Spurious correlation #5,302 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Votes for the Democratic Presidential candidate in Texas and the second variable is Hydopower energy generated in Nicaragua. 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 the Democratic Presidential candidate in Texas and the second variable is Hydopower energy generated in Nicaragua. The chart goes from 1980 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

When Democrats gain popularity in Texas, the collective excitement generates a surge in positive ions. These positive ions somehow make their way to Nicaragua, where they boost the water's innate energy, leading to an increase in hydropower production. It's shocking how electoral currents in one area can rev up the hydropower capabilities in another, but it seems like politics truly has the power to make waves, even across borders!

^{Show image generation prompt} Model: dalle-3
Prompt: [ Concept art ] A vibrant Texas city street scene fills the frame, bustling with people gathering to cast their votes for the Democratic Presidential candidate. The busy cityscape is decorated with American flags and campaign posters, and the excitement in the air is palpable. Energy begins to surge through the scene as invisible positive ions are represented by glowing, swirling patterns, creating a dynamic visual effect that highlights the charged atmosphere. In the background, a surreal representation of the ions travels overseas to Nicaragua, where the rushing waters of a majestic waterfall are depicted. The water seems to be infused with the energy of the ions, swirling and pulsating with newfound power. Symbolic representation of the hydropower plant shows energy being generated from the swirling waters, emphasizing the impactful connection between political fervor and environmental energy. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Votes for the Democratic Presidential candidate in Texas and Hydopower energy generated in Nicaragua. 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: Parallax art Cute 2D animation Concept art Surrealism Concept art
ChatGPT: Concept art

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Votes for the Democratic Presidential candidate in Texas and Hydopower energy generated in Nicaragua, in the following situation: When Democrats gain popularity in Texas, the collective excitement generates a surge in positive ions. These positive ions somehow make their way to Nicaragua, where they boost the water's innate energy, leading to an increase in hydropower production. It's shocking how electoral currents in one area can rev up the hydropower capabilities in another, but it seems like politics truly has the power to make waves, even across borders!. Keep the description simple.
ChatGPT: In a bustling Texas city, a group of people gather to cast their votes for the Democratic Presidential candidate. As the excitement builds, invisible positive ions begin to surge through the air. These ions travel across the ocean to Nicaragua, where they mingle with the rushing waters of a powerful waterfall. The water seems to gain a newfound energy, spinning the turbines of a hydropower plant, generating an increase in clean, renewable energy. It's a remarkable display of the interconnectedness of political fervor and environmental impact.

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: [ Concept art ] and depicting this scene: In a bustling Texas city, a group of people gather to cast their votes for the Democratic Presidential candidate. As the excitement builds, invisible positive ions begin to surge through the air. These ions travel across the ocean to Nicaragua, where they mingle with the rushing waters of a powerful waterfall. The water seems to gain a newfound energy, spinning the turbines of a hydropower plant, generating an increase in clean, renewable energy. It's a remarkable display of the interconnectedness of political fervor and environmental impact. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Concept art ] A vibrant Texas city street scene fills the frame, bustling with people gathering to cast their votes for the Democratic Presidential candidate. The busy cityscape is decorated with American flags and campaign posters, and the excitement in the air is palpable. Energy begins to surge through the scene as invisible positive ions are represented by glowing, swirling patterns, creating a dynamic visual effect that highlights the charged atmosphere. In the background, a surreal representation of the ions travels overseas to Nicaragua, where the rushing waters of a majestic waterfall are depicted. The water seems to be infused with the energy of the ions, swirling and pulsating with newfound power. Symbolic representation of the hydropower plant shows energy being generated from the swirling waters, emphasizing the impactful connection between political fervor and environmental energy.

*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 Votes for the Democrat Presidential candidate in Texas caused Hydopower energy generated in Nicaragua to increase.

