of household pest control. One might even say, "The voters are trapped in a cheese maze of political decisions!"
In conclusion, our findings support the notion that there exists a notable relationship between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. This unexpected connection invites a myriad of interpretations and invites us to consider the multi-layered influences that shape electoral behavior. As we navigate the labyrinth of data, it's clear that when it comes to politics and pest control, stranger connections have seldom been found.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In wrapping up this rather "cheesy" exploration, we find ourselves confronted with a correlation coefficient of 0.8298131 that twirls its whiskers and demands our attention. It seems that the voters of Iowa have a penchant for electing Senators as proficient at problem-solving as a top-tier mousetrap – after all, "Senator Cheddar" has a certain ring to it, doesn't it? Our findings illuminate the unseen ties between political leanings and the pursuit of pest control, proving that when it comes to politics, even the smallest details can have a big impact. As they say, "The best-laid mousetraps of politicians and pest controllers often go astray… but not in Iowa!"

The r-squared value of 0.6885898 further solidifies this unanticipated alliance, highlighting that a sizeable chunk of the variance in Senatorial votes can be elucidated by the fervor behind finding the ultimate mousetrap. One can almost imagine the Iowans asserting, "We want a Senator who can navigate the maze of legislation as deftly as we navigate the maze of mouse traps!" This connection isn't merely a squeak in the night – it's a resounding chorus of political preferences harmonizing with household pest control needs.

Alas, with a significance level of p < 0.05, we can confidently assert that this correlation is no fluke. It's as if the voters are saying, "We're hunting for a Senator who can outwit the opposition just like we outwit those cunning little critters!" The scatterplot, like a trail of breadcrumbs, paints a clear picture of this unexpected cohesion, leaving us pondering the myriad ways in which political sentiment intertwines with the hunt for the ultimate mousetrap.

In closing, our findings serve as a testament to the interwoven fabric of political choices and consumer inclinations. This quirky dance between Republican votes in Iowa and the search for the "best mousetrap" not only tickles the intellect but also underscores the unpredictable nature of human decision-making. It's a bit like finding a wedge of gouda in your political salad – unexpected, but undeniably delightful!

With that, we confidently affirm that further research in this "mousetrap-meets-ballot-box" realm is as unnecessary as a cat having an inventory of mice. As they say, "Why fix what ain't broke?" It's safe to say that this study has caught the problem in a sturdy trap, and it's time to move on to topics less... mousy.

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 Cheesing the System: Analyzing the Correlation Between Republican Votes for Senators in Iowa and Google Searches for 'Best Mousetrap'. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Unconventional Political Science

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 Cheesing the System: Analyzing the Correlation Between Republican Votes for Senators in Iowa and Google Searches for 'Best Mousetrap'. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Rodent Behavior Research

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Cheesing the System: Analyzing the Correlation Between Republican Votes for Senators in Iowa and Google Searches for 'Best Mousetrap' with an abstract of When it comes to politics, demographics, and consumer behavior, there's always more than meets the eye - or in this case, more than meets the whiskers. In this study, we delve into the intriguing world of Iowa politics and rodent control, aiming to shed light on the unexpected connection between Republican votes for Senators in Iowa and Google searches for 'best mousetrap'. This research not only seeks to provide insight into electoral patterns, but also hopes to catch some valuable data on consumer preferences and their interplay with political leanings.
Our research team harnessed data from the MIT Election Data and Science Lab, Harvard Dataverse and Google Trends to tackle this, dare we say, "gouda" question. Utilizing a time span from 2004 to 2020, we discovered a robust correlation coefficient of 0.8298131 and a noteworthy significance level (p < 0.05), highlighting the statistically significant relationship between these seemingly unrelated variables. It seems that the political landscape and the hunt for an effective mousetrap may be more entwined than initially perceived. As they say, "Big cheese attracts big votes!"
Our findings not only spur further investigation into the curious connections between political sentiment and consumer goods, but also lead us to ponder the implications for future election campaigns. Beyond the data, the sheer amusement of uncovering this unexpected link reminds us of the words of wisdom: "A mouse never entraps itself, but in matters of politics and pest control, stranger bedfellows have seldom been found.

ChatGPT:

Republican votes, Senators, Iowa, correlation analysis, Google searches, best mousetrap, consumer behavior, political leanings, electoral patterns, data analysis, MIT Election Data and Science Lab, Harvard Dataverse, Google Trends, correlation coefficient, statistical significance, political sentiment, consumer goods, election campaigns, political implications, pest control

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

Google searches for 'best mousetrap'
Detailed data title: Relative volume of Google searches for 'best mousetrap' (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 'best mousetrap'

Correlation r = 0.8298131 (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 = 0.6885898 (Coefficient of determination)
This means 68.9% of the change in the one variable (i.e., Google searches for 'best mousetrap') is predictable based on the change in the other (i.e., Votes for Republican Senators in Iowa) over the 6 years from 2004 through 2020.

p < 0.05, which statistically significant(Null hypothesis significance test)
The p-value is 0.041.^Show 0.0409807536237321700000000000
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 0.83 in 4.1% of random cases. Said differently, if you correlated 24 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.

[ 0.06, 0.98 ] 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 Iowa (Percentage of votes)	70.1836	37.2612	64.3525	52.1001	60.0899	50.8783
Google searches for 'best mousetrap' (Rel. search volume)	26.25	10.6667	15.9167	16	15.8333	12

Why this works

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.
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([70.1836,37.2612,64.3525,52.1001,60.0899,50.8783,])
array_2 = np.array([26.25,10.6667,15.9167,16,15.8333,12,])
array_1_name = "Votes for Republican Senators in Iowa"
array_2_name = "Google searches for 'best mousetrap'"

# 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.

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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
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Line chart for only Votes for Republican Senators in Iowa
Line chart for only Google searches for 'best mousetrap'
AI-generated correlation image
The spurious research paper: Cheesing the System: Analyzing the Correlation Between Republican Votes for Senators in Iowa and Google Searches for 'Best Mousetrap'

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Correlation ID: 5806 · Black Variable ID: 26386 · Red Variable ID: 1348


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