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Spurious correlation #5,521 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Rain in Perth and the second variable is Votes for Libertarian Senators in Alabama.  The chart goes from 1978 to 2002, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

The rain in Perth is actually a secret government experiment to promote independent thinking, leading to an increase in support for Libertarian candidates in far-off places like Alabama. How? Well, the rainwater is subtly infused with a belief in personal freedom and limited government, which is then carried across the ocean by, you guessed it, specially trained libertarian salmon. These politically enlightened fish make their way to the rivers of Alabama, where they tirelessly advocate for individual rights and the free market, ultimately swaying the senatorial election in favor of the Libertarians. It's a truly drip-down effect of aquatic activism!

Model: dalle-3
Prompt: [A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s] Create an image of a charming, picturesque setting where gentle rain falls over the cityscape of Perth, Australia. The rain nourishes the lush greenery and feeds into the rivers, imbuing the scene with tranquility and life. In the foreground, depict a group of determined libertarian salmon swimming purposefully through the clear streams. These salmon carry with them the subtle infusion of belief in personal freedom and limited government. As they journey, the salmon's route across the vast ocean could be shown, with politically enlightened symbols reflecting their movement. Finally, the scene should transition to the rivers of Alabama, where the tireless advocacy of the salmon has sparked an increase in support for Libertarian candidates in the senatorial election. The overall illustration should convey a captivating story of the salmon's politically enlightening journey and its impact. 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: Rain in Perth and Votes for Libertarian Senators in Alabama. 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 Macabre Futuristic A scene from Skyrim A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s
ChatGPT: A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s

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 Rain in Perth and Votes for Libertarian Senators in Alabama, in the following situation: The rain in Perth is actually a secret government experiment to promote independent thinking, leading to an increase in support for Libertarian candidates in far-off places like Alabama. How? Well, the rainwater is subtly infused with a belief in personal freedom and limited government, which is then carried across the ocean by, you guessed it, specially trained libertarian salmon. These politically enlightened fish make their way to the rivers of Alabama, where they tirelessly advocate for individual rights and the free market, ultimately swaying the senatorial election in favor of the Libertarians. It's a truly drip-down effect of aquatic activism!. Keep the description simple.
ChatGPT: In a picturesque setting, gentle rain falls over the city of Perth, Australia, nourishing the lush greenery and feeding into the rivers. Alongside this serene scene, a group of determined libertarian salmon swim purposefully through the clear streams, carrying with them the subtle infusion of belief in personal freedom and limited government. As they make their way across the vast ocean, their politically enlightened journey culminates in the rivers of Alabama, where their tireless advocacy for individual rights and the free market sparks an increase in support for Libertarian candidates in the senatorial election.

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 comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s ] and depicting this scene: In a picturesque setting, gentle rain falls over the city of Perth, Australia, nourishing the lush greenery and feeding into the rivers. Alongside this serene scene, a group of determined libertarian salmon swim purposefully through the clear streams, carrying with them the subtle infusion of belief in personal freedom and limited government. As they make their way across the vast ocean, their politically enlightened journey culminates in the rivers of Alabama, where their tireless advocacy for individual rights and the free market sparks an increase in support for Libertarian candidates in the senatorial election. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s] Create an image of a charming, picturesque setting where gentle rain falls over the cityscape of Perth, Australia. The rain nourishes the lush greenery and feeds into the rivers, imbuing the scene with tranquility and life. In the foreground, depict a group of determined libertarian salmon swimming purposefully through the clear streams. These salmon carry with them the subtle infusion of belief in personal freedom and limited government. As they journey, the salmon's route across the vast ocean could be shown, with politically enlightened symbols reflecting their movement. Finally, the scene should transition to the rivers of Alabama, where the tireless advocacy of the salmon has sparked an increase in support for Libertarian candidates in the senatorial election. The overall illustration should convey a captivating story of the salmon's politically enlightening journey and its impact.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in Rain in Perth positively influenced Libertarian votes for Senators in Alabama.

AI academic paper

(Because p < 0.05)
Rain or Shine: A Libertarian Lining in the Alabama Senate

The Journal of Political Contradictions

Jan 2024

Reminder: This paper is AI-generated. Not real!
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Rain in Perth and Libertarian votes for Senators in Alabama. Make lots of jokes, goofy observations, and puns.

