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Spurious correlation #4,611 · 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 Massachusetts and the second variable is Geothermal power generated in Indonesia.  The chart goes from 1982 to 2020, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As more support heated up for the Democrat candidate in Massachusetts, it sent a powerful jolt of energy through the political landscape. This surge in enthusiasm created a seismic shift, leading to an eruption of votes. This in turn sent a message that reverberated all the way to Indonesia, where it sparked a movement towards geothermal power. It seems like even from across the globe, the political climate has a way of influencing renewable energy - talk about a truly electri-frying connection!

Model: dalle-3
Prompt: Generate an image of a bustling voting center in Massachusetts, captured during a moment of heightened excitement as crowds of people gather to cast their votes for the Democrat Presidential candidate. The atmosphere is charged with anticipation, and the energy from the surging support creates powerful ripples that echo through the political landscape. As the energy spreads like a seismic wave, visualize the connection between the fervent political enthusiasm and the consequential shift towards renewable energy in Indonesia, symbolized by the spark of a geothermal power movement. The visual should emanate a sense of electrifying energy and convey the transformative impact of collective action. 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 Massachusetts and Geothermal power generated in Indonesia. 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: Hyper-realistic a funny image you would see on reddit Cutsy art illustration Steampunk A scene from Skyrim
ChatGPT: A scene from Skyrim

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 Massachusetts and Geothermal power generated in Indonesia, in the following situation: As more support heated up for the Democrat candidate in Massachusetts, it sent a powerful jolt of energy through the political landscape. This surge in enthusiasm created a seismic shift, leading to an eruption of votes. This in turn sent a message that reverberated all the way to Indonesia, where it sparked a movement towards geothermal power. It seems like even from across the globe, the political climate has a way of influencing renewable energy - talk about a truly electri-frying connection!. Keep the description simple.
ChatGPT: In Massachusetts, crowds of people gather to cast their votes for the Democrat Presidential candidate, creating a buzz of excitement. The surge of support sends a powerful jolt through the political landscape, resulting in an eruption of votes. This energy spreads like a seismic wave, reaching Indonesia, where it sparks a movement towards geothermal power. The connection between the political enthusiasm and the shift towards renewable energy is truly electrifying!

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 scene from Skyrim ] and depicting this scene: In Massachusetts, crowds of people gather to cast their votes for the Democrat Presidential candidate, creating a buzz of excitement. The surge of support sends a powerful jolt through the political landscape, resulting in an eruption of votes. This energy spreads like a seismic wave, reaching Indonesia, where it sparks a movement towards geothermal power. The connection between the political enthusiasm and the shift towards renewable energy is truly electrifying! Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a bustling voting center in Massachusetts, captured during a moment of heightened excitement as crowds of people gather to cast their votes for the Democrat Presidential candidate. The atmosphere is charged with anticipation, and the energy from the surging support creates powerful ripples that echo through the political landscape. As the energy spreads like a seismic wave, visualize the connection between the fervent political enthusiasm and the consequential shift towards renewable energy in Indonesia, symbolized by the spark of a geothermal power movement. The visual should emanate a sense of electrifying energy and convey the transformative impact of collective action.

*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 Massachusetts caused Geothermal power generated in Indonesia to increase. Include one good pun.

AI academic paper

(Because p < 0.01)
The Democra-Magma Connection: Exploring the Surprising Relationship Between Democratic Vote Share in Massachusetts and Geothermal Power Generation in Indonesia

The Journal of Geopolitical Geothermal Studies

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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Massachusetts and Geothermal power generated in Indonesia. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, just make it sound clever.

Your research team used data from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.9875980 and p < 0.01 for 1982 to 2020.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
"The Democra-Magma Connection: Exploring the Surprising Relationship Between Democratic Vote Share in Massachusetts and Geothermal Power Generation in Indonesia"

[[ABSTRACT]]
This paper presents a comprehensive analysis of the curious correlation between the percentage of votes for the Democratic presidential candidate in the state of Massachusetts and the annual geothermal power generation in Indonesia. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, this study covers the time period from 1982 to 2020. Through rigorous statistical analysis, a remarkably high correlation coefficient of 0.9875980 and a statistically significant p-value of less than 0.01 were observed. The implications of these findings are far-reaching, raising questions about the interplay between political preference in Massachusetts and geothermal energy extraction halfway across the globe. This study not only sheds light on these unexpected associations but also underscores the importance of exploring seemingly unrelated phenomena in the pursuit of scientific understanding.


Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 Massachusetts and Geothermal power generated in Indonesia. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
"The Democra-Magma Connection: Exploring the Surprising Relationship Between Democratic Vote Share in Massachusetts and Geothermal Power Generation in Indonesia"

[[ABSTRACT]]
This paper presents a comprehensive analysis of the curious correlation between the percentage of votes for the Democratic presidential candidate in the state of Massachusetts and the annual geothermal power generation in Indonesia. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, this study covers the time period from 1982 to 2020. Through rigorous statistical analysis, a remarkably high correlation coefficient of 0.9875980 and a statistically significant p-value of less than 0.01 were observed. The implications of these findings are far-reaching, raising questions about the interplay between political preference in Massachusetts and geothermal energy extraction halfway across the globe. This study not only sheds light on these unexpected associations but also underscores the importance of exploring seemingly unrelated phenomena in the pursuit of scientific understanding.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
Introduction

The intertwined dynamics between seemingly disparate variables have long captivated researchers across various disciplines. The peculiar relationship between the political climate in Massachusetts and the geothermal activity in Indonesia represents an intriguing puzzle in the realm of social and environmental sciences. This study delves into the enigmatic correlation, aiming to elucidate the underlying mechanisms driving the unexpected connection between the percentage of votes for the Democratic presidential candidate in Massachusetts and the geothermal power generation in Indonesia.

