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AI explanation
As the smog cleared, so did the opportunity for car bandits to make a clean getaway. It seems the air wasn't the only thing getting a breath of fresh air - the car thieves were also taking a break from their smoggy business. It's as if the reduction in pollution put the brakes on the thieves' activities, leaving them with less fuel for their criminal endeavors. This just goes to show that when it comes to crime, cleaner air really does drive down the rates of auto theft!
Model: dalle-3
Prompt: Visual Prompt: An aerial view of the smoggy Atlanta skyline gradually clearing, with the cityscape becoming more prominent as the haze disperses. Below, a parking lot comes into view, where several thieves are seen standing around stolen vehicles. The reduced air pollution seems to have slowed down their escape and illicit activities, leaving them idly waiting with a sense of frustration. The scene captures the unexpected impact of cleaner air as a deterrent to their criminal plans, with the once hazy cityscape now revealing a halted criminal operation. 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: Air pollution in Atlanta and Motor vehicle thefts in Georgia. 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: Cutsy graphics Psychedelic A Discovery magazine cover image Futuristic Sci-fi fantacy
ChatGPT: A Discovery magazine cover image
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 Air pollution in Atlanta and Motor vehicle thefts in Georgia, in the following situation: As the smog cleared, so did the opportunity for car bandits to make a clean getaway. It seems the air wasn't the only thing getting a breath of fresh air - the car thieves were also taking a break from their smoggy business. It's as if the reduction in pollution put the brakes on the thieves' activities, leaving them with less fuel for their criminal endeavors. This just goes to show that when it comes to crime, cleaner air really does drive down the rates of auto theft!. Keep the description simple.
ChatGPT: A smoggy Atlanta skyline gradually clears, revealing a parking lot where car thieves are unable to make a hasty escape due to the improved visibility. The reduced air pollution seems to have put a damper on their criminal activities, leaving the thieves idly waiting for an opportunity that never seems to arrive. The clean air serves as an unexpected deterrent, putting a halt to their illicit plans and leaving the stolen vehicles untouched.
Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A Discovery magazine cover image ] and depicting this scene: A smoggy Atlanta skyline gradually clears, revealing a parking lot where car thieves are unable to make a hasty escape due to the improved visibility. The reduced air pollution seems to have put a damper on their criminal activities, leaving the thieves idly waiting for an opportunity that never seems to arrive. The clean air serves as an unexpected deterrent, putting a halt to their illicit plans and leaving the stolen vehicles untouched. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Visual Prompt: An aerial view of the smoggy Atlanta skyline gradually clearing, with the cityscape becoming more prominent as the haze disperses. Below, a parking lot comes into view, where several thieves are seen standing around stolen vehicles. The reduced air pollution seems to have slowed down their escape and illicit activities, leaving them idly waiting with a sense of frustration. The scene captures the unexpected impact of cleaner air as a deterrent to their criminal plans, with the once hazy cityscape now revealing a halted criminal operation.
*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.
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 Air pollution in Atlanta caused Motor vehicle thefts in Georgia to decrease. Include one good pun.
AI academic paper
 |
Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled The Journal of Environmental Quirks Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Air pollution in Atlanta and Motor vehicle thefts in Georgia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Rhyme words in the title.
Your research team used data from Environmental Protection Agency and FBI Criminal Justice Information Services to assess this nagging question. You found a correlation coefficient of 0.8035113 and p < 0.01 for 1985 to 2022.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled
[[ABSTRACT]]
The relationship between environmental pollution and criminal activity has often been brushed aside as mere happenstance, but our research seeks to clear the air on this matter. Through a comprehensive analysis of air pollution levels in Atlanta and motor vehicle theft rates in Georgia, we aimed to unravel the veil of correlation. Our findings reveal a striking connection between these seemingly unrelated phenomena, leaving us to ponder whether the heist gets a breath of fresh air from the polluted atmosphere. Our study, spanning nearly four decades, unveils a correlation coefficient of 0.8035113 and a p-value of less than 0.01, not to steal the spotlight, but certainly worth breathing in. With these results, we wave goodbye to the notion that air pollution and car thefts are simply a coincidental coexistence. We hope this research sparks a clean getaway from the assumption that these issues are unrelated, and sheds light on the unseen connections between air quality and criminal behavior.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Air pollution in Atlanta and Motor vehicle thefts in Georgia. 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.
Here is the title and abstract of the paper:
[[TITLE]]
Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled
[[ABSTRACT]]
The relationship between environmental pollution and criminal activity has often been brushed aside as mere happenstance, but our research seeks to clear the air on this matter. Through a comprehensive analysis of air pollution levels in Atlanta and motor vehicle theft rates in Georgia, we aimed to unravel the veil of correlation. Our findings reveal a striking connection between these seemingly unrelated phenomena, leaving us to ponder whether the heist gets a breath of fresh air from the polluted atmosphere. Our study, spanning nearly four decades, unveils a correlation coefficient of 0.8035113 and a p-value of less than 0.01, not to steal the spotlight, but certainly worth breathing in. With these results, we wave goodbye to the notion that air pollution and car thefts are simply a coincidental coexistence. We hope this research sparks a clean getaway from the assumption that these issues are unrelated, and sheds light on the unseen connections between air quality and criminal behavior.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
Ah, the smell of exhaust fumes and the thrill of a daring car theft - not quite the sequence of events we expected to explore when delving into the intriguing intersection of air pollution and motor vehicle theft. The marriage of malodorous air and grand larceny may not seem cohabitable, but as researchers, it is our duty to take a deep breath and leave no stone unturned in the pursuit of scientific inquiry.
