Spurious correlation #1,643 · 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 in Kansas and the second variable is The number of couriers and messengers in Kansas. The chart goes from 2003 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 in Kansas and the second variable is The number of couriers and messengers in Kansas. The chart goes from 2003 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The decrease in motor vehicle thefts in Kansas led to a decrease in the number of couriers and messengers because, without stolen cars to deliver, the demand for their speedy services hit a roadblock. It seems the thieves couldn't keep the engines running for this particular profession's growth, putting the brakes on their job opportunities! It's a case of 'car-ma' for the couriers, as the stolen vehicle shortage shifted their career paths in a different direction. Looks like in this comedy of errors, the auto thieves unintentionally drove the courier business to a screeching halt!

^{Show image generation prompt} Model: dalle-3
Prompt: An image that looks like it is a scene from 'Star Wars', depicting a bustling town in Kansas where couriers and messengers deliver packages and letters on bicycles and scooters, weaving through the streets. In the distance, a group of people gather around a parked landspeeder, which has been broken into, highlighting the issue of vehicle thefts in the state. 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 in Kansas and The number of couriers and messengers in Kansas. 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: Surrealism An image that looks like it is a scene from 'Star Wars' Parallax art Cubism 3D Pixar Style
ChatGPT: An image that looks like it is a scene from 'Star Wars'

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 in Kansas and The number of couriers and messengers in Kansas together. Keep the description simple.
ChatGPT: In a bustling town in Kansas, a line of couriers and messengers deliver packages and letters on bicycles and scooters, weaving through the streets. In the distance, a group of people gather around a parked car, which has been broken into, emphasizing the issue of motor vehicle thefts in the state.

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: [ An image that looks like it is a scene from 'Star Wars' ] and depicting this scene: In a bustling town in Kansas, a line of couriers and messengers deliver packages and letters on bicycles and scooters, weaving through the streets. In the distance, a group of people gather around a parked car, which has been broken into, emphasizing the issue of motor vehicle thefts in the state. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: An image that looks like it is a scene from 'Star Wars', depicting a bustling town in Kansas where couriers and messengers deliver packages and letters on bicycles and scooters, weaving through the streets. In the distance, a group of people gather around a parked landspeeder, which has been broken into, highlighting the issue of vehicle thefts in the state.

*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 in Kansas caused The number of couriers and messengers in Kansas to decrease. Include one good pun.

AI academic paper

(Because p < 0.01)

Breaking and Delivering: A Wacky Correlation Between Motor Vehicle Thefts and Couriers in Kansas

The Journal of Eccentric Sociological Studies

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Motor vehicle thefts in Kansas and The number of couriers and messengers in Kansas. 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 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]]
Breaking and Delivering: A Wacky Correlation Between Motor Vehicle Thefts and Couriers in Kansas

[[ABSTRACT]]
The relationship between motor vehicle thefts and the number of couriers and messengers in Kansas has long been a source of curiosity in both law enforcement and delivery service circles. This study delves into the connection, employing data from the FBI Criminal Justice Information Services and the Bureau of Labor Statistics. Our findings revealed a rather surprising correlation coefficient of 0.8666944 with a statistically significant p-value of less than 0.01 for the years spanning from 2003 to 2022.

In delving into this unlikely relationship, we found that as the number of couriers and messengers in Kansas increases, so too does the incidence of motor vehicle thefts. It appears that the presence of delivery personnel may inadvertently provide more opportunities for motor vehicle theft, possibly due to the frequent coming and going of vehicles in areas served by couriers. It's like the thieves are saying, "Special delivery!"

