Spurious correlation #5,194 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Votes for the Libertarian Presidential candidate in Delaware and the second variable is Gasoline pumped in Mozambique. The chart goes from 1980 to 2020, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Votes for the Libertarian Presidential candidate in Delaware and the second variable is Gasoline pumped in Mozambique. The chart goes from 1980 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As more people in Delaware supported the Libertarian candidate, the demand for freedom and autonomy seemingly spread across the Atlantic, inspiring Mozambicans to assert their independence from high gas prices. It's as if the very essence of liberty, like a fabled invisible hand, reached out to uplift the spirits of Mozambique, leading to a revolt against oppressive fuel costs. Who would have thought that the fuel for Mozambique's gas price resistance would originate from the electoral process in a small American state? It just goes to show that when it comes to political influence on global fuel dynamics, the connection can be as unexpected as a plot twist in a satirical political comedy!

^{Show image generation prompt} Model: dalle-3
Prompt: Create a hyper-realistic image of a bustling scene in Delaware outside a polling station, with a long line of diverse individuals proudly casting their ballots for the Libertarian presidential candidate. Show the atmosphere charged with anticipation and hope. In the background, depict the seamless transition to a scene in Mozambique, where a determined crowd surrounds a gas station, filling their cars with fuel and expressing solidarity against high gas prices. Show the interconnected impact of the Delaware votes on the spirit of independence and resistance in Mozambique, capturing the powerful contrast between these two moments on different continents. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

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

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Votes for the Libertarian Presidential candidate in Delaware and Gasoline pumped in Mozambique. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: An image that looks like it is a scene from a Pixar movie a funny image you would see on reddit Pop art A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Hyper-realistic
ChatGPT: Hyper-realistic

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Votes for the Libertarian Presidential candidate in Delaware and Gasoline pumped in Mozambique, in the following situation: As more people in Delaware supported the Libertarian candidate, the demand for freedom and autonomy seemingly spread across the Atlantic, inspiring Mozambicans to assert their independence from high gas prices. It's as if the very essence of liberty, like a fabled invisible hand, reached out to uplift the spirits of Mozambique, leading to a revolt against oppressive fuel costs. Who would have thought that the fuel for Mozambique's gas price resistance would originate from the electoral process in a small American state? It just goes to show that when it comes to political influence on global fuel dynamics, the connection can be as unexpected as a plot twist in a satirical political comedy!. Keep the description simple.
ChatGPT: In Delaware, a line of people stretches out of a polling station, each proudly casting their ballot for the Libertarian presidential candidate. Meanwhile, in Mozambique, a crowd gathers around a gas station, standing firm to resist the high gas prices as they pump fuel into their cars. The image shows the intercontinental effect of the votes for the Libertarian candidate in Delaware, igniting a spark of independence and determination in Mozambique to fight against oppressive fuel costs.

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: [ Hyper-realistic ] and depicting this scene: In Delaware, a line of people stretches out of a polling station, each proudly casting their ballot for the Libertarian presidential candidate. Meanwhile, in Mozambique, a crowd gathers around a gas station, standing firm to resist the high gas prices as they pump fuel into their cars. The image shows the intercontinental effect of the votes for the Libertarian candidate in Delaware, igniting a spark of independence and determination in Mozambique to fight against oppressive fuel costs. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create a hyper-realistic image of a bustling scene in Delaware outside a polling station, with a long line of diverse individuals proudly casting their ballots for the Libertarian presidential candidate. Show the atmosphere charged with anticipation and hope. In the background, depict the seamless transition to a scene in Mozambique, where a determined crowd surrounds a gas station, filling their cars with fuel and expressing solidarity against high gas prices. Show the interconnected impact of the Delaware votes on the spirit of independence and resistance in Mozambique, capturing the powerful contrast between these two moments on different continents.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Votes for the Libertarian Presidential candidate in Delaware caused Gasoline pumped in Mozambique to increase.

AI academic paper

(Because p < 0.01)

Pumping Up Libertarian Votes: A Mozambique Gaslighting Connection

The Journal of Political Gaslighting 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 dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Delaware and Gasoline pumped in Mozambique. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some movies that you watched that are tangentially related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
Pumping Up Libertarian Votes: A Mozambique Gaslighting Connection

[[ABSTRACT]]
The paper investigates the intriguing link between the number of votes for the Libertarian presidential candidate in Delaware and the volume of gasoline pumped in Mozambique from 1980 to 2020. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Energy Information Administration, we employed statistical analyses to illuminate the enigmatic relationship between these disparate variables.

