Spurious correlation #2,230 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Motor vehicle thefts and the second variable is Gasoline pumped in Austria. The chart goes from 1985 to 2022, 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 Motor vehicle thefts and the second variable is Gasoline pumped in Austria. The chart goes from 1985 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of motor vehicle thefts plummeted, experts noticed a surprising ripple effect in Austria's gasoline industry. It turns out that as fewer cars were being stolen, there was a decreased demand for gasoline on the black market. This led to an overall decrease in the amount of gasoline being pumped in Austria. Who knew that the key to managing gasoline production lay in reducing car thefts? It just goes to show that when it comes to fueling up, even the most unexpected factors can drive change.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image where the gas station in Austria is showcased as a neon-lit hub of activity, with vibrant cyberpunk aesthetics adding a futuristic twist. The thief can be depicted as a shadowy figure, blending seamlessly into the dark and moody environment, while the car and its oblivious driver stand out in stark contrast. The attendants and customers should be bustling with energy, and the scene should be bustling with dynamic cyber enhancements to give it a data cyber art style. 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: Motor vehicle thefts and Gasoline pumped in Austria. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Sci-fi fantacy Cutsy art illustration Woodblock painting inspired by bauhaus Data cyber art
ChatGPT: Data cyber art

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Motor vehicle thefts and Gasoline pumped in Austria together. Keep the description simple.
ChatGPT: At a bustling gas station in Austria, a thief is shown sneaking around a parked car, attempting to steal it while the driver is pumping gas. The gas station attendants are busy assisting customers, unaware of the theft about to occur.

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: [ Data cyber art ] and depicting this scene: At a bustling gas station in Austria, a thief is shown sneaking around a parked car, attempting to steal it while the driver is pumping gas. The gas station attendants are busy assisting customers, unaware of the theft about to occur. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image where the gas station in Austria is showcased as a neon-lit hub of activity, with vibrant cyberpunk aesthetics adding a futuristic twist. The thief can be depicted as a shadowy figure, blending seamlessly into the dark and moody environment, while the car and its oblivious driver stand out in stark contrast. The attendants and customers should be bustling with energy, and the scene should be bustling with dynamic cyber enhancements to give it a data cyber art style.

*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 a decrease in Motor vehicle thefts caused Gasoline pumped in Austria to decrease.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Fueling the Fire: The Gas-Tly Connection Between Motor Vehicle Thefts and Gasoline Pumped in Austria

The Journal of Misdemeanor Mechanics

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 Motor vehicle thefts and Gasoline pumped in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
Fueling the Fire: The Gas-Tly Connection Between Motor Vehicle Thefts and Gasoline Pumped in Austria

[[ABSTRACT]]
The relationship between motor vehicle thefts and the fuel that powers them has been a hot topic of debate among researchers and law enforcement agencies alike. In this study, we delve into the Austrian landscape to uncover the long-speculated connection between gasoline consumption and the incidence of motor vehicle thefts. The findings of our research shed light on this intriguing relationship and provide valuable insights for policymakers and law enforcement agencies.

Drawing on data from the FBI Criminal Justice Information Services and the Energy Information Administration, we conducted a comprehensive analysis covering the period from 1985 to 2022. Our results revealed a remarkably strong correlation coefficient of 0.9501447 and a statistically significant p-value of less than 0.01, indicating a robust association between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria.

Now, onto the dad joke to fuel your laughter - Why don't thieves like to steal from gas stations? They're afraid of getting caught fuel-handed! This correlation study may seem gasp-worthy, but it's grounded in sound statistical analysis. Our findings suggest that there is merit in further exploring the potential mechanisms that underlie this intriguing association, which could potentially inform targeted interventions to curb motor vehicle thefts.

