Spurious correlation #5,725 · 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 Democratic Senators in California and the second variable is Solar power generated in Austria. The chart goes from 1993 to 2018, 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 Democratic Senators in California and the second variable is Solar power generated in Austria. The chart goes from 1993 to 2018, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The Democratic senators in California are shining a light on renewable energy, which has sparked a sunnier outlook on solar power. It's like they're conducting a solar revolution from across the pond, or should I say, solar system!

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image of a serene countryside setting in Austria, the landscape drenched in a golden glow from the abundant sunlight. Solar panels stand prominently against the picturesque scenery, harnessing the radiant energy. In the foreground, a Californian community gathers, casting their votes for Democratic senators. The campaign posters proudly display the senators' dedication to renewable energy and solar power. The sunlight glistens off the panels, evoking a sense of hope and progress. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

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

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Votes for Democratic Senators in California and Solar power generated in Austria. 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: Low poly A scene from Skyrim An image that looks like it is a scene from a Pixar movie Parallax art Cubism
ChatGPT: A scene from Skyrim

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Votes for Democratic Senators in California and Solar power generated in Austria, in the following situation: The Democratic senators in California are shining a light on renewable energy, which has sparked a sunnier outlook on solar power. It's like they're conducting a solar revolution from across the pond, or should I say, solar system!. Keep the description simple.
ChatGPT: Picture a sunny day in Austria, where solar panels are soaking up the abundant sunlight. In the foreground, a group of people in California are casting their votes for Democratic senators, with ballot papers in hand. The senators' campaign posters show their commitment to renewable energy and solar power. The sunlight reflects off the panels, creating a positive, bright energy that symbolizes the impact of the senators' initiatives on solar power.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A scene from Skyrim ] and depicting this scene: Picture a sunny day in Austria, where solar panels are soaking up the abundant sunlight. In the foreground, a group of people in California are casting their votes for Democratic senators, with ballot papers in hand. The senators' campaign posters show their commitment to renewable energy and solar power. The sunlight reflects off the panels, creating a positive, bright energy that symbolizes the impact of the senators' initiatives on solar power. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a serene countryside setting in Austria, the landscape drenched in a golden glow from the abundant sunlight. Solar panels stand prominently against the picturesque scenery, harnessing the radiant energy. In the foreground, a Californian community gathers, casting their votes for Democratic senators. The campaign posters proudly display the senators' dedication to renewable energy and solar power. The sunlight glistens off the panels, evoking a sense of hope and progress.

*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 Democrat votes for Senators in California caused Solar power generated in Austria to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Californian Democrat Votes and Austrian Solar Rates: A Correlation That Rhymes

The Journal of Eclectic Political and Solar Studies

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 Democrat votes for Senators in California and Solar power generated in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
Californian Democrat Votes and Austrian Solar Rates: A Correlation That Rhymes

[[ABSTRACT]]
In this paper, we delve into the unlikely connection between Democrat votes for Senators in California and the solar power generated in Austria. Our research team, armed with a quirky sense of curiosity, scoured the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to assess this seemingly ludicrous question. Despite the skepticism from our peers, we forged ahead and unearthed a correlation coefficient of 0.9682283 and p < 0.01 for the years 1993 to 2018, much to our surprise. It appears that the Californian political landscape and the Austrian solar scene may share more than just a love for sunshine – perhaps they are also soulmates in the grand cosmic dance of politics and renewable energy. As the data unfolded, we couldn't help but wonder if this correlation is a case of "solar opposites attract" or just a mere coincidence in the vast fabric of statistical comings and goings. Regardless, our findings add a whimsical twist to the age-old pondering of political and environmental ties. And as a relevant dad joke, we couldn't resist noting that this correlation is so strong, it's like Democrats in California and Austrian solar power are doing the Macarena in perfect harmony!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As we embark on this scholarly journey, we find ourselves pondering the peculiar connection between Californian Democrat votes and the solar power generated in Austria. It's a topic that may seem more outlandish than a stand-up comedian's take on solar panels, but as the saying goes, truth is stranger than fiction, much like a group of solar cells forming a sunlit disco party.
The propensity of Californians to lean towards the Democratic party and the sun-soaked commitment of Austrians to solar energy have raised eyebrows and piqued the interest of many, much like a dad joke that catches you off guard at the dinner table. However, armed with not just a sense of scientific rigor, but also a knack for playful inquiry, we set out to explore this correlation with the enthusiasm of a pun enthusiast at a comedy club.
One might ask, "What could possibly link these seemingly disparate entities?" Well, the answer could be as unexpected as finding a solar-powered charging station in the middle of a political rally – a correlation that could shed light on the dynamics between political preferences and environmental initiatives.
We waded through an ocean of data, navigated the treacherous seas of statistical analysis, and, much like a solar-powered sailboat, embraced the winds of uncertainty, all in pursuit of understanding this enigmatic relationship. And yes, you guessed it, we were "watt"-ching the data closely.
Our findings not only unearth a surprising correlation but also invite us to consider the whimsical dance of democracy and sustainability, akin to a surprising twist in a Broadway musical featuring anthropomorphic solar panels. The resonance found in our data could well be the scientific manifestation of "solar harmony," where Californian Democrats and Austrian solar power walk hand in hand, as if they were serenading us with a lively rendition of "Here Comes the Sun."

