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Spurious correlation #5,815 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Number of public school students in 6th grade and the second variable is Votes for the Republican Presidential candidate in North Dakota.  The chart goes from 1990 to 2020, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the 6th graders learned about the electoral process, they became adept at counting, prompting a surge in support for the Republican candidate. It seems like these students really know how to "count on" the GOP!

Model: dalle-3
Prompt: Generate an image using the style of a TIME magazine cover that depicts a scene in a North Dakota classroom. In this classroom, a group of 6th graders are fervently reciting the voting numbers for the Republican presidential candidate while diligently tallying the votes on a large chalkboard. The enthusiasm of the students is evident as they engage in this democratic process. The classroom is filled with the chatter and laughter of the students, highlighting the significant number of public school 6th graders in the state. Capture the atmosphere of youthful exuberance and civic participation within a classic school setting. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Number of public school students in 6th grade and Votes for the Republican Presidential candidate in North 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: Low poly A photo-realistic image Low poly An image that looks like it is a scene from a Pixar movie A TIME magazine cover image
ChatGPT: A TIME magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Number of public school students in 6th grade and Votes for the Republican Presidential candidate in North Dakota, in the following situation: As the 6th graders learned about the electoral process, they became adept at counting, prompting a surge in support for the Republican candidate. It seems like these students really know how to "count on" the GOP!. Keep the description simple.
ChatGPT: In a North Dakota classroom, a group of 6th graders eagerly recite the voting numbers for the Republican presidential candidate, their enthusiasm evident as they diligently tally the votes on a large chalkboard. Meanwhile, the classroom is filled with the chatter and laughter of the students, highlighting the significant number of public school students in 6th grade in the state.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A TIME magazine cover image ] and depicting this scene: In a North Dakota classroom, a group of 6th graders eagerly recite the voting numbers for the Republican presidential candidate, their enthusiasm evident as they diligently tally the votes on a large chalkboard. Meanwhile, the classroom is filled with the chatter and laughter of the students, highlighting the significant number of public school students in 6th grade in the state. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image using the style of a TIME magazine cover that depicts a scene in a North Dakota classroom. In this classroom, a group of 6th graders are fervently reciting the voting numbers for the Republican presidential candidate while diligently tallying the votes on a large chalkboard. The enthusiasm of the students is evident as they engage in this democratic process. The classroom is filled with the chatter and laughter of the students, highlighting the significant number of public school 6th graders in the state. Capture the atmosphere of youthful exuberance and civic participation within a classic school setting.

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

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

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 Number of public school students in 6th grade caused Votes for the Republican Presidential candidate in North Dakota to increase. Include one good pun.

AI academic paper

(Because p < 0.01)
Counting on the Correlation: A Study of the Republican Presidential Votes in North Dakota and the Number of 6th Grade Public School Students

Journal of Political Quirks and Statistical Curiosities

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 Number of public school students in 6th grade and Votes for the Republican Presidential candidate in North Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Include a pun in the title.

Your research team used data from National Center for Education Statistics and MIT Election Data and Science Lab, Harvard Dataverse to assess this nagging question. You found a correlation coefficient of 0.9399242 and p < 0.01 for 1990 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]]
Counting on the Correlation: A Study of the Republican Presidential Votes in North Dakota and the Number of 6th Grade Public School Students

[[ABSTRACT]]
In this paper, we set out to determine if there is a discernible connection between the number of 6th grade public school students and the votes for the Republican Presidential candidate in the state of North Dakota. Through our rigorous examination of data sourced from the National Center for Education Statistics and MIT Election Data and Science Lab, Harvard Dataverse, over the period spanning from 1990 to 2020, we uncovered a striking correlation coefficient of 0.9399242 with a statistically significant p-value of less than 0.01. While our findings provide robust evidence pointing to a strong positive relationship, it begs the question: are we witnessing the effects of political fervor emanating from the classroom discussions, or is this simply a case of "pupil-arity" among Republican voters? This study not only sheds light on the dynamics of electoral behavior but also raises intriguing questions about the influence of school-age demographics on political preferences.


