Spurious correlation #5,746 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Los Angeles and the second variable is Global revenue generated by McDonald's. The chart goes from 2005 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 Air pollution in Los Angeles and the second variable is Global revenue generated by McDonald's. The chart goes from 2005 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As air pollution in Los Angeles rose, people found themselves drawn to the familiar golden arches of McDonald's. It seems the smog acted as a 'McMuffler', leading to a surge in cravings for fast food. As the pollution levels beefed up, so did McDonald's profits, proving that when it comes to a toxic love for fast food, there's no air-clearing the cravings!

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image of the smog-covered Los Angeles skyline with a prominent, glowing pair of golden arches emerging from the haze. The McDonald's restaurant stands as a beacon in the pollution, drawing in a crowd of customers amidst the eerie atmosphere. The scene should capture the contrast between the murky surroundings and the vibrant allure of the fast food establishment, highlighting the peculiar magnetism of the smog in attracting customers to the iconic golden arches. 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 Los Angeles and Global revenue generated by McDonald's. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: An image that looks like it is a scene from A Disney Movie Cyber folk Cute cartoon Scalar art Woodblock painting
ChatGPT: Scalar art

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Los Angeles and Global revenue generated by McDonald's, in the following situation: As air pollution in Los Angeles rose, people found themselves drawn to the familiar golden arches of McDonald's. It seems the smog acted as a 'McMuffler', leading to a surge in cravings for fast food. As the pollution levels beefed up, so did McDonald's profits, proving that when it comes to a toxic love for fast food, there's no air-clearing the cravings!. Keep the description simple.
ChatGPT: The smog in Los Angeles loomed heavily over the city, creating a hazy skyline. Amidst the pollution, a bright and unmistakable pair of golden arches rose up, marking a bustling McDonald's restaurant. Customers flocked to the familiar sight, seeking comfort in the fast food offerings. The smog seemed to act as a peculiar magnet, drawing in more customers and boosting the revenue for the iconic fast food chain.

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: [ Scalar art ] and depicting this scene: The smog in Los Angeles loomed heavily over the city, creating a hazy skyline. Amidst the pollution, a bright and unmistakable pair of golden arches rose up, marking a bustling McDonald's restaurant. Customers flocked to the familiar sight, seeking comfort in the fast food offerings. The smog seemed to act as a peculiar magnet, drawing in more customers and boosting the revenue for the iconic fast food chain. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of the smog-covered Los Angeles skyline with a prominent, glowing pair of golden arches emerging from the haze. The McDonald's restaurant stands as a beacon in the pollution, drawing in a crowd of customers amidst the eerie atmosphere. The scene should capture the contrast between the murky surroundings and the vibrant allure of the fast food establishment, highlighting the peculiar magnetism of the smog in attracting customers to the iconic golden arches.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Air pollution in Los Angeles caused Global revenue generated by McDonald's to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Flipping the Golden Arches: Unveiling the Link Between Air Pollution in Los Angeles and McDonald's Global Pie

The Journal of Environmental Gastronomy

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 Air pollution in Los Angeles and Global revenue generated by McDonald's. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
"Flipping the Golden Arches: Unveiling the Link Between Air Pollution in Los Angeles and McDonald's Global Pie"

[[ABSTRACT]]
In this study, we unravel the undeniable connection between air pollution in the picturesque city of Los Angeles and the global revenue generated by the ubiquitous fast-food chain, McDonald's. Armed with data from the Environmental Protection Agency and Statista, we embarked on this journey to unveil the surprise correlation, aiming to shed light on an unexpected relationship. The correlation coefficient of 0.8291078 and p < 0.01 for the time span of 2005 to 2022 left us with more questions than answers, akin to a drive-thru order gone awry.

The findings of this research provide empirical evidence that points to a previously unnoticed relationship between the air quality index in Los Angeles and the global success of McDonald's. The numbers suggested that as the air in LA became more polluted, the golden arches around the world seemed to rake in more revenue, leaving us pondering the age-old question: is there a secret sauce in the smog that fuels the appetite for fast food? It’s like a McFlurry of unexpected connections, leaving us with a mix of intrigue and a craving for fries.

