Spurious correlation #5,686 · 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 Republican Senators in Texas and the second variable is Hydopower energy generated in Ecuador. The chart goes from 1980 to 2020, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Votes for Republican Senators in Texas and the second variable is Hydopower energy generated in Ecuador. The chart goes from 1980 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The increase in Republican votes for Senators in Texas has led to a surge in cowboy hat production. This has inadvertently created a high demand for felt, prompting Ecuador to cultivate more beavers for their pelts. With an expanding beaver population, Ecuador now has an abundance of dam-building expertise, resulting in a boost in hydropower energy generation. It seems like everything really is bigger in Texas, including the impact on hydroelectric infrastructure thousands of miles away! Yee-haw for renewable energy!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a magical realist landscape where the Texas desert seamlessly blends into an Ecuadorian rainforest. In the foreground, a towering cowboy hat factory stands on one side, while on the other, beaver habitats and dam-building activity are visible. The scene is infused with surreal elements, such as beavers wearing cowboy hats and wielding magical tools to construct mystical energy-generating dams. The overall composition should evoke a sense of wonder and whimsy, emphasizing the fantastical connections between seemingly disparate elements of these regions. 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 Republican Senators in Texas and Hydopower energy generated in Ecuador. 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: An image that looks like it is a scene from a Pixar movie Magic realism Cutsy art illustration Cutsy art illustration Pop art
ChatGPT: Magic realism

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 Republican Senators in Texas and Hydopower energy generated in Ecuador, in the following situation: The increase in Republican votes for Senators in Texas has led to a surge in cowboy hat production. This has inadvertently created a high demand for felt, prompting Ecuador to cultivate more beavers for their pelts. With an expanding beaver population, Ecuador now has an abundance of dam-building expertise, resulting in a boost in hydropower energy generation. It seems like everything really is bigger in Texas, including the impact on hydroelectric infrastructure thousands of miles away! Yee-haw for renewable energy!. Keep the description simple.
ChatGPT: In Texas, more people are voting for Republican senators. This has caused a surge in cowboy hat production, leading to a high demand for felt. Meanwhile, in Ecuador, there's been an increase in beaver cultivation to meet the demand for their pelts. As a result, there's now an abundance of dam-building expertise, resulting in a boost in hydropower energy generation.

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: [ Magic realism ] and depicting this scene: In Texas, more people are voting for Republican senators. This has caused a surge in cowboy hat production, leading to a high demand for felt. Meanwhile, in Ecuador, there's been an increase in beaver cultivation to meet the demand for their pelts. As a result, there's now an abundance of dam-building expertise, resulting in a boost in hydropower energy generation. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a magical realist landscape where the Texas desert seamlessly blends into an Ecuadorian rainforest. In the foreground, a towering cowboy hat factory stands on one side, while on the other, beaver habitats and dam-building activity are visible. The scene is infused with surreal elements, such as beavers wearing cowboy hats and wielding magical tools to construct mystical energy-generating dams. The overall composition should evoke a sense of wonder and whimsy, emphasizing the fantastical connections between seemingly disparate elements of these regions.

*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.
^{Show prompt for explanation} 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 Republican votes for Senators in Texas caused Hydopower energy generated in Ecuador to increase.

AI academic paper

(Because p < 0.01)

Hydropower Votes: A Current of Correlation between Republican Votes for Texas Senators and Hydropower Energy Generated in Ecuador

Journal of Ecological Politics and Renewable Energy

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} 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 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 Republican votes for Senators in Texas and Hydopower energy generated in Ecuador. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Hydropower Votes: A Current of Correlation between Republican Votes for Texas Senators and Hydropower Energy Generated in Ecuador"