Our results pose intriguing questions for future research, as well as practical implications for law enforcement and delivery service companies. While the findings may seem perplexing at first, they shed light on the interconnectedness of seemingly disparate aspects of society. Now, if we could only figure out a way to deliver justice to those pesky car thieves!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
When it comes to exploring the relationship between seemingly unrelated variables, researchers often find themselves in a maze of correlations and causations, hoping to uncover hidden patterns and connections. In the realm of criminology and labor economics, one might not immediately think that motor vehicle thefts and the number of couriers and messengers in Kansas would have anything in common. However, as this paper delves into their peculiar relationship, we find ourselves on the winding road of statistical discovery, where the unexpected becomes the norm and the mundane becomes, well, slightly less mundane.
Speaking of unexpected correlations, it's like the motor vehicle thefts and couriers in Kansas are in cahoots, playing a high-stakes game of tag! Or should I say, "tow" tag?
Moving beyond the realm of puns and into the realm of empirical inquiry, it is essential to establish the societal and economic significance of the variables under consideration. Motor vehicle theft, a criminal act with widespread implications for public safety and insurance costs, meets the seemingly more mundane world of courier and messenger services, which play a vital role in the logistics and delivery industry. This unlikely pair forms the basis of our investigation, challenging us to unravel their enigmatic connection, much like trying to decipher the hidden message in a cryptic crossword puzzle.
It's as if motor vehicle thefts and couriers in Kansas are engaged in a game of statistical hide and seek – but instead of seeking, they're looking to steal the spotlight!

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The correlation between motor vehicle thefts and the number of couriers and messengers in Kansas has intrigued researchers and perplexed law enforcement agencies for decades. In "Smith and Doe's Research on Crime and Labor Dynamics," the authors find a statistically significant positive relationship between the two variables, sparking curiosity and prompting further investigation. As we delve into the existing literature, it becomes clear that understanding this unlikely connection is more than just a mere delivery of knowledge – it's a wild ride through the corridors of statistical absurdity.

In their study, "The Courier Conundrum: Exploring Unconventional Correlations," Jones et al. present evidence suggesting a 0.8666944 correlation coefficient between motor vehicle thefts and the number of couriers and messengers in Kansas. This finding raises eyebrows and prompts questions that reach far beyond the boundaries of conventional wisdom. It's as if motor vehicle thefts and couriers in Kansas are performing an unlikely dance, with each theft serving as a twisted form of "parcel" delivery.

Turning to non-fiction works, "The Economics of Crime" by Becker delves into the economic incentives for criminal behavior, providing insights into the potential motivations behind motor vehicle thefts in areas with higher concentrations of couriers. On the labor front, "The Gig Economy: The Complete Guide to Getting Work" by Mulcahy sheds light on the burgeoning gig economy, where couriers and messengers thrive, but it offers little in the way of explaining their inadvertent linkage to motor vehicle thefts. Perhaps there's a chapter missing, titled "The Unintended Consequences of Door-to-Door Deliveries: An Exploration of Vehicular Vanishing Acts."

As we expand our search to fictional literature, works like "The Maltese Falcon" by Dashiell Hammett and "The Curious Incident of the Dog in the Night-Time" by Mark Haddon offer captivating narratives of mystery, deceit, and unexpected connections. While these novels may not directly tackle the correlation between motor vehicle thefts and couriers in Kansas, they remind us that truth can be stranger than fiction, especially when it comes to the statistical oddities of real-world data.

And for a more unconventional approach to our literature review, we turned to the captivating world of everyday labels and product descriptions, perusing the backs of shampoo bottles and cereal boxes in search of hidden wisdom. While these sources provided little in the way of empirical evidence, they did leave us with a newfound appreciation for the existential musings of inanimate objects – even if they couldn't lather, rinse, and repeat the surprising correlation we've uncovered.

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 in Kansas and The number of couriers and messengers in Kansas. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 FBI Criminal Justice Information Services and Bureau of Larbor Statistics . You used data from 2003 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]]
Breaking and Delivering: A Wacky Correlation Between Motor Vehicle Thefts and Couriers in Kansas

[[ABSTRACT]]
The relationship between motor vehicle thefts and the number of couriers and messengers in Kansas has long been a source of curiosity in both law enforcement and delivery service circles. This study delves into the connection, employing data from the FBI Criminal Justice Information Services and the Bureau of Labor Statistics. Our findings revealed a rather surprising correlation coefficient of 0.8666944 with a statistically significant p-value of less than 0.01 for the years spanning from 2003 to 2022.

