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Spurious correlation #3,562 · 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 Des Moines and the second variable is Liquefied petroleum gas used in Djibouti.  The chart goes from 1989 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As air pollution in Des Moines increased, it created a global demand for clean fuel alternatives. This led to a rise in the production and export of Liquefied petroleum gas in Djibouti, as they saw an opportunity to cash in on the smoggy situation. So, in a strange twist of fate, the dirty air in Des Moines ended up sparking a clean fuel boom in Djibouti. It's like they say, where there's smog, there's LPG!

Model: dalle-3
Prompt: Generate an image that showcases contrast - in the foreground, there's a group of workers installing shiny new LPG tanks despite the heavy smog in Des Moines, representing the city's move towards cleaner energy. In the background, depict the skyline obscured by the smog. Meanwhile, in a separate area, have a fleet of trucks unloading shipments of LPG in Djibouti, symbolizing the global impact of the shift in demand. This should create a visually striking cover image. 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 Des Moines and Liquefied petroleum gas used in Djibouti. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: An image that looks like it is a scene from 'Star Wars' An image that looks like it is a scene from 'Star Wars' Steampunk High-tech A Discovery magazine cover image
ChatGPT: A Discovery magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Des Moines and Liquefied petroleum gas used in Djibouti, in the following situation: Because the air pollution in Des Moines was so bad, it caused the city to seek out cleaner energy sources. This led to a surge in LPG demand, which coincidentally caused a ripple effect in Djibouti. As the saying goes, when Des Moines sneezes, Djibouti catches a clean fuel fever!. Keep the description simple.
ChatGPT: In Des Moines, heavy smog hovers over the city, obscuring the skyline and leaving the air hazy. However, in the midst of this pollution, a group of workers installs shiny new LPG tanks, representing the city's shift towards cleaner energy sources. Meanwhile, in Djibouti, a fleet of trucks unload shipments of LPG, symbolizing the ripple effect caused by the surge in demand from Des Moines.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A Discovery magazine cover image ] and depicting this scene: In Des Moines, heavy smog hovers over the city, obscuring the skyline and leaving the air hazy. However, in the midst of this pollution, a group of workers installs shiny new LPG tanks, representing the city's shift towards cleaner energy sources. Meanwhile, in Djibouti, a fleet of trucks unload shipments of LPG, symbolizing the ripple effect caused by the surge in demand from Des Moines. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that showcases contrast - in the foreground, there's a group of workers installing shiny new LPG tanks despite the heavy smog in Des Moines, representing the city's move towards cleaner energy. In the background, depict the skyline obscured by the smog. Meanwhile, in a separate area, have a fleet of trucks unloading shipments of LPG in Djibouti, symbolizing the global impact of the shift in demand. This should create a visually striking cover image.

*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 increases in Air pollution in Des Moines positively influenced Liquefied petroleum gas used in Djibouti. Include one good pun.

AI academic paper

(Because p < 0.01)
Asthma Drama: Air Pollution in Des Moines and Liquefied Petroleum Gas in Djibouti

The International Journal of Environmental Health and Atmospheric Chemistry

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 witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Des Moines and Liquefied petroleum gas used in Djibouti. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Rhyme words in the title.

Your research team used data from Environmental Protection Agency and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.8510556 and p < 0.01 for 1989 to 2021.

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]]
Asthma Drama: Air Pollution in Des Moines and Liquefied Petroleum Gas in Djibouti

[[ABSTRACT]]
This research delves into the tantalizing correlation between air pollution in Des Moines and the usage of liquefied petroleum gas in Djibouti. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we elucidate a correlation coefficient of 0.8510556 and a remarkable p-value of less than 0.01 for the period spanning 1989 to 2021. The tantalizing link between these two seemingly disparate phenomena raises eyebrows and tickles the imagination of researchers. Our findings provoke a reevaluation of current theories surrounding air pollution and energy usage, providing a breath of fresh air in the field of environmental research.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Des Moines and Liquefied petroleum gas used in Djibouti. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
Asthma Drama: Air Pollution in Des Moines and Liquefied Petroleum Gas in Djibouti

[[ABSTRACT]]
This research delves into the tantalizing correlation between air pollution in Des Moines and the usage of liquefied petroleum gas in Djibouti. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we elucidate a correlation coefficient of 0.8510556 and a remarkable p-value of less than 0.01 for the period spanning 1989 to 2021. The tantalizing link between these two seemingly disparate phenomena raises eyebrows and tickles the imagination of researchers. Our findings provoke a reevaluation of current theories surrounding air pollution and energy usage, providing a breath of fresh air in the field of environmental research.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

As the global community continues to grapple with the complexities of air quality and energy consumption, the relationship between air pollution and the utilization of liquefied petroleum gas (LPG) has emerged as an intriguing area of inquiry. The seemingly incongruous pairing of Des Moines, Iowa, and Djibouti, a small yet mighty nation nestled on the Horn of Africa, may initially strike one as unlikely bedfellows in the realm of environmental analysis. However, as we delve into the data, a compelling correlation between the two begins to unfold, much like a suspenseful plot twist in a gripping novel.

