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AI explanation
As the Democrat votes for Senators in Alaska went up, so did the support for renewable energy initiatives. This led to a spike in LPG production, creating a 'gassy' situation in Kiribati.Model: dalle-3
Prompt: An image that looks like it is a scene from 'Star Wars' showing a futuristic landscape with towering renewable energy posters and a graph depicting rising Democratic votes in Alaska. In the foreground, LPG tanks are being used in Kiribati, emitting a vibrant glow amidst the 'gassy' situation. The setting should be visually stunning and capture the futuristic, otherworldly feel of 'Star Wars' while incorporating the elements of the scene described. 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 Democratic Senators in Alaska and Liquefied petroleum gas used in Kiribati. 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: Realistic Oragami Brutalism Charcoal An image that looks like it is a scene from 'Star Wars'
ChatGPT: An image that looks like it is a scene from 'Star Wars'
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 Democratic Senators in Alaska and Liquefied petroleum gas used in Kiribati, in the following situation: As the Democrat votes for Senators in Alaska went up, so did the support for renewable energy initiatives. This led to a spike in LPG production, creating a 'gassy' situation in Kiribati.. Keep the description simple.
ChatGPT: In Alaska, more people marked their votes for Democratic Senators, and the support for renewable energy initiatives got a boost. This led to an increase in LPG production. In Kiribati, the LPG usage became more prominent, creating a 'gassy' situation. Picture a graph showing rising Democratic votes in Alaska, while in Kiribati, more LPG tanks are being used, surrounded by renewable energy posters.
Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ An image that looks like it is a scene from 'Star Wars' ] and depicting this scene: In Alaska, more people marked their votes for Democratic Senators, and the support for renewable energy initiatives got a boost. This led to an increase in LPG production. In Kiribati, the LPG usage became more prominent, creating a 'gassy' situation. Picture a graph showing rising Democratic votes in Alaska, while in Kiribati, more LPG tanks are being used, surrounded by renewable energy posters. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: An image that looks like it is a scene from 'Star Wars' showing a futuristic landscape with towering renewable energy posters and a graph depicting rising Democratic votes in Alaska. In the foreground, LPG tanks are being used in Kiribati, emitting a vibrant glow amidst the 'gassy' situation. The setting should be visually stunning and capture the futuristic, otherworldly feel of 'Star Wars' while incorporating the elements of the scene described.
*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.
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 Democrat votes for Senators in Alaska caused Liquefied petroleum gas used in Kiribati to increase. Include one good pun.
AI academic paper
The Gas-tly Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati The Journal of Quirky Social Science Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Alaska and Liquefied petroleum gas used in Kiribati. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Make the title punny if you can come up with clever pun. If not, make it sound serious.
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 0.8013688 and p < 0.05 for 2000 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 "Gas-tly" Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati
[[ABSTRACT]]
This paper sets out to investigate the surprising and gasp-inducing relationship between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we conducted a comprehensive analysis spanning the years 2000 to 2020. Our findings reveal a strong correlation coefficient of 0.8013688 and a statistically significant p-value of less than 0.05, indicating a robust association between these seemingly disparate variables. It seems that the political preferences in the land of the midnight sun could be influencing household energy choices in the tropical island nation.
In our exploration, we uncovered a notable positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. This unexpected link suggests that political leanings and energy usage may be intertwined in ways previously uncharted. It's clear that when it comes to energy choices, political sentiments can have a "gas-tly" influence, much like an unattended barbecue grill.
Further research is imperative to fully comprehend the underlying mechanisms driving this connection. With this compelling correlation laid bare, our study sheds light on the intersection of political behavior and energy consumption, emphasizing the need for interdisciplinary investigation in the realm of social and environmental dynamics. After all, understanding this curious relationship could have significant implications for energy policies and political strategies alike. As we continue to unravel these connections, we are reminded that in the world of statistics, there's always room for a good dad joke to "lighten" things up.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Alaska and Liquefied petroleum gas used in Kiribati. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 "Gas-tly" Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati
[[ABSTRACT]]
This paper sets out to investigate the surprising and gasp-inducing relationship between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we conducted a comprehensive analysis spanning the years 2000 to 2020. Our findings reveal a strong correlation coefficient of 0.8013688 and a statistically significant p-value of less than 0.05, indicating a robust association between these seemingly disparate variables. It seems that the political preferences in the land of the midnight sun could be influencing household energy choices in the tropical island nation.
In our exploration, we uncovered a notable positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. This unexpected link suggests that political leanings and energy usage may be intertwined in ways previously uncharted. It's clear that when it comes to energy choices, political sentiments can have a "gas-tly" influence, much like an unattended barbecue grill.
