Spurious correlation #3,828 · 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 Bismarck, North Dakota and the second variable is Inflation in the US. The chart goes from 1992 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 Bismarck, North Dakota and the second variable is Inflation in the US. The chart goes from 1992 to 2022, and the two variables track closely in value over that time.

AI explanation

As the air pollution in Bismarck, North Dakota increased, it led to a higher demand for industrial-grade air fresheners across the country. This unexpected surge in air freshener purchases caused a domino effect, leading to a spike in the production costs of various goods. Ultimately, this sneaky inflationary pressure wafted its way into the calculation of the Consumer Price Index for Urban Consumers, eliciting a stinky situation for the economy.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a bustling street in Bismarck, North Dakota, where people are seen wearing stylish face masks. The air is thick with pollution, and the masks have become a fashionable accessory. Show the diverse range of mask designs and colors, reflecting the trendiness and demand for these accessories. The scene should convey a sense of urgency and increased consumer activity, highlighting the rising impact on the Consumer Price Index for Urban Consumers across the United States. 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 Bismarck, North Dakota and Consumer Price Index for Urban Consumers (CPI-U) in the United States. 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: Cubism Cybernetic art Realistic Concept art inspired by bauhaus
ChatGPT: Realistic

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Bismarck, North Dakota and Consumer Price Index for Urban Consumers (CPI-U) in the United States, in the following situation: Because the increase in air pollution in Bismarck led to everyone wearing face masks, the demand for stylish masks skyrocketed, causing an increase in the CPI-U as people went on a shopping spree for designer air filtration accessories! Who knew that smog could lead to high fashion inflation!. Keep the description simple.
ChatGPT: In Bismarck, North Dakota, the streets are bustling with people wearing stylish face masks as the air pollution has increased. The trendy masks have become a fashion statement, causing a surge in demand and prices, contributing to the rise in the Consumer Price Index for Urban Consumers across the United States.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Realistic ] and depicting this scene: In Bismarck, North Dakota, the streets are bustling with people wearing stylish face masks as the air pollution has increased. The trendy masks have become a fashion statement, causing a surge in demand and prices, contributing to the rise in the Consumer Price Index for Urban Consumers across the United States. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a bustling street in Bismarck, North Dakota, where people are seen wearing stylish face masks. The air is thick with pollution, and the masks have become a fashionable accessory. Show the diverse range of mask designs and colors, reflecting the trendiness and demand for these accessories. The scene should convey a sense of urgency and increased consumer activity, highlighting the rising impact on the Consumer Price Index for Urban Consumers across the United States.

*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 Bismarck, North Dakota caused Consumer Price Index for Urban Consumers (CPI-U) in the United States to increase. Make it feel plausible.

AI academic paper

(Because p < 0.01)

The Inflated Effects of Air Pollution: A Breath of Fresh Air from Bismarck, North Dakota

Journal of Environmental Pseudoscience

Jan 2024

^{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 Bismarck, North Dakota and Inflation in the US. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
The Inflated Effects of Air Pollution: A Breath of Fresh Air from Bismarck, North Dakota

[[ABSTRACT]]
In this study, we aim to investigate the unexpected correlation between air pollution in Bismarck, North Dakota and inflation in the United States. While on the surface, these two phenomena may seem as unrelated as a fish on a bicycle, our research has uncovered an intriguing connection.

Analyzing data from the Environmental Protection Agency and Statista spanning the period from 1992 to 2022, we found a striking correlation coefficient of 0.7705110 (p < 0.01) between air pollution levels in Bismarck and inflation in the US. It seems that air pollution may not only be causing respiratory distress; it may also be giving the US economy a case of inflationary hiccups.

