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Spurious correlation #4,814 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Votes for the Democratic Presidential candidate in Hawaii and the second variable is Gasoline Prices in the US.  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 more people in Hawaii showed support for the Democratic candidate, the overall enthusiasm created a chain reaction of high-fives and fist bumps. This sudden surge in celebratory movements somehow disrupted the delicate balance of supply and demand in the gasoline market, leading to a nationwide increase in prices. Who knew that political excitement in a tropical paradise could fuel such a pump-tastic predicament for drivers across the country!

Model: dalle-3
Prompt: [A photo-realistic image] In Hawaii, a group of diverse people are gathered on a sunny beach, smiling and cheering as they proudly display "I Voted" stickers for the Democratic Presidential candidate. Amidst the excitement, high-fives and fist bumps create a ripple effect of jubilation. Meanwhile, on the mainland, a gas pump registers a sudden jump in the price display, as if caught up in the contagious energy, reflecting the unexpected impact of the celebratory chain reaction on gasoline prices nationwide. The scene captures the contrasting moments of joy and surprise on both the island and the mainland. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Votes for the Democrat Presidential candidate in Hawaii and Gasoline Prices in the US. 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: A scene from Skyrim An image that looks like it is a scene from 'Star Wars' A photo-realistic image a funny image macro Brutalism
ChatGPT: A photo-realistic 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 Votes for the Democrat Presidential candidate in Hawaii and Gasoline Prices in the US, in the following situation: As more people in Hawaii showed support for the Democratic candidate, the overall enthusiasm created a chain reaction of high-fives and fist bumps. This sudden surge in celebratory movements somehow disrupted the delicate balance of supply and demand in the gasoline market, leading to a nationwide increase in prices. Who knew that political excitement in a tropical paradise could fuel such a pump-tastic predicament for drivers across the country!. Keep the description simple.
ChatGPT: In Hawaii, a group of people are gathered, smiling and cheering, as they proudly display their "I Voted" stickers for the Democratic Presidential candidate. Amidst the excitement, high-fives and fist bumps create a ripple effect of jubilation. Simultaneously, a gas pump across the mainland registers a sudden jump in the price display, as if caught up in the contagious energy, reflecting the unexpected impact of the celebratory chain reaction on gasoline prices nationwide.

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 photo-realistic image ] and depicting this scene: In Hawaii, a group of people are gathered, smiling and cheering, as they proudly display their "I Voted" stickers for the Democratic Presidential candidate. Amidst the excitement, high-fives and fist bumps create a ripple effect of jubilation. Simultaneously, a gas pump across the mainland registers a sudden jump in the price display, as if caught up in the contagious energy, reflecting the unexpected impact of the celebratory chain reaction on gasoline prices nationwide. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [A photo-realistic image] In Hawaii, a group of diverse people are gathered on a sunny beach, smiling and cheering as they proudly display "I Voted" stickers for the Democratic Presidential candidate. Amidst the excitement, high-fives and fist bumps create a ripple effect of jubilation. Meanwhile, on the mainland, a gas pump registers a sudden jump in the price display, as if caught up in the contagious energy, reflecting the unexpected impact of the celebratory chain reaction on gasoline prices nationwide. The scene captures the contrasting moments of joy and surprise on both the island and the mainland.

*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 Votes for the Democrat Presidential candidate in Hawaii caused Gasoline Prices in the US to increase.

AI academic paper

(Because p < 0.01)
Hawaiian Hilarity: How Hawaii's Hopes for the Democrat Presidential Candidate Hike US Gasoline Prices

The Journal of Comedic Economics

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 silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Votes for the Democrat Presidential candidate in Hawaii and Gasoline Prices in the US. Make lots of jokes, goofy observations, and puns.

Make the title an alliteration.

Your research team used data from MIT Election Data and Science Lab, Harvard Dataverse and Statista to assess this nagging question. You found a correlation coefficient of 0.9256722 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]]
Hawaiian Hilarity: How Hawaii's Hopes for the Democrat Presidential Candidate Hike US Gasoline Prices

[[ABSTRACT]]
This research paper delves into the peculiar and surprising relationship between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States. Our team of researchers, armed with data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, took on the task of unraveling this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9256722 and a p-value of less than 0.01 for the years 1990 to 2020. Despite the initial skepticism towards this seemingly improbable correlation, our results provide evidence of a tangible link. Join us on this comedic journey through political preferences and petroleum prices, where we uncover the unexpected impact of aloha votes on fuel costs. Let's explore how the Aloha State's voting patterns may hold the key to unraveling the mystery of gasoline prices across the nation.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Votes for the Democrat Presidential candidate in Hawaii and Gasoline Prices in the US. Make lots of 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]]
Hawaiian Hilarity: How Hawaii's Hopes for the Democrat Presidential Candidate Hike US Gasoline Prices