As we embark on this investigative journey, we cannot help but wonder: Did the thieves simply "auto" take advantage of the smog-choked Atlanta air for their getaway vehicles, or is there a more complex "engine" at play in this tale of environmental pollution and criminal activities?
A proverbial puzzle indeed, but fear not, esteemed colleagues, for we are armed with data and statistical tools sharper than Sherlock's magnifying glass. We aim not only to uncover correlations but to ventilate the uncharted territory that lies at the crossroads of air quality and criminal mischief.
Now, let's dive into the nitty-gritty - or should I say the "dirty" details? Our study, spanning an impressive temporal range of nearly four decades, dived deep into the labyrinth of air pollution levels in Atlanta and the occurrence of motor vehicle theft in Georgia. Picture us as intrepid explorers, equipped with nothing but our statistical compass and a sense of humor - after all, in this "crime scene," laughter might just be the best medicine.
Delving into the treasure trove of numbers and graphs, we stumbled upon a rather astoundingly high correlation coefficient of 0.8035113 and a p-value of less than 0.01. Now, before you accuse us of grand larceny of significance, or worse - data manipulation, rest assured, dear readers, that these findings are as solid as a well-locked car door.
Our aim is not to be thieves of your attention, but rather to illuminate the unexpected nexus between air quality and criminal pursuits. We aim to paint a picture that is more than just black and white; amidst the shades of gray, we hope to capture the subtle nuances and interplay of factors that influence criminal behavior.
So, fasten your seatbelts, as we embark on a journey to untangle this intriguing riddle. It's more than just a statistical escapade; it's a pursuit of understanding, wrapped in a blanket of science, seasoned with a dash of humor, and served with a side of wry skepticism. After all, who said unraveling a scientific mystery couldn't be fun? Or at least, pun-derful.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Air pollution in Atlanta and Motor vehicle thefts in Georgia. 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 cite some social media posts you read that seem to be related.
Here is the title and abstract of the paper:
[[TITLE]]
Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled
[[ABSTRACT]]
The relationship between environmental pollution and criminal activity has often been brushed aside as mere happenstance, but our research seeks to clear the air on this matter. Through a comprehensive analysis of air pollution levels in Atlanta and motor vehicle theft rates in Georgia, we aimed to unravel the veil of correlation. Our findings reveal a striking connection between these seemingly unrelated phenomena, leaving us to ponder whether the heist gets a breath of fresh air from the polluted atmosphere. Our study, spanning nearly four decades, unveils a correlation coefficient of 0.8035113 and a p-value of less than 0.01, not to steal the spotlight, but certainly worth breathing in. With these results, we wave goodbye to the notion that air pollution and car thefts are simply a coincidental coexistence. We hope this research sparks a clean getaway from the assumption that these issues are unrelated, and sheds light on the unseen connections between air quality and criminal behavior.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Ah, the smell of exhaust fumes and the thrill of a daring car theft - not quite the sequence of events we expected to explore when delving into the intriguing intersection of air pollution and motor vehicle theft. The marriage of malodorous air and grand larceny may not seem cohabitable, but as researchers, it is our duty to take a deep breath and leave no stone unturned in the pursuit of scientific inquiry.
As we embark on this investigative journey, we cannot help but wonder: Did the thieves simply "auto" take advantage of the smog-choked Atlanta air for their getaway vehicles, or is there a more complex "engine" at play in this tale of environmental pollution and criminal activities?
A proverbial puzzle indeed, but fear not, esteemed colleagues, for we are armed with data and statistical tools sharper than Sherlock's magnifying glass. We aim not only to uncover correlations but to ventilate the uncharted territory that lies at the crossroads of air quality and criminal mischief.
Now, let's dive into the nitty-gritty - or should I say the "dirty" details? Our study, spanning an impressive temporal range of nearly four decades, dived deep into the labyrinth of air pollution levels in Atlanta and the occurrence of motor vehicle theft in Georgia. Picture us as intrepid explorers, equipped with nothing but our statistical compass and a sense of humor - after all, in this "crime scene," laughter might just be the best medicine.
Delving into the treasure trove of numbers and graphs, we stumbled upon a rather astoundingly high correlation coefficient of 0.8035113 and a p-value of less than 0.01. Now, before you accuse us of grand larceny of significance, or worse - data manipulation, rest assured, dear readers, that these findings are as solid as a well-locked car door.
Our aim is not to be thieves of your attention, but rather to illuminate the unexpected nexus between air quality and criminal pursuits. We aim to paint a picture that is more than just black and white; amidst the shades of gray, we hope to capture the subtle nuances and interplay of factors that influence criminal behavior.
So, fasten your seatbelts, as we embark on a journey to untangle this intriguing riddle. It's more than just a statistical escapade; it's a pursuit of understanding, wrapped in a blanket of science, seasoned with a dash of humor, and served with a side of wry skepticism. After all, who said unraveling a scientific mystery couldn't be fun? Or at least, pun-derful.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
In their study titled "The Impact of Air Pollution on Social Behaviors," Smith and Doe delve into the intricate relationship between environmental factors and criminal activity. They argue that exposure to air pollution can have detrimental effects on cognitive function, decision-making, and impulse control, potentially contributing to an increase in criminal behavior. This investigation sheds light on the potential links between air quality and unlawful activities, painting a picture of an invisible yet compelling connection.
On a related note, Jones et al. explore the geographical patterns of motor vehicle theft in their work "Geospatial Analysis of Vehicular Crime." Their findings reveal hotspots of automobile theft, highlighting the influence of urban environments and demographic factors on criminal behavior. Indeed, the spatial distribution of theft incidents seems to dance to a rhythm only discernible to the keen eyes of seasoned researchers.
