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Spurious correlation #5,743 · 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 Mobile, Alabama and the second variable is Liquefied petroleum gas used in Sao Tome and Principe.  The chart goes from 2000 to 2007, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the air in Mobile cleared up, it led to less gas being passed around. This, in turn, impacted the global supply and demand for Liquefied petroleum, creating a ripple effect all the way to Sao Tome and Principe. It seems like Mobile's cleaner air didn't just lighten the atmosphere, but also had a knack for putting a lid on gas production. It's a situation where a breath of fresh air in one city became a breath of relief for another, all while reminding us that when it comes to air quality, we're truly in this together. So, let's keep supporting cleaner skies and a healthier planet, because the impact is gas-tly significant!

Model: dalle-3
Prompt: Sure, here is an improved image generation prompt for DALL·E-3: Please create an image of two contrasting scenes: 1. A vibrant and bustling cityscape of Mobile, Alabama with clear, fresh air and a noticeable reduction in air pollutants. 2. A serene and peaceful sunset over the landscape of Sao Tome and Principe, with an emphasis on the impact of the global shift in the supply and demand for Liquefied petroleum gas, showing a ripple effect on the local use of gas. The interconnectedness of these two settings should be emphasized, showcasing the link between air quality and its influence on global resources. The visual should convey the shift in gas production worldwide due to the cleaner air in Mobile, and its impact on the local use of gas in Sao Tome and Principe. 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 Mobile, Alabama and Liquefied petroleum gas used in Sao Tome and Principe. 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: Realistic Hyper-realistic A TIME magazine cover image Cubism Cubism
ChatGPT: A TIME magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Mobile, Alabama and Liquefied petroleum gas used in Sao Tome and Principe, in the following situation: As the air in Mobile cleared up, it led to less gas being passed around. This, in turn, impacted the global supply and demand for Liquefied petroleum, creating a ripple effect all the way to Sao Tome and Principe. It seems like Mobile's cleaner air didn't just lighten the atmosphere, but also had a knack for putting a lid on gas production. It's a situation where a breath of fresh air in one city became a breath of relief for another, all while reminding us that when it comes to air quality, we're truly in this together. So, let's keep supporting cleaner skies and a healthier planet, because the impact is gas-tly significant!. Keep the description simple.
ChatGPT: In Mobile, Alabama, the air is now clear and fresh, with fewer pollutants lingering in the atmosphere. As a result, there's a noticeable decrease in the spread of gas. Meanwhile, in Sao Tome and Principe, this shift in the global supply and demand for Liquefied petroleum gas has a ripple effect, impacting the local use of gas. The cleaner air in Mobile has led to a reduction in gas production worldwide, highlighting the interconnectedness of air quality and its influence on global resources.

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 TIME magazine cover image ] and depicting this scene: In Mobile, Alabama, the air is now clear and fresh, with fewer pollutants lingering in the atmosphere. As a result, there's a noticeable decrease in the spread of gas. Meanwhile, in Sao Tome and Principe, this shift in the global supply and demand for Liquefied petroleum gas has a ripple effect, impacting the local use of gas. The cleaner air in Mobile has led to a reduction in gas production worldwide, highlighting the interconnectedness of air quality and its influence on global resources. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Sure, here is an improved image generation prompt for DALL·E-3: Please create an image of two contrasting scenes: 1. A vibrant and bustling cityscape of Mobile, Alabama with clear, fresh air and a noticeable reduction in air pollutants. 2. A serene and peaceful sunset over the landscape of Sao Tome and Principe, with an emphasis on the impact of the global shift in the supply and demand for Liquefied petroleum gas, showing a ripple effect on the local use of gas. The interconnectedness of these two settings should be emphasized, showcasing the link between air quality and its influence on global resources. The visual should convey the shift in gas production worldwide due to the cleaner air in Mobile, and its impact on the local use of gas in Sao Tome and Principe.

*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 a decrease in Air pollution in Mobile, Alabama caused Liquefied petroleum gas used in Sao Tome and Principe to decrease. Include one good pun.

AI academic paper

(Because p < 0.01)
Gas, Gastronomy, and Geography: The Gassy Connection Between Air Pollution in Mobile, Alabama, and Liquefied Petroleum Gas in Sao Tome and Principe

Journal of Atmospheric Flatulence 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 Mobile, Alabama and Liquefied petroleum gas used in Sao Tome and Principe. Make lots of jokes, goofy observations, and puns.

Make the title a clever pun.

Your research team used data from Environmental Protection Agency and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.8671568 and p < 0.01 for 2000 to 2007.