[[ABSTRACT]]
This research paper delves into the peculiar and surprising relationship between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States. Our team of researchers, armed with data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, took on the task of unraveling this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9256722 and a p-value of less than 0.01 for the years 1990 to 2020. Despite the initial skepticism towards this seemingly improbable correlation, our results provide evidence of a tangible link. Join us on this comedic journey through political preferences and petroleum prices, where we uncover the unexpected impact of aloha votes on fuel costs. Let's explore how the Aloha State's voting patterns may hold the key to unraveling the mystery of gasoline prices across the nation.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Picture this: a tropical paradise filled with palm trees, luaus, and hula dances. Now, imagine this same place holding the key to unlocking the mystery of gasoline prices across the United States. It may sound like the plot of a wacky sitcom, but here we are, ready to embark on a journey through statistics, politics, and petroleum with a healthy dose of humor thrown in.

The aim of this research paper is to bring to light the unexpected and comical relationship between Hawaiian voting preferences for the Democrat presidential candidate and gasoline prices in the US. As researchers, we were drawn to investigate this correlation after stumbling upon the robust statistical measures that pointed to a connection that was as surprising as a tropical snowstorm in Honolulu.

Armed with an arsenal of data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, we delved headfirst into the depths of this peculiar relationship. And let me tell you, the results we unearthed will make you question everything you thought you knew about the intersection of politics and petroleum prices.

Our findings unraveled a correlation coefficient so strong that it's as if statistical significance and a sense of humor decided to walk hand-in-hand. With a correlation coefficient of 0.9256722 and a p-value smaller than the tiny umbrella in a piña colada, the evidence is as clear as the Hawaiian waters – there is indeed a link between votes for the Democrat candidate in Hawaii and the rollercoaster that is gasoline prices in the US.

This paper looks to shed light on how the easygoing, aloha spirit of Hawaii might hold the answers that have eluded researchers in the realm of energy economics. So, grab your leis and your calculators, and join us on this lighthearted, yet revelatory, expedition as we uncover the unexpected impact of Hawaii's political inclinations on the nation's fuel costs. It's time to embrace the statistical hula and dance through the complex interplay of politics and petrol!


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Votes for the Democrat Presidential candidate in Hawaii and Gasoline Prices in the US. Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then you might move on to cartoons and children's shows that you watched for research.

Here is the title and abstract of the paper:
[[TITLE]]
Hawaiian Hilarity: How Hawaii's Hopes for the Democrat Presidential Candidate Hike US Gasoline Prices

[[ABSTRACT]]
This research paper delves into the peculiar and surprising relationship between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States. Our team of researchers, armed with data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, took on the task of unraveling this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9256722 and a p-value of less than 0.01 for the years 1990 to 2020. Despite the initial skepticism towards this seemingly improbable correlation, our results provide evidence of a tangible link. Join us on this comedic journey through political preferences and petroleum prices, where we uncover the unexpected impact of aloha votes on fuel costs. Let's explore how the Aloha State's voting patterns may hold the key to unraveling the mystery of gasoline prices across the nation.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Picture this: a tropical paradise filled with palm trees, luaus, and hula dances. Now, imagine this same place holding the key to unlocking the mystery of gasoline prices across the United States. It may sound like the plot of a wacky sitcom, but here we are, ready to embark on a journey through statistics, politics, and petroleum with a healthy dose of humor thrown in.
The aim of this research paper is to bring to light the unexpected and comical relationship between Hawaiian voting preferences for the Democrat presidential candidate and gasoline prices in the US. As researchers, we were drawn to investigate this correlation after stumbling upon the robust statistical measures that pointed to a connection that was as surprising as a tropical snowstorm in Honolulu.
Armed with an arsenal of data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, we delved headfirst into the depths of this peculiar relationship. And let me tell you, the results we unearthed will make you question everything you thought you knew about the intersection of politics and petroleum prices.
Our findings unraveled a correlation coefficient so strong that it's as if statistical significance and a sense of humor decided to walk hand-in-hand. With a correlation coefficient of 0.9256722 and a p-value smaller than the tiny umbrella in a piña colada, the evidence is as clear as the Hawaiian waters – there is indeed a link between votes for the Democrat candidate in Hawaii and the rollercoaster that is gasoline prices in the US.
This paper looks to shed light on how the easygoing, aloha spirit of Hawaii might hold the answers that have eluded researchers in the realm of energy economics. So, grab your leis and your calculators, and join us on this lighthearted, yet revelatory, expedition as we uncover the unexpected impact of Hawaii's political inclinations on the nation's fuel costs. It's time to embrace the statistical hula and dance through the complex interplay of politics and petrol!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In their seminal work, Smith and Doe (2005) examined the relationship between political voting behavior in island states and its potential impact on national economic indicators. Similarly, Jones (2010) conducted a comprehensive analysis of regional voting patterns and their implications on energy markets. These studies set the stage for our exploration of the intersection between the Aloha State's political proclivities and gasoline prices across the United States.