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 Number of public school students in 6th grade and Votes for the Republican Presidential candidate in North Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
Counting on the Correlation: A Study of the Republican Presidential Votes in North Dakota and the Number of 6th Grade Public School Students

[[ABSTRACT]]
In this paper, we set out to determine if there is a discernible connection between the number of 6th grade public school students and the votes for the Republican Presidential candidate in the state of North Dakota. Through our rigorous examination of data sourced from the National Center for Education Statistics and MIT Election Data and Science Lab, Harvard Dataverse, over the period spanning from 1990 to 2020, we uncovered a striking correlation coefficient of 0.9399242 with a statistically significant p-value of less than 0.01. While our findings provide robust evidence pointing to a strong positive relationship, it begs the question: are we witnessing the effects of political fervor emanating from the classroom discussions, or is this simply a case of "pupil-arity" among Republican voters? This study not only sheds light on the dynamics of electoral behavior but also raises intriguing questions about the influence of school-age demographics on political preferences.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The intersection of education and politics has long been an area of interest for researchers seeking to unravel the complex web of factors that influence electoral outcomes. In this light, we turn our attention towards the state of North Dakota, a place known for its expansive prairies, abundant oil reserves, and a perhaps less widely recognized affinity for the Republican Party. Our inquiry into the relationship between the number of 6th grade public school students and the votes for the Republican Presidential candidate over the past three decades brings a fresh perspective to the age-old debate of nature versus nurture, or in this case, classroom influence versus political inclination.

As we delve into this study, it's worth noting that North Dakota, with its vast landscapes and sparse population, may not immediately spring to mind as a hotbed of electoral intrigue. However, beneath the tranquil surface lies a community of voters who exhibit interesting patterns when it comes to their political preferences. From bison ranches to wheat fields, and from small rural towns to burgeoning cities, every corner of North Dakota may hold a clue to the intriguing relationship between the education system and the ballot box.

Our investigation stands on the shoulders of previous research exploring similar connections between education metrics and electoral trends. However, as we embark on this endeavor, we remain acutely aware of the potential for pitfalls when interpreting statistical associations. The eminent statistician George Box once remarked, "All models are wrong, but some are useful." Armed with this cautionary quote, we cautiously approach our findings, keeping in mind the importance of distinguishing correlation from causation and resisting the urge to leap to hasty conclusions.

In the crucible of data analysis, it is our hope that this study will not only add to the conglomerate of academic literature in this domain but also present the material in an accessible manner, so that both the aficionados of p-values and those merely curious about the quirks of political statistics can find something of interest. In the spirit of scientific inquiry, let us proceed onward to decipher the tantalizing tango between 6th graders and Republican votes in the great state of North 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 Number of public school students in 6th grade and Votes for the Republican Presidential candidate in North 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 the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
Counting on the Correlation: A Study of the Republican Presidential Votes in North Dakota and the Number of 6th Grade Public School Students

[[ABSTRACT]]
In this paper, we set out to determine if there is a discernible connection between the number of 6th grade public school students and the votes for the Republican Presidential candidate in the state of North Dakota. Through our rigorous examination of data sourced from the National Center for Education Statistics and MIT Election Data and Science Lab, Harvard Dataverse, over the period spanning from 1990 to 2020, we uncovered a striking correlation coefficient of 0.9399242 with a statistically significant p-value of less than 0.01. While our findings provide robust evidence pointing to a strong positive relationship, it begs the question: are we witnessing the effects of political fervor emanating from the classroom discussions, or is this simply a case of "pupil-arity" among Republican voters? This study not only sheds light on the dynamics of electoral behavior but also raises intriguing questions about the influence of school-age demographics on political preferences.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of education and politics has long been an area of interest for researchers seeking to unravel the complex web of factors that influence electoral outcomes. In this light, we turn our attention towards the state of North Dakota, a place known for its expansive prairies, abundant oil reserves, and a perhaps less widely recognized affinity for the Republican Party. Our inquiry into the relationship between the number of 6th grade public school students and the votes for the Republican Presidential candidate over the past three decades brings a fresh perspective to the age-old debate of nature versus nurture, or in this case, classroom influence versus political inclination.
As we delve into this study, it's worth noting that North Dakota, with its vast landscapes and sparse population, may not immediately spring to mind as a hotbed of electoral intrigue. However, beneath the tranquil surface lies a community of voters who exhibit interesting patterns when it comes to their political preferences. From bison ranches to wheat fields, and from small rural towns to burgeoning cities, every corner of North Dakota may hold a clue to the intriguing relationship between the education system and the ballot box.
Our investigation stands on the shoulders of previous research exploring similar connections between education metrics and electoral trends. However, as we embark on this endeavor, we remain acutely aware of the potential for pitfalls when interpreting statistical associations. The eminent statistician George Box once remarked, "All models are wrong, but some are useful." Armed with this cautionary quote, we cautiously approach our findings, keeping in mind the importance of distinguishing correlation from causation and resisting the urge to leap to hasty conclusions.
In the crucible of data analysis, it is our hope that this study will not only add to the conglomerate of academic literature in this domain but also present the material in an accessible manner, so that both the aficionados of p-values and those merely curious about the quirks of political statistics can find something of interest. In the spirit of scientific inquiry, let us proceed onward to decipher the tantalizing tango between 6th graders and Republican votes in the great state of North Dakota.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The connection between educational demographics and political preferences has beckoned researchers to peel back the layers of statistical intricacies, and analyze the potential interplay between these seemingly disparate realms. As we navigate through the manifold literature on this compelling subject, we begin with the seminal work of Smith, who examined the demographic landscape and electoral choices in rural communities in "Rural Realities: A Socio-Political Analysis." Smith's findings, while not directly mirroring our focus on 6th grade public school students and Republican votes in North Dakota, lay the groundwork for understanding the nuanced dynamics at play in electoral behaviors within specific geographic contexts.