The prevalence of asthma and other respiratory ailments in Des Moines has long been a source of concern for public health officials, while Djibouti's embrace of liquefied petroleum gas as a primary energy source has piqued the interest of energy analysts. Intriguingly, these seemingly disparate phenomena have sparked our curiosity, igniting a spark of inquiry into the web of interconnected environmental factors that extend far beyond geographical boundaries.

The serendipitous confluence of data from the Environmental Protection Agency and the Energy Information Administration has allowed us to embark on a statistical odyssey, culminating in the unearthing of a correlation coefficient of 0.8510556 and a p-value that gleamed brightly at less than 0.01, affirming the robustness of the relationship between air pollution in Des Moines and the usage of LPG in Djibouti. These numerical revelations, akin to a thought-provoking plot twist in a classic whodunit, beckon us to unravel the underlying mechanisms driving this unlikely yet captivating correlation.

Our research takes a fresh air approach, diving into the abyss of data spanning over three decades, unearthing insights that may prompt a paradigm shift in the current lexicon of environmental research. With a nod to the unexpected and a wink at traditional scientific boundaries, we invite our readers to embark on this asthmatic adventure, as we untangle the intricacies of asthma drama and its entanglement with air pollution and liquefied petroleum gas.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Des Moines and Liquefied petroleum gas used in Djibouti. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
Asthma Drama: Air Pollution in Des Moines and Liquefied Petroleum Gas in Djibouti

[[ABSTRACT]]
This research delves into the tantalizing correlation between air pollution in Des Moines and the usage of liquefied petroleum gas in Djibouti. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we elucidate a correlation coefficient of 0.8510556 and a remarkable p-value of less than 0.01 for the period spanning 1989 to 2021. The tantalizing link between these two seemingly disparate phenomena raises eyebrows and tickles the imagination of researchers. Our findings provoke a reevaluation of current theories surrounding air pollution and energy usage, providing a breath of fresh air in the field of environmental research.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As the global community continues to grapple with the complexities of air quality and energy consumption, the relationship between air pollution and the utilization of liquefied petroleum gas (LPG) has emerged as an intriguing area of inquiry. The seemingly incongruous pairing of Des Moines, Iowa, and Djibouti, a small yet mighty nation nestled on the Horn of Africa, may initially strike one as unlikely bedfellows in the realm of environmental analysis. However, as we delve into the data, a compelling correlation between the two begins to unfold, much like a suspenseful plot twist in a gripping novel.
The prevalence of asthma and other respiratory ailments in Des Moines has long been a source of concern for public health officials, while Djibouti's embrace of liquefied petroleum gas as a primary energy source has piqued the interest of energy analysts. Intriguingly, these seemingly disparate phenomena have sparked our curiosity, igniting a spark of inquiry into the web of interconnected environmental factors that extend far beyond geographical boundaries.
The serendipitous confluence of data from the Environmental Protection Agency and the Energy Information Administration has allowed us to embark on a statistical odyssey, culminating in the unearthing of a correlation coefficient of 0.8510556 and a p-value that gleamed brightly at less than 0.01, affirming the robustness of the relationship between air pollution in Des Moines and the usage of LPG in Djibouti. These numerical revelations, akin to a thought-provoking plot twist in a classic whodunit, beckon us to unravel the underlying mechanisms driving this unlikely yet captivating correlation.
Our research takes a fresh air approach, diving into the abyss of data spanning over three decades, unearthing insights that may prompt a paradigm shift in the current lexicon of environmental research. With a nod to the unexpected and a wink at traditional scientific boundaries, we invite our readers to embark on this asthmatic adventure, as we untangle the intricacies of asthma drama and its entanglement with air pollution and liquefied petroleum gas.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The exploration of the intriguing correlation between air pollution in Des Moines and the consumption of liquefied petroleum gas in Djibouti has sparked a deluge of research, replete with a litany of findings that range from the mundane to the positively captivating. From the works of Smith, Doe, and Jones - stalwart figures in the field of environmental analysis - to more unconventional sources of insight, the quest to unravel the enigmatic linkage between these two disparate phenomena has been both exhaustive and exhilarating.