Now, let's shift gears and take a detour into the world of non-fiction literature. In "The Big Necessity: The Unmentionable World of Human Waste and Why It Matters," Rose George invites readers to contemplate the intricate web of interconnected phenomena that shape our daily lives, including the unseen impact of air pollution on societal behaviors. Meanwhile, "Freakonomics: A Rogue Economist Explores the Hidden Side of Everything" by Steven D. Levitt and Stephen J. Dubner challenges us to question conventional wisdom and uncover the unexpected correlations that underpin human behavior – could the correlation between air pollution and vehicle theft be yet another hidden gem waiting to be unearthed?
Turning to the whimsical world of fiction, "Gone in Sixty Seconds" by Eleanor Cooney and Daniel Klein presents a riveting tale of car theft and high-speed chases, inviting readers to ponder the allure of the forbidden joyride and the murky allure of the underground world of automotive pilfering. In a similar vein, "The Great Gatsby" by F. Scott Fitzgerald offers a glimpse into the glamorous yet treacherous interplay of wealth, ambition, and crime in the melting pot of the Roaring Twenties – a period rife with societal transformations and, dare I say, thefts of hearts and automobiles alike.
In a surprising twist, a recent social media post on the correlation between air pollution and car theft caught the eye of this curious researcher. A user going by the handle @CleanAirCarThief boldly proclaimed, "A breath of fresh air is all I need to fuel my adventurous heists – who knew pollution could be a catalyst for clean getaways?" Their tongue-in-cheek remark seems to beckon us to peer beyond the obvious and embrace the unconventional facets of this captivating conundrum.
As we wade through the sea of research and innovative thought, it becomes clear that the confluence of air pollution and motor vehicle theft is not merely a matter of happenstance. Rather, it is a symphony of environmental cues and human behaviors, waiting to be deciphered with a good measure of intellectual curiosity – and perhaps a dash of humor.
And speaking of symphonies, did you hear about the car thief who tried to steal a vehicle but couldn't find the right key? He couldn't handle the "auto" theft, it was just too exhausting!
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Air pollution in Atlanta and Motor vehicle thefts in Georgia. 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 Environmental Protection Agency and FBI Criminal Justice Information Services . 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]]
Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled
[[ABSTRACT]]
The relationship between environmental pollution and criminal activity has often been brushed aside as mere happenstance, but our research seeks to clear the air on this matter. Through a comprehensive analysis of air pollution levels in Atlanta and motor vehicle theft rates in Georgia, we aimed to unravel the veil of correlation. Our findings reveal a striking connection between these seemingly unrelated phenomena, leaving us to ponder whether the heist gets a breath of fresh air from the polluted atmosphere. Our study, spanning nearly four decades, unveils a correlation coefficient of 0.8035113 and a p-value of less than 0.01, not to steal the spotlight, but certainly worth breathing in. With these results, we wave goodbye to the notion that air pollution and car thefts are simply a coincidental coexistence. We hope this research sparks a clean getaway from the assumption that these issues are unrelated, and sheds light on the unseen connections between air quality and criminal behavior.
[[INTRODUCTION]]
Ah, the smell of exhaust fumes and the thrill of a daring car theft - not quite the sequence of events we expected to explore when delving into the intriguing intersection of air pollution and motor vehicle theft. The marriage of malodorous air and grand larceny may not seem cohabitable, but as researchers, it is our duty to take a deep breath and leave no stone unturned in the pursuit of scientific inquiry.
As we embark on this investigative journey, we cannot help but wonder: Did the thieves simply "auto" take advantage of the smog-choked Atlanta air for their getaway vehicles, or is there a more complex "engine" at play in this tale of environmental pollution and criminal activities?
A proverbial puzzle indeed, but fear not, esteemed colleagues, for we are armed with data and statistical tools sharper than Sherlock's magnifying glass. We aim not only to uncover correlations but to ventilate the uncharted territory that lies at the crossroads of air quality and criminal mischief.
Now, let's dive into the nitty-gritty - or should I say the "dirty" details? Our study, spanning an impressive temporal range of nearly four decades, dived deep into the labyrinth of air pollution levels in Atlanta and the occurrence of motor vehicle theft in Georgia. Picture us as intrepid explorers, equipped with nothing but our statistical compass and a sense of humor - after all, in this "crime scene," laughter might just be the best medicine.
Delving into the treasure trove of numbers and graphs, we stumbled upon a rather astoundingly high correlation coefficient of 0.8035113 and a p-value of less than 0.01. Now, before you accuse us of grand larceny of significance, or worse - data manipulation, rest assured, dear readers, that these findings are as solid as a well-locked car door.
Our aim is not to be thieves of your attention, but rather to illuminate the unexpected nexus between air quality and criminal pursuits. We aim to paint a picture that is more than just black and white; amidst the shades of gray, we hope to capture the subtle nuances and interplay of factors that influence criminal behavior.
So, fasten your seatbelts, as we embark on a journey to untangle this intriguing riddle. It's more than just a statistical escapade; it's a pursuit of understanding, wrapped in a blanket of science, seasoned with a dash of humor, and served with a side of wry skepticism. After all, who said unraveling a scientific mystery couldn't be fun? Or at least, pun-derful.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To unlock the enigma of the puzzling relationship between air pollution and motor vehicle theft, we navigated through the labyrinth of scientific methodologies with the precision and grace of a Formula 1 car navigating a twisty track. Our data, spanning the years 1985 to 2022, was primarily sourced from the treasure troves of the Environmental Protection Agency and the FBI Criminal Justice Information Services – we needed to ensure our research had a clean record, after all.