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

Your research team used data from NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse to assess this nagging question. You found a correlation coefficient of 0.8237052 and p < 0.05 for 1978 to 2002.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Rain or Shine: A Libertarian Lining in the Alabama Senate

[[ABSTRACT]]
In this study, we explore the curious correlation between rainfall in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. While on the surface, this connection may seem as random as a rain shower in the desert, our team tirelessly researched and crunched the data to uncover some unexpected parallels. Leveraging the comprehensive data from the NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse, we uncovered a correlation coefficient that left us more amazed than a weatherman predicting a sunny day in Seattle. With a coefficient of 0.8237052 and a p-value less than 0.05 during the period from 1978 to 2002, the link between rain in Perth and Libertarian votes for Senators in Alabama cannot be dismissed as mere coincidence. Our findings open the floodgates to intriguing discussions about the impact of weather patterns on political behavior, and we hope to make a splash in the world of interdisciplinary research. So, grab your umbrella and join us on this precipitation of political and meteorological analysis!


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Rain in Perth and Libertarian votes for Senators in Alabama. Make lots of jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
Rain or Shine: A Libertarian Lining in the Alabama Senate

[[ABSTRACT]]
In this study, we explore the curious correlation between rainfall in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. While on the surface, this connection may seem as random as a rain shower in the desert, our team tirelessly researched and crunched the data to uncover some unexpected parallels. Leveraging the comprehensive data from the NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse, we uncovered a correlation coefficient that left us more amazed than a weatherman predicting a sunny day in Seattle. With a coefficient of 0.8237052 and a p-value less than 0.05 during the period from 1978 to 2002, the link between rain in Perth and Libertarian votes for Senators in Alabama cannot be dismissed as mere coincidence. Our findings open the floodgates to intriguing discussions about the impact of weather patterns on political behavior, and we hope to make a splash in the world of interdisciplinary research. So, grab your umbrella and join us on this precipitation of political and meteorological analysis!

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Rain has long been associated with a multitude of metaphors and symbolic meanings, from cleansing to renewal to sheer inconvenience when you've just washed your car. Meanwhile, politics has its own share of unpredictability, with candidates sometimes popping up as unexpectedly as a thunderstorm on a sunny day. In this paper, we aim to delve into the unexpected and rather unusual connection between rain in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. We understand that this correlation might sound as unrelated as a kangaroo in an ice rink, but our research has unearthed some compelling findings that are as surprising as a kangaroo hopping through a desert.

While one might expect weather in Perth and political tendencies in Alabama to share the same relevance as a penguin's swimming skills in the Sahara, our investigation has revealed a correlation coefficient that would raise more eyebrows than a surprise downpour in the Outback. We know it sounds as unlikely as finding a unicorn in a field, but with a coefficient of 0.8237052 and a p-value less than 0.05 from 1978 to 2002, the link between these seemingly unrelated events demands attention.

As we dive into this research, we invite you to enjoy the journey with us, and we hope our findings will "reign" supreme in the world of political and meteorological analysis. So, hold on to your hats (and umbrellas), as we navigate through this unexpected precipitation of data and analysis. Let's make it rain with some unlikely connections and a sprinkle of scholarly humor!


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 Rain in Perth and Libertarian votes for Senators in Alabama. Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
Rain or Shine: A Libertarian Lining in the Alabama Senate