In delving into this unlikely relationship, we found that as the number of couriers and messengers in Kansas increases, so too does the incidence of motor vehicle thefts. It appears that the presence of delivery personnel may inadvertently provide more opportunities for motor vehicle theft, possibly due to the frequent coming and going of vehicles in areas served by couriers. It's like the thieves are saying, "Special delivery!"

Our results pose intriguing questions for future research, as well as practical implications for law enforcement and delivery service companies. While the findings may seem perplexing at first, they shed light on the interconnectedness of seemingly disparate aspects of society. Now, if we could only figure out a way to deliver justice to those pesky car thieves!

[[INTRODUCTION]]
When it comes to exploring the relationship between seemingly unrelated variables, researchers often find themselves in a maze of correlations and causations, hoping to uncover hidden patterns and connections. In the realm of criminology and labor economics, one might not immediately think that motor vehicle thefts and the number of couriers and messengers in Kansas would have anything in common. However, as this paper delves into their peculiar relationship, we find ourselves on the winding road of statistical discovery, where the unexpected becomes the norm and the mundane becomes, well, slightly less mundane.
Speaking of unexpected correlations, it's like the motor vehicle thefts and couriers in Kansas are in cahoots, playing a high-stakes game of tag! Or should I say, "tow" tag?
Moving beyond the realm of puns and into the realm of empirical inquiry, it is essential to establish the societal and economic significance of the variables under consideration. Motor vehicle theft, a criminal act with widespread implications for public safety and insurance costs, meets the seemingly more mundane world of courier and messenger services, which play a vital role in the logistics and delivery industry. This unlikely pair forms the basis of our investigation, challenging us to unravel their enigmatic connection, much like trying to decipher the hidden message in a cryptic crossword puzzle.
It's as if motor vehicle thefts and couriers in Kansas are engaged in a game of statistical hide and seek – but instead of seeking, they're looking to steal the spotlight!

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

Ah, the thrilling world of methodology, where research dreams are dissected and statistical monsters are tamed. In our quest to uncover the mysterious link between motor vehicle thefts and the number of couriers and messengers in Kansas, we navigated the treacherous terrain of data collection and analysis with the cautious optimism of scientists embarking on a quest for the elusive statistical unicorn. Now, let's embark on a journey through our zany research methodology, where the rules of science collide with the chaos of dad jokes and puns.

Data Collection:
First and foremost, we delved into the vast realms of data provided by the FBI Criminal Justice Information Services and the Bureau of Labor Statistics. Like intrepid adventurers in a digital jungle, we scoured the depths of databases spanning the years 2003 to 2022, extracting nuggets of numerical wisdom like caffeinated prospectors panning for statistical gold. We then meticulously compiled the number of motor vehicle thefts and the count of couriers and messengers in the wild and wonderful state of Kansas, creating a tapestry of numbers that would make even the most seasoned accountant gaze in awe.

It's like we were on a quest for the Holy Grail of data, except instead of knights, we had statistical software, and instead of a grail, we found a correlation coefficient.

Data Analysis:
With our trusty statistical software in hand, we embarked on the epic journey of data analysis, wielding the mighty tools of correlation and regression with the finesse of a wizard casting spells in a statistical realm. We calculated the correlation coefficient between motor vehicle thefts and the number of couriers and messengers, and let me tell you, it was a sight to behold. The numbers danced like electrons in a statistical atom, revealing a correlation coefficient of 0.8666944, a value so strikingly high that it practically waved a statistical flag and shouted, "Here I am, I'm significant!"

But wait, there's more! We also conducted a regression analysis to explore the predictive power of couriers and messengers on motor vehicle thefts, unraveling the mysterious web of causation in a way that would make Sherlock Holmes proud. And lo and behold, our findings yielded a statistically significant p-value of less than 0.01, indicating a relationship so robust that it would make the Titanic jealous.

It's like our data was a well-organized library, and the statistical tests were the dedicated librarians meticulously categorizing and shelving every piece of information.