AI academic paper

(Because p < 0.01)

The Texas-Democrat Vote Tally and Nicaraguan Hydropower: A Tenuous Tandem

The Journal of Political Energy Dynamics

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 dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Votes for the Democrat Presidential candidate in Texas and Hydopower energy generated in Nicaragua. 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
The Texas-Democrat Vote Tally and Nicaraguan Hydropower: A Tenuous Tandem

[[ABSTRACT]]
This study scrutinizes the intriguing link between the votes garnered by the Democrat Presidential candidate in the state of Texas and the hydroelectric power generated in Nicaragua from 1980 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we uncovered a correlation coefficient of 0.8926604 and p < 0.01, indicating a statistically significant relationship between these seemingly unrelated variables. While the association would seemingly be bewildering, as political preferences in Texas are not known to directly influence energy output in Nicaragua, the findings stir the imagination and lead to probing questions about potential underlying factors. The results may elicit a wry smile, but the implications for future research and policy considerations are nothing to scoff at.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The juxtaposition of politics and energy production is an unusual terrain for analysis, yet this study delves into the curious association between the votes accruing to the Democrat Presidential candidate in the state of Texas and the output of hydroelectric power in Nicaragua. One might be forgiven for raising an eyebrow at the mere mention of such a correlation, for the interconnectedness of these seemingly disparate phenomena is not readily apparent. However, as the saying goes, "The proof is in the pudding," and statistical analysis reveals an unexpected relationship worthy of investigation.
In the annals of quantitative research, rare is the occasion when political trends in the Lone Star State intersect with the generation of hydroelectric power in a distant Central American nation. Nevertheless, like an enigmatic puzzle waiting to be solved, this linkage beckons us to scrutinize the underlying mechanisms at play. While the notion that Texan voting proclivities could exert an influence on the hydroelectric landscape of Nicaragua may initially raise an arch of skepticism, the data tell a tale that demands attention. The power of statistical analysis, much like the force of a rushing river, compels us to take note of the confluence of these two disparate domains.
The unexpected nature of this association may indeed prompt a quizzical grin, but it also serves as a reminder of the multifaceted interplay of global socio-political and environmental dynamics. Though this discovery may seem like the punchline to a particularly perplexing joke, the implications extend beyond mere amusement. This inquiry opens the door to a deeper understanding of the complex interrelationships that color our world, and invites further investigation into the manifold forces shaping our collective destinies.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Prior to delving into the peculiar relationship between the Democratic vote tally in Texas and the hydroelectric power output in Nicaragua, it is prudent to survey existing literature that may shed light on seemingly unconnected phenomena intertwining in unexpected ways. Smith et al. (2015) examined political voting patterns in U.S. states and their potential impact on international energy dynamics. They found a modest correlation between political affiliations and energy production in neighboring countries. Doe and Jones (2018) investigated the role of transnational political events on global energy markets, but did not specifically explore the influence of state-level elections on energy generation in distant regions.

Turning to more general works with potential bearing on this juxtaposition, "The Energy Landscape: A Sociology of Energy Consumption" by John Q. Public and "Political Pendulums: An Analysis of Electoral Swings" by Joan Smith present insights that may indirectly inform our understanding of the unexpected linkages observed in the present study.

Taking a more imaginative leap, the fictional works "Power Struggles: a Novel of Political Intrigue" by A.C. Politician and "Rivers of Destiny: A Hydro-Energy Thriller" by H. Watts offer creative interpretations of the potential interplay between political machinations and energy production.Moreover, board games such as "Power Grid" and "Electioneering: Energy Edition" may provide metaphorical parallels to the entwined themes under consideration.

As we venture further into this exploration, the seemingly tangential connections between Texas voting behaviors and Nicaraguan hydropower are akin to stumbling upon a hidden treasure map in the unlikeliest of locations—a discovery both confounding and exhilarating.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Votes for the Democrat Presidential candidate in Texas and Hydopower energy generated in Nicaragua. 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]]
The Texas-Democrat Vote Tally and Nicaraguan Hydropower: A Tenuous Tandem

[[ABSTRACT]]
This study scrutinizes the intriguing link between the votes garnered by the Democrat Presidential candidate in the state of Texas and the hydroelectric power generated in Nicaragua from 1980 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we uncovered a correlation coefficient of 0.8926604 and p < 0.01, indicating a statistically significant relationship between these seemingly unrelated variables. While the association would seemingly be bewildering, as political preferences in Texas are not known to directly influence energy output in Nicaragua, the findings stir the imagination and lead to probing questions about potential underlying factors. The results may elicit a wry smile, but the implications for future research and policy considerations are nothing to scoff at.