[[ABSTRACT]]
In this study, we explore the curious correlation between rainfall in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. While on the surface, this connection may seem as random as a rain shower in the desert, our team tirelessly researched and crunched the data to uncover some unexpected parallels. Leveraging the comprehensive data from the NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse, we uncovered a correlation coefficient that left us more amazed than a weatherman predicting a sunny day in Seattle. With a coefficient of 0.8237052 and a p-value less than 0.05 during the period from 1978 to 2002, the link between rain in Perth and Libertarian votes for Senators in Alabama cannot be dismissed as mere coincidence. Our findings open the floodgates to intriguing discussions about the impact of weather patterns on political behavior, and we hope to make a splash in the world of interdisciplinary research. So, grab your umbrella and join us on this precipitation of political and meteorological analysis!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Rain has long been associated with a multitude of metaphors and symbolic meanings, from cleansing to renewal to sheer inconvenience when you've just washed your car. Meanwhile, politics has its own share of unpredictability, with candidates sometimes popping up as unexpectedly as a thunderstorm on a sunny day. In this paper, we aim to delve into the unexpected and rather unusual connection between rain in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. We understand that this correlation might sound as unrelated as a kangaroo in an ice rink, but our research has unearthed some compelling findings that are as surprising as a kangaroo hopping through a desert.
While one might expect weather in Perth and political tendencies in Alabama to share the same relevance as a penguin's swimming skills in the Sahara, our investigation has revealed a correlation coefficient that would raise more eyebrows than a surprise downpour in the Outback. We know it sounds as unlikely as finding a unicorn in a field, but with a coefficient of 0.8237052 and a p-value less than 0.05 from 1978 to 2002, the link between these seemingly unrelated events demands attention.
As we dive into this research, we invite you to enjoy the journey with us, and we hope our findings will "reign" supreme in the world of political and meteorological analysis. So, hold on to your hats (and umbrellas), as we navigate through this unexpected precipitation of data and analysis. Let's make it rain with some unlikely connections and a sprinkle of scholarly humor!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The curious correlation between rainfall in Perth, Australia and the votes for Libertarian candidates for Senators in Alabama, USA draws attention to an unexpected intersection of meteorological phenomena and political behavior. In "Smith and Doe's Study on Weather and Voting Patterns," the authors find a significant relationship between precipitation levels and voter turnout, laying the groundwork for our exploration. Additionally, "Jones' Analysis of Political Affiliation and Weather Events" highlights the potential influence of weather conditions on voters' mood and decision-making process.

Moving beyond the traditional literature, our investigation also incorporates insights from non-fiction works such as "Rain: A Natural and Cultural History" by Cynthia Barnett and "The Libertarian Reader: Classic and Contemporary Writings from Lao-Tzu to Milton Friedman" edited by David Boaz. These sources provide valuable context for understanding the meteorological and political dimensions of our research.

Furthermore, fictional literature brings a whimsical yet relevant perspective to our study, with books like "Cloud Atlas" by David Mitchell and "For Whom the Bell Tolls" by Ernest Hemingway mirroring the juxtaposition of disparate elements, much like rain in Perth and Libertarian votes in Alabama.

In an unexpected twist, the internet meme "Hide the Pain Harold," known for his forced smile amidst ironic discomfort, resonates with the perplexing nature of our findings. The juxtaposition of rain in an arid region and political inclinations towards Libertarian candidates elicits a similarly bemused response, aligning with the spirit of this internet sensation.

As we navigate through this curious confluence of weather and politics, we aim to shed light on the enigmatic connection between rain in Perth and Libertarian votes for Senators in Alabama, while injecting a dash of humor and unexpected surprises along the way. So, fasten your seatbelts, and get ready for a wild ride through this uncharted territory of interdisciplinary inquiry!


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 Rain in Perth and Libertarian votes for Senators in Alabama. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse . You used data from 1978 to 2002

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]]
Rain or Shine: A Libertarian Lining in the Alabama Senate

[[ABSTRACT]]
In this study, we explore the curious correlation between rainfall in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. While on the surface, this connection may seem as random as a rain shower in the desert, our team tirelessly researched and crunched the data to uncover some unexpected parallels. Leveraging the comprehensive data from the NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse, we uncovered a correlation coefficient that left us more amazed than a weatherman predicting a sunny day in Seattle. With a coefficient of 0.8237052 and a p-value less than 0.05 during the period from 1978 to 2002, the link between rain in Perth and Libertarian votes for Senators in Alabama cannot be dismissed as mere coincidence. Our findings open the floodgates to intriguing discussions about the impact of weather patterns on political behavior, and we hope to make a splash in the world of interdisciplinary research. So, grab your umbrella and join us on this precipitation of political and meteorological analysis!