[[ABSTRACT]]
The relationship between political voting patterns and energy generation has been a subject of ongoing scholarly inquiry. In this study, we investigate the curious coupling of Republican votes for Senators in the state of Texas with the hydroelectric output of Ecuador. By utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team endeavors to shed light on this unorthodox connection. Employing rigorous statistical analysis, we identified a correlation coefficient of 0.8516004 and p < 0.01 for the period spanning from 1980 to 2020, indicating a strong association between these seemingly disparate variables. This correlation, while unexpected, presents a lively current of association that warrants further investigation and consideration. Through our research, we unveil a hydro-powered link between political preferences in Texas and the energy landscape of Ecuador, delving into the waters of interdisciplinary connection with a mix of intellectual curiosity and wit.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intertwining of the political and environmental realms has long intrigued scholars seeking to unravel the currents of influence shaping our world. In this paper, we embark on a peculiar journey to explore the correlation between Republican votes for Senators in Texas and the hydroelectric energy generated in Ecuador. While this connection may seem as unlikely as a paddlewheel on a desert dune, our investigation delves into the depths of data to navigate this uncharted terrain.
The confluence of conservative votes in the Lone Star State with the hydro-powered output of Ecuador is an enigmatic whirlpool in the sea of political and energy dynamics. With skepticism, curiosity, and a pinch of humor, we set out to navigate this river of statistical analysis, aiming to illuminate the surprising link that has emerged from the depths of our data.
As we wade into this unorthodox endeavor, we find ourselves meandering through a landscape rich with data sources, methodological considerations, and relentless puns about "power." Our study surges forth with a current of academic rigor while remaining buoyant with the humor and levity essential for traversing these uncharted waters of interdisciplinary research.
Through this endeavor, we hope not only to outline the statistical relationship between these seemingly disparate variables but also to stimulate a wave of curiosity and contemplation about the interconnectedness of political preferences and global energy dynamics. As we embark on this intellectual adventure, we invite readers to don their scholarly life vests and join us in navigating the whitewater rapids of this unexpected linkage.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The intersection of politics and energy generation has been the subject of numerous scholarly investigations, with researchers attempting to untangle the web of connections between seemingly unrelated variables. In "Smith et al.," the authors delve into the complexities of political voting patterns and environmental impact, laying the groundwork for our own exploration of the curious correlation between Republican votes for Texas Senators and hydropower energy generated in Ecuador.

As we peer into the swirling eddies of academic literature, we encounter "Doe's Study," revealing the intricate dance between political ideologies and global energy landscapes. Meanwhile, "Jones et al." offer a comprehensive analysis of hydroelectric power production dynamics in South America, providing a context for our focus on Ecuador's hydropower output.

Expanding our scope, we pivot to non-fiction works such as "The Big Thirst" by Charles Fishman, which, while not directly related to our specific research topic, metaphorically quenches our thirst for understanding the broader implications of water and energy dynamics on a global scale. Similarly, "The Shock Doctrine" by Naomi Klein, though centered on economic theories, presents an electrifying examination of power dynamics and their impact on political decision-making.

In the realm of fiction, we navigate the turbulent waters of literary works such as "The Hydrogen Sonata" by Iain M. Banks, seamlessly blending science fiction with themes of power generation and political maneuvering. Alongside this, "Solar" by Ian McEwan provides a wryly humorous exploration of solar energy and ethical dilemmas, sparking a glimmer of playful insight into the serious undercurrents of our research.

As our academic raft approaches the bend in the river, we reach unconventional sources of insight, drawing inspiration from unexpected quarters. In a lighthearted deviation from traditional scholarly avenues, we humorously note that the backs of shampoo bottles and cereal boxes, though not cited in academic research, still yield valuable perspectives on the persuasive power of marketing and the dynamics of consumer decision-making. While their relevance may float at the periphery of scholarly discourse, their presence illustrates the versatility of sources that can inform and amuse in equal measure.

With the current of literature guiding our intellectual voyage, we navigate the hybrid currents of serious scholarship and whimsical inquiry, buoyed by the waves of knowledge and the occasional hidden pun. As we continue our journey, we invite readers to set sail with us, embracing the ebbs and flows of interdisciplinary exploration with a spirit of curiosity and a touch of irreverence.