Expanding our purview, we encounter the insightful investigation by Doe, et al., in the adeptly titled "Voting Variations: Exploring the Unpredictability of Electoral Outcomes." Their comprehensive analysis of electoral trends in predominantly agrarian states offers valuable insights into the idiosyncrasies of rural voting patterns, pointing towards the influence of local dynamics on political affiliations. Though the study does not explicitly delve into the association between educational demographics and Republican votes, it affords a valuable perspective on the multifaceted nature of electoral behavior.

Venturing further, we entwine our exploration with the informative literature found in "The Education Landscape: A Comprehensive Analysis," which elucidates the intricate interplay between educational metrics and societal trends. Building on this foundation, the engaging narrative in "The Sociology of Voting: Pathways to Political Affiliation" offers a compelling discourse on the social dimensions that underpin electoral choices. While these works do not specifically address our focal point of 6th grade student population and Republican votes in North Dakota, they provide a panoramic view of the complex landscape in which our study unfolds.

Transitioning from non-fiction literature to fictional works that present analogous themes, we find resonance in the realm of imaginative narratives. The fictional universe of "Education and Elections: Insights from Imaginative Realms" presents allegorical tales that, while not grounded in empirical data, offer intriguing parallels to the dynamics we seek to unravel. Similarly, the classic "Vote Voyage: Navigating Political Currents through Fiction" weaves captivating narratives that, in their own imaginative way, reflect the intricate intermeshing of schooling and electoral landscapes.

In a departure from traditional scholarly sources, our pursuit of knowledge led us to unconventional arenas, where we gleaned unexpected insights from the unlikeliest of sources. Among these, the back of shampoo bottles proved to be an unlikely but surprisingly enlightening reservoir of information – offering quirky anecdotes about bubbles and lather, and inadvertently shedding light on the whimsical interplay between education and political proclivities.

Thus, armed with a tapestry of scholarly works, imaginative literature, and unconventional musings, we embark on our foray into the enigmatic correlation between the number of 6th grade public school students and the Republican Presidential votes in the state of North 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 Number of public school students in 6th grade and Votes for the Republican Presidential candidate in North Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from National Center for Education Statistics and MIT Election Data and Science Lab, Harvard Dataverse . You used data from 1990 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]]
Counting on the Correlation: A Study of the Republican Presidential Votes in North Dakota and the Number of 6th Grade Public School Students

[[ABSTRACT]]
In this paper, we set out to determine if there is a discernible connection between the number of 6th grade public school students and the votes for the Republican Presidential candidate in the state of North Dakota. Through our rigorous examination of data sourced from the National Center for Education Statistics and MIT Election Data and Science Lab, Harvard Dataverse, over the period spanning from 1990 to 2020, we uncovered a striking correlation coefficient of 0.9399242 with a statistically significant p-value of less than 0.01. While our findings provide robust evidence pointing to a strong positive relationship, it begs the question: are we witnessing the effects of political fervor emanating from the classroom discussions, or is this simply a case of "pupil-arity" among Republican voters? This study not only sheds light on the dynamics of electoral behavior but also raises intriguing questions about the influence of school-age demographics on political preferences.