Moving beyond the traditional confines of academic literature, our foray into the realm of non-fiction books yielded insightful perspectives. In "The Price of Politics" by Bob Woodward, the complex dynamics of political decision-making are explored, shedding light on the unseen forces that shape economic policies. Furthermore, "The Frackers" by Gregory Zuckerman delves into the intricacies of the energy industry, offering valuable insights into the fluctuating dynamics of fuel markets. These works provided a foundation for our understanding of the multifaceted factors influencing gasoline prices.

Transitioning to a more whimsical landscape, we turned our attention to fiction works that, albeit not rooted in empirical evidence, offer imaginative portrayals of political intrigue and economic quagmires. In "The Pelican Brief" by John Grisham, the blend of suspenseful storytelling and legal drama provides a captivating backdrop to explore the far-reaching consequences of political decisions. Additionally, "Atlas Shrugged" by Ayn Rand, though steeped in philosophical discourse, paints a vivid picture of the interplay between individual agency and economic landscapes.

Venturing into uncharted territory, we sought inspiration from unexpected sources - cartoons and children's shows. The timeless antics of "The Simpsons" and the zany escapades of "SpongeBob SquarePants" provided a refreshing lens through which to examine the complexities of political processes and their ramifications on economic systems. As unlikely as it may seem, these lighthearted sources offered valuable insights into the intersection of political preferences and market dynamics.

As we navigate through the literature, from scholarly works to fictional narratives and even animated entertainment, it becomes evident that the fusion of politics and petrol yields an intriguing tapestry of interconnectedness. Our findings, while rooted in statistical rigor, are buoyed by a spirit of curiosity and humor, mirroring the unexpected convergence of Hawaiian voting patterns and gasoline prices in the US.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Votes for the Democrat Presidential candidate in Hawaii and Gasoline Prices in the US. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and Statista . 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]]
Hawaiian Hilarity: How Hawaii's Hopes for the Democrat Presidential Candidate Hike US Gasoline Prices

[[ABSTRACT]]
This research paper delves into the peculiar and surprising relationship between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States. Our team of researchers, armed with data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, took on the task of unraveling this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9256722 and a p-value of less than 0.01 for the years 1990 to 2020. Despite the initial skepticism towards this seemingly improbable correlation, our results provide evidence of a tangible link. Join us on this comedic journey through political preferences and petroleum prices, where we uncover the unexpected impact of aloha votes on fuel costs. Let's explore how the Aloha State's voting patterns may hold the key to unraveling the mystery of gasoline prices across the nation.

[[INTRODUCTION]]
Picture this: a tropical paradise filled with palm trees, luaus, and hula dances. Now, imagine this same place holding the key to unlocking the mystery of gasoline prices across the United States. It may sound like the plot of a wacky sitcom, but here we are, ready to embark on a journey through statistics, politics, and petroleum with a healthy dose of humor thrown in.
The aim of this research paper is to bring to light the unexpected and comical relationship between Hawaiian voting preferences for the Democrat presidential candidate and gasoline prices in the US. As researchers, we were drawn to investigate this correlation after stumbling upon the robust statistical measures that pointed to a connection that was as surprising as a tropical snowstorm in Honolulu.
Armed with an arsenal of data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, we delved headfirst into the depths of this peculiar relationship. And let me tell you, the results we unearthed will make you question everything you thought you knew about the intersection of politics and petroleum prices.
Our findings unraveled a correlation coefficient so strong that it's as if statistical significance and a sense of humor decided to walk hand-in-hand. With a correlation coefficient of 0.9256722 and a p-value smaller than the tiny umbrella in a piña colada, the evidence is as clear as the Hawaiian waters – there is indeed a link between votes for the Democrat candidate in Hawaii and the rollercoaster that is gasoline prices in the US.
This paper looks to shed light on how the easygoing, aloha spirit of Hawaii might hold the answers that have eluded researchers in the realm of energy economics. So, grab your leis and your calculators, and join us on this lighthearted, yet revelatory, expedition as we uncover the unexpected impact of Hawaii's political inclinations on the nation's fuel costs. It's time to embrace the statistical hula and dance through the complex interplay of politics and petrol!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