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

To our astonishment, the intersection of Californian Democrat votes and Austrian solar power has garnered minimal attention in the academic sphere. Nevertheless, our irrepressible curiosity led us to explore the nooks and crannies of diverse research domains, hoping to shed light on this unprecedented correlation. As we trudged through the literature like intrepid explorers, we stumbled upon a handful of studies that, albeit tangentially, touched upon the elusive link between political inclinations and renewable energy sources.

In "Green Politics," the authors delve into the intricate web of environmental activism and political ideologies, offering insights into the potential influence of party affiliations on sustainable initiatives. Their work, much like a solar eclipse, casts a shadow of speculation on the overlap of Democratic support and solar power utilization.

A study by Smith et al. (2017) on "Renewable Energy Policies" examines various factors influencing the adoption and expansion of solar energy across different regions. While their focus lies on policy frameworks and economic incentives, their findings hint at the underlying role of political dynamics in shaping the trajectory of solar energy utilization. It's as if they left us with a solar-powered trail of breadcrumbs to follow.

Now, let's take a whimsical detour and ponder the potential influence of fictional narratives on our understanding of this correlation. Could it be that the dystopian landscapes of "The Hunger Games" or the political intrigue in "House of Cards" offer subtle allegories to the dynamics at play? As we traverse the realm of fiction, we can't help but draw parallels between the power struggles in these narratives and the metaphorical tug-of-war between political affiliations and renewable energy preferences. It's almost like fiction is trying to whisper a not-so-fictional truth in our ears.

Speaking of whispers, let's not overlook the whispers of inspiration that board games can offer. In games like "Power Grid," players grapple with the complexities of energy production and distribution, mirroring the intricate dance of political forces and environmental sustainability. Perhaps, amidst the strategic maneuvering and tactical decisions, there lie clues to the elusive bond between Californian Democrat votes and Austrian solar power generation. It's almost like the board game is nudging us towards an electrifying revelation.

As we meander through this unconventional tapestry of literature and conjecture, we remain steadfast in our pursuit of unraveling the enigmatic connection between seemingly unrelated domains. While it may appear to be a quixotic quest, much like chasing shadows in the sunlight, we are determined to illuminate the unexplored nuances of this fascinating correlation. And yes, we'd be remiss if we didn't note that this pursuit is more adventurous than a solar-powered road trip through the valleys of curiosity!

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 Democrat votes for Senators in California and Solar power generated in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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 1993 to 2018

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]]
Californian Democrat Votes and Austrian Solar Rates: A Correlation That Rhymes

[[ABSTRACT]]
In this paper, we delve into the unlikely connection between Democrat votes for Senators in California and the solar power generated in Austria. Our research team, armed with a quirky sense of curiosity, scoured the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to assess this seemingly ludicrous question. Despite the skepticism from our peers, we forged ahead and unearthed a correlation coefficient of 0.9682283 and p < 0.01 for the years 1993 to 2018, much to our surprise. It appears that the Californian political landscape and the Austrian solar scene may share more than just a love for sunshine – perhaps they are also soulmates in the grand cosmic dance of politics and renewable energy. As the data unfolded, we couldn't help but wonder if this correlation is a case of "solar opposites attract" or just a mere coincidence in the vast fabric of statistical comings and goings. Regardless, our findings add a whimsical twist to the age-old pondering of political and environmental ties. And as a relevant dad joke, we couldn't resist noting that this correlation is so strong, it's like Democrats in California and Austrian solar power are doing the Macarena in perfect harmony!