At first glance, one might be forgiven for dismissing this association as mere happenstance, a statistical fluke born from the complexities of data analysis. However, upon closer examination, the robustness of this correlation challenges conventional notions of causality and demands a rigorous investigation. With meticulous attention to detail and a keen eye for statistical nuance, this study endeavors to unravel the mystery behind this surprising Democra-Magma connection.

The choice of Massachusetts and Indonesia as the focal points of this investigation is not arbitrary. Massachusetts, known for its rich political history and academic prowess, provides a unique backdrop for examining voting patterns in a region with a distinct political landscape. On the other hand, Indonesia, a vast and diverse archipelago nestled within the Pacific Ring of Fire, stands as a global hotspot for geothermal energy production. The juxtaposition of these two geographically and culturally distinct regions adds an element of intrigue to our exploration of the interconnectedness of political sentiment and geothermal activity.

As we embark on this scientific endeavor, it is essential to acknowledge the inherent skepticism that may greet such an unorthodox investigation. Yet, it is precisely within the realms of the unconventional that groundbreaking discoveries often await. By embracing the unanticipated and challenging the boundaries of traditional disciplinary boundaries, we open doors to unanticipated insights and aha moments that defy the constraints of conventional wisdom.

In the pursuit of understanding complex phenomena, it is vital to embrace an open-minded approach that welcomes unexpected correlations and their implications. Through rigorous empirical analysis and an unwavering commitment to scientific inquiry, we aim to not only unravel the intricacies of the Democra-Magma connection but also to inspire further curiosity and exploration in the relentless pursuit of knowledge. Join us on this intellectual expedition as we venture into the uncharted territories of political-geothermal interplay, where statistical analysis meets a touch of serendipity, and scholarly pursuits dare to defy traditional norms.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Votes for the Democrat Presidential candidate in Massachusetts and Geothermal power generated in Indonesia. 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 name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
"The Democra-Magma Connection: Exploring the Surprising Relationship Between Democratic Vote Share in Massachusetts and Geothermal Power Generation in Indonesia"

[[ABSTRACT]]
This paper presents a comprehensive analysis of the curious correlation between the percentage of votes for the Democratic presidential candidate in the state of Massachusetts and the annual geothermal power generation in Indonesia. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, this study covers the time period from 1982 to 2020. Through rigorous statistical analysis, a remarkably high correlation coefficient of 0.9875980 and a statistically significant p-value of less than 0.01 were observed. The implications of these findings are far-reaching, raising questions about the interplay between political preference in Massachusetts and geothermal energy extraction halfway across the globe. This study not only sheds light on these unexpected associations but also underscores the importance of exploring seemingly unrelated phenomena in the pursuit of scientific understanding.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Introduction
The intertwined dynamics between seemingly disparate variables have long captivated researchers across various disciplines. The peculiar relationship between the political climate in Massachusetts and the geothermal activity in Indonesia represents an intriguing puzzle in the realm of social and environmental sciences. This study delves into the enigmatic correlation, aiming to elucidate the underlying mechanisms driving the unexpected connection between the percentage of votes for the Democratic presidential candidate in Massachusetts and the geothermal power generation in Indonesia.
At first glance, one might be forgiven for dismissing this association as mere happenstance, a statistical fluke born from the complexities of data analysis. However, upon closer examination, the robustness of this correlation challenges conventional notions of causality and demands a rigorous investigation. With meticulous attention to detail and a keen eye for statistical nuance, this study endeavors to unravel the mystery behind this surprising Democra-Magma connection.
The choice of Massachusetts and Indonesia as the focal points of this investigation is not arbitrary. Massachusetts, known for its rich political history and academic prowess, provides a unique backdrop for examining voting patterns in a region with a distinct political landscape. On the other hand, Indonesia, a vast and diverse archipelago nestled within the Pacific Ring of Fire, stands as a global hotspot for geothermal energy production. The juxtaposition of these two geographically and culturally distinct regions adds an element of intrigue to our exploration of the interconnectedness of political sentiment and geothermal activity.
As we embark on this scientific endeavor, it is essential to acknowledge the inherent skepticism that may greet such an unorthodox investigation. Yet, it is precisely within the realms of the unconventional that groundbreaking discoveries often await. By embracing the unanticipated and challenging the boundaries of traditional disciplinary boundaries, we open doors to unanticipated insights and aha moments that defy the constraints of conventional wisdom.
In the pursuit of understanding complex phenomena, it is vital to embrace an open-minded approach that welcomes unexpected correlations and their implications. Through rigorous empirical analysis and an unwavering commitment to scientific inquiry, we aim to not only unravel the intricacies of the Democra-Magma connection but also to inspire further curiosity and exploration in the relentless pursuit of knowledge. Join us on this intellectual expedition as we venture into the uncharted territories of political-geothermal interplay, where statistical analysis meets a touch of serendipity, and scholarly pursuits dare to defy traditional norms.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The perplexing correlation between the percentage of votes for the Democratic presidential candidate in Massachusetts and the annual geothermal power generation in Indonesia has spurred a diverse array of academic inquiries and oddball investigations. Smith et al. (2015) laid the groundwork for this line of research, delving into the social, economic, and environmental factors shaping the interplay between political preferences in Massachusetts and global geothermal dynamics. Their rigorous analysis uncovered initial hints of a connection, setting the stage for subsequent scholarly endeavors.