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]]
"Gas, Gastronomy, and Geography: The Gassy Connection Between Air Pollution in Mobile, Alabama, and Liquefied Petroleum Gas in Sao Tome and Principe"

[[ABSTRACT]]
In this study, we embark on a journey to uncover the fascinating link between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in the exotic archipelago of Sao Tome and Principe. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we delve into the pungent world of gas emissions and atmospheric dynamics. Our findings reveal a correlation coefficient of 0.8671568, suggesting a strong association between the two seemingly disparate locations. With p < 0.01 for the period from 2000 to 2007, this correlation piques our interest, as we ponder the implications of this gaseous connection on environmental and public health policies. Join us as we navigate through the labyrinth of gas-related geopolitics and explore the unexpected ties that bind these distant locales together.


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 Mobile, Alabama and Liquefied petroleum gas used in Sao Tome and Principe. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
"Gas, Gastronomy, and Geography: The Gassy Connection Between Air Pollution in Mobile, Alabama, and Liquefied Petroleum Gas in Sao Tome and Principe"

[[ABSTRACT]]
In this study, we embark on a journey to uncover the fascinating link between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in the exotic archipelago of Sao Tome and Principe. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we delve into the pungent world of gas emissions and atmospheric dynamics. Our findings reveal a correlation coefficient of 0.8671568, suggesting a strong association between the two seemingly disparate locations. With p < 0.01 for the period from 2000 to 2007, this correlation piques our interest, as we ponder the implications of this gaseous connection on environmental and public health policies. Join us as we navigate through the labyrinth of gas-related geopolitics and explore the unexpected ties that bind these distant locales together.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Gas, gas, everywhere! As researchers, we are constantly on the hunt for unexpected relationships, the kind that leaves you gasping for breath in both awe and confusion. In this study, we delve into the intriguing world of air pollution and the usage of liquefied petroleum gas (LPG), taking us on a journey from the pragmatic streets of Mobile, Alabama, to the sun-drenched shores of Sao Tome and Principe. It is a tale of gas, gastronomy, and geography, as we unravel the connection between these seemingly unrelated domains.

Now, you might be wondering, "What's the gas-tronomical significance of such a study?" Well, hang tight, because as we dig into the data from the Environmental Protection Agency and the Energy Information Administration, we uncover a correlation coefficient that's so high, it would make any statistician giddy. With a correlation of 0.8671568, we're talking about a connection so strong, it's like they've been holding hands across the Atlantic Ocean.

But wait, there's more! With a p-value less than 0.01 for the time period from 2000 to 2007, this correlation is not just a fleeting flirtation; it's a long-term relationship that demands attention. We're wading into the murky depths of gas emissions and atmospheric dynamics, grappling with the complexities of environmental interplay like intrepid explorers navigating uncharted territory.

So, as we buckle up for this gaseous adventure, we invite you to join us on this odyssey of unexpected connections, where the air may be heavy with pollutants but the possibilities for groundbreaking discoveries are practically weightless. Let's embark on this journey and unravel the mysteries of gas-related geopolitics that lie beneath the surface of these disparate yet strangely intertwined locations.


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 Mobile, Alabama and Liquefied petroleum gas used in Sao Tome and Principe. Make lots of jokes, goofy observations, and puns.

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 few real TV shows that sound like they might be relevant to the topic that you watched as research.

Here is the title and abstract of the paper:
[[TITLE]]
"Gas, Gastronomy, and Geography: The Gassy Connection Between Air Pollution in Mobile, Alabama, and Liquefied Petroleum Gas in Sao Tome and Principe"

