Spurious correlation #3,874 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Fossil fuel use in Bahrain and the second variable is Total number of automotive recalls. The chart goes from 1980 to 2021, 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 Fossil fuel use in Bahrain and the second variable is Total number of automotive recalls. The chart goes from 1980 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The fumes were creating a supercharged effect, revving up the likelihood of automotive malfunctions. Can you be-leaf it? It's enough to make any car owner oil with frustration!

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Generate an image depicting the bustling streets of Bahrain, where cars are sliding on the road due to excess oil residue. A towering digital billboard in the background shows increasing automotive recalls, while oil tankers are seen lining up at the nearby port. The scene should capture the chaos of the street and the contrast between the modern digital billboard and the traditional oil tankers. The focus should be on the cars slipping and skidding on the oil-covered roads, creating a sense of tension and urgency. 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: Fossil fuel use in Bahrain and Total number of automotive recalls. 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: Glitch art Cutsy graphics Concept art Realistic Scalar art
ChatGPT: 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 Fossil fuel use in Bahrain and Total number of automotive recalls, in the following situation: Because the excessive use of fossil fuels in Bahrain led to increased oil residue on the roads, causing cars to skid and crash, resulting in a higher number of automotive recalls.. Keep the description simple.
ChatGPT: On the busy streets of Bahrain, rows of cars are slipping and skidding due to the excess oil residue from combustion engines. Amidst the chaos, a large digital billboard displays the soaring number of automotive recalls, while oil tankers line up at the nearby port, ready to unload their fossil fuel cargo.

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: [ Realistic ] and depicting this scene: On the busy streets of Bahrain, rows of cars are slipping and skidding due to the excess oil residue from combustion engines. Amidst the chaos, a large digital billboard displays the soaring number of automotive recalls, while oil tankers line up at the nearby port, ready to unload their fossil fuel cargo. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image depicting the bustling streets of Bahrain, where cars are sliding on the road due to excess oil residue. A towering digital billboard in the background shows increasing automotive recalls, while oil tankers are seen lining up at the nearby port. The scene should capture the chaos of the street and the contrast between the modern digital billboard and the traditional oil tankers. The focus should be on the cars slipping and skidding on the oil-covered roads, creating a sense of tension and urgency.

*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 Fossil fuel use in Bahrain caused Total number of automotive recalls to increase.

AI academic paper

(Because p < 0.01)

Fueling the Fire: The Gas Connection Between Fossil Fuel Use in Bahrain and Automotive Recalls

The International Journal of Petroleum and Automotive Engineering

Jan 2024

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

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Fossil fuel use in Bahrain and Total number of automotive recalls. 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
Fueling the Fire: The Gas Connection Between Fossil Fuel Use in Bahrain and Automotive Recalls

[[ABSTRACT]]
As the old saying goes, "Where there's smoke, there's fire." In our case, where there's fossil fuel use in Bahrain, there seems to be a blazing correlation with the total number of automotive recalls. Our research team delved deep into this combustible topic, utilizing data from the Energy Information Administration and the US Department of Transportation. Through our rigorous analysis, we discovered a scorching correlation coefficient of 0.9671276 and a p-value less than 0.01 for the years 1980 to 2021. These findings suggest that there may indeed be sparks flying between fossil fuel consumption in Bahrain and the eruption of automotive recalls. The relationship between these variables is nothing short of incendiary, potentially igniting a need for further investigation into the intricacies of this connection. Join us as we fan the flames of curiosity and let the data kindle a new understanding of the fiery relationship between fossil fuel use and automotive recalls.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Fire up your engines, folks, because we're about to dive into a sizzling investigation that connects the burning issue of fossil fuel use in Bahrain to the heated world of automotive recalls. As researchers, we often find ourselves trekking into uncharted territory, armed with statistical tools and a healthy dose of curiosity. Our mission? To unravel the fiery relationship between these seemingly unrelated variables and shed light on whether there's more than meets the eye – or should we say, the exhaust pipe?
In the realm of data analysis, uncovering correlations can feel like stumbling upon hidden treasure, especially when the variables at play appear to be as distant as a desert oasis is from an ice rink. Fossil fuel consumption and automotive recalls might seem like an odd couple, but as we gathered our data from the Energy Information Administration and the US Department of Transportation, we couldn't help but notice some smoldering patterns that begged to be explored.
Now, before we ignite the flames of curiosity further, let's take a moment to appreciate the sheer unpredictability of research. Like the whims of a mad scientist, our findings can often surprise us, challenging our assumptions and leading us down unexpected rabbit holes. And what could be more unexpected than finding a potential link between the gas-guzzling habits of a small island nation and the safety concerns of cars and trucks crisscrossing the highways? It's like discovering that your favorite childhood toys – a chemistry set and a toy car – have been secretly plotting to collaborate all along.
As we venture into this scorching hot topic, we invite you to grab your lab coat and join us in delving into the combustible world of data analysis. Strap in for a wild ride through the fiery realm of statistical significance and correlation coefficients that may just set your scientific heart ablaze. Our findings are sure to spark some lively discussions and perhaps even kindle a newfound appreciation for the unexpected connections that lurk beneath the surface of seemingly unrelated phenomena.
So, buckle up and get ready to explore the gas connection between fossil fuel use in Bahrain and automotive recalls. It's bound to be an exhilarating journey, filled with unexpected twists and turns – much like navigating rush hour traffic in a bustling metropolis.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The connection between fossil fuel use in Bahrain and automotive recalls has sparked interest in a wide range of academic and non-academic sources, shedding light on this unexpected relationship that seems to be fueling more than just cars. Smith and Doe (2015) provided an early examination of the potential link, highlighting the combustible nature of the topic and laying the groundwork for further investigation. Furthermore, Jones et al. (2018) delved into the fiery depths of this correlation, igniting discussions about the underlying mechanisms at play.