Our findings raise important questions about the economic impact of environmental factors, providing a breath of fresh air to the field of environmental economics. Oh, the irony of polluted air having an "inflated" effect on the economy! This research sheds light on the unexpected ways in which seemingly disparate factors can influence one another, leaving us with a "breathtaking" revelation.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Air pollution and its impact on human health and the environment have been subjects of extensive research and public concern for decades. Similarly, inflation, the rise in the price of goods and services over time, has been a central issue in economic policy discussions. The connection between these two seemingly unconnected topics may appear as bizarre as a snowman in the desert, but our study delves into unearthing the surprising relationship between air pollution in Bismarck, North Dakota, and inflation in the United States.
As we embark on this journey to unravel the mysterious bond between these two seemingly unrelated phenomena, it is essential to recognize the gravity of our task. This is not a tale for the faint-hearted or a research topic for those without a sense of adventure. One might even say that exploring the connection between air pollution and inflation is akin to navigating through a fog of uncertainty, with the occasional whiff of statistical significance to guide our way. Just like a bad pun, this correlation cannot be ignored.
The city of Bismarck, North Dakota, situated along the Missouri River and known for its friendly residents and scenic beauty, takes center stage in our investigation. Oh, Bismarck - the capital city named after the founder of Germany's unified empire, Otto von Bismarck, and now playing a role in this unexpected economic drama. It seems this city has more to offer than just breathtaking sunsets and picturesque landscapes; its air pollution levels hold a surprise that not even the most astute economist could have predicted. It's almost as if Bismarck's air pollution is saying, "You can't inflate the importance of our role in this research!"
Our analysis, conducted with rigorous methodology and a determination not unlike a bloodhound on the trail of a scent, has revealed compelling results. The statistical correlation we have uncovered between air pollution in Bismarck and inflation in the United States is as clear as the North Dakota sky on a cloudless day. It's like finding a needle in a haystack, or in this case, a link between air quality and economic trends in an unexpected corner of the country.
In the words of a wise economist, "Correlation does not imply causation," but in our case, it certainly piques curiosity and raises an eyebrow or two. The connection we have unearthed acts as a reminder that even the most disparate elements in our world can sometimes march to the beat of the same drum. It's a bit like finding out that the air pollution in Bismarck is like the unsung hero of the US inflation story, quietly exerting its influence without a trace of recognition. Just like a good dad joke, the correlation between air pollution and inflation may cause some eye-rolling, but it's hard to ignore its impact.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The relationship between environmental factors and economic indicators has been a topic of interest to researchers across various fields. Smith and Doe (2005) examined the impact of air pollution on regional economic performance, while Jones (2010) investigated the influence of environmental factors on inflation dynamics. These studies have laid the groundwork for understanding the complex interplay between pollution and economic outcomes. Despite the solemn tone of these studies, the connection between air pollution and inflation, much like a well-timed dad joke, continues to surprise and amuse.

In "Economic Effects of Environmental Pollution," the authors find that air pollution can lead to reduced labor productivity and increased healthcare costs, painting a bleak picture of its impact on economic well-being. However, our study takes a different approach, uncovering the unexpected link between air pollution in Bismarck, North Dakota, and inflation in the United States. It's like stumbling upon a comedic twist in an otherwise serious narrative.

Moving beyond the realm of economics, environmental literature provides valuable insights into the broader consequences of air pollution. "Silent Spring" by Rachel Carson and "This Changes Everything" by Naomi Klein offer poignant accounts of the environmental and social ramifications of pollution, reminding us that the effects of air pollution extend far beyond economic indicators. These works serve as a sobering reminder amidst the lighthearted banter about air pollution and inflation - a solemn drumbeat amid the cacophony of puns.

In the realm of fiction, novels like "Cloud Atlas" by David Mitchell and "Choke" by Chuck Palahniuk offer imaginative explorations of societal and environmental challenges, perhaps unintentionally mirroring the peculiar connection between air pollution and inflation that we have uncovered. Just as fiction blurs the lines between reality and imagination, our research blurs the boundaries between seemingly unrelated phenomena, leaving us in a state of bemused contemplation.

To ensure a comprehensive review of the existing literature, we also ventured into unconventional territory, exploring the reaches of unconventional sources. From the back of shampoo bottles to the depths of internet memes, every source that mentioned air pollution and inflation was fair game. Don't worry, we maintained academic rigor even as we navigated the nonsensical landscape of non-peer-reviewed content.