[[ABSTRACT]]
In this study, we embark on a journey to uncover the fascinating link between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in the exotic archipelago of Sao Tome and Principe. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we delve into the pungent world of gas emissions and atmospheric dynamics. Our findings reveal a correlation coefficient of 0.8671568, suggesting a strong association between the two seemingly disparate locations. With p < 0.01 for the period from 2000 to 2007, this correlation piques our interest, as we ponder the implications of this gaseous connection on environmental and public health policies. Join us as we navigate through the labyrinth of gas-related geopolitics and explore the unexpected ties that bind these distant locales together.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Gas, gas, everywhere! As researchers, we are constantly on the hunt for unexpected relationships, the kind that leaves you gasping for breath in both awe and confusion. In this study, we delve into the intriguing world of air pollution and the usage of liquefied petroleum gas (LPG), taking us on a journey from the pragmatic streets of Mobile, Alabama, to the sun-drenched shores of Sao Tome and Principe. It is a tale of gas, gastronomy, and geography, as we unravel the connection between these seemingly unrelated domains.
Now, you might be wondering, "What's the gas-tronomical significance of such a study?" Well, hang tight, because as we dig into the data from the Environmental Protection Agency and the Energy Information Administration, we uncover a correlation coefficient that's so high, it would make any statistician giddy. With a correlation of 0.8671568, we're talking about a connection so strong, it's like they've been holding hands across the Atlantic Ocean.
But wait, there's more! With a p-value less than 0.01 for the time period from 2000 to 2007, this correlation is not just a fleeting flirtation; it's a long-term relationship that demands attention. We're wading into the murky depths of gas emissions and atmospheric dynamics, grappling with the complexities of environmental interplay like intrepid explorers navigating uncharted territory.
So, as we buckle up for this gaseous adventure, we invite you to join us on this odyssey of unexpected connections, where the air may be heavy with pollutants but the possibilities for groundbreaking discoveries are practically weightless. Let's embark on this journey and unravel the mysteries of gas-related geopolitics that lie beneath the surface of these disparate yet strangely intertwined locations.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Smith, Doe, and Jones have diligently explored the interplay between air pollution and its far-reaching effects, while also highlighting the usage of liquefied petroleum gas (LPG) in various global contexts. In "Air Quality: Monitoring, Modeling, and Health Impact," the authors find compelling evidence of the detrimental effects of air pollution on public health, drawing attention to the urgent need for comprehensive regulatory measures. Furthermore, in "Energy Economics," the authors delve into the multifaceted dynamics of LPG usage, shedding light on its economic implications for developing nations.

Venturing beyond the realms of non-fiction literature, the works of fiction also offer curious parallels to our exploration. In "The Smoke Jumper," we encounter a thrilling narrative of environmental activism amidst the backdrop of air pollution, while "The Gaslight Stalker" provides a suspenseful tale that draws uneasy parallels to the insidious presence of gaseous emissions in urban landscapes.

Our research journey also led us to examine television programming for additional insights. Among the informative offerings, "Breaking Bad" and "The Big Bang Theory" surprisingly provided valuable perspectives on the intersection of chemistry and gas dynamics, albeit in a slightly unconventional manner for scholarly pursuits. The suspenseful intrigue of "Stranger Things" and the comedic overtones of "Parks and Recreation" piqued our interest in unexpected ways.

As we trawl through this eclectic mix of literature and media, it becomes evident that our study has more surprising connections than we initially anticipated. This multidisciplinary approach has enriched our understanding, making us acutely aware that the world of gas-related phenomena extends far beyond conventional academic boundaries. With a touch of humor and a dash of whimsy, our gaseous odyssey takes on new dimensions, underscoring the delightful quirks of scholarly inquiry.


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 Mobile, Alabama and Liquefied petroleum gas used in Sao Tome and Principe. Make lots of jokes, goofy observations, and puns. 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 Energy Information Administration . You used data from 2000 to 2007

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]]
"Gas, Gastronomy, and Geography: The Gassy Connection Between Air Pollution in Mobile, Alabama, and Liquefied Petroleum Gas in Sao Tome and Principe"

[[ABSTRACT]]
In this study, we embark on a journey to uncover the fascinating link between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in the exotic archipelago of Sao Tome and Principe. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we delve into the pungent world of gas emissions and atmospheric dynamics. Our findings reveal a correlation coefficient of 0.8671568, suggesting a strong association between the two seemingly disparate locations. With p < 0.01 for the period from 2000 to 2007, this correlation piques our interest, as we ponder the implications of this gaseous connection on environmental and public health policies. Join us as we navigate through the labyrinth of gas-related geopolitics and explore the unexpected ties that bind these distant locales together.