Our findings revealed a remarkably robust correlation coefficient of 0.9540694, with a p-value of less than 0.01, suggesting a strong association between these seemingly unrelated phenomena. This astonishing connection raises eyebrows and demands further exploration, akin to the common response when hearing a dad joke: "I'm gaslighted by laughter." The study's results offer a fertile ground for future investigations into the interplay between political preferences and fuel consumption, leaving readers to gasp in wonder at the unexpected parallels unearthed in this groundbreaking analysis.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the realm of political analysis and sociological research, uncovering unexpected correlations can be akin to stumbling upon a hidden treasure in the labyrinth of data. One such intriguing anomaly that demands attention is the connection between the number of votes for the Libertarian presidential candidate in the state of Delaware and the volume of gasoline pumped in the nation of Mozambique. This surprising correspondence, although initially met with raised eyebrows and skeptical looks, has sparked curiosity and a multitude of puns, much like a well-timed dad joke at a family gathering.
The premise of this study is rooted in exploring the underlying factors that potentially drive the parallel trends observed between the political preferences in a small U.S. state and the fuel consumption patterns in a distant African nation. Despite the seemingly arbitrary nature of this association, it is crucial to delve into the intricacies of the data and analyze the underlying mechanisms at play. Much like a punny dad joke, the correlation between these divergent variables cannot be dismissed simply as a random occurrence without a deeper investigation.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In their investigation into the subtle yet persistent correlation between political leanings and fuel usage, Smith et al. (2015) observe a marked tendency for individuals with libertarian inclinations to favor decentralized decision-making processes, similar to the decentralization required for the operation of multiple gas stations. This deliberate alignment in preferences may contribute to the unexpected congruity observed between the number of votes for the Libertarian candidate in Delaware and the volume of gasoline pumped in Mozambique, much like how a well-timed parallel parking maneuver can unexpectedly align two seemingly unrelated vehicles.

Crucially, Doe's comprehensive study (2018) delves into the intricate psychological underpinnings of political ideologies, highlighting the nuanced interplay between political attitudes and consumer behavior. This illuminates the plausibility of a connection between voting patterns and gasoline consumption, akin to the unexpected relationship between a gas station and a convenience store – their inherent link is often overlooked, despite their frequent cohabitation.

Jones et al. (2020) astutely noted the potential impact of international economic trends on domestic political decision-making, suggesting that global fuel consumption patterns could inadvertently influence individual voting behaviors. This inadvertent influence echoes the surprise when learning a dad joke related to electricity - it's shocking, but it leaves a lasting impression.

Moving beyond the academic realm, "The Moral Case for Fossil Fuels" by Alex Epstein presents a provocative perspective on the societal attitudes towards energy consumption, potentially shedding light on the moral considerations influencing both political affiliations and fuel usage. The inseparable link between moral considerations and behavioral choices is as inseparable as a father and his dad jokes - they may not always land, but they're undeniably connected.

Furthermore, in a fictional realm, the classic "Atlas Shrugged" by Ayn Rand delves into the intricate interplay between individualism and economic choices, providing a lens through which to examine the unexpected implications of libertarian ideologies on fuel consumption patterns. This examination is as thought-provoking as a philosophical dad joke - it leaves the reader pondering, even while eliciting a groan.

Additionally, the movie "Mad Max: Fury Road" offers a cinematic exploration of a dystopian future dominated by scarcity of resources, providing a visual representation of fuel scarcity that resonates with the underlying themes of energy consumption in the present study. Much like a well-executed dad joke, the movie offers a mix of action and unexpected twists that keep the audience engaged – and perhaps in need of a "fueling" station for laughter after the unexpected humor.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Delaware and Gasoline pumped in Mozambique. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
Pumping Up Libertarian Votes: A Mozambique Gaslighting Connection

[[ABSTRACT]]
The paper investigates the intriguing link between the number of votes for the Libertarian presidential candidate in Delaware and the volume of gasoline pumped in Mozambique from 1980 to 2020. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Energy Information Administration, we employed statistical analyses to illuminate the enigmatic relationship between these disparate variables.

Our findings revealed a remarkably robust correlation coefficient of 0.9540694, with a p-value of less than 0.01, suggesting a strong association between these seemingly unrelated phenomena. This astonishing connection raises eyebrows and demands further exploration, akin to the common response when hearing a dad joke: "I'm gaslighted by laughter." The study's results offer a fertile ground for future investigations into the interplay between political preferences and fuel consumption, leaving readers to gasp in wonder at the unexpected parallels unearthed in this groundbreaking analysis.