Moving beyond the realm of austere academic tomes, we encounter a colorful array of non-fiction literature that tangentially touches on the nuances of political landscapes and geothermal forces. In "Renewable Energy: Power for a Sustainable Future" by Boyle (2012), the authors explore the potential of geothermal energy as a sustainable alternative to conventional power sources. While Boyle fails to mention the potential influence of Massachusetts' voting patterns on global geothermal dynamics, the underlying themes resonate with the broader discourse on energy production and its intersection with societal preferences.

On the fiction front, the narrative of unexpected linkages takes an intriguing twist. In Jules Verne's "Journey to the Center of the Earth," the protagonists embark on a tumultuous subterranean adventure, encountering fascinating geological phenomena along the way. While Verne's literary masterpiece is steeped in fantastical elements, its portrayal of Earth's inner workings serves as a whimsical reminder of the intricate interconnectedness of geothermal activities, albeit without any mentions of ballot boxes and political inclinations.

Venturing into the digital domain, popular internet memes have occasionally poked fun at the idiosyncrasies of Massachusetts' political landscape and the enigmatic allure of geothermal power. The "Boston Tea Party" meme, aptly referencing both Massachusetts' historical significance and the fervor for renewable energy, has emerged as a lighthearted nod to the state's political ethos. Furthermore, the "Geothermal Cat" meme, featuring a feline seemingly entrenched in Earth's scorching embrace, playfully hints at the pervasive reach of geothermal energy, if not its explicit ties to political voting behaviors.

As we navigate the labyrinth of literature and cultural references, it becomes evident that the Democra-Magma connection transcends the bounds of traditional scholarly inquiry, permeating various facets of creative expression and popular discourse. This interdisciplinary landscape sets the stage for a mélange of insights and curiosities, inviting us to ponder the unlikeliest of correlations with equal parts analytical rigor and whimsical wonderment.


Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Votes for the Democrat Presidential candidate in Massachusetts and Geothermal power generated in Indonesia. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration . You used data from 1982 to 2020

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"The Democra-Magma Connection: Exploring the Surprising Relationship Between Democratic Vote Share in Massachusetts and Geothermal Power Generation in Indonesia"

[[ABSTRACT]]
This paper presents a comprehensive analysis of the curious correlation between the percentage of votes for the Democratic presidential candidate in the state of Massachusetts and the annual geothermal power generation in Indonesia. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, this study covers the time period from 1982 to 2020. Through rigorous statistical analysis, a remarkably high correlation coefficient of 0.9875980 and a statistically significant p-value of less than 0.01 were observed. The implications of these findings are far-reaching, raising questions about the interplay between political preference in Massachusetts and geothermal energy extraction halfway across the globe. This study not only sheds light on these unexpected associations but also underscores the importance of exploring seemingly unrelated phenomena in the pursuit of scientific understanding.

[[INTRODUCTION]]
Introduction
The intertwined dynamics between seemingly disparate variables have long captivated researchers across various disciplines. The peculiar relationship between the political climate in Massachusetts and the geothermal activity in Indonesia represents an intriguing puzzle in the realm of social and environmental sciences. This study delves into the enigmatic correlation, aiming to elucidate the underlying mechanisms driving the unexpected connection between the percentage of votes for the Democratic presidential candidate in Massachusetts and the geothermal power generation in Indonesia.
At first glance, one might be forgiven for dismissing this association as mere happenstance, a statistical fluke born from the complexities of data analysis. However, upon closer examination, the robustness of this correlation challenges conventional notions of causality and demands a rigorous investigation. With meticulous attention to detail and a keen eye for statistical nuance, this study endeavors to unravel the mystery behind this surprising Democra-Magma connection.
The choice of Massachusetts and Indonesia as the focal points of this investigation is not arbitrary. Massachusetts, known for its rich political history and academic prowess, provides a unique backdrop for examining voting patterns in a region with a distinct political landscape. On the other hand, Indonesia, a vast and diverse archipelago nestled within the Pacific Ring of Fire, stands as a global hotspot for geothermal energy production. The juxtaposition of these two geographically and culturally distinct regions adds an element of intrigue to our exploration of the interconnectedness of political sentiment and geothermal activity.
As we embark on this scientific endeavor, it is essential to acknowledge the inherent skepticism that may greet such an unorthodox investigation. Yet, it is precisely within the realms of the unconventional that groundbreaking discoveries often await. By embracing the unanticipated and challenging the boundaries of traditional disciplinary boundaries, we open doors to unanticipated insights and aha moments that defy the constraints of conventional wisdom.
In the pursuit of understanding complex phenomena, it is vital to embrace an open-minded approach that welcomes unexpected correlations and their implications. Through rigorous empirical analysis and an unwavering commitment to scientific inquiry, we aim to not only unravel the intricacies of the Democra-Magma connection but also to inspire further curiosity and exploration in the relentless pursuit of knowledge. Join us on this intellectual expedition as we venture into the uncharted territories of political-geothermal interplay, where statistical analysis meets a touch of serendipity, and scholarly pursuits dare to defy traditional norms.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Data Collection
The first step in unraveling the enigmatic Democra-Magma connection was a comprehensive data collection process. Our research team scoured databases from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, sifting through an ocean of data points akin to seeking a needle in a haystack, but with less hay and more Excel spreadsheets. The data spanned a robust timeline from 1982 to 2020, capturing a wide array of presidential elections and geothermal power generation figures.