First and foremost, let's address the "elephant in the room" – how on earth do we connect votes for the Democrat presidential candidate in Hawaii and gasoline prices in the US? Well, our research team didn't just rely on a crystal ball or consult the Oracle at Delphi. No, we took a more scientific approach, harnessing the power of data and statistical analysis to unravel this quirky conundrum.

To begin our escapade through the statistical wonderland, we gathered historical data on votes for the Democrat presidential candidate in Hawaii from the MIT Election Data and Science Lab. These numbers weren't just any ordinary digits – oh no, they were as vital as a cup of Kona coffee on a Monday morning. By capitalizing on these electoral insights from across the Pacific, we laid the groundwork for understanding Hawaii's political pulse.

Moving on to the other side of the equation, we yanked data on gasoline prices in the US from the extensive repository of the Harvard Dataverse. These price figures weren't just run-of-the-mill data points; they were the building blocks of our research edifice. With these fuel costs in hand, we gamely jived into the world of energy economics, ready to unveil the unforeseen correlations that awaited us.

But wait, we're not done yet! To ensure the robustness and rigor of our analyses, we also enlisted the support of Statista, a treasure trove of statistical information. This allowed us to double-check our findings, making sure that our results weren't just a statistical fluke or a product of mere chance – because let's face it, we're not in the business of fairy tales. We're after hard-hitting, statistically significant truths!

Now, you might be thinking, "How did you actually go about quantifying the relationship between these Hawaiian votes and gasoline prices?" We didn't consult the stars or divine the answers from tea leaves (though that would have been quite the spectacle). Instead, we employed the trusty tools of statistical analysis, including regression models, correlation coefficients, and p-values.

In the initial footsteps of our journey, we calculated the correlation coefficient between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the US. This wasn't just any ordinary correlation – it was a robust, eye-popping coefficient that shone brighter than a solar eclipse. With a correlation coefficient of 0.9256722, our findings hinted at a connection that was as striking as a rainbow amidst a storm.

Furthermore, with a p-value smaller than the probability of finding a needle in a haystack, our results firmly established statistical significance. This wasn't some statistical mirage or a whimsical fluke; it was a rock-solid indication that the connection we had unearthed was more concrete than a tiki statue on the shores of Waikiki.

So, armed with these potent statistical instruments and a hearty sense of humor, we waltzed through the terrain of data analysis, uncovering the unexpected interplay between Hawaiian political preferences and the nation's fuel costs. It was a journey filled with numerical wonders, statistical surprises, and a generous helping of laughter – because let's face it, what's science without a sprinkle of humor? And that, my friends, is the joy of scientific exploration – where statistics meet silliness, and research meets revelry.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Votes for the Democrat Presidential candidate in Hawaii and Gasoline Prices in the US. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

For the time period 1990 to 2020, you found a correlation 0.9256722, r-squared of 0.8568691, 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]]
Hawaiian Hilarity: How Hawaii's Hopes for the Democrat Presidential Candidate Hike US Gasoline Prices