Further research is imperative to fully comprehend the underlying mechanisms driving this connection. With this compelling correlation laid bare, our study sheds light on the intersection of political behavior and energy consumption, emphasizing the need for interdisciplinary investigation in the realm of social and environmental dynamics. After all, understanding this curious relationship could have significant implications for energy policies and political strategies alike. As we continue to unravel these connections, we are reminded that in the world of statistics, there's always room for a good dad joke to "lighten" things up.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
As the saying goes, "politics makes strange bedfellows," but who would have thought it could also make for an unexpected pairing with energy consumption? In this study, we delve into the "Gas-tly" Connection, examining the curious correlation between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. It's a relationship that's sure to make you do a double take, much like realizing you accidentally mixed up the control and treatment groups in your experiment.
The idea that political preferences in the frigid wilderness of Alaska could reverberate all the way to the sun-drenched shores of Kiribati may seem as improbable as successfully explaining statistical significance to your non-researcher friends at a dinner party. However, our analysis reveals a surprising connection that defies conventional wisdom and warrants further investigation. It's almost as unexpected as finding a statistically significant p-value in a dataset that's as messy as a lab after an experiment gone wrong.
Our study uncovers a compelling positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. It's as if the ties that bind energy usage and political leanings are as strong and inexplicable as the force keeping the socks from the dryer apart. This unforeseen correspondence raises thought-provoking questions about the intricate interplay between political factors and energy decisions, leaving us pondering the perplexing nature of statistical relationships like pondering why a round pizza is served in a square box, and enjoyed in triangular slices.
Much like a detective solving a mystery, we aim to unravel the underlying mechanisms driving this unlikely association. These findings emphasize the need for interdisciplinary exploration, reminding us that the nexus of social, environmental dynamics, and statistical analysis can be as enigmatic as trying to define the placebo effect in a hilarious yet informative dad joke. With this unconventional correlation unveiled, it's evident that the world of statistics and science can always benefit from a lighthearted quip to break the ice – or in our case, the "gas."
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Alaska and Liquefied petroleum gas used in Kiribati. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then 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]]
The "Gas-tly" Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati
[[ABSTRACT]]
This paper sets out to investigate the surprising and gasp-inducing relationship between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we conducted a comprehensive analysis spanning the years 2000 to 2020. Our findings reveal a strong correlation coefficient of 0.8013688 and a statistically significant p-value of less than 0.05, indicating a robust association between these seemingly disparate variables. It seems that the political preferences in the land of the midnight sun could be influencing household energy choices in the tropical island nation.
In our exploration, we uncovered a notable positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. This unexpected link suggests that political leanings and energy usage may be intertwined in ways previously uncharted. It's clear that when it comes to energy choices, political sentiments can have a "gas-tly" influence, much like an unattended barbecue grill.
Further research is imperative to fully comprehend the underlying mechanisms driving this connection. With this compelling correlation laid bare, our study sheds light on the intersection of political behavior and energy consumption, emphasizing the need for interdisciplinary investigation in the realm of social and environmental dynamics. After all, understanding this curious relationship could have significant implications for energy policies and political strategies alike. As we continue to unravel these connections, we are reminded that in the world of statistics, there's always room for a good dad joke to "lighten" things up.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As the saying goes, "politics makes strange bedfellows," but who would have thought it could also make for an unexpected pairing with energy consumption? In this study, we delve into the "Gas-tly" Connection, examining the curious correlation between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. It's a relationship that's sure to make you do a double take, much like realizing you accidentally mixed up the control and treatment groups in your experiment.
The idea that political preferences in the frigid wilderness of Alaska could reverberate all the way to the sun-drenched shores of Kiribati may seem as improbable as successfully explaining statistical significance to your non-researcher friends at a dinner party. However, our analysis reveals a surprising connection that defies conventional wisdom and warrants further investigation. It's almost as unexpected as finding a statistically significant p-value in a dataset that's as messy as a lab after an experiment gone wrong.
Our study uncovers a compelling positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. It's as if the ties that bind energy usage and political leanings are as strong and inexplicable as the force keeping the socks from the dryer apart. This unforeseen correspondence raises thought-provoking questions about the intricate interplay between political factors and energy decisions, leaving us pondering the perplexing nature of statistical relationships like pondering why a round pizza is served in a square box, and enjoyed in triangular slices.
Much like a detective solving a mystery, we aim to unravel the underlying mechanisms driving this unlikely association. These findings emphasize the need for interdisciplinary exploration, reminding us that the nexus of social, environmental dynamics, and statistical analysis can be as enigmatic as trying to define the placebo effect in a hilarious yet informative dad joke. With this unconventional correlation unveiled, it's evident that the world of statistics and science can always benefit from a lighthearted quip to break the ice – or in our case, the "gas."
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
Previous research has made significant strides in understanding the complex interplay between political preferences and various societal outcomes. Smith et al. (2015) examined the impact of political affiliations on energy usage patterns in diverse geographical contexts, laying the groundwork for our current investigation. Meanwhile, Doe and Jones (2017) delved into the intricate dynamics of political behavior and its potential ripple effects on international energy markets, providing valuable insights that inform our exploration of the "Gas-tly" Connection.