In "The Gas Chronicles" by Petroleum Politics, lorem and ipsum are presented, showcasing the dynamic interplay between fuel consumption and its impact on automotive safety. The authors reveal the unexpected twists and turns of this narrative, demonstrating how the story of fuel and recalls is far from running on fumes.

On the non-fiction front, works such as "The Burning Truth: Fossil Fuel Dilemma" by Climate Crisis Coalition and "Recalls Under the Hood: Unveiling Automotive Safety" by Vehicle Vigilance Foundation offer insightful perspectives on the broader context of fossil fuel use and automotive recalls. The fiery passion of these authors for unraveling the complexities of the automotive industry and its relationship with fuel consumption is truly ablaze.

Turning to the world of fiction, "The Inferno Drive" by Ignatius Camshaft and "Recall: A Tale of Flaming Fury" by Ember Sparks may not be scholarly treatises, but their thematic resonance with our research topic is undeniably captivating. The imaginative exploration of infernal themes in these works serves as a reminder that even the most fantastical tales can offer sparks of insight into our own fiery investigation.

In conducting this literature review, the authors also gathered data from an array of unconventional sources, including the backs of shampoo bottles, where the chemical compositions and safety precautions provided a surprisingly relevant perspective on the intersection of combustible elements and potential risks – a hair-raising connection, to say the least.

As we wade through this sea of literature, puns, and unexpected connections, it is clear that the discourse surrounding the relationship between fossil fuel use in Bahrain and automotive recalls is as varied and surprising as uncovering a hidden treasure trove in the desert sands.

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 Fossil fuel use in Bahrain and Total number of automotive recalls. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and US DOT . You used data from 1980 to 2021

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]]
Fueling the Fire: The Gas Connection Between Fossil Fuel Use in Bahrain and Automotive Recalls

[[ABSTRACT]]
As the old saying goes, "Where there's smoke, there's fire." In our case, where there's fossil fuel use in Bahrain, there seems to be a blazing correlation with the total number of automotive recalls. Our research team delved deep into this combustible topic, utilizing data from the Energy Information Administration and the US Department of Transportation. Through our rigorous analysis, we discovered a scorching correlation coefficient of 0.9671276 and a p-value less than 0.01 for the years 1980 to 2021. These findings suggest that there may indeed be sparks flying between fossil fuel consumption in Bahrain and the eruption of automotive recalls. The relationship between these variables is nothing short of incendiary, potentially igniting a need for further investigation into the intricacies of this connection. Join us as we fan the flames of curiosity and let the data kindle a new understanding of the fiery relationship between fossil fuel use and automotive recalls.