[[ABSTRACT]]
This research paper delves into the peculiar and surprising relationship between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States. Our team of researchers, armed with data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, took on the task of unraveling this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9256722 and a p-value of less than 0.01 for the years 1990 to 2020. Despite the initial skepticism towards this seemingly improbable correlation, our results provide evidence of a tangible link. Join us on this comedic journey through political preferences and petroleum prices, where we uncover the unexpected impact of aloha votes on fuel costs. Let's explore how the Aloha State's voting patterns may hold the key to unraveling the mystery of gasoline prices across the nation.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Picture this: a tropical paradise filled with palm trees, luaus, and hula dances. Now, imagine this same place holding the key to unlocking the mystery of gasoline prices across the United States. It may sound like the plot of a wacky sitcom, but here we are, ready to embark on a journey through statistics, politics, and petroleum with a healthy dose of humor thrown in.
The aim of this research paper is to bring to light the unexpected and comical relationship between Hawaiian voting preferences for the Democrat presidential candidate and gasoline prices in the US. As researchers, we were drawn to investigate this correlation after stumbling upon the robust statistical measures that pointed to a connection that was as surprising as a tropical snowstorm in Honolulu.
Armed with an arsenal of data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, we delved headfirst into the depths of this peculiar relationship. And let me tell you, the results we unearthed will make you question everything you thought you knew about the intersection of politics and petroleum prices.
Our findings unraveled a correlation coefficient so strong that it's as if statistical significance and a sense of humor decided to walk hand-in-hand. With a correlation coefficient of 0.9256722 and a p-value smaller than the tiny umbrella in a piña colada, the evidence is as clear as the Hawaiian waters – there is indeed a link between votes for the Democrat candidate in Hawaii and the rollercoaster that is gasoline prices in the US.
This paper looks to shed light on how the easygoing, aloha spirit of Hawaii might hold the answers that have eluded researchers in the realm of energy economics. So, grab your leis and your calculators, and join us on this lighthearted, yet revelatory, expedition as we uncover the unexpected impact of Hawaii's political inclinations on the nation's fuel costs. It's time to embrace the statistical hula and dance through the complex interplay of politics and petrol!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

In sifting through the data like a prospector searching for gold, our team stumbled upon an unexpected nugget of insight: a strong positive correlation between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States. The correlation coefficient of 0.9256722 elicited a collective gasp from our research team, as it signaled a surprisingly robust connection between political preferences in the Pacific paradise and the not-so-stable fluctuations of gas prices across the nation.

The r-squared value of 0.8568691 reinforced our findings, indicating that approximately 85.69% of the variation in gasoline prices in the US could be explained by the votes for the Democrat candidate in Hawaii over the period from 1990 to 2020. It's as if Hawaii's political sway has been quietly whispering to the gasoline prices, "Aloha, let's hula together!"

Furthermore, the p-value of less than 0.01 winked at us mischievously, as if daring us to doubt the statistical significance of this unexpected relationship. But we held firm to our data like a surfer on a wave, and the evidence spoke for itself – there's a correlation that's as real as a beachside breeze.

The significance of this correlation is showcased vividly in Fig. 1, a scatterplot that visually captures the undeniable link between votes for the Democrat candidate in Hawaii and gasoline prices in the US. It's as if the data points are doing the hula, swaying to the rhythm of this curious and humorous dance between political inclinations and fuel costs.

Our results not only provide statistical evidence of this unexpected connection but also invite further investigation into the underlying mechanisms at play. Could it be that the laid-back attitude of Hawaii is somehow influencing the tumultuous landscape of gasoline prices in the US? Or perhaps there's a comical cosmic force at play, where each ballot cast in the Aloha State sends ripples through the petroleum market like a wave from Waikiki.

In any case, our findings shed light on a relationship that is as fascinating as it is unexpected, adding a touch of whimsy to the oft-serious world of statistical analysis and economic correlations. So, let's raise a coconut to the surprising power of aloha and its influence on the nation's fuel costs – because in this comedic tale of political preferences and petroleum prices, the joke may just be on us!


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Votes for the Democrat Presidential candidate in Hawaii and Gasoline Prices in the US. Make lots of 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]]
Hawaiian Hilarity: How Hawaii's Hopes for the Democrat Presidential Candidate Hike US Gasoline Prices

[[ABSTRACT]]
This research paper delves into the peculiar and surprising relationship between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States. Our team of researchers, armed with data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, took on the task of unraveling this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9256722 and a p-value of less than 0.01 for the years 1990 to 2020. Despite the initial skepticism towards this seemingly improbable correlation, our results provide evidence of a tangible link. Join us on this comedic journey through political preferences and petroleum prices, where we uncover the unexpected impact of aloha votes on fuel costs. Let's explore how the Aloha State's voting patterns may hold the key to unraveling the mystery of gasoline prices across the nation.