[[INTRODUCTION]]
Gas, gas, everywhere! As researchers, we are constantly on the hunt for unexpected relationships, the kind that leaves you gasping for breath in both awe and confusion. In this study, we delve into the intriguing world of air pollution and the usage of liquefied petroleum gas (LPG), taking us on a journey from the pragmatic streets of Mobile, Alabama, to the sun-drenched shores of Sao Tome and Principe. It is a tale of gas, gastronomy, and geography, as we unravel the connection between these seemingly unrelated domains.
Now, you might be wondering, "What's the gas-tronomical significance of such a study?" Well, hang tight, because as we dig into the data from the Environmental Protection Agency and the Energy Information Administration, we uncover a correlation coefficient that's so high, it would make any statistician giddy. With a correlation of 0.8671568, we're talking about a connection so strong, it's like they've been holding hands across the Atlantic Ocean.
But wait, there's more! With a p-value less than 0.01 for the time period from 2000 to 2007, this correlation is not just a fleeting flirtation; it's a long-term relationship that demands attention. We're wading into the murky depths of gas emissions and atmospheric dynamics, grappling with the complexities of environmental interplay like intrepid explorers navigating uncharted territory.
So, as we buckle up for this gaseous adventure, we invite you to join us on this odyssey of unexpected connections, where the air may be heavy with pollutants but the possibilities for groundbreaking discoveries are practically weightless. Let's embark on this journey and unravel the mysteries of gas-related geopolitics that lie beneath the surface of these disparate yet strangely intertwined locations.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

Ah, the methodology section, where science meets mystery and statistics dance with uncertainty. Join us as we unpack the methods behind this gassy expedition. Our data collection process resembled a grand treasure hunt, except the treasure was information, and the map was the internet – a labyrinthine web of data just waiting to be deciphered. We scoured the Environmental Protection Agency and the Energy Information Administration for valuable nuggets of knowledge, sifting through virtual mountains of data to sculpt our research foundation.

Our journey through the virtual expanse of cyberspace led us to unearth data from the years 2000 to 2007, a time period that, much like a fine wine, had aged gracefully and offered us a ripe sampling of gaseous insights. As our eager fingers navigated the keyboard, we indeed found ourselves at times feeling like intrepid explorers braving uncharted territory.

We utilized a top-secret, super-advanced analytic approach we've affectionately named "The Gaseous Grapple," which involved a complex concoction of statistical analyses, atmospheric modeling, and occasional bouts of interpretive dance to truly grasp the elusive essence of the data. Our team members donned their metaphorical oxygen masks, ready to plunge headfirst into the pungent world of gaseous exploration.

The statistical analyses involved a concoction of correlation coefficients, p-values, and confidence intervals, all swirling together in a beaker of scientific intrigue like something out of a mad chemist's wildest dream. And just as chemists carefully measure and mix their volatile concoctions, we meticulously combined our statistical ingredients to unlock the elusive mysteries shrouded within the data.

With careful consideration, we harnessed the power of regression analysis to untangle the web of relationships between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas in the exotic lands of Sao Tome and Principe. We approached our data with the same precision and dedication as a chef blending the perfect flavors in a gastronomic masterpiece, seeking to extract the most delectable tidbits of information from our twisty, statistical potpourri.

The culmination of our research methods hinged on a myriad of tests, analyses, and deep dives into the vast sea of data. So, as we emerge from the hazy fog of methodology, our gaseous odyssey continues, propelled by the winds of statistical certainty and the tantalizing scent of groundbreaking discoveries just waiting to be unearthed.


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 Mobile, Alabama and Liquefied petroleum gas used in Sao Tome and Principe. Make lots of jokes, goofy observations, and puns. 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 Energy Information Administration .

For the time period 2000 to 2007, you found a correlation 0.8671568, r-squared of 0.7519609, 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]]
"Gas, Gastronomy, and Geography: The Gassy Connection Between Air Pollution in Mobile, Alabama, and Liquefied Petroleum Gas in Sao Tome and Principe"

[[ABSTRACT]]
In this study, we embark on a journey to uncover the fascinating link between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in the exotic archipelago of Sao Tome and Principe. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we delve into the pungent world of gas emissions and atmospheric dynamics. Our findings reveal a correlation coefficient of 0.8671568, suggesting a strong association between the two seemingly disparate locations. With p < 0.01 for the period from 2000 to 2007, this correlation piques our interest, as we ponder the implications of this gaseous connection on environmental and public health policies. Join us as we navigate through the labyrinth of gas-related geopolitics and explore the unexpected ties that bind these distant locales together.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Gas, gas, everywhere! As researchers, we are constantly on the hunt for unexpected relationships, the kind that leaves you gasping for breath in both awe and confusion. In this study, we delve into the intriguing world of air pollution and the usage of liquefied petroleum gas (LPG), taking us on a journey from the pragmatic streets of Mobile, Alabama, to the sun-drenched shores of Sao Tome and Principe. It is a tale of gas, gastronomy, and geography, as we unravel the connection between these seemingly unrelated domains.
Now, you might be wondering, "What's the gas-tronomical significance of such a study?" Well, hang tight, because as we dig into the data from the Environmental Protection Agency and the Energy Information Administration, we uncover a correlation coefficient that's so high, it would make any statistician giddy. With a correlation of 0.8671568, we're talking about a connection so strong, it's like they've been holding hands across the Atlantic Ocean.
But wait, there's more! With a p-value less than 0.01 for the time period from 2000 to 2007, this correlation is not just a fleeting flirtation; it's a long-term relationship that demands attention. We're wading into the murky depths of gas emissions and atmospheric dynamics, grappling with the complexities of environmental interplay like intrepid explorers navigating uncharted territory.
So, as we buckle up for this gaseous adventure, we invite you to join us on this odyssey of unexpected connections, where the air may be heavy with pollutants but the possibilities for groundbreaking discoveries are practically weightless. Let's embark on this journey and unravel the mysteries of gas-related geopolitics that lie beneath the surface of these disparate yet strangely intertwined locations.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The correlation between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in Sao Tome and Principe proved to be nothing short of a breath of fresh air for statisticians and scientists alike. With a correlation coefficient of 0.8671568, it seems the fumes from Mobile found a kindred spirit in the LPG usage of Sao Tome and Principe. Like two star-crossed lovers, these variables danced harmoniously in our statistical tango, leaving us almost dizzy from the robustness of the relationship.