In conclusion, our research provides compelling evidence of the gas-tly connection between gasoline consumption and motor vehicle thefts in Austria, offering valuable insights for law enforcement strategies and emphasizing the importance of considering fuel-related factors in addressing this challenging issue.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Motor vehicle theft is a pervasive issue that continues to fuel concerns among law enforcement agencies and policymakers worldwide. In Austria, the incidence of motor vehicle thefts has prompted a quest for a deeper understanding of the factors that drive this criminal activity. As researchers, we couldn't resist diving into this investigation, fueled by the idea that gasoline consumption might be more than just a fuel for vehicles – it could also be fueling the fire of motor vehicle thefts.
Speaking of fueling the fire, here's a dad joke to ignite your sense of humor: Why did the car thief take a bath? Because he wanted to make a clean getaway! Now, back to our study on the gas-tly connection between motor vehicle thefts and gasoline pumped in Austria.
This study aims to explore the potential association between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria. While the idea of a connection between gasoline consumption and theft may seem like a stretch, our findings are no mere fumes of speculation. In fact, they are grounded in a robust statistical analysis that will drive home the significance of this correlation.
Now, let's get serious for a moment. Our research is not just about huffing and puffing about correlations; it aims to provide actionable insights for law enforcement and policy-making. By uncovering the factors that stoke the flames of motor vehicle thefts, we hope to spark discussions on targeted interventions and ignition of effective strategies to curb this criminal activity.
Before we rev up and accelerate into the discussion of our research findings, here's another dad joke to fuel your laughter: What do you call a stolen Tesla? An Edison! Now, let's rev those engines and delve into the gas-tly connection between motor vehicle thefts and gasoline pumped in Austria.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The relationship between motor vehicle thefts and the fuel that powers them is a topic that has garnered attention from researchers and law enforcement agencies alike. In "Smith and Doe's" study, the authors find revolutionary data connecting the increase in gasoline consumption to a rise in motor vehicle thefts. The dynamics of this relationship have often been overlooked, with the focus primarily placed on traditional theft deterrents. However, could the very fuel that propels vehicles also play a role in propelling the incidence of thefts? Our study aims to delve into this intriguing conundrum.

As we delve into this enigmatic correlation, it's important to tread carefully through the data, ensuring we don't step on any statistical landmines. Speaking of which, why do thieves prefer to steal automobiles under cover of darkness? Because they don't want to be spotted by anyone with a light bulb for a witness! Now, back to our serious investigation into the gas-tly connection between gasoline consumption and motor vehicle thefts in Austria.

In "Jones's" comprehensive review, the authors explore the impact of fuel consumption on criminal behaviors, shedding light on the potential ramifications of unchecked gasoline usage. The investigation brings forth compelling evidence that challenges traditional perspectives on halting motor vehicle thefts. Could it be that the driving force behind these thefts is, quite literally, the fuel itself? Our study ventures into uncharted territory to unravel this enigma, with a fuel for thought that just might ignite a paradigm shift in addressing this societal challenge.

Moving beyond academia, let's fuel our literature review with relevant non-fiction books such as "The Big Book of Car Crimes" and "Fueling the Flames: Understanding the Relationship Between Gasoline and Crime." These publications shed light on the intricate interplay between fuel consumption and criminal activities, providing a comprehensive backdrop for our investigation. Now, let's rev up for a pun-tastic ride through some relevant fiction books such as "The Great Gatsby Gets Gas" and "Pump Fiction: Tales of Fuel and Felony." These imaginative titles add a layer of whimsy to our serious investigation, showing that even literature enjoys a good play on words.

Cruising through the world of cartoons, it's hard to overlook the relevance of shows like "Wacky Races" and "Speed Racer," where fuel-powered vehicles take center stage in thrilling escapades. Additionally, the iconic "Scooby-Doo" series often features mysteries involving motor vehicles, offering light-hearted yet insightful narratives that mirror certain aspects of our research. And let's not forget the high-octane action in "The Fast and the Furious" film series, where the allure of powerful engines and high-stakes thefts takes center stage, adding a dash of Hollywood glamour to our academic investigation.

As we transition from the serious to the lighthearted, it's crucial to maintain a balanced approach to our literature review, ensuring that we fuel both the intellectual and comedic facets of our research. And speaking of fuel, why did the thief pour gasoline on himself? He wanted to make a clean getaway! Now, back to our scholarly exploration of the gas-tly connection between motor vehicle thefts and gasoline pumped in Austria.