To kick off our investigation, we strapped on our statistical seatbelts and fired up the engine of correlation analysis. We employed the Pearson correlation coefficient to measure the strength and direction of the relationship between air pollution levels in Atlanta and motor vehicle thefts in Georgia. Like diligent detectives, we also calculated the p-value to gauge the statistical significance of our findings. No stone was left unturned in our mission to throw light on this shady connection.
In our quest for knowledge, we didn't just stop at staring at numbers; we also harnessed the power of graphical analysis to visualize the trends and patterns in the data. It was like creating a work of art, but instead of paintbrushes, we wielded scatter plots and trend lines to craft a masterpiece of scientific investigation. To break the monotony of endless data crunching, we may or may not have indulged in a game or two of "Pictionary" using the plotted points – anything to keep the wits sharp!
The ever-resourceful tools of multivariate regression analysis were also summoned from the depths of statistical arsenal to ascertain whether other confounding variables played a role in the observed relationship. We were determined to separate the signal from the noise, just like a mechanic fine-tuning an engine to rid it of any unexpected clunking noises. If only all conundrums could be solved with a trusty set of regression equations!
Now, here comes the part where we let you in on a little secret – the subtle art of "Gaussian Copula" modeling. Yes, we delved into the world of copulas, those nifty statistical models that allowed us to capture the dependencies between air pollution and car theft in a way that classical methods simply couldn't. It was like dabbling in a bit of science fiction, only this time, the aliens were represented by archimedean copulas and the spacecraft was an abstract representation of the joint distribution function. To say we were over the moon about this technique would be an understatement.
In addition to the quantitative realm, we also paid homage to the qualitative side of our investigation. Interviews with law enforcement agencies and environmental experts provided valuable insights, shedding light on the ground realities and giving depth to our understanding. Listening to these firsthand accounts was like having front-row seats to a thrilling drama, with each anecdote adding another layer to the narrative.
In summary, our methodology can be likened to a well-choreographed dance, where statistical analyses, graphical representations, and interviews twirled together to create a mesmerizing performance. We aimed not just to uncover correlations but to paint a comprehensive picture of the interplay between air quality and vehicular villainy. And with a little statistical wizardry and a sprinkle of humor, we daresay we succeeded – like a perfectly executed joke, our findings packed a punch!
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Atlanta and Motor vehicle thefts in Georgia. 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 Environmental Protection Agency and FBI Criminal Justice Information Services .
For the time period 1985 to 2022, you found a correlation 0.8035113, r-squared of 0.6456304, and p < 0.01.
One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.
Here is the title and abstract of the paper:
[[TITLE]]
Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled
[[ABSTRACT]]
The relationship between environmental pollution and criminal activity has often been brushed aside as mere happenstance, but our research seeks to clear the air on this matter. Through a comprehensive analysis of air pollution levels in Atlanta and motor vehicle theft rates in Georgia, we aimed to unravel the veil of correlation. Our findings reveal a striking connection between these seemingly unrelated phenomena, leaving us to ponder whether the heist gets a breath of fresh air from the polluted atmosphere. Our study, spanning nearly four decades, unveils a correlation coefficient of 0.8035113 and a p-value of less than 0.01, not to steal the spotlight, but certainly worth breathing in. With these results, we wave goodbye to the notion that air pollution and car thefts are simply a coincidental coexistence. We hope this research sparks a clean getaway from the assumption that these issues are unrelated, and sheds light on the unseen connections between air quality and criminal behavior.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
Ah, the smell of exhaust fumes and the thrill of a daring car theft - not quite the sequence of events we expected to explore when delving into the intriguing intersection of air pollution and motor vehicle theft. The marriage of malodorous air and grand larceny may not seem cohabitable, but as researchers, it is our duty to take a deep breath and leave no stone unturned in the pursuit of scientific inquiry.
As we embark on this investigative journey, we cannot help but wonder: Did the thieves simply "auto" take advantage of the smog-choked Atlanta air for their getaway vehicles, or is there a more complex "engine" at play in this tale of environmental pollution and criminal activities?
A proverbial puzzle indeed, but fear not, esteemed colleagues, for we are armed with data and statistical tools sharper than Sherlock's magnifying glass. We aim not only to uncover correlations but to ventilate the uncharted territory that lies at the crossroads of air quality and criminal mischief.
Now, let's dive into the nitty-gritty - or should I say the "dirty" details? Our study, spanning an impressive temporal range of nearly four decades, dived deep into the labyrinth of air pollution levels in Atlanta and the occurrence of motor vehicle theft in Georgia. Picture us as intrepid explorers, equipped with nothing but our statistical compass and a sense of humor - after all, in this "crime scene," laughter might just be the best medicine.
Delving into the treasure trove of numbers and graphs, we stumbled upon a rather astoundingly high correlation coefficient of 0.8035113 and a p-value of less than 0.01. Now, before you accuse us of grand larceny of significance, or worse - data manipulation, rest assured, dear readers, that these findings are as solid as a well-locked car door.
Our aim is not to be thieves of your attention, but rather to illuminate the unexpected nexus between air quality and criminal pursuits. We aim to paint a picture that is more than just black and white; amidst the shades of gray, we hope to capture the subtle nuances and interplay of factors that influence criminal behavior.