Our study not only offers a novel perspective on the interconnected nature of environmental factors and global economic trends but also beckons for further investigation into the enigmatic forces at play within these disparate realms. With a side of fries and a witty joke, this research aims to spark a refreshing conversation at the intersection of environmental studies and business economics, proving that even the unlikeliest pairings can find common ground – just like a burger and fries.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between environmental factors and economic trends has long been a subject of scholarly inquiry, often leading researchers to unexpected discoveries and the occasional existential crisis. In this vein, our study aims to uncover the enigmatic connection between the air quality index in Los Angeles and the global revenue generated by the ever-present fast-food titan, McDonald's. It's almost like finding a pickle in the middle of a Big Mac – unexpected, slightly puzzling, and yet strangely intriguing.
As we delve into the labyrinth of data and statistical analyses, akin to navigating through a maze of chicken nuggets, we seek to uncover the underlying correlation between the clear blue skies of Los Angeles and the golden pies of McDonald's global revenue. It's a bit like trying to figure out the ratio of sesame seeds to bun size on a classic Big Mac – challenging, but ultimately worth the journey.
Armed with data from the Environmental Protection Agency and the formidable database of Statista, we endeavor to shine a light on this unexplored relationship, opening a window into the intertwined world of environmental factors and corporate profitability. It's like uncovering the secret menu items of statistical phenomena – surprising, often debunking expectations, and leaving us with a new flavor of insight.
With a correlation coefficient of 0.8291078 and a p-value less than 0.01 for the period spanning from 2005 to 2022, our findings present us with an intriguing puzzle, much like trying to solve a riddle about why the chicken crossed the road to get to the Big Mac on the other side. The statistical significance of our results begs the question: is there a hidden variable we have yet to uncover, much like the mystery behind the special sauce in the iconic Big Mac?
Indeed, the implications of our findings transcend the realm of fast-food economics and environmental science, presenting a tantalizing conundrum that warrants further exploration, much like the unyielding mystery of why the McFlurry machine always seems to be out of order when you need it the most. This research opens the door to a fresh perspective at the intersection of seemingly disparate disciplines, inviting scholars to explore the unexpected connections and synergies that lie beneath the surface, much like finding the golden fries at the bottom of the bag.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The literature surrounding the correlation between air pollution and economic indicators has been a subject of extensive inquiry, with researchers striving to untangle the intricate web of connections. Smith et al. (2010) explored the impact of air quality on business performance, shedding light on the unexpected ways in which environmental factors can influence economic outcomes. Similarly, Doe and Jones (2015) delved into the relationship between urban pollution and consumer behavior, offering valuable insights into the unforeseen effects of smog on commercial activities. These studies lay the groundwork for our investigation, as we embark on a quest to uncover the surprising connection between air pollution in Los Angeles and the global revenue generated by the illustrious purveyor of fast food, McDonald's.

Now, let's dabble in a more unconventional set of sources. In "The Economics of Fast Food" by Foodie McFooderson (2018), the author examines the economic impact of fast-food chains on global consumer spending, providing a tantalizing backdrop for our exploration of the connection between air quality and fast-food revenue. As we continue down this path, we encounter "The Smoggy Mystery" by A. Q. Index (2016), a work of fiction that intertwines the allure of the fast-food industry with the enigmatic forces of environmental pollution. While not grounded in empirical research, this literary work offers a whimsical perspective that prompts us to ponder the uncharted territory of our investigation.

And now for a palate cleanser in the form of a relevant dad joke: Did you hear about the fast-food restaurant on the moon? Great food, no atmosphere!

Shifting gears, the impact of air pollution on global economic trends has also found its way into the realm of popular culture, with internet memes such as the "McDonald's Smog Special" highlighting the quirky juxtaposition of environmental concerns and fast-food cravings. This meme, akin to a digital work of art, invites us to consider the unexpected intersections of pollution awareness and dietary preferences in a lighthearted and slightly cheesy manner.

But I digress. Returning to the scholarly pursuits at hand, our exploration of the correlation between air pollution in Los Angeles and the global revenue generated by McDonald's proves to be an intriguing endeavor, reminiscent of peeling back the layers of an onion – except in this case, the layers are made of golden fries, and the tears are tears of joy.

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 Air pollution in Los Angeles and Global revenue generated by McDonald's. 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 Statista . You used data from 2005 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]]
"Flipping the Golden Arches: Unveiling the Link Between Air Pollution in Los Angeles and McDonald's Global Pie"

[[ABSTRACT]]
In this study, we unravel the undeniable connection between air pollution in the picturesque city of Los Angeles and the global revenue generated by the ubiquitous fast-food chain, McDonald's. Armed with data from the Environmental Protection Agency and Statista, we embarked on this journey to unveil the surprise correlation, aiming to shed light on an unexpected relationship. The correlation coefficient of 0.8291078 and p < 0.01 for the time span of 2005 to 2022 left us with more questions than answers, akin to a drive-thru order gone awry.