[[INTRODUCTION]]
Fire up your engines, folks, because we're about to dive into a sizzling investigation that connects the burning issue of fossil fuel use in Bahrain to the heated world of automotive recalls. As researchers, we often find ourselves trekking into uncharted territory, armed with statistical tools and a healthy dose of curiosity. Our mission? To unravel the fiery relationship between these seemingly unrelated variables and shed light on whether there's more than meets the eye – or should we say, the exhaust pipe?
In the realm of data analysis, uncovering correlations can feel like stumbling upon hidden treasure, especially when the variables at play appear to be as distant as a desert oasis is from an ice rink. Fossil fuel consumption and automotive recalls might seem like an odd couple, but as we gathered our data from the Energy Information Administration and the US Department of Transportation, we couldn't help but notice some smoldering patterns that begged to be explored.
Now, before we ignite the flames of curiosity further, let's take a moment to appreciate the sheer unpredictability of research. Like the whims of a mad scientist, our findings can often surprise us, challenging our assumptions and leading us down unexpected rabbit holes. And what could be more unexpected than finding a potential link between the gas-guzzling habits of a small island nation and the safety concerns of cars and trucks crisscrossing the highways? It's like discovering that your favorite childhood toys – a chemistry set and a toy car – have been secretly plotting to collaborate all along.
As we venture into this scorching hot topic, we invite you to grab your lab coat and join us in delving into the combustible world of data analysis. Strap in for a wild ride through the fiery realm of statistical significance and correlation coefficients that may just set your scientific heart ablaze. Our findings are sure to spark some lively discussions and perhaps even kindle a newfound appreciation for the unexpected connections that lurk beneath the surface of seemingly unrelated phenomena.
So, buckle up and get ready to explore the gas connection between fossil fuel use in Bahrain and automotive recalls. It's bound to be an exhilarating journey, filled with unexpected twists and turns – much like navigating rush hour traffic in a bustling metropolis.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Now, let's roll up our sleeves and dissect the juicy details of how we wrangled this data beast to uncover the blazing connection between fossil fuel use in Bahrain and automotive recalls. Our methodology was like a carefully orchestrated chemistry experiment, mixing together a concoction of data sources, statistical analyses, and a healthy sprinkle of skepticism to ensure we weren't just blowing smoke.

Data Collection:

We scoured the virtual sands of the internet, sifting through mountains of data to extract the golden nuggets of information on fossil fuel consumption in Bahrain and the total number of automotive recalls. The Energy Information Administration and the US Department of Transportation became our trusty companions in this quest, providing us with a treasure trove of historical data spanning the years 1980 to 2021. It was like panning for statistical gold, only instead of striking it rich, we struck correlations that set our scientific hearts ablaze.

Statistical Analysis:

With our data in hand, we flexed our statistical muscles, employing the classic Pearson correlation coefficient to measure the strength and direction of the relationship between fossil fuel use in Bahrain and automotive recalls. We also waltzed into the domain of p-values, assessing the significance of our findings with the same gusto as a scientist on a caffeine high.

Now, the statistical arts may seem like a mysterious potion brewed in the cauldron of academia, but fear not! We navigated these treacherous statistical waters with the agility of a swashbuckling pirate, ensuring that our results were not merely the product of statistical flukes or mirages in the desert of data.

To further solidify our findings, we performed additional sensitivity analyses and robustness checks, like a diligent chef tasting a dish repeatedly to ensure the flavors were just right. We adjusted for potential confounders and outliers, making sure our conclusions were as sturdy as a camel navigating the dunes of empirical scrutiny.

Ethical Considerations:

As responsible researchers, we handled our data with the care and attention of a bomb squad disarming a statistical minefield. We adhered to the highest standards of data ethics, ensuring the confidentiality and privacy of the information we used. No data points were harmed in the making of this research, and all statistical analyses were conducted with the well-being of our variables in mind.

In conclusion, our methodology was a concoction of data excavation, statistical acrobatics, and ethical fortitude, resulting in a robust exploration of the hot-blooded relationship between fossil fuel use in Bahrain and automotive recalls. With our methodological compass pointing true north, we set sail into uncharted statistical waters, unearthing correlations that lit a fire under our understanding of these seemingly disparate variables.

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 Fossil fuel use in Bahrain and Total number of automotive recalls. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and US DOT .

For the time period 1980 to 2021, you found a correlation 0.9671276, r-squared of 0.9353357, and p < 0.01.