Addressing Potential Confounders:
In our pursuit of scientific rigor, we acknowledged the lurking specter of confounding variables, those mischievous troublemakers that can throw a statistical monkey wrench into the most well-laid plans. To vanquish these pesky foes, we conducted various sensitivity analyses and robustness checks, ensuring that our findings stood tall and proud like a sturdy scientific oak in the face of potential data-driven storms.

It's like we were guarding our statistical fortress against the onslaught of confounders, armed with the shield of empirical evidence and the sword of methodological precision.

So there you have it, the madcap journey through our research methodology, where data collection, analysis, and confounder-wrangling blend with the whimsy of dad jokes and the thrill of statistical discovery. Onward to the land of results, where the fruits of our labor await like a statistical orchard ripe for the picking!

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 in Kansas and The number of couriers and messengers in Kansas. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
Breaking and Delivering: A Wacky Correlation Between Motor Vehicle Thefts and Couriers in Kansas

[[ABSTRACT]]
The relationship between motor vehicle thefts and the number of couriers and messengers in Kansas has long been a source of curiosity in both law enforcement and delivery service circles. This study delves into the connection, employing data from the FBI Criminal Justice Information Services and the Bureau of Labor Statistics. Our findings revealed a rather surprising correlation coefficient of 0.8666944 with a statistically significant p-value of less than 0.01 for the years spanning from 2003 to 2022.

In delving into this unlikely relationship, we found that as the number of couriers and messengers in Kansas increases, so too does the incidence of motor vehicle thefts. It appears that the presence of delivery personnel may inadvertently provide more opportunities for motor vehicle theft, possibly due to the frequent coming and going of vehicles in areas served by couriers. It's like the thieves are saying, "Special delivery!"

Our results pose intriguing questions for future research, as well as practical implications for law enforcement and delivery service companies. While the findings may seem perplexing at first, they shed light on the interconnectedness of seemingly disparate aspects of society. Now, if we could only figure out a way to deliver justice to those pesky car thieves!

[[LITERATURE REVIEW]]
The correlation between motor vehicle thefts and the number of couriers and messengers in Kansas has intrigued researchers and perplexed law enforcement agencies for decades. In "Smith and Doe's Research on Crime and Labor Dynamics," the authors find a statistically significant positive relationship between the two variables, sparking curiosity and prompting further investigation. As we delve into the existing literature, it becomes clear that understanding this unlikely connection is more than just a mere delivery of knowledge – it's a wild ride through the corridors of statistical absurdity.
In their study, "The Courier Conundrum: Exploring Unconventional Correlations," Jones et al. present evidence suggesting a 0.8666944 correlation coefficient between motor vehicle thefts and the number of couriers and messengers in Kansas. This finding raises eyebrows and prompts questions that reach far beyond the boundaries of conventional wisdom. It's as if motor vehicle thefts and couriers in Kansas are performing an unlikely dance, with each theft serving as a twisted form of "parcel" delivery.
Turning to non-fiction works, "The Economics of Crime" by Becker delves into the economic incentives for criminal behavior, providing insights into the potential motivations behind motor vehicle thefts in areas with higher concentrations of couriers. On the labor front, "The Gig Economy: The Complete Guide to Getting Work" by Mulcahy sheds light on the burgeoning gig economy, where couriers and messengers thrive, but it offers little in the way of explaining their inadvertent linkage to motor vehicle thefts. Perhaps there's a chapter missing, titled "The Unintended Consequences of Door-to-Door Deliveries: An Exploration of Vehicular Vanishing Acts."
As we expand our search to fictional literature, works like "The Maltese Falcon" by Dashiell Hammett and "The Curious Incident of the Dog in the Night-Time" by Mark Haddon offer captivating narratives of mystery, deceit, and unexpected connections. While these novels may not directly tackle the correlation between motor vehicle thefts and couriers in Kansas, they remind us that truth can be stranger than fiction, especially when it comes to the statistical oddities of real-world data.
And for a more unconventional approach to our literature review, we turned to the captivating world of everyday labels and product descriptions, perusing the backs of shampoo bottles and cereal boxes in search of hidden wisdom. While these sources provided little in the way of empirical evidence, they did leave us with a newfound appreciation for the existential musings of inanimate objects – even if they couldn't lather, rinse, and repeat the surprising correlation we've uncovered.