The findings of this research provide empirical evidence that points to a previously unnoticed relationship between the air quality index in Los Angeles and the global success of McDonald's. The numbers suggested that as the air in LA became more polluted, the golden arches around the world seemed to rake in more revenue, leaving us pondering the age-old question: is there a secret sauce in the smog that fuels the appetite for fast food? It’s like a McFlurry of unexpected connections, leaving us with a mix of intrigue and a craving for fries.

Our study not only offers a novel perspective on the interconnected nature of environmental factors and global economic trends but also beckons for further investigation into the enigmatic forces at play within these disparate realms. With a side of fries and a witty joke, this research aims to spark a refreshing conversation at the intersection of environmental studies and business economics, proving that even the unlikeliest pairings can find common ground – just like a burger and fries.

[[INTRODUCTION]]
The relationship between environmental factors and economic trends has long been a subject of scholarly inquiry, often leading researchers to unexpected discoveries and the occasional existential crisis. In this vein, our study aims to uncover the enigmatic connection between the air quality index in Los Angeles and the global revenue generated by the ever-present fast-food titan, McDonald's. It's almost like finding a pickle in the middle of a Big Mac – unexpected, slightly puzzling, and yet strangely intriguing.
As we delve into the labyrinth of data and statistical analyses, akin to navigating through a maze of chicken nuggets, we seek to uncover the underlying correlation between the clear blue skies of Los Angeles and the golden pies of McDonald's global revenue. It's a bit like trying to figure out the ratio of sesame seeds to bun size on a classic Big Mac – challenging, but ultimately worth the journey.
Armed with data from the Environmental Protection Agency and the formidable database of Statista, we endeavor to shine a light on this unexplored relationship, opening a window into the intertwined world of environmental factors and corporate profitability. It's like uncovering the secret menu items of statistical phenomena – surprising, often debunking expectations, and leaving us with a new flavor of insight.
With a correlation coefficient of 0.8291078 and a p-value less than 0.01 for the period spanning from 2005 to 2022, our findings present us with an intriguing puzzle, much like trying to solve a riddle about why the chicken crossed the road to get to the Big Mac on the other side. The statistical significance of our results begs the question: is there a hidden variable we have yet to uncover, much like the mystery behind the special sauce in the iconic Big Mac?
Indeed, the implications of our findings transcend the realm of fast-food economics and environmental science, presenting a tantalizing conundrum that warrants further exploration, much like the unyielding mystery of why the McFlurry machine always seems to be out of order when you need it the most. This research opens the door to a fresh perspective at the intersection of seemingly disparate disciplines, inviting scholars to explore the unexpected connections and synergies that lie beneath the surface, much like finding the golden fries at the bottom of the bag.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To tackle the perplexing question of the apparent link between air pollution in Los Angeles and the global revenue of McDonald's, we embarked on a quest that could rival the arduous journey of finding the last chicken nugget at the bottom of the packet. Our research team scoured through the treasure trove of data from the Environmental Protection Agency and Statista, utilizing a mix of statistical and computational methods – a concoction as intriguing as the elusive blend of ingredients in a McRib sandwich.

First, we gathered historical air quality index (AQI) data for Los Angeles from 2005 to 2022, noting the variations in particulate matter, nitrogen dioxide, and ozone levels – a process akin to uncovering the layers of condiments in a Big Mac, carefully dissecting each element to understand its impact. We then delved into the labyrinth of McDonald's global revenue figures for the same time span, navigating through the intricate web of financial reports and market analyses – a journey not unlike navigating the countless options on a McDonald's menu board.

Next, we performed a series of rigorous statistical analyses, employing techniques as diverse as a Happy Meal toy collection. We calculated the correlation coefficient between the AQI in Los Angeles and McDonald's global revenue, using the same level of precision as determining the optimal fry-to-salt ratio – a delicate balance crucial for the perfect flavor. Additionally, we conducted a regression analysis to discern the potential causal relationship between air pollution and fast-food financial success, wielding statistical tools with the finesse of a chef assembling the perfect Big Mac.

To ensure the robustness of our findings, we employed a variety of quality control measures, meticulously checking for outliers and influential data points – much like ensuring that every fry in the batch meets the golden standard. We also conducted sensitivity analyses, probing the stability of our results against different model specifications, akin to taste-testing the consistency of the special sauce to ensure its uniform appeal.