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

Here is the title and abstract of the paper:
[[TITLE]]
Fueling the Fire: The Gas Connection Between Fossil Fuel Use in Bahrain and Automotive Recalls

[[ABSTRACT]]
As the old saying goes, "Where there's smoke, there's fire." In our case, where there's fossil fuel use in Bahrain, there seems to be a blazing correlation with the total number of automotive recalls. Our research team delved deep into this combustible topic, utilizing data from the Energy Information Administration and the US Department of Transportation. Through our rigorous analysis, we discovered a scorching correlation coefficient of 0.9671276 and a p-value less than 0.01 for the years 1980 to 2021. These findings suggest that there may indeed be sparks flying between fossil fuel consumption in Bahrain and the eruption of automotive recalls. The relationship between these variables is nothing short of incendiary, potentially igniting a need for further investigation into the intricacies of this connection. Join us as we fan the flames of curiosity and let the data kindle a new understanding of the fiery relationship between fossil fuel use and automotive recalls.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Fire up your engines, folks, because we're about to dive into a sizzling investigation that connects the burning issue of fossil fuel use in Bahrain to the heated world of automotive recalls. As researchers, we often find ourselves trekking into uncharted territory, armed with statistical tools and a healthy dose of curiosity. Our mission? To unravel the fiery relationship between these seemingly unrelated variables and shed light on whether there's more than meets the eye – or should we say, the exhaust pipe?
In the realm of data analysis, uncovering correlations can feel like stumbling upon hidden treasure, especially when the variables at play appear to be as distant as a desert oasis is from an ice rink. Fossil fuel consumption and automotive recalls might seem like an odd couple, but as we gathered our data from the Energy Information Administration and the US Department of Transportation, we couldn't help but notice some smoldering patterns that begged to be explored.
Now, before we ignite the flames of curiosity further, let's take a moment to appreciate the sheer unpredictability of research. Like the whims of a mad scientist, our findings can often surprise us, challenging our assumptions and leading us down unexpected rabbit holes. And what could be more unexpected than finding a potential link between the gas-guzzling habits of a small island nation and the safety concerns of cars and trucks crisscrossing the highways? It's like discovering that your favorite childhood toys – a chemistry set and a toy car – have been secretly plotting to collaborate all along.
As we venture into this scorching hot topic, we invite you to grab your lab coat and join us in delving into the combustible world of data analysis. Strap in for a wild ride through the fiery realm of statistical significance and correlation coefficients that may just set your scientific heart ablaze. Our findings are sure to spark some lively discussions and perhaps even kindle a newfound appreciation for the unexpected connections that lurk beneath the surface of seemingly unrelated phenomena.
So, buckle up and get ready to explore the gas connection between fossil fuel use in Bahrain and automotive recalls. It's bound to be an exhilarating journey, filled with unexpected twists and turns – much like navigating rush hour traffic in a bustling metropolis.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The sizzling saga of our research journey has led us to some truly illuminating findings. After meticulously analyzing the data from 1980 to 2021, we found a scorching correlation coefficient of 0.9671276 between fossil fuel use in Bahrain and the total number of automotive recalls. If that number doesn't raise the temperature in the room, I don't know what will! Our analysis also revealed an r-squared value of 0.9353357, indicating that a whopping 93.5% of the variation in automotive recalls can be explained by changes in fossil fuel use in Bahrain. It's as if the two variables are doing a fiery tango, each step perfectly in sync with the other.

Now, I know what you're thinking - "What's with all the heat metaphors?" Well, when it comes to uncovering such scorching statistical relationships, it's hard not to get carried away. The p-value less than 0.01 further fans the flames of significance, providing strong evidence that this connection is no mere flash in the pan. It's the real deal, folks – a red-hot link between fossil fuel consumption and the automotive world that demands our attention.

But enough with the numbers; let's talk about the visual proof. Behold, Fig. 1, a scatterplot that vividly illustrates the fiery correlation between these two variables. It's like watching a fiery dance unfold before your very eyes, with each data point adding fuel to the flames of our research conclusions.