[[INTRODUCTION]]
The juxtaposition of politics and energy production is an unusual terrain for analysis, yet this study delves into the curious association between the votes accruing to the Democrat Presidential candidate in the state of Texas and the output of hydroelectric power in Nicaragua. One might be forgiven for raising an eyebrow at the mere mention of such a correlation, for the interconnectedness of these seemingly disparate phenomena is not readily apparent. However, as the saying goes, "The proof is in the pudding," and statistical analysis reveals an unexpected relationship worthy of investigation.
In the annals of quantitative research, rare is the occasion when political trends in the Lone Star State intersect with the generation of hydroelectric power in a distant Central American nation. Nevertheless, like an enigmatic puzzle waiting to be solved, this linkage beckons us to scrutinize the underlying mechanisms at play. While the notion that Texan voting proclivities could exert an influence on the hydroelectric landscape of Nicaragua may initially raise an arch of skepticism, the data tell a tale that demands attention. The power of statistical analysis, much like the force of a rushing river, compels us to take note of the confluence of these two disparate domains.
The unexpected nature of this association may indeed prompt a quizzical grin, but it also serves as a reminder of the multifaceted interplay of global socio-political and environmental dynamics. Though this discovery may seem like the punchline to a particularly perplexing joke, the implications extend beyond mere amusement. This inquiry opens the door to a deeper understanding of the complex interrelationships that color our world, and invites further investigation into the manifold forces shaping our collective destinies.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The methodology employed in this study entailed the meticulous collection and analysis of data pertaining to the respective variables of interest. The investigation began with the procurement of historical voting data for the Democrat Presidential candidate in the state of Texas from the MIT Election Data and Science Lab. Data for hydroelectric power generation in Nicaragua was obtained from the Energy Information Administration, capturing the years from 1980 to 2020. The selection of these sources was primarily due to their comprehensive coverage and accessibility, in addition to our research team’s passionate belief in the adage "MIT and Harvard – where all the cool data hangs out."

The acquired data underwent rigorous cleansing and validation procedures to ensure accuracy and integrity. This involved identifying and addressing any anomalies, inconsistencies, or downright suspicious entries, akin to separating the wheat from the chaff, or the genuine hydro from the electric.

Statistical analyses were then performed to examine the potential relationship between the two variables of interest. Correlation coefficients were computed to quantify the strength and direction of the association, while significance testing was conducted to evaluate the presence of any meaningful relationships. The use of a statistical software package allowed for the execution of these analyses with finesse, though at times it felt more like herding cats – a striking parallel to the endeavor of quantifying the dynamics between Texan political preferences and Nicaraguan hydropower.

In order to account for potential confounding variables or external influences, sensitivity analyses were undertaken to test the robustness of the observed relationships. This process involved introducing various control variables into the analytical models, much like adding seasoning to a dish to enhance its flavor, but in this case, the seasoning included factors such as global economic conditions and regional climatic patterns rather than salt and pepper.

Additionally, time series analysis was conducted to assess the temporal patterns and dynamics of the relationship between the variables over the study period. This allowed for a deeper understanding of how changes in the Texan political landscape may have reverberated through time to impact the hydroelectric output in Nicaragua, in a manner akin to the ripples of a stone cast into a tranquil pond – or, in this case, an electoral ballot cast in the Lone Star State.

Lastly, the findings were subjected to peer review and validation by external experts in the fields of political science and energy economics. Their input and feedback served as a checks-and-balances mechanism, akin to the role of referees in a basketball game, ensuring that the conclusions drawn were anchored in scholarly rigor and not mere flights of fancy.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Votes for the Democrat Presidential candidate in Texas and Hydopower energy generated in Nicaragua. 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 .

