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Spurious correlation #4,705 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Killian and the second variable is Votes for the Libertarian Presidential candidate in South Dakota.  The chart goes from 1982 to 2020, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

Perhaps every new baby named Killian was secretly registered as a libertarian voter, creating a tiny but dedicated army of politically active infants. As their numbers grew, so did the support for the Libertarian candidate, thanks to the unexpected influence of these baby politicos. Or perhaps there's a charismatic political figure named Killian who inadvertently sparked a wave of libertarian fervor, simply by being so charming that people couldn't help but embrace his political ideology. It's a name that not only demands attention, but also apparently sways political allegiance in the most unexpected of ways.

Model: dalle-3
Prompt: An image that looks like a scene from A Disney Movie, depicting a bustling South Dakota town, with an enchanting parade of babies wearing "I Voted" stickers, their little fists raised in solidarity, captivating the crowd. The name "Killian" is in big, bold letters on their shirts, and their enthusiastic coos seem to echo the rallying cry for the Libertarian Presidential candidate. A charismatic figure, also named Killian, stands on stage, smiling with magnetic charm, inadvertently swaying the political allegiance of the crowd. The scene is filled with vibrant colors and enchanting details, capturing the magic of a Disney movie. 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: Popularity of the first name Killian and Votes for the Libertarian Presidential candidate in South Dakota. 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: Futuristic Glitch art An image that looks like it is a scene from A Disney Movie Cyber folk Surrealism
ChatGPT: An image that looks like it is a scene from A Disney Movie

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 Popularity of the first name Killian and Votes for the Libertarian Presidential candidate in South Dakota, in the following situation: Perhaps every new baby named Killian was secretly registered as a libertarian voter, creating a tiny but dedicated army of politically active infants. As their numbers grew, so did the support for the Libertarian candidate, thanks to the unexpected influence of these baby politicos. Or perhaps there's a charismatic political figure named Killian who inadvertently sparked a wave of libertarian fervor, simply by being so charming that people couldn't help but embrace his political ideology. It's a name that not only demands attention, but also apparently sways political allegiance in the most unexpected of ways.. Keep the description simple.
ChatGPT: In a bustling South Dakota town, a parade of infants wearing "I Voted" stickers, their tiny fists raised in solidarity, captivates the crowd. The name "Killian" is in big, bold letters on their shirts, and their enthusiastic coos seem to echo the rallying cry for the Libertarian Presidential candidate. The sight of these adorable voter-babies has sparked a wave of support for the libertarian cause, all thanks to the unexpected influence of these politically active infants. A charismatic figure, also named Killian, smiles from the stage, his magnetic charm inadvertently swaying the political allegiance of the crowd.

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: [ An image that looks like it is a scene from A Disney Movie ] and depicting this scene: In a bustling South Dakota town, a parade of infants wearing "I Voted" stickers, their tiny fists raised in solidarity, captivates the crowd. The name "Killian" is in big, bold letters on their shirts, and their enthusiastic coos seem to echo the rallying cry for the Libertarian Presidential candidate. The sight of these adorable voter-babies has sparked a wave of support for the libertarian cause, all thanks to the unexpected influence of these politically active infants. A charismatic figure, also named Killian, smiles from the stage, his magnetic charm inadvertently swaying the political allegiance of the crowd. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: An image that looks like a scene from A Disney Movie, depicting a bustling South Dakota town, with an enchanting parade of babies wearing "I Voted" stickers, their little fists raised in solidarity, captivating the crowd. The name "Killian" is in big, bold letters on their shirts, and their enthusiastic coos seem to echo the rallying cry for the Libertarian Presidential candidate. A charismatic figure, also named Killian, stands on stage, smiling with magnetic charm, inadvertently swaying the political allegiance of the crowd. The scene is filled with vibrant colors and enchanting details, capturing the magic of a Disney movie.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Popularity of the first name Killian caused Votes for the Libertarian Presidential candidate in South Dakota to increase.

AI academic paper

(Because p < 0.01)
Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020

Journal of Social Dynamics and Cultural Trends

Jan 2024

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




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Popularity of the first name Killian and Votes for the Libertarian Presidential candidate in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Rhyme words in the title.

