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Spurious correlation #1,383 · 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 Vernal, Utah and the second variable is Itaú Unibanco Holding's stock price (ITUB).  The chart goes from 2003 to 2023, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

The smog from all that air pollution acted as a natural smokescreen, hiding any potential red flags from investors. Itaú Unibanco Holding's stock was on the rise, smog or no smog. Who knew the key to financial success was just a breath of fresh... or not so fresh air.

Model: dalle-3
Prompt: [ A black-and-white newspaper illustration ] Generate an image of the hazy sky over Vernal, Utah, with the outline of the majestic mountains shrouded in the poor air quality. In the foreground, depict people in the city checking their phones, with their expressions mirroring the fluctuations of Itaú Unibanco Holding's stock price displayed on digital billboards scattered throughout the area. Capture the contrast between the natural beauty of the mountains and the modern urban environment, all shrouded in the hazy sky. 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: Less than ideal air quality in Vernal, Utah and Itaú Unibanco Holding's stock price. 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: Concept art A scene from Skyrim A black-and-white newspaper illustration Art nouveau inspired by bauhaus
ChatGPT: A black-and-white newspaper illustration

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 Less than ideal air quality in Vernal, Utah and Itaú Unibanco Holding's stock price together. Keep the description simple.
ChatGPT: The sky over Vernal, Utah is hazy with a tinge of grey, with the outline of the majestic mountains in the background obscured by the poor air quality. Amidst the haze, people in the city are seen checking their phones, their expressions mirroring the fluctuations of Itaú Unibanco Holding's stock price displayed on digital billboards scattered throughout the area.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A black-and-white newspaper illustration ] and depicting this scene: The sky over Vernal, Utah is hazy with a tinge of grey, with the outline of the majestic mountains in the background obscured by the poor air quality. Amidst the haze, people in the city are seen checking their phones, their expressions mirroring the fluctuations of Itaú Unibanco Holding's stock price displayed on digital billboards scattered throughout the area. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A black-and-white newspaper illustration ] Generate an image of the hazy sky over Vernal, Utah, with the outline of the majestic mountains shrouded in the poor air quality. In the foreground, depict people in the city checking their phones, with their expressions mirroring the fluctuations of Itaú Unibanco Holding's stock price displayed on digital billboards scattered throughout the area. Capture the contrast between the natural beauty of the mountains and the modern urban environment, all shrouded in the hazy sky.

*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.

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 Vernal, Utah caused Itaú Unibanco Holding's stock price (ITUB) to increase. Include one good pun.

AI academic paper

(Because p < 0.01)
The Pungent Pollution Puzzle: Probing the Pertinence of Particulate Matter on Itaú Unibanco Holding's Stock Price

The Journal of Environmental Economics and Stock Market Dynamics

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Air pollution in Vernal, Utah and Itaú Unibanco Holding's stock price (ITUB). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Make the title an alliteration.

Your research team used data from Environmental Protection Agency and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.7566280 and p < 0.01 for 2003 to 2023.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
The Pungent Pollution Puzzle: Probing the Pertinence of Particulate Matter on Itaú Unibanco Holding's Stock Price

[[ABSTRACT]]
In this study, we delved into the delightful duality of air pollution in Vernal, Utah, and the dynamics of Itaú Unibanco Holding's (ITUB) stock price. Leveraging data from the Environmental Protection Agency and LSEG Analytics (Refinitiv), we endeavored to disentangle the potential link between the atmospheric intricacies of Vernal, Utah, and the financial fluctuations of ITUB. With a correlation coefficient of 0.7566280 and p < 0.01 for the period of 2003 to 2023, our exploratory analysis has uncovered an intriguing association that demands further investigation.

Amidst the haze of particulate matter, our findings reveal a compelling connection between the air quality in Vernal and ITUB's stock price, establishing an atmosphere of intrigue for the financial and environmental communities alike. To our surprise, the data presents a compelling case that the level of pollution in Vernal appears to waft its way into the financial realm, shaping the stock price of Itaú Unibanco Holding. As we sifted through the data, we couldn't help but quip that this correlation might just be a breath of fresh air for those seeking to discern the undercurrents of financial markets.

Our research highlights the importance of accounting for environmental factors when analyzing stock price patterns, calling attention to the need for a breath of fresh air in economic and financial modeling. Despite the smog of uncertainty, our findings signal an opportunity for further investigation into the intersection of environmental influences and market dynamics, shedding light on the delicate balance between economic fluctuations and atmospheric perturbations. We hope our research brings a breath of fresh air to the academic community and inspires a wave of interdisciplinary studies that bridge the gap between finance and environmental science.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between Air pollution in Vernal, Utah and Itaú Unibanco Holding's stock price (ITUB). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
The Pungent Pollution Puzzle: Probing the Pertinence of Particulate Matter on Itaú Unibanco Holding's Stock Price

[[ABSTRACT]]
In this study, we delved into the delightful duality of air pollution in Vernal, Utah, and the dynamics of Itaú Unibanco Holding's (ITUB) stock price. Leveraging data from the Environmental Protection Agency and LSEG Analytics (Refinitiv), we endeavored to disentangle the potential link between the atmospheric intricacies of Vernal, Utah, and the financial fluctuations of ITUB. With a correlation coefficient of 0.7566280 and p < 0.01 for the period of 2003 to 2023, our exploratory analysis has uncovered an intriguing association that demands further investigation.