For the time period 1980 to 2020, you found a correlation 0.8926604, r-squared of 0.7968425, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
The Texas-Democrat Vote Tally and Nicaraguan Hydropower: A Tenuous Tandem

[[ABSTRACT]]
This study scrutinizes the intriguing link between the votes garnered by the Democrat Presidential candidate in the state of Texas and the hydroelectric power generated in Nicaragua from 1980 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we uncovered a correlation coefficient of 0.8926604 and p < 0.01, indicating a statistically significant relationship between these seemingly unrelated variables. While the association would seemingly be bewildering, as political preferences in Texas are not known to directly influence energy output in Nicaragua, the findings stir the imagination and lead to probing questions about potential underlying factors. The results may elicit a wry smile, but the implications for future research and policy considerations are nothing to scoff at.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The juxtaposition of politics and energy production is an unusual terrain for analysis, yet this study delves into the curious association between the votes accruing to the Democrat Presidential candidate in the state of Texas and the output of hydroelectric power in Nicaragua. One might be forgiven for raising an eyebrow at the mere mention of such a correlation, for the interconnectedness of these seemingly disparate phenomena is not readily apparent. However, as the saying goes, "The proof is in the pudding," and statistical analysis reveals an unexpected relationship worthy of investigation.
In the annals of quantitative research, rare is the occasion when political trends in the Lone Star State intersect with the generation of hydroelectric power in a distant Central American nation. Nevertheless, like an enigmatic puzzle waiting to be solved, this linkage beckons us to scrutinize the underlying mechanisms at play. While the notion that Texan voting proclivities could exert an influence on the hydroelectric landscape of Nicaragua may initially raise an arch of skepticism, the data tell a tale that demands attention. The power of statistical analysis, much like the force of a rushing river, compels us to take note of the confluence of these two disparate domains.
The unexpected nature of this association may indeed prompt a quizzical grin, but it also serves as a reminder of the multifaceted interplay of global socio-political and environmental dynamics. Though this discovery may seem like the punchline to a particularly perplexing joke, the implications extend beyond mere amusement. This inquiry opens the door to a deeper understanding of the complex interrelationships that color our world, and invites further investigation into the manifold forces shaping our collective destinies.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of the relationship between the votes received by the Democrat Presidential candidate in Texas and the hydroelectric power generated in Nicaragua yielded a correlation coefficient of 0.8926604, indicating a strong positive association between the two variables. The coefficient of determination (r-squared) of 0.7968425 suggests that approximately 79.68% of the variability in Nicaraguan hydropower generation can be explained by the variation in votes for the Democrat candidate in Texas from 1980 to 2020. Moreover, the obtained p-value of less than 0.01 indicates a statistically significant relationship.

In Figure 1, the scatterplot illustrates the striking alignment of the data points, compellingly demonstrating the coherence between these ostensibly incongruent phenomena. The visual representation of the data points reinforces the surprising connection and evokes a sense of intrigue that is not commonly encountered in traditional research inquiries.

The remarkable correlation we uncovered may seem as unexpected as stumbling upon a budding cactus in the midst of a cascading waterfall – seemingly incongruous, yet undeniably present. The implications of this unanticipated juxtaposition prompt contemplation on the intricate and unforeseen interplay of global socio-political and environmental dynamics, leaving one with a sense of bemused wonderment. While the findings may evoke a chuckle or two, they warrant serious consideration and serve as a preamble to further, more in-depth investigations into the underlying mechanisms at play.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Votes for the Democrat Presidential candidate in Texas and Hydopower energy generated in Nicaragua. 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]]
The Texas-Democrat Vote Tally and Nicaraguan Hydropower: A Tenuous Tandem

[[ABSTRACT]]
This study scrutinizes the intriguing link between the votes garnered by the Democrat Presidential candidate in the state of Texas and the hydroelectric power generated in Nicaragua from 1980 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we uncovered a correlation coefficient of 0.8926604 and p < 0.01, indicating a statistically significant relationship between these seemingly unrelated variables. While the association would seemingly be bewildering, as political preferences in Texas are not known to directly influence energy output in Nicaragua, the findings stir the imagination and lead to probing questions about potential underlying factors. The results may elicit a wry smile, but the implications for future research and policy considerations are nothing to scoff at.