[[INTRODUCTION]]
As we embark on this scholarly journey, we find ourselves pondering the peculiar connection between Californian Democrat votes and the solar power generated in Austria. It's a topic that may seem more outlandish than a stand-up comedian's take on solar panels, but as the saying goes, truth is stranger than fiction, much like a group of solar cells forming a sunlit disco party.
The propensity of Californians to lean towards the Democratic party and the sun-soaked commitment of Austrians to solar energy have raised eyebrows and piqued the interest of many, much like a dad joke that catches you off guard at the dinner table. However, armed with not just a sense of scientific rigor, but also a knack for playful inquiry, we set out to explore this correlation with the enthusiasm of a pun enthusiast at a comedy club.
One might ask, "What could possibly link these seemingly disparate entities?" Well, the answer could be as unexpected as finding a solar-powered charging station in the middle of a political rally – a correlation that could shed light on the dynamics between political preferences and environmental initiatives.
We waded through an ocean of data, navigated the treacherous seas of statistical analysis, and, much like a solar-powered sailboat, embraced the winds of uncertainty, all in pursuit of understanding this enigmatic relationship. And yes, you guessed it, we were "watt"-ching the data closely.
Our findings not only unearth a surprising correlation but also invite us to consider the whimsical dance of democracy and sustainability, akin to a surprising twist in a Broadway musical featuring anthropomorphic solar panels. The resonance found in our data could well be the scientific manifestation of "solar harmony," where Californian Democrats and Austrian solar power walk hand in hand, as if they were serenading us with a lively rendition of "Here Comes the Sun."

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the mystery of the correlation between Californian Democrat votes and Austrian solar power, our research team employed a blend of analytical techniques, statistical wizardry, and a sprinkle of whimsy to navigate this uncharted territory. Our data sources, including the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, provided us with a veritable treasure trove of information spanning the years 1993 to 2018. We then meticulously sifted through this data much like a prospector searching for gold, except our gold happened to be in the form of statistical patterns and political solar flares.

To kick off our methodological dance, we first harmonized the data from the various sources, ensuring that the Democrat votes in California and the solar power data from Austria were in perfect rhythm, much like a choreographed routine in a solar-powered musical. With the data aligned, we then performed a series of intricate statistical analyses, twirling and spinning through regression models and correlation coefficients with the finesse of a seasoned ballroom dancer, albeit with more spreadsheets and fewer sequins.

But wait, there's more! Our approach wasn't just about crunching numbers; we also embraced the power of visualization to bring our findings to life. We conjured up graphs and charts, transforming our data into a vibrant tapestry of political and solar intricacies, much like a master painter creating a canvas of statistical art while throwing in a subtle nod to the classic "Starry Night" by Van Gogh, but with solar panels instead of stars.

In parallel, we engaged in a spot of qualitative analysis, delving into historical and political narratives to enrich our understanding of the contextual nuances at play. It was like unraveling the plot of a riveting political thriller, except the climax involved a surprisingly strong correlation between Californian Democrats and Austrian solar power, and not a covert espionage operation.

To ensure the robustness of our findings, we meticulously cross-validated our results using alternative statistical methods and sensitivity analyses. This was like double-checking the recipe for a particularly tricky soufflé, except instead of eggs and flour, we were working with political data and solar energy statistics – equally delicate and prone to unexpected inflation.

Lastly, to add a touch of lightheartedness to our methodological expedition, we maintained an open line of communication with experts in both political science and renewable energy. This not only enriched our perspectives but also provided a platform for the exchange of amusing anecdotes and the occasional political pun, much like a gathering of intellectual jesters in the court of statistical inquiry.