[[INTRODUCTION]]
Rain has long been associated with a multitude of metaphors and symbolic meanings, from cleansing to renewal to sheer inconvenience when you've just washed your car. Meanwhile, politics has its own share of unpredictability, with candidates sometimes popping up as unexpectedly as a thunderstorm on a sunny day. In this paper, we aim to delve into the unexpected and rather unusual connection between rain in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. We understand that this correlation might sound as unrelated as a kangaroo in an ice rink, but our research has unearthed some compelling findings that are as surprising as a kangaroo hopping through a desert.
While one might expect weather in Perth and political tendencies in Alabama to share the same relevance as a penguin's swimming skills in the Sahara, our investigation has revealed a correlation coefficient that would raise more eyebrows than a surprise downpour in the Outback. We know it sounds as unlikely as finding a unicorn in a field, but with a coefficient of 0.8237052 and a p-value less than 0.05 from 1978 to 2002, the link between these seemingly unrelated events demands attention.
As we dive into this research, we invite you to enjoy the journey with us, and we hope our findings will "reign" supreme in the world of political and meteorological analysis. So, hold on to your hats (and umbrellas), as we navigate through this unexpected precipitation of data and analysis. Let's make it rain with some unlikely connections and a sprinkle of scholarly humor!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Now, onto the nitty-gritty of how we unraveled this tangled web of rain and libertarian leanings. First, let's address the elephant in the room – why on earth are we even attempting to correlate rainfall in Perth with the voting behavior of Alabama Senators? Well, as they say, when life gives you rain, you make it pour over some unexpected statistical relationships!

Data Collection:

Our research team embarked on a virtual expedition, scouring the vast landscape of the internet for relevant data. We mainly relied on the offerings of the NOAA National Climate Data Center and the MIT Election Data and Science Lab, Harvard Dataverse. It felt like we were data-mining ninjas, stealthily extracting precious information while dodging the occasional cat video or meme that threatened to distract us from our noble pursuit of knowledge.

Data Selection and Cleaning:

To ensure that our data were as squeaky clean as a freshly washed car (before an unexpected downpour, of course), we meticulously selected rainfall data from Perth, Australia, and Libertarian votes for Senators in Alabama, USA. We then proceeded to perform data cleaning operations more intensive than a car wash on a muddy truck. This involved removing any outliers that threatened to muddy the statistical waters and make our findings as murky as a swamp in the Everglades.

Statistical Analysis:

With our pristine data in hand, we performed statistical analyses as sophisticated as a well-tailored suit on a kangaroo. We calculated correlation coefficients and p-values like seasoned meteorological statisticians, aiming to unravel the intricacies of this unlikely connection. We used cutting-edge software for our analyses, making sure our results were as accurate as a GPS guiding a lost hiker out of the wilderness.

Time Frame:

Our data covered the period from 1978 to 2002, providing us with a substantial chunk of time to observe the ebbs and flows of rainfall and political preferences. We didn't want to miss even a single political thundercloud or libertarian drizzle within this timeframe.

Amidst this academic odyssey of data wrangling and analysis, we approached our research with a healthy sense of skepticism and curiosity, knowing that we were delving into uncharted territories with the humility of a lost tourist asking for directions in a foreign land. Our methodology blended rigor with a splash of whimsy, akin to conducting a symphony orchestra in the midst of a rainstorm.

So, with our umbrellas at the ready and our statistical rain boots laced up, we marched into the data quagmire, ready to uncover the intriguing dance between meteorology and political ideologies. Let's shine a light on the shadowy realm of meteoropolitics and explore the unexpected connections that make the world of research as dynamic and unpredictable as, well, the weather!


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

Please make up the results section of an academic research paper presenting the findings of the connection between Rain in Perth and Libertarian votes for Senators in Alabama. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse .

For the time period 1978 to 2002, you found a correlation 0.8237052, r-squared of 0.6784903, and p < 0.05.

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

Here is the title and abstract of the paper:
[[TITLE]]
Rain or Shine: A Libertarian Lining in the Alabama Senate

[[ABSTRACT]]
In this study, we explore the curious correlation between rainfall in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. While on the surface, this connection may seem as random as a rain shower in the desert, our team tirelessly researched and crunched the data to uncover some unexpected parallels. Leveraging the comprehensive data from the NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse, we uncovered a correlation coefficient that left us more amazed than a weatherman predicting a sunny day in Seattle. With a coefficient of 0.8237052 and a p-value less than 0.05 during the period from 1978 to 2002, the link between rain in Perth and Libertarian votes for Senators in Alabama cannot be dismissed as mere coincidence. Our findings open the floodgates to intriguing discussions about the impact of weather patterns on political behavior, and we hope to make a splash in the world of interdisciplinary research. So, grab your umbrella and join us on this precipitation of political and meteorological analysis!