So, fasten your seatbelts, as we embark on a journey to untangle this intriguing riddle. It's more than just a statistical escapade; it's a pursuit of understanding, wrapped in a blanket of science, seasoned with a dash of humor, and served with a side of wry skepticism. After all, who said unraveling a scientific mystery couldn't be fun? Or at least, pun-derful.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
Having embarked on our statistical adventure with open minds (and open noses in the case of air pollution), we found ourselves facing the startling revelation of a robust relationship between air pollution in Atlanta and motor vehicle thefts in Georgia. The correlation coefficient of 0.8035113 danced before our eyes, akin to a well-choreographed car chase scene. This correlation was not a mere flirtation; it was a full-blown affair between the pungent particles lingering in the air and the allure of a stolen ride.
Fig. 1 presents a scatterplot that artistically captures the strong link we uncovered, almost as if the data points themselves conspired to tell a tale of their own. It's as if every stolen car whispered, "I took a breath of fresh air on the way out," defying the conventional wisdom that these variables are as far apart as a clean getaway and a cloud of smog.
Now, let's address the elephant in the room – or should we say, the exhaust emissions in the laboratory? Yes, we are well aware that correlation does not imply causation, but it's hard to ignore the suggestive implications of our findings. It’s like finding a guilty fingerprint on the scene of a crime – it doesn’t immediately prove guilt, but it sure warrants a closer investigation.
You might be wondering, “What are the odds of this correlation occurring by mere chance?” Well, we’re here to tell you that the odds are as slim as a cat burglar squeezing through a tiny window. With an r-squared value of 0.6456304 and a p-value of less than 0.01, we can confidently say that this connection is not a random caper but a well-planned heist of statistical significance.
In the words of a seasoned detective, we are inclined to believe that there is smoke without a fire somewhere. Our findings not only challenge the status quo but also leave us pondering whether the proverbial "smoke and fire" can be extended to the “pollution and theft” scenario. It seems that in this case, the scent of foul air and the allure of an ill-gotten ride might just be partners in crime, or at least in statistical mischief.
As we reflect on our research, we can't help but chuckle at the unexpected bridge we found between pollution and pilferage. It’s almost poetic – a tale of environmental woes and criminal maneuvers, each dancing to the tune of the other. As we close this chapter, we hope our findings serve as a vehicle for deeper exploration into the hidden connections that thread through our world, and encourage others to sniff out the unexpected links in science.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Air pollution in Atlanta and Motor vehicle thefts in Georgia. 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]]
Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled
[[ABSTRACT]]
The relationship between environmental pollution and criminal activity has often been brushed aside as mere happenstance, but our research seeks to clear the air on this matter. Through a comprehensive analysis of air pollution levels in Atlanta and motor vehicle theft rates in Georgia, we aimed to unravel the veil of correlation. Our findings reveal a striking connection between these seemingly unrelated phenomena, leaving us to ponder whether the heist gets a breath of fresh air from the polluted atmosphere. Our study, spanning nearly four decades, unveils a correlation coefficient of 0.8035113 and a p-value of less than 0.01, not to steal the spotlight, but certainly worth breathing in. With these results, we wave goodbye to the notion that air pollution and car thefts are simply a coincidental coexistence. We hope this research sparks a clean getaway from the assumption that these issues are unrelated, and sheds light on the unseen connections between air quality and criminal behavior.
[[LITERATURE REVIEW]]
In their study titled "The Impact of Air Pollution on Social Behaviors," Smith and Doe delve into the intricate relationship between environmental factors and criminal activity. They argue that exposure to air pollution can have detrimental effects on cognitive function, decision-making, and impulse control, potentially contributing to an increase in criminal behavior. This investigation sheds light on the potential links between air quality and unlawful activities, painting a picture of an invisible yet compelling connection.
On a related note, Jones et al. explore the geographical patterns of motor vehicle theft in their work "Geospatial Analysis of Vehicular Crime." Their findings reveal hotspots of automobile theft, highlighting the influence of urban environments and demographic factors on criminal behavior. Indeed, the spatial distribution of theft incidents seems to dance to a rhythm only discernible to the keen eyes of seasoned researchers.
Now, let's shift gears and take a detour into the world of non-fiction literature. In "The Big Necessity: The Unmentionable World of Human Waste and Why It Matters," Rose George invites readers to contemplate the intricate web of interconnected phenomena that shape our daily lives, including the unseen impact of air pollution on societal behaviors. Meanwhile, "Freakonomics: A Rogue Economist Explores the Hidden Side of Everything" by Steven D. Levitt and Stephen J. Dubner challenges us to question conventional wisdom and uncover the unexpected correlations that underpin human behavior – could the correlation between air pollution and vehicle theft be yet another hidden gem waiting to be unearthed?
Turning to the whimsical world of fiction, "Gone in Sixty Seconds" by Eleanor Cooney and Daniel Klein presents a riveting tale of car theft and high-speed chases, inviting readers to ponder the allure of the forbidden joyride and the murky allure of the underground world of automotive pilfering. In a similar vein, "The Great Gatsby" by F. Scott Fitzgerald offers a glimpse into the glamorous yet treacherous interplay of wealth, ambition, and crime in the melting pot of the Roaring Twenties – a period rife with societal transformations and, dare I say, thefts of hearts and automobiles alike.
In a surprising twist, a recent social media post on the correlation between air pollution and car theft caught the eye of this curious researcher. A user going by the handle @CleanAirCarThief boldly proclaimed, "A breath of fresh air is all I need to fuel my adventurous heists – who knew pollution could be a catalyst for clean getaways?" Their tongue-in-cheek remark seems to beckon us to peer beyond the obvious and embrace the unconventional facets of this captivating conundrum.
As we wade through the sea of research and innovative thought, it becomes clear that the confluence of air pollution and motor vehicle theft is not merely a matter of happenstance. Rather, it is a symphony of environmental cues and human behaviors, waiting to be deciphered with a good measure of intellectual curiosity – and perhaps a dash of humor.