In summary, our methodology blended the precision of analytical rigor with the spirit of playful inquiry, much like a waltz between reason and whimsy, creating a harmonious symphony of statistical exploration. And yes, we dare say, our methodology had all the right moves, much like a group of solar-powered robots performing the robot dance in perfect synchronization.

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 Democrat votes for Senators in California and Solar power generated in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
Californian Democrat Votes and Austrian Solar Rates: A Correlation That Rhymes

[[ABSTRACT]]
In this paper, we delve into the unlikely connection between Democrat votes for Senators in California and the solar power generated in Austria. Our research team, armed with a quirky sense of curiosity, scoured the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to assess this seemingly ludicrous question. Despite the skepticism from our peers, we forged ahead and unearthed a correlation coefficient of 0.9682283 and p < 0.01 for the years 1993 to 2018, much to our surprise. It appears that the Californian political landscape and the Austrian solar scene may share more than just a love for sunshine – perhaps they are also soulmates in the grand cosmic dance of politics and renewable energy. As the data unfolded, we couldn't help but wonder if this correlation is a case of "solar opposites attract" or just a mere coincidence in the vast fabric of statistical comings and goings. Regardless, our findings add a whimsical twist to the age-old pondering of political and environmental ties. And as a relevant dad joke, we couldn't resist noting that this correlation is so strong, it's like Democrats in California and Austrian solar power are doing the Macarena in perfect harmony!

[[LITERATURE REVIEW]]
To our astonishment, the intersection of Californian Democrat votes and Austrian solar power has garnered minimal attention in the academic sphere. Nevertheless, our irrepressible curiosity led us to explore the nooks and crannies of diverse research domains, hoping to shed light on this unprecedented correlation. As we trudged through the literature like intrepid explorers, we stumbled upon a handful of studies that, albeit tangentially, touched upon the elusive link between political inclinations and renewable energy sources.
In "Green Politics," the authors delve into the intricate web of environmental activism and political ideologies, offering insights into the potential influence of party affiliations on sustainable initiatives. Their work, much like a solar eclipse, casts a shadow of speculation on the overlap of Democratic support and solar power utilization.
A study by Smith et al. (2017) on "Renewable Energy Policies" examines various factors influencing the adoption and expansion of solar energy across different regions. While their focus lies on policy frameworks and economic incentives, their findings hint at the underlying role of political dynamics in shaping the trajectory of solar energy utilization. It's as if they left us with a solar-powered trail of breadcrumbs to follow.
Now, let's take a whimsical detour and ponder the potential influence of fictional narratives on our understanding of this correlation. Could it be that the dystopian landscapes of "The Hunger Games" or the political intrigue in "House of Cards" offer subtle allegories to the dynamics at play? As we traverse the realm of fiction, we can't help but draw parallels between the power struggles in these narratives and the metaphorical tug-of-war between political affiliations and renewable energy preferences. It's almost like fiction is trying to whisper a not-so-fictional truth in our ears.
Speaking of whispers, let's not overlook the whispers of inspiration that board games can offer. In games like "Power Grid," players grapple with the complexities of energy production and distribution, mirroring the intricate dance of political forces and environmental sustainability. Perhaps, amidst the strategic maneuvering and tactical decisions, there lie clues to the elusive bond between Californian Democrat votes and Austrian solar power generation. It's almost like the board game is nudging us towards an electrifying revelation.
As we meander through this unconventional tapestry of literature and conjecture, we remain steadfast in our pursuit of unraveling the enigmatic connection between seemingly unrelated domains. While it may appear to be a quixotic quest, much like chasing shadows in the sunlight, we are determined to illuminate the unexplored nuances of this fascinating correlation. And yes, we'd be remiss if we didn't note that this pursuit is more adventurous than a solar-powered road trip through the valleys of curiosity!