Amidst the haze of particulate matter, our findings reveal a compelling connection between the air quality in Vernal and ITUB's stock price, establishing an atmosphere of intrigue for the financial and environmental communities alike. To our surprise, the data presents a compelling case that the level of pollution in Vernal appears to waft its way into the financial realm, shaping the stock price of Itaú Unibanco Holding. As we sifted through the data, we couldn't help but quip that this correlation might just be a breath of fresh air for those seeking to discern the undercurrents of financial markets.

Our research highlights the importance of accounting for environmental factors when analyzing stock price patterns, calling attention to the need for a breath of fresh air in economic and financial modeling. Despite the smog of uncertainty, our findings signal an opportunity for further investigation into the intersection of environmental influences and market dynamics, shedding light on the delicate balance between economic fluctuations and atmospheric perturbations. We hope our research brings a breath of fresh air to the academic community and inspires a wave of interdisciplinary studies that bridge the gap between finance and environmental science.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Picture this: the scenic city of Vernal, Utah, nestled amidst the stunning landscapes of the Uintah Basin. It's a place where the crisp mountain air meets the soothing tranquility of nature, creating an idyllic setting for outdoor adventures. But behind this picturesque facade lies a pungent puzzle - the presence of particulate matter in the air. Yes, you heard that right - the air in Vernal might be as clear as mud!

Now, let's take a moment to acknowledge the elephant in the room - or should I say, the smog in the city. Air pollution is no laughing matter, but it certainly adds a breath of mystery to our research. With noses wrinkled and statistical tools in hand, we set out to investigate this aromatic enigma and its unexpected connection to the stock price of Itaú Unibanco Holding (ITUB).

The essence of our research lies in unraveling this unlikely relationship between the atmospheric anomalies of Vernal and the financial fluctuations of ITUB. With a correlation coefficient that would make even the most stoic statistician crack a smile, our study sheds light on the potential interplay between environmental perturbations and market dynamics.

They say the stock market is like an unpredictable breeze, but who knew it could be affected by the gentle whisper of airborne particles from Vernal? It seems that no matter where we look, there's always a whiff of unexpected connections waiting to be uncovered.

Our exploration into this distinctive linkage serves as a breath of fresh air in the world of financial research, adding a splash of intrigue to the traditional models and theories. As we maneuver through the labyrinth of data, we can't help but appreciate the fresh perspective our findings offer, like a gust of wind clearing the fog of conventional wisdom.

So, grab your inhalers and buckle up for a journey through the realms of finance and environmental science, as we dive into the confluence of air quality and stock prices. It's a breath-taking ride, quite literally!


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Vernal, Utah and Itaú Unibanco Holding's stock price (ITUB). 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]]
The Pungent Pollution Puzzle: Probing the Pertinence of Particulate Matter on Itaú Unibanco Holding's Stock Price

[[ABSTRACT]]
In this study, we delved into the delightful duality of air pollution in Vernal, Utah, and the dynamics of Itaú Unibanco Holding's (ITUB) stock price. Leveraging data from the Environmental Protection Agency and LSEG Analytics (Refinitiv), we endeavored to disentangle the potential link between the atmospheric intricacies of Vernal, Utah, and the financial fluctuations of ITUB. With a correlation coefficient of 0.7566280 and p < 0.01 for the period of 2003 to 2023, our exploratory analysis has uncovered an intriguing association that demands further investigation.

Amidst the haze of particulate matter, our findings reveal a compelling connection between the air quality in Vernal and ITUB's stock price, establishing an atmosphere of intrigue for the financial and environmental communities alike. To our surprise, the data presents a compelling case that the level of pollution in Vernal appears to waft its way into the financial realm, shaping the stock price of Itaú Unibanco Holding. As we sifted through the data, we couldn't help but quip that this correlation might just be a breath of fresh air for those seeking to discern the undercurrents of financial markets.

Our research highlights the importance of accounting for environmental factors when analyzing stock price patterns, calling attention to the need for a breath of fresh air in economic and financial modeling. Despite the smog of uncertainty, our findings signal an opportunity for further investigation into the intersection of environmental influences and market dynamics, shedding light on the delicate balance between economic fluctuations and atmospheric perturbations. We hope our research brings a breath of fresh air to the academic community and inspires a wave of interdisciplinary studies that bridge the gap between finance and environmental science.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Picture this: the scenic city of Vernal, Utah, nestled amidst the stunning landscapes of the Uintah Basin. It's a place where the crisp mountain air meets the soothing tranquility of nature, creating an idyllic setting for outdoor adventures. But behind this picturesque facade lies a pungent puzzle - the presence of particulate matter in the air. Yes, you heard that right - the air in Vernal might be as clear as mud!

Now, let's take a moment to acknowledge the elephant in the room - or should I say, the smog in the city. Air pollution is no laughing matter, but it certainly adds a breath of mystery to our research. With noses wrinkled and statistical tools in hand, we set out to investigate this aromatic enigma and its unexpected connection to the stock price of Itaú Unibanco Holding (ITUB).

The essence of our research lies in unraveling this unlikely relationship between the atmospheric anomalies of Vernal and the financial fluctuations of ITUB. With a correlation coefficient that would make even the most stoic statistician crack a smile, our study sheds light on the potential interplay between environmental perturbations and market dynamics.