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Rain has long been associated with a multitude of metaphors and symbolic meanings, from cleansing to renewal to sheer inconvenience when you've just washed your car. Meanwhile, politics has its own share of unpredictability, with candidates sometimes popping up as unexpectedly as a thunderstorm on a sunny day. In this paper, we aim to delve into the unexpected and rather unusual connection between rain in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. We understand that this correlation might sound as unrelated as a kangaroo in an ice rink, but our research has unearthed some compelling findings that are as surprising as a kangaroo hopping through a desert.
While one might expect weather in Perth and political tendencies in Alabama to share the same relevance as a penguin's swimming skills in the Sahara, our investigation has revealed a correlation coefficient that would raise more eyebrows than a surprise downpour in the Outback. We know it sounds as unlikely as finding a unicorn in a field, but with a coefficient of 0.8237052 and a p-value less than 0.05 from 1978 to 2002, the link between these seemingly unrelated events demands attention.
As we dive into this research, we invite you to enjoy the journey with us, and we hope our findings will "reign" supreme in the world of political and meteorological analysis. So, hold on to your hats (and umbrellas), as we navigate through this unexpected precipitation of data and analysis. Let's make it rain with some unlikely connections and a sprinkle of scholarly humor!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

After analyzing the data collected from the NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse, we found a correlation coefficient of 0.8237052 between the amount of rainfall in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. This correlation value is as strong as a front of thunderstorms approaching during a picnic; it caught us off guard and left us reaching for our academic umbrellas to shield ourselves from the downpour of statistical significance.

Furthermore, the r-squared value of 0.6784903 indicates that approximately 67.85% of the variability in Libertarian votes for Senators in Alabama can be explained by the amount of rain in Perth. It's like saying 67.85% of the influence of an election outcome can be predicted by the probability of rain falling on a cricket match!

The p-value being less than 0.05 provides strong evidence against the null hypothesis that the variables are unrelated. This result is so statistically significant that it's like finding a drop of rain in the middle of the Sahara - highly improbable!

In Figure 1, the scatterplot illustrates the striking correlation between the two variables. It's like a beautiful dance between two seemingly distant entities – rain in Perth and libertarian votes in Alabama – a dance that deserves a standing ovation from the scientific community.

In conclusion, our findings present a snapshot of a fascinating relationship between seemingly unrelated events. We encourage further exploration and discussion on the implications of weather patterns on political behavior, and we hope our findings will make a splash in the scholarly community, like a sudden downpour during a heatwave. We invite researchers to grab their umbrellas and join us in this journey of unexpected connections and scholarly amusement.

Let's keep the forecast unpredictable and the analysis vibrant!


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 Rain in Perth and Libertarian votes for Senators in Alabama. Make lots of 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]]
Rain or Shine: A Libertarian Lining in the Alabama Senate

[[ABSTRACT]]
In this study, we explore the curious correlation between rainfall in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. While on the surface, this connection may seem as random as a rain shower in the desert, our team tirelessly researched and crunched the data to uncover some unexpected parallels. Leveraging the comprehensive data from the NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse, we uncovered a correlation coefficient that left us more amazed than a weatherman predicting a sunny day in Seattle. With a coefficient of 0.8237052 and a p-value less than 0.05 during the period from 1978 to 2002, the link between rain in Perth and Libertarian votes for Senators in Alabama cannot be dismissed as mere coincidence. Our findings open the floodgates to intriguing discussions about the impact of weather patterns on political behavior, and we hope to make a splash in the world of interdisciplinary research. So, grab your umbrella and join us on this precipitation of political and meteorological analysis!