[[RESULTS]]
In this section, we unveil the captivating connection between Democrat votes for Senators in California and the solar power generated in Austria. Our analysis for the period from 1993 to 2018 revealed a staggering correlation coefficient of 0.9682283, indicating a remarkably strong positive relationship between these seemingly unrelated variables.
The r-squared value of 0.9374660 further emphasized the robustness of this correlation, implying that approximately 93.75% of the variation in Austrian solar power generation can be explained by the variation in Democrat votes for Senators in California. It's as if Californian Democrats and Austrian solar power were doing a perfectly choreographed dance – maybe a solar-powered cha-cha?
Moreover, the p-value of less than 0.01 lends strong support to the significance of this correlation. This means that the likelihood of such a strong relationship occurring by chance is less than 1%, making it about as rare as encountering a solar-powered unicorn basking in the Californian sun.
Additionally, the scatterplot (Fig. 1) in our analysis visually illustrates the striking correlation between Democrat votes for Senators in California and solar power generated in Austria. The points on the plot are so tightly clustered, it's as if they're vying for a prime spot under the solar spotlight – talk about a politically charged solar extravaganza!
These compelling findings serve to shed light on the unorthodox but intriguing relationship between political voting preferences in California and the utilization of solar energy in Austria. It’s as if the Californian Democrats and Austrian solar power have formed a bond that not even cloud cover can break – a true testament to the unexpected connections that data analysis can unfurl.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our investigation into the connection between Democrat votes for Senators in California and solar power generated in Austria have revealed an astonishingly strong correlation, much like the gravitational pull between celestial bodies in the vast expanse of space. Our findings align with previous literature suggesting subtle ties between political inclinations and renewable energy sources, akin to uncovering hidden constellations in the night sky.

Our research not only reinforces the notion of a significant relationship between Californian Democratic support and Austrian solar power utilization but also unveils the robustness of this intercontinental connection. It’s almost as if Californian Democrats and Austrian solar power are engaged in an intercontinental tango, moving in perfect sync despite the geographical chasm between them.

The striking correlation coefficient of 0.9682283 can be likened to a perfectly orchestrated symphony, with Californian Democrats and Austrian solar power in a harmonious dance. This bond, though surprising, underscores the intricate interplay between political preferences and environmental initiatives, much like a hybrid car seamlessly integrating electric and gasoline power – talk about a politically charged fusion!

Furthermore, the r-squared value of 0.9374660 emphasizes the substantial explanatory power of Democrat votes for Senators in California on Austrian solar power generation, akin to the compelling narrative of an underdog emerging victorious against all odds. This statistical feat implies that nearly 93.75% of the variations in Austrian solar power generation can be elucidated by understanding the ebbs and flows of Democrat votes for Senators in California. It’s as if this correlation is the ultimate solar-powered buddy comedy; they just can’t seem to outshine each other.

In line with the quirky nature of our findings, the p-value of less than 0.01 accentuates the significance of this correlation. It indicates a less than 1% chance of this relationship occurring by sheer happenstance – a probability as rare as finding a solar-powered unicorn cavorting in the Austrian Alps. It's almost like a whimsical tale where Californian Democrats and Austrian solar power embark on a captivating adventure, defying the odds with every sun-kissed step they take.

As we scrutinize the scatterplot (Fig. 1) depicting the captivating correlation, the tightly clustered points resemble a crowded dance floor where every move is astutely synchronized. It's akin to a political rally turned solar-powered soirée, with every data point vying for a prime spot under the radiant solar spotlight. This visual showcase of the correlation is akin to a vibrant mural capturing the unexpected fusion of political fervor and sustainable energy.

Our findings summon a whimsical twist to the often stoic realm of statistical analysis, offering an engaging narrative of the unanticipated kismet between the political climate in California and the solar landscape in Austria. It’s as if Californian Democrats and Austrian solar power are engaged in an endearing pas de deux, choreographing a dance that defies conventional expectations.

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 Democrat votes for Senators in California and Solar power generated in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
Californian Democrat Votes and Austrian Solar Rates: A Correlation That Rhymes

[[ABSTRACT]]
In this paper, we delve into the unlikely connection between Democrat votes for Senators in California and the solar power generated in Austria. Our research team, armed with a quirky sense of curiosity, scoured the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to assess this seemingly ludicrous question. Despite the skepticism from our peers, we forged ahead and unearthed a correlation coefficient of 0.9682283 and p < 0.01 for the years 1993 to 2018, much to our surprise. It appears that the Californian political landscape and the Austrian solar scene may share more than just a love for sunshine – perhaps they are also soulmates in the grand cosmic dance of politics and renewable energy. As the data unfolded, we couldn't help but wonder if this correlation is a case of "solar opposites attract" or just a mere coincidence in the vast fabric of statistical comings and goings. Regardless, our findings add a whimsical twist to the age-old pondering of political and environmental ties. And as a relevant dad joke, we couldn't resist noting that this correlation is so strong, it's like Democrats in California and Austrian solar power are doing the Macarena in perfect harmony!

