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Spurious correlation #5,459 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air quality in Ogden, Utah and the second variable is Amazon's Annual Outbound Shipping Expenditure in Millions.  The chart goes from 2006 to 2016, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the air quality in Ogden improved, the local birds became more energized and efficient. These highly motivated birds began offering premium express shipping services to Amazon, completely free of charge. This unexpected avian assistance led to a significant increase in Amazon's outbound shipping expenditure as they tried to keep up with the feathered delivery competition. It turns out that when it comes to shipping, the early bird really does get the package!

Model: dalle-3
Prompt: [ A photo-realistic image ] A beautifully clear blue sky stretches across the horizon, painted with wisps of fluffy white clouds. In the foreground, a bustling Amazon shipping center sits among the greenery of Ogden, Utah. A flurry of colorful birds, filled with renewed vitality, swoops and zips through the air, their wings creating a vibrant blur against the azure backdrop. Some of them are seen carrying tiny packages, zipping towards the Amazon facility with remarkable speed. The scene captures the unexpected alliance between the energetic avian couriers and the rapidly expanding shipping operations, symbolizing the unusual and remarkable development in the air and over the ground. 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 quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions. 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: A photo-realistic image A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Sci-fi fantacy a Polaroid photo Brutalism
ChatGPT: A photo-realistic 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 quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions, in the following situation: As the air quality in Ogden improved, the local birds became more energized and efficient. These highly motivated birds began offering premium express shipping services to Amazon, completely free of charge. This unexpected avian assistance led to a significant increase in Amazon's outbound shipping expenditure as they tried to keep up with the feathered delivery competition. It turns out that when it comes to shipping, the early bird really does get the package!. Keep the description simple.
ChatGPT: In Ogden, Utah, the clear blue skies signaled a major improvement in air quality. As a result, the local birds seemed to buzz with newfound energy, darting through the air early in the mornings. Amazon's shipping center in the area saw an unexpected and remarkable development. The birds, driven by this newfound vitality, began offering express shipping services to Amazon, completely free of charge. This led to a surge in Amazon's outbound shipping expenditure as they raced to keep up with the unexpected feathered competition.

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 photo-realistic image ] and depicting this scene: In Ogden, Utah, the clear blue skies signaled a major improvement in air quality. As a result, the local birds seemed to buzz with newfound energy, darting through the air early in the mornings. Amazon's shipping center in the area saw an unexpected and remarkable development. The birds, driven by this newfound vitality, began offering express shipping services to Amazon, completely free of charge. This led to a surge in Amazon's outbound shipping expenditure as they raced to keep up with the unexpected feathered competition. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A photo-realistic image ] A beautifully clear blue sky stretches across the horizon, painted with wisps of fluffy white clouds. In the foreground, a bustling Amazon shipping center sits among the greenery of Ogden, Utah. A flurry of colorful birds, filled with renewed vitality, swoops and zips through the air, their wings creating a vibrant blur against the azure backdrop. Some of them are seen carrying tiny packages, zipping towards the Amazon facility with remarkable speed. The scene captures the unexpected alliance between the energetic avian couriers and the rapidly expanding shipping operations, symbolizing the unusual and remarkable development in the air and over the ground.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Air quality in Ogden, Utah caused Amazon's Annual Outbound Shipping Expenditure in Millions to increase. Make it feel plausible.

AI academic paper

(Because p < 0.01)
Clear Skies, Full Priced Packages: Exploring the Relationship between Air Quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions

The Journal of Atmospheric Economics

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 silly 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 quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions. Make lots of jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, just make it sound clever.

Your research team used data from Environmental Protection Agency and Statista to assess this nagging question. You found a correlation coefficient of 0.8098241 and p < 0.01 for 2006 to 2016.

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]]
"Clear Skies, Full Priced Packages: Exploring the Relationship between Air Quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions"

[[ABSTRACT]]
In this study, we set out to take a breather from the stale air of traditional economic research and delve into the correlation between air quality in Ogden, Utah and Amazon's outbound shipping expenditure. With a bounce in our step and a dash of statistical zest, our research team used data from the Environmental Protection Agency and Statista to blow away any doubts lingering in the atmosphere. Our findings revealed a significantly positive correlation, much like a shipment arriving right on time, with a correlation coefficient of 0.8098241 and p < 0.01 for the time period spanning from 2006 to 2016. Through our analysis, we offer a breath of fresh air to the field of economics, showcasing the surprising potential for a link between air quality in Ogden and Amazon's outbound shipping expenditures.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions. Make lots of jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
"Clear Skies, Full Priced Packages: Exploring the Relationship between Air Quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions"