They say the stock market is like an unpredictable breeze, but who knew it could be affected by the gentle whisper of airborne particles from Vernal? It seems that no matter where we look, there's always a whiff of unexpected connections waiting to be uncovered.
Our exploration into this distinctive linkage serves as a breath of fresh air in the world of financial research, adding a splash of intrigue to the traditional models and theories. As we maneuver through the labyrinth of data, we can't help but appreciate the fresh perspective our findings offer, like a gust of wind clearing the fog of conventional wisdom.
So, grab your inhalers and buckle up for a journey through the realms of finance and environmental science, as we dive into the confluence of air quality and stock prices. It's a breath-taking ride, quite literally!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The connection between environmental factors and financial markets has been a topic of increasing interest in academic and professional circles. Smith et al. (2016) elucidate the impact of air pollution on economic indicators, highlighting the intricate relationship between atmospheric conditions and market behavior. Similarly, Doe and Jones (2018) delve into the influence of environmental factors on stock prices, providing a comprehensive analysis of the interplay between air quality and financial performance.

But let's not get bogged down in the seriousness of it all, shall we? Let's lighten the mood a bit with a joke. Why did the stockbroker bring a ladder to work? Because he wanted to take stock of the situation!

In "Air Pollution and Economic Growth," Lorem and Ipsum (2014) explore the repercussions of air pollution on economic development, offering valuable insights into the far-reaching effects of environmental degradation. This work lays a solid foundation for understanding the broader implications of air quality on economic outcomes, setting the stage for our investigation into the curious case of Vernal's atmospheric intricacies and their impact on Itaú Unibanco Holding's stock price.

Speaking of curious cases, have you heard about the claustrophobic skydiver? He couldn't handle the atmosphere!

In the realm of finance, "Stocks and Stones: How Market Movements Shape Our World" by Jane Doe (2019) and "The Financial Ponderings" by John Smith (2021) present comprehensive analyses of stock market behavior, offering valuable perspectives on the factors that influence stock prices. However, these works fail to address the aromatic allure of air pollution and its potential sway on financial markets - a gap that our research enthusiastically fills.

Now, let's take a detour into the realm of fiction. Imagine a world where stock prices are at the mercy of airborne anomalies – "The Smoggy Stock Exchange" and "The Polluted Price Plunge" could be bestselling titles!

In the age of memes and internet culture, the "Distracted Boyfriend" meme takes on a whole new meaning when applied to the relationship between air pollution in Vernal and Itaú Unibanco Holding's stock price. Who would've thought that a distracted boyfriend could symbolize the subtle shifts in financial markets caused by environmental factors?

And on that note, let's dive deeper into the quirky world of correlation coefficients and stock price perturbations. But first, a quick one-liner: How do you organize a space party? You planet!


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Air pollution in Vernal, Utah and Itaú Unibanco Holding's stock price (ITUB). 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 LSEG Analytics (Refinitiv) . You used data from 2003 to 2023

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 Pungent Pollution Puzzle: Probing the Pertinence of Particulate Matter on Itaú Unibanco Holding's Stock Price

[[ABSTRACT]]
In this study, we delved into the delightful duality of air pollution in Vernal, Utah, and the dynamics of Itaú Unibanco Holding's (ITUB) stock price. Leveraging data from the Environmental Protection Agency and LSEG Analytics (Refinitiv), we endeavored to disentangle the potential link between the atmospheric intricacies of Vernal, Utah, and the financial fluctuations of ITUB. With a correlation coefficient of 0.7566280 and p < 0.01 for the period of 2003 to 2023, our exploratory analysis has uncovered an intriguing association that demands further investigation.

Amidst the haze of particulate matter, our findings reveal a compelling connection between the air quality in Vernal and ITUB's stock price, establishing an atmosphere of intrigue for the financial and environmental communities alike. To our surprise, the data presents a compelling case that the level of pollution in Vernal appears to waft its way into the financial realm, shaping the stock price of Itaú Unibanco Holding. As we sifted through the data, we couldn't help but quip that this correlation might just be a breath of fresh air for those seeking to discern the undercurrents of financial markets.

Our research highlights the importance of accounting for environmental factors when analyzing stock price patterns, calling attention to the need for a breath of fresh air in economic and financial modeling. Despite the smog of uncertainty, our findings signal an opportunity for further investigation into the intersection of environmental influences and market dynamics, shedding light on the delicate balance between economic fluctuations and atmospheric perturbations. We hope our research brings a breath of fresh air to the academic community and inspires a wave of interdisciplinary studies that bridge the gap between finance and environmental science.

[[INTRODUCTION]]
Picture this: the scenic city of Vernal, Utah, nestled amidst the stunning landscapes of the Uintah Basin. It's a place where the crisp mountain air meets the soothing tranquility of nature, creating an idyllic setting for outdoor adventures. But behind this picturesque facade lies a pungent puzzle - the presence of particulate matter in the air. Yes, you heard that right - the air in Vernal might be as clear as mud!

Now, let's take a moment to acknowledge the elephant in the room - or should I say, the smog in the city. Air pollution is no laughing matter, but it certainly adds a breath of mystery to our research. With noses wrinkled and statistical tools in hand, we set out to investigate this aromatic enigma and its unexpected connection to the stock price of Itaú Unibanco Holding (ITUB).

The essence of our research lies in unraveling this unlikely relationship between the atmospheric anomalies of Vernal and the financial fluctuations of ITUB. With a correlation coefficient that would make even the most stoic statistician crack a smile, our study sheds light on the potential interplay between environmental perturbations and market dynamics.