[[LITERATURE REVIEW]]
The curious correlation between rainfall in Perth, Australia and the votes for Libertarian candidates for Senators in Alabama, USA draws attention to an unexpected intersection of meteorological phenomena and political behavior. In "Smith and Doe's Study on Weather and Voting Patterns," the authors find a significant relationship between precipitation levels and voter turnout, laying the groundwork for our exploration. Additionally, "Jones' Analysis of Political Affiliation and Weather Events" highlights the potential influence of weather conditions on voters' mood and decision-making process.
Moving beyond the traditional literature, our investigation also incorporates insights from non-fiction works such as "Rain: A Natural and Cultural History" by Cynthia Barnett and "The Libertarian Reader: Classic and Contemporary Writings from Lao-Tzu to Milton Friedman" edited by David Boaz. These sources provide valuable context for understanding the meteorological and political dimensions of our research.
Furthermore, fictional literature brings a whimsical yet relevant perspective to our study, with books like "Cloud Atlas" by David Mitchell and "For Whom the Bell Tolls" by Ernest Hemingway mirroring the juxtaposition of disparate elements, much like rain in Perth and Libertarian votes in Alabama.
In an unexpected twist, the internet meme "Hide the Pain Harold," known for his forced smile amidst ironic discomfort, resonates with the perplexing nature of our findings. The juxtaposition of rain in an arid region and political inclinations towards Libertarian candidates elicits a similarly bemused response, aligning with the spirit of this internet sensation.
As we navigate through this curious confluence of weather and politics, we aim to shed light on the enigmatic connection between rain in Perth and Libertarian votes for Senators in Alabama, while injecting a dash of humor and unexpected surprises along the way. So, fasten your seatbelts, and get ready for a wild ride through this uncharted territory of interdisciplinary inquiry!

[[RESULTS]]
After analyzing the data collected from the NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse, we found a correlation coefficient of 0.8237052 between the amount of rainfall in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. This correlation value is as strong as a front of thunderstorms approaching during a picnic; it caught us off guard and left us reaching for our academic umbrellas to shield ourselves from the downpour of statistical significance.
Furthermore, the r-squared value of 0.6784903 indicates that approximately 67.85% of the variability in Libertarian votes for Senators in Alabama can be explained by the amount of rain in Perth. It's like saying 67.85% of the influence of an election outcome can be predicted by the probability of rain falling on a cricket match!
The p-value being less than 0.05 provides strong evidence against the null hypothesis that the variables are unrelated. This result is so statistically significant that it's like finding a drop of rain in the middle of the Sahara - highly improbable!
In Figure 1, the scatterplot illustrates the striking correlation between the two variables. It's like a beautiful dance between two seemingly distant entities – rain in Perth and libertarian votes in Alabama – a dance that deserves a standing ovation from the scientific community.
In conclusion, our findings present a snapshot of a fascinating relationship between seemingly unrelated events. We encourage further exploration and discussion on the implications of weather patterns on political behavior, and we hope our findings will make a splash in the scholarly community, like a sudden downpour during a heatwave. We invite researchers to grab their umbrellas and join us in this journey of unexpected connections and scholarly amusement.
Let's keep the forecast unpredictable and the analysis vibrant!

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our study has dived into the fascinating correlation between rain in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. Much like a surprise thunderstorm on a sunny day, our findings have shaken up the conventional wisdom about the influence of weather patterns on political preferences.

Our results not only affirm the prior research by Smith and Doe on weather and voting patterns and Jones' analysis of political affiliation and weather events but also provide an unexpected twist that feels like a plot development in a novel by David Mitchell. The strong correlation coefficient of 0.8237052 we uncovered is as eye-catching as a rainbow after a summer storm. This robust statistical linkage between rain in Perth and Libertarian votes in Alabama supports the idea that weather conditions can play a significant role in shaping political behavior. It's as though the atmospheric pressure in Perth is contributing to the political climate in Alabama, creating a whirlwind of electoral outcomes.

The literature review has served as both a guiding light and a road map, leading us through the uncharted territory of interdisciplinary inquiry. We've gladly embraced the unexpected humor and whimsy found in our sources, aligning with the mischievous spirit of our research. By incorporating insights from non-fiction works and embracing the whimsical perspective of fictional literature, we've added both scholarly depth and a dash of laughter to our study, akin to finding a hidden joke in the footnotes of a serious text.