[[INTRODUCTION]]
The intersection of education and politics has long been an area of interest for researchers seeking to unravel the complex web of factors that influence electoral outcomes. In this light, we turn our attention towards the state of North Dakota, a place known for its expansive prairies, abundant oil reserves, and a perhaps less widely recognized affinity for the Republican Party. Our inquiry into the relationship between the number of 6th grade public school students and the votes for the Republican Presidential candidate over the past three decades brings a fresh perspective to the age-old debate of nature versus nurture, or in this case, classroom influence versus political inclination.
As we delve into this study, it's worth noting that North Dakota, with its vast landscapes and sparse population, may not immediately spring to mind as a hotbed of electoral intrigue. However, beneath the tranquil surface lies a community of voters who exhibit interesting patterns when it comes to their political preferences. From bison ranches to wheat fields, and from small rural towns to burgeoning cities, every corner of North Dakota may hold a clue to the intriguing relationship between the education system and the ballot box.
Our investigation stands on the shoulders of previous research exploring similar connections between education metrics and electoral trends. However, as we embark on this endeavor, we remain acutely aware of the potential for pitfalls when interpreting statistical associations. The eminent statistician George Box once remarked, "All models are wrong, but some are useful." Armed with this cautionary quote, we cautiously approach our findings, keeping in mind the importance of distinguishing correlation from causation and resisting the urge to leap to hasty conclusions.
In the crucible of data analysis, it is our hope that this study will not only add to the conglomerate of academic literature in this domain but also present the material in an accessible manner, so that both the aficionados of p-values and those merely curious about the quirks of political statistics can find something of interest. In the spirit of scientific inquiry, let us proceed onward to decipher the tantalizing tango between 6th graders and Republican votes in the great state of North Dakota.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To investigate the link between the number of 6th grade public school students and the votes for the Republican Presidential candidate in the state of North Dakota, a combination of traditional statistical methods and a hint of whimsy were employed. The dataset covering the period from 1990 to 2020 was culled together from various sources, with a primary reliance on the National Center for Education Statistics and the MIT Election Data and Science Lab, Harvard Dataverse. The compilation of data unveiled a plethora of numerical nuggets, ripe for the picking of patterns and peculiarities.

The first step in our methodological dance was to conduct a thorough exploration of the data landscape. This involved scrutinizing the population of 6th grade public school students and the corresponding counts of votes for the Republican Presidential candidate in North Dakota. Of course, no scientific pursuit is complete without a healthy dose of skepticism, so we also took a discerning look at potential confounding variables, such as the price of wheat, the state of the local bison population, or the average wind speed in the month of October.

Moving on to the statistical maneuvers, we unleashed the might of correlation analysis to discern any meaningful connections between the variables of interest. Armed with equations and an abacus, we calculated the Pearson correlation coefficient and its trusty sidekick, the p-value, to gauge the strength and significance of the association. The results, we must say, were as eye-catching as a bison in a wheat field – a correlation coefficient of 0.9399242 loomed large, accompanied by a p-value of less than 0.01, akin to a winning lottery ticket in the world of statistical significance.

To supplement these analyses, we delved into the realm of time series modeling, teasing out the temporal trends in the number of 6th grade students and the Republican votes. Here, we rolled up our sleeves and donned our forecasting hats, employing fancy terms like autoregressive integrated moving average (ARIMA) models to illuminate the dynamics over time. It was quite the rollercoaster ride, akin to navigating through a patchwork of prairies and oil derricks in the quest for statistical enlightenment.

In tandem with these quantitative exploits, qualitative insights were sought through interviews and interactions with the local community, attempting to glean the nuanced influences at play. Sifting through the anecdotes and observations, we navigated the information superhighway with our compass pointed towards understanding the mysterious ways in which 6th grade students and Republican votes may cross paths.

In the end, our methodological medley of statistical analyses, time series modeling, and qualitative musings waltzed hand in hand, illuminating the seemingly synchronous rhythm between 6th grade students and Republican votes in the unique context of North 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 Number of public school students in 6th grade and Votes for the Republican Presidential candidate in North Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from National Center for Education Statistics and MIT Election Data and Science Lab, Harvard Dataverse .

For the time period 1990 to 2020, you found a correlation 0.9399242, r-squared of 0.8834575, 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]]
Counting on the Correlation: A Study of the Republican Presidential Votes in North Dakota and the Number of 6th Grade Public School Students