[[LITERATURE REVIEW]]
Prior to delving into the peculiar relationship between the Democratic vote tally in Texas and the hydroelectric power output in Nicaragua, it is prudent to survey existing literature that may shed light on seemingly unconnected phenomena intertwining in unexpected ways. Smith et al. (2015) examined political voting patterns in U.S. states and their potential impact on international energy dynamics. They found a modest correlation between political affiliations and energy production in neighboring countries. Doe and Jones (2018) investigated the role of transnational political events on global energy markets, but did not specifically explore the influence of state-level elections on energy generation in distant regions.
Turning to more general works with potential bearing on this juxtaposition, "The Energy Landscape: A Sociology of Energy Consumption" by John Q. Public and "Political Pendulums: An Analysis of Electoral Swings" by Joan Smith present insights that may indirectly inform our understanding of the unexpected linkages observed in the present study.
Taking a more imaginative leap, the fictional works "Power Struggles: a Novel of Political Intrigue" by A.C. Politician and "Rivers of Destiny: A Hydro-Energy Thriller" by H. Watts offer creative interpretations of the potential interplay between political machinations and energy production.Moreover, board games such as "Power Grid" and "Electioneering: Energy Edition" may provide metaphorical parallels to the entwined themes under consideration.
As we venture further into this exploration, the seemingly tangential connections between Texas voting behaviors and Nicaraguan hydropower are akin to stumbling upon a hidden treasure map in the unlikeliest of locations—a discovery both confounding and exhilarating.

[[RESULTS]]
The analysis of the relationship between the votes received by the Democrat Presidential candidate in Texas and the hydroelectric power generated in Nicaragua yielded a correlation coefficient of 0.8926604, indicating a strong positive association between the two variables. The coefficient of determination (r-squared) of 0.7968425 suggests that approximately 79.68% of the variability in Nicaraguan hydropower generation can be explained by the variation in votes for the Democrat candidate in Texas from 1980 to 2020. Moreover, the obtained p-value of less than 0.01 indicates a statistically significant relationship.
In Figure 1, the scatterplot illustrates the striking alignment of the data points, compellingly demonstrating the coherence between these ostensibly incongruent phenomena. The visual representation of the data points reinforces the surprising connection and evokes a sense of intrigue that is not commonly encountered in traditional research inquiries.
The remarkable correlation we uncovered may seem as unexpected as stumbling upon a budding cactus in the midst of a cascading waterfall – seemingly incongruous, yet undeniably present. The implications of this unanticipated juxtaposition prompt contemplation on the intricate and unforeseen interplay of global socio-political and environmental dynamics, leaving one with a sense of bemused wonderment. While the findings may evoke a chuckle or two, they warrant serious consideration and serve as a preamble to further, more in-depth investigations into the underlying mechanisms at play.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study uncovered a robust relationship between the votes for the Democrat Presidential candidate in Texas and the hydroelectric power generated in Nicaragua. These results are in line with the previous research by Smith et al. (2015), who also observed a correlation between political affiliations and energy production in neighboring countries. It appears that there is indeed more than meets the eye when it comes to the influence of state-level elections on energy generation in distant regions.

Moreover, the substantial correlation coefficient and statistically significant p-value lend credence to the idea that this connection, though seemingly baffling, is not to be dismissed outright. It is akin to stumbling upon a treasure map in an unexpected location – an exhilarating and confounding discovery indeed.

The scatterplot graphically conveys the striking coherence between the Democrat vote tally in Texas and Nicaraguan hydropower generation, leaving us with a sense of intrigue usually reserved for unexpected plot twists in a H. Watts novel. One cannot help but wonder at the unanticipated alignment of these seemingly incongruent elements, much like finding a cactus thriving amidst a gushing waterfall.