Furthermore, we considered various potential confounding variables, such as demographic shifts, economic indicators, and changes in consumer behavior, much like examining the diverse components of a Happy Meal to understand their collective influence. Through advanced statistical techniques, we sought to isolate the distinct impact of air pollution on McDonald's global revenue, akin to distinguishing the unique flavor profile of each item on the menu.

In this way, our methodology captures the essence of unraveling an intricate puzzle, akin to piecing together the enigmatic allure of a Happy Meal toy, leading us to the surprising revelation of the hidden link between smog-filled skies and the golden arches of fast-food supremacy.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Los Angeles and Global revenue generated by McDonald's. 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 Statista .

For the time period 2005 to 2022, you found a correlation 0.8291078, r-squared of 0.6874198, 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]]
"Flipping the Golden Arches: Unveiling the Link Between Air Pollution in Los Angeles and McDonald's Global Pie"

[[ABSTRACT]]
In this study, we unravel the undeniable connection between air pollution in the picturesque city of Los Angeles and the global revenue generated by the ubiquitous fast-food chain, McDonald's. Armed with data from the Environmental Protection Agency and Statista, we embarked on this journey to unveil the surprise correlation, aiming to shed light on an unexpected relationship. The correlation coefficient of 0.8291078 and p < 0.01 for the time span of 2005 to 2022 left us with more questions than answers, akin to a drive-thru order gone awry.

The findings of this research provide empirical evidence that points to a previously unnoticed relationship between the air quality index in Los Angeles and the global success of McDonald's. The numbers suggested that as the air in LA became more polluted, the golden arches around the world seemed to rake in more revenue, leaving us pondering the age-old question: is there a secret sauce in the smog that fuels the appetite for fast food? It’s like a McFlurry of unexpected connections, leaving us with a mix of intrigue and a craving for fries.

Our study not only offers a novel perspective on the interconnected nature of environmental factors and global economic trends but also beckons for further investigation into the enigmatic forces at play within these disparate realms. With a side of fries and a witty joke, this research aims to spark a refreshing conversation at the intersection of environmental studies and business economics, proving that even the unlikeliest pairings can find common ground – just like a burger and fries.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The relationship between environmental factors and economic trends has long been a subject of scholarly inquiry, often leading researchers to unexpected discoveries and the occasional existential crisis. In this vein, our study aims to uncover the enigmatic connection between the air quality index in Los Angeles and the global revenue generated by the ever-present fast-food titan, McDonald's. It's almost like finding a pickle in the middle of a Big Mac – unexpected, slightly puzzling, and yet strangely intriguing.
As we delve into the labyrinth of data and statistical analyses, akin to navigating through a maze of chicken nuggets, we seek to uncover the underlying correlation between the clear blue skies of Los Angeles and the golden pies of McDonald's global revenue. It's a bit like trying to figure out the ratio of sesame seeds to bun size on a classic Big Mac – challenging, but ultimately worth the journey.
Armed with data from the Environmental Protection Agency and the formidable database of Statista, we endeavor to shine a light on this unexplored relationship, opening a window into the intertwined world of environmental factors and corporate profitability. It's like uncovering the secret menu items of statistical phenomena – surprising, often debunking expectations, and leaving us with a new flavor of insight.
With a correlation coefficient of 0.8291078 and a p-value less than 0.01 for the period spanning from 2005 to 2022, our findings present us with an intriguing puzzle, much like trying to solve a riddle about why the chicken crossed the road to get to the Big Mac on the other side. The statistical significance of our results begs the question: is there a hidden variable we have yet to uncover, much like the mystery behind the special sauce in the iconic Big Mac?
Indeed, the implications of our findings transcend the realm of fast-food economics and environmental science, presenting a tantalizing conundrum that warrants further exploration, much like the unyielding mystery of why the McFlurry machine always seems to be out of order when you need it the most. This research opens the door to a fresh perspective at the intersection of seemingly disparate disciplines, inviting scholars to explore the unexpected connections and synergies that lie beneath the surface, much like finding the golden fries at the bottom of the bag.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of the relationship between air pollution in Los Angeles and the global revenue generated by McDonald's yielded a correlation coefficient of 0.8291078, indicating a strong positive correlation between these two seemingly unrelated variables. It's like finding the missing piece of a McNugget puzzle – unexpected, undoubtedly satisfying, and leaving us with a sense of accomplishment. The r-squared value of 0.6874198 further attested to the robustness of the relationship, much like the reliability of the ice cream machine being out of service at your local Mickey D’s.

The p-value being less than 0.01 emphasized the statistical significance of this connection, leaving us no choice but to acknowledge the unexpected bond between air pollution in the City of Angels and the worldwide appetite for Big Macs and Happy Meals. It's as surprising as getting an extra nugget in your meal – surely delightful but not entirely anticipated.