In conclusion, our findings not only highlight the searing relationship between fossil fuel use in Bahrain and automotive recalls but also underscore the need for further investigation into the mechanisms driving this connection. The implications of this scorching correlation could have far-reaching effects on automotive safety and fuel consumption patterns. So, as we bask in the glow of these scintillating findings, let's not extinguish the flames of curiosity just yet. There's plenty more to uncover in this blazing relationship, and we're just getting started on our scientific journey through the heat of statistical 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 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 Fossil fuel use in Bahrain and Total number of automotive recalls. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
Fueling the Fire: The Gas Connection Between Fossil Fuel Use in Bahrain and Automotive Recalls

[[ABSTRACT]]
As the old saying goes, "Where there's smoke, there's fire." In our case, where there's fossil fuel use in Bahrain, there seems to be a blazing correlation with the total number of automotive recalls. Our research team delved deep into this combustible topic, utilizing data from the Energy Information Administration and the US Department of Transportation. Through our rigorous analysis, we discovered a scorching correlation coefficient of 0.9671276 and a p-value less than 0.01 for the years 1980 to 2021. These findings suggest that there may indeed be sparks flying between fossil fuel consumption in Bahrain and the eruption of automotive recalls. The relationship between these variables is nothing short of incendiary, potentially igniting a need for further investigation into the intricacies of this connection. Join us as we fan the flames of curiosity and let the data kindle a new understanding of the fiery relationship between fossil fuel use and automotive recalls.

[[LITERATURE REVIEW]]
The connection between fossil fuel use in Bahrain and automotive recalls has sparked interest in a wide range of academic and non-academic sources, shedding light on this unexpected relationship that seems to be fueling more than just cars. Smith and Doe (2015) provided an early examination of the potential link, highlighting the combustible nature of the topic and laying the groundwork for further investigation. Furthermore, Jones et al. (2018) delved into the fiery depths of this correlation, igniting discussions about the underlying mechanisms at play.
In "The Gas Chronicles" by Petroleum Politics, lorem and ipsum are presented, showcasing the dynamic interplay between fuel consumption and its impact on automotive safety. The authors reveal the unexpected twists and turns of this narrative, demonstrating how the story of fuel and recalls is far from running on fumes.
On the non-fiction front, works such as "The Burning Truth: Fossil Fuel Dilemma" by Climate Crisis Coalition and "Recalls Under the Hood: Unveiling Automotive Safety" by Vehicle Vigilance Foundation offer insightful perspectives on the broader context of fossil fuel use and automotive recalls. The fiery passion of these authors for unraveling the complexities of the automotive industry and its relationship with fuel consumption is truly ablaze.
Turning to the world of fiction, "The Inferno Drive" by Ignatius Camshaft and "Recall: A Tale of Flaming Fury" by Ember Sparks may not be scholarly treatises, but their thematic resonance with our research topic is undeniably captivating. The imaginative exploration of infernal themes in these works serves as a reminder that even the most fantastical tales can offer sparks of insight into our own fiery investigation.
In conducting this literature review, the authors also gathered data from an array of unconventional sources, including the backs of shampoo bottles, where the chemical compositions and safety precautions provided a surprisingly relevant perspective on the intersection of combustible elements and potential risks – a hair-raising connection, to say the least.
As we wade through this sea of literature, puns, and unexpected connections, it is clear that the discourse surrounding the relationship between fossil fuel use in Bahrain and automotive recalls is as varied and surprising as uncovering a hidden treasure trove in the desert sands.

[[RESULTS]]
The sizzling saga of our research journey has led us to some truly illuminating findings. After meticulously analyzing the data from 1980 to 2021, we found a scorching correlation coefficient of 0.9671276 between fossil fuel use in Bahrain and the total number of automotive recalls. If that number doesn't raise the temperature in the room, I don't know what will! Our analysis also revealed an r-squared value of 0.9353357, indicating that a whopping 93.5% of the variation in automotive recalls can be explained by changes in fossil fuel use in Bahrain. It's as if the two variables are doing a fiery tango, each step perfectly in sync with the other.
Now, I know what you're thinking - "What's with all the heat metaphors?" Well, when it comes to uncovering such scorching statistical relationships, it's hard not to get carried away. The p-value less than 0.01 further fans the flames of significance, providing strong evidence that this connection is no mere flash in the pan. It's the real deal, folks – a red-hot link between fossil fuel consumption and the automotive world that demands our attention.
But enough with the numbers; let's talk about the visual proof. Behold, Fig. 1, a scatterplot that vividly illustrates the fiery correlation between these two variables. It's like watching a fiery dance unfold before your very eyes, with each data point adding fuel to the flames of our research conclusions.
In conclusion, our findings not only highlight the searing relationship between fossil fuel use in Bahrain and automotive recalls but also underscore the need for further investigation into the mechanisms driving this connection. The implications of this scorching correlation could have far-reaching effects on automotive safety and fuel consumption patterns. So, as we bask in the glow of these scintillating findings, let's not extinguish the flames of curiosity just yet. There's plenty more to uncover in this blazing relationship, and we're just getting started on our scientific journey through the heat of statistical analysis.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Now that we've thrown caution to the wind and stoked the fires of scientific inquiry, it's time to delve into the smoldering depths of our scorching findings. Our results have not only added fuel to the existing literature on the connection between fossil fuel use in Bahrain and automotive recalls but have also set the stage for some hot debate.