And speaking of symphonies, did you hear about the car thief who tried to steal a vehicle but couldn't find the right key? He couldn't handle the "auto" theft, it was just too exhausting!
[[RESULTS]]
Having embarked on our statistical adventure with open minds (and open noses in the case of air pollution), we found ourselves facing the startling revelation of a robust relationship between air pollution in Atlanta and motor vehicle thefts in Georgia. The correlation coefficient of 0.8035113 danced before our eyes, akin to a well-choreographed car chase scene. This correlation was not a mere flirtation; it was a full-blown affair between the pungent particles lingering in the air and the allure of a stolen ride.
Fig. 1 presents a scatterplot that artistically captures the strong link we uncovered, almost as if the data points themselves conspired to tell a tale of their own. It's as if every stolen car whispered, "I took a breath of fresh air on the way out," defying the conventional wisdom that these variables are as far apart as a clean getaway and a cloud of smog.
Now, let's address the elephant in the room – or should we say, the exhaust emissions in the laboratory? Yes, we are well aware that correlation does not imply causation, but it's hard to ignore the suggestive implications of our findings. It’s like finding a guilty fingerprint on the scene of a crime – it doesn’t immediately prove guilt, but it sure warrants a closer investigation.
You might be wondering, “What are the odds of this correlation occurring by mere chance?” Well, we’re here to tell you that the odds are as slim as a cat burglar squeezing through a tiny window. With an r-squared value of 0.6456304 and a p-value of less than 0.01, we can confidently say that this connection is not a random caper but a well-planned heist of statistical significance.
In the words of a seasoned detective, we are inclined to believe that there is smoke without a fire somewhere. Our findings not only challenge the status quo but also leave us pondering whether the proverbial "smoke and fire" can be extended to the “pollution and theft” scenario. It seems that in this case, the scent of foul air and the allure of an ill-gotten ride might just be partners in crime, or at least in statistical mischief.
As we reflect on our research, we can't help but chuckle at the unexpected bridge we found between pollution and pilferage. It’s almost poetic – a tale of environmental woes and criminal maneuvers, each dancing to the tune of the other. As we close this chapter, we hope our findings serve as a vehicle for deeper exploration into the hidden connections that thread through our world, and encourage others to sniff out the unexpected links in science.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our research has cast a spotlight on the uncanny connection between air pollution in Atlanta and motor vehicle thefts in Georgia, revealing an unexpected partnership akin to an entwined tango between environmental woes and criminal exploits. The correlation coefficient of 0.8035113 that emerged from our analysis proved to be more than just a casual acquaintance; it was a robust and statistically significant association, not unlike a mischief of rats scampering through the maze of variables. These findings corroborate the work of Smith and Doe, emphasizing the potential influence of environmental factors on criminal behavior. Indeed, it seems that the polluted air might just serve as an unwitting accomplice to the pursuits of an audacious car thief.
This unique association, much like a clearance sale at a car dealership, invites us to question the conventional and embrace the extraordinary. Despite the whimsical tidbits found in fiction literature, including the elusive allure of a forbidden joyride and the intriguing patterns that only seasoned eyes can discern, our findings lend concrete weight to the notion that environmental cues can intertwine with human behavior in unexpected ways. It's as if the statistical stars aligned to unveil a compelling narrative, leaving us to ponder the possibility of a pollution-powered pilfer and its influence on the criminal underbelly of society.
Our journey through the statistical landscape has not only reinforced the likelihood of a tangible relationship between air pollution and vehicle theft but has also underscored the necessity of delving deeper into the unseen tendrils that bind seemingly disparate phenomena. It's akin to chasing a double-dealing bandit through a maze of convoluted statistics, with each turn revealing a new twist in the narrative. The statistically significant r-squared value and p-value of less than 0.01 further emphasize the credibility and robustness of this unearthed connection, leaving little room for doubt that this correlation is not a mere serendipitous encounter but a thoughtfully orchestrated symphony of influence.
In the spirit of uncovering hidden connections, our study has not only broadened the spectrum of research in environmental criminology but has also opened the door to a myriad of tantalizing questions and possibilities. It's like stumbling upon a treasure trove of insights in the unlikeliest of places, ultimately leaving us with a wealth of fresh avenues to explore. As we navigate this landscape of intriguing connections and entangled variables, we envision our research serving as a trailblazer in the pursuit of unraveling the unforeseen influences that permeate the fabric of human behavior.
And speaking of unforeseen influences, did you hear about the car thief who returned a stolen car because it was a hybrid? He couldn't handle the "electric" excitement!
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Air pollution in Atlanta and Motor vehicle thefts in Georgia. 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]]
Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled
[[ABSTRACT]]
The relationship between environmental pollution and criminal activity has often been brushed aside as mere happenstance, but our research seeks to clear the air on this matter. Through a comprehensive analysis of air pollution levels in Atlanta and motor vehicle theft rates in Georgia, we aimed to unravel the veil of correlation. Our findings reveal a striking connection between these seemingly unrelated phenomena, leaving us to ponder whether the heist gets a breath of fresh air from the polluted atmosphere. Our study, spanning nearly four decades, unveils a correlation coefficient of 0.8035113 and a p-value of less than 0.01, not to steal the spotlight, but certainly worth breathing in. With these results, we wave goodbye to the notion that air pollution and car thefts are simply a coincidental coexistence. We hope this research sparks a clean getaway from the assumption that these issues are unrelated, and sheds light on the unseen connections between air quality and criminal behavior.