In "The Shampoo Chronicles," the authors speculate on the potential link between air pollution particles and the rise in shampoo prices, in a comical twist that mirrors the unexpected correlation we have discovered. As we tiptoed through unconventional sources, braving the onslaught of absurd connections and quirky commentaries, we remained steadfast in our commitment to uncovering the truth, however impractical the journey may have seemed.

In conclusion, the literature on air pollution and inflation serves as a testament to the unexpected pleasures and surprises that research can unveil. From the solemn to the absurd, the serious to the fantastical, the existing body of literature has paved the way for our own whimsical exploration of the perplexing bond between polluted air in Bismarck, North Dakota, and inflation in the United States. And with each offbeat source we encountered, we were reminded of the wondrous, if slightly ludicrous, nature of academic inquiry.

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 Bismarck, North Dakota and Inflation in the US. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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 1992 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]]
The Inflated Effects of Air Pollution: A Breath of Fresh Air from Bismarck, North Dakota

[[ABSTRACT]]
In this study, we aim to investigate the unexpected correlation between air pollution in Bismarck, North Dakota and inflation in the United States. While on the surface, these two phenomena may seem as unrelated as a fish on a bicycle, our research has uncovered an intriguing connection.

Analyzing data from the Environmental Protection Agency and Statista spanning the period from 1992 to 2022, we found a striking correlation coefficient of 0.7705110 (p < 0.01) between air pollution levels in Bismarck and inflation in the US. It seems that air pollution may not only be causing respiratory distress; it may also be giving the US economy a case of inflationary hiccups.

Our findings raise important questions about the economic impact of environmental factors, providing a breath of fresh air to the field of environmental economics. Oh, the irony of polluted air having an "inflated" effect on the economy! This research sheds light on the unexpected ways in which seemingly disparate factors can influence one another, leaving us with a "breathtaking" revelation.

[[INTRODUCTION]]
Air pollution and its impact on human health and the environment have been subjects of extensive research and public concern for decades. Similarly, inflation, the rise in the price of goods and services over time, has been a central issue in economic policy discussions. The connection between these two seemingly unconnected topics may appear as bizarre as a snowman in the desert, but our study delves into unearthing the surprising relationship between air pollution in Bismarck, North Dakota, and inflation in the United States.
As we embark on this journey to unravel the mysterious bond between these two seemingly unrelated phenomena, it is essential to recognize the gravity of our task. This is not a tale for the faint-hearted or a research topic for those without a sense of adventure. One might even say that exploring the connection between air pollution and inflation is akin to navigating through a fog of uncertainty, with the occasional whiff of statistical significance to guide our way. Just like a bad pun, this correlation cannot be ignored.
The city of Bismarck, North Dakota, situated along the Missouri River and known for its friendly residents and scenic beauty, takes center stage in our investigation. Oh, Bismarck - the capital city named after the founder of Germany's unified empire, Otto von Bismarck, and now playing a role in this unexpected economic drama. It seems this city has more to offer than just breathtaking sunsets and picturesque landscapes; its air pollution levels hold a surprise that not even the most astute economist could have predicted. It's almost as if Bismarck's air pollution is saying, "You can't inflate the importance of our role in this research!"
Our analysis, conducted with rigorous methodology and a determination not unlike a bloodhound on the trail of a scent, has revealed compelling results. The statistical correlation we have uncovered between air pollution in Bismarck and inflation in the United States is as clear as the North Dakota sky on a cloudless day. It's like finding a needle in a haystack, or in this case, a link between air quality and economic trends in an unexpected corner of the country.
In the words of a wise economist, "Correlation does not imply causation," but in our case, it certainly piques curiosity and raises an eyebrow or two. The connection we have unearthed acts as a reminder that even the most disparate elements in our world can sometimes march to the beat of the same drum. It's a bit like finding out that the air pollution in Bismarck is like the unsung hero of the US inflation story, quietly exerting its influence without a trace of recognition. Just like a good dad joke, the correlation between air pollution and inflation may cause some eye-rolling, but it's hard to ignore its impact.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the curious connection between air pollution in Bismarck, North Dakota, and inflation in the United States, we employed a variety of data collection and analysis methods. Our research team carefully gathered data from reputable sources, primarily drawing from the Environmental Protection Agency (EPA) and Statista. This allowed us to obtain comprehensive datasets encompassing the period from 1992 to 2022, a time frame extensive enough to capture long-term trends and fluctuations. It's like we were sifting through a mountain of data, looking for the hidden treasure of correlation between air pollution and inflation, and boy did we strike gold.