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 Motor vehicle thefts and Gasoline pumped in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Your research team collected data from all across the internet, but mostly just used information from FBI Criminal Justice Information Services and Energy Information Administration . You used data from 1985 to 2022

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-Tly Connection Between Motor Vehicle Thefts and Gasoline Pumped in Austria

[[ABSTRACT]]
The relationship between motor vehicle thefts and the fuel that powers them has been a hot topic of debate among researchers and law enforcement agencies alike. In this study, we delve into the Austrian landscape to uncover the long-speculated connection between gasoline consumption and the incidence of motor vehicle thefts. The findings of our research shed light on this intriguing relationship and provide valuable insights for policymakers and law enforcement agencies.

Drawing on data from the FBI Criminal Justice Information Services and the Energy Information Administration, we conducted a comprehensive analysis covering the period from 1985 to 2022. Our results revealed a remarkably strong correlation coefficient of 0.9501447 and a statistically significant p-value of less than 0.01, indicating a robust association between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria.

Now, onto the dad joke to fuel your laughter - Why don't thieves like to steal from gas stations? They're afraid of getting caught fuel-handed! This correlation study may seem gasp-worthy, but it's grounded in sound statistical analysis. Our findings suggest that there is merit in further exploring the potential mechanisms that underlie this intriguing association, which could potentially inform targeted interventions to curb motor vehicle thefts.

In conclusion, our research provides compelling evidence of the gas-tly connection between gasoline consumption and motor vehicle thefts in Austria, offering valuable insights for law enforcement strategies and emphasizing the importance of considering fuel-related factors in addressing this challenging issue.

[[INTRODUCTION]]
Motor vehicle theft is a pervasive issue that continues to fuel concerns among law enforcement agencies and policymakers worldwide. In Austria, the incidence of motor vehicle thefts has prompted a quest for a deeper understanding of the factors that drive this criminal activity. As researchers, we couldn't resist diving into this investigation, fueled by the idea that gasoline consumption might be more than just a fuel for vehicles – it could also be fueling the fire of motor vehicle thefts.
Speaking of fueling the fire, here's a dad joke to ignite your sense of humor: Why did the car thief take a bath? Because he wanted to make a clean getaway! Now, back to our study on the gas-tly connection between motor vehicle thefts and gasoline pumped in Austria.
This study aims to explore the potential association between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria. While the idea of a connection between gasoline consumption and theft may seem like a stretch, our findings are no mere fumes of speculation. In fact, they are grounded in a robust statistical analysis that will drive home the significance of this correlation.
Now, let's get serious for a moment. Our research is not just about huffing and puffing about correlations; it aims to provide actionable insights for law enforcement and policy-making. By uncovering the factors that stoke the flames of motor vehicle thefts, we hope to spark discussions on targeted interventions and ignition of effective strategies to curb this criminal activity.
Before we rev up and accelerate into the discussion of our research findings, here's another dad joke to fuel your laughter: What do you call a stolen Tesla? An Edison! Now, let's rev those engines and delve into the gas-tly connection between motor vehicle thefts and gasoline pumped in Austria.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

In this study, we employed a hybrid approach that blended traditional statistical analysis with a touch of whimsy and a sprinkle of puns. Our data collection involved harnessing the power of the internet and navigating through a labyrinth of websites, databases, and digital archives to unearth the relevant information. While it felt like embarking on a virtual treasure hunt, our diligence in sifting through data sources eventually paid off – much like finding the elusive "golden gallon" of gasoline.

To quantify the amount of gasoline pumped, we tapped into the reservoir of data provided by the Energy Information Administration (EIA). We explored a multitude of datasets, dissecting the voluminous records of gasoline consumption with the precision of a mechanic examining an intricate engine. By meticulously parsing through the numbers, we aimed to capture the ebbs and flows of gasoline usage, without getting too gassed out in the process.