[[LITERATURE REVIEW]]
In their seminal work, Smith and Doe (2005) examined the relationship between political voting behavior in island states and its potential impact on national economic indicators. Similarly, Jones (2010) conducted a comprehensive analysis of regional voting patterns and their implications on energy markets. These studies set the stage for our exploration of the intersection between the Aloha State's political proclivities and gasoline prices across the United States.
Moving beyond the traditional confines of academic literature, our foray into the realm of non-fiction books yielded insightful perspectives. In "The Price of Politics" by Bob Woodward, the complex dynamics of political decision-making are explored, shedding light on the unseen forces that shape economic policies. Furthermore, "The Frackers" by Gregory Zuckerman delves into the intricacies of the energy industry, offering valuable insights into the fluctuating dynamics of fuel markets. These works provided a foundation for our understanding of the multifaceted factors influencing gasoline prices.
Transitioning to a more whimsical landscape, we turned our attention to fiction works that, albeit not rooted in empirical evidence, offer imaginative portrayals of political intrigue and economic quagmires. In "The Pelican Brief" by John Grisham, the blend of suspenseful storytelling and legal drama provides a captivating backdrop to explore the far-reaching consequences of political decisions. Additionally, "Atlas Shrugged" by Ayn Rand, though steeped in philosophical discourse, paints a vivid picture of the interplay between individual agency and economic landscapes.
Venturing into uncharted territory, we sought inspiration from unexpected sources - cartoons and children's shows. The timeless antics of "The Simpsons" and the zany escapades of "SpongeBob SquarePants" provided a refreshing lens through which to examine the complexities of political processes and their ramifications on economic systems. As unlikely as it may seem, these lighthearted sources offered valuable insights into the intersection of political preferences and market dynamics.
As we navigate through the literature, from scholarly works to fictional narratives and even animated entertainment, it becomes evident that the fusion of politics and petrol yields an intriguing tapestry of interconnectedness. Our findings, while rooted in statistical rigor, are buoyed by a spirit of curiosity and humor, mirroring the unexpected convergence of Hawaiian voting patterns and gasoline prices in the US.

[[RESULTS]]
In sifting through the data like a prospector searching for gold, our team stumbled upon an unexpected nugget of insight: a strong positive correlation between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States. The correlation coefficient of 0.9256722 elicited a collective gasp from our research team, as it signaled a surprisingly robust connection between political preferences in the Pacific paradise and the not-so-stable fluctuations of gas prices across the nation.
The r-squared value of 0.8568691 reinforced our findings, indicating that approximately 85.69% of the variation in gasoline prices in the US could be explained by the votes for the Democrat candidate in Hawaii over the period from 1990 to 2020. It's as if Hawaii's political sway has been quietly whispering to the gasoline prices, "Aloha, let's hula together!"
Furthermore, the p-value of less than 0.01 winked at us mischievously, as if daring us to doubt the statistical significance of this unexpected relationship. But we held firm to our data like a surfer on a wave, and the evidence spoke for itself – there's a correlation that's as real as a beachside breeze.
The significance of this correlation is showcased vividly in Fig. 1, a scatterplot that visually captures the undeniable link between votes for the Democrat candidate in Hawaii and gasoline prices in the US. It's as if the data points are doing the hula, swaying to the rhythm of this curious and humorous dance between political inclinations and fuel costs.
Our results not only provide statistical evidence of this unexpected connection but also invite further investigation into the underlying mechanisms at play. Could it be that the laid-back attitude of Hawaii is somehow influencing the tumultuous landscape of gasoline prices in the US? Or perhaps there's a comical cosmic force at play, where each ballot cast in the Aloha State sends ripples through the petroleum market like a wave from Waikiki.
In any case, our findings shed light on a relationship that is as fascinating as it is unexpected, adding a touch of whimsy to the oft-serious world of statistical analysis and economic correlations. So, let's raise a coconut to the surprising power of aloha and its influence on the nation's fuel costs – because in this comedic tale of political preferences and petroleum prices, the joke may just be on us!

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The correlation between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States is not just a statistical conundrum; it's a source of endless amusement. Our findings not only confirm the previous research by Smith and Doe (2005) and Jones (2010) but also pay homage to the unexpectedly insightful perspectives of "The Simpsons" and "SpongeBob SquarePants". After all, who would have thought that cartoon capers and political proclivities could converge to influence the price at the pump?

With a correlation coefficient as strong as a Kona coffee, our results whimsically waltz in step with the enigmatic dance of statistics and societal quirks. The r-squared value of 0.8568691 implies that approximately 85.69% of the variations in gasoline prices in the US pirouette to the rhythm of Hawaii's political sway. It's as if the Hawaiian voters and gasoline prices are engaged in a comedic tango, with hips swaying like data points on a scatterplot.

The p-value, less than 0.01, is the ultimate punchline – a statistical mic drop that asserts the undeniable significance of this unexpected relationship. It's akin to the humorous twist in a sitcom that leaves the audience speechless, except in this case, the audience is the scientific community scratching their heads in delightful bewilderment.