Your research team used data from US Social Security Administration and MIT Election Data and Science Lab, Harvard Dataverse to assess this nagging question. You found a correlation coefficient of 0.9707005 and p < 0.01 for 1982 to 2020.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
"Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020"

[[ABSTRACT]]
This pioneering research investigates the curious relationship between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in South Dakota from 1982 to 2020. Leveraging data from the US Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse, our study uncovers a significant correlation between the two seemingly disparate variables. A striking correlation coefficient of 0.9707005 and p < 0.01 suggests a compelling association, highlighting the impact of a name's popularity on political preferences. Our findings illuminate a hitherto unexplored dimension of electoral behavior, shedding new light on the intriguing interplay between nomenclature trends and political choices. This research contributes to the burgeoning literature on unconventional predictors of voting behavior, providing a nuanced understanding of the whimsical and, at times, whimsy-filled world of electoral dynamics.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Popularity of the first name Killian and Votes for the Libertarian Presidential candidate in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
"Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020"

[[ABSTRACT]]
This pioneering research investigates the curious relationship between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in South Dakota from 1982 to 2020. Leveraging data from the US Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse, our study uncovers a significant correlation between the two seemingly disparate variables. A striking correlation coefficient of 0.9707005 and p < 0.01 suggests a compelling association, highlighting the impact of a name's popularity on political preferences. Our findings illuminate a hitherto unexplored dimension of electoral behavior, shedding new light on the intriguing interplay between nomenclature trends and political choices. This research contributes to the burgeoning literature on unconventional predictors of voting behavior, providing a nuanced understanding of the whimsical and, at times, whimsy-filled world of electoral dynamics.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Humans have long been fascinated by the interplay between seemingly unrelated variables, much like a mad scientist mixing potions in a lab - who knows what volatile concoctions might emerge? In this spirit of curiosity, we delve into the enigmatic correlation between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in the evocative expanse of South Dakota. While at first glance, these two entities appear as distant as the poles of a magnet, our investigation has uncovered a magnetic attraction between them that is nothing short of electrifying.

Over the years, researchers have explored a plethora of factors influencing political preferences, from socioeconomic status to regional demographics. However, the potential influence of an individual's name has been largely overlooked, hidden in the statistical underbrush like a rare species of statistical sasquatch. Our study aims to shine a spotlight on this underappreciated variable, acknowledging that a rose by any other name might not just smell as sweet, but vote quite differently as well.

Statisticians and researchers alike often navigate through the labyrinth of potential variables in search of those overlooked gems, just as a prospector hunts for gold in a river; similarly, our investigation from 1982 to 2020 involves searching for electoral nuggets amidst the data streams of the U.S. Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse. We are driven by the desire to unearth the unexpected, embracing the thrilling unpredictability akin to a statistical rollercoaster ride.

As we embark on this academic escapade, we invite readers to join us in peeling back the layers of this intriguing onion of variables, embracing the whimsical and at times downright wacky world of electoral dynamics. It is a journey that seeks to uncover the connections hidden in plain sight, much like finding Waldo in a sea of statistical noise. With this mindset, we turn to our data with a twinkle in our eye and a sense of statistical adventure, ready to decipher the mysterious dance between the popularity of "Killian" and the ticklish tango of Libertarian presidential votes in South Dakota.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Popularity of the first name Killian and Votes for the Libertarian Presidential candidate in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020"

[[ABSTRACT]]
This pioneering research investigates the curious relationship between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in South Dakota from 1982 to 2020. Leveraging data from the US Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse, our study uncovers a significant correlation between the two seemingly disparate variables. A striking correlation coefficient of 0.9707005 and p < 0.01 suggests a compelling association, highlighting the impact of a name's popularity on political preferences. Our findings illuminate a hitherto unexplored dimension of electoral behavior, shedding new light on the intriguing interplay between nomenclature trends and political choices. This research contributes to the burgeoning literature on unconventional predictors of voting behavior, providing a nuanced understanding of the whimsical and, at times, whimsy-filled world of electoral dynamics.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Humans have long been fascinated by the interplay between seemingly unrelated variables, much like a mad scientist mixing potions in a lab - who knows what volatile concoctions might emerge? In this spirit of curiosity, we delve into the enigmatic correlation between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in the evocative expanse of South Dakota. While at first glance, these two entities appear as distant as the poles of a magnet, our investigation has uncovered a magnetic attraction between them that is nothing short of electrifying.
Over the years, researchers have explored a plethora of factors influencing political preferences, from socioeconomic status to regional demographics. However, the potential influence of an individual's name has been largely overlooked, hidden in the statistical underbrush like a rare species of statistical sasquatch. Our study aims to shine a spotlight on this underappreciated variable, acknowledging that a rose by any other name might not just smell as sweet, but vote quite differently as well.
Statisticians and researchers alike often navigate through the labyrinth of potential variables in search of those overlooked gems, just as a prospector hunts for gold in a river; similarly, our investigation from 1982 to 2020 involves searching for electoral nuggets amidst the data streams of the U.S. Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse. We are driven by the desire to unearth the unexpected, embracing the thrilling unpredictability akin to a statistical rollercoaster ride.
As we embark on this academic escapade, we invite readers to join us in peeling back the layers of this intriguing onion of variables, embracing the whimsical and at times downright wacky world of electoral dynamics. It is a journey that seeks to uncover the connections hidden in plain sight, much like finding Waldo in a sea of statistical noise. With this mindset, we turn to our data with a twinkle in our eye and a sense of statistical adventure, ready to decipher the mysterious dance between the popularity of "Killian" and the ticklish tango of Libertarian presidential votes in South Dakota.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In the quest to unravel the labyrinthine tapestry of electoral behavior, researchers have often sought to shed light on the elusive influencers that shape voting preferences. From socioeconomic factors to regional peculiarities, the exploration of these determinants has been as varied as a buffet at a statistical smorgasbord. However, amidst this cacophony of variables, one often overlooked factor has emerged like a cryptic figure in a foggy electorate - the influence of a person's name.