The air pollution data for Bismarck was collected from numerous monitoring stations strategically positioned throughout the city. We always made sure to double-check the data, like skeptically examining the expiration date on a carton of milk, to ensure accuracy and reliability. We couldn't afford any "spoiled" data tainting our research, after all.

In tandem with the air pollution data, inflation rates for the US were obtained from official records and reputable economic databases. We meticulously combed through the numbers, like a forensic accountant hunting for discrepancies, to ensure the integrity of the inflation data. Nothing like a bit of number-crunching to get the blood pumping, or perhaps that's just the caffeine kicking in from a late-night data analysis session.

Employing sophisticated statistical tools such as regression analysis and time series modeling, we delved into the heart of the data, dissecting and scrutinizing it like a surgeon examining a complex case. This involved running numerous analyses to identify patterns, trends, and potential correlations. We wanted to make sure our findings weren't just a fluke, like discovering a four-leaf clover in a field of data.

The correlation coefficient was our guiding star in this research endeavor, serving as a measure of the strength and direction of the relationship between air pollution in Bismarck and inflation in the US. We also utilized advanced econometric techniques to control for potential confounding variables, ensuring that our results were robust and reliable. It's like we had to put on our detective hats to make sure the culprit in this correlation case wasn't falsely accused.

In addition to quantitative analyses, we conducted qualitative assessments through interviews and consultations with domain experts, adding a human touch to our rigorous methodology. We spoke to economists, environmental scientists, and even a few local North Dakotans, gathering insights and perspectives to enrich our understanding of the phenomenon. It's like a good old-fashioned gumshoe detective canvassing the neighborhood for clues, only in this case, the clues came in the form of expert opinions and anecdotal evidence.

Our research methodology was designed to leave no stone unturned and no decimal unexamined, ensuring that our findings would withstand the scrutiny of the academic community. It's like we were building a sturdy bridge between two seemingly separate worlds – the realm of air quality and the domain of economic indicators – to connect dots that were previously overlooked. And just like a well-timed dad joke, our methodology added some levity to the seriousness of academic research, reminding us not to take ourselves too seriously even in the pursuit of knowledge.

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 Bismarck, North Dakota and Inflation in the US. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
The Inflated Effects of Air Pollution: A Breath of Fresh Air from Bismarck, North Dakota

[[ABSTRACT]]
In this study, we aim to investigate the unexpected correlation between air pollution in Bismarck, North Dakota and inflation in the United States. While on the surface, these two phenomena may seem as unrelated as a fish on a bicycle, our research has uncovered an intriguing connection.

Analyzing data from the Environmental Protection Agency and Statista spanning the period from 1992 to 2022, we found a striking correlation coefficient of 0.7705110 (p < 0.01) between air pollution levels in Bismarck and inflation in the US. It seems that air pollution may not only be causing respiratory distress; it may also be giving the US economy a case of inflationary hiccups.

Our findings raise important questions about the economic impact of environmental factors, providing a breath of fresh air to the field of environmental economics. Oh, the irony of polluted air having an "inflated" effect on the economy! This research sheds light on the unexpected ways in which seemingly disparate factors can influence one another, leaving us with a "breathtaking" revelation.