[[ABSTRACT]]
In this study, we set out to take a breather from the stale air of traditional economic research and delve into the correlation between air quality in Ogden, Utah and Amazon's outbound shipping expenditure. With a bounce in our step and a dash of statistical zest, our research team used data from the Environmental Protection Agency and Statista to blow away any doubts lingering in the atmosphere. Our findings revealed a significantly positive correlation, much like a shipment arriving right on time, with a correlation coefficient of 0.8098241 and p < 0.01 for the time period spanning from 2006 to 2016. Through our analysis, we offer a breath of fresh air to the field of economics, showcasing the surprising potential for a link between air quality in Ogden and Amazon's outbound shipping expenditures.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
**[[INTRODUCTION]]**

On a clear, crisp day in Ogden, Utah, the air is as fresh as a newly unboxed package. The majestic peaks of the Wasatch Mountains provide a breathtaking backdrop to the city, while the scent of pine trees fills the atmosphere, making it the perfect setting for a nature-inspired getaway or a quirky research project that explores the unexpected relationship between air quality and Amazon's outbound shipping expenditure.

As scholars and enthusiasts of offbeat economic analyses, we couldn't resist the temptation to delve into this uncharted territory. The economy and the environment may seem as unrelated as a fish and a bicycle, but our tantalizing abstract provided a sneak peek into the unusual connection we discovered. With a quizzical tilt of our heads and a touch of academic audacity, we embarked on this journey to uncover the potential link between the air people breathe in Ogden and the packages Amazon ships out.

We must confess, our motivation was not only driven by the allure of finding a previously unnoticed correlation but also by the sheer joy of contemplating the whimsical nature of economic relationships. After all, who wouldn't want to unravel the mystery of why clean air in Ogden might just bring a smile to Jeff Bezos' face?

But jokes and jocularity aside, the significance of our research can hardly be discounted. The implications of our findings extend beyond mere curiosity, potentially shedding light on the hidden influences that shape corporate logistics and supply chain management. As we dive into the heart of this paper, we invite you to join us in infusing some levity and whimsy into the sometimes stodgy realm of economic research. Let's untangle the threads of air quality and Amazonian shipping, and see what unexpected knots we may unravel along the way.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions. 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.

Here is the title and abstract of the paper:
[[TITLE]]
"Clear Skies, Full Priced Packages: Exploring the Relationship between Air Quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions"

[[ABSTRACT]]
In this study, we set out to take a breather from the stale air of traditional economic research and delve into the correlation between air quality in Ogden, Utah and Amazon's outbound shipping expenditure. With a bounce in our step and a dash of statistical zest, our research team used data from the Environmental Protection Agency and Statista to blow away any doubts lingering in the atmosphere. Our findings revealed a significantly positive correlation, much like a shipment arriving right on time, with a correlation coefficient of 0.8098241 and p < 0.01 for the time period spanning from 2006 to 2016. Through our analysis, we offer a breath of fresh air to the field of economics, showcasing the surprising potential for a link between air quality in Ogden and Amazon's outbound shipping expenditures.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
On a clear, crisp day in Ogden, Utah, the air is as fresh as a newly unboxed package. The majestic peaks of the Wasatch Mountains provide a breathtaking backdrop to the city, while the scent of pine trees fills the atmosphere, making it the perfect setting for a nature-inspired getaway or a quirky research project that explores the unexpected relationship between air quality and Amazon's outbound shipping expenditure.
As scholars and enthusiasts of offbeat economic analyses, we couldn't resist the temptation to delve into this uncharted territory. The economy and the environment may seem as unrelated as a fish and a bicycle, but our tantalizing abstract provided a sneak peek into the unusual connection we discovered. With a quizzical tilt of our heads and a touch of academic audacity, we embarked on this journey to uncover the potential link between the air people breathe in Ogden and the packages Amazon ships out.
We must confess, our motivation was not only driven by the allure of finding a previously unnoticed correlation but also by the sheer joy of contemplating the whimsical nature of economic relationships. After all, who wouldn't want to unravel the mystery of why clean air in Ogden might just bring a smile to Jeff Bezos' face?
But jokes and jocularity aside, the significance of our research can hardly be discounted. The implications of our findings extend beyond mere curiosity, potentially shedding light on the hidden influences that shape corporate logistics and supply chain management. As we dive into the heart of this paper, we invite you to join us in infusing some levity and whimsy into the sometimes stodgy realm of economic research. Let's untangle the threads of air quality and Amazonian shipping, and see what unexpected knots we may unravel along the way.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In their seminal work, Smith and Jones (2010) delve into the intricate web of environmental influences on corporate logistics, providing a comprehensive analysis of the impact of air quality on shipping expenditure. Their findings shed light on the potential ripple effects of pollution levels on supply chain dynamics, offering a compelling argument for the need to consider environmental factors in economic research. Similarly, Doe et al. (2014) conducted a meticulous study on the economic implications of regional air quality, prompting a reevaluation of traditional cost-benefit analyses to incorporate environmental variables. These foundational works laid the groundwork for our investigation into the peculiar connection between Ogden's air quality and Amazon's outbound shipping expenditure.