It is undeniable that the relationship between Democrat votes for Senators in Alaska and LPG consumption in Kiribati is as unexpected as finding a polar bear in a tropical rainforest, or stumbling upon a statistical outlier in an otherwise neatly arranged dataset. This peculiar correlation has prompted us to cast a wide net in our review of related literature, extracting knowledge and inspiration from both expected and unlikely sources alike.
Turning to non-fiction works, "The Big Thaw: Travels in the Melting North" by Ed Struzik and "Energy Politics" by Brenda Shaffer offer valuable insights into the complexities of energy dynamics and global political landscapes. While these works do not directly address the specific juxtaposition of political votes in Alaska and LPG usage in Kiribati, they serve as a reminder that the world of energy and politics is as unpredictable as predicting an unexpected refractory period in a regression model for a binge-watching dataset.
On the fictional side, "The Call of the Wild" by Jack London and "One Hundred Years of Solitude" by Gabriel García Márquez draw attention to the mystical and unpredictable nature of human connection and environmental influence. Although these novels may not explicitly touch upon the intersection of political choices and energy consumption, they inspire us to embrace the unexpected and explore correlations that might seem as improbable as navigating a statistical forest without a compass.
The pursuit of a deeper understanding has led us to embrace unconventional sources of insight as well. Drawing on our enviable dedication to scholarly pursuits, we found valuable inspiration in children's shows such as "Blue's Clues" and "Dora the Explorer." Their fervent spirit of exploration and problem-solving has invigorated our approach to uncovering the unexpected correlation between political votes in Alaska and LPG usage in Kiribati. After all, who would have thought that statistical discoveries and children's TV could share the same spirit of curiosity and wonder?
As we synthesize these diverse sources of inspiration and knowledge, it becomes evident that the intersection of political choices and energy consumption offers a realm of discovery as vast and enigmatic as the universe itself. Indeed, uncovering the unexpected ties that bind the political and the energetic invites us to embrace the wonder of discovery with a lighthearted spirit, much like finding joy in a well-crafted dad joke amidst the rigors of scholarly pursuit.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Alaska and Liquefied petroleum gas used in Kiribati. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 2000 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 "Gas-tly" Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati
[[ABSTRACT]]
This paper sets out to investigate the surprising and gasp-inducing relationship between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we conducted a comprehensive analysis spanning the years 2000 to 2020. Our findings reveal a strong correlation coefficient of 0.8013688 and a statistically significant p-value of less than 0.05, indicating a robust association between these seemingly disparate variables. It seems that the political preferences in the land of the midnight sun could be influencing household energy choices in the tropical island nation.
In our exploration, we uncovered a notable positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. This unexpected link suggests that political leanings and energy usage may be intertwined in ways previously uncharted. It's clear that when it comes to energy choices, political sentiments can have a "gas-tly" influence, much like an unattended barbecue grill.
Further research is imperative to fully comprehend the underlying mechanisms driving this connection. With this compelling correlation laid bare, our study sheds light on the intersection of political behavior and energy consumption, emphasizing the need for interdisciplinary investigation in the realm of social and environmental dynamics. After all, understanding this curious relationship could have significant implications for energy policies and political strategies alike. As we continue to unravel these connections, we are reminded that in the world of statistics, there's always room for a good dad joke to "lighten" things up.
[[INTRODUCTION]]
As the saying goes, "politics makes strange bedfellows," but who would have thought it could also make for an unexpected pairing with energy consumption? In this study, we delve into the "Gas-tly" Connection, examining the curious correlation between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. It's a relationship that's sure to make you do a double take, much like realizing you accidentally mixed up the control and treatment groups in your experiment.
The idea that political preferences in the frigid wilderness of Alaska could reverberate all the way to the sun-drenched shores of Kiribati may seem as improbable as successfully explaining statistical significance to your non-researcher friends at a dinner party. However, our analysis reveals a surprising connection that defies conventional wisdom and warrants further investigation. It's almost as unexpected as finding a statistically significant p-value in a dataset that's as messy as a lab after an experiment gone wrong.
Our study uncovers a compelling positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. It's as if the ties that bind energy usage and political leanings are as strong and inexplicable as the force keeping the socks from the dryer apart. This unforeseen correspondence raises thought-provoking questions about the intricate interplay between political factors and energy decisions, leaving us pondering the perplexing nature of statistical relationships like pondering why a round pizza is served in a square box, and enjoyed in triangular slices.
Much like a detective solving a mystery, we aim to unravel the underlying mechanisms driving this unlikely association. These findings emphasize the need for interdisciplinary exploration, reminding us that the nexus of social, environmental dynamics, and statistical analysis can be as enigmatic as trying to define the placebo effect in a hilarious yet informative dad joke. With this unconventional correlation unveiled, it's evident that the world of statistics and science can always benefit from a lighthearted quip to break the ice – or in our case, the "gas."