Let's circle back to the sizzling elements of our literature review. The works of Smith and Doe (2015) and Jones et al. (2018) provided the initial sparks of interest in this fiery correlation, and our findings have fanned those flames into an inferno of statistical significance. The unexpected twists and turns outlined in "The Gas Chronicles" by Petroleum Politics have found validation in our research, fueling the notion that the narrative of fuel and recalls is far from running on fumes. As for our unconventional sources, even the backs of shampoo bottles have proven to be unexpectedly relevant, presenting a hair-raising connection that has now ignited into a blazing statistical reality.

Our scorching correlation coefficient and r-squared value have certainly set the scientific world ablaze, providing robust support for the notion that changes in fossil fuel use in Bahrain are closely intertwined with the eruption of automotive recalls. It's as if these data points are performing a fiery tango, and the p-value less than 0.01 is the applause that echoes through the statistical ballroom.

Now, let's address the elephant in the room – the sheer number of heat metaphors in our results section. It's hard to resist the temptation to spice up the discussion with a dash of flamboyant language when the findings themselves are ablaze with significance. So, as we waltz through the scalding dance of statistics, let's not extinguish the flames of enthusiasm just yet. It's clear that this scorching correlation holds the potential to spark further investigations into the intricate dynamics of automotive safety and fuel consumption patterns.

As we bask in the radiant glow of these findings, let's remember that this research is just the spark that ignites a much larger fire of inquiry. There's still plenty of uncharted territory in this blazing relationship, and we're eager to fuel the flames of curiosity as we continue to unravel the searing mysteries of this perhaps unexpectedly hot topic. After all, where there's statistical smoke, there's bound to be some fiery correlations waiting to be unearthed!

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 Fossil fuel use in Bahrain and Total number of automotive recalls. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
Fueling the Fire: The Gas Connection Between Fossil Fuel Use in Bahrain and Automotive Recalls

[[ABSTRACT]]
As the old saying goes, "Where there's smoke, there's fire." In our case, where there's fossil fuel use in Bahrain, there seems to be a blazing correlation with the total number of automotive recalls. Our research team delved deep into this combustible topic, utilizing data from the Energy Information Administration and the US Department of Transportation. Through our rigorous analysis, we discovered a scorching correlation coefficient of 0.9671276 and a p-value less than 0.01 for the years 1980 to 2021. These findings suggest that there may indeed be sparks flying between fossil fuel consumption in Bahrain and the eruption of automotive recalls. The relationship between these variables is nothing short of incendiary, potentially igniting a need for further investigation into the intricacies of this connection. Join us as we fan the flames of curiosity and let the data kindle a new understanding of the fiery relationship between fossil fuel use and automotive recalls.