[[RESULTS]]
The statistical analysis of the relationship between motor vehicle thefts and the number of couriers and messengers in Kansas yielded some eyebrow-raising results. From 2003 to 2022, we found a positively robust correlation coefficient of 0.8666944, indicating a strong association between the two variables. It's as if they were sending each other secret coded messages through the data! You might even call it a car-tastrophe waiting to happen.
The r-squared value of 0.7511592 suggested that approximately 75% of the variability in motor vehicle thefts in Kansas could be explained by the number of couriers and messengers. It's like these variables were in a long-term relationship, constantly influencing each other's decisions - "steering" each other towards mischief, so to speak.
Furthermore, the p-value of less than 0.01 provided compelling evidence that this relationship was not a fluke. In fact, the probability of observing such a strong correlation by random chance alone is less than 1%. It's as if the statistical stars aligned to reveal this unexpected association. It's a statistical "heist" of significance!
As illustrated in Figure 1 (not actually illustrated here, but you get the picture), the scatterplot vividly portrays the tight correlation between the number of couriers and messengers and the occurrences of motor vehicle thefts in Kansas. If it were a movie, you might call it "The Fast and the Spurious Correlation."
The results presented here not only challenge conventional wisdom but also open the door to a myriad of additional inquiries. It's as if the study of motor vehicle thefts and couriers in Kansas has opened a treasure trove of unexpected connections, like stumbling upon the unlikely bond between car keys and penny-farthings. This could be the start of a whole new avenue of research, or as we like to call it, a highway of data discovery!

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our findings present a compelling case for the unorthodox relationship between motor vehicle thefts and the number of couriers and messengers in Kansas. While the notion of delivery personnel inadvertently contributing to increased theft may seem counterintuitive at first, the statistical evidence supports this unexpected association. It's as if there's a mischievous game of car Cat and Mouse playing out in the data.

The literature review set the stage for our investigation, with prior research hinting at a correlation that seemed to defy conventional logic. By taking this connection seriously, we've not only confirmed the prior findings but also added a layer of statistical robustness to the relationship. It's like unraveling a mystery and finding that the culprit was hiding in plain sight all along – a bit like finding your car keys in the fridge!

The substantial correlation coefficient and the high r-squared value indicate a strong, explanatory relationship between couriers and motor vehicle thefts. It's as if they're in perfect sync, moving in tandem like a well-choreographed ballet of larceny and delivery services. The p-value, signaling the unlikelihood of this relationship occurring by random chance, adds a touch of statistical drama to the narrative. It's like the variables are saying, "We're not just going to drive off into the statistical sunset unnoticed!"

The implications of our findings extend beyond the realm of statistical oddities. Understanding this unusual correlation opens doors to practical considerations for law enforcement and delivery service companies. It's as if we've uncovered an unexpected connection that can help both industries strategize and collaborate more effectively. You might say we've delivered a "package deal" of insights that can benefit society as a whole.

In conclusion, our results not only support prior research but also shine a spotlight on the quirky interconnectedness of seemingly unrelated variables. The statistical tango between motor vehicle thefts and couriers in Kansas has shown us that truth is indeed stranger than fiction, especially when it comes to data analysis. It's as if we've stumbled upon a statistical eureka moment, uncovering a whole new world of unexpected correlations waiting to be explored. Who knew that the world of statistics could be so full of surprises? It's like a statistical rollercoaster ride – thrilling, enlightening, and at times, a little bit dizzying!

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 in Kansas and The number of couriers and messengers in Kansas. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
Breaking and Delivering: A Wacky Correlation Between Motor Vehicle Thefts and Couriers in Kansas

[[ABSTRACT]]
The relationship between motor vehicle thefts and the number of couriers and messengers in Kansas has long been a source of curiosity in both law enforcement and delivery service circles. This study delves into the connection, employing data from the FBI Criminal Justice Information Services and the Bureau of Labor Statistics. Our findings revealed a rather surprising correlation coefficient of 0.8666944 with a statistically significant p-value of less than 0.01 for the years spanning from 2003 to 2022.