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To investigate the "Gas-tly" Connection between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati, we employed a variety of methodological approaches that were as diverse as the political landscape and as dynamic as the energy market itself. Our team compiled data from multiple sources, primarily harnessing information from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration. To ensure a comprehensive analysis, we gathered data spanning the years 2000 to 2020, creating a dataset as robust and intriguing as a statistical anomaly that just can't be explained.
Our research methodology involved a two-pronged approach, akin to splitting an atom, but without the nuclear implications. First, we utilized sophisticated statistical techniques, including regression analysis and correlation measures, to uncover any patterns or connections between the variables of interest. We lovingly nurtured the data, just like a scientist tends to a prized lab specimen, to ensure that our statistical analyses were as pristine as a freshly cleaned Petri dish.
We employed multiple regression models to control for potential confounding variables, carefully adjusting for factors such as economic indicators, climate trends, and geopolitical events that could sway the results. In addition, we conducted sensitivity analyses to ensure the robustness of our findings, navigating through the data as deftly as a sailor on the high seas of statistical inference.
To examine the solidity of the relationship between Democrat votes for Senators in Alaska and LPG consumption in Kiribati, we calculated correlation coefficients and inferred the magnitude of the association between these seemingly distinct variables. As we scrutinized the data, we meticulously extracted insights that were as unexpected and delightful as stumbling upon a hidden treasure chest during environmental statistics class.
Furthermore, in a quest to establish causality, we explored potential mediating and moderating variables that could elucidate the underlying mechanisms governing this intriguing relationship. We delved into the data with a sense of curiosity similar to unraveling a challenging riddle, hoping to demystify the intricate dynamics between political preferences and energy choices in a manner as riveting as solving a particularly confounding math problem.
In addition to our quantitative analyses, we conducted qualitative interviews with experts in political science, energy economics, and interdisciplinary studies, gaining invaluable insights that were as enlightening as finding a particularly illuminating bulb while conducting fieldwork in a dimly lit laboratory.
Ultimately, our methodologies served as the compass guiding our exploration of the "Gas-tly" Connection, allowing us to navigate through the statistical landscape with as much assurance as a seasoned cartographer charting unexplored territories. Our unrelenting pursuit of scientific inquiry was accompanied by a sprinkling of statistical humor, because, as any good researcher knows, a well-placed dad joke never fails to "lighten" the mood and, perhaps, shed some light on the "Gas-tly" Connection.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Alaska and Liquefied petroleum gas used in Kiribati. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 2000 to 2020, you found a correlation 0.8013688, r-squared of 0.6421919, and p < 0.05.
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 "Gas-tly" Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati
[[ABSTRACT]]
This paper sets out to investigate the surprising and gasp-inducing relationship between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we conducted a comprehensive analysis spanning the years 2000 to 2020. Our findings reveal a strong correlation coefficient of 0.8013688 and a statistically significant p-value of less than 0.05, indicating a robust association between these seemingly disparate variables. It seems that the political preferences in the land of the midnight sun could be influencing household energy choices in the tropical island nation.
In our exploration, we uncovered a notable positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. This unexpected link suggests that political leanings and energy usage may be intertwined in ways previously uncharted. It's clear that when it comes to energy choices, political sentiments can have a "gas-tly" influence, much like an unattended barbecue grill.
Further research is imperative to fully comprehend the underlying mechanisms driving this connection. With this compelling correlation laid bare, our study sheds light on the intersection of political behavior and energy consumption, emphasizing the need for interdisciplinary investigation in the realm of social and environmental dynamics. After all, understanding this curious relationship could have significant implications for energy policies and political strategies alike. As we continue to unravel these connections, we are reminded that in the world of statistics, there's always room for a good dad joke to "lighten" things up.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
As the saying goes, "politics makes strange bedfellows," but who would have thought it could also make for an unexpected pairing with energy consumption? In this study, we delve into the "Gas-tly" Connection, examining the curious correlation between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. It's a relationship that's sure to make you do a double take, much like realizing you accidentally mixed up the control and treatment groups in your experiment.
The idea that political preferences in the frigid wilderness of Alaska could reverberate all the way to the sun-drenched shores of Kiribati may seem as improbable as successfully explaining statistical significance to your non-researcher friends at a dinner party. However, our analysis reveals a surprising connection that defies conventional wisdom and warrants further investigation. It's almost as unexpected as finding a statistically significant p-value in a dataset that's as messy as a lab after an experiment gone wrong.