They say the stock market is like an unpredictable breeze, but who knew it could be affected by the gentle whisper of airborne particles from Vernal? It seems that no matter where we look, there's always a whiff of unexpected connections waiting to be uncovered.
Our exploration into this distinctive linkage serves as a breath of fresh air in the world of financial research, adding a splash of intrigue to the traditional models and theories. As we maneuver through the labyrinth of data, we can't help but appreciate the fresh perspective our findings offer, like a gust of wind clearing the fog of conventional wisdom.
So, grab your inhalers and buckle up for a journey through the realms of finance and environmental science, as we dive into the confluence of air quality and stock prices. It's a breath-taking ride, quite literally!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To capture the essence of this unlikely association between air pollution in Vernal, Utah, and the stock price of Itaú Unibanco Holding (ITUB), our research team embarked on a data odyssey that relied on a mixture of meticulous data mining and statistical wizardry. Our approach was as methodical as a scientist sniffing out an elusive aroma, seeking to unravel the peculiar scent of financial fluctuations intertwined with the atmospheric nuances of Vernal.

First and foremost, our study harnessed a comprehensive dataset from the Environmental Protection Agency, providing a treasure trove of air quality measurements in Vernal, Utah. This data, akin to a fine bouquet of atmospheric readings, allowed us to quantify the levels of particulate matter and other air pollutants that hung in the air like an uninvited guest at a scholarly soirée. Additionally, we sourced financial data from the venerable LSEG Analytics (Refinitiv), navigating the labyrinth of stock prices with the finesse of a seasoned market analyst.

With these disparate datasets in hand, we indulged in the delicate art of data cleansing and harmonization, akin to orchestrating a symphony of statistical variables. Our team meticulously scrutinized the data for outliers, inaccuracies, and missing values, ensuring that our analysis would be as crisp and clear as a gust of wind blowing through the Utah landscape.

To establish the initial relationship between air pollution in Vernal and ITUB's stock price, we employed the trusty tool of correlation analysis, calculating the Pearson correlation coefficient with the precision of a sculptor shaping a masterpiece. This allowed us to quantify the strength and direction of the association, providing a quantitative measure of the atmospheric influence on financial markets.

In a quest to untangle the temporal dimension of this intricate relationship, we dabbled in time series analysis, modeling the fluctuations in air quality and stock price over the period from 2003 to 2023. This allowed us to capture the ebb and flow of both variables, unveiling the rhythmic dance of environmental perturbations and market dynamics.

Furthermore, our study delved into the realm of regression analysis, endeavoring to tease out the causal threads that weave through the fabric of our findings. We sought to discern whether the level of air pollution in Vernal exerts a significant influence on ITUB's stock price, akin to detective Sherlock Holmes unraveling a particularly enigmatic financial mystery.

In a lighthearted attempt to add a dash of creativity to our quantitative analysis, we named our statistical models after famous fictional detectives – from the "Sherlock Regression" to the "Miss Marple Correlation." It was our playful way of infusing the rigorous world of statistics with a touch of literary flair, as we sought to unravel the narrative hidden within the numerical tapestry.

Lastly, to account for potential confounding variables that might obscure the true nature of the relationship, we attempted to control for external factors such as market trends, economic indicators, and even the occasional meteorological whimsy. Our statistical toolbox was brimming with methods to mitigate the influence of these extraneous elements, ensuring that our analysis would hone in on the direct link between air pollution in Vernal and the stock price of ITUB.

In the end, our methodology was a swirling blend of statistical rigidity and imaginative playfulness, akin to sipping a thought-provoking concoction at a scientific soiree. With our data drenched in rigor and our analyses tinged with whimsy, we set the stage for an innovative exploration into the enigmatic interplay of environmental fragrances and financial fortunes.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Vernal, Utah and Itaú Unibanco Holding's stock price (ITUB). 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 LSEG Analytics (Refinitiv) .

For the time period 2003 to 2023, you found a correlation 0.7566280, r-squared of 0.5724859, 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]]
The Pungent Pollution Puzzle: Probing the Pertinence of Particulate Matter on Itaú Unibanco Holding's Stock Price

[[ABSTRACT]]
In this study, we delved into the delightful duality of air pollution in Vernal, Utah, and the dynamics of Itaú Unibanco Holding's (ITUB) stock price. Leveraging data from the Environmental Protection Agency and LSEG Analytics (Refinitiv), we endeavored to disentangle the potential link between the atmospheric intricacies of Vernal, Utah, and the financial fluctuations of ITUB. With a correlation coefficient of 0.7566280 and p < 0.01 for the period of 2003 to 2023, our exploratory analysis has uncovered an intriguing association that demands further investigation.

Amidst the haze of particulate matter, our findings reveal a compelling connection between the air quality in Vernal and ITUB's stock price, establishing an atmosphere of intrigue for the financial and environmental communities alike. To our surprise, the data presents a compelling case that the level of pollution in Vernal appears to waft its way into the financial realm, shaping the stock price of Itaú Unibanco Holding. As we sifted through the data, we couldn't help but quip that this correlation might just be a breath of fresh air for those seeking to discern the undercurrents of financial markets.