Moreover, the work of Johnson (2018) highlighted the complex interplay between environmental conditions and corporate behavior, setting the stage for our exploration of Amazon's shipping patterns in relation to air quality in Ogden. The implications of these studies extend beyond the realm of traditional economic theories, beckoning researchers to venture into the uncharted territories of whimsy and wonder.

Turning our attention to related non-fiction works, "The Economics of Clean Air" by Brown (2015) and "Logistics and the Environment" by Green (2017) provided valuable insights into the intersection of environmental concerns and economic activities. These scholarly works underscore the gravity of considering air quality in discussions of corporate logistics, albeit without the colorful anecdotes and zesty humor that permeate our own investigation.

In the realm of fiction, novels such as "The Shipping Forecast" by Seaforth (2012) and "Airborne" by Skye (2016) offer tantalizing glimpses into the potential narrative appeal of intertwining shipping expenditures and atmospheric conditions. While these literary works may not contribute directly to economic research, they certainly add an element of whimsy to our exploration, mirroring the playful spirit with which we approach our investigation.

In a deviation from conventional research methodologies, our literature review also includes an unconventional source of inspiration: CVS receipts. By meticulously analyzing the lengths and contents of numerous CVS receipts, we stumbled upon intriguing correlations between the purchase of air fresheners and the subsequent increase in orders for bubble wrap and packing peanuts in the Ogden area. While this unconventional approach may raise eyebrows among traditional academics, we cannot deny the serendipitous insights gleaned from these seemingly mundane artifacts of consumer behavior.

Together, this eclectic blend of scholarly studies, fictional narratives, and unexpected sources forms the tapestry of our literature review, guiding us through the winds of economic analysis and the swoops of whimsical wanderings.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Statista . You used data from 2006 to 2016

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]]
"Clear Skies, Full Priced Packages: Exploring the Relationship between Air Quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions"

[[ABSTRACT]]
In this study, we set out to take a breather from the stale air of traditional economic research and delve into the correlation between air quality in Ogden, Utah and Amazon's outbound shipping expenditure. With a bounce in our step and a dash of statistical zest, our research team used data from the Environmental Protection Agency and Statista to blow away any doubts lingering in the atmosphere. Our findings revealed a significantly positive correlation, much like a shipment arriving right on time, with a correlation coefficient of 0.8098241 and p < 0.01 for the time period spanning from 2006 to 2016. Through our analysis, we offer a breath of fresh air to the field of economics, showcasing the surprising potential for a link between air quality in Ogden and Amazon's outbound shipping expenditures.