In delving into this unlikely relationship, we found that as the number of couriers and messengers in Kansas increases, so too does the incidence of motor vehicle thefts. It appears that the presence of delivery personnel may inadvertently provide more opportunities for motor vehicle theft, possibly due to the frequent coming and going of vehicles in areas served by couriers. It's like the thieves are saying, "Special delivery!"

Our results pose intriguing questions for future research, as well as practical implications for law enforcement and delivery service companies. While the findings may seem perplexing at first, they shed light on the interconnectedness of seemingly disparate aspects of society. Now, if we could only figure out a way to deliver justice to those pesky car thieves!

[[INTRDUCTION]]
When it comes to exploring the relationship between seemingly unrelated variables, researchers often find themselves in a maze of correlations and causations, hoping to uncover hidden patterns and connections. In the realm of criminology and labor economics, one might not immediately think that motor vehicle thefts and the number of couriers and messengers in Kansas would have anything in common. However, as this paper delves into their peculiar relationship, we find ourselves on the winding road of statistical discovery, where the unexpected becomes the norm and the mundane becomes, well, slightly less mundane.
Speaking of unexpected correlations, it's like the motor vehicle thefts and couriers in Kansas are in cahoots, playing a high-stakes game of tag! Or should I say, "tow" tag?
Moving beyond the realm of puns and into the realm of empirical inquiry, it is essential to establish the societal and economic significance of the variables under consideration. Motor vehicle theft, a criminal act with widespread implications for public safety and insurance costs, meets the seemingly more mundane world of courier and messenger services, which play a vital role in the logistics and delivery industry. This unlikely pair forms the basis of our investigation, challenging us to unravel their enigmatic connection, much like trying to decipher the hidden message in a cryptic crossword puzzle.
It's as if motor vehicle thefts and couriers in Kansas are engaged in a game of statistical hide and seek – but instead of seeking, they're looking to steal the spotlight!

[[RESULTS]]
The statistical analysis of the relationship between motor vehicle thefts and the number of couriers and messengers in Kansas yielded some eyebrow-raising results. From 2003 to 2022, we found a positively robust correlation coefficient of 0.8666944, indicating a strong association between the two variables. It's as if they were sending each other secret coded messages through the data! You might even call it a car-tastrophe waiting to happen.
The r-squared value of 0.7511592 suggested that approximately 75% of the variability in motor vehicle thefts in Kansas could be explained by the number of couriers and messengers. It's like these variables were in a long-term relationship, constantly influencing each other's decisions - "steering" each other towards mischief, so to speak.
Furthermore, the p-value of less than 0.01 provided compelling evidence that this relationship was not a fluke. In fact, the probability of observing such a strong correlation by random chance alone is less than 1%. It's as if the statistical stars aligned to reveal this unexpected association. It's a statistical "heist" of significance!
As illustrated in Figure 1 (not actually illustrated here, but you get the picture), the scatterplot vividly portrays the tight correlation between the number of couriers and messengers and the occurrences of motor vehicle thefts in Kansas. If it were a movie, you might call it "The Fast and the Spurious Correlation."
The results presented here not only challenge conventional wisdom but also open the door to a myriad of additional inquiries. It's as if the study of motor vehicle thefts and couriers in Kansas has opened a treasure trove of unexpected connections, like stumbling upon the unlikely bond between car keys and penny-farthings. This could be the start of a whole new avenue of research, or as we like to call it, a highway of data discovery!

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the findings of this study have unveiled a remarkably strong correlation between the number of couriers and messengers in Kansas and the incidence of motor vehicle thefts. It's as if these variables are in cahoots, orchestrating a grand "car-napping" scheme across the state.

The statistical significance of the results boldly proclaims that this association is no mere statistical fluke. It's as if the numbers are shouting, "Hey, look at us! We're for real!" This revelation not only challenges conventional thinking but also underscores the interconnectedness of seemingly unrelated societal aspects. It's like discovering a hidden message in the form of data-driven detective work—these variables are revealing a plot twist that no one saw coming.