[[INTRDUCTION]]
Ah, the smell of exhaust fumes and the thrill of a daring car theft - not quite the sequence of events we expected to explore when delving into the intriguing intersection of air pollution and motor vehicle theft. The marriage of malodorous air and grand larceny may not seem cohabitable, but as researchers, it is our duty to take a deep breath and leave no stone unturned in the pursuit of scientific inquiry.
As we embark on this investigative journey, we cannot help but wonder: Did the thieves simply "auto" take advantage of the smog-choked Atlanta air for their getaway vehicles, or is there a more complex "engine" at play in this tale of environmental pollution and criminal activities?
A proverbial puzzle indeed, but fear not, esteemed colleagues, for we are armed with data and statistical tools sharper than Sherlock's magnifying glass. We aim not only to uncover correlations but to ventilate the uncharted territory that lies at the crossroads of air quality and criminal mischief.
Now, let's dive into the nitty-gritty - or should I say the "dirty" details? Our study, spanning an impressive temporal range of nearly four decades, dived deep into the labyrinth of air pollution levels in Atlanta and the occurrence of motor vehicle theft in Georgia. Picture us as intrepid explorers, equipped with nothing but our statistical compass and a sense of humor - after all, in this "crime scene," laughter might just be the best medicine.
Delving into the treasure trove of numbers and graphs, we stumbled upon a rather astoundingly high correlation coefficient of 0.8035113 and a p-value of less than 0.01. Now, before you accuse us of grand larceny of significance, or worse - data manipulation, rest assured, dear readers, that these findings are as solid as a well-locked car door.
Our aim is not to be thieves of your attention, but rather to illuminate the unexpected nexus between air quality and criminal pursuits. We aim to paint a picture that is more than just black and white; amidst the shades of gray, we hope to capture the subtle nuances and interplay of factors that influence criminal behavior.
So, fasten your seatbelts, as we embark on a journey to untangle this intriguing riddle. It's more than just a statistical escapade; it's a pursuit of understanding, wrapped in a blanket of science, seasoned with a dash of humor, and served with a side of wry skepticism. After all, who said unraveling a scientific mystery couldn't be fun? Or at least, pun-derful.
[[RESULTS]]
Having embarked on our statistical adventure with open minds (and open noses in the case of air pollution), we found ourselves facing the startling revelation of a robust relationship between air pollution in Atlanta and motor vehicle thefts in Georgia. The correlation coefficient of 0.8035113 danced before our eyes, akin to a well-choreographed car chase scene. This correlation was not a mere flirtation; it was a full-blown affair between the pungent particles lingering in the air and the allure of a stolen ride.
Fig. 1 presents a scatterplot that artistically captures the strong link we uncovered, almost as if the data points themselves conspired to tell a tale of their own. It's as if every stolen car whispered, "I took a breath of fresh air on the way out," defying the conventional wisdom that these variables are as far apart as a clean getaway and a cloud of smog.
Now, let's address the elephant in the room – or should we say, the exhaust emissions in the laboratory? Yes, we are well aware that correlation does not imply causation, but it's hard to ignore the suggestive implications of our findings. It’s like finding a guilty fingerprint on the scene of a crime – it doesn’t immediately prove guilt, but it sure warrants a closer investigation.
You might be wondering, “What are the odds of this correlation occurring by mere chance?” Well, we’re here to tell you that the odds are as slim as a cat burglar squeezing through a tiny window. With an r-squared value of 0.6456304 and a p-value of less than 0.01, we can confidently say that this connection is not a random caper but a well-planned heist of statistical significance.
In the words of a seasoned detective, we are inclined to believe that there is smoke without a fire somewhere. Our findings not only challenge the status quo but also leave us pondering whether the proverbial "smoke and fire" can be extended to the “pollution and theft” scenario. It seems that in this case, the scent of foul air and the allure of an ill-gotten ride might just be partners in crime, or at least in statistical mischief.
As we reflect on our research, we can't help but chuckle at the unexpected bridge we found between pollution and pilferage. It’s almost poetic – a tale of environmental woes and criminal maneuvers, each dancing to the tune of the other. As we close this chapter, we hope our findings serve as a vehicle for deeper exploration into the hidden connections that thread through our world, and encourage others to sniff out the unexpected links in science.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
As we wrap up our investigation into the intricate ballet between air pollution and motor vehicle theft, we find ourselves with more than just food for thought – we have what can only be described as ambiguous odiferous evidence. The correlation coefficient of 0.8035113 and a p-value of less than 0.01 not only tickle the fancy of statistical enthusiasts but also raise some metaphorical eyebrows. This relationship is more intertwined than a cunning thief in a web of deceit. It seems that the smoggy air and the heists had more in common than we initially suspected – talk about a breath of fresh air in the world of research!
Our findings do not simply raise eyebrows; they raise questions – much like a curious cat burglar prowling in the night. While correlation does not equal causation, this connection has left us with a lingering suspicion. It’s like finding a getaway car with a questionable air freshener – quite the aromatic paradox. However, let’s not jump to conclusions just yet; we mustn’t let our excitement steal the spotlight.
In the wise words of a seasoned detective, it seems that there's more than a whiff of smoke; there must be a flickering flame somewhere, waiting to be discovered. But let’s not overinflate this discovery's tires – it’s not time to drive off into wild conjectures just yet. However, we can confidently say that this link cannot be waved off as a statistical fluke; it’s as clear as a well-polished windshield.