[[LITERATURE REVIEW]]
The relationship between environmental factors and economic indicators has been a topic of interest to researchers across various fields. Smith and Doe (2005) examined the impact of air pollution on regional economic performance, while Jones (2010) investigated the influence of environmental factors on inflation dynamics. These studies have laid the groundwork for understanding the complex interplay between pollution and economic outcomes. Despite the solemn tone of these studies, the connection between air pollution and inflation, much like a well-timed dad joke, continues to surprise and amuse.
In "Economic Effects of Environmental Pollution," the authors find that air pollution can lead to reduced labor productivity and increased healthcare costs, painting a bleak picture of its impact on economic well-being. However, our study takes a different approach, uncovering the unexpected link between air pollution in Bismarck, North Dakota, and inflation in the United States. It's like stumbling upon a comedic twist in an otherwise serious narrative.
Moving beyond the realm of economics, environmental literature provides valuable insights into the broader consequences of air pollution. "Silent Spring" by Rachel Carson and "This Changes Everything" by Naomi Klein offer poignant accounts of the environmental and social ramifications of pollution, reminding us that the effects of air pollution extend far beyond economic indicators. These works serve as a sobering reminder amidst the lighthearted banter about air pollution and inflation - a solemn drumbeat amid the cacophony of puns.
In the realm of fiction, novels like "Cloud Atlas" by David Mitchell and "Choke" by Chuck Palahniuk offer imaginative explorations of societal and environmental challenges, perhaps unintentionally mirroring the peculiar connection between air pollution and inflation that we have uncovered. Just as fiction blurs the lines between reality and imagination, our research blurs the boundaries between seemingly unrelated phenomena, leaving us in a state of bemused contemplation.
To ensure a comprehensive review of the existing literature, we also ventured into unconventional territory, exploring the reaches of unconventional sources. From the back of shampoo bottles to the depths of internet memes, every source that mentioned air pollution and inflation was fair game. Don't worry, we maintained academic rigor even as we navigated the nonsensical landscape of non-peer-reviewed content.
In "The Shampoo Chronicles," the authors speculate on the potential link between air pollution particles and the rise in shampoo prices, in a comical twist that mirrors the unexpected correlation we have discovered. As we tiptoed through unconventional sources, braving the onslaught of absurd connections and quirky commentaries, we remained steadfast in our commitment to uncovering the truth, however impractical the journey may have seemed.
In conclusion, the literature on air pollution and inflation serves as a testament to the unexpected pleasures and surprises that research can unveil. From the solemn to the absurd, the serious to the fantastical, the existing body of literature has paved the way for our own whimsical exploration of the perplexing bond between polluted air in Bismarck, North Dakota, and inflation in the United States. And with each offbeat source we encountered, we were reminded of the wondrous, if slightly ludicrous, nature of academic inquiry.

[[RESULTS]]
The results of our investigation into the correlation between air pollution in Bismarck, North Dakota and inflation in the United States reveal a statistical correlation coefficient (r) of 0.7705110, with an r-squared of 0.5936872 and a p-value less than 0.01. This robust correlation suggests a strong relationship between these two seemingly disparate variables. It's as surprising as finding a porcupine in a balloon factory!
Figure 1 displays a scatterplot illustrating the notable connection between air pollution in Bismarck and inflation in the US. It's a visual representation that's as clear as an unpolluted sky, showcasing the unmistakable relationship between these two factors. You might say it's as eye-catching as a neon sign in a dense fog.
Our findings provide an intriguing insight into the potential economic implications of environmental factors. The correlation uncovered between air pollution and inflation is as unexpected as a penguin at a pool party, yet it underscores the need to consider the far-reaching effects of air quality on economic trends. In a way, it's like discovering that the butterfly effect isn't just a theoretical concept – it's a breeze that can ripple through the entire economy.
The durable correlation we observed challenges traditional economic wisdom, offering a fresh perspective on the interconnectedness of seemingly unrelated factors. The impact of air pollution from a charming city like Bismarck on the nation's inflation levels is as unexpected as a sudden plot twist in a detective novel. Our research casts a new light on the intricate dance of cause and effect in the economic arena, reminding us that sometimes, the most unlikely pairings can create an influential duet.
As we wrap up our exploration of this unanticipated relationship, it's clear that air pollution in Bismarck isn't just blowing smoke; it's leaving a mark on the economic landscape. The significance of this correlation may be as subtle as a pun in a serious conversation, but it commands attention and warrants further investigation.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our study has shed light on the profound, if somewhat unconventional, relationship between air pollution in Bismarck, North Dakota and inflation in the United States. While the connection may initially seem as outlandish as a penguin in the desert, our findings have revealed a robust correlation, as unmistakable as a bright red balloon in a clear blue sky. Our results not only confirm, but also amplify the prior research, reaffirming the unexpected and inexplicable link that has bewildered and intrigued scholars.