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 Republican votes for Senators in Texas and Hydopower energy generated in Ecuador. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration . You used data from 1980 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]]
"Hydropower Votes: A Current of Correlation between Republican Votes for Texas Senators and Hydropower Energy Generated in Ecuador"

[[ABSTRACT]]
The relationship between political voting patterns and energy generation has been a subject of ongoing scholarly inquiry. In this study, we investigate the curious coupling of Republican votes for Senators in the state of Texas with the hydroelectric output of Ecuador. By utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team endeavors to shed light on this unorthodox connection. Employing rigorous statistical analysis, we identified a correlation coefficient of 0.8516004 and p < 0.01 for the period spanning from 1980 to 2020, indicating a strong association between these seemingly disparate variables. This correlation, while unexpected, presents a lively current of association that warrants further investigation and consideration. Through our research, we unveil a hydro-powered link between political preferences in Texas and the energy landscape of Ecuador, delving into the waters of interdisciplinary connection with a mix of intellectual curiosity and wit.

[[INTRODUCTION]]
The intertwining of the political and environmental realms has long intrigued scholars seeking to unravel the currents of influence shaping our world. In this paper, we embark on a peculiar journey to explore the correlation between Republican votes for Senators in Texas and the hydroelectric energy generated in Ecuador. While this connection may seem as unlikely as a paddlewheel on a desert dune, our investigation delves into the depths of data to navigate this uncharted terrain.
The confluence of conservative votes in the Lone Star State with the hydro-powered output of Ecuador is an enigmatic whirlpool in the sea of political and energy dynamics. With skepticism, curiosity, and a pinch of humor, we set out to navigate this river of statistical analysis, aiming to illuminate the surprising link that has emerged from the depths of our data.
As we wade into this unorthodox endeavor, we find ourselves meandering through a landscape rich with data sources, methodological considerations, and relentless puns about "power." Our study surges forth with a current of academic rigor while remaining buoyant with the humor and levity essential for traversing these uncharted waters of interdisciplinary research.
Through this endeavor, we hope not only to outline the statistical relationship between these seemingly disparate variables but also to stimulate a wave of curiosity and contemplation about the interconnectedness of political preferences and global energy dynamics. As we embark on this intellectual adventure, we invite readers to don their scholarly life vests and join us in navigating the whitewater rapids of this unexpected linkage.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

In order to dive into the depths of the murky waters of statistical analysis and unravel the mystery behind the connection between Republican votes for Senators in Texas and the hydroelectric energy generated in Ecuador, our research team embarked on a methodological voyage that blended meticulous data collection with a dash of whimsy and a sprinkle of caffeine-fueled late-night brainstorming sessions.

Data Collection:
Our team scoured the vast expanse of the internet, traversing the digital landscapes like swashbuckling data pirates, in search of the elusive treasure troves of information. We plundered the MIT Election Data and Science Lab and raided the Harvard Dataverse, extracting electoral data with the precision of political archaeologists unearthing ancient relics. Meanwhile, we delved into the labyrinthine archives of the Energy Information Administration, emerging with the hydroelectric output data of Ecuador clutched in our hands like intrepid explorers brandishing precious artifacts.

Statistical Analysis:
Armed with our plundered data, we invoked the arcane powers of statistical analysis, summoning correlations, p-values, and scatter plots from the depths of our software incantations. Like sorcerers of significance, we scrutinized the data for patterns and relationships, casting aside irrelevant variables like Merlin parting the Red Sea.

Correlation Calculation:
With bated breath, we unleashed the mystical forces of correlation coefficient computation upon our data. Through esoteric rites of mathematical manipulation, we unveiled a correlation coefficient of 0.8516004, signaling a strong association between Republican votes for Texas Senators and the hydroelectric energy generated in Ecuador.

Validity Checks:
To ensure the credibility of our findings, we conducted a series of validity checks, scrutinizing the robustness of the correlation in the face of potential confounding variables. Like scholarly sleuths, we interrogated our data, subjecting it to a battery of tests to discern any fleeting trickery or statistical sleight of hand.

Time Span:
Our data spanned the temporal tapestry from 1980 to 2020, capturing the undulating ebb and flow of political tides and hydroelectric currents over the decades. This expansive timeline allowed us to chart the course of the correlation through the annals of time, akin to cryptohydrologists unraveling the age-old mysteries of hydro-political dynamics.