With a robust r-squared value and a p-value less than 0.05, our results are like a meteorological marvel that demands attention not only from the academic community but also from weather forecasters and political pundits alike. The scatterplot in Figure 1 visually encapsulates this captivating relationship, akin to a dynamic tango between climate quirks and political preferences. It's as if the rain in Perth and the Libertarian votes in Alabama are engaged in an intricate dance that captures the imagination and challenges conventional thinking.

In conclusion, our findings lead to a deeper understanding of the interconnectedness of seemingly unrelated events, much like finding unexpected humor in a serious academic paper. We invite fellow researchers to don their metaphorical rain boots and join us in exploring the exciting terrain of interdisciplinary inquiry where rain, politics, and scholarly amusement converge. Let's keep the forecast unpredictable and the analysis vibrant, just like the capricious weather in Perth and the unpredictable preferences of Libertarian voters in Alabama.


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 Rain in Perth and Libertarian votes for Senators in Alabama. Make lots of 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]]
Rain or Shine: A Libertarian Lining in the Alabama Senate

[[ABSTRACT]]
In this study, we explore the curious correlation between rainfall in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. While on the surface, this connection may seem as random as a rain shower in the desert, our team tirelessly researched and crunched the data to uncover some unexpected parallels. Leveraging the comprehensive data from the NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse, we uncovered a correlation coefficient that left us more amazed than a weatherman predicting a sunny day in Seattle. With a coefficient of 0.8237052 and a p-value less than 0.05 during the period from 1978 to 2002, the link between rain in Perth and Libertarian votes for Senators in Alabama cannot be dismissed as mere coincidence. Our findings open the floodgates to intriguing discussions about the impact of weather patterns on political behavior, and we hope to make a splash in the world of interdisciplinary research. So, grab your umbrella and join us on this precipitation of political and meteorological analysis!

[[INTRDUCTION]]
Rain has long been associated with a multitude of metaphors and symbolic meanings, from cleansing to renewal to sheer inconvenience when you've just washed your car. Meanwhile, politics has its own share of unpredictability, with candidates sometimes popping up as unexpectedly as a thunderstorm on a sunny day. In this paper, we aim to delve into the unexpected and rather unusual connection between rain in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. We understand that this correlation might sound as unrelated as a kangaroo in an ice rink, but our research has unearthed some compelling findings that are as surprising as a kangaroo hopping through a desert.
While one might expect weather in Perth and political tendencies in Alabama to share the same relevance as a penguin's swimming skills in the Sahara, our investigation has revealed a correlation coefficient that would raise more eyebrows than a surprise downpour in the Outback. We know it sounds as unlikely as finding a unicorn in a field, but with a coefficient of 0.8237052 and a p-value less than 0.05 from 1978 to 2002, the link between these seemingly unrelated events demands attention.
As we dive into this research, we invite you to enjoy the journey with us, and we hope our findings will "reign" supreme in the world of political and meteorological analysis. So, hold on to your hats (and umbrellas), as we navigate through this unexpected precipitation of data and analysis. Let's make it rain with some unlikely connections and a sprinkle of scholarly humor!

[[RESULTS]]
After analyzing the data collected from the NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse, we found a correlation coefficient of 0.8237052 between the amount of rainfall in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. This correlation value is as strong as a front of thunderstorms approaching during a picnic; it caught us off guard and left us reaching for our academic umbrellas to shield ourselves from the downpour of statistical significance.
Furthermore, the r-squared value of 0.6784903 indicates that approximately 67.85% of the variability in Libertarian votes for Senators in Alabama can be explained by the amount of rain in Perth. It's like saying 67.85% of the influence of an election outcome can be predicted by the probability of rain falling on a cricket match!
The p-value being less than 0.05 provides strong evidence against the null hypothesis that the variables are unrelated. This result is so statistically significant that it's like finding a drop of rain in the middle of the Sahara - highly improbable!
In Figure 1, the scatterplot illustrates the striking correlation between the two variables. It's like a beautiful dance between two seemingly distant entities – rain in Perth and libertarian votes in Alabama – a dance that deserves a standing ovation from the scientific community.
In conclusion, our findings present a snapshot of a fascinating relationship between seemingly unrelated events. We encourage further exploration and discussion on the implications of weather patterns on political behavior, and we hope our findings will make a splash in the scholarly community, like a sudden downpour during a heatwave. We invite researchers to grab their umbrellas and join us in this journey of unexpected connections and scholarly amusement.
Let's keep the forecast unpredictable and the analysis vibrant!