Smith, in "The Name Game: An Exploration of Moniker Influence on Political Leanings," presented a seminal study that hinted at the potential impact of nomenclature trends on electoral choices. Doe, in "The Butterfly Ballot Effect: Unearthing Quirky Influencers of Political Preferences," echoed similar sentiments, providing a tantalizing peek into the underappreciated realm of individual names shaping voting behavior. Jones, in "What's in a Name? A Meta-Analysis of Name-Associated Behavioral Peculiarities," substantiated these findings, further igniting curiosity about the relationship between names and political predilections.

Turning to non-fiction literature, the works of Freakonomics authors Levitt and Dubner stand out as relevant sources. Their exploration of unconventional societal phenomena bears relevance to the arcane connection we seek to unveil. Additionally, Malcolm Gladwell's "Outliers" offers thought-provoking insights into the unexpected influencers of human behavior, prompting us to consider the potential impact of a name's popularity on political inclinations.

Shifting to the realm of fiction, Orwell's "1984" may seem an odd addition to this discourse, yet its portrayal of the power of language to shape perceptions resonates with the intricate influence of nomenclature on political choices. Moreover, Dan Brown's "The Da Vinci Code" presents a puzzle-like narrative, mirroring the enigmatic nature of the correlation between a name's popularity and electoral preferences.

As in any scholarly pursuit, our literature review has navigated through an array of sources to inform our investigation. In addition to established academic works, our discerning analysis has also drawn from unconventional sources, including but not limited to, the cryptic messages hidden within supermarket receipts and the whimsical oddities found in the annals of tabloid journalism. The richness of our literary exploration serves as a testament to the colorful and, at times, comical journey we have embarked upon in unraveling the connection between the popularity of the first name "Killian" and votes for the Libertarian presidential candidate in South Dakota.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Popularity of the first name Killian and Votes for the Libertarian Presidential candidate in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and MIT Election Data and Science Lab, Harvard Dataverse . You used data from 1982 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]]
"Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020"

[[ABSTRACT]]
This pioneering research investigates the curious relationship between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in South Dakota from 1982 to 2020. Leveraging data from the US Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse, our study uncovers a significant correlation between the two seemingly disparate variables. A striking correlation coefficient of 0.9707005 and p < 0.01 suggests a compelling association, highlighting the impact of a name's popularity on political preferences. Our findings illuminate a hitherto unexplored dimension of electoral behavior, shedding new light on the intriguing interplay between nomenclature trends and political choices. This research contributes to the burgeoning literature on unconventional predictors of voting behavior, providing a nuanced understanding of the whimsical and, at times, whimsy-filled world of electoral dynamics.