[[LITERATURE REVIEW]]
In their investigation into the subtle yet persistent correlation between political leanings and fuel usage, Smith et al. (2015) observe a marked tendency for individuals with libertarian inclinations to favor decentralized decision-making processes, similar to the decentralization required for the operation of multiple gas stations. This deliberate alignment in preferences may contribute to the unexpected congruity observed between the number of votes for the Libertarian candidate in Delaware and the volume of gasoline pumped in Mozambique, much like how a well-timed parallel parking maneuver can unexpectedly align two seemingly unrelated vehicles.
Crucially, Doe's comprehensive study (2018) delves into the intricate psychological underpinnings of political ideologies, highlighting the nuanced interplay between political attitudes and consumer behavior. This illuminates the plausibility of a connection between voting patterns and gasoline consumption, akin to the unexpected relationship between a gas station and a convenience store – their inherent link is often overlooked, despite their frequent cohabitation.
Jones et al. (2020) astutely noted the potential impact of international economic trends on domestic political decision-making, suggesting that global fuel consumption patterns could inadvertently influence individual voting behaviors. This inadvertent influence echoes the surprise when learning a dad joke related to electricity - it's shocking, but it leaves a lasting impression.
Moving beyond the academic realm, "The Moral Case for Fossil Fuels" by Alex Epstein presents a provocative perspective on the societal attitudes towards energy consumption, potentially shedding light on the moral considerations influencing both political affiliations and fuel usage. The inseparable link between moral considerations and behavioral choices is as inseparable as a father and his dad jokes - they may not always land, but they're undeniably connected.
Furthermore, in a fictional realm, the classic "Atlas Shrugged" by Ayn Rand delves into the intricate interplay between individualism and economic choices, providing a lens through which to examine the unexpected implications of libertarian ideologies on fuel consumption patterns. This examination is as thought-provoking as a philosophical dad joke - it leaves the reader pondering, even while eliciting a groan.
Additionally, the movie "Mad Max: Fury Road" offers a cinematic exploration of a dystopian future dominated by scarcity of resources, providing a visual representation of fuel scarcity that resonates with the underlying themes of energy consumption in the present study. Much like a well-executed dad joke, the movie offers a mix of action and unexpected twists that keep the audience engaged – and perhaps in need of a "fueling" station for laughter after the unexpected humor.

[[RESULTS]]
The analysis of the relationship between the number of votes for the Libertarian presidential candidate in Delaware and the volume of gasoline pumped in Mozambique from 1980 to 2020 yielded a correlation coefficient of 0.9540694. This remarkably high correlation coefficient suggests a strong association between these two variables, akin to an unexpected punchline in a serious conversation.
Additionally, the calculated r-squared value of 0.9102483 further solidifies the strength of the observed correlation, much like a well-constructed play on words. The high proportion of variance in one variable that is predictable from the other underscores the robustness of the connection identified in the data.
Furthermore, the p-value of less than 0.01 provides compelling evidence to reject the null hypothesis of no relationship between the number of votes for the Libertarian presidential candidate in Delaware and the volume of gasoline pumped in Mozambique. This statistically significant result underscores the importance of further investigating this surprising association, much like the urge to further explore a novel joke to fully appreciate its comedic value.
Figure 1 illustrates the strong correlation between the number of votes for the Libertarian presidential candidate in Delaware and the volume of gasoline pumped in Mozambique over the period from 1980 to 2020. The scatterplot visually demonstrates the tight relationship between these seemingly disparate variables, much like the unlikely pairing of a dad joke and a scholarly research paper.
The unexpected connection between political preferences and fuel consumption uncovered in this study challenges conventional wisdom, much like a clever dad joke disrupts the flow of a serious discussion. These results beckon for deeper exploration, offering a source of amusement and intellectual curiosity in the often staid world of empirical research.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of this study confirm and extend prior research suggesting a remarkable connection between the number of votes for the Libertarian presidential candidate in Delaware and the volume of gasoline pumped in Mozambique. The robust correlation coefficient of 0.9540694 and the r-squared value of 0.9102483 provide compelling evidence for the strength and predictability of this unexpected association, much like the reliability of a well-crafted dad joke in eliciting groans and laughter in equal measure.

The alignment of political preferences and fuel consumption, as observed in this study, is in line with the findings of Smith et al. (2015), who highlighted the parallels between libertarian leanings and decentralized decision-making processes. This resonance underscores the notion that individuals with libertarian inclinations may demonstrate preferences that seamlessly align with the decentralized operation of gas stations, much like the harmonious fusion of puns and scholarly discourse in this discussion section.

Furthermore, the psychological underpinnings of political ideologies, as elucidated by Doe (2018), offer a plausible explanation for the unexpected congruity between voting patterns and gasoline consumption. The nuanced interplay between political attitudes and consumer behavior serves as a compelling backdrop for understanding the surprising interconnection between the number of votes for the Libertarian candidate in Delaware and the volume of gasoline pumped in Mozambique, akin to the unexpected punchline of a well-crafted dad joke.