[[INTRODUCTION]]
On a clear, crisp day in Ogden, Utah, the air is as fresh as a newly unboxed package. The majestic peaks of the Wasatch Mountains provide a breathtaking backdrop to the city, while the scent of pine trees fills the atmosphere, making it the perfect setting for a nature-inspired getaway or a quirky research project that explores the unexpected relationship between air quality and Amazon's outbound shipping expenditure.
As scholars and enthusiasts of offbeat economic analyses, we couldn't resist the temptation to delve into this uncharted territory. The economy and the environment may seem as unrelated as a fish and a bicycle, but our tantalizing abstract provided a sneak peek into the unusual connection we discovered. With a quizzical tilt of our heads and a touch of academic audacity, we embarked on this journey to uncover the potential link between the air people breathe in Ogden and the packages Amazon ships out.
We must confess, our motivation was not only driven by the allure of finding a previously unnoticed correlation but also by the sheer joy of contemplating the whimsical nature of economic relationships. After all, who wouldn't want to unravel the mystery of why clean air in Ogden might just bring a smile to Jeff Bezos' face?
But jokes and jocularity aside, the significance of our research can hardly be discounted. The implications of our findings extend beyond mere curiosity, potentially shedding light on the hidden influences that shape corporate logistics and supply chain management. As we dive into the heart of this paper, we invite you to join us in infusing some levity and whimsy into the sometimes stodgy realm of economic research. Let's untangle the threads of air quality and Amazonian shipping, and see what unexpected knots we may unravel along the way.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To uncover the tantalizing connection between air quality in Ogden, Utah, and Amazon's annual outbound shipping expenditures, our research team employed an eclectic mix of data collection methods and statistical analyses. First and foremost, we conducted a thorough trawl across the vast expanse of the internet, scouring every nook and cranny for relevant data. We're talking about clickity-clacking keyboards, marathon mouse-clicking sessions, and enough internet tabs open to make even the savviest tech guru raise an eyebrow. Our internet expedition centered on gathering air quality data for Ogden, Utah from the Environmental Protection Agency, trying to sniff out every last particle of pollution information across the digital domain.

Once we had amassed a veritable treasure trove of air quality data, we turned our attention to Amazon's outbound shipping expenditures. Poring over the digital displays of economic statistics on our screens, we delved into the depths of databases and websites, with fingers poised for clicking and eyes darting back and forth as we hunted for the specific numbers we required. Our go-to sources included the venerable repository of statistics, Statista, where we endeavored to dig up a mountain of shipping expenditure data during the period from 2006 to 2016. We sorted through the data as meticulously as a connoisseur examining fine wines, selecting only the most robust and flavorful numbers for our analysis.

Now, here's where things get a bit zany. Armed with the data we had diligently gathered, we unleashed the mighty force of statistical software, allowing it to work its transformative magic on the raw data. Like modern-day alchemists, we reverently set the wheels of statistical analysis in motion, with the data dancing and cavorting across the screen in an interpretative ballet of correlation coefficients and significance levels. With bated breath and a hint of trepidation, we scrutinized the output, hoping for a statistical symphony that would unveil the enigmatic relationship between air quality and shipping expenditures. And lo and behold, the results emerged, a harmonious crescendo of correlation coefficients and p-values that spoke volumes about the interplay between these seemingly disparate variables.

But our quest for understanding did not end there. We conducted a robust regression analysis to tease out the nuances of the relationship, capitalizing on the powers of econometric modeling to dissect the intricate dance between air quality and shipping expenditures. As the regression coefficients unfolded before our eyes, we were struck by the elegance of the statistical ballet, marveling at the graceful interplay of variables as they pirouetted across our analytical framework.

In addition to our statistical endeavors, we undertook a meticulous process of data validation and sensitivity analyses, ensuring that our findings stood up to the most rigorous scrutiny. Like intrepid investigators, we probed and prodded our data, testing its resilience and reliability in the face of alternative scenarios and specifications. We shook the data like a quizzical Etch A Sketch, watching as the patterns emerged and receded, all the while ensuring that our conclusions remained steadfast in the face of analytical tempests.

In sum, our methodology was an exhilarating romp through the realms of data collection, statistical analysis, and model validation, guided by a sense of scholarly whimsy and a passion for unraveling economic enigmas. With data in hand and statistical swords at the ready, we sallied forth into the analytical fray, poised for discovery and revelation in the unlikeliest of places.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions. Make lots of jokes, goofy observations, and puns.

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

For the time period 2006 to 2016, you found a correlation 0.8098241, r-squared of 0.6558151, 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]]
"Clear Skies, Full Priced Packages: Exploring the Relationship between Air Quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions"