As for the motor vehicle theft data, we delved into the repository of crime statistics offered by the FBI Criminal Justice Information Services, navigating through the digital landscape like intrepid explorers seeking to decode the secrets of criminal activity. We meticulously combed through the voluminous records of stolen vehicles, recognizing that understanding theft patterns requires more than just a fleeting glance - it demands a thorough and methodical inventory, not unlike counting the myriad spark plugs in an engine.

Next, we engaged in a meticulous process of data cleaning and wrangling, much akin to tuning a finely crafted engine to achieve optimal performance. We sifted through the data with the precision of a master mechanic, discarding any outliers and anomalies with the same expediency as removing a faulty spark plug from an engine. Our goal was to ensure that the data we harnessed harmonized seamlessly, like the synchronized pistons in a well-oiled motor.

To estimate the strength and direction of the relationship between gasoline consumption and motor vehicle thefts, we employed advanced statistical tools such as correlation analysis and regression modeling. We meticulously crunched the numbers, not unlike an expert mechanic meticulously tuning an engine to optimize its performance, to unveil the intricate patterns that underscore the gas-tly connection between these variables.

Lastly, we conducted a sensitivity analysis to scrutinize the robustness of our findings, much like subjecting an experimental prototype vehicle to a battery of rigorous tests to ensure its resilience in diverse conditions. This meticulous scrutiny allowed us to gauge the reliability and stability of our results, ensuring that they revved up to meet the stringent standards of statistical rigor.

Though the road we traveled was not without its twists and turns, we arrived at our destination - unraveling the nuanced relationship between gasoline consumption and motor vehicle thefts, akin to a thrilling journey through the winding paths of statistical exploration.

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 Motor vehicle thefts and Gasoline pumped in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
Fueling the Fire: The Gas-Tly Connection Between Motor Vehicle Thefts and Gasoline Pumped in Austria

[[ABSTRACT]]
The relationship between motor vehicle thefts and the fuel that powers them has been a hot topic of debate among researchers and law enforcement agencies alike. In this study, we delve into the Austrian landscape to uncover the long-speculated connection between gasoline consumption and the incidence of motor vehicle thefts. The findings of our research shed light on this intriguing relationship and provide valuable insights for policymakers and law enforcement agencies.

Drawing on data from the FBI Criminal Justice Information Services and the Energy Information Administration, we conducted a comprehensive analysis covering the period from 1985 to 2022. Our results revealed a remarkably strong correlation coefficient of 0.9501447 and a statistically significant p-value of less than 0.01, indicating a robust association between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria.

Now, onto the dad joke to fuel your laughter - Why don't thieves like to steal from gas stations? They're afraid of getting caught fuel-handed! This correlation study may seem gasp-worthy, but it's grounded in sound statistical analysis. Our findings suggest that there is merit in further exploring the potential mechanisms that underlie this intriguing association, which could potentially inform targeted interventions to curb motor vehicle thefts.

In conclusion, our research provides compelling evidence of the gas-tly connection between gasoline consumption and motor vehicle thefts in Austria, offering valuable insights for law enforcement strategies and emphasizing the importance of considering fuel-related factors in addressing this challenging issue.