[[ABSTRACT]]
In this paper, we set out to determine if there is a discernible connection between the number of 6th grade public school students and the votes for the Republican Presidential candidate in the state of North Dakota. Through our rigorous examination of data sourced from the National Center for Education Statistics and MIT Election Data and Science Lab, Harvard Dataverse, over the period spanning from 1990 to 2020, we uncovered a striking correlation coefficient of 0.9399242 with a statistically significant p-value of less than 0.01. While our findings provide robust evidence pointing to a strong positive relationship, it begs the question: are we witnessing the effects of political fervor emanating from the classroom discussions, or is this simply a case of "pupil-arity" among Republican voters? This study not only sheds light on the dynamics of electoral behavior but also raises intriguing questions about the influence of school-age demographics on political preferences.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intersection of education and politics has long been an area of interest for researchers seeking to unravel the complex web of factors that influence electoral outcomes. In this light, we turn our attention towards the state of North Dakota, a place known for its expansive prairies, abundant oil reserves, and a perhaps less widely recognized affinity for the Republican Party. Our inquiry into the relationship between the number of 6th grade public school students and the votes for the Republican Presidential candidate over the past three decades brings a fresh perspective to the age-old debate of nature versus nurture, or in this case, classroom influence versus political inclination.
As we delve into this study, it's worth noting that North Dakota, with its vast landscapes and sparse population, may not immediately spring to mind as a hotbed of electoral intrigue. However, beneath the tranquil surface lies a community of voters who exhibit interesting patterns when it comes to their political preferences. From bison ranches to wheat fields, and from small rural towns to burgeoning cities, every corner of North Dakota may hold a clue to the intriguing relationship between the education system and the ballot box.
Our investigation stands on the shoulders of previous research exploring similar connections between education metrics and electoral trends. However, as we embark on this endeavor, we remain acutely aware of the potential for pitfalls when interpreting statistical associations. The eminent statistician George Box once remarked, "All models are wrong, but some are useful." Armed with this cautionary quote, we cautiously approach our findings, keeping in mind the importance of distinguishing correlation from causation and resisting the urge to leap to hasty conclusions.
In the crucible of data analysis, it is our hope that this study will not only add to the conglomerate of academic literature in this domain but also present the material in an accessible manner, so that both the aficionados of p-values and those merely curious about the quirks of political statistics can find something of interest. In the spirit of scientific inquiry, let us proceed onward to decipher the tantalizing tango between 6th graders and Republican votes in the great state of North Dakota.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The statistical analysis revealed a remarkably robust correlation between the number of 6th grade public school students and the votes for the Republican Presidential candidate in North Dakota. The correlation coefficient of 0.9399242 suggests a strong positive relationship between these variables. This finding may prompt some to dub it the "election equation" or the "balloting balance," as it illuminates a close association between the presence of 6th graders and the prevalence of Republican-leaning voters.

Furthermore, the r-squared value of 0.8834575 indicates that approximately 88.35% of the variation in Republican Presidential votes can be explained by the number of 6th grade public school students. It seems that 6th graders and Republican votes are as tightly intertwined as DNA strands in a double helix, each affecting the other in a seemingly inseparable manner.

Upon plotting the data, the resultant scatterplot (Fig.1) vividly illustrates this strong correlation, with the data points resembling a map of constellations in the electoral sky, all pointing overwhelmingly toward a positive association. It's as if the 6th grade public school students are casting their vote in the Republican ballot box long before they reach the legal voting age. We may have stumbled upon a new form of "pre-voting" phenomenon.

The p-value of less than 0.01 underscores the statistical significance of this correlation, leaving us with a level of confidence that is higher than the Dakota plains. It seems that the impact of 6th graders on Republican votes is not to be trifled with, and their presence in the education system may very well sow the seeds of future political affiliation.

In conclusion, our findings unveil a compelling connection between the number of 6th grade public school students and the votes for the Republican Presidential candidate in North Dakota, highlighting the influence of educational demographics on electoral dynamics. This study not only advances our understanding of the interplay between classroom composition and political preferences but also invites further investigation into the intersection of education and electoral behavior.


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 Number of public school students in 6th grade and Votes for the Republican Presidential candidate in North Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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]]
Counting on the Correlation: A Study of the Republican Presidential Votes in North Dakota and the Number of 6th Grade Public School Students

[[ABSTRACT]]
In this paper, we set out to determine if there is a discernible connection between the number of 6th grade public school students and the votes for the Republican Presidential candidate in the state of North Dakota. Through our rigorous examination of data sourced from the National Center for Education Statistics and MIT Election Data and Science Lab, Harvard Dataverse, over the period spanning from 1990 to 2020, we uncovered a striking correlation coefficient of 0.9399242 with a statistically significant p-value of less than 0.01. While our findings provide robust evidence pointing to a strong positive relationship, it begs the question: are we witnessing the effects of political fervor emanating from the classroom discussions, or is this simply a case of "pupil-arity" among Republican voters? This study not only sheds light on the dynamics of electoral behavior but also raises intriguing questions about the influence of school-age demographics on political preferences.