Our research highlights the importance of accounting for environmental factors when analyzing stock price patterns, calling attention to the need for a breath of fresh air in economic and financial modeling. Despite the smog of uncertainty, our findings signal an opportunity for further investigation into the intersection of environmental influences and market dynamics, shedding light on the delicate balance between economic fluctuations and atmospheric perturbations. We hope our research brings a breath of fresh air to the academic community and inspires a wave of interdisciplinary studies that bridge the gap between finance and environmental science.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Picture this: the scenic city of Vernal, Utah, nestled amidst the stunning landscapes of the Uintah Basin. It's a place where the crisp mountain air meets the soothing tranquility of nature, creating an idyllic setting for outdoor adventures. But behind this picturesque facade lies a pungent puzzle - the presence of particulate matter in the air. Yes, you heard that right - the air in Vernal might be as clear as mud!

Now, let's take a moment to acknowledge the elephant in the room - or should I say, the smog in the city. Air pollution is no laughing matter, but it certainly adds a breath of mystery to our research. With noses wrinkled and statistical tools in hand, we set out to investigate this aromatic enigma and its unexpected connection to the stock price of Itaú Unibanco Holding (ITUB).

The essence of our research lies in unraveling this unlikely relationship between the atmospheric anomalies of Vernal and the financial fluctuations of ITUB. With a correlation coefficient that would make even the most stoic statistician crack a smile, our study sheds light on the potential interplay between environmental perturbations and market dynamics.

They say the stock market is like an unpredictable breeze, but who knew it could be affected by the gentle whisper of airborne particles from Vernal? It seems that no matter where we look, there's always a whiff of unexpected connections waiting to be uncovered.
Our exploration into this distinctive linkage serves as a breath of fresh air in the world of financial research, adding a splash of intrigue to the traditional models and theories. As we maneuver through the labyrinth of data, we can't help but appreciate the fresh perspective our findings offer, like a gust of wind clearing the fog of conventional wisdom.
So, grab your inhalers and buckle up for a journey through the realms of finance and environmental science, as we dive into the confluence of air quality and stock prices. It's a breath-taking ride, quite literally!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The data analysis yielded a noteworthy correlation coefficient of 0.7566280 between air pollution in Vernal, Utah, and Itaú Unibanco Holding's (ITUB) stock price. With an r-squared value of 0.5724859 and a p-value less than 0.01, our statistical analysis provided robust evidence of a significant relationship between these seemingly disparate variables.

Fig. 1 showcases a scatterplot that visually captures the striking correlation unearthed by our research. As you can see, the data points form a pattern as clear as the skies over Vernal... or should I say, as murky as the polluted air. It's a visual representation that harbors a tale as intriguing as a stock market thriller!

The statistical significance of our findings prompts us to ponder the question: Could it be that the only thing particulate matter is accumulating is wealth for savvy investors in ITUB? It certainly seems like there's more than just dust in the wind when it comes to understanding the financial implications of atmospheric conditions.

Our results raise eyebrows as well as awareness regarding the potential impact of environmental factors on stock prices, prompting us to delve deeper into the intricate interplay between air quality and market performance. It's like a gust of fresh insight blowing through the narrow corridors of traditional financial analysis, leaving us invigorated and gasping for more revelations.

In conclusion, our research illuminates a compelling connection between air pollution in Vernal, Utah, and Itaú Unibanco Holding's stock price, adding a breath of fresh air to the discussion around environmental influences on financial markets. It's clear that when it comes to market movements, sometimes the answers aren't just up in the air - they're floating amidst the particles of Vernal.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Vernal, Utah and Itaú Unibanco Holding's stock price (ITUB). 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]]
The Pungent Pollution Puzzle: Probing the Pertinence of Particulate Matter on Itaú Unibanco Holding's Stock Price

[[ABSTRACT]]
In this study, we delved into the delightful duality of air pollution in Vernal, Utah, and the dynamics of Itaú Unibanco Holding's (ITUB) stock price. Leveraging data from the Environmental Protection Agency and LSEG Analytics (Refinitiv), we endeavored to disentangle the potential link between the atmospheric intricacies of Vernal, Utah, and the financial fluctuations of ITUB. With a correlation coefficient of 0.7566280 and p < 0.01 for the period of 2003 to 2023, our exploratory analysis has uncovered an intriguing association that demands further investigation.

Amidst the haze of particulate matter, our findings reveal a compelling connection between the air quality in Vernal and ITUB's stock price, establishing an atmosphere of intrigue for the financial and environmental communities alike. To our surprise, the data presents a compelling case that the level of pollution in Vernal appears to waft its way into the financial realm, shaping the stock price of Itaú Unibanco Holding. As we sifted through the data, we couldn't help but quip that this correlation might just be a breath of fresh air for those seeking to discern the undercurrents of financial markets.

Our research highlights the importance of accounting for environmental factors when analyzing stock price patterns, calling attention to the need for a breath of fresh air in economic and financial modeling. Despite the smog of uncertainty, our findings signal an opportunity for further investigation into the intersection of environmental influences and market dynamics, shedding light on the delicate balance between economic fluctuations and atmospheric perturbations. We hope our research brings a breath of fresh air to the academic community and inspires a wave of interdisciplinary studies that bridge the gap between finance and environmental science.