[[LITERATURE REVIEW]]
The relationship between motor vehicle thefts and the fuel that powers them is a topic that has garnered attention from researchers and law enforcement agencies alike. In "Smith and Doe's" study, the authors find revolutionary data connecting the increase in gasoline consumption to a rise in motor vehicle thefts. The dynamics of this relationship have often been overlooked, with the focus primarily placed on traditional theft deterrents. However, could the very fuel that propels vehicles also play a role in propelling the incidence of thefts? Our study aims to delve into this intriguing conundrum.
As we delve into this enigmatic correlation, it's important to tread carefully through the data, ensuring we don't step on any statistical landmines. Speaking of which, why do thieves prefer to steal automobiles under cover of darkness? Because they don't want to be spotted by anyone with a light bulb for a witness! Now, back to our serious investigation into the gas-tly connection between gasoline consumption and motor vehicle thefts in Austria.
In "Jones's" comprehensive review, the authors explore the impact of fuel consumption on criminal behaviors, shedding light on the potential ramifications of unchecked gasoline usage. The investigation brings forth compelling evidence that challenges traditional perspectives on halting motor vehicle thefts. Could it be that the driving force behind these thefts is, quite literally, the fuel itself? Our study ventures into uncharted territory to unravel this enigma, with a fuel for thought that just might ignite a paradigm shift in addressing this societal challenge.
Moving beyond academia, let's fuel our literature review with relevant non-fiction books such as "The Big Book of Car Crimes" and "Fueling the Flames: Understanding the Relationship Between Gasoline and Crime." These publications shed light on the intricate interplay between fuel consumption and criminal activities, providing a comprehensive backdrop for our investigation. Now, let's rev up for a pun-tastic ride through some relevant fiction books such as "The Great Gatsby Gets Gas" and "Pump Fiction: Tales of Fuel and Felony." These imaginative titles add a layer of whimsy to our serious investigation, showing that even literature enjoys a good play on words.
Cruising through the world of cartoons, it's hard to overlook the relevance of shows like "Wacky Races" and "Speed Racer," where fuel-powered vehicles take center stage in thrilling escapades. Additionally, the iconic "Scooby-Doo" series often features mysteries involving motor vehicles, offering light-hearted yet insightful narratives that mirror certain aspects of our research. And let's not forget the high-octane action in "The Fast and the Furious" film series, where the allure of powerful engines and high-stakes thefts takes center stage, adding a dash of Hollywood glamour to our academic investigation.
As we transition from the serious to the lighthearted, it's crucial to maintain a balanced approach to our literature review, ensuring that we fuel both the intellectual and comedic facets of our research. And speaking of fuel, why did the thief pour gasoline on himself? He wanted to make a clean getaway! Now, back to our scholarly exploration of the gas-tly connection between motor vehicle thefts and gasoline pumped in Austria.

[[RESULTS]]
The analysis of the data obtained from the FBI Criminal Justice Information Services and Energy Information Administration revealed a striking correlation coefficient of 0.9501447 between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria. This strong correlation suggests that there is indeed a gas-tly connection between the two variables, lending credence to the idea that gasoline consumption may play a significant role in fueling the incidence of motor vehicle thefts.
Now, let's pump the brakes for a moment and appreciate the gravity of this correlation. It's no small feat to uncover such a strong association, and it certainly revs up our excitement for further exploration of this intriguing phenomenon.
The r-squared value of 0.9027749 further elucidates the robustness of this relationship, indicating that over 90% of the variability in motor vehicle thefts can be explained by the amount of gasoline pumped. That's a remarkably high proportion, highlighting the substantial influence of gasoline consumption on the incidence of motor vehicle thefts.
Fig. 1 (to be included) provides a visual representation of this remarkable correlation, showcasing how gasoline consumption and motor vehicle thefts align with remarkable precision. It's almost as if they were two peas in a pod, or in this case, two fuels in a tank!
In essence, our findings suggest that there is more to the relationship between gasoline consumption and motor vehicle thefts than meets the eye. While some may consider this correlation a mere gas-tronomical coincidence, our statistically significant p-value of less than 0.01 speaks volumes about the validity of this association.
Now, for a little fuel for thought – Why did the car thief install a skylight? He wanted to see a car-jacked!
In summary, our research has uncovered a compelling link between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria, paving the way for further investigation into the mechanisms and potential interventions related to this gas-tly connection.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of our study are unequivocal in demonstrating a robust correlation between gasoline consumption and motor vehicle thefts in Austria. These results provide substantial support for prior research, including the pioneering work of Smith and Doe, who first hinted at the intriguing connection between gasoline consumption and the incidence of motor vehicle thefts. Their laborious investigations piqued our curiosity and ignited a spark of inspiration, fueling our determination to delve into this gas-tly correlation. It's safe to say that their work laid the groundwork for our own ignition into the matter at hand.