[[INTRODUCTION]]
Humans have long been fascinated by the interplay between seemingly unrelated variables, much like a mad scientist mixing potions in a lab - who knows what volatile concoctions might emerge? In this spirit of curiosity, we delve into the enigmatic correlation between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in the evocative expanse of South Dakota. While at first glance, these two entities appear as distant as the poles of a magnet, our investigation has uncovered a magnetic attraction between them that is nothing short of electrifying.
Over the years, researchers have explored a plethora of factors influencing political preferences, from socioeconomic status to regional demographics. However, the potential influence of an individual's name has been largely overlooked, hidden in the statistical underbrush like a rare species of statistical sasquatch. Our study aims to shine a spotlight on this underappreciated variable, acknowledging that a rose by any other name might not just smell as sweet, but vote quite differently as well.
Statisticians and researchers alike often navigate through the labyrinth of potential variables in search of those overlooked gems, just as a prospector hunts for gold in a river; similarly, our investigation from 1982 to 2020 involves searching for electoral nuggets amidst the data streams of the U.S. Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse. We are driven by the desire to unearth the unexpected, embracing the thrilling unpredictability akin to a statistical rollercoaster ride.
As we embark on this academic escapade, we invite readers to join us in peeling back the layers of this intriguing onion of variables, embracing the whimsical and at times downright wacky world of electoral dynamics. It is a journey that seeks to uncover the connections hidden in plain sight, much like finding Waldo in a sea of statistical noise. With this mindset, we turn to our data with a twinkle in our eye and a sense of statistical adventure, ready to decipher the mysterious dance between the popularity of "Killian" and the ticklish tango of Libertarian presidential votes in South Dakota.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To unravel the captivating conundrum of Killian's popularity and its curious connection to voter preferences for Libertarian presidential candidates in the picturesque plains of South Dakota, we embarked on a methodological journey reminiscent of a scavenger hunt – seeking out elusive clues amidst the vast expanse of data.

Data Collection:
We sourced information on the prevalence of the first name "Killian" from the US Social Security Administration, which provided a rich tapestry of nomenclature trends spanning from 1982 to 2020. Alongside this, we gleaned data on votes for Libertarian presidential candidates in South Dakota from the prestigious MIT Election Data and Science Lab, Harvard Dataverse. This comprehensive dataset allowed us to traverse through time, capturing the ebb and flow of both a name's popularity and the electoral odyssey in South Dakota.

Statistical Exploration:
With our quiver brimming with data, we set out to navigate the statistical cosmos, armed with hypothesis testing and regression analysis as our compass and sextant. We calculated correlation coefficients and p-values with the fervor of treasure hunters seeking the fabled statistical El Dorado, in pursuit of unveiling the qualitatively elusive yet quantitatively significant relationship between the popularity of "Killian" and Libertarian presidential votes.

Control Variables:
In our analytical quest, we considered covariates that could potentially confound or obscure the underlying connection, much like a detective sifting through red herrings. Factors such as demographic shifts, political climates, and societal trends were carefully controlled for, ensuring that we could attribute any identified associations to the esoteric influence of a name rather than lurking confounding variables.

Robustness Checks and Sensitivity Analyses:
Embracing the unpredictability of statistics, we subjected our findings to a battery of robustness checks and sensitivity analyses, akin to stress-testing a bridge to ensure its reliability. This scrutiny allowed us to ascertain the resilience of our results across various statistical models, confirming the enduring strength of the observed relationship amidst the statistical tempest.

Ethical Considerations:
We conducted this research with the utmost ethical diligence, safeguarding the privacy and anonymity of individuals whose names and political preferences were part of the dataset. Our commitment to ethical conduct rivaled a Jedi's vow to the Force, ensuring that our investigation upheld the principles of integrity and respect for individual privacy.

In summary, our methodology embraced the enthusiasm of a scientific expedition through a statistical jungle, diligently navigating the terrain of data to shed light on the whimsical interplay between nomenclature and political predilections. This methodological traverse allowed us to unearth a correlation that sparkles with scientific intrigue, unveiling the unforeseen alliance between the name "Killian" and the capricious dance of Libertarian votes in the enchanting electoral landscape of South Dakota.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Popularity of the first name Killian and Votes for the Libertarian Presidential candidate in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and MIT Election Data and Science Lab, Harvard Dataverse .

For the time period 1982 to 2020, you found a correlation 0.9707005, r-squared of 0.9422595, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020"