We must heed the call of these findings and recognize that further research in this area may not yield additional significant results. It's like trying to find a needle in a haystack within a field of haystacks—we've hit the jackpot here, folks! To pursue additional investigations would be akin to beating a dead horse thief. Therefore, it is with confidence that we assert this definitive conclusion: no more research is needed in this particular domain of inquiry. It's like closing the case on a well-solved puzzle—time to move on to the next statistical enigma!

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 Breaking and Delivering: A Wacky Correlation Between Motor Vehicle Thefts and Couriers in Kansas. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Eccentric Sociological Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Breaking and Delivering: A Wacky Correlation Between Motor Vehicle Thefts and Couriers in Kansas. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Eccentric Transportation Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Breaking and Delivering: A Wacky Correlation Between Motor Vehicle Thefts and Couriers in Kansas with an abstract of The relationship between motor vehicle thefts and the number of couriers and messengers in Kansas has long been a source of curiosity in both law enforcement and delivery service circles. This study delves into the connection, employing data from the FBI Criminal Justice Information Services and the Bureau of Labor Statistics. Our findings revealed a rather surprising correlation coefficient of 0.8666944 with a statistically significant p-value of less than 0.01 for the years spanning from 2003 to 2022.
In delving into this unlikely relationship, we found that as the number of couriers and messengers in Kansas increases, so too does the incidence of motor vehicle thefts. It appears that the presence of delivery personnel may inadvertently provide more opportunities for motor vehicle theft, possibly due to the frequent coming and going of vehicles in areas served by couriers. It's like the thieves are saying, "Special delivery!"
Our results pose intriguing questions for future research, as well as practical implications for law enforcement and delivery service companies. While the findings may seem perplexing at first, they shed light on the interconnectedness of seemingly disparate aspects of society. Now, if we could only figure out a way to deliver justice to those pesky car thieves!

ChatGPT:

motor vehicle thefts, couriers and messengers, Kansas, correlation coefficient, FBI Criminal Justice Information Services, Bureau of Labor Statistics, statistic significance, p-value, delivery service, law enforcement, crime trends

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

The number of couriers and messengers in Kansas
Detailed data title: BLS estimate of couriers and messengers in Kansas
Source: Bureau of Larbor Statistics
See what else correlates with The number of couriers and messengers in Kansas

Correlation r = 0.8666944 (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 = 0.7511592 (Coefficient of determination)
This means 75.1% of the change in the one variable (i.e., The number of couriers and messengers in Kansas) is predictable based on the change in the other (i.e., Motor vehicle thefts in Kansas) over the 20 years from 2003 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 7.7E-7.^Show 0.0000007704766780539976000000
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 0.87 in 7.7E-5% of random cases. Said differently, if you correlated 1,297,898 random variables^Note You don't actually need 1 million 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 19 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 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.

[ 0.69, 0.95 ] 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.

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Motor vehicle thefts in Kansas (Motor Vehicle Theft rate)	287.4	311.3	339.8	315.6	309.8	264.3	211.4	210.6	232.9	234.9	230.4	239.1	241	255	254	272.4	236.6	248.1	267.8	230.2
The number of couriers and messengers in Kansas (Couriers And Messengers)	1320	1370	1630	1600	1320	970	700	670	610	510	540	520	730	600	540	660	590	630	560	740

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.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([287.4,311.3,339.8,315.6,309.8,264.3,211.4,210.6,232.9,234.9,230.4,239.1,241,255,254,272.4,236.6,248.1,267.8,230.2,])
array_2 = np.array([1320,1370,1630,1600,1320,970,700,670,610,510,540,520,730,600,540,660,590,630,560,740,])
array_1_name = "Motor vehicle thefts in Kansas"
array_2_name = "The number of couriers and messengers in Kansas"

# 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 in Kansas
Line chart for only The number of couriers and messengers in Kansas
AI-generated correlation image
The spurious research paper: Breaking and Delivering: A Wacky Correlation Between Motor Vehicle Thefts and Couriers in Kansas

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Correlation ID: 1643 · Black Variable ID: 20177 · Red Variable ID: 8270


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