In "Air Quality and Respiratory Health in Urban Environments," Smith et al. emphasize the detrimental impact of air pollution on respiratory well-being, echoing the concerns surrounding asthma prevalence in Des Moines. Similarly, Doe's seminal work, "Liquefied Petroleum Gas: A Tale of Energy and Emissions," sheds light on the usage of LPG as a significant energy source in Djibouti, providing a contextual backdrop for the investigation at hand. Furthermore, Jones' comprehensive analysis of "Environmental Implications of Energy Choices" offers a comprehensive overview of the environmental ramifications of different energy sources, encompassing potential linkages to air pollution trends.

Transitioning from the realm of academic treatises to more accessible literature, non-fictional works such as "The Air We Breathe: A Comprehensive Overview of Urban Air Quality" and "Energy Conundrums: From Fossil Fuels to Liquefied Petroleum Gas" serve as accessible windows into the complex interplay between air pollution and energy utilization. In a similar vein, fictional narratives such as "Smoke and Fire: A Tale of Environmental Intrigue" and "The Gas Chronicles: A Saga of Energy and Atmosphere" offer allegorical perspectives on the multifaceted dynamics underlying our research inquiry.

An unexpected treasure trove of insight has arisen from the unlikeliest of sources, with social media platforms providing an eclectic array of perspectives from individuals recounting their experiences with air pollution and LPG usage. From impassioned tweets detailing the perils of urban smog to witty Instagram posts showcasing the versatility of LPG in culinary pursuits, these digital anecdotes serve as a colorful mosaic that enriches our understanding of the societal implications of our research findings.



Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Des Moines and Liquefied petroleum gas used in Djibouti. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Energy Information Administration . You used data from 1989 to 2021

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]]
Asthma Drama: Air Pollution in Des Moines and Liquefied Petroleum Gas in Djibouti

[[ABSTRACT]]
This research delves into the tantalizing correlation between air pollution in Des Moines and the usage of liquefied petroleum gas in Djibouti. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we elucidate a correlation coefficient of 0.8510556 and a remarkable p-value of less than 0.01 for the period spanning 1989 to 2021. The tantalizing link between these two seemingly disparate phenomena raises eyebrows and tickles the imagination of researchers. Our findings provoke a reevaluation of current theories surrounding air pollution and energy usage, providing a breath of fresh air in the field of environmental research.

[[INTRODUCTION]]
As the global community continues to grapple with the complexities of air quality and energy consumption, the relationship between air pollution and the utilization of liquefied petroleum gas (LPG) has emerged as an intriguing area of inquiry. The seemingly incongruous pairing of Des Moines, Iowa, and Djibouti, a small yet mighty nation nestled on the Horn of Africa, may initially strike one as unlikely bedfellows in the realm of environmental analysis. However, as we delve into the data, a compelling correlation between the two begins to unfold, much like a suspenseful plot twist in a gripping novel.
The prevalence of asthma and other respiratory ailments in Des Moines has long been a source of concern for public health officials, while Djibouti's embrace of liquefied petroleum gas as a primary energy source has piqued the interest of energy analysts. Intriguingly, these seemingly disparate phenomena have sparked our curiosity, igniting a spark of inquiry into the web of interconnected environmental factors that extend far beyond geographical boundaries.
The serendipitous confluence of data from the Environmental Protection Agency and the Energy Information Administration has allowed us to embark on a statistical odyssey, culminating in the unearthing of a correlation coefficient of 0.8510556 and a p-value that gleamed brightly at less than 0.01, affirming the robustness of the relationship between air pollution in Des Moines and the usage of LPG in Djibouti. These numerical revelations, akin to a thought-provoking plot twist in a classic whodunit, beckon us to unravel the underlying mechanisms driving this unlikely yet captivating correlation.
Our research takes a fresh air approach, diving into the abyss of data spanning over three decades, unearthing insights that may prompt a paradigm shift in the current lexicon of environmental research. With a nod to the unexpected and a wink at traditional scientific boundaries, we invite our readers to embark on this asthmatic adventure, as we untangle the intricacies of asthma drama and its entanglement with air pollution and liquefied petroleum gas.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To unravel the enigmatic link between air pollution in Des Moines and the utilization of liquefied petroleum gas (LPG) in Djibouti, our research team embarked on a methodological escapade that involved a smorgasbord of data collection and statistical analysis. Our data, sourced primarily from the Environmental Protection Agency and the Energy Information Administration, served as the foundation for this investigative journey spanning from 1989 to 2021.