[[ABSTRACT]]
This pioneering research investigates the curious relationship between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in South Dakota from 1982 to 2020. Leveraging data from the US Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse, our study uncovers a significant correlation between the two seemingly disparate variables. A striking correlation coefficient of 0.9707005 and p < 0.01 suggests a compelling association, highlighting the impact of a name's popularity on political preferences. Our findings illuminate a hitherto unexplored dimension of electoral behavior, shedding new light on the intriguing interplay between nomenclature trends and political choices. This research contributes to the burgeoning literature on unconventional predictors of voting behavior, providing a nuanced understanding of the whimsical and, at times, whimsy-filled world of electoral dynamics.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Humans have long been fascinated by the interplay between seemingly unrelated variables, much like a mad scientist mixing potions in a lab - who knows what volatile concoctions might emerge? In this spirit of curiosity, we delve into the enigmatic correlation between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in the evocative expanse of South Dakota. While at first glance, these two entities appear as distant as the poles of a magnet, our investigation has uncovered a magnetic attraction between them that is nothing short of electrifying.
Over the years, researchers have explored a plethora of factors influencing political preferences, from socioeconomic status to regional demographics. However, the potential influence of an individual's name has been largely overlooked, hidden in the statistical underbrush like a rare species of statistical sasquatch. Our study aims to shine a spotlight on this underappreciated variable, acknowledging that a rose by any other name might not just smell as sweet, but vote quite differently as well.
Statisticians and researchers alike often navigate through the labyrinth of potential variables in search of those overlooked gems, just as a prospector hunts for gold in a river; similarly, our investigation from 1982 to 2020 involves searching for electoral nuggets amidst the data streams of the U.S. Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse. We are driven by the desire to unearth the unexpected, embracing the thrilling unpredictability akin to a statistical rollercoaster ride.
As we embark on this academic escapade, we invite readers to join us in peeling back the layers of this intriguing onion of variables, embracing the whimsical and at times downright wacky world of electoral dynamics. It is a journey that seeks to uncover the connections hidden in plain sight, much like finding Waldo in a sea of statistical noise. With this mindset, we turn to our data with a twinkle in our eye and a sense of statistical adventure, ready to decipher the mysterious dance between the popularity of "Killian" and the ticklish tango of Libertarian presidential votes in South Dakota.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our analysis revealed a striking correlation between the popularity of the first name "Killian" and the preference for the Libertarian presidential candidate in South Dakota. Over the time period from 1982 to 2020, we found a remarkably high correlation coefficient of 0.9707005, indicating a robust relationship between these seemingly unrelated variables. With an r-squared of 0.9422595, this correlation explains a substantial 94.23% of the variance in the voting behavior, leaving a mere 5.77% to the whims of the political winds.

In statistical terms, the p-value of less than 0.01 underscores the significance of this association, rendering it statistically significant and not merely a chance encounter in the entangled web of data. It appears that the popularity of the name "Killian" exerts an influence on the political leanings of South Dakotans, illustrating the profound effect of nomenclature on electoral choices. It seems that the name "Killian" has not only been popular among parents, but also influential in the political domain, akin to a catchy political campaign jingle that gets stuck in one's head.

As Fig. 1 showcases, the scatterplot vividly portrays this strong relationship, resembling a dance between data points that moves in rhythm with the fluctuations of popularity and political preference. Like two unlikely dance partners, "Killian" and Libertarian votes in South Dakota exhibit a harmonious and synchronized movement that defies traditional expectations, illustrating the whimsical nature of electoral dynamics.

These findings contribute to the growing body of unconventional predictors of voting behavior, illustrating the multifaceted and occasionally capricious nature of electoral behavior. The magnetic allure of the name "Killian" on Libertarian presidential votes in South Dakota opens a pandora's box of questions, enticing further exploration into the delightful and confounding world of statistical surprises.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Killian and Votes for the Libertarian Presidential candidate in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020"

[[ABSTRACT]]
This pioneering research investigates the curious relationship between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in South Dakota from 1982 to 2020. Leveraging data from the US Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse, our study uncovers a significant correlation between the two seemingly disparate variables. A striking correlation coefficient of 0.9707005 and p < 0.01 suggests a compelling association, highlighting the impact of a name's popularity on political preferences. Our findings illuminate a hitherto unexplored dimension of electoral behavior, shedding new light on the intriguing interplay between nomenclature trends and political choices. This research contributes to the burgeoning literature on unconventional predictors of voting behavior, providing a nuanced understanding of the whimsical and, at times, whimsy-filled world of electoral dynamics.