The statistically significant correlation coefficient of 0.9501447, along with the r-squared value of 0.9027749, closely mirrors the findings of previous researchers and further reinforces the notion that the amount of gasoline pumped indeed serves as a key determinant of motor vehicle thefts. This aligns with Jones's comprehensive review, which underscored the potential influence of unchecked gasoline usage on criminal activities, offering a fuel for thought that our study has since ignited into a fiery inferno of academic inquiry.

In tandem with the prior literature, we have successfully added fuel to the fire of understanding regarding the driving forces behind motor vehicle thefts. Our study expands upon existing research, shedding light on the magnitude of the association and highlighting the pressing need for targeted interventions that consider the role of gasoline consumption in the dynamics of motor vehicle thefts.

Our results not only affirm the gas-tly connection between gasoline consumption and motor vehicle thefts but also provide a visual representation in Fig. 1, akin to two gears in perfect synchrony, or in this case, two wheels in a daring getaway. The alignment between gasoline consumption and motor vehicle thefts displayed remarkable precision, akin to a well-oiled engine running smoothly towards a paradigm-altering realization.

While some may consider this correlation a mere gas-tronomical coincidence, we urge the academic and law enforcement communities to recognize the depth and significance of this association. It is imperative to drive forward with further investigations to unravel the intricate mechanisms underpinning this correlation, with a determination to spark innovative interventions that hold the potential to put the brakes on motor vehicle thefts in Austria and beyond.

And now, for a little fuel for thought – Why don't thieves like to steal from gas stations at night? Because the steaks are too high! This gas-tly connection may seem riddled with puns, but the significance of our findings cannot be slighted in any way, shape, or form.

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 Motor vehicle thefts and Gasoline pumped in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Fueling the Fire: The Gas-Tly Connection Between Motor Vehicle Thefts and Gasoline Pumped in Austria

[[ABSTRACT]]
The relationship between motor vehicle thefts and the fuel that powers them has been a hot topic of debate among researchers and law enforcement agencies alike. In this study, we delve into the Austrian landscape to uncover the long-speculated connection between gasoline consumption and the incidence of motor vehicle thefts. The findings of our research shed light on this intriguing relationship and provide valuable insights for policymakers and law enforcement agencies.

Drawing on data from the FBI Criminal Justice Information Services and the Energy Information Administration, we conducted a comprehensive analysis covering the period from 1985 to 2022. Our results revealed a remarkably strong correlation coefficient of 0.9501447 and a statistically significant p-value of less than 0.01, indicating a robust association between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria.

Now, onto the dad joke to fuel your laughter - Why don't thieves like to steal from gas stations? They're afraid of getting caught fuel-handed! This correlation study may seem gasp-worthy, but it's grounded in sound statistical analysis. Our findings suggest that there is merit in further exploring the potential mechanisms that underlie this intriguing association, which could potentially inform targeted interventions to curb motor vehicle thefts.

In conclusion, our research provides compelling evidence of the gas-tly connection between gasoline consumption and motor vehicle thefts in Austria, offering valuable insights for law enforcement strategies and emphasizing the importance of considering fuel-related factors in addressing this challenging issue.

[[INTRDUCTION]]
Motor vehicle theft is a pervasive issue that continues to fuel concerns among law enforcement agencies and policymakers worldwide. In Austria, the incidence of motor vehicle thefts has prompted a quest for a deeper understanding of the factors that drive this criminal activity. As researchers, we couldn't resist diving into this investigation, fueled by the idea that gasoline consumption might be more than just a fuel for vehicles – it could also be fueling the fire of motor vehicle thefts.
Speaking of fueling the fire, here's a dad joke to ignite your sense of humor: Why did the car thief take a bath? Because he wanted to make a clean getaway! Now, back to our study on the gas-tly connection between motor vehicle thefts and gasoline pumped in Austria.
This study aims to explore the potential association between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria. While the idea of a connection between gasoline consumption and theft may seem like a stretch, our findings are no mere fumes of speculation. In fact, they are grounded in a robust statistical analysis that will drive home the significance of this correlation.
Now, let's get serious for a moment. Our research is not just about huffing and puffing about correlations; it aims to provide actionable insights for law enforcement and policy-making. By uncovering the factors that stoke the flames of motor vehicle thefts, we hope to spark discussions on targeted interventions and ignition of effective strategies to curb this criminal activity.
Before we rev up and accelerate into the discussion of our research findings, here's another dad joke to fuel your laughter: What do you call a stolen Tesla? An Edison! Now, let's rev those engines and delve into the gas-tly connection between motor vehicle thefts and gasoline pumped in Austria.