As we park this adventure in the realm of environmental epidemiology and criminology, we propose that no further research is needed in this area. Our research, like a secure car alarm, has sounded an alert, revealing an unexpected link between two seemingly unrelated phenomena. It's time to put the brakes on additional studies and hit the open road of discovery in other uncharted territories. This conclusion is as solid as a locked car door – no need to break in for more insights here!
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 Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Environmental Quirks
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 Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled. Respond only with the name of a fictional organization.
ChatGPT:
The Society for Whimsical Environmental 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 Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled with an abstract of The relationship between environmental pollution and criminal activity has often been brushed aside as mere happenstance, but our research seeks to clear the air on this matter. Through a comprehensive analysis of air pollution levels in Atlanta and motor vehicle theft rates in Georgia, we aimed to unravel the veil of correlation. Our findings reveal a striking connection between these seemingly unrelated phenomena, leaving us to ponder whether the heist gets a breath of fresh air from the polluted atmosphere. Our study, spanning nearly four decades, unveils a correlation coefficient of 0.8035113 and a p-value of less than 0.01, not to steal the spotlight, but certainly worth breathing in. With these results, we wave goodbye to the notion that air pollution and car thefts are simply a coincidental coexistence. We hope this research sparks a clean getaway from the assumption that these issues are unrelated, and sheds light on the unseen connections between air quality and criminal behavior.
ChatGPT:
air pollution, automobile theft, environmental pollution, criminal activity, pollution levels, motor vehicle theft rates, Atlanta, Georgia, correlation, correlation coefficient, p-value, clean getaway, air quality, criminal behavior
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Air pollution in AtlantaDetailed data title: Percentage of days with air quality at 'unhealthy for sensitive groups' or worse in Atlanta-Sandy Springs-Roswell, GA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Atlanta
Motor vehicle thefts in Georgia
Detailed data title: The motor vehicle theft rate per 100,000 residents in Georgia
Source: FBI Criminal Justice Information Services
See what else correlates with Motor vehicle thefts in Georgia
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 = 0.6456304 (Coefficient of determination)
This means 64.6% of the change in the one variable (i.e., Motor vehicle thefts in Georgia) is predictable based on the change in the other (i.e., Air pollution in Atlanta) over the 38 years from 1985 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.3E-9. 0.0000000012587107007604173000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.
But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.
Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.8 in 1.3E-7% of random cases. Said differently, if you correlated 794,463,731 random variables You don't actually need 794 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 37 degrees of freedom, 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.
[ 0.65, 0.89 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
| 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 | |
| Air pollution in Atlanta (Bad air quality days) | 10.6849 | 20.8219 | 26.8493 | 27.0492 | 19.726 | 29.863 | 19.4521 | 17.4863 | 26.8493 | 15.0685 | 23.2877 | 19.3989 | 19.1781 | 29.863 | 35.3425 | 31.4208 | 22.4658 | 19.4521 | 15.6164 | 14.2077 | 18.6301 | 23.5616 | 22.7397 | 14.4809 | 6.57534 | 12.8767 | 18.3562 | 7.65027 | 3.56164 | 4.93151 | 4.38356 | 8.74317 | 3.0137 | 2.73973 | 5.20548 | 0.819672 | 2.19178 | 2.46575 |
| Motor vehicle thefts in Georgia (Motor Vehicle Theft rate) | 369 | 430.3 | 492.4 | 554.6 | 653.7 | 673.6 | 611.3 | 576.4 | 593.8 | 557.2 | 608.4 | 628.5 | 595.4 | 556.6 | 515.1 | 472.8 | 447.2 | 445.2 | 500.1 | 496 | 487 | 460.6 | 445.5 | 409.3 | 337.4 | 312.4 | 302.5 | 288.5 | 271.7 | 274.9 | 266.2 | 256.6 | 250 | 241.2 | 211.6 | 238.2 | 192.1 | 206.5 |
Why this works
- Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
- Lack of causal connection: There is probably
Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied. - Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple
Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.Step 2: Open a plaintext editor like Notepad and paste the code below into it.
Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"
Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.
Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.
Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.
Step 7: Run the Python script by typing "python calculate_correlation.py"
If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:
"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."
# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats
# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):
# Calculate Pearson correlation coefficient and p-value
correlation, p_value = stats.pearsonr(array1, array2)
# Calculate R-squared as the square of the correlation coefficient
r_squared = correlation**2
return correlation, r_squared, p_value
# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([10.6849,20.8219,26.8493,27.0492,19.726,29.863,19.4521,17.4863,26.8493,15.0685,23.2877,19.3989,19.1781,29.863,35.3425,31.4208,22.4658,19.4521,15.6164,14.2077,18.6301,23.5616,22.7397,14.4809,6.57534,12.8767,18.3562,7.65027,3.56164,4.93151,4.38356,8.74317,3.0137,2.73973,5.20548,0.819672,2.19178,2.46575,])
array_2 = np.array([369,430.3,492.4,554.6,653.7,673.6,611.3,576.4,593.8,557.2,608.4,628.5,595.4,556.6,515.1,472.8,447.2,445.2,500.1,496,487,460.6,445.5,409.3,337.4,312.4,302.5,288.5,271.7,274.9,266.2,256.6,250,241.2,211.6,238.2,192.1,206.5,])
array_1_name = "Air pollution in Atlanta"
array_2_name = "Motor vehicle thefts in Georgia"
# 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
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Download images for these variables:
- High resolution line chart
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 Air pollution in Atlanta
- Line chart for only Motor vehicle thefts in Georgia
- AI-generated correlation image
- The spurious research paper: Air Pollution and Automobile Theft: A Rhyming Riddle Unveiled
You're a rater extraordinaire!
Correlation ID: 5423 · Black Variable ID: 20291 · Red Variable ID: 20136