[[INTRDUCTION]]
As we embark on this scholarly journey, we find ourselves pondering the peculiar connection between Californian Democrat votes and the solar power generated in Austria. It's a topic that may seem more outlandish than a stand-up comedian's take on solar panels, but as the saying goes, truth is stranger than fiction, much like a group of solar cells forming a sunlit disco party.
The propensity of Californians to lean towards the Democratic party and the sun-soaked commitment of Austrians to solar energy have raised eyebrows and piqued the interest of many, much like a dad joke that catches you off guard at the dinner table. However, armed with not just a sense of scientific rigor, but also a knack for playful inquiry, we set out to explore this correlation with the enthusiasm of a pun enthusiast at a comedy club.
One might ask, "What could possibly link these seemingly disparate entities?" Well, the answer could be as unexpected as finding a solar-powered charging station in the middle of a political rally – a correlation that could shed light on the dynamics between political preferences and environmental initiatives.
We waded through an ocean of data, navigated the treacherous seas of statistical analysis, and, much like a solar-powered sailboat, embraced the winds of uncertainty, all in pursuit of understanding this enigmatic relationship. And yes, you guessed it, we were "watt"-ching the data closely.
Our findings not only unearth a surprising correlation but also invite us to consider the whimsical dance of democracy and sustainability, akin to a surprising twist in a Broadway musical featuring anthropomorphic solar panels. The resonance found in our data could well be the scientific manifestation of "solar harmony," where Californian Democrats and Austrian solar power walk hand in hand, as if they were serenading us with a lively rendition of "Here Comes the Sun."

[[RESULTS]]
In this section, we unveil the captivating connection between Democrat votes for Senators in California and the solar power generated in Austria. Our analysis for the period from 1993 to 2018 revealed a staggering correlation coefficient of 0.9682283, indicating a remarkably strong positive relationship between these seemingly unrelated variables.
The r-squared value of 0.9374660 further emphasized the robustness of this correlation, implying that approximately 93.75% of the variation in Austrian solar power generation can be explained by the variation in Democrat votes for Senators in California. It's as if Californian Democrats and Austrian solar power were doing a perfectly choreographed dance – maybe a solar-powered cha-cha?
Moreover, the p-value of less than 0.01 lends strong support to the significance of this correlation. This means that the likelihood of such a strong relationship occurring by chance is less than 1%, making it about as rare as encountering a solar-powered unicorn basking in the Californian sun.
Additionally, the scatterplot (Fig. 1) in our analysis visually illustrates the striking correlation between Democrat votes for Senators in California and solar power generated in Austria. The points on the plot are so tightly clustered, it's as if they're vying for a prime spot under the solar spotlight – talk about a politically charged solar extravaganza!
These compelling findings serve to shed light on the unorthodox but intriguing relationship between political voting preferences in California and the utilization of solar energy in Austria. It’s as if the Californian Democrats and Austrian solar power have formed a bond that not even cloud cover can break – a true testament to the unexpected connections that data analysis can unfurl.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has illuminated an astonishing correlation between Democrat votes for Senators in California and the solar power generated in Austria. The robust correlation coefficient of 0.9682283 and a remarkably low p-value affirm the compelling link between these seemingly disparate variables. It's as if Californian Democrats and Austrian solar power are in perfect sync, much like a precision-engineered solar-powered Swiss watch!

Our findings provoke us to contemplate the intriguing interplay between political preferences and environmental initiatives, akin to a thought-provoking subplot in a quirky political satire. This correlation may very well be the manifestation of a harmonious duet between political leanings and renewable energy, where Californian Democrats and Austrian solar power sway in rhythm, as if they were performing a lively rendition of "You Are the Sunshine of My Life."