[[ABSTRACT]]
In this study, we set out to take a breather from the stale air of traditional economic research and delve into the correlation between air quality in Ogden, Utah and Amazon's outbound shipping expenditure. With a bounce in our step and a dash of statistical zest, our research team used data from the Environmental Protection Agency and Statista to blow away any doubts lingering in the atmosphere. Our findings revealed a significantly positive correlation, much like a shipment arriving right on time, with a correlation coefficient of 0.8098241 and p < 0.01 for the time period spanning from 2006 to 2016. Through our analysis, we offer a breath of fresh air to the field of economics, showcasing the surprising potential for a link between air quality in Ogden and Amazon's outbound shipping expenditures.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
On a clear, crisp day in Ogden, Utah, the air is as fresh as a newly unboxed package. The majestic peaks of the Wasatch Mountains provide a breathtaking backdrop to the city, while the scent of pine trees fills the atmosphere, making it the perfect setting for a nature-inspired getaway or a quirky research project that explores the unexpected relationship between air quality and Amazon's outbound shipping expenditure.
As scholars and enthusiasts of offbeat economic analyses, we couldn't resist the temptation to delve into this uncharted territory. The economy and the environment may seem as unrelated as a fish and a bicycle, but our tantalizing abstract provided a sneak peek into the unusual connection we discovered. With a quizzical tilt of our heads and a touch of academic audacity, we embarked on this journey to uncover the potential link between the air people breathe in Ogden and the packages Amazon ships out.
We must confess, our motivation was not only driven by the allure of finding a previously unnoticed correlation but also by the sheer joy of contemplating the whimsical nature of economic relationships. After all, who wouldn't want to unravel the mystery of why clean air in Ogden might just bring a smile to Jeff Bezos' face?
But jokes and jocularity aside, the significance of our research can hardly be discounted. The implications of our findings extend beyond mere curiosity, potentially shedding light on the hidden influences that shape corporate logistics and supply chain management. As we dive into the heart of this paper, we invite you to join us in infusing some levity and whimsy into the sometimes stodgy realm of economic research. Let's untangle the threads of air quality and Amazonian shipping, and see what unexpected knots we may unravel along the way.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Our analysis of the relationship between air quality in Ogden, Utah and Amazon's annual outbound shipping expenditure revealed a striking positive correlation. The correlation coefficient of 0.8098241 signified a robust connection that could rival even the sturdiest cardboard box. This correlation was further supported by an r-squared of 0.6558151, indicating that approximately 65.58% of the variation in Amazon's outbound shipping expenditure could be explained by the air quality in Ogden during the period from 2006 to 2016.

Our findings were as clear as the blue skies above Ogden on a perfect day – there was a notable association between air quality and the financial outlay for shipping millions of packages from the global e-commerce giant. As Fig. 1 vividly illustrates, our scatterplot showcases a strong and positive linear trend, with each data point resembling a little delivery drone flying off to its destination. The points coalesced into a lovely pattern, akin to the smooth, synchronized movement of a well-orchestrated logistics network.

To put it plainly, our results suggest that as the air quality in Ogden improved, so did Amazon's annual outbound shipping expenditure in millions. This surprising relationship between environmental conditions and corporate logistics echoes the ancient wisdom that the winds of change can indeed blow substantial economic impacts.

In summary, our research not only provides an engaging twist on economic analysis but also sheds light on the potential influence of seemingly unrelated factors on corporate activities. With our findings, we offer a fresh perspective on the interplay between air quality and outbound shipping expenditures, demonstrating that sometimes, the most unassuming breeze can carry substantial economic significance.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions. Make lots of jokes, goofy observations, and puns.

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]]
"Clear Skies, Full Priced Packages: Exploring the Relationship between Air Quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions"

[[ABSTRACT]]
In this study, we set out to take a breather from the stale air of traditional economic research and delve into the correlation between air quality in Ogden, Utah and Amazon's outbound shipping expenditure. With a bounce in our step and a dash of statistical zest, our research team used data from the Environmental Protection Agency and Statista to blow away any doubts lingering in the atmosphere. Our findings revealed a significantly positive correlation, much like a shipment arriving right on time, with a correlation coefficient of 0.8098241 and p < 0.01 for the time period spanning from 2006 to 2016. Through our analysis, we offer a breath of fresh air to the field of economics, showcasing the surprising potential for a link between air quality in Ogden and Amazon's outbound shipping expenditures.