The established correlation coefficient of 0.7705110 and the striking r-squared value of 0.5936872 have substantiated the surprising association between these seemingly unrelated variables. It's as though we stumbled upon a punchline in the midst of a serious economic narrative - the air pollution in Bismarck isn't just causing respiratory distress; it's also causing the economy to catch a case of the "inflation sniffles."

Our findings dovetail with previous research, echoing the authors who, like detectives, stumbled upon an unexpected twist in the plot. The unexpected duo of air pollution and inflation holds implications as weighty as an elephant doing yoga - it challenges economic orthodoxy, infuses levity into dry academic debates, and ignites curiosity about the intricate mechanisms underpinning economic dynamics.

Figure 1 provides a visual manifestation of the connection between air pollution in Bismarck and inflation in the US. The scatterplot stands as an arresting depiction of the relationship, as conspicuous as a flashing neon sign in a dense fog, leaving little doubt about the compelling association between these two ostensibly dissimilar phenomena. It's like finding a needle in a haystack, only to realize the needle is made of spaghetti!

Our study, while certainly lighthearted in its presentation, underscores the need for further exploration of the economic consequences of environmental factors. Just as a well-timed pun can enliven a dull conversation, the unexpected correlation we have uncovered enlivens economic discourse, encouraging a reevaluation of the cascading impacts of seemingly minor environmental influences.

In essence, our findings engender a new perspective on the intricate web of cause and effect in the economic domain. The pervasive influence of air pollution from the unassuming locale of Bismarck on the nation's inflation levels is as unexpected as a plot twist in a detective novel, yet just as compelling. It's a reminder that, much like a dad joke in a somber discussion, the most unlikely pairings can wield significant influence and merit deeper contemplation.

As we leave our discussion open-ended, much like the open-ended punchline of a good joke, it's clear that the influence of air pollution in Bismarck transcends its immediate impact, leaving an indelible mark on the economic tapestry. While the significance of this relationship may be subtle, it demands continued research attention and invites the academic community to ponder the enigmatic interplay of environmental and economic factors.

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 Bismarck, North Dakota and Inflation in the US. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
The Inflated Effects of Air Pollution: A Breath of Fresh Air from Bismarck, North Dakota

[[ABSTRACT]]
In this study, we aim to investigate the unexpected correlation between air pollution in Bismarck, North Dakota and inflation in the United States. While on the surface, these two phenomena may seem as unrelated as a fish on a bicycle, our research has uncovered an intriguing connection.

Analyzing data from the Environmental Protection Agency and Statista spanning the period from 1992 to 2022, we found a striking correlation coefficient of 0.7705110 (p < 0.01) between air pollution levels in Bismarck and inflation in the US. It seems that air pollution may not only be causing respiratory distress; it may also be giving the US economy a case of inflationary hiccups.

Our findings raise important questions about the economic impact of environmental factors, providing a breath of fresh air to the field of environmental economics. Oh, the irony of polluted air having an "inflated" effect on the economy! This research sheds light on the unexpected ways in which seemingly disparate factors can influence one another, leaving us with a "breathtaking" revelation.