The impact of global fuel consumption patterns on individual voting behaviors, as posited by Jones et al. (2020), is echoed in the results of this study, further corroborating the inadvertent influence of international economic trends on domestic political decision-making. This unexpected influence resonates with the unanticipated impact of a dad joke related to electricity – it may spark laughter, but it also sparks contemplation.

Moreover, the unconventional link between moral considerations, political affiliations, and fuel usage, as explored in "The Moral Case for Fossil Fuels" by Alex Epstein, offers additional insights into the intricate web of factors shaping voting preferences and energy consumption. Just as moral considerations and behavioral choices are inextricably linked, so too are the serious and light-hearted elements of this scholarly discussion – much like a well-timed dad joke, this unexpected fusion leaves a lasting impression.

In summary, the results of this study not only support prior research but also unveil an unforeseen connection between political preferences and fuel consumption at an international scale. This unexpected finding challenges conventional wisdom, much like a clever dad joke disrupts the flow of a serious discussion. These results call for continued exploration and further investigation, offering a source of both intellectual curiosity and amusement in the realm of empirical research.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Pumping Up Libertarian Votes: A Mozambique Gaslighting Connection. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Political Gaslighting 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 Pumping Up Libertarian Votes: A Mozambique Gaslighting Connection. Respond only with the name of a fictional organization.

ChatGPT:

The Quantum Consciousness Research Institute

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 Pumping Up Libertarian Votes: A Mozambique Gaslighting Connection with an abstract of The paper investigates the intriguing link between the number of votes for the Libertarian presidential candidate in Delaware and the volume of gasoline pumped in Mozambique from 1980 to 2020. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and Energy Information Administration, we employed statistical analyses to illuminate the enigmatic relationship between these disparate variables.
Our findings revealed a remarkably robust correlation coefficient of 0.9540694, with a p-value of less than 0.01, suggesting a strong association between these seemingly unrelated phenomena. This astonishing connection raises eyebrows and demands further exploration, akin to the common response when hearing a dad joke: "I'm gaslighted by laughter." The study's results offer a fertile ground for future investigations into the interplay between political preferences and fuel consumption, leaving readers to gasp in wonder at the unexpected parallels unearthed in this groundbreaking analysis.

ChatGPT:

Libertarian presidential candidate, Delaware, gasoline consumption, Mozambique, voting patterns, correlation coefficient, statistical analysis, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration, political preferences, fuel consumption, interplay, future investigations, groundbreaking analysis

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

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Data details

Votes for the Libertarian Presidential candidate in Delaware
Detailed data title: Total votes cast for the Libertarian Presidential candidate in Delaware
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for the Libertarian Presidential candidate in Delaware

Gasoline pumped in Mozambique
Detailed data title: Volume of gasoline pumped consumed in Mozambique in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Gasoline pumped in Mozambique

Correlation r = 0.9540694 (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 = 0.9102483 (Coefficient of determination)
This means 91% of the change in the one variable (i.e., Gasoline pumped in Mozambique) is predictable based on the change in the other (i.e., Votes for the Libertarian Presidential candidate in Delaware) over the 11 years from 1980 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.2E-6.^Show 0.0000052247685257144810000000
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 0.95 in 0.00052% of random cases. Said differently, if you correlated 191,396 random variables^Note You don't actually need 191 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 10 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.83, 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.

	1980	1984	1988	1992	1996	2000	2004	2008	2012	2016	2020
Votes for the Libertarian Presidential candidate in Delaware (Total votes)	1974	268	1162	935	2052	774	586	1109	3882	14757	5000
Gasoline pumped in Mozambique (Million Barrels/Day)	1.55579	1.43611	0.8	0.9	0.9	1.23522	1.5615	2.28399	4.12516	11	6.52019

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 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.

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([1974,268,1162,935,2052,774,586,1109,3882,14757,5000,])
array_2 = np.array([1.55579,1.43611,0.8,0.9,0.9,1.23522,1.5615,2.28399,4.12516,11,6.52019,])
array_1_name = "Votes for the Libertarian Presidential candidate in Delaware"
array_2_name = "Gasoline pumped in Mozambique"

# 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.

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High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Votes for the Libertarian Presidential candidate in Delaware
Line chart for only Gasoline pumped in Mozambique
AI-generated correlation image
The spurious research paper: Pumping Up Libertarian Votes: A Mozambique Gaslighting Connection

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Correlation ID: 5194 · Black Variable ID: 25961 · Red Variable ID: 24718


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