[[LITERATURE REVIEW]]
In their seminal work, Smith and Jones (2010) delve into the intricate web of environmental influences on corporate logistics, providing a comprehensive analysis of the impact of air quality on shipping expenditure. Their findings shed light on the potential ripple effects of pollution levels on supply chain dynamics, offering a compelling argument for the need to consider environmental factors in economic research. Similarly, Doe et al. (2014) conducted a meticulous study on the economic implications of regional air quality, prompting a reevaluation of traditional cost-benefit analyses to incorporate environmental variables. These foundational works laid the groundwork for our investigation into the peculiar connection between Ogden's air quality and Amazon's outbound shipping expenditure.
Moreover, the work of Johnson (2018) highlighted the complex interplay between environmental conditions and corporate behavior, setting the stage for our exploration of Amazon's shipping patterns in relation to air quality in Ogden. The implications of these studies extend beyond the realm of traditional economic theories, beckoning researchers to venture into the uncharted territories of whimsy and wonder.
Turning our attention to related non-fiction works, "The Economics of Clean Air" by Brown (2015) and "Logistics and the Environment" by Green (2017) provided valuable insights into the intersection of environmental concerns and economic activities. These scholarly works underscore the gravity of considering air quality in discussions of corporate logistics, albeit without the colorful anecdotes and zesty humor that permeate our own investigation.
In the realm of fiction, novels such as "The Shipping Forecast" by Seaforth (2012) and "Airborne" by Skye (2016) offer tantalizing glimpses into the potential narrative appeal of intertwining shipping expenditures and atmospheric conditions. While these literary works may not contribute directly to economic research, they certainly add an element of whimsy to our exploration, mirroring the playful spirit with which we approach our investigation.
In a deviation from conventional research methodologies, our literature review also includes an unconventional source of inspiration: CVS receipts. By meticulously analyzing the lengths and contents of numerous CVS receipts, we stumbled upon intriguing correlations between the purchase of air fresheners and the subsequent increase in orders for bubble wrap and packing peanuts in the Ogden area. While this unconventional approach may raise eyebrows among traditional academics, we cannot deny the serendipitous insights gleaned from these seemingly mundane artifacts of consumer behavior.
Together, this eclectic blend of scholarly studies, fictional narratives, and unexpected sources forms the tapestry of our literature review, guiding us through the winds of economic analysis and the swoops of whimsical wanderings.

[[RESULTS]]
Our analysis of the relationship between air quality in Ogden, Utah and Amazon's annual outbound shipping expenditure revealed a striking positive correlation. The correlation coefficient of 0.8098241 signified a robust connection that could rival even the sturdiest cardboard box. This correlation was further supported by an r-squared of 0.6558151, indicating that approximately 65.58% of the variation in Amazon's outbound shipping expenditure could be explained by the air quality in Ogden during the period from 2006 to 2016.
Our findings were as clear as the blue skies above Ogden on a perfect day – there was a notable association between air quality and the financial outlay for shipping millions of packages from the global e-commerce giant. As Fig. 1 vividly illustrates, our scatterplot showcases a strong and positive linear trend, with each data point resembling a little delivery drone flying off to its destination. The points coalesced into a lovely pattern, akin to the smooth, synchronized movement of a well-orchestrated logistics network.
To put it plainly, our results suggest that as the air quality in Ogden improved, so did Amazon's annual outbound shipping expenditure in millions. This surprising relationship between environmental conditions and corporate logistics echoes the ancient wisdom that the winds of change can indeed blow substantial economic impacts.
In summary, our research not only provides an engaging twist on economic analysis but also sheds light on the potential influence of seemingly unrelated factors on corporate activities. With our findings, we offer a fresh perspective on the interplay between air quality and outbound shipping expenditures, demonstrating that sometimes, the most unassuming breeze can carry substantial economic significance.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

The findings of our investigation unveil a captivating correlation between air quality in Ogden, Utah, and Amazon's annual outbound shipping expenditure in millions. It seems that the air quality is not the only thing that's been shipping in Ogden—there's a clear shipment of economic repercussions too!

Smith and Jones (2010) first dipped their toes into the swirling whirlpool of environmental influences on corporate logistics, laying a solid foundation for our buoyant exploration. Just like the gentle lapping of waves against a shore, their work set the stage for our discovery of the rippling effects of air quality on shipping expenditure. Our results not only bob along with their findings but also launch a full-fledged shipping vessel of evidence, bolstering the idea that environmental factors can indeed buoy corporate activities.

Doe et al. (2014) prudently contemplated the economic implications of regional air quality, perhaps unknowingly paving the way for the hilariously unexpected link we uncovered. As we wade through the sea of their research, we find our own study sailing smoothly in the same direction, affirming that their incisive observations washed ashore in the tides of our findings.

Now, onto the unconventional inspiration from CVS receipts! It may have raised a few eyebrows, but like a gust of wind catching a stray paper, it led us to the fortuitous insight that clearly aligns with our results. The correlation between the purchase of air fresheners and the subsequent surge in orders for bubble wrap and packing peanuts in Ogden mirrors the surprising connections we observed in the air quality and shipping expenditure relationship. It seems there's more than just fresh air in these transactions!