Figure 1 illustrates the scatterplot depicting the striking positive correlation between air pollution in Los Angeles and global revenue from McDonald's, mirroring the meteoric rise of demand for McFlurries on a hot summer day. The data points are aligned so closely, it's as if they were queuing up for the drive-thru at a particularly popular Mickey D's location, eagerly awaiting their turn for an environmental-economic fusion meal.

These findings prompt further investigation into the mechanisms underlying this intriguing relationship, akin to the mystery of why the fries always taste better when shared with friends. It seems that the smog of LA might hold the key to a puzzling yet lucrative pathway for fast-food giants, sparking contemplation reminiscent of pondering the number of pickles on a standard hamburger – inconspicuous, yet undeniably significant.

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 Air pollution in Los Angeles and Global revenue generated by McDonald's. 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]]
"Flipping the Golden Arches: Unveiling the Link Between Air Pollution in Los Angeles and McDonald's Global Pie"

[[ABSTRACT]]
In this study, we unravel the undeniable connection between air pollution in the picturesque city of Los Angeles and the global revenue generated by the ubiquitous fast-food chain, McDonald's. Armed with data from the Environmental Protection Agency and Statista, we embarked on this journey to unveil the surprise correlation, aiming to shed light on an unexpected relationship. The correlation coefficient of 0.8291078 and p < 0.01 for the time span of 2005 to 2022 left us with more questions than answers, akin to a drive-thru order gone awry.

The findings of this research provide empirical evidence that points to a previously unnoticed relationship between the air quality index in Los Angeles and the global success of McDonald's. The numbers suggested that as the air in LA became more polluted, the golden arches around the world seemed to rake in more revenue, leaving us pondering the age-old question: is there a secret sauce in the smog that fuels the appetite for fast food? It’s like a McFlurry of unexpected connections, leaving us with a mix of intrigue and a craving for fries.

Our study not only offers a novel perspective on the interconnected nature of environmental factors and global economic trends but also beckons for further investigation into the enigmatic forces at play within these disparate realms. With a side of fries and a witty joke, this research aims to spark a refreshing conversation at the intersection of environmental studies and business economics, proving that even the unlikeliest pairings can find common ground – just like a burger and fries.

[[LITERATURE REVIEW]]
The literature surrounding the correlation between air pollution and economic indicators has been a subject of extensive inquiry, with researchers striving to untangle the intricate web of connections. Smith et al. (2010) explored the impact of air quality on business performance, shedding light on the unexpected ways in which environmental factors can influence economic outcomes. Similarly, Doe and Jones (2015) delved into the relationship between urban pollution and consumer behavior, offering valuable insights into the unforeseen effects of smog on commercial activities. These studies lay the groundwork for our investigation, as we embark on a quest to uncover the surprising connection between air pollution in Los Angeles and the global revenue generated by the illustrious purveyor of fast food, McDonald's.
Now, let's dabble in a more unconventional set of sources. In "The Economics of Fast Food" by Foodie McFooderson (2018), the author examines the economic impact of fast-food chains on global consumer spending, providing a tantalizing backdrop for our exploration of the connection between air quality and fast-food revenue. As we continue down this path, we encounter "The Smoggy Mystery" by A. Q. Index (2016), a work of fiction that intertwines the allure of the fast-food industry with the enigmatic forces of environmental pollution. While not grounded in empirical research, this literary work offers a whimsical perspective that prompts us to ponder the uncharted territory of our investigation.
And now for a palate cleanser in the form of a relevant dad joke: Did you hear about the fast-food restaurant on the moon? Great food, no atmosphere!
Shifting gears, the impact of air pollution on global economic trends has also found its way into the realm of popular culture, with internet memes such as the "McDonald's Smog Special" highlighting the quirky juxtaposition of environmental concerns and fast-food cravings. This meme, akin to a digital work of art, invites us to consider the unexpected intersections of pollution awareness and dietary preferences in a lighthearted and slightly cheesy manner.
But I digress. Returning to the scholarly pursuits at hand, our exploration of the correlation between air pollution in Los Angeles and the global revenue generated by McDonald's proves to be an intriguing endeavor, reminiscent of peeling back the layers of an onion – except in this case, the layers are made of golden fries, and the tears are tears of joy.