With that said, based on our comprehensive analysis, we assert with a beaming sense of confidence that no further research is needed in this peculiar junction of political votes and solar power. It seems this unexpected correlation has been thoroughly illuminated, and it's time to let this quirky pair of political and environmental factors have their moment in the sun without any further "watt"s and puns.

But hey, if there's ever a need for a chuckle-inducing exploration of surprising correlations in the future, we'll be here with our dad jokes and statistical analyses at the ready!

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 Californian Democrat Votes and Austrian Solar Rates: A Correlation That Rhymes. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Eclectic Political and Solar Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Californian Democrat Votes and Austrian Solar Rates: A Correlation That Rhymes. Respond only with the name of a fictional organization.

ChatGPT:

Institute for Intercontinental Political and Solar 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 Californian Democrat Votes and Austrian Solar Rates: A Correlation That Rhymes with an abstract of In this paper, we delve into the unlikely connection between Democrat votes for Senators in California and the solar power generated in Austria. Our research team, armed with a quirky sense of curiosity, scoured the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to assess this seemingly ludicrous question. Despite the skepticism from our peers, we forged ahead and unearthed a correlation coefficient of 0.9682283 and p < 0.01 for the years 1993 to 2018, much to our surprise. It appears that the Californian political landscape and the Austrian solar scene may share more than just a love for sunshine – perhaps they are also soulmates in the grand cosmic dance of politics and renewable energy. As the data unfolded, we couldn't help but wonder if this correlation is a case of "solar opposites attract" or just a mere coincidence in the vast fabric of statistical comings and goings. Regardless, our findings add a whimsical twist to the age-old pondering of political and environmental ties. And as a relevant dad joke, we couldn't resist noting that this correlation is so strong, it's like Democrats in California and Austrian solar power are doing the Macarena in perfect harmony!

ChatGPT:

California Democrat votes, Austrian solar rates, correlation, solar power generation, politics, renewable energy, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration, correlation coefficient, statistical analysis, environmental ties, political landscape, cosmic dance, renewable energy, solar opposites attract, coincidence, whimsical twist, statistical correlation, data analysis

*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 Democratic Senators in California
Detailed data title: Percentage of votes cast for Federal Democrat Senate candidates in California
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for Democratic Senators in California

Solar power generated in Austria
Detailed data title: Total solar power generated in Austria in billion kWh
Source: Energy Information Administration
See what else correlates with Solar power generated in Austria

Correlation r = 0.9682283 (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 = 0.9374660 (Coefficient of determination)
This means 93.7% of the change in the one variable (i.e., Solar power generated in Austria) is predictable based on the change in the other (i.e., Votes for Democratic Senators in California) over the 9 years from 1993 through 2018.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.8E-5.^Show 0.0000182468131892610000000000
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 0.97 in 0.0018% of random cases. Said differently, if you correlated 54,804 random variables^Note You don't actually need 54 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 8 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 8 because we have two variables measured over a period of 9 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.

[ 0.85, 0.99 ] 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.

	1994	1998	2000	2004	2006	2010	2012	2016	2018
Votes for Democratic Senators in California (Percentage of votes)	46.7361	53.0571	55.8428	57.7081	59.4311	52.1836	62.5243	100	100
Solar power generated in Austria (Billion kWh)	0.001	0.002	0.003	0.018	0.022	0.084421	0.322197	1.0423	1.38655

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.
Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.
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([46.7361,53.0571,55.8428,57.7081,59.4311,52.1836,62.5243,100,100,])
array_2 = np.array([0.001,0.002,0.003,0.018,0.022,0.084421,0.322197,1.0423,1.38655,])
array_1_name = "Votes for Democratic Senators in California"
array_2_name = "Solar power generated in Austria"

# 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 Democratic Senators in California
Line chart for only Solar power generated in Austria
AI-generated correlation image
The spurious research paper: Californian Democrat Votes and Austrian Solar Rates: A Correlation That Rhymes

View another random correlation

How fun was this correlation?

Your rating is stellar!

Correlation ID: 5725 · Black Variable ID: 26354 · Red Variable ID: 23480


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