While the implications of this unlikely association may elicit a bemused smile, the import of such a finding should not be underestimated. It incites contemplation on the intricate interplay between global socio-political factors and environmental dynamics, much like pondering the intricacies of a challenging board game. This discovery opens the door to further, more nuanced investigations into the driving forces behind this paradoxical connection, inviting researchers to embark on a journey of exploration akin to solving a mystery in "Electioneering: Energy Edition."

In sum, the results of this study underscore the importance of staying open to unexpected connections and the need for continued investigation into the underlying mechanisms at play. This study serves as a reminder of the depth and complexity of the interactions that shape our world – a compelling narrative worthy of further exploration.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Votes for the Democrat Presidential candidate in Texas and Hydopower energy generated in Nicaragua. 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]]
The Texas-Democrat Vote Tally and Nicaraguan Hydropower: A Tenuous Tandem

[[ABSTRACT]]
This study scrutinizes the intriguing link between the votes garnered by the Democrat Presidential candidate in the state of Texas and the hydroelectric power generated in Nicaragua from 1980 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we uncovered a correlation coefficient of 0.8926604 and p < 0.01, indicating a statistically significant relationship between these seemingly unrelated variables. While the association would seemingly be bewildering, as political preferences in Texas are not known to directly influence energy output in Nicaragua, the findings stir the imagination and lead to probing questions about potential underlying factors. The results may elicit a wry smile, but the implications for future research and policy considerations are nothing to scoff at.

[[INTRDUCTION]]
The juxtaposition of politics and energy production is an unusual terrain for analysis, yet this study delves into the curious association between the votes accruing to the Democrat Presidential candidate in the state of Texas and the output of hydroelectric power in Nicaragua. One might be forgiven for raising an eyebrow at the mere mention of such a correlation, for the interconnectedness of these seemingly disparate phenomena is not readily apparent. However, as the saying goes, "The proof is in the pudding," and statistical analysis reveals an unexpected relationship worthy of investigation.
In the annals of quantitative research, rare is the occasion when political trends in the Lone Star State intersect with the generation of hydroelectric power in a distant Central American nation. Nevertheless, like an enigmatic puzzle waiting to be solved, this linkage beckons us to scrutinize the underlying mechanisms at play. While the notion that Texan voting proclivities could exert an influence on the hydroelectric landscape of Nicaragua may initially raise an arch of skepticism, the data tell a tale that demands attention. The power of statistical analysis, much like the force of a rushing river, compels us to take note of the confluence of these two disparate domains.
The unexpected nature of this association may indeed prompt a quizzical grin, but it also serves as a reminder of the multifaceted interplay of global socio-political and environmental dynamics. Though this discovery may seem like the punchline to a particularly perplexing joke, the implications extend beyond mere amusement. This inquiry opens the door to a deeper understanding of the complex interrelationships that color our world, and invites further investigation into the manifold forces shaping our collective destinies.

[[RESULTS]]
The analysis of the relationship between the votes received by the Democrat Presidential candidate in Texas and the hydroelectric power generated in Nicaragua yielded a correlation coefficient of 0.8926604, indicating a strong positive association between the two variables. The coefficient of determination (r-squared) of 0.7968425 suggests that approximately 79.68% of the variability in Nicaraguan hydropower generation can be explained by the variation in votes for the Democrat candidate in Texas from 1980 to 2020. Moreover, the obtained p-value of less than 0.01 indicates a statistically significant relationship.
In Figure 1, the scatterplot illustrates the striking alignment of the data points, compellingly demonstrating the coherence between these ostensibly incongruent phenomena. The visual representation of the data points reinforces the surprising connection and evokes a sense of intrigue that is not commonly encountered in traditional research inquiries.
The remarkable correlation we uncovered may seem as unexpected as stumbling upon a budding cactus in the midst of a cascading waterfall – seemingly incongruous, yet undeniably present. The implications of this unanticipated juxtaposition prompt contemplation on the intricate and unforeseen interplay of global socio-political and environmental dynamics, leaving one with a sense of bemused wonderment. While the findings may evoke a chuckle or two, they warrant serious consideration and serve as a preamble to further, more in-depth investigations into the underlying mechanisms at play.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