Ethical Considerations:
In our pursuit of knowledge, we navigated the ethical currents with the diligence of scholarly mariners, ensuring that our research adhered to the highest standards of integrity and respect for the data sources. Ethical clearance was obtained from the Institutional Review Board of [Insert Imaginary University Name] to sail these uncharted waters of interdisciplinary inquiry.

In summary, our research methodology fused rigorous data collection, statistical sorcery, and the spirit of scholarly exploration, buoyed by the waves of intellectual curiosity and propelled by the wind of whimsy. As we hoist our methodological sails and navigate the unknown waters of academic inquiry, we invite readers to join us on this expedition, equipped with a healthy dose of skepticism and a pair of dashing academic galoshes.

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 Republican votes for Senators in Texas and Hydopower energy generated in Ecuador. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Hydropower Votes: A Current of Correlation between Republican Votes for Texas Senators and Hydropower Energy Generated in Ecuador"

[[ABSTRACT]]
The relationship between political voting patterns and energy generation has been a subject of ongoing scholarly inquiry. In this study, we investigate the curious coupling of Republican votes for Senators in the state of Texas with the hydroelectric output of Ecuador. By utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team endeavors to shed light on this unorthodox connection. Employing rigorous statistical analysis, we identified a correlation coefficient of 0.8516004 and p < 0.01 for the period spanning from 1980 to 2020, indicating a strong association between these seemingly disparate variables. This correlation, while unexpected, presents a lively current of association that warrants further investigation and consideration. Through our research, we unveil a hydro-powered link between political preferences in Texas and the energy landscape of Ecuador, delving into the waters of interdisciplinary connection with a mix of intellectual curiosity and wit.

[[LITERATURE REVIEW]]
The intersection of politics and energy generation has been the subject of numerous scholarly investigations, with researchers attempting to untangle the web of connections between seemingly unrelated variables. In "Smith et al.," the authors delve into the complexities of political voting patterns and environmental impact, laying the groundwork for our own exploration of the curious correlation between Republican votes for Texas Senators and hydropower energy generated in Ecuador.
As we peer into the swirling eddies of academic literature, we encounter "Doe's Study," revealing the intricate dance between political ideologies and global energy landscapes. Meanwhile, "Jones et al." offer a comprehensive analysis of hydroelectric power production dynamics in South America, providing a context for our focus on Ecuador's hydropower output.
Expanding our scope, we pivot to non-fiction works such as "The Big Thirst" by Charles Fishman, which, while not directly related to our specific research topic, metaphorically quenches our thirst for understanding the broader implications of water and energy dynamics on a global scale. Similarly, "The Shock Doctrine" by Naomi Klein, though centered on economic theories, presents an electrifying examination of power dynamics and their impact on political decision-making.
In the realm of fiction, we navigate the turbulent waters of literary works such as "The Hydrogen Sonata" by Iain M. Banks, seamlessly blending science fiction with themes of power generation and political maneuvering. Alongside this, "Solar" by Ian McEwan provides a wryly humorous exploration of solar energy and ethical dilemmas, sparking a glimmer of playful insight into the serious undercurrents of our research.
As our academic raft approaches the bend in the river, we reach unconventional sources of insight, drawing inspiration from unexpected quarters. In a lighthearted deviation from traditional scholarly avenues, we humorously note that the backs of shampoo bottles and cereal boxes, though not cited in academic research, still yield valuable perspectives on the persuasive power of marketing and the dynamics of consumer decision-making. While their relevance may float at the periphery of scholarly discourse, their presence illustrates the versatility of sources that can inform and amuse in equal measure.
With the current of literature guiding our intellectual voyage, we navigate the hybrid currents of serious scholarship and whimsical inquiry, buoyed by the waves of knowledge and the occasional hidden pun. As we continue our journey, we invite readers to set sail with us, embracing the ebbs and flows of interdisciplinary exploration with a spirit of curiosity and a touch of irreverence.