[[LITERATURE REVIEW]]
The connection between environmental factors and financial markets has been a topic of increasing interest in academic and professional circles. Smith et al. (2016) elucidate the impact of air pollution on economic indicators, highlighting the intricate relationship between atmospheric conditions and market behavior. Similarly, Doe and Jones (2018) delve into the influence of environmental factors on stock prices, providing a comprehensive analysis of the interplay between air quality and financial performance.
But let's not get bogged down in the seriousness of it all, shall we? Let's lighten the mood a bit with a joke. Why did the stockbroker bring a ladder to work? Because he wanted to take stock of the situation!
In "Air Pollution and Economic Growth," Lorem and Ipsum (2014) explore the repercussions of air pollution on economic development, offering valuable insights into the far-reaching effects of environmental degradation. This work lays a solid foundation for understanding the broader implications of air quality on economic outcomes, setting the stage for our investigation into the curious case of Vernal's atmospheric intricacies and their impact on Itaú Unibanco Holding's stock price.
Speaking of curious cases, have you heard about the claustrophobic skydiver? He couldn't handle the atmosphere!
In the realm of finance, "Stocks and Stones: How Market Movements Shape Our World" by Jane Doe (2019) and "The Financial Ponderings" by John Smith (2021) present comprehensive analyses of stock market behavior, offering valuable perspectives on the factors that influence stock prices. However, these works fail to address the aromatic allure of air pollution and its potential sway on financial markets - a gap that our research enthusiastically fills.
Now, let's take a detour into the realm of fiction. Imagine a world where stock prices are at the mercy of airborne anomalies – "The Smoggy Stock Exchange" and "The Polluted Price Plunge" could be bestselling titles!
In the age of memes and internet culture, the "Distracted Boyfriend" meme takes on a whole new meaning when applied to the relationship between air pollution in Vernal and Itaú Unibanco Holding's stock price. Who would've thought that a distracted boyfriend could symbolize the subtle shifts in financial markets caused by environmental factors?
And on that note, let's dive deeper into the quirky world of correlation coefficients and stock price perturbations. But first, a quick one-liner: How do you organize a space party? You planet!

[[RESULTS]]
The data analysis yielded a noteworthy correlation coefficient of 0.7566280 between air pollution in Vernal, Utah, and Itaú Unibanco Holding's (ITUB) stock price. With an r-squared value of 0.5724859 and a p-value less than 0.01, our statistical analysis provided robust evidence of a significant relationship between these seemingly disparate variables.
Fig. 1 showcases a scatterplot that visually captures the striking correlation unearthed by our research. As you can see, the data points form a pattern as clear as the skies over Vernal... or should I say, as murky as the polluted air. It's a visual representation that harbors a tale as intriguing as a stock market thriller!
The statistical significance of our findings prompts us to ponder the question: Could it be that the only thing particulate matter is accumulating is wealth for savvy investors in ITUB? It certainly seems like there's more than just dust in the wind when it comes to understanding the financial implications of atmospheric conditions.
Our results raise eyebrows as well as awareness regarding the potential impact of environmental factors on stock prices, prompting us to delve deeper into the intricate interplay between air quality and market performance. It's like a gust of fresh insight blowing through the narrow corridors of traditional financial analysis, leaving us invigorated and gasping for more revelations.
In conclusion, our research illuminates a compelling connection between air pollution in Vernal, Utah, and Itaú Unibanco Holding's stock price, adding a breath of fresh air to the discussion around environmental influences on financial markets. It's clear that when it comes to market movements, sometimes the answers aren't just up in the air - they're floating amidst the particles of Vernal.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our findings provide robust evidence supporting the claim that air pollution in Vernal, Utah, exerts a discernible influence on Itaú Unibanco Holding's (ITUB) stock price. This robust connection aligns with previous studies by Smith et al. and Doe and Jones, which substantiated the impact of environmental factors on economic indicators. Our research adds a breath of fresh air to this literature by specifically focusing on the delightful duality of air pollution in Vernal and its connection to the dynamics of ITUB's stock price.

The correlation coefficient of 0.7566280 obtained in our analysis serves as a firm foundation for understanding the atmospheric intricacies and their manifestations in the financial realm. This statistically significant association is as clear as the skies over Vernal – or should we say as murky as the polluted air? It brings a breath of fresh air to the perspective that environmental factors, often overlooked, can exert a significant influence on stock prices. It appears that the particulate matter in the air isn't just accumulating – it's influencing wealth in the financial markets.

Our analysis not only supports the existing literature but also transcends it by providing a tangible linkage between seemingly disparate variables. This discovery is as refreshing as a gulp of clean air in polluted surroundings, spotlighting the need for further research into the intersection of atmospheric conditions and market dynamics. It's almost like a breath of fresh air in the realm of financial analysis – a gust of insight blowing through the traditional corridors of market patterns and trends.

The unexpected connection we've unveiled underscores the need to broaden the scope of financial models to incorporate these environmental variables. It prompts us to question whether the financial airwaves are indeed affected by the atmospheric perturbations of Vernal. Could it be that the financial world and the atmosphere are more entwined than we ever imagined? It looks like the only thing up in the air isn't just stock market projections; it's the particles of Vernal, shaping the financial landscape in ways we hadn't previously envisioned.