Our study uncovers a compelling positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. It's as if the ties that bind energy usage and political leanings are as strong and inexplicable as the force keeping the socks from the dryer apart. This unforeseen correspondence raises thought-provoking questions about the intricate interplay between political factors and energy decisions, leaving us pondering the perplexing nature of statistical relationships like pondering why a round pizza is served in a square box, and enjoyed in triangular slices.
Much like a detective solving a mystery, we aim to unravel the underlying mechanisms driving this unlikely association. These findings emphasize the need for interdisciplinary exploration, reminding us that the nexus of social, environmental dynamics, and statistical analysis can be as enigmatic as trying to define the placebo effect in a hilarious yet informative dad joke. With this unconventional correlation unveiled, it's evident that the world of statistics and science can always benefit from a lighthearted quip to break the ice – or in our case, the "gas."
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The analysis of the data spanning from 2000 to 2020 revealed a noteworthy correlation coefficient of 0.8013688 between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) consumption in Kiribati. This correlation, indicated by an r-squared of 0.6421919 and a p-value of less than 0.05, suggests a robust and significant relationship between these seemingly unrelated variables. It seems that the political spectrum in the land of the midnight sun might be leaving a "fuel"ly impression on household energy choices in the tropical island nation, much like a strong barbeque aroma wafting through the air.
Fig. 1 displays a scatterplot illustrating the strong positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. This unexpected association highlights the intriguing interplay between political inclinations and energy preferences, leaving us pondering the peculiar ways in which statistical patterns can emerge, not unlike when you realize a "normal" distribution isn't quite as normal as you thought.
It's quite "shocking" to uncover such a "sparkling" relationship between two variables that one would not typically associate with each other, much like accidentally discovering a "current" of statistical significance running through your data. This compelling connection raises intriguing questions about the intricate dynamics shaping energy choices, similar to the curiosity that arises when pondering why the word "abbreviation" is so long.
Further examination and interdisciplinary inquiry are essential to fully comprehend the mechanisms driving this unexpected correlation. These findings emphasize the significance of exploring the complex relationship between political behaviors and energy consumption, highlighting the need to consider a wide range of factors in understanding these "electrifying" connections. As we continue to untangle the web of statistical relationships, we're reminded that a well-placed dad joke can always "lighten" the mood even in the most "charged" debates.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Alaska and Liquefied petroleum gas used in Kiribati. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 "Gas-tly" Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati
[[ABSTRACT]]
This paper sets out to investigate the surprising and gasp-inducing relationship between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we conducted a comprehensive analysis spanning the years 2000 to 2020. Our findings reveal a strong correlation coefficient of 0.8013688 and a statistically significant p-value of less than 0.05, indicating a robust association between these seemingly disparate variables. It seems that the political preferences in the land of the midnight sun could be influencing household energy choices in the tropical island nation.
In our exploration, we uncovered a notable positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. This unexpected link suggests that political leanings and energy usage may be intertwined in ways previously uncharted. It's clear that when it comes to energy choices, political sentiments can have a "gas-tly" influence, much like an unattended barbecue grill.
Further research is imperative to fully comprehend the underlying mechanisms driving this connection. With this compelling correlation laid bare, our study sheds light on the intersection of political behavior and energy consumption, emphasizing the need for interdisciplinary investigation in the realm of social and environmental dynamics. After all, understanding this curious relationship could have significant implications for energy policies and political strategies alike. As we continue to unravel these connections, we are reminded that in the world of statistics, there's always room for a good dad joke to "lighten" things up.
[[LITERATURE REVIEW]]
Previous research has made significant strides in understanding the complex interplay between political preferences and various societal outcomes. Smith et al. (2015) examined the impact of political affiliations on energy usage patterns in diverse geographical contexts, laying the groundwork for our current investigation. Meanwhile, Doe and Jones (2017) delved into the intricate dynamics of political behavior and its potential ripple effects on international energy markets, providing valuable insights that inform our exploration of the "Gas-tly" Connection.
It is undeniable that the relationship between Democrat votes for Senators in Alaska and LPG consumption in Kiribati is as unexpected as finding a polar bear in a tropical rainforest, or stumbling upon a statistical outlier in an otherwise neatly arranged dataset. This peculiar correlation has prompted us to cast a wide net in our review of related literature, extracting knowledge and inspiration from both expected and unlikely sources alike.
Turning to non-fiction works, "The Big Thaw: Travels in the Melting North" by Ed Struzik and "Energy Politics" by Brenda Shaffer offer valuable insights into the complexities of energy dynamics and global political landscapes. While these works do not directly address the specific juxtaposition of political votes in Alaska and LPG usage in Kiribati, they serve as a reminder that the world of energy and politics is as unpredictable as predicting an unexpected refractory period in a regression model for a binge-watching dataset.
On the fictional side, "The Call of the Wild" by Jack London and "One Hundred Years of Solitude" by Gabriel García Márquez draw attention to the mystical and unpredictable nature of human connection and environmental influence. Although these novels may not explicitly touch upon the intersection of political choices and energy consumption, they inspire us to embrace the unexpected and explore correlations that might seem as improbable as navigating a statistical forest without a compass.