Selection Criteria
To ensure the integrity and reliability of the data, rigorous selection criteria were employed. Only data points corresponding to the Democratic vote share in Massachusetts and the annual geothermal power output in Indonesia were considered. We did entertain the idea of including data from other political affiliations and geothermal sources, but it turns out that mixing politics and heat can lead to some rather heated debates and potentially explosive discussions – characteristics best left to geothermal reservoirs rather than conference rooms.

Statistical Analysis
With a trove of data at our disposal, it was time to dive headfirst into the statistical rabbit hole. The correlation between the Democratic vote share in Massachusetts and geothermal power generation in Indonesia was calculated using robust statistical methods, with an emphasis on avoiding the gravitational pull of outliers that could potentially distort the results. It's worth noting that statistical analysis, much like baking a cake, requires a delicate balance of ingredients – too much correlation and you risk overfitting, too little and your cake (or findings) may fall flat.

In addition, a multitude of statistical tests were employed to assess the strength and significance of the observed correlation. The mere mention of p-values and confidence intervals has been known to induce both excitement and trepidation in researchers, akin to a rollercoaster ride at an amusement park – exhilarating for some and stomach-churning for others.

Control Variables
To guard against spurious correlations and confounding factors, control variables such as population demographics, economic indicators, and the number of volcanoes in close proximity to polling stations were considered. These control variables served as the proverbial guardrails on this statistical highway, ensuring that our findings remained grounded in sound analytical principles rather than veering into speculative territory.

Interdisciplinary Consultation
Given the unconventional nature of our investigation, consultations with experts across diverse fields were instrumental in shaping our research approach. Insights from political scientists, geologists, statisticians, and even a few enthusiastic conspiracy theorists were instrumental in broadening our perspectives and ensuring a comprehensive understanding of the multifaceted Democra-Magma connection.

Ethical Considerations
In adherence to ethical research practices, the anonymity and confidentiality of individual voting preferences and geothermal power producers were carefully safeguarded. Not to mention, maintaining ethical rigor in research is the scientific equivalent of flossing – often overlooked, but undeniably essential for the long-term health of the discipline.

In summary, the methodology employed in this study exemplifies a harmonious fusion of meticulous data collection, robust statistical analysis, interdisciplinary collaboration, and a sprinkling of humor – because let's face it, when dealing with unexpected correlations, a bit of levity goes a long way in demystifying the complexities of science.


Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 Massachusetts and Geothermal power generated in Indonesia. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

For the time period 1982 to 2020, you found a correlation 0.9875980, r-squared of 0.9753499, 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]]
"The Democra-Magma Connection: Exploring the Surprising Relationship Between Democratic Vote Share in Massachusetts and Geothermal Power Generation in Indonesia"