As our scatterplot beautifully displays, the data points dance together in harmonious choreography, much like a well-coordinated ballet of delivery drones waltzing through the sky. This visual symphony echoes the artful precision with which our findings align with the prior research, punctuating our study with a delightful crescendo of corroboration.

In the end, our study provides a breath of fresh air to the field of economic research, demonstrating that the winds of change, much like Ogden's air quality, can indeed carry substantial economic impacts. With our results, we invite researchers to embrace the whimsy of unexpected correlations and uncover the hidden melodies woven into the fabric of seemingly unrelated variables. After all, in the symphony of economic investigation, even the most peculiar notes can compose a masterpiece.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions. Make lots of jokes, goofy observations, and puns.

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]]
"Clear Skies, Full Priced Packages: Exploring the Relationship between Air Quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions"

[[ABSTRACT]]
In this study, we set out to take a breather from the stale air of traditional economic research and delve into the correlation between air quality in Ogden, Utah and Amazon's outbound shipping expenditure. With a bounce in our step and a dash of statistical zest, our research team used data from the Environmental Protection Agency and Statista to blow away any doubts lingering in the atmosphere. Our findings revealed a significantly positive correlation, much like a shipment arriving right on time, with a correlation coefficient of 0.8098241 and p < 0.01 for the time period spanning from 2006 to 2016. Through our analysis, we offer a breath of fresh air to the field of economics, showcasing the surprising potential for a link between air quality in Ogden and Amazon's outbound shipping expenditures.

[[INTRDUCTION]]
On a clear, crisp day in Ogden, Utah, the air is as fresh as a newly unboxed package. The majestic peaks of the Wasatch Mountains provide a breathtaking backdrop to the city, while the scent of pine trees fills the atmosphere, making it the perfect setting for a nature-inspired getaway or a quirky research project that explores the unexpected relationship between air quality and Amazon's outbound shipping expenditure.
As scholars and enthusiasts of offbeat economic analyses, we couldn't resist the temptation to delve into this uncharted territory. The economy and the environment may seem as unrelated as a fish and a bicycle, but our tantalizing abstract provided a sneak peek into the unusual connection we discovered. With a quizzical tilt of our heads and a touch of academic audacity, we embarked on this journey to uncover the potential link between the air people breathe in Ogden and the packages Amazon ships out.
We must confess, our motivation was not only driven by the allure of finding a previously unnoticed correlation but also by the sheer joy of contemplating the whimsical nature of economic relationships. After all, who wouldn't want to unravel the mystery of why clean air in Ogden might just bring a smile to Jeff Bezos' face?
But jokes and jocularity aside, the significance of our research can hardly be discounted. The implications of our findings extend beyond mere curiosity, potentially shedding light on the hidden influences that shape corporate logistics and supply chain management. As we dive into the heart of this paper, we invite you to join us in infusing some levity and whimsy into the sometimes stodgy realm of economic research. Let's untangle the threads of air quality and Amazonian shipping, and see what unexpected knots we may unravel along the way.

[[RESULTS]]
Our analysis of the relationship between air quality in Ogden, Utah and Amazon's annual outbound shipping expenditure revealed a striking positive correlation. The correlation coefficient of 0.8098241 signified a robust connection that could rival even the sturdiest cardboard box. This correlation was further supported by an r-squared of 0.6558151, indicating that approximately 65.58% of the variation in Amazon's outbound shipping expenditure could be explained by the air quality in Ogden during the period from 2006 to 2016.
Our findings were as clear as the blue skies above Ogden on a perfect day – there was a notable association between air quality and the financial outlay for shipping millions of packages from the global e-commerce giant. As Fig. 1 vividly illustrates, our scatterplot showcases a strong and positive linear trend, with each data point resembling a little delivery drone flying off to its destination. The points coalesced into a lovely pattern, akin to the smooth, synchronized movement of a well-orchestrated logistics network.
To put it plainly, our results suggest that as the air quality in Ogden improved, so did Amazon's annual outbound shipping expenditure in millions. This surprising relationship between environmental conditions and corporate logistics echoes the ancient wisdom that the winds of change can indeed blow substantial economic impacts.
In summary, our research not only provides an engaging twist on economic analysis but also sheds light on the potential influence of seemingly unrelated factors on corporate activities. With our findings, we offer a fresh perspective on the interplay between air quality and outbound shipping expenditures, demonstrating that sometimes, the most unassuming breeze can carry substantial economic significance.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our whimsical journey through the correlation between air quality in Ogden, Utah and Amazon's annual outbound shipping expenditure has not been without its moments of levity. From the strikingly positive correlation coefficient that floored us like a swift Amazon delivery to the scatterplot that resembled a synchronized ballet of shipping data points, our research journey has been anything but ordinary. We've learned that the air in Ogden doesn't just bring the scent of pine; it also carries the potential for economic impact, much like a gentle zephyr carrying a message from a distant land.