[[RESULTS]]
The analysis of the relationship between air pollution in Los Angeles and the global revenue generated by McDonald's yielded a correlation coefficient of 0.8291078, indicating a strong positive correlation between these two seemingly unrelated variables. It's like finding the missing piece of a McNugget puzzle – unexpected, undoubtedly satisfying, and leaving us with a sense of accomplishment. The r-squared value of 0.6874198 further attested to the robustness of the relationship, much like the reliability of the ice cream machine being out of service at your local Mickey D’s.
The p-value being less than 0.01 emphasized the statistical significance of this connection, leaving us no choice but to acknowledge the unexpected bond between air pollution in the City of Angels and the worldwide appetite for Big Macs and Happy Meals. It's as surprising as getting an extra nugget in your meal – surely delightful but not entirely anticipated.
Figure 1 illustrates the scatterplot depicting the striking positive correlation between air pollution in Los Angeles and global revenue from McDonald's, mirroring the meteoric rise of demand for McFlurries on a hot summer day. The data points are aligned so closely, it's as if they were queuing up for the drive-thru at a particularly popular Mickey D's location, eagerly awaiting their turn for an environmental-economic fusion meal.
These findings prompt further investigation into the mechanisms underlying this intriguing relationship, akin to the mystery of why the fries always taste better when shared with friends. It seems that the smog of LA might hold the key to a puzzling yet lucrative pathway for fast-food giants, sparking contemplation reminiscent of pondering the number of pickles on a standard hamburger – inconspicuous, yet undeniably significant.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

In light of the unexpected yet compelling results revealing a significant positive correlation between air pollution in Los Angeles and global revenue generated by McDonald's, it becomes evident that there is more to this relationship than meets the eye. It's like discovering that the real golden ticket was hidden in the burgers all along – an unexpected twist that captures the imagination and leaves us pondering the mysteries of fast food and environmental influence.

Our findings align with the previous research by Smith et al. (2010) and Doe and Jones (2015), which highlighted the intricate interplay between environmental factors and economic outcomes. Just as a burger without cheese leaves a void, our study fills an intriguing gap in the literature by providing empirical evidence of the unanticipated connection between air quality and fast-food revenue. It's like stumbling upon a well-done burger when you ordered medium rare – surprisingly satisfying and unlike anything you expected.

As we reflect on the striking correlation coefficient of 0.8291078, we're reminded of the ancient riddle that asks, "What do you call a fake noodle? An impasta." While this correlation is anything but fake, its surprising nature and statistical significance invite a lighthearted air to the conversation, akin to the unexpected humor in a science-themed meme.

Furthermore, the literature review brought to the forefront the unconventional yet relevant sources that have contributed to the exploration of this correlation. While "The Smoggy Mystery" by A. Q. Index (2016) may be a work of fiction, its whimsical take on the interaction of fast-food economics and environmental pollution prompts a shift in perspective, much like finding a pickle in your french fries – a delightful surprise that challenges traditional expectations.

The p-value being less than 0.01 adds an element of statistical surprise to our endeavor, reminiscent of discovering that the toy in your Happy Meal is actually better quality than anticipated. It underlines the robustness of the connection, emphasizing the need to delve deeper into the mechanisms underlying this unexpected relationship.

While our findings may leave us with a side of fries and a freshly brewed research question, it's imperative to recognize the offbeat and intriguing nature of our discovery. Like a perfectly timed punchline, the correlation between air pollution in Los Angeles and the global revenue generated by McDonald's adds a touch of unexpected delight to the realms of environmental studies and business economics, leaving us eager to explore the enigmatic forces that bind them together.

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 Air pollution in Los Angeles and Global revenue generated by McDonald's. 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]]
"Flipping the Golden Arches: Unveiling the Link Between Air Pollution in Los Angeles and McDonald's Global Pie"

[[ABSTRACT]]
In this study, we unravel the undeniable connection between air pollution in the picturesque city of Los Angeles and the global revenue generated by the ubiquitous fast-food chain, McDonald's. Armed with data from the Environmental Protection Agency and Statista, we embarked on this journey to unveil the surprise correlation, aiming to shed light on an unexpected relationship. The correlation coefficient of 0.8291078 and p < 0.01 for the time span of 2005 to 2022 left us with more questions than answers, akin to a drive-thru order gone awry.

The findings of this research provide empirical evidence that points to a previously unnoticed relationship between the air quality index in Los Angeles and the global success of McDonald's. The numbers suggested that as the air in LA became more polluted, the golden arches around the world seemed to rake in more revenue, leaving us pondering the age-old question: is there a secret sauce in the smog that fuels the appetite for fast food? It’s like a McFlurry of unexpected connections, leaving us with a mix of intrigue and a craving for fries.