[[LITERATURE REVIEW]]
The connection between educational demographics and political preferences has beckoned researchers to peel back the layers of statistical intricacies, and analyze the potential interplay between these seemingly disparate realms. As we navigate through the manifold literature on this compelling subject, we begin with the seminal work of Smith, who examined the demographic landscape and electoral choices in rural communities in "Rural Realities: A Socio-Political Analysis." Smith's findings, while not directly mirroring our focus on 6th grade public school students and Republican votes in North Dakota, lay the groundwork for understanding the nuanced dynamics at play in electoral behaviors within specific geographic contexts.
Expanding our purview, we encounter the insightful investigation by Doe, et al., in the adeptly titled "Voting Variations: Exploring the Unpredictability of Electoral Outcomes." Their comprehensive analysis of electoral trends in predominantly agrarian states offers valuable insights into the idiosyncrasies of rural voting patterns, pointing towards the influence of local dynamics on political affiliations. Though the study does not explicitly delve into the association between educational demographics and Republican votes, it affords a valuable perspective on the multifaceted nature of electoral behavior.
Venturing further, we entwine our exploration with the informative literature found in "The Education Landscape: A Comprehensive Analysis," which elucidates the intricate interplay between educational metrics and societal trends. Building on this foundation, the engaging narrative in "The Sociology of Voting: Pathways to Political Affiliation" offers a compelling discourse on the social dimensions that underpin electoral choices. While these works do not specifically address our focal point of 6th grade student population and Republican votes in North Dakota, they provide a panoramic view of the complex landscape in which our study unfolds.
Transitioning from non-fiction literature to fictional works that present analogous themes, we find resonance in the realm of imaginative narratives. The fictional universe of "Education and Elections: Insights from Imaginative Realms" presents allegorical tales that, while not grounded in empirical data, offer intriguing parallels to the dynamics we seek to unravel. Similarly, the classic "Vote Voyage: Navigating Political Currents through Fiction" weaves captivating narratives that, in their own imaginative way, reflect the intricate intermeshing of schooling and electoral landscapes.
In a departure from traditional scholarly sources, our pursuit of knowledge led us to unconventional arenas, where we gleaned unexpected insights from the unlikeliest of sources. Among these, the back of shampoo bottles proved to be an unlikely but surprisingly enlightening reservoir of information – offering quirky anecdotes about bubbles and lather, and inadvertently shedding light on the whimsical interplay between education and political proclivities.
Thus, armed with a tapestry of scholarly works, imaginative literature, and unconventional musings, we embark on our foray into the enigmatic correlation between the number of 6th grade public school students and the Republican Presidential votes in the state of North Dakota.

[[RESULTS]]
The statistical analysis revealed a remarkably robust correlation between the number of 6th grade public school students and the votes for the Republican Presidential candidate in North Dakota. The correlation coefficient of 0.9399242 suggests a strong positive relationship between these variables. This finding may prompt some to dub it the "election equation" or the "balloting balance," as it illuminates a close association between the presence of 6th graders and the prevalence of Republican-leaning voters.
Furthermore, the r-squared value of 0.8834575 indicates that approximately 88.35% of the variation in Republican Presidential votes can be explained by the number of 6th grade public school students. It seems that 6th graders and Republican votes are as tightly intertwined as DNA strands in a double helix, each affecting the other in a seemingly inseparable manner.
Upon plotting the data, the resultant scatterplot (Fig.1) vividly illustrates this strong correlation, with the data points resembling a map of constellations in the electoral sky, all pointing overwhelmingly toward a positive association. It's as if the 6th grade public school students are casting their vote in the Republican ballot box long before they reach the legal voting age. We may have stumbled upon a new form of "pre-voting" phenomenon.
The p-value of less than 0.01 underscores the statistical significance of this correlation, leaving us with a level of confidence that is higher than the Dakota plains. It seems that the impact of 6th graders on Republican votes is not to be trifled with, and their presence in the education system may very well sow the seeds of future political affiliation.
In conclusion, our findings unveil a compelling connection between the number of 6th grade public school students and the votes for the Republican Presidential candidate in North Dakota, highlighting the influence of educational demographics on electoral dynamics. This study not only advances our understanding of the interplay between classroom composition and political preferences but also invites further investigation into the intersection of education and electoral behavior.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The striking correlation we observed between the number of 6th grade public school students and the votes for the Republican Presidential candidate in North Dakota bolsters previous research on the intertwined nature of educational demographics and political preferences. The statistical magnitudes we uncovered, akin to a hidden treasure chest beneath the gravelly terrain, indicate a formidable influence of school-age demographics on electoral proclivities. This not only confirms the air of "pupil-arity" posited in earlier literature but provides a concrete validation, solidifying the notion that the educational ecosystem plays a pivotal role in shaping political affiliations.

The resounding statistical significance of our findings, with a p-value lower than the likelihood of finding a needle in a haystack, attests to the robustness of the relationship we unveiled. This demonstrates that the impact of 6th graders on Republican votes is not to be discounted, pushing the boundaries of conventional wisdom to encompass the subtle but profound influence of young minds.

Our discovery underlines the need to heed the lessons whispered by the back of shampoo bottles and fictional narratives, which have, in their own peculiar ways, provided insightful allegories to the multifaceted interplay between schooling and electoral landscapes. The permeating influence of educational demographics on political choices, akin to a silent conductor orchestrating a symphony from the shadows, is now illuminated by our empirical evidence, adding a new chapter to the saga of electoral dynamics.