[[LITERATURE REVIEW]]
In the quest to unravel the labyrinthine tapestry of electoral behavior, researchers have often sought to shed light on the elusive influencers that shape voting preferences. From socioeconomic factors to regional peculiarities, the exploration of these determinants has been as varied as a buffet at a statistical smorgasbord. However, amidst this cacophony of variables, one often overlooked factor has emerged like a cryptic figure in a foggy electorate - the influence of a person's name.
Smith, in "The Name Game: An Exploration of Moniker Influence on Political Leanings," presented a seminal study that hinted at the potential impact of nomenclature trends on electoral choices. Doe, in "The Butterfly Ballot Effect: Unearthing Quirky Influencers of Political Preferences," echoed similar sentiments, providing a tantalizing peek into the underappreciated realm of individual names shaping voting behavior. Jones, in "What's in a Name? A Meta-Analysis of Name-Associated Behavioral Peculiarities," substantiated these findings, further igniting curiosity about the relationship between names and political predilections.
Turning to non-fiction literature, the works of Freakonomics authors Levitt and Dubner stand out as relevant sources. Their exploration of unconventional societal phenomena bears relevance to the arcane connection we seek to unveil. Additionally, Malcolm Gladwell's "Outliers" offers thought-provoking insights into the unexpected influencers of human behavior, prompting us to consider the potential impact of a name's popularity on political inclinations.
Shifting to the realm of fiction, Orwell's "1984" may seem an odd addition to this discourse, yet its portrayal of the power of language to shape perceptions resonates with the intricate influence of nomenclature on political choices. Moreover, Dan Brown's "The Da Vinci Code" presents a puzzle-like narrative, mirroring the enigmatic nature of the correlation between a name's popularity and electoral preferences.
As in any scholarly pursuit, our literature review has navigated through an array of sources to inform our investigation. In addition to established academic works, our discerning analysis has also drawn from unconventional sources, including but not limited to, the cryptic messages hidden within supermarket receipts and the whimsical oddities found in the annals of tabloid journalism. The richness of our literary exploration serves as a testament to the colorful and, at times, comical journey we have embarked upon in unraveling the connection between the popularity of the first name "Killian" and votes for the Libertarian presidential candidate in South Dakota.

[[RESULTS]]
The results of our analysis revealed a striking correlation between the popularity of the first name "Killian" and the preference for the Libertarian presidential candidate in South Dakota. Over the time period from 1982 to 2020, we found a remarkably high correlation coefficient of 0.9707005, indicating a robust relationship between these seemingly unrelated variables. With an r-squared of 0.9422595, this correlation explains a substantial 94.23% of the variance in the voting behavior, leaving a mere 5.77% to the whims of the political winds.
In statistical terms, the p-value of less than 0.01 underscores the significance of this association, rendering it statistically significant and not merely a chance encounter in the entangled web of data. It appears that the popularity of the name "Killian" exerts an influence on the political leanings of South Dakotans, illustrating the profound effect of nomenclature on electoral choices. It seems that the name "Killian" has not only been popular among parents, but also influential in the political domain, akin to a catchy political campaign jingle that gets stuck in one's head.
As Fig. 1 showcases, the scatterplot vividly portrays this strong relationship, resembling a dance between data points that moves in rhythm with the fluctuations of popularity and political preference. Like two unlikely dance partners, "Killian" and Libertarian votes in South Dakota exhibit a harmonious and synchronized movement that defies traditional expectations, illustrating the whimsical nature of electoral dynamics.
These findings contribute to the growing body of unconventional predictors of voting behavior, illustrating the multifaceted and occasionally capricious nature of electoral behavior. The magnetic allure of the name "Killian" on Libertarian presidential votes in South Dakota opens a pandora's box of questions, enticing further exploration into the delightful and confounding world of statistical surprises.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of our study have unmasked a fascinating association between the popularity of the first name "Killian" and votes for the Libertarian presidential candidate in South Dakota. Our findings not only align with prior research on the influence of nomenclature trends on electoral behavior but also illuminate the quirkier aspects of statistical exploration.

Our investigation, building on the foundations laid by Smith's "The Name Game" and Doe's "The Butterfly Ballot Effect," adds to the burgeoning literature on unconventional predictors of voting behavior. The substantial correlation coefficient of 0.9707005 we observed echoes the surprising yet thought-provoking insights shared by Jones in "What's in a Name?" It seems that the influence of a name on political preferences is not a mere flight of fancy but rather a tangible and robust phenomenon, as substantiated by our statistical analysis.

The scatterplot depicting the relationship between the popularity of the name "Killian" and Libertarian votes in South Dakota does not merely illustrate a statistical correlation; it paints a whimsical picture of an unlikely duo dancing in harmonious synchrony. This finding stands in line with Levitt and Dubner's elucidation of unconventional societal phenomena, adding a touch of amusement to the otherwise serious pursuit of scientific inquiry.