First and foremost, we set out to compile comprehensive datasets on air quality indicators in Des Moines, including but not limited to particulate matter, nitrogen dioxide, and ozone levels. In a bid to capture the multifaceted nature of air pollution, we cast a wide net across various sources, exercising due diligence to ensure the integrity and representativeness of the data. As we dove headfirst into the sea of information, it became clearer than the Iowa skies in spring that meticulous data curation was crucial in capturing the nuances of air quality fluctuations over the decades.

Simultaneously, our quirky crew delved into the eccentric world of liquefied petroleum gas (LPG) consumption in Djibouti, leveraging data on production, consumption patterns, and import/export figures to paint a vivid portrait of the nation's energetic endeavors. We navigated through the labyrinthine pathways of energy statistics, braving the occasional statistical anomalies that leapt out like mischievous gremlins in the data.

With our data marshaled into proper formation, we unleashed the formidable power of statistical analysis, employing the time-honored tools of correlation coefficients and p-values to illuminate the potential relationship between air pollution in Des Moines and LPG usage in Djibouti. Through regressions and other statistical techniques, we sought to discern whether the dance of the data points revealed a harmonious waltz or a discordant cacophony, akin to an orchestra tuning before a symphony.

Additionally, our intrepid team explored the ecological, socio-economic, and geopolitical implications underlying the observed correlation, delving into the interconnected web of environmental factors with the gusto of pioneers exploring uncharted territories. While the brunt of our analysis focused on quantitative methods, qualitative insights shimmered through like hidden gems, adding layers of complexity to our understanding of the intertwining narratives of air pollution and LPG usage.

In sum, our methodology weaves together the threads of meticulous data collection, rigorous statistical analysis, and a dash of creative interpretation, akin to a master chef concocting a delectable scientific dish. This methodological potpourri, flavored with a hint of whimsy, served as the conduit for unlocking the tantalizing correlation between air pollution in Des Moines and liquefied petroleum gas in Djibouti, beckoning us to look beyond the surface and unearth the quirky parallels that lie beneath.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Des Moines and Liquefied petroleum gas used in Djibouti. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Energy Information Administration .

For the time period 1989 to 2021, you found a correlation 0.8510556, r-squared of 0.7242956, 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]]
Asthma Drama: Air Pollution in Des Moines and Liquefied Petroleum Gas in Djibouti

[[ABSTRACT]]
This research delves into the tantalizing correlation between air pollution in Des Moines and the usage of liquefied petroleum gas in Djibouti. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we elucidate a correlation coefficient of 0.8510556 and a remarkable p-value of less than 0.01 for the period spanning 1989 to 2021. The tantalizing link between these two seemingly disparate phenomena raises eyebrows and tickles the imagination of researchers. Our findings provoke a reevaluation of current theories surrounding air pollution and energy usage, providing a breath of fresh air in the field of environmental research.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
As the global community continues to grapple with the complexities of air quality and energy consumption, the relationship between air pollution and the utilization of liquefied petroleum gas (LPG) has emerged as an intriguing area of inquiry. The seemingly incongruous pairing of Des Moines, Iowa, and Djibouti, a small yet mighty nation nestled on the Horn of Africa, may initially strike one as unlikely bedfellows in the realm of environmental analysis. However, as we delve into the data, a compelling correlation between the two begins to unfold, much like a suspenseful plot twist in a gripping novel.
The prevalence of asthma and other respiratory ailments in Des Moines has long been a source of concern for public health officials, while Djibouti's embrace of liquefied petroleum gas as a primary energy source has piqued the interest of energy analysts. Intriguingly, these seemingly disparate phenomena have sparked our curiosity, igniting a spark of inquiry into the web of interconnected environmental factors that extend far beyond geographical boundaries.
The serendipitous confluence of data from the Environmental Protection Agency and the Energy Information Administration has allowed us to embark on a statistical odyssey, culminating in the unearthing of a correlation coefficient of 0.8510556 and a p-value that gleamed brightly at less than 0.01, affirming the robustness of the relationship between air pollution in Des Moines and the usage of LPG in Djibouti. These numerical revelations, akin to a thought-provoking plot twist in a classic whodunit, beckon us to unravel the underlying mechanisms driving this unlikely yet captivating correlation.
Our research takes a fresh air approach, diving into the abyss of data spanning over three decades, unearthing insights that may prompt a paradigm shift in the current lexicon of environmental research. With a nod to the unexpected and a wink at traditional scientific boundaries, we invite our readers to embark on this asthmatic adventure, as we untangle the intricacies of asthma drama and its entanglement with air pollution and liquefied petroleum gas.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our investigation have revealed a striking correlation between air pollution in Des Moines and the usage of liquefied petroleum gas (LPG) in Djibouti, much like the unexpected pairing of peanut butter and jelly – seemingly disparate on their own, yet creating a compelling combination when brought together. Our analysis, spanning from the year 1989 to 2021, unearthed a correlation coefficient of 0.8510556, with an r-squared value of 0.7242956 and a p-value that gleamed like a gem at less than 0.01. These findings have added a breath of fresh air to the discourse surrounding environmental research, raising eyebrows and prompting further inquiry into the interplay of air quality and energy usage on a global scale.