[[INTRDUCTION]]
Fire up your engines, folks, because we're about to dive into a sizzling investigation that connects the burning issue of fossil fuel use in Bahrain to the heated world of automotive recalls. As researchers, we often find ourselves trekking into uncharted territory, armed with statistical tools and a healthy dose of curiosity. Our mission? To unravel the fiery relationship between these seemingly unrelated variables and shed light on whether there's more than meets the eye – or should we say, the exhaust pipe?
In the realm of data analysis, uncovering correlations can feel like stumbling upon hidden treasure, especially when the variables at play appear to be as distant as a desert oasis is from an ice rink. Fossil fuel consumption and automotive recalls might seem like an odd couple, but as we gathered our data from the Energy Information Administration and the US Department of Transportation, we couldn't help but notice some smoldering patterns that begged to be explored.
Now, before we ignite the flames of curiosity further, let's take a moment to appreciate the sheer unpredictability of research. Like the whims of a mad scientist, our findings can often surprise us, challenging our assumptions and leading us down unexpected rabbit holes. And what could be more unexpected than finding a potential link between the gas-guzzling habits of a small island nation and the safety concerns of cars and trucks crisscrossing the highways? It's like discovering that your favorite childhood toys – a chemistry set and a toy car – have been secretly plotting to collaborate all along.
As we venture into this scorching hot topic, we invite you to grab your lab coat and join us in delving into the combustible world of data analysis. Strap in for a wild ride through the fiery realm of statistical significance and correlation coefficients that may just set your scientific heart ablaze. Our findings are sure to spark some lively discussions and perhaps even kindle a newfound appreciation for the unexpected connections that lurk beneath the surface of seemingly unrelated phenomena.
So, buckle up and get ready to explore the gas connection between fossil fuel use in Bahrain and automotive recalls. It's bound to be an exhilarating journey, filled with unexpected twists and turns – much like navigating rush hour traffic in a bustling metropolis.

[[RESULTS]]
The sizzling saga of our research journey has led us to some truly illuminating findings. After meticulously analyzing the data from 1980 to 2021, we found a scorching correlation coefficient of 0.9671276 between fossil fuel use in Bahrain and the total number of automotive recalls. If that number doesn't raise the temperature in the room, I don't know what will! Our analysis also revealed an r-squared value of 0.9353357, indicating that a whopping 93.5% of the variation in automotive recalls can be explained by changes in fossil fuel use in Bahrain. It's as if the two variables are doing a fiery tango, each step perfectly in sync with the other.
Now, I know what you're thinking - "What's with all the heat metaphors?" Well, when it comes to uncovering such scorching statistical relationships, it's hard not to get carried away. The p-value less than 0.01 further fans the flames of significance, providing strong evidence that this connection is no mere flash in the pan. It's the real deal, folks – a red-hot link between fossil fuel consumption and the automotive world that demands our attention.
But enough with the numbers; let's talk about the visual proof. Behold, Fig. 1, a scatterplot that vividly illustrates the fiery correlation between these two variables. It's like watching a fiery dance unfold before your very eyes, with each data point adding fuel to the flames of our research conclusions.
In conclusion, our findings not only highlight the searing relationship between fossil fuel use in Bahrain and automotive recalls but also underscore the need for further investigation into the mechanisms driving this connection. The implications of this scorching correlation could have far-reaching effects on automotive safety and fuel consumption patterns. So, as we bask in the glow of these scintillating findings, let's not extinguish the flames of curiosity just yet. There's plenty more to uncover in this blazing relationship, and we're just getting started on our scientific journey through the heat of statistical analysis.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

Well, folks, it looks like we've fueled the flames of curiosity and found ourselves in quite a hot mess of statistical sizzle. The scorching correlation coefficient of 0.9671276 between fossil fuel use in Bahrain and the total number of automotive recalls has left us feeling like we're standing a little too close to a bonfire at a beach party. With an r-squared value of 0.9353357, it's as if these variables have been dancing cheek to cheek in a fiery tango that could rival any summer cookout.

But before we get too fired up, let's not forget the importance of keeping a cool head. While the numbers may be heating things up, we mustn't jump to conclusions quicker than a marshmallow over a campfire. Our p-value of less than 0.01 certainly adds some serious fuel to the research fire, indicating that this correlation is no mere fluke – it's the real deal, folks. It's got more heat than a jalapeño on a sunny day!

When we look at Fig. 1, it's like staring directly into the belly of a statistical volcano, witnessing the bubbling lava of correlation flow before our very eyes. It's a sight to behold, as if statistical significance decided to throw a beach party and invite all the data points for a fiery fiesta.

In conclusion, it's clear that there's a red-hot connection between fossil fuel use in Bahrain and automotive recalls that demands our attention. These findings are more lit than a lab experiment gone wrong, and they beckon us to keep the flames of investigation burning bright. However, at this point, it seems we've stoked the fire enough. There's no need for further research in this domain; it's hotter than a summer day in Bahrain, and we've already turned up the heat to the max.

So, let's toast to these scorching results and move on to cooler research pastures. After all, we don't want to play with fire for too long – unless we're roasting marshmallows!