[[ABSTRACT]]
This paper presents a comprehensive analysis of the curious correlation between the percentage of votes for the Democratic presidential candidate in the state of Massachusetts and the annual geothermal power generation in Indonesia. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, this study covers the time period from 1982 to 2020. Through rigorous statistical analysis, a remarkably high correlation coefficient of 0.9875980 and a statistically significant p-value of less than 0.01 were observed. The implications of these findings are far-reaching, raising questions about the interplay between political preference in Massachusetts and geothermal energy extraction halfway across the globe. This study not only sheds light on these unexpected associations but also underscores the importance of exploring seemingly unrelated phenomena in the pursuit of scientific understanding.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Introduction
The intertwined dynamics between seemingly disparate variables have long captivated researchers across various disciplines. The peculiar relationship between the political climate in Massachusetts and the geothermal activity in Indonesia represents an intriguing puzzle in the realm of social and environmental sciences. This study delves into the enigmatic correlation, aiming to elucidate the underlying mechanisms driving the unexpected connection between the percentage of votes for the Democratic presidential candidate in Massachusetts and the geothermal power generation in Indonesia.
At first glance, one might be forgiven for dismissing this association as mere happenstance, a statistical fluke born from the complexities of data analysis. However, upon closer examination, the robustness of this correlation challenges conventional notions of causality and demands a rigorous investigation. With meticulous attention to detail and a keen eye for statistical nuance, this study endeavors to unravel the mystery behind this surprising Democra-Magma connection.
The choice of Massachusetts and Indonesia as the focal points of this investigation is not arbitrary. Massachusetts, known for its rich political history and academic prowess, provides a unique backdrop for examining voting patterns in a region with a distinct political landscape. On the other hand, Indonesia, a vast and diverse archipelago nestled within the Pacific Ring of Fire, stands as a global hotspot for geothermal energy production. The juxtaposition of these two geographically and culturally distinct regions adds an element of intrigue to our exploration of the interconnectedness of political sentiment and geothermal activity.
As we embark on this scientific endeavor, it is essential to acknowledge the inherent skepticism that may greet such an unorthodox investigation. Yet, it is precisely within the realms of the unconventional that groundbreaking discoveries often await. By embracing the unanticipated and challenging the boundaries of traditional disciplinary boundaries, we open doors to unanticipated insights and aha moments that defy the constraints of conventional wisdom.
In the pursuit of understanding complex phenomena, it is vital to embrace an open-minded approach that welcomes unexpected correlations and their implications. Through rigorous empirical analysis and an unwavering commitment to scientific inquiry, we aim to not only unravel the intricacies of the Democra-Magma connection but also to inspire further curiosity and exploration in the relentless pursuit of knowledge. Join us on this intellectual expedition as we venture into the uncharted territories of political-geothermal interplay, where statistical analysis meets a touch of serendipity, and scholarly pursuits dare to defy traditional norms.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our analysis revealed a striking correlation between the percentage of votes for the Democratic presidential candidate in Massachusetts and the annual geothermal power generation in Indonesia. Over the time period spanning from 1982 to 2020, we found a correlation coefficient of 0.9875980, indicating a remarkably strong linear relationship between these two seemingly disparate variables. The r-squared value of 0.9753499 further underscores the robustness of this association, explaining approximately 97.5% of the variance in geothermal power generation in Indonesia based on the Democratic vote share in Massachusetts.

The statistical significance of this correlation was reaffirmed by a p-value of less than 0.01, prompting a collective eyebrow raise among the research team. It seems that the probability of this association occurring by mere chance is less than the probability of your pen running out of ink right when you're about to write down your groundbreaking scientific hypothesis. In other words, it's highly unlikely.

Figure 1 depicts a scatterplot illustrating the conspicuous link between Democratic vote share in Massachusetts and geothermal power generation in Indonesia. The data points form a nearly perfect straight line, akin to a student diligently following the strict guidelines of an exam, leaving little room for error or deviation. It's as if these variables have formed an unexpected but unbreakable bond, akin to the unspoken friendship between lab partners who have been through countless experiments together.

Upon reflection, our findings challenge conventional wisdom and beckon further exploration into the underlying mechanisms at play. Perhaps there's a geothermal vent hidden beneath the hallowed grounds of Massachusetts, or maybe there's a "Democrat for Geothermal Energy" grassroots movement quietly shaping the energy policy dynamics in Indonesia. The possibilities are as intriguing as they are enigmatic, much like a good mystery novel that leaves you guessing till the very end.

In conclusion, the discovery of this hitherto overlooked association between political preference in Massachusetts and geothermal power production in Indonesia underscores the intricate interconnections that abound in the world of seemingly unrelated variables. This study not only adds a touch of whimsy to the often serious realm of statistical analysis but also implores researchers to cast a wider net in search of unanticipated correlations that may yield unexpected insights. After all, as we navigate the labyrinthine pathways of statistical analysis, a bit of serendipity may be just the ingredient needed to unravel the enigmas of our world.


Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Votes for the Democrat Presidential candidate in Massachusetts and Geothermal power generated in Indonesia. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"The Democra-Magma Connection: Exploring the Surprising Relationship Between Democratic Vote Share in Massachusetts and Geothermal Power Generation in Indonesia"

[[ABSTRACT]]
This paper presents a comprehensive analysis of the curious correlation between the percentage of votes for the Democratic presidential candidate in the state of Massachusetts and the annual geothermal power generation in Indonesia. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, this study covers the time period from 1982 to 2020. Through rigorous statistical analysis, a remarkably high correlation coefficient of 0.9875980 and a statistically significant p-value of less than 0.01 were observed. The implications of these findings are far-reaching, raising questions about the interplay between political preference in Massachusetts and geothermal energy extraction halfway across the globe. This study not only sheds light on these unexpected associations but also underscores the importance of exploring seemingly unrelated phenomena in the pursuit of scientific understanding.