While our findings may seem amusing, they also open the door to deeper inquiry. Is there a whimsical wizardry at play, where the gentle aloha breeze from Hawaii influences the tempestuous storm of gasoline prices across the nation? Or are there comical cosmic forces at work, with each ballot cast in the Aloha State triggering a ripple effect in the petroleum market, like a series of laugh-out-loud cosmic pratfalls?

In sum, the unexpected link between Hawaiian political leanings and nationwide gasoline prices injects a refreshing touch of whimsy into the typically serious realm of statistical analysis. Let's raise a toast to the power of the aloha spirit and its impact on the nation's fuel costs. After all, in this zany tale of political preferences and petroleum prices, the punchline may just be on us!


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Votes for the Democrat Presidential candidate in Hawaii and Gasoline Prices in the US. Make lots of 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]]
Hawaiian Hilarity: How Hawaii's Hopes for the Democrat Presidential Candidate Hike US Gasoline Prices

[[ABSTRACT]]
This research paper delves into the peculiar and surprising relationship between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States. Our team of researchers, armed with data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, took on the task of unraveling this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9256722 and a p-value of less than 0.01 for the years 1990 to 2020. Despite the initial skepticism towards this seemingly improbable correlation, our results provide evidence of a tangible link. Join us on this comedic journey through political preferences and petroleum prices, where we uncover the unexpected impact of aloha votes on fuel costs. Let's explore how the Aloha State's voting patterns may hold the key to unraveling the mystery of gasoline prices across the nation.

[[INTRDUCTION]]
Picture this: a tropical paradise filled with palm trees, luaus, and hula dances. Now, imagine this same place holding the key to unlocking the mystery of gasoline prices across the United States. It may sound like the plot of a wacky sitcom, but here we are, ready to embark on a journey through statistics, politics, and petroleum with a healthy dose of humor thrown in.
The aim of this research paper is to bring to light the unexpected and comical relationship between Hawaiian voting preferences for the Democrat presidential candidate and gasoline prices in the US. As researchers, we were drawn to investigate this correlation after stumbling upon the robust statistical measures that pointed to a connection that was as surprising as a tropical snowstorm in Honolulu.
Armed with an arsenal of data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, we delved headfirst into the depths of this peculiar relationship. And let me tell you, the results we unearthed will make you question everything you thought you knew about the intersection of politics and petroleum prices.
Our findings unraveled a correlation coefficient so strong that it's as if statistical significance and a sense of humor decided to walk hand-in-hand. With a correlation coefficient of 0.9256722 and a p-value smaller than the tiny umbrella in a piña colada, the evidence is as clear as the Hawaiian waters – there is indeed a link between votes for the Democrat candidate in Hawaii and the rollercoaster that is gasoline prices in the US.
This paper looks to shed light on how the easygoing, aloha spirit of Hawaii might hold the answers that have eluded researchers in the realm of energy economics. So, grab your leis and your calculators, and join us on this lighthearted, yet revelatory, expedition as we uncover the unexpected impact of Hawaii's political inclinations on the nation's fuel costs. It's time to embrace the statistical hula and dance through the complex interplay of politics and petrol!

[[RESULTS]]
In sifting through the data like a prospector searching for gold, our team stumbled upon an unexpected nugget of insight: a strong positive correlation between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States. The correlation coefficient of 0.9256722 elicited a collective gasp from our research team, as it signaled a surprisingly robust connection between political preferences in the Pacific paradise and the not-so-stable fluctuations of gas prices across the nation.
The r-squared value of 0.8568691 reinforced our findings, indicating that approximately 85.69% of the variation in gasoline prices in the US could be explained by the votes for the Democrat candidate in Hawaii over the period from 1990 to 2020. It's as if Hawaii's political sway has been quietly whispering to the gasoline prices, "Aloha, let's hula together!"
Furthermore, the p-value of less than 0.01 winked at us mischievously, as if daring us to doubt the statistical significance of this unexpected relationship. But we held firm to our data like a surfer on a wave, and the evidence spoke for itself – there's a correlation that's as real as a beachside breeze.
The significance of this correlation is showcased vividly in Fig. 1, a scatterplot that visually captures the undeniable link between votes for the Democrat candidate in Hawaii and gasoline prices in the US. It's as if the data points are doing the hula, swaying to the rhythm of this curious and humorous dance between political inclinations and fuel costs.
Our results not only provide statistical evidence of this unexpected connection but also invite further investigation into the underlying mechanisms at play. Could it be that the laid-back attitude of Hawaii is somehow influencing the tumultuous landscape of gasoline prices in the US? Or perhaps there's a comical cosmic force at play, where each ballot cast in the Aloha State sends ripples through the petroleum market like a wave from Waikiki.
In any case, our findings shed light on a relationship that is as fascinating as it is unexpected, adding a touch of whimsy to the oft-serious world of statistical analysis and economic correlations. So, let's raise a coconut to the surprising power of aloha and its influence on the nation's fuel costs – because in this comedic tale of political preferences and petroleum prices, the joke may just be on us!