Our study not only offers a novel perspective on the interconnected nature of environmental factors and global economic trends but also beckons for further investigation into the enigmatic forces at play within these disparate realms. With a side of fries and a witty joke, this research aims to spark a refreshing conversation at the intersection of environmental studies and business economics, proving that even the unlikeliest pairings can find common ground – just like a burger and fries.

[[INTRDUCTION]]
The relationship between environmental factors and economic trends has long been a subject of scholarly inquiry, often leading researchers to unexpected discoveries and the occasional existential crisis. In this vein, our study aims to uncover the enigmatic connection between the air quality index in Los Angeles and the global revenue generated by the ever-present fast-food titan, McDonald's. It's almost like finding a pickle in the middle of a Big Mac – unexpected, slightly puzzling, and yet strangely intriguing.
As we delve into the labyrinth of data and statistical analyses, akin to navigating through a maze of chicken nuggets, we seek to uncover the underlying correlation between the clear blue skies of Los Angeles and the golden pies of McDonald's global revenue. It's a bit like trying to figure out the ratio of sesame seeds to bun size on a classic Big Mac – challenging, but ultimately worth the journey.
Armed with data from the Environmental Protection Agency and the formidable database of Statista, we endeavor to shine a light on this unexplored relationship, opening a window into the intertwined world of environmental factors and corporate profitability. It's like uncovering the secret menu items of statistical phenomena – surprising, often debunking expectations, and leaving us with a new flavor of insight.
With a correlation coefficient of 0.8291078 and a p-value less than 0.01 for the period spanning from 2005 to 2022, our findings present us with an intriguing puzzle, much like trying to solve a riddle about why the chicken crossed the road to get to the Big Mac on the other side. The statistical significance of our results begs the question: is there a hidden variable we have yet to uncover, much like the mystery behind the special sauce in the iconic Big Mac?
Indeed, the implications of our findings transcend the realm of fast-food economics and environmental science, presenting a tantalizing conundrum that warrants further exploration, much like the unyielding mystery of why the McFlurry machine always seems to be out of order when you need it the most. This research opens the door to a fresh perspective at the intersection of seemingly disparate disciplines, inviting scholars to explore the unexpected connections and synergies that lie beneath the surface, much like finding the golden fries at the bottom of the bag.

[[RESULTS]]
The analysis of the relationship between air pollution in Los Angeles and the global revenue generated by McDonald's yielded a correlation coefficient of 0.8291078, indicating a strong positive correlation between these two seemingly unrelated variables. It's like finding the missing piece of a McNugget puzzle – unexpected, undoubtedly satisfying, and leaving us with a sense of accomplishment. The r-squared value of 0.6874198 further attested to the robustness of the relationship, much like the reliability of the ice cream machine being out of service at your local Mickey D’s.
The p-value being less than 0.01 emphasized the statistical significance of this connection, leaving us no choice but to acknowledge the unexpected bond between air pollution in the City of Angels and the worldwide appetite for Big Macs and Happy Meals. It's as surprising as getting an extra nugget in your meal – surely delightful but not entirely anticipated.
Figure 1 illustrates the scatterplot depicting the striking positive correlation between air pollution in Los Angeles and global revenue from McDonald's, mirroring the meteoric rise of demand for McFlurries on a hot summer day. The data points are aligned so closely, it's as if they were queuing up for the drive-thru at a particularly popular Mickey D's location, eagerly awaiting their turn for an environmental-economic fusion meal.
These findings prompt further investigation into the mechanisms underlying this intriguing relationship, akin to the mystery of why the fries always taste better when shared with friends. It seems that the smog of LA might hold the key to a puzzling yet lucrative pathway for fast-food giants, sparking contemplation reminiscent of pondering the number of pickles on a standard hamburger – inconspicuous, yet undeniably significant.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has shed light on the surprising connection between air pollution in Los Angeles and the global revenue generated by McDonald's. The striking correlation coefficient and p-value have left us pondering the age-old question: is there a secret sauce in the smog that fuels the appetite for fast food? It's like a McFlurry of unexpected connections, leaving us with a mix of intrigue and a craving for fries.

The robust statistical evidence, combined with the playful spirit of exploration, suggests that this unforeseen relationship warrants further scrutiny – much like the persistent inquiry into the perennial question, "Why did the tomato turn red?" Because it saw the salad dressing. Our research opens the door to a world of unimaginable connections, much like discovering a forgotten french fry at the bottom of the bag.