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 Fueling the Fire: The Gas Connection Between Fossil Fuel Use in Bahrain and Automotive Recalls. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of Petroleum and Automotive Engineering

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 Fueling the Fire: The Gas Connection Between Fossil Fuel Use in Bahrain and Automotive Recalls. Respond only with the name of a fictional organization.

ChatGPT:

The Global Institute for Petroleum Research and Sustainability (GIPRS)

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 Fueling the Fire: The Gas Connection Between Fossil Fuel Use in Bahrain and Automotive Recalls with an abstract of As the old saying goes, "Where there's smoke, there's fire." In our case, where there's fossil fuel use in Bahrain, there seems to be a blazing correlation with the total number of automotive recalls. Our research team delved deep into this combustible topic, utilizing data from the Energy Information Administration and the US Department of Transportation. Through our rigorous analysis, we discovered a scorching correlation coefficient of 0.9671276 and a p-value less than 0.01 for the years 1980 to 2021. These findings suggest that there may indeed be sparks flying between fossil fuel consumption in Bahrain and the eruption of automotive recalls. The relationship between these variables is nothing short of incendiary, potentially igniting a need for further investigation into the intricacies of this connection. Join us as we fan the flames of curiosity and let the data kindle a new understanding of the fiery relationship between fossil fuel use and automotive recalls.

ChatGPT:

fossil fuel use Bahrain, automotive recalls, correlation coefficient, p-value, Energy Information Administration, US Department of Transportation, fossil fuel consumption, Bahrain, automotive industry, environmental impact, fuel-related issues

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

Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error

Data details

Fossil fuel use in Bahrain
Detailed data title: Total fossil fuel use in Bahrain in billion kWh
Source: Energy Information Administration
See what else correlates with Fossil fuel use in Bahrain

Total number of automotive recalls
Source: US DOT
See what else correlates with Total number of automotive recalls

Correlation r = 0.9671276 (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 = 0.9353357 (Coefficient of determination)
This means 93.5% of the change in the one variable (i.e., Total number of automotive recalls) is predictable based on the change in the other (i.e., Fossil fuel use in Bahrain) over the 42 years from 1980 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.1E-25.^Show 0.0000000000000000000000002115
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.97 in 2.1E-23% of random cases. Said differently, if you correlated 4,728,132,387,706,856,009,629,696 random variables^Note You don't actually need 4 septillion 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 41 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 41 because we have two variables measured over a period of 42 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.

[ 0.94, 0.98 ] 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	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Fossil fuel use in Bahrain (Billion kWh)	1.554	1.699	1.881	2.083	2.272	2.761	3.018	3.117	3.273	3.281	3.281	3.285	3.662	3.989	4.277	4.335	4.715	4.738	5.427	5.599	13.023	13.737	14.338	14.755	15.177	18.205	19.774	20.419	21.45	21.207	22.3946	22.8777	23.2885	24.361	25.6178	26.775	26.7994	27.4715	27.7732	31.435	29.8464	31.7566
Total number of automotive recalls (Recalls)	220	197	174	182	209	227	219	252	241	281	270	281	217	264	288	357	341	318	413	444	621	559	510	600	699	645	613	713	780	570	722	655	661	710	869	971	1031	897	1032	963	883	1093

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([1.554,1.699,1.881,2.083,2.272,2.761,3.018,3.117,3.273,3.281,3.281,3.285,3.662,3.989,4.277,4.335,4.715,4.738,5.427,5.599,13.023,13.737,14.338,14.755,15.177,18.205,19.774,20.419,21.45,21.207,22.3946,22.8777,23.2885,24.361,25.6178,26.775,26.7994,27.4715,27.7732,31.435,29.8464,31.7566,])
array_2 = np.array([220,197,174,182,209,227,219,252,241,281,270,281,217,264,288,357,341,318,413,444,621,559,510,600,699,645,613,713,780,570,722,655,661,710,869,971,1031,897,1032,963,883,1093,])
array_1_name = "Fossil fuel use in Bahrain"
array_2_name = "Total number of automotive recalls"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Fossil fuel use in Bahrain
Line chart for only Total number of automotive recalls
AI-generated correlation image
The spurious research paper: Fueling the Fire: The Gas Connection Between Fossil Fuel Use in Bahrain and Automotive Recalls

View another random correlation

How fun was this correlation?

You're the rating guru we've been waiting for!

Correlation ID: 3874 · Black Variable ID: 23489 · Red Variable ID: 1116


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