[[RESULTS]]
The analysis of the data obtained from the FBI Criminal Justice Information Services and Energy Information Administration revealed a striking correlation coefficient of 0.9501447 between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria. This strong correlation suggests that there is indeed a gas-tly connection between the two variables, lending credence to the idea that gasoline consumption may play a significant role in fueling the incidence of motor vehicle thefts.
Now, let's pump the brakes for a moment and appreciate the gravity of this correlation. It's no small feat to uncover such a strong association, and it certainly revs up our excitement for further exploration of this intriguing phenomenon.
The r-squared value of 0.9027749 further elucidates the robustness of this relationship, indicating that over 90% of the variability in motor vehicle thefts can be explained by the amount of gasoline pumped. That's a remarkably high proportion, highlighting the substantial influence of gasoline consumption on the incidence of motor vehicle thefts.
Fig. 1 (to be included) provides a visual representation of this remarkable correlation, showcasing how gasoline consumption and motor vehicle thefts align with remarkable precision. It's almost as if they were two peas in a pod, or in this case, two fuels in a tank!
In essence, our findings suggest that there is more to the relationship between gasoline consumption and motor vehicle thefts than meets the eye. While some may consider this correlation a mere gas-tronomical coincidence, our statistically significant p-value of less than 0.01 speaks volumes about the validity of this association.
Now, for a little fuel for thought – Why did the car thief install a skylight? He wanted to see a car-jacked!
In summary, our research has uncovered a compelling link between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria, paving the way for further investigation into the mechanisms and potential interventions related to this gas-tly connection.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has filled up the tank of knowledge by establishing a robust and significant correlation between gasoline consumption and motor vehicle thefts in Austria. This finding has ignited a spark of interest in exploring the mechanisms underlying this gas-tly connection and devising targeted strategies to put the brakes on motor vehicle thefts.

As we refuel our understanding of this phenomenon, it's essential to acknowledge the potential implications of our findings. This correlation isn't just a pit stop in the realm of criminology and energy analysis; it's a roadmap for law enforcement agencies and policymakers to navigate towards more effective interventions.

Now, for one last dad joke to drive home the point: Why do thieves prefer to steal Honda Civics? Because they know they can make a quick getaway and blend in with the traffic – it's a steal-thy approach!

Given the compelling nature of our findings and the future directions they suggest, it's safe to say that no more research is needed in this area. Our work has already fueled the bonfire of knowledge and shed light on the gas-tly connection between gasoline pumped and motor vehicle thefts in Austria. It's time to put the pedal to the metal and implement strategies to put this correlation in the rear-view mirror for good.

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-Tly Connection Between Motor Vehicle Thefts and Gasoline Pumped in Austria. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Misdemeanor Mechanics

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-Tly Connection Between Motor Vehicle Thefts and Gasoline Pumped in Austria. Respond only with the name of a fictional organization.

ChatGPT:

The International Association for the Study of Vehicular Mischief (IASVM)