Our study, much like Orwell's "1984," delves into the power of language and nomenclature on shaping perceptions, albeit in the domain of electoral choices. It is intriguing to note that the seemingly fantastical connection we have unearthed mirrors the puzzle-like narrative of Dan Brown's "The Da Vinci Code," prompting us to embark on a journey of intellectual unravelment akin to solving a cryptic enigma.

As with any scholarly undertaking, our literature review has allowed us to journey through the conventional and the whimsical, from established academic works to the cryptic messages hidden within supermarket receipts. The diversity of our literary exploration stands as a testament to the engrossing and occasionally comical journey we have undertaken in unraveling the connection between the popularity of the first name "Killian" and votes for the Libertarian presidential candidate in South Dakota.

In the spirit of scientific inquiry, our study transcends the bounds of conventional expectations, shedding light on the delightful and perplexing world of statistical revelations. Our findings call for further exploration into the enigmatic impact of nomenclature on political preferences, urging researchers to embrace the whimsy-filled and captivating nature of statistical surprises.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Popularity of the first name Killian and Votes for the Libertarian Presidential candidate in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020"

[[ABSTRACT]]
This pioneering research investigates the curious relationship between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in South Dakota from 1982 to 2020. Leveraging data from the US Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse, our study uncovers a significant correlation between the two seemingly disparate variables. A striking correlation coefficient of 0.9707005 and p < 0.01 suggests a compelling association, highlighting the impact of a name's popularity on political preferences. Our findings illuminate a hitherto unexplored dimension of electoral behavior, shedding new light on the intriguing interplay between nomenclature trends and political choices. This research contributes to the burgeoning literature on unconventional predictors of voting behavior, providing a nuanced understanding of the whimsical and, at times, whimsy-filled world of electoral dynamics.

[[INTRDUCTION]]
Humans have long been fascinated by the interplay between seemingly unrelated variables, much like a mad scientist mixing potions in a lab - who knows what volatile concoctions might emerge? In this spirit of curiosity, we delve into the enigmatic correlation between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in the evocative expanse of South Dakota. While at first glance, these two entities appear as distant as the poles of a magnet, our investigation has uncovered a magnetic attraction between them that is nothing short of electrifying.
Over the years, researchers have explored a plethora of factors influencing political preferences, from socioeconomic status to regional demographics. However, the potential influence of an individual's name has been largely overlooked, hidden in the statistical underbrush like a rare species of statistical sasquatch. Our study aims to shine a spotlight on this underappreciated variable, acknowledging that a rose by any other name might not just smell as sweet, but vote quite differently as well.
Statisticians and researchers alike often navigate through the labyrinth of potential variables in search of those overlooked gems, just as a prospector hunts for gold in a river; similarly, our investigation from 1982 to 2020 involves searching for electoral nuggets amidst the data streams of the U.S. Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse. We are driven by the desire to unearth the unexpected, embracing the thrilling unpredictability akin to a statistical rollercoaster ride.
As we embark on this academic escapade, we invite readers to join us in peeling back the layers of this intriguing onion of variables, embracing the whimsical and at times downright wacky world of electoral dynamics. It is a journey that seeks to uncover the connections hidden in plain sight, much like finding Waldo in a sea of statistical noise. With this mindset, we turn to our data with a twinkle in our eye and a sense of statistical adventure, ready to decipher the mysterious dance between the popularity of "Killian" and the ticklish tango of Libertarian presidential votes in South Dakota.

[[RESULTS]]
The results of our analysis revealed a striking correlation between the popularity of the first name "Killian" and the preference for the Libertarian presidential candidate in South Dakota. Over the time period from 1982 to 2020, we found a remarkably high correlation coefficient of 0.9707005, indicating a robust relationship between these seemingly unrelated variables. With an r-squared of 0.9422595, this correlation explains a substantial 94.23% of the variance in the voting behavior, leaving a mere 5.77% to the whims of the political winds.
In statistical terms, the p-value of less than 0.01 underscores the significance of this association, rendering it statistically significant and not merely a chance encounter in the entangled web of data. It appears that the popularity of the name "Killian" exerts an influence on the political leanings of South Dakotans, illustrating the profound effect of nomenclature on electoral choices. It seems that the name "Killian" has not only been popular among parents, but also influential in the political domain, akin to a catchy political campaign jingle that gets stuck in one's head.
As Fig. 1 showcases, the scatterplot vividly portrays this strong relationship, resembling a dance between data points that moves in rhythm with the fluctuations of popularity and political preference. Like two unlikely dance partners, "Killian" and Libertarian votes in South Dakota exhibit a harmonious and synchronized movement that defies traditional expectations, illustrating the whimsical nature of electoral dynamics.
These findings contribute to the growing body of unconventional predictors of voting behavior, illustrating the multifaceted and occasionally capricious nature of electoral behavior. The magnetic allure of the name "Killian" on Libertarian presidential votes in South Dakota opens a pandora's box of questions, enticing further exploration into the delightful and confounding world of statistical surprises.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, this pioneering longitudinal study offers compelling evidence of a robust correlation between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in South Dakota. The striking correlation coefficient and statistically significant p-value highlight the substantial influence of nomenclature trends on electoral dynamics. It appears that the name "Killian" has not only gained popularity among parents but also wielded unexpected influence in the realm of politics, akin to a captivating political earworm.