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has shone a spotlight on the hilariously captivating relationship between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the US. The remarkable correlation coefficient of 0.9256722 has left us as bewildered as a tourist trying to figure out which way is north using a compass in the magnetic field of a nearby volcano. The p-value smaller than a pixel in a Hawaii sunset photo further tantalizes us with the undeniable statistical significance of this unexpected connection.

The significant impact of Hawaiian voting preferences on gasoline prices is as surprising as finding a pineapple growing on a pear tree. It's like the statistical equivalent of catching a wave at Pipeline while juggling test tubes – unexpected, thrilling, and a bit wacky.

Our findings not only challenge conventional wisdom but also injects a dose of whimsy into the typically serious world of economic correlations. Universities, is there anything gasoline prices can't do? In any case, we assert with confidence that no more research is needed in this area; the hula between Hawaiian votes and US gasoline prices is a scientific comical tale that needs no further unraveling. So, let's bid aloha to this cheeky correlation and continue with our scholarly journey, where even the most unexpected statistical relationships can bring a smile to our faces.


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 Hawaiian Hilarity: How Hawaii's Hopes for the Democrat Presidential Candidate Hike US Gasoline Prices. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Comedic Economics


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 Hawaiian Hilarity: How Hawaii's Hopes for the Democrat Presidential Candidate Hike US Gasoline Prices. Respond only with the name of a fictional organization.

ChatGPT:

The Association for Comedic Environmental Economics Research


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Hawaiian Hilarity: How Hawaii's Hopes for the Democrat Presidential Candidate Hike US Gasoline Prices with an abstract of This research paper delves into the peculiar and surprising relationship between votes for the Democrat presidential candidate in Hawaii and gasoline prices in the United States. Our team of researchers, armed with data from MIT Election Data and Science Lab, Harvard Dataverse, and Statista, took on the task of unraveling this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9256722 and a p-value of less than 0.01 for the years 1990 to 2020. Despite the initial skepticism towards this seemingly improbable correlation, our results provide evidence of a tangible link. Join us on this comedic journey through political preferences and petroleum prices, where we uncover the unexpected impact of aloha votes on fuel costs. Let's explore how the Aloha State's voting patterns may hold the key to unraveling the mystery of gasoline prices across the nation.

ChatGPT:

Hawaii, Democrat presidential candidate, gasoline prices, United States, correlation, MIT Election Data and Science Lab, Harvard Dataverse, Statista, voting patterns, aloha votes, petroleum prices, fuel costs, Aloha State

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



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Data details

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

Gasoline Prices in the US
Detailed data title: US Retail Gasoline Price
Source: Statista
See what else correlates with Gasoline Prices in the US

Correlation r = 0.9256722 (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 = 0.8568691 (Coefficient of determination)
This means 85.7% of the change in the one variable (i.e., Gasoline Prices in the US) is predictable based on the change in the other (i.e., Votes for the Democratic Presidential candidate in Hawaii) over the 8 years from 1990 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00097. 0.0009702038915400906000000000
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 0.93 in 0.097% of random cases. Said differently, if you correlated 1,031 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.

[ 0.64, 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
Votes for the Democratic Presidential candidate in Hawaii (Percentage of votes)48.092856.928855.791754.009671.452970.147960.980863.1494
Gasoline Prices in the US (US Dollars per Gallon)1.091.21.481.853.253.622.142.17




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.
  5. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([48.0928,56.9288,55.7917,54.0096,71.4529,70.1479,60.9808,63.1494,])
array_2 = np.array([1.09,1.2,1.48,1.85,3.25,3.62,2.14,2.17,])
array_1_name = "Votes for the Democratic Presidential candidate in Hawaii"
array_2_name = "Gasoline Prices in the US"

# 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: 4814 · Black Variable ID: 26082 · Red Variable ID: 461
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