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-Tly Connection Between Motor Vehicle Thefts and Gasoline Pumped in Austria with an abstract of The relationship between motor vehicle thefts and the fuel that powers them has been a hot topic of debate among researchers and law enforcement agencies alike. In this study, we delve into the Austrian landscape to uncover the long-speculated connection between gasoline consumption and the incidence of motor vehicle thefts. The findings of our research shed light on this intriguing relationship and provide valuable insights for policymakers and law enforcement agencies.
Drawing on data from the FBI Criminal Justice Information Services and the Energy Information Administration, we conducted a comprehensive analysis covering the period from 1985 to 2022. Our results revealed a remarkably strong correlation coefficient of 0.9501447 and a statistically significant p-value of less than 0.01, indicating a robust association between the amount of gasoline pumped and the incidence of motor vehicle thefts in Austria.
Now, onto the dad joke to fuel your laughter - Why don't thieves like to steal from gas stations? They're afraid of getting caught fuel-handed! This correlation study may seem gasp-worthy, but it's grounded in sound statistical analysis. Our findings suggest that there is merit in further exploring the potential mechanisms that underlie this intriguing association, which could potentially inform targeted interventions to curb motor vehicle thefts.
In conclusion, our research provides compelling evidence of the gas-tly connection between gasoline consumption and motor vehicle thefts in Austria, offering valuable insights for law enforcement strategies and emphasizing the importance of considering fuel-related factors in addressing this challenging issue.

ChatGPT:

fuel consumption, motor vehicle thefts, Austria, gasoline pump data, correlation study, statistical analysis, FBI Criminal Justice Information Services, Energy Information Administration, law enforcement strategies

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

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Data details

Motor vehicle thefts
Detailed data title: The motor vehicle theft rate per 100,000 residents in United States
Source: FBI Criminal Justice Information Services
See what else correlates with Motor vehicle thefts

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

Correlation r = 0.9501447 (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 = 0.9027749 (Coefficient of determination)
This means 90.3% of the change in the one variable (i.e., Gasoline pumped in Austria) is predictable based on the change in the other (i.e., Motor vehicle thefts) over the 38 years from 1985 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 8.4E-20.^Show 0.0000000000000000000835170243
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 8.4E-18% of random cases. Said differently, if you correlated 11,973,606,679,374,950,400 random variables^Note You don't actually need 11 quintillion 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 37 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 37 because we have two variables measured over a period of 38 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.

[ 0.91, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	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	2022
Motor vehicle thefts (Motor Vehicle Theft rate)	463.5	509.8	531.9	586.1	634	655.8	659	631.6	606.3	591.3	560.3	525.7	505.7	459.9	422.5	412.2	430.5	432.9	433.7	421.5	416.8	400.2	364.9	315.4	259.2	239.1	230	230.4	221.3	215.4	222.2	237.3	237.7	230.2	220.8	246	255.9	282.7
Gasoline pumped in Austria (Million Barrels/Day)	56.2521	57.0192	57.9616	59.1011	60.0959	59.0603	64.611	61.8005	59.4959	57.4356	55.3973	51.2514	48.7342	51.0247	47.5753	45.735	46.074	49.6575	50.8356	49.8661	48.7726	46.1178	45.5151	43.9781	43.2247	42.9068	39.8027	39.5984	38.5534	37.5699	37.9781	37.8087	37.4767	38.389	38.1973	31.8306	33.3425	34.7233

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([463.5,509.8,531.9,586.1,634,655.8,659,631.6,606.3,591.3,560.3,525.7,505.7,459.9,422.5,412.2,430.5,432.9,433.7,421.5,416.8,400.2,364.9,315.4,259.2,239.1,230,230.4,221.3,215.4,222.2,237.3,237.7,230.2,220.8,246,255.9,282.7,])
array_2 = np.array([56.2521,57.0192,57.9616,59.1011,60.0959,59.0603,64.611,61.8005,59.4959,57.4356,55.3973,51.2514,48.7342,51.0247,47.5753,45.735,46.074,49.6575,50.8356,49.8661,48.7726,46.1178,45.5151,43.9781,43.2247,42.9068,39.8027,39.5984,38.5534,37.5699,37.9781,37.8087,37.4767,38.389,38.1973,31.8306,33.3425,34.7233,])
array_1_name = "Motor vehicle thefts"
array_2_name = "Gasoline pumped in Austria"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Motor vehicle thefts
Line chart for only Gasoline pumped in Austria
AI-generated correlation image
The spurious research paper: Fueling the Fire: The Gas-Tly Connection Between Motor Vehicle Thefts and Gasoline Pumped in Austria

View another random correlation

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Correlation ID: 2230 · Black Variable ID: 20137 · Red Variable ID: 24162


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