As we continue on this research journey, let's remember the value of exploring unconventional connections and challenging established paradigms. Our findings embody the excitement of uncovering hitherto unexplored intersections between environmental influences and market dynamics. This research is a breath of fresh air, not just for the academic community but for the financial world, and it stands as a testament to the enlightening potential of interdisciplinary studies.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Vernal, Utah and Itaú Unibanco Holding's stock price (ITUB). 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]]
The Pungent Pollution Puzzle: Probing the Pertinence of Particulate Matter on Itaú Unibanco Holding's Stock Price

[[ABSTRACT]]
In this study, we delved into the delightful duality of air pollution in Vernal, Utah, and the dynamics of Itaú Unibanco Holding's (ITUB) stock price. Leveraging data from the Environmental Protection Agency and LSEG Analytics (Refinitiv), we endeavored to disentangle the potential link between the atmospheric intricacies of Vernal, Utah, and the financial fluctuations of ITUB. With a correlation coefficient of 0.7566280 and p < 0.01 for the period of 2003 to 2023, our exploratory analysis has uncovered an intriguing association that demands further investigation.

Amidst the haze of particulate matter, our findings reveal a compelling connection between the air quality in Vernal and ITUB's stock price, establishing an atmosphere of intrigue for the financial and environmental communities alike. To our surprise, the data presents a compelling case that the level of pollution in Vernal appears to waft its way into the financial realm, shaping the stock price of Itaú Unibanco Holding. As we sifted through the data, we couldn't help but quip that this correlation might just be a breath of fresh air for those seeking to discern the undercurrents of financial markets.

Our research highlights the importance of accounting for environmental factors when analyzing stock price patterns, calling attention to the need for a breath of fresh air in economic and financial modeling. Despite the smog of uncertainty, our findings signal an opportunity for further investigation into the intersection of environmental influences and market dynamics, shedding light on the delicate balance between economic fluctuations and atmospheric perturbations. We hope our research brings a breath of fresh air to the academic community and inspires a wave of interdisciplinary studies that bridge the gap between finance and environmental science.

[[INTRDUCTION]]
Picture this: the scenic city of Vernal, Utah, nestled amidst the stunning landscapes of the Uintah Basin. It's a place where the crisp mountain air meets the soothing tranquility of nature, creating an idyllic setting for outdoor adventures. But behind this picturesque facade lies a pungent puzzle - the presence of particulate matter in the air. Yes, you heard that right - the air in Vernal might be as clear as mud!

Now, let's take a moment to acknowledge the elephant in the room - or should I say, the smog in the city. Air pollution is no laughing matter, but it certainly adds a breath of mystery to our research. With noses wrinkled and statistical tools in hand, we set out to investigate this aromatic enigma and its unexpected connection to the stock price of Itaú Unibanco Holding (ITUB).

The essence of our research lies in unraveling this unlikely relationship between the atmospheric anomalies of Vernal and the financial fluctuations of ITUB. With a correlation coefficient that would make even the most stoic statistician crack a smile, our study sheds light on the potential interplay between environmental perturbations and market dynamics.

They say the stock market is like an unpredictable breeze, but who knew it could be affected by the gentle whisper of airborne particles from Vernal? It seems that no matter where we look, there's always a whiff of unexpected connections waiting to be uncovered.
Our exploration into this distinctive linkage serves as a breath of fresh air in the world of financial research, adding a splash of intrigue to the traditional models and theories. As we maneuver through the labyrinth of data, we can't help but appreciate the fresh perspective our findings offer, like a gust of wind clearing the fog of conventional wisdom.
So, grab your inhalers and buckle up for a journey through the realms of finance and environmental science, as we dive into the confluence of air quality and stock prices. It's a breath-taking ride, quite literally!

[[RESULTS]]
The data analysis yielded a noteworthy correlation coefficient of 0.7566280 between air pollution in Vernal, Utah, and Itaú Unibanco Holding's (ITUB) stock price. With an r-squared value of 0.5724859 and a p-value less than 0.01, our statistical analysis provided robust evidence of a significant relationship between these seemingly disparate variables.
Fig. 1 showcases a scatterplot that visually captures the striking correlation unearthed by our research. As you can see, the data points form a pattern as clear as the skies over Vernal... or should I say, as murky as the polluted air. It's a visual representation that harbors a tale as intriguing as a stock market thriller!
The statistical significance of our findings prompts us to ponder the question: Could it be that the only thing particulate matter is accumulating is wealth for savvy investors in ITUB? It certainly seems like there's more than just dust in the wind when it comes to understanding the financial implications of atmospheric conditions.
Our results raise eyebrows as well as awareness regarding the potential impact of environmental factors on stock prices, prompting us to delve deeper into the intricate interplay between air quality and market performance. It's like a gust of fresh insight blowing through the narrow corridors of traditional financial analysis, leaving us invigorated and gasping for more revelations.
In conclusion, our research illuminates a compelling connection between air pollution in Vernal, Utah, and Itaú Unibanco Holding's stock price, adding a breath of fresh air to the discussion around environmental influences on financial markets. It's clear that when it comes to market movements, sometimes the answers aren't just up in the air - they're floating amidst the particles of Vernal.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

As the dust settles on our research, it's crystal clear that there's more to the air in Vernal than meets the eye – it's got its particu-lure matters. Our findings have unveiled a correlation between air pollution levels and the stock price of Itaú Unibanco Holding that's as robust as a brick house. The statistical evidence we've gathered might just blow your mind, but rest assured, it's not just hot air.

Our study beckons us to ponder whether the fluctuations in ITUB's stock price may not just be influenced by market trends, but also by the whims and fancies of the winds carrying particulate matter from Vernal. It's like the market is playing a game of "Stocks and Pollutants" – talk about an unexpected twist in financial forecasting!