As we traverse the labyrinth of statistical analytics, it becomes abundantly clear that the number of 6th grade public school students is not merely a numerical abstraction, but a harbinger of political tendencies, wielded by unseen forces to choreograph the electoral ballet. Our study serves as a clarion call for further exploration of the intricate intermeshing of schooling and political proclivities, inviting researchers to delve into the depths of educational demographics and their ripple effects on electoral behaviors.

In essence, our findings underscore the compelling nexus between the presence of 6th graders in the educational milieu and the sway of Republican votes in North Dakota, imbuing the electoral landscape with the hues of scholarly insight and statistical rigor. Thus, the classroom compositions of today may very well echo in the future reverberations of political landscapes, lending credence to the adage that the lessons learned within school walls may well extend far beyond their confines, leaving an indelible mark on the electoral contours of tomorrow.


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 Number of public school students in 6th grade and Votes for the Republican Presidential candidate in North Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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]]
Counting on the Correlation: A Study of the Republican Presidential Votes in North Dakota and the Number of 6th Grade Public School Students

[[ABSTRACT]]
In this paper, we set out to determine if there is a discernible connection between the number of 6th grade public school students and the votes for the Republican Presidential candidate in the state of North Dakota. Through our rigorous examination of data sourced from the National Center for Education Statistics and MIT Election Data and Science Lab, Harvard Dataverse, over the period spanning from 1990 to 2020, we uncovered a striking correlation coefficient of 0.9399242 with a statistically significant p-value of less than 0.01. While our findings provide robust evidence pointing to a strong positive relationship, it begs the question: are we witnessing the effects of political fervor emanating from the classroom discussions, or is this simply a case of "pupil-arity" among Republican voters? This study not only sheds light on the dynamics of electoral behavior but also raises intriguing questions about the influence of school-age demographics on political preferences.

[[INTRDUCTION]]
The intersection of education and politics has long been an area of interest for researchers seeking to unravel the complex web of factors that influence electoral outcomes. In this light, we turn our attention towards the state of North Dakota, a place known for its expansive prairies, abundant oil reserves, and a perhaps less widely recognized affinity for the Republican Party. Our inquiry into the relationship between the number of 6th grade public school students and the votes for the Republican Presidential candidate over the past three decades brings a fresh perspective to the age-old debate of nature versus nurture, or in this case, classroom influence versus political inclination.
As we delve into this study, it's worth noting that North Dakota, with its vast landscapes and sparse population, may not immediately spring to mind as a hotbed of electoral intrigue. However, beneath the tranquil surface lies a community of voters who exhibit interesting patterns when it comes to their political preferences. From bison ranches to wheat fields, and from small rural towns to burgeoning cities, every corner of North Dakota may hold a clue to the intriguing relationship between the education system and the ballot box.
Our investigation stands on the shoulders of previous research exploring similar connections between education metrics and electoral trends. However, as we embark on this endeavor, we remain acutely aware of the potential for pitfalls when interpreting statistical associations. The eminent statistician George Box once remarked, "All models are wrong, but some are useful." Armed with this cautionary quote, we cautiously approach our findings, keeping in mind the importance of distinguishing correlation from causation and resisting the urge to leap to hasty conclusions.
In the crucible of data analysis, it is our hope that this study will not only add to the conglomerate of academic literature in this domain but also present the material in an accessible manner, so that both the aficionados of p-values and those merely curious about the quirks of political statistics can find something of interest. In the spirit of scientific inquiry, let us proceed onward to decipher the tantalizing tango between 6th graders and Republican votes in the great state of North Dakota.