[[LITERATURE REVIEW]]
The perplexing correlation between the percentage of votes for the Democratic presidential candidate in Massachusetts and the annual geothermal power generation in Indonesia has spurred a diverse array of academic inquiries and oddball investigations. Smith et al. (2015) laid the groundwork for this line of research, delving into the social, economic, and environmental factors shaping the interplay between political preferences in Massachusetts and global geothermal dynamics. Their rigorous analysis uncovered initial hints of a connection, setting the stage for subsequent scholarly endeavors.
Moving beyond the realm of austere academic tomes, we encounter a colorful array of non-fiction literature that tangentially touches on the nuances of political landscapes and geothermal forces. In "Renewable Energy: Power for a Sustainable Future" by Boyle (2012), the authors explore the potential of geothermal energy as a sustainable alternative to conventional power sources. While Boyle fails to mention the potential influence of Massachusetts' voting patterns on global geothermal dynamics, the underlying themes resonate with the broader discourse on energy production and its intersection with societal preferences.
On the fiction front, the narrative of unexpected linkages takes an intriguing twist. In Jules Verne's "Journey to the Center of the Earth," the protagonists embark on a tumultuous subterranean adventure, encountering fascinating geological phenomena along the way. While Verne's literary masterpiece is steeped in fantastical elements, its portrayal of Earth's inner workings serves as a whimsical reminder of the intricate interconnectedness of geothermal activities, albeit without any mentions of ballot boxes and political inclinations.
Venturing into the digital domain, popular internet memes have occasionally poked fun at the idiosyncrasies of Massachusetts' political landscape and the enigmatic allure of geothermal power. The "Boston Tea Party" meme, aptly referencing both Massachusetts' historical significance and the fervor for renewable energy, has emerged as a lighthearted nod to the state's political ethos. Furthermore, the "Geothermal Cat" meme, featuring a feline seemingly entrenched in Earth's scorching embrace, playfully hints at the pervasive reach of geothermal energy, if not its explicit ties to political voting behaviors.
As we navigate the labyrinth of literature and cultural references, it becomes evident that the Democra-Magma connection transcends the bounds of traditional scholarly inquiry, permeating various facets of creative expression and popular discourse. This interdisciplinary landscape sets the stage for a mélange of insights and curiosities, inviting us to ponder the unlikeliest of correlations with equal parts analytical rigor and whimsical wonderment.

[[RESULTS]]
The results of our analysis revealed a striking correlation between the percentage of votes for the Democratic presidential candidate in Massachusetts and the annual geothermal power generation in Indonesia. Over the time period spanning from 1982 to 2020, we found a correlation coefficient of 0.9875980, indicating a remarkably strong linear relationship between these two seemingly disparate variables. The r-squared value of 0.9753499 further underscores the robustness of this association, explaining approximately 97.5% of the variance in geothermal power generation in Indonesia based on the Democratic vote share in Massachusetts.
The statistical significance of this correlation was reaffirmed by a p-value of less than 0.01, prompting a collective eyebrow raise among the research team. It seems that the probability of this association occurring by mere chance is less than the probability of your pen running out of ink right when you're about to write down your groundbreaking scientific hypothesis. In other words, it's highly unlikely.
Figure 1 depicts a scatterplot illustrating the conspicuous link between Democratic vote share in Massachusetts and geothermal power generation in Indonesia. The data points form a nearly perfect straight line, akin to a student diligently following the strict guidelines of an exam, leaving little room for error or deviation. It's as if these variables have formed an unexpected but unbreakable bond, akin to the unspoken friendship between lab partners who have been through countless experiments together.
Upon reflection, our findings challenge conventional wisdom and beckon further exploration into the underlying mechanisms at play. Perhaps there's a geothermal vent hidden beneath the hallowed grounds of Massachusetts, or maybe there's a "Democrat for Geothermal Energy" grassroots movement quietly shaping the energy policy dynamics in Indonesia. The possibilities are as intriguing as they are enigmatic, much like a good mystery novel that leaves you guessing till the very end.
In conclusion, the discovery of this hitherto overlooked association between political preference in Massachusetts and geothermal power production in Indonesia underscores the intricate interconnections that abound in the world of seemingly unrelated variables. This study not only adds a touch of whimsy to the often serious realm of statistical analysis but also implores researchers to cast a wider net in search of unanticipated correlations that may yield unexpected insights. After all, as we navigate the labyrinthine pathways of statistical analysis, a bit of serendipity may be just the ingredient needed to unravel the enigmas of our world.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our findings unveil a truly astonishing intercontinental tango between the political palette of Massachusetts and the geothermal choreography of Indonesia. The correlation coefficient of 0.9875980, reminiscent of a well-orchestrated symphony, showcases the harmonious alignment between the percentage of Democratic votes in Massachusetts and the annual geothermal power generation in Indonesia. The statistical significance of this correlation, with a p-value less likely than stumbling upon a unicorn riding a unicycle, underscores the robustness of this unexpected relationship.

Building on the light-hearted observations of our literature review, we find that this serendipitous alliance between electoral leanings and geothermal activity defies conventional notions of causality. It's as if the voters in Massachusetts are subconsciously sending geothermal energy vibes across the oceans, or maybe there's a geothermal deity with a soft spot for democratic preferences. Our results not only corroborate the initial hints of a connection put forth by Smith et al. (2015) but also offer a trajectory for further scholarly inquiry into this Democra-Magma enigma.

The scatterplot, akin to a well-behaved herd of statistical data points, visually encapsulates the almost telepathic correspondence between these seemingly disparate variables. It's as if Massachusetts is whispering, "I'm with you, geothermal energy," declaring a partisan allegiance to sustainable power generation. Meanwhile, Indonesia responds with an appreciative nod, reciprocating the sentiment by cranking up its geothermal prowess. This unspoken dialogue transcends the realm of pure numbers, personifying the intertwining dance of politics and geothermal energy on the global stage.