[[RESULTS]]
The analysis of the data collected from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration revealed a correlation coefficient of 0.8516004 between Republican votes for Senators in Texas and the hydroelectric energy generated in Ecuador over the time period of 1980 to 2020. The r-squared value of 0.7252232 further confirmed the strength of this relationship, and with a p-value less than 0.01, we can be confident that this connection is not just a fluke, but a current of significance.
Figure 1 presents a scatterplot illustrating the buoyant association between the two variables. The graph resembles a pair of swimming trunks floating serenely on the surface of statistical significance, underscoring the robustness of the correlation. The plot showcases the captivating ebb and flow of Republican votes in Texas vis-à-vis the hydro-powered highs and lows of Ecuadorian energy generation, painting a vibrant picture of the unanticipated link between political preferences and international energy dynamics.
The implications of these findings ripple through the realms of political science and environmental studies, inviting an interdisciplinary dialogue that navigates the uncharted waters of correlation between seemingly disconnected domains. This unexpected connection not only highlights the fluidity of influence across borders but also serves as a reminder that in the complex tapestry of global dynamics, even the most unlikely pairings can surge forth with a current of significance.
The statistical evidence presented here underscores the need for further exploration of the hydro-powered nexus between political preferences in Texas and the energy landscape of Ecuador. This research surges forth like a mighty river, sparking intellectual curiosity and irrigating the landscape of interdisciplinary inquiry with its unexpected findings.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The currents of correlation illuminated by our research findings offer a fascinating confluence of political and environmental phenomena. Our study upholds and extends prior research, acknowledging the insightful works of "Smith et al." and "Doe's Study" that set the stage for our exploration. It's worth noting that the metaphorical currents described by Jones et al. in their analysis of hydroelectric power production dynamics in South America seem to have found a tangible manifestation in our own investigation. Additionally, the whimsically buoyant insights drawn from literature and unconventional sources serve as a delightful undercurrent suffusing our discussion with a touch of irreverence.

Our results not only validate the robustness of the correlation between Republican votes for Senators in Texas and the hydropower energy generated in Ecuador but also amplify the significance of this hitherto uncharted connection. The buoyant association, analogous to a pair of swimming trunks adrift on statistical waters, underscores the unexpected yet substantial interplay between political preferences and energy dynamics. The unmistakable ebb and flow depicted in the scatterplot mirror the flux of influence spanning continents, akin to a playful dance across the watery canvas of interdisciplinary inquiry.

The current of significance flowing from our findings prompts a call for further investigation into the hydro-powered nexus between political preferences in Texas and the energy landscape of Ecuador. This unexpected linkage not only highlights the fluidity of influence across borders but also serves as a reminder that even the most improbable pairings can surge forth with a current of significance.

In sum, our research navigates uncharted waters, ushering in a flood of interdisciplinary dialogue and underscoring the intrinsic fluidity of connections in the global tapestry of political and environmental dynamics. As we delve deeper into this hydro-powered realm of scholarly inquiry, we invite fellow explorers to embrace the surging currents of intellectual curiosity and irreverence, set adrift on the playful waves of unconventional insight.

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 Republican votes for Senators in Texas and Hydopower energy generated in Ecuador. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Hydropower Votes: A Current of Correlation between Republican Votes for Texas Senators and Hydropower Energy Generated in Ecuador"

[[ABSTRACT]]
The relationship between political voting patterns and energy generation has been a subject of ongoing scholarly inquiry. In this study, we investigate the curious coupling of Republican votes for Senators in the state of Texas with the hydroelectric output of Ecuador. By utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team endeavors to shed light on this unorthodox connection. Employing rigorous statistical analysis, we identified a correlation coefficient of 0.8516004 and p < 0.01 for the period spanning from 1980 to 2020, indicating a strong association between these seemingly disparate variables. This correlation, while unexpected, presents a lively current of association that warrants further investigation and consideration. Through our research, we unveil a hydro-powered link between political preferences in Texas and the energy landscape of Ecuador, delving into the waters of interdisciplinary connection with a mix of intellectual curiosity and wit.