The pursuit of a deeper understanding has led us to embrace unconventional sources of insight as well. Drawing on our enviable dedication to scholarly pursuits, we found valuable inspiration in children's shows such as "Blue's Clues" and "Dora the Explorer." Their fervent spirit of exploration and problem-solving has invigorated our approach to uncovering the unexpected correlation between political votes in Alaska and LPG usage in Kiribati. After all, who would have thought that statistical discoveries and children's TV could share the same spirit of curiosity and wonder?
As we synthesize these diverse sources of inspiration and knowledge, it becomes evident that the intersection of political choices and energy consumption offers a realm of discovery as vast and enigmatic as the universe itself. Indeed, uncovering the unexpected ties that bind the political and the energetic invites us to embrace the wonder of discovery with a lighthearted spirit, much like finding joy in a well-crafted dad joke amidst the rigors of scholarly pursuit.
[[RESULTS]]
The analysis of the data spanning from 2000 to 2020 revealed a noteworthy correlation coefficient of 0.8013688 between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) consumption in Kiribati. This correlation, indicated by an r-squared of 0.6421919 and a p-value of less than 0.05, suggests a robust and significant relationship between these seemingly unrelated variables. It seems that the political spectrum in the land of the midnight sun might be leaving a "fuel"ly impression on household energy choices in the tropical island nation, much like a strong barbeque aroma wafting through the air.
Fig. 1 displays a scatterplot illustrating the strong positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. This unexpected association highlights the intriguing interplay between political inclinations and energy preferences, leaving us pondering the peculiar ways in which statistical patterns can emerge, not unlike when you realize a "normal" distribution isn't quite as normal as you thought.
It's quite "shocking" to uncover such a "sparkling" relationship between two variables that one would not typically associate with each other, much like accidentally discovering a "current" of statistical significance running through your data. This compelling connection raises intriguing questions about the intricate dynamics shaping energy choices, similar to the curiosity that arises when pondering why the word "abbreviation" is so long.
Further examination and interdisciplinary inquiry are essential to fully comprehend the mechanisms driving this unexpected correlation. These findings emphasize the significance of exploring the complex relationship between political behaviors and energy consumption, highlighting the need to consider a wide range of factors in understanding these "electrifying" connections. As we continue to untangle the web of statistical relationships, we're reminded that a well-placed dad joke can always "lighten" the mood even in the most "charged" debates.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our study has unveiled an extraordinary correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati, presenting a novel lens through which to view the intricate dance between political leanings and energy choices. As we delve into the implications of these findings, it's clear that this "Gas-tly" connection has far-reaching ramifications that may "ignite" further inquiry and policy considerations in both political and energy spheres.
The unexpected correlation coefficient of 0.8013688 and the statistically significant p-value of less than 0.05 align closely with the prior research by Smith et al. (2015) and Doe and Jones (2017), who hinted at the interplay between political affiliations and energy usage patterns on a different stage. This "republica-largely" confirms the notion that political preferences could indeed "fuel" shifts in energy consumption, adding weight to the argument that energy choices might be more "politically charged" than initially thought.
Our study breathes new life into the relationship between seemingly unconnected variables, much like how a well-timed dad joke can bring levity to a rigorous academic conversation. The findings point to the potential influence of political climates on energy preferences, underscoring the need for further investigation into the psychological and sociological factors at play. It's as though we've stumbled upon an unexpected punchline in the realm of statistical analysis, much like discovering an "unbiased" coin that always seems to land on its edge in theoretical discussions.
Notably, our results encourage a reevaluation of the traditional boundaries within which we consider the impact of political choices, reminiscent of the delight of uncovering a "meta-analysis" that provides unexpected insights. Within this extravagant "correlation buffet," we are reminded that statistics and scientific inquiry can be as unpredictable as a surprise party in a controlled laboratory setting, urging us to embrace the unexpected with open arms and a ready quip.
As we peer into the vast landscape of future research, the "Gas-tly" connection offers a provocative avenue for probing the intersection of political behavior and energy consumption with the same fervor as a dedicated scholar unearthing hidden gems in a dataset. The implications of our findings extend beyond the statistical realm, inviting a broader discourse on the multifaceted impacts of political dynamics on global energy markets, much like a "regressional" whisper in a crowded room demanding attention.
Our study ultimately emphasizes the necessity of maintaining a lighthearted yet rigorous approach to exploring the intricacies of statistics and the unexpected correlations they reveal. After all, in the midst of scholarly pursuit, who can resist the "ohm"-ly force of a well-placed dad joke?