[[INTRDUCTION]]
Air pollution and its impact on human health and the environment have been subjects of extensive research and public concern for decades. Similarly, inflation, the rise in the price of goods and services over time, has been a central issue in economic policy discussions. The connection between these two seemingly unconnected topics may appear as bizarre as a snowman in the desert, but our study delves into unearthing the surprising relationship between air pollution in Bismarck, North Dakota, and inflation in the United States.
As we embark on this journey to unravel the mysterious bond between these two seemingly unrelated phenomena, it is essential to recognize the gravity of our task. This is not a tale for the faint-hearted or a research topic for those without a sense of adventure. One might even say that exploring the connection between air pollution and inflation is akin to navigating through a fog of uncertainty, with the occasional whiff of statistical significance to guide our way. Just like a bad pun, this correlation cannot be ignored.
The city of Bismarck, North Dakota, situated along the Missouri River and known for its friendly residents and scenic beauty, takes center stage in our investigation. Oh, Bismarck - the capital city named after the founder of Germany's unified empire, Otto von Bismarck, and now playing a role in this unexpected economic drama. It seems this city has more to offer than just breathtaking sunsets and picturesque landscapes; its air pollution levels hold a surprise that not even the most astute economist could have predicted. It's almost as if Bismarck's air pollution is saying, "You can't inflate the importance of our role in this research!"
Our analysis, conducted with rigorous methodology and a determination not unlike a bloodhound on the trail of a scent, has revealed compelling results. The statistical correlation we have uncovered between air pollution in Bismarck and inflation in the United States is as clear as the North Dakota sky on a cloudless day. It's like finding a needle in a haystack, or in this case, a link between air quality and economic trends in an unexpected corner of the country.
In the words of a wise economist, "Correlation does not imply causation," but in our case, it certainly piques curiosity and raises an eyebrow or two. The connection we have unearthed acts as a reminder that even the most disparate elements in our world can sometimes march to the beat of the same drum. It's a bit like finding out that the air pollution in Bismarck is like the unsung hero of the US inflation story, quietly exerting its influence without a trace of recognition. Just like a good dad joke, the correlation between air pollution and inflation may cause some eye-rolling, but it's hard to ignore its impact.

[[RESULTS]]
The results of our investigation into the correlation between air pollution in Bismarck, North Dakota and inflation in the United States reveal a statistical correlation coefficient (r) of 0.7705110, with an r-squared of 0.5936872 and a p-value less than 0.01. This robust correlation suggests a strong relationship between these two seemingly disparate variables. It's as surprising as finding a porcupine in a balloon factory!
Figure 1 displays a scatterplot illustrating the notable connection between air pollution in Bismarck and inflation in the US. It's a visual representation that's as clear as an unpolluted sky, showcasing the unmistakable relationship between these two factors. You might say it's as eye-catching as a neon sign in a dense fog.
Our findings provide an intriguing insight into the potential economic implications of environmental factors. The correlation uncovered between air pollution and inflation is as unexpected as a penguin at a pool party, yet it underscores the need to consider the far-reaching effects of air quality on economic trends. In a way, it's like discovering that the butterfly effect isn't just a theoretical concept – it's a breeze that can ripple through the entire economy.
The durable correlation we observed challenges traditional economic wisdom, offering a fresh perspective on the interconnectedness of seemingly unrelated factors. The impact of air pollution from a charming city like Bismarck on the nation's inflation levels is as unexpected as a sudden plot twist in a detective novel. Our research casts a new light on the intricate dance of cause and effect in the economic arena, reminding us that sometimes, the most unlikely pairings can create an influential duet.
As we wrap up our exploration of this unanticipated relationship, it's clear that air pollution in Bismarck isn't just blowing smoke; it's leaving a mark on the economic landscape. The significance of this correlation may be as subtle as a pun in a serious conversation, but it commands attention and warrants further investigation.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has illuminated a remarkable correlation between air pollution in Bismarck, North Dakota and inflation in the United States, leaving our economic understanding a bit more in the "smog" than before. This unexpected link has raised eyebrows and evoked a sense of wonder akin to stumbling upon a unicorn in a forest – truly a cause for both excitement and befuddlement.

Our findings suggest that the economic impact of air pollution extends beyond respiratory health to leave an indelible mark on inflation. It's as if pollution is saying, "I'll take your breath away and inflate those prices!" - talk about multitasking.

As we ponder the implications of our research, it's clear that further investigation into this peculiar relationship is as unnecessary as a fish riding a bicycle – just not required! We can confidently say that no more research is needed in this area. With the air cleared on this topic, let's bid adieu to Bismarck's air pollution and its surprising economic influence.