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

As we close the umbrella on this whirlwind of research, our findings have uncovered a correlation between rain in Perth and Libertarian votes for Senators in Alabama that is as surprising as finding a kangaroo in a snowstorm – and no, we're not talking about some bizarre zoo escape plot!

With a correlation coefficient resembling a lightning bolt of statistical significance, it's clear that this connection is not just a passing shower of coincidence. Our results have left us more astounded than a weatherman trying to predict the exact minute it'll start raining cats and dogs.

The implications of weather on political behavior may sound as far-fetched as a koala water skiing, but our findings suggest that rain in one part of the world may indeed influence voting patterns in another, just like a drizzle turning into a downpour.

In the end, we assert that no further research is needed in this area. We've weathered the storm of skepticism, and our findings stand as solid as an umbrella in a hurricane. It's time to let this unexpected correlation reign supreme, and for researchers to grab their raincoats and explore new horizons of interdisciplinary connections!

No more research needed in this area – we've made it rain with knowledge!


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 Rain or Shine: A Libertarian Lining in the Alabama Senate. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Political Contradictions


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 Rain or Shine: A Libertarian Lining in the Alabama Senate. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Advancement of Political Paradoxes


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 Rain or Shine: A Libertarian Lining in the Alabama Senate with an abstract of In this study, we explore the curious correlation between rainfall in Perth, Australia, and the votes for Libertarian candidates for Senators in Alabama, USA. While on the surface, this connection may seem as random as a rain shower in the desert, our team tirelessly researched and crunched the data to uncover some unexpected parallels. Leveraging the comprehensive data from the NOAA National Climate Data Center and MIT Election Data and Science Lab, Harvard Dataverse, we uncovered a correlation coefficient that left us more amazed than a weatherman predicting a sunny day in Seattle. With a coefficient of 0.8237052 and a p-value less than 0.05 during the period from 1978 to 2002, the link between rain in Perth and Libertarian votes for Senators in Alabama cannot be dismissed as mere coincidence. Our findings open the floodgates to intriguing discussions about the impact of weather patterns on political behavior, and we hope to make a splash in the world of interdisciplinary research. So, grab your umbrella and join us on this precipitation of political and meteorological analysis!

ChatGPT:

rainfall, Perth Australia, Libertarian candidates, Alabama Senate, correlation, NOAA National Climate Data Center, MIT Election Data and Science Lab, Harvard Dataverse, weather patterns, political behavior, interdisciplinary research

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



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Data details

Rain in Perth
Detailed data title: Number of days with >= 0.01 inch/0.254 millimeter precipitation in the year at PERTH AIRPORT, AS
Source: NOAA National Climate Data Center
See what else correlates with Rain in Perth

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

Correlation r = 0.8237052 (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 = 0.6784903 (Coefficient of determination)
This means 67.8% of the change in the one variable (i.e., Votes for Libertarian Senators in Alabama) is predictable based on the change in the other (i.e., Rain in Perth) over the 6 years from 1978 through 2002.

p < 0.05, which statistically significant(Null hypothesis significance test)
The p-value is 0.044. 0.0438801561976061360000000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.82 in 4.4% of random cases. Said differently, if you correlated 23 random variables Which I absolutely did.
with the same 5 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 5 because we have two variables measured over a period of 6 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.

[ 0.04, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!


All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
197819801984199219962002
Rain in Perth (Precipitation days)99103108121109101
Votes for Libertarian Senators in Alabama (Total votes)60061309812191318112155020234




Why this works

  1. 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.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
  4. 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.
  5. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."


# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([99,103,108,121,109,101,])
array_2 = np.array([6006,13098,12191,31811,21550,20234,])
array_1_name = "Rain in Perth"
array_2_name = "Votes for Libertarian Senators in Alabama"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)



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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.

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Correlation ID: 5521 · Black Variable ID: 25375 · Red Variable ID: 26196
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