The r-squared value of 0.7519609 further tantalized our scientific palate, suggesting that a whopping 75.19609% of the variation in air pollution in Mobile could be explained by the usage of LPG in Sao Tome and Principe. It's as if the LPG in Sao Tome and Principe whispered sweet nothings to the air pollution in Mobile, persuading it to sway in tandem to the rhythms of atmospheric whims.

To visually encapsulate the strength of this connection, we present Fig. 1, a scatterplot that vividly illustrates the strong correlation between these unlikely companions. It's a sight to behold, like witnessing a cosmic ballet between two celestial bodies, albeit with a touch of industrial fragrance.

And to top it all off, with a p-value of less than 0.01 for the period from 2000 to 2007, this gaseous partnership passed the ultimate test of statistical significance with flying colors. It's not just a mere coincidence; it's a statistically sanctioned marriage of two variables that defied geographical and atmospheric odds.

In conclusion, our findings unveil a truly remarkable link between air pollution in Mobile, Alabama, and the usage of LPG in Sao Tome and Principe, shedding light on the interwoven tapestry of gas dynamics that transcend borders and oceans. This gassy connection challenges conventional wisdom and beckons further exploration into the far-reaching implications for environmental and public health policies. So, buckle up and join us on this comedic journey through the labyrinth of gases, where statistical significance meets the whimsical wonders of atmospheric interplay.


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 Mobile, Alabama and Liquefied petroleum gas used in Sao Tome and Principe. Make lots of jokes, goofy observations, and puns. 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]]
"Gas, Gastronomy, and Geography: The Gassy Connection Between Air Pollution in Mobile, Alabama, and Liquefied Petroleum Gas in Sao Tome and Principe"

[[ABSTRACT]]
In this study, we embark on a journey to uncover the fascinating link between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in the exotic archipelago of Sao Tome and Principe. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we delve into the pungent world of gas emissions and atmospheric dynamics. Our findings reveal a correlation coefficient of 0.8671568, suggesting a strong association between the two seemingly disparate locations. With p < 0.01 for the period from 2000 to 2007, this correlation piques our interest, as we ponder the implications of this gaseous connection on environmental and public health policies. Join us as we navigate through the labyrinth of gas-related geopolitics and explore the unexpected ties that bind these distant locales together.

[[LITERATURE REVIEW]]
Smith, Doe, and Jones have diligently explored the interplay between air pollution and its far-reaching effects, while also highlighting the usage of liquefied petroleum gas (LPG) in various global contexts. In "Air Quality: Monitoring, Modeling, and Health Impact," the authors find compelling evidence of the detrimental effects of air pollution on public health, drawing attention to the urgent need for comprehensive regulatory measures. Furthermore, in "Energy Economics," the authors delve into the multifaceted dynamics of LPG usage, shedding light on its economic implications for developing nations.
Venturing beyond the realms of non-fiction literature, the works of fiction also offer curious parallels to our exploration. In "The Smoke Jumper," we encounter a thrilling narrative of environmental activism amidst the backdrop of air pollution, while "The Gaslight Stalker" provides a suspenseful tale that draws uneasy parallels to the insidious presence of gaseous emissions in urban landscapes.
Our research journey also led us to examine television programming for additional insights. Among the informative offerings, "Breaking Bad" and "The Big Bang Theory" surprisingly provided valuable perspectives on the intersection of chemistry and gas dynamics, albeit in a slightly unconventional manner for scholarly pursuits. The suspenseful intrigue of "Stranger Things" and the comedic overtones of "Parks and Recreation" piqued our interest in unexpected ways.
As we trawl through this eclectic mix of literature and media, it becomes evident that our study has more surprising connections than we initially anticipated. This multidisciplinary approach has enriched our understanding, making us acutely aware that the world of gas-related phenomena extends far beyond conventional academic boundaries. With a touch of humor and a dash of whimsy, our gaseous odyssey takes on new dimensions, underscoring the delightful quirks of scholarly inquiry.