The discovery of a robust correlation between the votes for the Democrat Presidential candidate in Texas and the hydroelectric power generated in Nicaragua from 1980 to 2020 has brought forth a level of astonishment akin to stumbling upon a majestic tumbleweed in the midst of a bustling metropolis - a spectacle both unexpected and thought-provoking. While the seeming incongruity of this relationship may elicit a wry smile, the statistical evidence compels us to take this correlation seriously. The implications of this unanticipated linkage prompt contemplation on the intricate and unforeseen interplay of global socio-political and environmental dynamics, leaving one with a sense of bemused wonderment. Furthermore, the strength of the association, as indicated by the correlation coefficient and p-value, underscores the need for deeper inquiry into the potential underlying mechanisms.

Yet, in the grand tradition of academic research, it appears that this particular inquiry may mark the terminus of this peculiar journey. As such, it is with a sense of both amusement and satisfaction that we assert that no further research is needed in this vein. The unanticipated correlation between Texan voting preferences and Nicaraguan hydroelectric power generation stands as a testament to the capricious nature of empirical inquiry, and as such, it seems fitting to leave this curious confluence of phenomena to the annals of statistical oddities and whimsical research curiosities.

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 Texas-Democrat Vote Tally and Nicaraguan Hydropower: A Tenuous Tandem. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Political Energy Dynamics

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 Texas-Democrat Vote Tally and Nicaraguan Hydropower: A Tenuous Tandem. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Transnational Energy and Political Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Texas-Democrat Vote Tally and Nicaraguan Hydropower: A Tenuous Tandem with an abstract of This study scrutinizes the intriguing link between the votes garnered by the Democrat Presidential candidate in the state of Texas and the hydroelectric power generated in Nicaragua from 1980 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we uncovered a correlation coefficient of 0.8926604 and p < 0.01, indicating a statistically significant relationship between these seemingly unrelated variables. While the association would seemingly be bewildering, as political preferences in Texas are not known to directly influence energy output in Nicaragua, the findings stir the imagination and lead to probing questions about potential underlying factors. The results may elicit a wry smile, but the implications for future research and policy considerations are nothing to scoff at.

ChatGPT:

Texas, Democrat, vote, tally, Nicaraguan, hydropower, correlation, energy, output, presidential candidate, state, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration

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

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Data details

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

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

Correlation r = 0.8926604 (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 = 0.7968425 (Coefficient of determination)
This means 79.7% of the change in the one variable (i.e., Hydopower energy generated in Nicaragua) is predictable based on the change in the other (i.e., Votes for the Democratic Presidential candidate in Texas) over the 11 years from 1980 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00022.^Show 0.0002176285096692248000000000
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 0.89 in 0.022% of random cases. Said differently, if you correlated 4,595 random variables^Note Which I absolutely did.
with the same 10 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 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.

[ 0.63, 0.97 ] 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.

	1980	1984	1988	1992	1996	2000	2004	2008	2012	2016	2020
Votes for the Democratic Presidential candidate in Texas (Percentage of votes)	41.42	36.1139	43.3494	37.0785	43.8318	37.982	38.2243	43.6831	41.3834	43.2353	46.479
Hydopower energy generated in Nicaragua (Billion kWh)	0.506	0.233	0.391	0.254	0.427	0.208	0.318	0.52947	0.415	0.422	0.574471

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

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{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([41.42,36.1139,43.3494,37.0785,43.8318,37.982,38.2243,43.6831,41.3834,43.2353,46.479,])
array_2 = np.array([0.506,0.233,0.391,0.254,0.427,0.208,0.318,0.52947,0.415,0.422,0.574471,])
array_1_name = "Votes for the Democratic Presidential candidate in Texas"
array_2_name = "Hydopower energy generated in Nicaragua"

# 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 the Democratic Presidential candidate in Texas
Line chart for only Hydopower energy generated in Nicaragua
AI-generated correlation image
The spurious research paper: The Texas-Democrat Vote Tally and Nicaraguan Hydropower: A Tenuous Tandem

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Correlation ID: 5302 · Black Variable ID: 26172 · Red Variable ID: 23862


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