Fig. 1 presents a scatterplot depicting the robust correlation between air pollution in Des Moines and the usage of LPG in Djibouti, much like a dynamic dance between two unexpected partners. The scatterplot serves as a visual testament to the strong relationship uncovered through our analysis, inviting researchers to marvel at the undeniable connection between these seemingly unrelated variables.

Our investigation has not only shed light on the correlation between air pollution in Des Moines and the usage of LPG in Djibouti but has also highlighted the interconnectedness of environmental phenomena across geographical boundaries. The tantalizing link between these two variables sparks curiosity, ignites a spark of inquiry, and beckons researchers to delve deeper into the intricate web of environmental factors that transcend traditional boundaries, much like peeling back the layers of a particularly suspenseful onion.

In conclusion, our findings beckon the scientific community to embrace this asthmatic adventure, adopting a fresh air approach to unraveling the complexities of air pollution and liquefied petroleum gas usage. These results may lead to a paradigm shift in our understanding of the environmental and public health implications of air quality and energy consumption, injecting a breath of fresh air into the discourse and propelling us into a new era of environmental research.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Des Moines and Liquefied petroleum gas used in Djibouti. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
Asthma Drama: Air Pollution in Des Moines and Liquefied Petroleum Gas in Djibouti

[[ABSTRACT]]
This research delves into the tantalizing correlation between air pollution in Des Moines and the usage of liquefied petroleum gas in Djibouti. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we elucidate a correlation coefficient of 0.8510556 and a remarkable p-value of less than 0.01 for the period spanning 1989 to 2021. The tantalizing link between these two seemingly disparate phenomena raises eyebrows and tickles the imagination of researchers. Our findings provoke a reevaluation of current theories surrounding air pollution and energy usage, providing a breath of fresh air in the field of environmental research.

[[LITERATURE REVIEW]]
The exploration of the intriguing correlation between air pollution in Des Moines and the consumption of liquefied petroleum gas in Djibouti has sparked a deluge of research, replete with a litany of findings that range from the mundane to the positively captivating. From the works of Smith, Doe, and Jones - stalwart figures in the field of environmental analysis - to more unconventional sources of insight, the quest to unravel the enigmatic linkage between these two disparate phenomena has been both exhaustive and exhilarating.
In "Air Quality and Respiratory Health in Urban Environments," Smith et al. emphasize the detrimental impact of air pollution on respiratory well-being, echoing the concerns surrounding asthma prevalence in Des Moines. Similarly, Doe's seminal work, "Liquefied Petroleum Gas: A Tale of Energy and Emissions," sheds light on the usage of LPG as a significant energy source in Djibouti, providing a contextual backdrop for the investigation at hand. Furthermore, Jones' comprehensive analysis of "Environmental Implications of Energy Choices" offers a comprehensive overview of the environmental ramifications of different energy sources, encompassing potential linkages to air pollution trends.
Transitioning from the realm of academic treatises to more accessible literature, non-fictional works such as "The Air We Breathe: A Comprehensive Overview of Urban Air Quality" and "Energy Conundrums: From Fossil Fuels to Liquefied Petroleum Gas" serve as accessible windows into the complex interplay between air pollution and energy utilization. In a similar vein, fictional narratives such as "Smoke and Fire: A Tale of Environmental Intrigue" and "The Gas Chronicles: A Saga of Energy and Atmosphere" offer allegorical perspectives on the multifaceted dynamics underlying our research inquiry.
An unexpected treasure trove of insight has arisen from the unlikeliest of sources, with social media platforms providing an eclectic array of perspectives from individuals recounting their experiences with air pollution and LPG usage. From impassioned tweets detailing the perils of urban smog to witty Instagram posts showcasing the versatility of LPG in culinary pursuits, these digital anecdotes serve as a colorful mosaic that enriches our understanding of the societal implications of our research findings.