Our study propels the academically inclined and the whimsically inclined alike to ponder the enigmatic forces at play. Could there be a clandestine underground tunnel linking Massachusetts to Indonesia, transporting political ideologies and geothermal fervor across continents? Or perhaps, this Democra-Magma connection is a testament to the interconnectedness of the world, much like the six degrees of separation, albeit with a volcanic twist. As we navigate the captivating labyrinth of statistical inquiry, our gaze inevitably turns to a broader canvas of unanticipated correlations, where the peculiar and the profound converge in a scientific pas de deux.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Votes for the Democrat Presidential candidate in Massachusetts and Geothermal power generated in Indonesia. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"The Democra-Magma Connection: Exploring the Surprising Relationship Between Democratic Vote Share in Massachusetts and Geothermal Power Generation in Indonesia"

[[ABSTRACT]]
This paper presents a comprehensive analysis of the curious correlation between the percentage of votes for the Democratic presidential candidate in the state of Massachusetts and the annual geothermal power generation in Indonesia. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, this study covers the time period from 1982 to 2020. Through rigorous statistical analysis, a remarkably high correlation coefficient of 0.9875980 and a statistically significant p-value of less than 0.01 were observed. The implications of these findings are far-reaching, raising questions about the interplay between political preference in Massachusetts and geothermal energy extraction halfway across the globe. This study not only sheds light on these unexpected associations but also underscores the importance of exploring seemingly unrelated phenomena in the pursuit of scientific understanding.

[[INTRDUCTION]]
Introduction
The intertwined dynamics between seemingly disparate variables have long captivated researchers across various disciplines. The peculiar relationship between the political climate in Massachusetts and the geothermal activity in Indonesia represents an intriguing puzzle in the realm of social and environmental sciences. This study delves into the enigmatic correlation, aiming to elucidate the underlying mechanisms driving the unexpected connection between the percentage of votes for the Democratic presidential candidate in Massachusetts and the geothermal power generation in Indonesia.
At first glance, one might be forgiven for dismissing this association as mere happenstance, a statistical fluke born from the complexities of data analysis. However, upon closer examination, the robustness of this correlation challenges conventional notions of causality and demands a rigorous investigation. With meticulous attention to detail and a keen eye for statistical nuance, this study endeavors to unravel the mystery behind this surprising Democra-Magma connection.
The choice of Massachusetts and Indonesia as the focal points of this investigation is not arbitrary. Massachusetts, known for its rich political history and academic prowess, provides a unique backdrop for examining voting patterns in a region with a distinct political landscape. On the other hand, Indonesia, a vast and diverse archipelago nestled within the Pacific Ring of Fire, stands as a global hotspot for geothermal energy production. The juxtaposition of these two geographically and culturally distinct regions adds an element of intrigue to our exploration of the interconnectedness of political sentiment and geothermal activity.
As we embark on this scientific endeavor, it is essential to acknowledge the inherent skepticism that may greet such an unorthodox investigation. Yet, it is precisely within the realms of the unconventional that groundbreaking discoveries often await. By embracing the unanticipated and challenging the boundaries of traditional disciplinary boundaries, we open doors to unanticipated insights and aha moments that defy the constraints of conventional wisdom.
In the pursuit of understanding complex phenomena, it is vital to embrace an open-minded approach that welcomes unexpected correlations and their implications. Through rigorous empirical analysis and an unwavering commitment to scientific inquiry, we aim to not only unravel the intricacies of the Democra-Magma connection but also to inspire further curiosity and exploration in the relentless pursuit of knowledge. Join us on this intellectual expedition as we venture into the uncharted territories of political-geothermal interplay, where statistical analysis meets a touch of serendipity, and scholarly pursuits dare to defy traditional norms.

[[RESULTS]]
The results of our analysis revealed a striking correlation between the percentage of votes for the Democratic presidential candidate in Massachusetts and the annual geothermal power generation in Indonesia. Over the time period spanning from 1982 to 2020, we found a correlation coefficient of 0.9875980, indicating a remarkably strong linear relationship between these two seemingly disparate variables. The r-squared value of 0.9753499 further underscores the robustness of this association, explaining approximately 97.5% of the variance in geothermal power generation in Indonesia based on the Democratic vote share in Massachusetts.
The statistical significance of this correlation was reaffirmed by a p-value of less than 0.01, prompting a collective eyebrow raise among the research team. It seems that the probability of this association occurring by mere chance is less than the probability of your pen running out of ink right when you're about to write down your groundbreaking scientific hypothesis. In other words, it's highly unlikely.
Figure 1 depicts a scatterplot illustrating the conspicuous link between Democratic vote share in Massachusetts and geothermal power generation in Indonesia. The data points form a nearly perfect straight line, akin to a student diligently following the strict guidelines of an exam, leaving little room for error or deviation. It's as if these variables have formed an unexpected but unbreakable bond, akin to the unspoken friendship between lab partners who have been through countless experiments together.
Upon reflection, our findings challenge conventional wisdom and beckon further exploration into the underlying mechanisms at play. Perhaps there's a geothermal vent hidden beneath the hallowed grounds of Massachusetts, or maybe there's a "Democrat for Geothermal Energy" grassroots movement quietly shaping the energy policy dynamics in Indonesia. The possibilities are as intriguing as they are enigmatic, much like a good mystery novel that leaves you guessing till the very end.
In conclusion, the discovery of this hitherto overlooked association between political preference in Massachusetts and geothermal power production in Indonesia underscores the intricate interconnections that abound in the world of seemingly unrelated variables. This study not only adds a touch of whimsy to the often serious realm of statistical analysis but also implores researchers to cast a wider net in search of unanticipated correlations that may yield unexpected insights. After all, as we navigate the labyrinthine pathways of statistical analysis, a bit of serendipity may be just the ingredient needed to unravel the enigmas of our world.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

The compelling correlation between Democratic vote share in Massachusetts and geothermal power production in Indonesia has left us both astounded and amused. Through rigorous statistical analysis, we've unraveled a relationship that is as baffling as it is captivating. It's like finding a hidden treasure map in the footnotes of a bureaucratic document - unexpected, yet undeniably thrilling.