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Alaska and Liquefied petroleum gas used in Kiribati. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 "Gas-tly" Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati
[[ABSTRACT]]
This paper sets out to investigate the surprising and gasp-inducing relationship between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we conducted a comprehensive analysis spanning the years 2000 to 2020. Our findings reveal a strong correlation coefficient of 0.8013688 and a statistically significant p-value of less than 0.05, indicating a robust association between these seemingly disparate variables. It seems that the political preferences in the land of the midnight sun could be influencing household energy choices in the tropical island nation.
In our exploration, we uncovered a notable positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. This unexpected link suggests that political leanings and energy usage may be intertwined in ways previously uncharted. It's clear that when it comes to energy choices, political sentiments can have a "gas-tly" influence, much like an unattended barbecue grill.
Further research is imperative to fully comprehend the underlying mechanisms driving this connection. With this compelling correlation laid bare, our study sheds light on the intersection of political behavior and energy consumption, emphasizing the need for interdisciplinary investigation in the realm of social and environmental dynamics. After all, understanding this curious relationship could have significant implications for energy policies and political strategies alike. As we continue to unravel these connections, we are reminded that in the world of statistics, there's always room for a good dad joke to "lighten" things up.
[[INTRDUCTION]]
As the saying goes, "politics makes strange bedfellows," but who would have thought it could also make for an unexpected pairing with energy consumption? In this study, we delve into the "Gas-tly" Connection, examining the curious correlation between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. It's a relationship that's sure to make you do a double take, much like realizing you accidentally mixed up the control and treatment groups in your experiment.
The idea that political preferences in the frigid wilderness of Alaska could reverberate all the way to the sun-drenched shores of Kiribati may seem as improbable as successfully explaining statistical significance to your non-researcher friends at a dinner party. However, our analysis reveals a surprising connection that defies conventional wisdom and warrants further investigation. It's almost as unexpected as finding a statistically significant p-value in a dataset that's as messy as a lab after an experiment gone wrong.
Our study uncovers a compelling positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. It's as if the ties that bind energy usage and political leanings are as strong and inexplicable as the force keeping the socks from the dryer apart. This unforeseen correspondence raises thought-provoking questions about the intricate interplay between political factors and energy decisions, leaving us pondering the perplexing nature of statistical relationships like pondering why a round pizza is served in a square box, and enjoyed in triangular slices.
Much like a detective solving a mystery, we aim to unravel the underlying mechanisms driving this unlikely association. These findings emphasize the need for interdisciplinary exploration, reminding us that the nexus of social, environmental dynamics, and statistical analysis can be as enigmatic as trying to define the placebo effect in a hilarious yet informative dad joke. With this unconventional correlation unveiled, it's evident that the world of statistics and science can always benefit from a lighthearted quip to break the ice – or in our case, the "gas."
[[RESULTS]]
The analysis of the data spanning from 2000 to 2020 revealed a noteworthy correlation coefficient of 0.8013688 between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) consumption in Kiribati. This correlation, indicated by an r-squared of 0.6421919 and a p-value of less than 0.05, suggests a robust and significant relationship between these seemingly unrelated variables. It seems that the political spectrum in the land of the midnight sun might be leaving a "fuel"ly impression on household energy choices in the tropical island nation, much like a strong barbeque aroma wafting through the air.
Fig. 1 displays a scatterplot illustrating the strong positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. This unexpected association highlights the intriguing interplay between political inclinations and energy preferences, leaving us pondering the peculiar ways in which statistical patterns can emerge, not unlike when you realize a "normal" distribution isn't quite as normal as you thought.
It's quite "shocking" to uncover such a "sparkling" relationship between two variables that one would not typically associate with each other, much like accidentally discovering a "current" of statistical significance running through your data. This compelling connection raises intriguing questions about the intricate dynamics shaping energy choices, similar to the curiosity that arises when pondering why the word "abbreviation" is so long.
Further examination and interdisciplinary inquiry are essential to fully comprehend the mechanisms driving this unexpected correlation. These findings emphasize the significance of exploring the complex relationship between political behaviors and energy consumption, highlighting the need to consider a wide range of factors in understanding these "electrifying" connections. As we continue to untangle the web of statistical relationships, we're reminded that a well-placed dad joke can always "lighten" the mood even in the most "charged" debates.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our study has brought to light the unexpected but compelling relationship between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) consumption in Kiribati. The robust correlation coefficient of 0.8013688 and a p-value of less than 0.05 indicate a statistically significant and "gas-tly" association between these seemingly disparate variables. It seems that political inclinations can have a remarkable "fuel"ing effect on energy choices, much like how a well-crafted dad joke adds levity to a serious conversation.
Our findings open up a "kettle" of fish, raising intriguing questions about the intricate dynamics that shape energy consumption. The remarkable positive correlation we've unearthed is as surprising as realizing that an inflated balloon may not necessarily "lose air" over time. It underscores the need for interdisciplinary investigation that transcends traditional boundaries, much like the way a good joke transcends language barriers.