Our findings underscore the whimsical and sometimes capricious nature of electoral behavior, revealing the unexpected dance between the popularity of a name and the electoral tango in South Dakota. As with any statistical discovery, our results raise as many questions as they answer, beckoning further inquiry into the delightful and confounding world of statistical anomalies.

It seems that in the world of electoral dynamics, even the most unexpected variables can waltz into the spotlight, much like an unassuming wallflower morphing into the life of the statistical party. So, as we bid adieu to this enthralling saga of names and votes, we encourage future researchers to embrace the unforeseen, to seek out the statistical sasquatches hidden in the underbrush and to uncover the electoral dance partners that defy conventional expectations.

Therefore, based on the compelling nature of our findings and the sheer delight of uncovering the unexpected, we assert that no further research in this particular area is needed. After all, why look for statistical sasquatches when we've already observed the surprising spectacle of "Killian" and Libertarian votes in South Dakota?


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 Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Social Dynamics and Cultural Trends


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Social Dynamics and Civic Engagement (ISDCE)


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 Killian's Popularity Yields Libertarian's Volatility: A Longitudinal Study in South Dakota from '82 to 2020 with an abstract of This pioneering research investigates the curious relationship between the popularity of the first name "Killian" and voter preference for the Libertarian presidential candidate in South Dakota from 1982 to 2020. Leveraging data from the US Social Security Administration and the MIT Election Data and Science Lab, Harvard Dataverse, our study uncovers a significant correlation between the two seemingly disparate variables. A striking correlation coefficient of 0.9707005 and p < 0.01 suggests a compelling association, highlighting the impact of a name's popularity on political preferences. Our findings illuminate a hitherto unexplored dimension of electoral behavior, shedding new light on the intriguing interplay between nomenclature trends and political choices. This research contributes to the burgeoning literature on unconventional predictors of voting behavior, providing a nuanced understanding of the whimsical and, at times, whimsy-filled world of electoral dynamics.

ChatGPT:

"Killian" popularity, South Dakota, Libertarian presidential candidate, US Social Security Administration data, MIT Election Data and Science Lab, Harvard Dataverse, voting behavior, nomenclature trends, political preferences, electoral dynamics

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



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Data details

Popularity of the first name Killian
Detailed data title: Babies of all sexes born in the US named Killian
Source: US Social Security Administration
See what else correlates with Popularity of the first name Killian

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

Correlation r = 0.9707005 (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 = 0.9422595 (Coefficient of determination)
This means 94.2% of the change in the one variable (i.e., Votes for the Libertarian Presidential candidate in South Dakota) is predictable based on the change in the other (i.e., Popularity of the first name Killian) over the 8 years from 1982 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.2E-5. 0.0000615072206928425900000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.97 in 0.0062% of random cases. Said differently, if you correlated 16,258 random variables Which I absolutely did.
with the same 7 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 7 because we have two variables measured over a period of 8 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.

[ 0.84, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!


All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
19921996200020042008201220162020
Popularity of the first name Killian (Babies born)931611581662902801400911
Votes for the Libertarian Presidential candidate in South Dakota (Percentage of votes)0.2420790.4545650.5255020.2483160.4803981.592845.633722.62536




Why this works

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




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."


# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([93,161,158,166,290,280,1400,911,])
array_2 = np.array([0.242079,0.454565,0.525502,0.248316,0.480398,1.59284,5.63372,2.62536,])
array_1_name = "Popularity of the first name Killian"
array_2_name = "Votes for the Libertarian Presidential candidate in South Dakota"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)



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Correlation ID: 4705 · Black Variable ID: 3936 · Red Variable ID: 26168
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