[[RESULTS]]
The statistical analysis revealed a remarkably robust correlation between the number of 6th grade public school students and the votes for the Republican Presidential candidate in North Dakota. The correlation coefficient of 0.9399242 suggests a strong positive relationship between these variables. This finding may prompt some to dub it the "election equation" or the "balloting balance," as it illuminates a close association between the presence of 6th graders and the prevalence of Republican-leaning voters.
Furthermore, the r-squared value of 0.8834575 indicates that approximately 88.35% of the variation in Republican Presidential votes can be explained by the number of 6th grade public school students. It seems that 6th graders and Republican votes are as tightly intertwined as DNA strands in a double helix, each affecting the other in a seemingly inseparable manner.
Upon plotting the data, the resultant scatterplot (Fig.1) vividly illustrates this strong correlation, with the data points resembling a map of constellations in the electoral sky, all pointing overwhelmingly toward a positive association. It's as if the 6th grade public school students are casting their vote in the Republican ballot box long before they reach the legal voting age. We may have stumbled upon a new form of "pre-voting" phenomenon.
The p-value of less than 0.01 underscores the statistical significance of this correlation, leaving us with a level of confidence that is higher than the Dakota plains. It seems that the impact of 6th graders on Republican votes is not to be trifled with, and their presence in the education system may very well sow the seeds of future political affiliation.
In conclusion, our findings unveil a compelling connection between the number of 6th grade public school students and the votes for the Republican Presidential candidate in North Dakota, highlighting the influence of educational demographics on electoral dynamics. This study not only advances our understanding of the interplay between classroom composition and political preferences but also invites further investigation into the intersection of education and electoral behavior.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In closing, our research has unearthed a remarkably strong correlation between the number of 6th grade public school students and the votes for the Republican Presidential candidate in North Dakota. The findings point to a connection so compelling that it leaves one wondering if these students are just practicing their future political prowess a little early. It seems that, much like a game of musical chairs, these 6th graders are already jostling for a spot in the political arena, albeit not yet old enough to legally claim one.

Our study shines a light on the intricate dance between educational demographics and political preferences, revealing a relationship as intertwined as the roots of a prairie grass. It's as if the 6th graders are casting their ballots in the minds of the electorate long before they can do so with a ballot paper. The statistical robustness of the correlation coefficient, r-squared value, and p-value further bolster the validity of our findings, making it clear that the influence of 6th graders on Republican votes is not to be dismissed lightly.

In conclusion, our research adds a fresh perspective to the age-old debate of nature versus nurture in political affiliations and invites scholars to delve deeper into the role of educational demographics in shaping electoral dynamics. However, it is our firm assertion that no further research in this area is needed; after all, we've already counted the correlations!


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 Counting on the Correlation: A Study of the Republican Presidential Votes in North Dakota and the Number of 6th Grade Public School Students. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Political Quirks and Statistical Curiosities


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 Counting on the Correlation: A Study of the Republican Presidential Votes in North Dakota and the Number of 6th Grade Public School Students. Respond only with the name of a fictional organization.

ChatGPT:

The Consortium for Social and Political Quirk Studies (CSPQS)


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 Counting on the Correlation: A Study of the Republican Presidential Votes in North Dakota and the Number of 6th Grade Public School Students with an abstract of In this paper, we set out to determine if there is a discernible connection between the number of 6th grade public school students and the votes for the Republican Presidential candidate in the state of North Dakota. Through our rigorous examination of data sourced from the National Center for Education Statistics and MIT Election Data and Science Lab, Harvard Dataverse, over the period spanning from 1990 to 2020, we uncovered a striking correlation coefficient of 0.9399242 with a statistically significant p-value of less than 0.01. While our findings provide robust evidence pointing to a strong positive relationship, it begs the question: are we witnessing the effects of political fervor emanating from the classroom discussions, or is this simply a case of "pupil-arity" among Republican voters? This study not only sheds light on the dynamics of electoral behavior but also raises intriguing questions about the influence of school-age demographics on political preferences.

ChatGPT:

Republican Presidential votes, North Dakota, 6th grade public school students, correlation coefficient, National Center for Education Statistics, MIT Election Data and Science Lab, Harvard Dataverse, political preferences, school-age demographics, electoral behavior

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



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Data details

Number of public school students in 6th grade
Detailed data title: 6th grade enrollment in public elementary and secondary schools
Source: National Center for Education Statistics
See what else correlates with Number of public school students in 6th grade

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

Correlation r = 0.9399242 (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 = 0.8834575 (Coefficient of determination)
This means 88.3% of the change in the one variable (i.e., Votes for the Republican Presidential candidate in North Dakota) is predictable based on the change in the other (i.e., Number of public school students in 6th grade) over the 8 years from 1990 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00052. 0.0005179197440723328000000000
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 0.94 in 0.052% of random cases. Said differently, if you correlated 1,931 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.

[ 0.7, 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
Number of public school students in 6th grade (Students)33026703493630366319037352803613520372335037539103747690
Votes for the Republican Presidential candidate in North Dakota (Percentage of votes)44.21646.938860.658662.861353.250158.315762.955665.1141




Why this works

  1. Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
  4. Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.




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([3302670,3493630,3663190,3735280,3613520,3723350,3753910,3747690,])
array_2 = np.array([44.216,46.9388,60.6586,62.8613,53.2501,58.3157,62.9556,65.1141,])
array_1_name = "Number of public school students in 6th grade"
array_2_name = "Votes for the Republican Presidential candidate in North 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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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."

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Correlation ID: 5815 · Black Variable ID: 1303 · Red Variable ID: 26150
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