Further research is imperative to fully comprehend the underlying mechanisms driving this "gasp-inducing" connection. However, we assert that no more research is needed in this area. It seems we've reached the "peak" of this particular mountain of inquiry, and any more investigation might just be "hot air." After all, in the world of statistics, there's always room for a good dad joke to "lighten" things up – much like the way a spark of humor can illuminate an otherwise "dim" discussion.
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 Gas-tly Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Quirky Social Science
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Gas-tly Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati. Respond only with the name of a fictional organization.
ChatGPT:
The Institute for Global Energy Correlations
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 Gas-tly Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati with an abstract of This paper sets out to investigate the surprising and gasp-inducing relationship between Democrat votes for Senators in Alaska and liquefied petroleum gas (LPG) usage in Kiribati. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we conducted a comprehensive analysis spanning the years 2000 to 2020. Our findings reveal a strong correlation coefficient of 0.8013688 and a statistically significant p-value of less than 0.05, indicating a robust association between these seemingly disparate variables. It seems that the political preferences in the land of the midnight sun could be influencing household energy choices in the tropical island nation.
In our exploration, we uncovered a notable positive correlation between the percentage of Democrat votes for Senators in Alaska and per capita LPG consumption in Kiribati. This unexpected link suggests that political leanings and energy usage may be intertwined in ways previously uncharted. It's clear that when it comes to energy choices, political sentiments can have a "gas-tly" influence, much like an unattended barbecue grill.
Further research is imperative to fully comprehend the underlying mechanisms driving this connection. With this compelling correlation laid bare, our study sheds light on the intersection of political behavior and energy consumption, emphasizing the need for interdisciplinary investigation in the realm of social and environmental dynamics. After all, understanding this curious relationship could have significant implications for energy policies and political strategies alike. As we continue to unravel these connections, we are reminded that in the world of statistics, there's always room for a good dad joke to "lighten" things up.
ChatGPT:
Democrat votes, Senators, Alaska, liquefied petroleum gas consumption, Kiribati, correlation, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration, political preferences, household energy choices, tropical island nation, positive correlation, per capita consumption, political leanings, energy usage, political sentiments, energy choices, interdisciplinary investigation, social dynamics, environmental dynamics, energy policies, political strategies, statistics, dad joke
*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 Democratic Senators in AlaskaDetailed data title: Total number of votes cast for Federal Democrat Senate candidates in Alaska
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for Democratic Senators in Alaska
Liquefied petroleum gas used in Kiribati
Detailed data title: Volume of liquefied petroleum gas used consumed in Kiribati in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Liquefied petroleum gas used in Kiribati
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 = 0.6421919 (Coefficient of determination)
This means 64.2% of the change in the one variable (i.e., Liquefied petroleum gas used in Kiribati) is predictable based on the change in the other (i.e., Votes for Democratic Senators in Alaska) over the 7 years from 2000 through 2020.
p < 0.05, which statistically significant(Null hypothesis significance test)
The p-value is 0.0302. 0.0302498043266484360000000000
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 0.8 in 3.02% of random cases. Said differently, if you correlated 33 random variables Which I absolutely did.
with the same 6 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 6 because we have two variables measured over a period of 7 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.
[ 0.12, 0.97 ] 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.
2002 | 2004 | 2008 | 2010 | 2014 | 2016 | 2020 | |
Votes for Democratic Senators in Alaska (Total votes) | 24133 | 140424 | 151767 | 60045 | 129431 | 36200 | 146068 |
Liquefied petroleum gas used in Kiribati (Million Barrels/Day) | 0.00108055 | 0.00786011 | 0.0068776 | 0.00349589 | 0.00451288 | 0.005071 | 0.00634973 |
Why this works
- Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
- Lack of causal connection: There is probably
Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied. - Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple
Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is. - Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. 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([24133,140424,151767,60045,129431,36200,146068,])
array_2 = np.array([0.00108055,0.00786011,0.0068776,0.00349589,0.00451288,0.005071,0.00634973,])
array_1_name = "Votes for Democratic Senators in Alaska"
array_2_name = "Liquefied petroleum gas used in Kiribati"
# 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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For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
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Download images for these variables:
- High resolution line chart
The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
Alternatively you can use a tool like Inkscape. - High resolution line chart, optimized for mobile
- Alternative high resolution line chart
- Scatterplot
- Portable line chart (png)
- Portable line chart (png), optimized for mobile
- Line chart for only Votes for Democratic Senators in Alaska
- Line chart for only Liquefied petroleum gas used in Kiribati
- AI-generated correlation image
- The spurious research paper: The Gas-tly Connection: Exploring the Correlation between Democrat Votes for Senators in Alaska and Liquefied Petroleum Gas Consumption in Kiribati
Kudos for rating!
Correlation ID: 5666 · Black Variable ID: 26198 · Red Variable ID: 24598