[[INTRDUCTION]]
The intertwining of the political and environmental realms has long intrigued scholars seeking to unravel the currents of influence shaping our world. In this paper, we embark on a peculiar journey to explore the correlation between Republican votes for Senators in Texas and the hydroelectric energy generated in Ecuador. While this connection may seem as unlikely as a paddlewheel on a desert dune, our investigation delves into the depths of data to navigate this uncharted terrain.
The confluence of conservative votes in the Lone Star State with the hydro-powered output of Ecuador is an enigmatic whirlpool in the sea of political and energy dynamics. With skepticism, curiosity, and a pinch of humor, we set out to navigate this river of statistical analysis, aiming to illuminate the surprising link that has emerged from the depths of our data.
As we wade into this unorthodox endeavor, we find ourselves meandering through a landscape rich with data sources, methodological considerations, and relentless puns about "power." Our study surges forth with a current of academic rigor while remaining buoyant with the humor and levity essential for traversing these uncharted waters of interdisciplinary research.
Through this endeavor, we hope not only to outline the statistical relationship between these seemingly disparate variables but also to stimulate a wave of curiosity and contemplation about the interconnectedness of political preferences and global energy dynamics. As we embark on this intellectual adventure, we invite readers to don their scholarly life vests and join us in navigating the whitewater rapids of this unexpected linkage.

[[RESULTS]]
The analysis of the data collected from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration revealed a correlation coefficient of 0.8516004 between Republican votes for Senators in Texas and the hydroelectric energy generated in Ecuador over the time period of 1980 to 2020. The r-squared value of 0.7252232 further confirmed the strength of this relationship, and with a p-value less than 0.01, we can be confident that this connection is not just a fluke, but a current of significance.
Figure 1 presents a scatterplot illustrating the buoyant association between the two variables. The graph resembles a pair of swimming trunks floating serenely on the surface of statistical significance, underscoring the robustness of the correlation. The plot showcases the captivating ebb and flow of Republican votes in Texas vis-à-vis the hydro-powered highs and lows of Ecuadorian energy generation, painting a vibrant picture of the unanticipated link between political preferences and international energy dynamics.
The implications of these findings ripple through the realms of political science and environmental studies, inviting an interdisciplinary dialogue that navigates the uncharted waters of correlation between seemingly disconnected domains. This unexpected connection not only highlights the fluidity of influence across borders but also serves as a reminder that in the complex tapestry of global dynamics, even the most unlikely pairings can surge forth with a current of significance.
The statistical evidence presented here underscores the need for further exploration of the hydro-powered nexus between political preferences in Texas and the energy landscape of Ecuador. This research surges forth like a mighty river, sparking intellectual curiosity and irrigating the landscape of interdisciplinary inquiry with its unexpected findings.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has navigated the tumultuous waters of statistical analysis to reveal a remarkable correlation between Republican votes for Senators in Texas and the hydropower energy generated in Ecuador. The robustness of this connection, akin to an electric current running through the political and environmental domains, emphasizes the multifaceted interplay of seemingly unrelated variables. Like a surfer catching a wave of insight, we have ridden this unexpected linkage to unveil a confluence of influence that resonates across borders and disciplines.

As we reflect on these findings, it becomes evident that even the most unconventional associations can surge forth with a current of significance. The buoyant correlation coefficient, akin to a rubber duck bobbing in the waves of data, underscores the veracity of this unorthodox connection. Our results not only illuminate the surprising link between political preferences in Texas and the energy landscape of Ecuador but also serve as a reminder that scholarly inquiry should always be a buoyant voyage, filled with intellectual curiosity and perhaps the occasional pun about "power."

In navigating this uncharted terrain, our study has undoubtedly stirred waves of introspection and contemplation, inviting scholars from diverse fields to plunge into the depths of this unexpected linkage. The implications of our research ripple through the currents of academic discourse, urging further exploration and analysis to unravel the intricacies of this hydro-powered nexus. However, with the wit and insight of our findings, it is clear that no further research is needed in this area. We have successfully unearthed the surging current of correlation between these seemingly divergent domains, leaving no stone unturned and no wave unchallenged in our quest for enlightening research.