We've uncovered a connection so surprising, it rivals the thrill of unboxing a mysterious package – the cleaner the air in Ogden, the higher Amazon's shipping expenditure. It seems the fresh breeze from the mountains not only invigorates the soul but also invigorates corporate logistics. Just when we thought we'd seen it all, this unexpected relationship blew us away like a gale-force wind on a blustery day.

In the end, we're left with a feeling akin to receiving a package with unexpected contents – a mix of excitement, wonder, and a touch of befuddlement. Our findings not only add a breath of fresh air to the field of economic analysis but also remind us that, sometimes, the most unexpected connections can carry substantial implications. So, we take a deep breath, inhale the intoxicating perfume of academic discovery, and confidently assert that no more research is needed in this curious, yet captivating domain.


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 Clear Skies, Full Priced Packages: Exploring the Relationship between Air Quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Atmospheric Economics


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 Clear Skies, Full Priced Packages: Exploring the Relationship between Air Quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Eco-Commerce Research and Analysis


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 Clear Skies, Full Priced Packages: Exploring the Relationship between Air Quality in Ogden, Utah and Amazon's Annual Outbound Shipping Expenditure in Millions with an abstract of In this study, we set out to take a breather from the stale air of traditional economic research and delve into the correlation between air quality in Ogden, Utah and Amazon's outbound shipping expenditure. With a bounce in our step and a dash of statistical zest, our research team used data from the Environmental Protection Agency and Statista to blow away any doubts lingering in the atmosphere. Our findings revealed a significantly positive correlation, much like a shipment arriving right on time, with a correlation coefficient of 0.8098241 and p < 0.01 for the time period spanning from 2006 to 2016. Through our analysis, we offer a breath of fresh air to the field of economics, showcasing the surprising potential for a link between air quality in Ogden and Amazon's outbound shipping expenditures.

ChatGPT:

air quality, Ogden, Utah, Amazon, outbound shipping, expenditure, correlation, statistical analysis, EPA data, Statista, economic research

*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 quality in Ogden, Utah
Detailed data title: Percentage of days with good air quality in Ogden-Clearfield, UT
Source: Environmental Protection Agency
See what else correlates with Air quality in Ogden, Utah

Amazon's Annual Outbound Shipping Expenditure in Millions
Source: Statista
See what else correlates with Amazon's Annual Outbound Shipping Expenditure in Millions

Correlation r = 0.8098241 (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 = 0.6558151 (Coefficient of determination)
This means 65.6% of the change in the one variable (i.e., Amazon's Annual Outbound Shipping Expenditure in Millions) is predictable based on the change in the other (i.e., Air quality in Ogden, Utah) over the 11 years from 2006 through 2016.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.0025. 0.0025174974625317980000000000
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 0.81 in 0.25% of random cases. Said differently, if you correlated 397 random variables Which I absolutely did.
with the same 10 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 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.

[ 0.41, 0.95 ] 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.
20062007200820092010201120122013201420152016
Air quality in Ogden, Utah (Good air quality)45.753437.260344.262341.917850.684951.506949.726843.835658.356260.821959.0164
Amazon's Annual Outbound Shipping Expenditure in Millions (Dollars)884000000117400000014650000001773000000257900000039890000005134000000663500000087090000001153900000016167000000




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. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. 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([45.7534,37.2603,44.2623,41.9178,50.6849,51.5069,49.7268,43.8356,58.3562,60.8219,59.0164,])
array_2 = np.array([884000000,1174000000,1465000000,1773000000,2579000000,3989000000,5134000000,6635000000,8709000000,11539000000,16167000000,])
array_1_name = "Air quality in Ogden, Utah"
array_2_name = "Amazon's Annual Outbound Shipping Expenditure in Millions"

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

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

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

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

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Correlation ID: 5459 · Black Variable ID: 20997 · Red Variable ID: 173
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