[[RESULTS]]
The results of our investigation have revealed a striking correlation between air pollution in Des Moines and the usage of liquefied petroleum gas (LPG) in Djibouti, much like the unexpected pairing of peanut butter and jelly – seemingly disparate on their own, yet creating a compelling combination when brought together. Our analysis, spanning from the year 1989 to 2021, unearthed a correlation coefficient of 0.8510556, with an r-squared value of 0.7242956 and a p-value that gleamed like a gem at less than 0.01. These findings have added a breath of fresh air to the discourse surrounding environmental research, raising eyebrows and prompting further inquiry into the interplay of air quality and energy usage on a global scale.
Fig. 1 presents a scatterplot depicting the robust correlation between air pollution in Des Moines and the usage of LPG in Djibouti, much like a dynamic dance between two unexpected partners. The scatterplot serves as a visual testament to the strong relationship uncovered through our analysis, inviting researchers to marvel at the undeniable connection between these seemingly unrelated variables.
Our investigation has not only shed light on the correlation between air pollution in Des Moines and the usage of LPG in Djibouti but has also highlighted the interconnectedness of environmental phenomena across geographical boundaries. The tantalizing link between these two variables sparks curiosity, ignites a spark of inquiry, and beckons researchers to delve deeper into the intricate web of environmental factors that transcend traditional boundaries, much like peeling back the layers of a particularly suspenseful onion.
In conclusion, our findings beckon the scientific community to embrace this asthmatic adventure, adopting a fresh air approach to unraveling the complexities of air pollution and liquefied petroleum gas usage. These results may lead to a paradigm shift in our understanding of the environmental and public health implications of air quality and energy consumption, injecting a breath of fresh air into the discourse and propelling us into a new era of environmental research.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our findings not only corroborate but also significantly bolster the existing literature, much like a well-timed gust of wind fortifying a meticulously constructed house of cards. The correlation coefficient of 0.8510556 we unearthed aligns harmoniously with the concerns raised in Smith's work on air quality and respiratory health, whose insights were as foundational as the bedrock of Djibouti's coastline. The pertinence of this discovery to Des Moines' asthma prevalence is almost as clear as the polluted air hovering over a bustling cityscape. Similarly, the resounding support for Doe's narrative of Liquefied Petroleum Gas as a vital energy source in Djibouti is akin to uncovering a treasure trove of data gold.

Our results, like a perfectly choreographed ballet performance, dance in sync with Jones' comprehensive analysis, demonstrating the profound environmental implications of energy choices and offering an exquisite pas de deux of empirical validation. The p-value, shimmering as brightly as a Djiboutian sunrise, reaffirms the robustness of our findings and underscores the unassailable strength of the relationship between air pollution in Des Moines and LPG usage in Djibouti.

The unexpected perspectives from social media, much like a lively potpourri of vibrant colors in an otherwise monochrome landscape, have enriched our understanding of the fascinating interplay between air pollution and LPG usage. The anecdotes, as diverse as the eclectic ingredients in a culinary kaleidoscope, further underscore the societal ramifications of our research inquiries.

In stride with the burgeoning body of research, our investigation elucidates the interconnectedness of environmental phenomena across geographic boundaries, like a harmonious symphony resonating through the global air. Our findings provoke a reevaluation of established paradigms, breathing new life into the discourse surrounding environmental research, much like a breath of fresh air into a musty room.

Our study, like a gust of wind sweeping through a stuffy room, has pushed open a window of opportunity for future research, inviting scholars to embark on an adventurous expedition into the enigmatic realm of air pollution and energy utilization, much like a scientific odyssey. Without a doubt, our results have positioned us at the cusp of a new era of environmental inquiry, beckoning the scientific community to embrace this asthmatic adventure with a fresh air approach, much like taking a leisurely stroll on a crisp morning.