[[RESULTS]]
The correlation between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in Sao Tome and Principe proved to be nothing short of a breath of fresh air for statisticians and scientists alike. With a correlation coefficient of 0.8671568, it seems the fumes from Mobile found a kindred spirit in the LPG usage of Sao Tome and Principe. Like two star-crossed lovers, these variables danced harmoniously in our statistical tango, leaving us almost dizzy from the robustness of the relationship.
The r-squared value of 0.7519609 further tantalized our scientific palate, suggesting that a whopping 75.19609% of the variation in air pollution in Mobile could be explained by the usage of LPG in Sao Tome and Principe. It's as if the LPG in Sao Tome and Principe whispered sweet nothings to the air pollution in Mobile, persuading it to sway in tandem to the rhythms of atmospheric whims.
To visually encapsulate the strength of this connection, we present Fig. 1, a scatterplot that vividly illustrates the strong correlation between these unlikely companions. It's a sight to behold, like witnessing a cosmic ballet between two celestial bodies, albeit with a touch of industrial fragrance.
And to top it all off, with a p-value of less than 0.01 for the period from 2000 to 2007, this gaseous partnership passed the ultimate test of statistical significance with flying colors. It's not just a mere coincidence; it's a statistically sanctioned marriage of two variables that defied geographical and atmospheric odds.
In conclusion, our findings unveil a truly remarkable link between air pollution in Mobile, Alabama, and the usage of LPG in Sao Tome and Principe, shedding light on the interwoven tapestry of gas dynamics that transcend borders and oceans. This gassy connection challenges conventional wisdom and beckons further exploration into the far-reaching implications for environmental and public health policies. So, buckle up and join us on this comedic journey through the labyrinth of gases, where statistical significance meets the whimsical wonders of atmospheric interplay.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of our study have both astonished and amused us, revealing a symbiotic relationship between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in Sao Tome and Principe that would rival even the most endearing rom-coms. The strength of the correlation coefficient, resembling a dynamic duo, exemplifies how these seemingly unrelated variables found common ground, much like Bonny and Clyde, only less felonious and with a whiff of statistical significance.

Building upon the literary meanderings in our literature review, our findings not only validate but also exhilaratingly animate the gasp-inducing parallels we stumbled upon. Like a page-turner, the statistical tango we observed in the correlation coefficient mirrors the pulse-quickening suspense of "The Gaslight Stalker," albeit without the anxiety of imminent peril. In a parallel universe where statistical significance reigns supreme, these variables have woven a thrilling tale of intercontinental intrigue, captivating our hearts and minds.

Let's not forget the scatterplot that visually encapsulated this burgeoning romance between air pollution in Mobile and LPG usage in Sao Tome and Principe. Not just a mere graph, it's an artistic rendition of statistical significance, akin to a Jackson Pollock masterpiece, minus the paint and plus an aromatic elegance that tickles the senses. The whimsical wonders of atmospheric interplay have been brought to life in this visual display, transcending the boundaries of conventional scientific expression with its delightful flair.

Moreover, our results add a quirky twist to the otherwise serious discussion of environmental and public health policies. The gaseous link unveiled in our study challenges conventional wisdom and beckons further exploration, much like a whimsical "Parks and Recreation" episode peppering academia with unexpected levity. It’s a comedic journey through the labyrinth of gases, where statistical significance meets the delightfully unexpected quirks of atmospheric interplay.

We humbly suggest that future research endeavors delve deeper into this gassy odyssey, exploring the impact of this connection on environmental and public health policies, geopolitical dynamics, and perhaps even the potential for transcontinental gas-based gastronomy collaborations. The world of scholarly inquiry, much like the world of gases, is replete with unexpected connections and nuances, awaiting the intrepid souls willing to traverse its tantalizing labyrinth. So, let us embrace the delightful quirks of scholarly inquiry and embark on this whimsical odyssey, one statistical test at a time.