It's safe to say that our research has added a breath of fresh air to the conversation about environmental factors affecting stock prices, proving that there's more to market movements than meets the eye. It's as if the financial world has caught a whiff of the environmental realm, and the two are dancing an intricately choreographed tango.

In light of these findings, we believe it's time to ring the alarm bells and alert the financial and environmental communities to this unexpected connection. However, with the extent of our current findings, we're confident that there's no need for further research – we've taken a deep dive and surfaced with some truly eye-opening results.

So, as we bid adieu to this pungent puzzle, we're left with one lesson: When it comes to the stock market, the air in Vernal might just hold the breath of an unexpected influencer. And with that, we can confidently say that the air pollution in Vernal, Utah, has left its mark – not just on the environment, but on the financial world as well!

As for future research in this area, there's no need to put your head in the clouds – we've covered it all. The link between air pollution in Vernal, Utah, and Itaú Unibanco Holding's stock price has been well and truly sniffed out.


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 Pungent Pollution Puzzle: Probing the Pertinence of Particulate Matter on Itaú Unibanco Holding's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Environmental Economics and Stock Market Dynamics


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 Pungent Pollution Puzzle: Probing the Pertinence of Particulate Matter on Itaú Unibanco Holding's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Environmental Economics


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 Pungent Pollution Puzzle: Probing the Pertinence of Particulate Matter on Itaú Unibanco Holding's Stock Price with an abstract of In this study, we delved into the delightful duality of air pollution in Vernal, Utah, and the dynamics of Itaú Unibanco Holding's (ITUB) stock price. Leveraging data from the Environmental Protection Agency and LSEG Analytics (Refinitiv), we endeavored to disentangle the potential link between the atmospheric intricacies of Vernal, Utah, and the financial fluctuations of ITUB. With a correlation coefficient of 0.7566280 and p < 0.01 for the period of 2003 to 2023, our exploratory analysis has uncovered an intriguing association that demands further investigation.
Amidst the haze of particulate matter, our findings reveal a compelling connection between the air quality in Vernal and ITUB's stock price, establishing an atmosphere of intrigue for the financial and environmental communities alike. To our surprise, the data presents a compelling case that the level of pollution in Vernal appears to waft its way into the financial realm, shaping the stock price of Itaú Unibanco Holding. As we sifted through the data, we couldn't help but quip that this correlation might just be a breath of fresh air for those seeking to discern the undercurrents of financial markets.
Our research highlights the importance of accounting for environmental factors when analyzing stock price patterns, calling attention to the need for a breath of fresh air in economic and financial modeling. Despite the smog of uncertainty, our findings signal an opportunity for further investigation into the intersection of environmental influences and market dynamics, shedding light on the delicate balance between economic fluctuations and atmospheric perturbations. We hope our research brings a breath of fresh air to the academic community and inspires a wave of interdisciplinary studies that bridge the gap between finance and environmental science.

ChatGPT:

Itaú Unibanco Holding, stock price, air pollution, Vernal Utah, particulate matter, Environmental Protection Agency, LSEG Analytics, correlation coefficient, financial fluctuations, economic modeling, environmental influences, market dynamics, interdisciplinary studies

*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 Vernal, Utah
Detailed data title: Percentage of days with moderate or worse air quality in Vernal, UT
Source: Environmental Protection Agency
See what else correlates with Air pollution in Vernal, Utah

Itaú Unibanco Holding's stock price (ITUB)
Detailed data title: Opening price of Itaú Unibanco Holding (ITUB) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function

See what else correlates with Itaú Unibanco Holding's stock price (ITUB)

Correlation r = 0.7566280 (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 = 0.5724859 (Coefficient of determination)
This means 57.2% of the change in the one variable (i.e., Itaú Unibanco Holding's stock price (ITUB)) is predictable based on the change in the other (i.e., Air pollution in Vernal, Utah) over the 21 years from 2003 through 2023.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 7.21E-5. 0.0000720501454075487700000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.76 in 0.00721% of random cases. Said differently, if you correlated 13,879 random variables Which I absolutely did.
with the same 20 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 20 because we have two variables measured over a period of 21 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.

[ 0.48, 0.9 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
200320042005200620072008200920102011201220132014201520162017201820192020202120222023
Air pollution in Vernal, Utah (Bad air quality days)000041.104354.216930.31554.794546.301452.45963.287735.616431.780831.967243.013748.219238.904130.327939.178129.041152.7473
Itaú Unibanco Holding's stock price (ITUB) (Stock price)0.791.622.514.126.058.64.810.4811.118.547.616.597.063.857.018.879.269.216.113.744.48




Why this works

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




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([0,0,0,0,41.1043,54.2169,30.315,54.7945,46.3014,52.459,63.2877,35.6164,31.7808,31.9672,43.0137,48.2192,38.9041,30.3279,39.1781,29.0411,52.7473,])
array_2 = np.array([0.79,1.62,2.51,4.12,6.05,8.6,4.8,10.48,11.11,8.54,7.61,6.59,7.06,3.85,7.01,8.87,9.26,9.21,6.11,3.74,4.48,])
array_1_name = "Air pollution in Vernal, Utah"
array_2_name = "Itaú Unibanco Holding's stock price (ITUB)"

# 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)



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Correlation ID: 1383 · Black Variable ID: 21390 · Red Variable ID: 1719
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