These findings manifest as a testament to the enduring value of pursuing seemingly unrelated variables, reminding us of the delightful surprises and unanticipated connections that underpin the perpetually fascinating field of research.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Des Moines and Liquefied petroleum gas used in Djibouti. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Asthma Drama: Air Pollution in Des Moines and Liquefied Petroleum Gas in Djibouti

[[ABSTRACT]]
This research delves into the tantalizing correlation between air pollution in Des Moines and the usage of liquefied petroleum gas in Djibouti. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we elucidate a correlation coefficient of 0.8510556 and a remarkable p-value of less than 0.01 for the period spanning 1989 to 2021. The tantalizing link between these two seemingly disparate phenomena raises eyebrows and tickles the imagination of researchers. Our findings provoke a reevaluation of current theories surrounding air pollution and energy usage, providing a breath of fresh air in the field of environmental research.

[[INTRDUCTION]]
As the global community continues to grapple with the complexities of air quality and energy consumption, the relationship between air pollution and the utilization of liquefied petroleum gas (LPG) has emerged as an intriguing area of inquiry. The seemingly incongruous pairing of Des Moines, Iowa, and Djibouti, a small yet mighty nation nestled on the Horn of Africa, may initially strike one as unlikely bedfellows in the realm of environmental analysis. However, as we delve into the data, a compelling correlation between the two begins to unfold, much like a suspenseful plot twist in a gripping novel.
The prevalence of asthma and other respiratory ailments in Des Moines has long been a source of concern for public health officials, while Djibouti's embrace of liquefied petroleum gas as a primary energy source has piqued the interest of energy analysts. Intriguingly, these seemingly disparate phenomena have sparked our curiosity, igniting a spark of inquiry into the web of interconnected environmental factors that extend far beyond geographical boundaries.
The serendipitous confluence of data from the Environmental Protection Agency and the Energy Information Administration has allowed us to embark on a statistical odyssey, culminating in the unearthing of a correlation coefficient of 0.8510556 and a p-value that gleamed brightly at less than 0.01, affirming the robustness of the relationship between air pollution in Des Moines and the usage of LPG in Djibouti. These numerical revelations, akin to a thought-provoking plot twist in a classic whodunit, beckon us to unravel the underlying mechanisms driving this unlikely yet captivating correlation.
Our research takes a fresh air approach, diving into the abyss of data spanning over three decades, unearthing insights that may prompt a paradigm shift in the current lexicon of environmental research. With a nod to the unexpected and a wink at traditional scientific boundaries, we invite our readers to embark on this asthmatic adventure, as we untangle the intricacies of asthma drama and its entanglement with air pollution and liquefied petroleum gas.

[[RESULTS]]
The results of our investigation have revealed a striking correlation between air pollution in Des Moines and the usage of liquefied petroleum gas (LPG) in Djibouti, much like the unexpected pairing of peanut butter and jelly – seemingly disparate on their own, yet creating a compelling combination when brought together. Our analysis, spanning from the year 1989 to 2021, unearthed a correlation coefficient of 0.8510556, with an r-squared value of 0.7242956 and a p-value that gleamed like a gem at less than 0.01. These findings have added a breath of fresh air to the discourse surrounding environmental research, raising eyebrows and prompting further inquiry into the interplay of air quality and energy usage on a global scale.
Fig. 1 presents a scatterplot depicting the robust correlation between air pollution in Des Moines and the usage of LPG in Djibouti, much like a dynamic dance between two unexpected partners. The scatterplot serves as a visual testament to the strong relationship uncovered through our analysis, inviting researchers to marvel at the undeniable connection between these seemingly unrelated variables.
Our investigation has not only shed light on the correlation between air pollution in Des Moines and the usage of LPG in Djibouti but has also highlighted the interconnectedness of environmental phenomena across geographical boundaries. The tantalizing link between these two variables sparks curiosity, ignites a spark of inquiry, and beckons researchers to delve deeper into the intricate web of environmental factors that transcend traditional boundaries, much like peeling back the layers of a particularly suspenseful onion.
In conclusion, our findings beckon the scientific community to embrace this asthmatic adventure, adopting a fresh air approach to unraveling the complexities of air pollution and liquefied petroleum gas usage. These results may lead to a paradigm shift in our understanding of the environmental and public health implications of air quality and energy consumption, injecting a breath of fresh air into the discourse and propelling us into a new era of environmental research.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study has revealed a compelling correlation between air pollution in Des Moines and the usage of liquefied petroleum gas (LPG) in Djibouti, akin to the surprising harmony of a peanut butter and jelly pair. The robust correlation coefficient of 0.8510556 and the gleaming p-value of less than 0.01 have illuminated this unexpected relationship, triggering a wave of curiosity that could rival the astonishment of discovering a hidden treasure. Our findings not only provide a breath of fresh air in the field of environmental research but also prompt a reevaluation of prevailing theories and conventional wisdom, much like a gust of wind that sweeps away old cobwebs.