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 Mobile, Alabama and Liquefied petroleum gas used in Sao Tome and Principe. Make lots of jokes, goofy observations, and puns. 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]]
"Gas, Gastronomy, and Geography: The Gassy Connection Between Air Pollution in Mobile, Alabama, and Liquefied Petroleum Gas in Sao Tome and Principe"

[[ABSTRACT]]
In this study, we embark on a journey to uncover the fascinating link between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in the exotic archipelago of Sao Tome and Principe. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we delve into the pungent world of gas emissions and atmospheric dynamics. Our findings reveal a correlation coefficient of 0.8671568, suggesting a strong association between the two seemingly disparate locations. With p < 0.01 for the period from 2000 to 2007, this correlation piques our interest, as we ponder the implications of this gaseous connection on environmental and public health policies. Join us as we navigate through the labyrinth of gas-related geopolitics and explore the unexpected ties that bind these distant locales together.

[[INTRDUCTION]]
Gas, gas, everywhere! As researchers, we are constantly on the hunt for unexpected relationships, the kind that leaves you gasping for breath in both awe and confusion. In this study, we delve into the intriguing world of air pollution and the usage of liquefied petroleum gas (LPG), taking us on a journey from the pragmatic streets of Mobile, Alabama, to the sun-drenched shores of Sao Tome and Principe. It is a tale of gas, gastronomy, and geography, as we unravel the connection between these seemingly unrelated domains.
Now, you might be wondering, "What's the gas-tronomical significance of such a study?" Well, hang tight, because as we dig into the data from the Environmental Protection Agency and the Energy Information Administration, we uncover a correlation coefficient that's so high, it would make any statistician giddy. With a correlation of 0.8671568, we're talking about a connection so strong, it's like they've been holding hands across the Atlantic Ocean.
But wait, there's more! With a p-value less than 0.01 for the time period from 2000 to 2007, this correlation is not just a fleeting flirtation; it's a long-term relationship that demands attention. We're wading into the murky depths of gas emissions and atmospheric dynamics, grappling with the complexities of environmental interplay like intrepid explorers navigating uncharted territory.
So, as we buckle up for this gaseous adventure, we invite you to join us on this odyssey of unexpected connections, where the air may be heavy with pollutants but the possibilities for groundbreaking discoveries are practically weightless. Let's embark on this journey and unravel the mysteries of gas-related geopolitics that lie beneath the surface of these disparate yet strangely intertwined locations.

[[RESULTS]]
The correlation between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in Sao Tome and Principe proved to be nothing short of a breath of fresh air for statisticians and scientists alike. With a correlation coefficient of 0.8671568, it seems the fumes from Mobile found a kindred spirit in the LPG usage of Sao Tome and Principe. Like two star-crossed lovers, these variables danced harmoniously in our statistical tango, leaving us almost dizzy from the robustness of the relationship.
The r-squared value of 0.7519609 further tantalized our scientific palate, suggesting that a whopping 75.19609% of the variation in air pollution in Mobile could be explained by the usage of LPG in Sao Tome and Principe. It's as if the LPG in Sao Tome and Principe whispered sweet nothings to the air pollution in Mobile, persuading it to sway in tandem to the rhythms of atmospheric whims.
To visually encapsulate the strength of this connection, we present Fig. 1, a scatterplot that vividly illustrates the strong correlation between these unlikely companions. It's a sight to behold, like witnessing a cosmic ballet between two celestial bodies, albeit with a touch of industrial fragrance.
And to top it all off, with a p-value of less than 0.01 for the period from 2000 to 2007, this gaseous partnership passed the ultimate test of statistical significance with flying colors. It's not just a mere coincidence; it's a statistically sanctioned marriage of two variables that defied geographical and atmospheric odds.
In conclusion, our findings unveil a truly remarkable link between air pollution in Mobile, Alabama, and the usage of LPG in Sao Tome and Principe, shedding light on the interwoven tapestry of gas dynamics that transcend borders and oceans. This gassy connection challenges conventional wisdom and beckons further exploration into the far-reaching implications for environmental and public health policies. So, buckle up and join us on this comedic journey through the labyrinth of gases, where statistical significance meets the whimsical wonders of atmospheric interplay.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In wrapping up our gaseous escapade, it's clear that the air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in Sao Tome and Principe are more intertwined than a pair of overly friendly molecules at a science mixer. With a correlation coefficient that would make even the most stoic researcher crack a little smile – 0.8671568, to be exact – it's as if these variables were performing a syncopated symphony across the miles.