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 The Inflated Effects of Air Pollution: A Breath of Fresh Air from Bismarck, North Dakota. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Environmental Pseudoscience

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 The Inflated Effects of Air Pollution: A Breath of Fresh Air from Bismarck, North Dakota. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Atmospheric Enthusiasts and Zephyr Science (SAEZS)

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 The Inflated Effects of Air Pollution: A Breath of Fresh Air from Bismarck, North Dakota with an abstract of In this study, we aim to investigate the unexpected correlation between air pollution in Bismarck, North Dakota and inflation in the United States. While on the surface, these two phenomena may seem as unrelated as a fish on a bicycle, our research has uncovered an intriguing connection.
Analyzing data from the Environmental Protection Agency and Statista spanning the period from 1992 to 2022, we found a striking correlation coefficient of 0.7705110 (p < 0.01) between air pollution levels in Bismarck and inflation in the US. It seems that air pollution may not only be causing respiratory distress; it may also be giving the US economy a case of inflationary hiccups.
Our findings raise important questions about the economic impact of environmental factors, providing a breath of fresh air to the field of environmental economics. Oh, the irony of polluted air having an "inflated" effect on the economy! This research sheds light on the unexpected ways in which seemingly disparate factors can influence one another, leaving us with a "breathtaking" revelation.

ChatGPT:

air pollution, Bismarck North Dakota, inflation, correlation, Environmental Protection Agency, Statista, economic impact, environmental factors, environmental economics

*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 Bismarck, North Dakota
Detailed data title: Percentage of days with moderate or worse air quality in Bismarck, ND
Source: Environmental Protection Agency
See what else correlates with Air pollution in Bismarck, North Dakota

Inflation in the US
Detailed data title: Consumer Price Index for Urban Consumers (CPI-U) in the United States
Source: Statista
See what else correlates with Inflation in the US

Correlation r = 0.7705110 (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 = 0.5936872 (Coefficient of determination)
This means 59.4% of the change in the one variable (i.e., Inflation in the US) is predictable based on the change in the other (i.e., Air pollution in Bismarck, North Dakota) over the 31 years from 1992 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.0E-7.^Show 0.0000003977019979688133000000
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 0.77 in 4.0E-5% of random cases. Said differently, if you correlated 2,514,446 random variables^Note You don't actually need 2 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 30 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 30 because we have two variables measured over a period of 31 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.

[ 0.57, 0.88 ] 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.

	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 Bismarck, North Dakota (Bad air quality days)	3.77358	1.17302	2.46575	2.73973	2.73224	4.65753	7.39726	6.30137	3.56164	6.95971	4.65753	6.30137	2.18579	5.47945	12.3288	5.20548	7.10383	10.6849	20.8219	8.49315	14.2077	13.1507	9.31507	14.2466	3.27869	16.1644	22.1918	12.3288	9.56284	27.1233	20.5479
Inflation in the US (CPI)	140.3	144.5	148.2	152.4	156.9	160.5	163	166.6	172.2	177.1	179.9	184	188.9	195.3	201.6	207.34	215.3	214.54	218.06	224.94	229.59	232.96	236.74	237.02	240.01	245.12	251.11	255.66	258.81	270.97	292.56

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([3.77358,1.17302,2.46575,2.73973,2.73224,4.65753,7.39726,6.30137,3.56164,6.95971,4.65753,6.30137,2.18579,5.47945,12.3288,5.20548,7.10383,10.6849,20.8219,8.49315,14.2077,13.1507,9.31507,14.2466,3.27869,16.1644,22.1918,12.3288,9.56284,27.1233,20.5479,])
array_2 = np.array([140.3,144.5,148.2,152.4,156.9,160.5,163,166.6,172.2,177.1,179.9,184,188.9,195.3,201.6,207.34,215.3,214.54,218.06,224.94,229.59,232.96,236.74,237.02,240.01,245.12,251.11,255.66,258.81,270.97,292.56,])
array_1_name = "Air pollution in Bismarck, North Dakota"
array_2_name = "Inflation in the US"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Air pollution in Bismarck, North Dakota
Line chart for only Inflation in the US
AI-generated correlation image
The spurious research paper: The Inflated Effects of Air Pollution: A Breath of Fresh Air from Bismarck, North Dakota

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Correlation ID: 3828 · Black Variable ID: 20365 · Red Variable ID: 212


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