The robust correlation coefficient of 0.9875980 has solidified the bond between these seemingly unrelated variables, akin to the unbreakable alliance between peanut butter and jelly. Our findings challenge conventional realities and beckon further investigation into the mysterious forces shaping this curious connection. The statistical significance of this association is about as likely as finding a statistically significant p-value in a sea of random data.

In the realm of scholarly pursuits, embracing the unexpected can often lead to groundbreaking revelations. Our study not only emphasizes the importance of thinking outside the box but also highlights the whimsy that can emanate from the world of statistical analysis. It's as if the data points themselves were whispering secrets of hidden ties between politics and geothermal activity, akin to a plot twist in a riveting detective novel.

As we close this chapter, we assert that the Democra-Magma connection stands as a fortuitous anomaly in the annals of statistical inquiry. Akin to stumbling upon a scientific Easter egg, it highlights the serendipitous nature of research endeavors. The pursuit of unanticipated correlations and their implications reveals the potential for unexpected insights that can mold the landscape of scientific understanding. In this spirit, we assert confidently that no more research is needed in this area. After all, sometimes, a touch of serendipity is all it takes to illuminate the uncharted territories of statistical interplay.

This concludes our investigation. As we bid adieu to the Democra-Magma connection, we invite fellow scholars to embark on their own intellectual expeditions – where the unexpected may be the key to unlocking the mysteries of our world.


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 The Democra-Magma Connection: Exploring the Surprising Relationship Between Democratic Vote Share in Massachusetts and Geothermal Power Generation in Indonesia. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Geopolitical Geothermal Studies


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 The Democra-Magma Connection: Exploring the Surprising Relationship Between Democratic Vote Share in Massachusetts and Geothermal Power Generation in Indonesia. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Democratic Geothermal Studies


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 The Democra-Magma Connection: Exploring the Surprising Relationship Between Democratic Vote Share in Massachusetts and Geothermal Power Generation in Indonesia with an abstract of This paper presents a comprehensive analysis of the curious correlation between the percentage of votes for the Democratic presidential candidate in the state of Massachusetts and the annual geothermal power generation in Indonesia. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, this study covers the time period from 1982 to 2020. Through rigorous statistical analysis, a remarkably high correlation coefficient of 0.9875980 and a statistically significant p-value of less than 0.01 were observed. The implications of these findings are far-reaching, raising questions about the interplay between political preference in Massachusetts and geothermal energy extraction halfway across the globe. This study not only sheds light on these unexpected associations but also underscores the importance of exploring seemingly unrelated phenomena in the pursuit of scientific understanding.

ChatGPT:

Democratic vote share, Massachusetts, geothermal power generation, Indonesia, correlation, statistical analysis, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration, political preference, geothermal energy extraction, correlation coefficient

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

Geothermal power generated in Indonesia
Detailed data title: Total geothermal power generated in Indonesia in billion kWh
Source: Energy Information Administration
See what else correlates with Geothermal power generated in Indonesia

Correlation r = 0.9875980 (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 = 0.9753499 (Coefficient of determination)
This means 97.5% of the change in the one variable (i.e., Geothermal power generated in Indonesia) is predictable based on the change in the other (i.e., Votes for the Democratic Presidential candidate in Massachusetts) over the 10 years from 1982 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.02E-7. 0.0000001019677881502102200000
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 0.99 in 1.02E-5% of random cases. Said differently, if you correlated 9,807,019 random variables You don't actually need 9 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 9 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 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.

[ 0.95, 1 ] 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.
1984198819921996200020042008201220162020
Votes for the Democratic Presidential candidate in Massachusetts (Total votes)1239610140142013186401571510161649018038001904100192129019952002382200
Geothermal power generated in Indonesia (Billion kWh)0.2050.9611.0842.3524.8696.6568.3099.41710.65615.563




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. Confounding variable: 2020 is particularly different from the other years on this graph. Confounding variables (like global pandemics) will cause two variables to look connected when in fact a "sneaky third" variable is influencing both of them behind the scenes.
  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([1239610,1401420,1318640,1571510,1616490,1803800,1904100,1921290,1995200,2382200,])
array_2 = np.array([0.205,0.961,1.084,2.352,4.869,6.656,8.309,9.417,10.656,15.563,])
array_1_name = "Votes for the Democratic Presidential candidate in Massachusetts"
array_2_name = "Geothermal power generated in Indonesia"

# 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: 4611 · Black Variable ID: 25990 · Red Variable ID: 23737
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