The r-squared value of 0.7519609 tells us that a whopping 75.19609% of the air pollution in Mobile could be explained by the LPG usage in Sao Tome and Principe. That's a correlation so strong, it's like these two were sharing the same atmospheric cocktail at a research conference.

And let's not forget our statistical stunner, the p-value of less than 0.01 from 2000 to 2007. This isn't just your run-of-the-mill fling between variables; this is the kind of relationship that makes other p-values green with envy.

So, where does this leave us? Well, it's safe to say that we've unraveled a gaseous saga that's as complex and captivating as a soap opera. With such a strong connection between these unlikely companions, it's clear that further research in this area might just be like beating a dead horse – or, in this case, a gasping horse, given the pollution implications.

In conclusion, let's call it a day on this gassy odyssey, secure in the knowledge that the gases in Mobile and Sao Tome and Principe have found their statistical soulmates. There's no need to delve deeper into this particular fart of statistical significance. Case closed, and may the winds of science carry us to new and equally pungent frontiers!


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 Gas, Gastronomy, and Geography: The Gassy Connection Between Air Pollution in Mobile, Alabama, and Liquefied Petroleum Gas in Sao Tome and Principe. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Atmospheric Flatulence 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 Gas, Gastronomy, and Geography: The Gassy Connection Between Air Pollution in Mobile, Alabama, and Liquefied Petroleum Gas in Sao Tome and Principe. Respond only with the name of a fictional organization.

ChatGPT:

Society for Atmospheric Gas Analysis and Culinary Studies


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Gas, Gastronomy, and Geography: The Gassy Connection Between Air Pollution in Mobile, Alabama, and Liquefied Petroleum Gas in Sao Tome and Principe with an abstract of In this study, we embark on a journey to uncover the fascinating link between air pollution in Mobile, Alabama, and the usage of liquefied petroleum gas (LPG) in the exotic archipelago of Sao Tome and Principe. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we delve into the pungent world of gas emissions and atmospheric dynamics. Our findings reveal a correlation coefficient of 0.8671568, suggesting a strong association between the two seemingly disparate locations. With p < 0.01 for the period from 2000 to 2007, this correlation piques our interest, as we ponder the implications of this gaseous connection on environmental and public health policies. Join us as we navigate through the labyrinth of gas-related geopolitics and explore the unexpected ties that bind these distant locales together.

ChatGPT:

Gas emissions, air pollution, liquefied petroleum gas, LPG usage, Mobile Alabama, Sao Tome and Principe, correlation coefficient, atmospheric dynamics, environmental policies, public health policies

*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 Mobile, Alabama
Detailed data title: Percentage of days 'unhealthy' or worse air quality in Mobile, AL
Source: Environmental Protection Agency
See what else correlates with Air pollution in Mobile, Alabama

Liquefied petroleum gas used in Sao Tome and Principe
Detailed data title: Volume of liquefied petroleum gas used consumed in Sao Tome and Principe in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Liquefied petroleum gas used in Sao Tome and Principe

Correlation r = 0.8671568 (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 = 0.7519609 (Coefficient of determination)
This means 75.2% of the change in the one variable (i.e., Liquefied petroleum gas used in Sao Tome and Principe) is predictable based on the change in the other (i.e., Air pollution in Mobile, Alabama) over the 8 years from 2000 through 2007.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.0053. 0.0052924054734058830000000000
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 0.87 in 0.53% of random cases. Said differently, if you correlated 189 random variables Which I absolutely did.
with the same 7 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 7 because we have two variables measured over a period of 8 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.

[ 0.42, 0.98 ] 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.
20002001200220032004200520062007
Air pollution in Mobile, Alabama (Bad air quality days)3.157890.34843200.5524861.114210.2923980.8356550.557103
Liquefied petroleum gas used in Sao Tome and Principe (Million Barrels/Day)0.006021860.0006356160.0006356160.0006356160.001267760.0009534250.004131510.00127123




Why this works

  1. Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  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.
  4. Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.




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([3.15789,0.348432,0,0.552486,1.11421,0.292398,0.835655,0.557103,])
array_2 = np.array([0.00602186,0.000635616,0.000635616,0.000635616,0.00126776,0.000953425,0.00413151,0.00127123,])
array_1_name = "Air pollution in Mobile, Alabama"
array_2_name = "Liquefied petroleum gas used in Sao Tome and Principe"

# 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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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.

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Correlation ID: 5743 · Black Variable ID: 20914 · Red Variable ID: 24876
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