The scatterplot, a visual testament to the strong correlation, invites researchers to marvel at the dance between these seemingly unrelated variables, akin to witnessing a choreographed tango between two unassuming partners. This revelation urges the scientific community to embrace this asthmatic adventure, pressing forward with a fresh air approach to unravel the intricate web of environmental factors that extend beyond traditional boundaries. The interconnectedness of these phenomena, much like peeling back the layers of a particularly suspenseful onion, has sparked a new wave of inquiry and analysis that may lead to a paradigm shift in the way we comprehend the environmental and public health implications of air quality and energy consumption.

Therefore, no further research is advisable in this area. It's time to breathe a sigh of relief and let these findings settle, like dust particles in a sunbeam.


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 Asthma Drama: Air Pollution in Des Moines and Liquefied Petroleum Gas in Djibouti. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of Environmental Health and Atmospheric Chemistry


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 Asthma Drama: Air Pollution in Des Moines and Liquefied Petroleum Gas in Djibouti. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Global Air Quality and Environmental Health


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 Asthma Drama: Air Pollution in Des Moines and Liquefied Petroleum Gas in Djibouti with an abstract of This research delves into the tantalizing correlation between air pollution in Des Moines and the usage of liquefied petroleum gas in Djibouti. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we elucidate a correlation coefficient of 0.8510556 and a remarkable p-value of less than 0.01 for the period spanning 1989 to 2021. The tantalizing link between these two seemingly disparate phenomena raises eyebrows and tickles the imagination of researchers. Our findings provoke a reevaluation of current theories surrounding air pollution and energy usage, providing a breath of fresh air in the field of environmental research.

ChatGPT:

air pollution, Des Moines, liquefied petroleum gas, Djibouti, correlation, Environmental Protection Agency, Energy Information Administration, correlation coefficient, p-value, 1989-2021, environmental research, asthma, air quality

*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 Des Moines
Detailed data title: Percentage of days with moderate or worse air quality in Des Moines-West Des Moines, IA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Des Moines

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

Correlation r = 0.8510556 (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 = 0.7242956 (Coefficient of determination)
This means 72.4% of the change in the one variable (i.e., Liquefied petroleum gas used in Djibouti) is predictable based on the change in the other (i.e., Air pollution in Des Moines) over the 33 years from 1989 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.51E-10. 0.0000000003505871088906282500
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 0.85 in 3.51E-8% of random cases. Said differently, if you correlated 2,852,358,158 random variables You don't actually need 2 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 32 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 32 because we have two variables measured over a period of 33 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.

[ 0.72, 0.92 ] 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.
198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320142015201620172018201920202021
Air pollution in Des Moines (Bad air quality days)15.616415.61649.8630116.913912.45910.684915.342510.92917.174510.958926.027445.08238.630135.068536.438429.23539.72629.315138.082236.61229.041132.876731.780834.972728.767121.917819.178114.75412022.191816.164415.84722.1918
Liquefied petroleum gas used in Djibouti (Million Barrels/Day)0.20.20.20.20.20.20.20.20.20.20.20.792350.7945210.7945210.7945210.7289620.6991780.6673970.6356160.633880.6356160.6356160.6356160.6356160.6356160.6356160.5974790.4754090.4767120.4767120.4767120.4551690.48028




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([15.6164,15.6164,9.86301,16.9139,12.459,10.6849,15.3425,10.929,17.1745,10.9589,26.0274,45.082,38.6301,35.0685,36.4384,29.235,39.726,29.3151,38.0822,36.612,29.0411,32.8767,31.7808,34.9727,28.7671,21.9178,19.1781,14.7541,20,22.1918,16.1644,15.847,22.1918,])
array_2 = np.array([0.2,0.2,0.2,0.2,0.2,0.2,0.2,0.2,0.2,0.2,0.2,0.79235,0.794521,0.794521,0.794521,0.728962,0.699178,0.667397,0.635616,0.63388,0.635616,0.635616,0.635616,0.635616,0.635616,0.635616,0.597479,0.475409,0.476712,0.476712,0.476712,0.455169,0.48028,])
array_1_name = "Air pollution in Des Moines"
array_2_name = "Liquefied petroleum gas used in Djibouti"

# 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: 3562 · Black Variable ID: 20545 · Red Variable ID: 24356
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