However, it seems that no more research is needed in this area. Just like when the fries at the bottom of the bag are gone, the research on the connection between air pollution in Los Angeles and McDonald's global revenue has reached its satisfying conclusion.

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 Flipping the Golden Arches: Unveiling the Link Between Air Pollution in Los Angeles and McDonald's Global Pie. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Environmental Gastronomy

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 Flipping the Golden Arches: Unveiling the Link Between Air Pollution in Los Angeles and McDonald's Global Pie. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Urban Air Quality and Fast Food Consumption Patterns

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 Flipping the Golden Arches: Unveiling the Link Between Air Pollution in Los Angeles and McDonald's Global Pie with an abstract of In this study, we unravel the undeniable connection between air pollution in the picturesque city of Los Angeles and the global revenue generated by the ubiquitous fast-food chain, McDonald's. Armed with data from the Environmental Protection Agency and Statista, we embarked on this journey to unveil the surprise correlation, aiming to shed light on an unexpected relationship. The correlation coefficient of 0.8291078 and p < 0.01 for the time span of 2005 to 2022 left us with more questions than answers, akin to a drive-thru order gone awry.
The findings of this research provide empirical evidence that points to a previously unnoticed relationship between the air quality index in Los Angeles and the global success of McDonald's. The numbers suggested that as the air in LA became more polluted, the golden arches around the world seemed to rake in more revenue, leaving us pondering the age-old question: is there a secret sauce in the smog that fuels the appetite for fast food? It’s like a McFlurry of unexpected connections, leaving us with a mix of intrigue and a craving for fries.
Our study not only offers a novel perspective on the interconnected nature of environmental factors and global economic trends but also beckons for further investigation into the enigmatic forces at play within these disparate realms. With a side of fries and a witty joke, this research aims to spark a refreshing conversation at the intersection of environmental studies and business economics, proving that even the unlikeliest pairings can find common ground – just like a burger and fries.

ChatGPT:

"air pollution Los Angeles McDonald's correlation," "environmental impact fast food industry," "global revenue fast food chains air quality index," "connection air pollution global economic trends," "air quality index Los Angeles environmental effects," "impact of pollution on fast food consumption," "McDonald's success air pollution Los Angeles," "relationship between air pollution and fast food sales," "empirical evidence air pollution economic success"

*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 Los Angeles
Detailed data title: Percentage of days with moderate or worse air quality in Los Angeles-Long Beach-Anaheim, CA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Los Angeles

Global revenue generated by McDonald's
Source: Statista
See what else correlates with Global revenue generated by McDonald's

Correlation r = 0.8291078 (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 = 0.6874198 (Coefficient of determination)
This means 68.7% of the change in the one variable (i.e., Global revenue generated by McDonald's) is predictable based on the change in the other (i.e., Air pollution in Los Angeles) over the 18 years from 2005 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.11E-5.^Show 0.0000210748567842958940000000
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 0.83 in 0.00211% of random cases. Said differently, if you correlated 47,450 random variables^Note You don't actually need 47 thousand variables to find a correlation like this one. 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.

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 17 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 17 because we have two variables measured over a period of 18 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.

[ 0.59, 0.93 ] 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.

	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Air pollution in Los Angeles (Bad air quality days)	84.9315	84.3836	88.4931	93.1694	90.9589	91.2329	96.4384	91.2568	93.9726	93.6986	93.6986	91.2568	89.589	90.411	81.9178	83.6066	89.3151	89.0411
Global revenue generated by McDonald's (Billion US Dollars)	19.12	20.9	22.79	23.52	22.75	24.08	27.01	27.57	28.11	27.44	25.41	24.62	22.82	21.03	21.08	19.21	23.22	23.18

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^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([84.9315,84.3836,88.4931,93.1694,90.9589,91.2329,96.4384,91.2568,93.9726,93.6986,93.6986,91.2568,89.589,90.411,81.9178,83.6066,89.3151,89.0411,])
array_2 = np.array([19.12,20.9,22.79,23.52,22.75,24.08,27.01,27.57,28.11,27.44,25.41,24.62,22.82,21.03,21.08,19.21,23.22,23.18,])
array_1_name = "Air pollution in Los Angeles"
array_2_name = "Global revenue generated by McDonald's"

# 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
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Line chart for only Air pollution in Los Angeles
Line chart for only Global revenue generated by McDonald's
AI-generated correlation image
The spurious research paper: Flipping the Golden Arches: Unveiling the Link Between Air Pollution in Los Angeles and McDonald's Global Pie

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Correlation ID: 5746 · Black Variable ID: 20840 · Red Variable ID: 432


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