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 Hydropower Votes: A Current of Correlation between Republican Votes for Texas Senators and Hydropower Energy Generated in Ecuador. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Ecological Politics and Renewable Energy

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 Hydropower Votes: A Current of Correlation between Republican Votes for Texas Senators and Hydropower Energy Generated in Ecuador. Respond only with the name of a fictional organization.

ChatGPT:

Society for International Renewable Energy Integration and Political Dynamics (SIREIPD)

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 Hydropower Votes: A Current of Correlation between Republican Votes for Texas Senators and Hydropower Energy Generated in Ecuador with an abstract of The relationship between political voting patterns and energy generation has been a subject of ongoing scholarly inquiry. In this study, we investigate the curious coupling of Republican votes for Senators in the state of Texas with the hydroelectric output of Ecuador. By utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team endeavors to shed light on this unorthodox connection. Employing rigorous statistical analysis, we identified a correlation coefficient of 0.8516004 and p < 0.01 for the period spanning from 1980 to 2020, indicating a strong association between these seemingly disparate variables. This correlation, while unexpected, presents a lively current of association that warrants further investigation and consideration. Through our research, we unveil a hydro-powered link between political preferences in Texas and the energy landscape of Ecuador, delving into the waters of interdisciplinary connection with a mix of intellectual curiosity and wit.

ChatGPT:

Republican votes, Texas Senators, hydropower energy, Ecuador, correlation, political voting patterns, energy generation, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration, statistical analysis, correlation coefficient

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

Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error

Data details

Votes for Republican Senators in Texas
Detailed data title: Total number of votes cast for Federal Republican Senate candidates in Texas
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for Republican Senators in Texas

Hydopower energy generated in Ecuador
Detailed data title: Total hydopower energy generated in Ecuador in billion kWh
Source: Energy Information Administration
See what else correlates with Hydopower energy generated in Ecuador

Correlation r = 0.8516004 (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 = 0.7252232 (Coefficient of determination)
This means 72.5% of the change in the one variable (i.e., Hydopower energy generated in Ecuador) is predictable based on the change in the other (i.e., Votes for Republican Senators in Texas) over the 14 years from 1980 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00011.^Show 0.0001111267535624803300000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note 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 0.85 in 0.011% of random cases. Said differently, if you correlated 8,999 random variables^Note Which I absolutely did.
with the same 13 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 13 because we have two variables measured over a period of 14 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.

[ 0.59, 0.95 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} 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: ^Note 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.

	1982	1984	1988	1990	1994	1996	2000	2002	2006	2008	2012	2014	2018	2020
Votes for Republican Senators in Texas (Total votes)	1256760	3111350	2129230	2302360	2604220	3027680	4078950	2496240	2661790	4337470	4440140	2861530	4260550	5962980
Hydopower energy generated in Ecuador (Billion kWh)	0.89	3.163	4.741	4.937	6.499	6.281	7.533	7.45	7.059	11.181	12.116	11.343	20.4712	24.3333

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^Note 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^Note 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.
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.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} 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([1256760,3111350,2129230,2302360,2604220,3027680,4078950,2496240,2661790,4337470,4440140,2861530,4260550,5962980,])
array_2 = np.array([0.89,3.163,4.741,4.937,6.499,6.281,7.533,7.45,7.059,11.181,12.116,11.343,20.4712,24.3333,])
array_1_name = "Votes for Republican Senators in Texas"
array_2_name = "Hydopower energy generated in Ecuador"

# 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)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note 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 Republican Senators in Texas
Line chart for only Hydopower energy generated in Ecuador
AI-generated correlation image
The spurious research paper: Hydropower Votes: A Current of Correlation between Republican Votes for Texas Senators and Hydropower Energy Generated in Ecuador

View another random correlation

How fun was this correlation?

Bravo! Your evaluation rocks!

Correlation ID: 5686 · Black Variable ID: 26320 · Red Variable ID: 23640


Problem variable:
Issue:
Additional details: Optional
Confirm you are a human: