Spurious correlation #4,690 · 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 Arkadelphia, Arkansas and the second variable is Customer satisfaction with Apple. The chart goes from 1994 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air quality in Arkadelphia, Arkansas and the second variable is Customer satisfaction with Apple. The chart goes from 1994 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the air quality in Arkadelphia improved, the local apple orchards flourished, leading to an abundance of top-quality apples. This influx of superior apples led to an increase in customer satisfaction with Apple products, as people subconsciously felt a stronger connection to the brand while enjoying the crisp, clean air and envisioning a world where every breath was as fresh as biting into a juicy apple.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of an apple orchard in Arkadelphia, Arkansas, with a clear blue sky overhead. The focus should be on the apple trees gently swaying in the breeze, with customers leisurely strolling through the local apple market in the background. The scene should emanate a serene and contented atmosphere, with the air filled with the sweet scent of blossoming orchards. The image should also capture the harmony between the flourishing apple orchards and the revitalized air quality, enhancing customer satisfaction with Apple products. 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 Arkadelphia, Arkansas and Customer satisfaction with Apple. 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: Symbolism Cutsy graphics Cutsy art illustration Sci-fi fantacy Macabre
ChatGPT: Symbolism

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 Arkadelphia, Arkansas and Customer satisfaction with Apple, in the following situation: As the air quality in Arkadelphia improved, the local apple orchards flourished, leading to an abundance of top-quality apples. This influx of superior apples led to an increase in customer satisfaction with Apple products, as people subconsciously felt a stronger connection to the brand while enjoying the crisp, clean air and envisioning a world where every breath was as fresh as biting into a juicy apple.. Keep the description simple.
ChatGPT: A clear blue sky stretches over Arkadelphia, Arkansas, as apple trees sway gently in the breeze. The air is filled with the sweet scent of blossoming orchards. Customers leisurely stroll through the local apple market, their faces beaming with delight as they bite into the crisp, juicy apples and savor the fresh, clean air. The harmony between the flourishing apple orchards and the revitalized air quality creates a serene and contented atmosphere that enhances customer satisfaction with Apple products.

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: [ Symbolism ] and depicting this scene: A clear blue sky stretches over Arkadelphia, Arkansas, as apple trees sway gently in the breeze. The air is filled with the sweet scent of blossoming orchards. Customers leisurely stroll through the local apple market, their faces beaming with delight as they bite into the crisp, juicy apples and savor the fresh, clean air. The harmony between the flourishing apple orchards and the revitalized air quality creates a serene and contented atmosphere that enhances customer satisfaction with Apple products. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of an apple orchard in Arkadelphia, Arkansas, with a clear blue sky overhead. The focus should be on the apple trees gently swaying in the breeze, with customers leisurely strolling through the local apple market in the background. The scene should emanate a serene and contented atmosphere, with the air filled with the sweet scent of blossoming orchards. The image should also capture the harmony between the flourishing apple orchards and the revitalized air quality, enhancing customer satisfaction with Apple products.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Air quality in Arkadelphia, Arkansas caused Customer satisfaction with Apple to increase.

AI academic paper

(Because p < 0.01)

Astonishing Air Quality and Apple Affinity: Analyzing the Association Between Air Quality in Arkadelphia, Arkansas and Customer Satisfaction with Apple

The Journal of Environmental Aesthetics and Fruit-Based Technology

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 quality in Arkadelphia, Arkansas and Customer satisfaction with Apple. 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]]
Astonishing Air Quality and Apple Affinity: Analyzing the Association Between Air Quality in Arkadelphia, Arkansas and Customer Satisfaction with Apple

[[ABSTRACT]]
This paper investigates the relationship between the air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. Utilizing data from the Environmental Protection Agency and the American Customer Satisfaction Index spanning from 1994 to 2021, we applied statistical analyses to uncover the potential connection between these seemingly disparate entities. The correlation coefficient of 0.8070970 with a p-value of less than 0.01 indicated a noteworthy association between the two variables. Our findings suggest an intriguing interplay between local air quality and the sentiment towards Apple, thereby shedding light on the unexpected influences on consumer satisfaction. While the link between air quality and customer preferences may appear transparent, our research fosters a deeper understanding of the nuanced factors that shape consumer perceptions.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between environmental factors and consumer behavior has long been a subject of interest in both academic and practical spheres. From the influence of ambient music on shopping habits to the psychological effects of color on purchasing decisions, the quest to uncover the intricacies of consumer preferences knows no bounds. In this vein, our study delves into the unexplored territory of the connection between air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. While the correlation may seem as unlikely as finding a needle in a haystack made of iCloud, the data-driven approach we employ seeks to shed light on this compelling conundrum.
Arkadelphia, Arkansas, a town renowned for its picturesque landscapes and unassuming charm, serves as our setting for this inquiry. Nestled among the rolling hills and whispering pines, the community's air quality has not been a topic of widespread discussion in academic circles. Nevertheless, the silent yet omnipresent influence of air quality on consumer sentiments toward Apple products beckoned our attention. As consumers flock to the sleek and tantalizing offerings of Apple, the breeze in Arkadelphia unfurls its own narrative, weaving a tale of invisible yet palpable impact.
The empirical backbone of our investigation is derived from the comprehensive datasets provided by the Environmental Protection Agency and the American Customer Satisfaction Index. Spanning nearly three decades, these troves of information offer a rare glimpse into the ebb and flow of the air quality in Arkadelphia and the undulating tides of Apple aficionado approval. Through the lens of statistical analyses, we navigate the tempestuous seas of data, seeking to discern patterns and relationships that elude casual observation.
As we navigate this juncture where atmospheric musings and technological fervor converge, we invite the reader to embark on this intellectual escapade with an open mind. The results of our inquiry promise to paint a landscape where the gusts of air quality and the allure of Apple intermingle in unexpected harmony, fostering a newfound appreciation for the whimsical interplay of consumer sentiments.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The present literature review delves into prior research investigating the relationship between environmental factors and consumer behavior, with a particular focus on air quality and customer preferences. The authors find Smith et al. and Doe et al., who have probed the impact of air quality on consumer sentiment, shedding light on the intricate interplay between environmental variables and consumer behavior. Additionally, Jones et al. have contributed to the understanding of customer satisfaction with technology products, offering valuable insights into the complex dynamics that underpin consumer preferences.

Encompassing the broader context of consumer behavior and environmental influences, seminal works such as "The Economics of Air Quality" and "Consumer Psychology: Understanding Customer Preferences" provide a foundational understanding of the multifaceted factors at play in shaping consumer attitudes. Moving beyond the traditional confines of scholarly literature, fictitious accounts such as "The Air Quality Mysteries" and "The Apple Chronicles: A Tale of Consumer Intrigue" offer imaginative narratives that, while not empirical, capture the essence of the curious connection between air quality and consumer satisfaction.

Moreover, the researchers came across various social media posts that pertain to the relationship between air quality and consumer sentiments toward Apple. One notable post on a popular microblogging platform reads, "The crispness of the air in Arkadelphia seems to translate to the satisfaction with my Apple devices. Coincidence? I think not." Such anecdotal observations, while not scientifically rigorous, underscore the pervasiveness of this phenomenon in colloquial discourse and the public consciousness.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 quality in Arkadelphia, Arkansas and Customer satisfaction with Apple. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 American Customer Satisfaction Index . You used data from 1994 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]]
Astonishing Air Quality and Apple Affinity: Analyzing the Association Between Air Quality in Arkadelphia, Arkansas and Customer Satisfaction with Apple

[[ABSTRACT]]
This paper investigates the relationship between the air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. Utilizing data from the Environmental Protection Agency and the American Customer Satisfaction Index spanning from 1994 to 2021, we applied statistical analyses to uncover the potential connection between these seemingly disparate entities. The correlation coefficient of 0.8070970 with a p-value of less than 0.01 indicated a noteworthy association between the two variables. Our findings suggest an intriguing interplay between local air quality and the sentiment towards Apple, thereby shedding light on the unexpected influences on consumer satisfaction. While the link between air quality and customer preferences may appear transparent, our research fosters a deeper understanding of the nuanced factors that shape consumer perceptions.

[[INTRODUCTION]]
The relationship between environmental factors and consumer behavior has long been a subject of interest in both academic and practical spheres. From the influence of ambient music on shopping habits to the psychological effects of color on purchasing decisions, the quest to uncover the intricacies of consumer preferences knows no bounds. In this vein, our study delves into the unexplored territory of the connection between air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. While the correlation may seem as unlikely as finding a needle in a haystack made of iCloud, the data-driven approach we employ seeks to shed light on this compelling conundrum.
Arkadelphia, Arkansas, a town renowned for its picturesque landscapes and unassuming charm, serves as our setting for this inquiry. Nestled among the rolling hills and whispering pines, the community's air quality has not been a topic of widespread discussion in academic circles. Nevertheless, the silent yet omnipresent influence of air quality on consumer sentiments toward Apple products beckoned our attention. As consumers flock to the sleek and tantalizing offerings of Apple, the breeze in Arkadelphia unfurls its own narrative, weaving a tale of invisible yet palpable impact.
The empirical backbone of our investigation is derived from the comprehensive datasets provided by the Environmental Protection Agency and the American Customer Satisfaction Index. Spanning nearly three decades, these troves of information offer a rare glimpse into the ebb and flow of the air quality in Arkadelphia and the undulating tides of Apple aficionado approval. Through the lens of statistical analyses, we navigate the tempestuous seas of data, seeking to discern patterns and relationships that elude casual observation.
As we navigate this juncture where atmospheric musings and technological fervor converge, we invite the reader to embark on this intellectual escapade with an open mind. The results of our inquiry promise to paint a landscape where the gusts of air quality and the allure of Apple intermingle in unexpected harmony, fostering a newfound appreciation for the whimsical interplay of consumer sentiments.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The data collection process for this study involved a meticulous curation of information from diverse sources, predominantly drawing from the Environmental Protection Agency (EPA) and the American Customer Satisfaction Index (ACSI). The data spanned the extensive timeframe from 1994 to 2021, encompassing a rich tapestry of environmental and consumer sentiment data. Assembling the dataset resembled an intricate patchwork quilt, with each data point acting as a thread in the larger fabric of our analysis.

To examine the air quality in Arkadelphia, Arkansas, the EPA's air quality monitoring stations provided a plethora of atmospheric measurements, capturing the ebb and flow of pollutants and particulate matter. These datasets were akin to the whispers of the wind, carrying the subtle nuances of air quality fluctuations over the years. Meanwhile, the ACSI offered a window into the realm of consumer satisfaction with Apple products, employing surveys as the vessels for capturing the fluctuating tides of consumer sentiment.

In a bid to conjoin these seemingly incongruous datasets, rigorous statistical analyses were undertaken. The correlation analyses functioned as the compass guiding us through the maelstrom of data points, allowing for the identification of potential associations between air quality and customer satisfaction with Apple. The calculation of the correlation coefficient and determination of statistical significance served as the heralds illuminating the potential interplay between these variables.

Furthermore, to ensure the robustness of our findings, various sensitivity analyses were conducted, akin to tuning the strings of a lute to discern the resonant frequency of our results. The inclusion of additional demographic and economic variables as covariates lent depth and nuance to our exploration, enriching the canvas upon which the portraits of air quality and consumer sentiment were painted.

In summary, the methodology underpinning this study sought to engage with the datasets in a manner akin to a choreographed dance, where each step and movement contributed to the elucidation of the complex relationship between air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. The interplay between the atmospheric ballet of Arkadelphia's air and the symphony of consumer preferences unfolded through the deft manipulation of data and statistical analyses, culminating in the unveiling of a compelling association between these seemingly disparate phenomena.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 quality in Arkadelphia, Arkansas and Customer satisfaction with Apple. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 American Customer Satisfaction Index .

For the time period 1994 to 2021, you found a correlation 0.8070970, r-squared of 0.6514055, 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]]
Astonishing Air Quality and Apple Affinity: Analyzing the Association Between Air Quality in Arkadelphia, Arkansas and Customer Satisfaction with Apple

[[ABSTRACT]]
This paper investigates the relationship between the air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. Utilizing data from the Environmental Protection Agency and the American Customer Satisfaction Index spanning from 1994 to 2021, we applied statistical analyses to uncover the potential connection between these seemingly disparate entities. The correlation coefficient of 0.8070970 with a p-value of less than 0.01 indicated a noteworthy association between the two variables. Our findings suggest an intriguing interplay between local air quality and the sentiment towards Apple, thereby shedding light on the unexpected influences on consumer satisfaction. While the link between air quality and customer preferences may appear transparent, our research fosters a deeper understanding of the nuanced factors that shape consumer perceptions.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The relationship between environmental factors and consumer behavior has long been a subject of interest in both academic and practical spheres. From the influence of ambient music on shopping habits to the psychological effects of color on purchasing decisions, the quest to uncover the intricacies of consumer preferences knows no bounds. In this vein, our study delves into the unexplored territory of the connection between air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. While the correlation may seem as unlikely as finding a needle in a haystack made of iCloud, the data-driven approach we employ seeks to shed light on this compelling conundrum.
Arkadelphia, Arkansas, a town renowned for its picturesque landscapes and unassuming charm, serves as our setting for this inquiry. Nestled among the rolling hills and whispering pines, the community's air quality has not been a topic of widespread discussion in academic circles. Nevertheless, the silent yet omnipresent influence of air quality on consumer sentiments toward Apple products beckoned our attention. As consumers flock to the sleek and tantalizing offerings of Apple, the breeze in Arkadelphia unfurls its own narrative, weaving a tale of invisible yet palpable impact.
The empirical backbone of our investigation is derived from the comprehensive datasets provided by the Environmental Protection Agency and the American Customer Satisfaction Index. Spanning nearly three decades, these troves of information offer a rare glimpse into the ebb and flow of the air quality in Arkadelphia and the undulating tides of Apple aficionado approval. Through the lens of statistical analyses, we navigate the tempestuous seas of data, seeking to discern patterns and relationships that elude casual observation.
As we navigate this juncture where atmospheric musings and technological fervor converge, we invite the reader to embark on this intellectual escapade with an open mind. The results of our inquiry promise to paint a landscape where the gusts of air quality and the allure of Apple intermingle in unexpected harmony, fostering a newfound appreciation for the whimsical interplay of consumer sentiments.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analyses applied to the data revealed a correlation coefficient of 0.8070970, indicating a strong and positive relationship between air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. The r-squared value of 0.6514055 further elucidated that approximately 65.14% of the variance in Apple customer satisfaction could be explained by the variance in air quality. Moreover, with a p-value of less than 0.01, the association between these two seemingly unrelated variables proved to be statistically significant.

The figure (Fig. 1) depicts a scatterplot illustrating the robust correlation between air quality and Apple customer satisfaction. The data points form a strikingly upward-sloping pattern, resembling the ascent of an Apple product launch's hype.

These findings, while initially surprising, underscore the intricate interplay between the atmospheric conditions of Arkadelphia and the sentiments of Apple enthusiasts. The influence of air quality, akin to the subtle aroma of a freshly unboxed iPhone, permeates the backdrop of consumer preferences, contributing to the overarching tapestry of satisfaction and delight.

In summary, our investigation has brought to light the unanticipated concordance between local air quality and the allure of Apple, emphasizing the interconnectedness of environmental factors and consumer sentiments. This revelation, akin to stumbling upon a hidden gem in a digital orchard, invites further contemplation on the diverse influences that shape consumer satisfaction.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 quality in Arkadelphia, Arkansas and Customer satisfaction with Apple. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
Astonishing Air Quality and Apple Affinity: Analyzing the Association Between Air Quality in Arkadelphia, Arkansas and Customer Satisfaction with Apple

[[ABSTRACT]]
This paper investigates the relationship between the air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. Utilizing data from the Environmental Protection Agency and the American Customer Satisfaction Index spanning from 1994 to 2021, we applied statistical analyses to uncover the potential connection between these seemingly disparate entities. The correlation coefficient of 0.8070970 with a p-value of less than 0.01 indicated a noteworthy association between the two variables. Our findings suggest an intriguing interplay between local air quality and the sentiment towards Apple, thereby shedding light on the unexpected influences on consumer satisfaction. While the link between air quality and customer preferences may appear transparent, our research fosters a deeper understanding of the nuanced factors that shape consumer perceptions.

[[LITERATURE REVIEW]]
The present literature review delves into prior research investigating the relationship between environmental factors and consumer behavior, with a particular focus on air quality and customer preferences. The authors find Smith et al. and Doe et al., who have probed the impact of air quality on consumer sentiment, shedding light on the intricate interplay between environmental variables and consumer behavior. Additionally, Jones et al. have contributed to the understanding of customer satisfaction with technology products, offering valuable insights into the complex dynamics that underpin consumer preferences.
Encompassing the broader context of consumer behavior and environmental influences, seminal works such as "The Economics of Air Quality" and "Consumer Psychology: Understanding Customer Preferences" provide a foundational understanding of the multifaceted factors at play in shaping consumer attitudes. Moving beyond the traditional confines of scholarly literature, fictitious accounts such as "The Air Quality Mysteries" and "The Apple Chronicles: A Tale of Consumer Intrigue" offer imaginative narratives that, while not empirical, capture the essence of the curious connection between air quality and consumer satisfaction.
Moreover, the researchers came across various social media posts that pertain to the relationship between air quality and consumer sentiments toward Apple. One notable post on a popular microblogging platform reads, "The crispness of the air in Arkadelphia seems to translate to the satisfaction with my Apple devices. Coincidence? I think not." Such anecdotal observations, while not scientifically rigorous, underscore the pervasiveness of this phenomenon in colloquial discourse and the public consciousness.

[[RESULTS]]
The statistical analyses applied to the data revealed a correlation coefficient of 0.8070970, indicating a strong and positive relationship between air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. The r-squared value of 0.6514055 further elucidated that approximately 65.14% of the variance in Apple customer satisfaction could be explained by the variance in air quality. Moreover, with a p-value of less than 0.01, the association between these two seemingly unrelated variables proved to be statistically significant.
The figure (Fig. 1) depicts a scatterplot illustrating the robust correlation between air quality and Apple customer satisfaction. The data points form a strikingly upward-sloping pattern, resembling the ascent of an Apple product launch's hype.
These findings, while initially surprising, underscore the intricate interplay between the atmospheric conditions of Arkadelphia and the sentiments of Apple enthusiasts. The influence of air quality, akin to the subtle aroma of a freshly unboxed iPhone, permeates the backdrop of consumer preferences, contributing to the overarching tapestry of satisfaction and delight.
In summary, our investigation has brought to light the unanticipated concordance between local air quality and the allure of Apple, emphasizing the interconnectedness of environmental factors and consumer sentiments. This revelation, akin to stumbling upon a hidden gem in a digital orchard, invites further contemplation on the diverse influences that shape consumer satisfaction.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The present study sought to untangle the enigmatic relationship between air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. Our findings not only corroborate prior research but also offer a fresh perspective on the interplay between seemingly unrelated domains.

Our results align with the works of Smith et al. and Doe et al., highlighting the significant impact of air quality on consumer sentiment. The robust correlation coefficient obtained in our analysis echoes the pioneering efforts of these prior studies, emphasizing the pervasive influence of atmospheric conditions on consumer attitudes. This connection, resembling the sturdy charging cable of an iPhone, elucidates the enduring link between environmental factors and consumer preferences.

Moving beyond the confines of traditional academia, our findings also resonate with the anecdotal accounts discovered in social media posts. The notable post on the correlation between air quality and Apple satisfaction, while lacking scientific rigor, reflects the sentiments echoed in our empirical data. Such informal narratives, akin to the informal voice command feature of Siri, capture the essence of the unanticipated association between air quality and consumer preferences.

Furthermore, our results hint at the underlying mechanisms shaping consumer sentiment, echoing the insights from "The Apple Chronicles: A Tale of Consumer Intrigue." This fictitious narrative, while not grounded in empirical evidence, conveys a symbolic resonance with our empirical findings, reflecting the subtle yet profound impact of environmental factors on consumer satisfaction. Such fictional musings, akin to the cryptic clues in a digital treasure hunt, offer a whimsical yet insightful understanding of the intricate dynamics at play in shaping consumer attitudes.

In conclusion, our study reinforces the notion that the air quality in Arkadelphia, Arkansas, exerts a remarkable influence on the sentiments of Apple enthusiasts. This unexpected connection, reminiscent of the fortuitous discovery of a hidden Easter egg in a software update, invites further exploration into the multifaceted factors that underpin consumer satisfaction.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 quality in Arkadelphia, Arkansas and Customer satisfaction with Apple. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
Astonishing Air Quality and Apple Affinity: Analyzing the Association Between Air Quality in Arkadelphia, Arkansas and Customer Satisfaction with Apple

[[ABSTRACT]]
This paper investigates the relationship between the air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. Utilizing data from the Environmental Protection Agency and the American Customer Satisfaction Index spanning from 1994 to 2021, we applied statistical analyses to uncover the potential connection between these seemingly disparate entities. The correlation coefficient of 0.8070970 with a p-value of less than 0.01 indicated a noteworthy association between the two variables. Our findings suggest an intriguing interplay between local air quality and the sentiment towards Apple, thereby shedding light on the unexpected influences on consumer satisfaction. While the link between air quality and customer preferences may appear transparent, our research fosters a deeper understanding of the nuanced factors that shape consumer perceptions.

[[INTRDUCTION]]
The relationship between environmental factors and consumer behavior has long been a subject of interest in both academic and practical spheres. From the influence of ambient music on shopping habits to the psychological effects of color on purchasing decisions, the quest to uncover the intricacies of consumer preferences knows no bounds. In this vein, our study delves into the unexplored territory of the connection between air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. While the correlation may seem as unlikely as finding a needle in a haystack made of iCloud, the data-driven approach we employ seeks to shed light on this compelling conundrum.
Arkadelphia, Arkansas, a town renowned for its picturesque landscapes and unassuming charm, serves as our setting for this inquiry. Nestled among the rolling hills and whispering pines, the community's air quality has not been a topic of widespread discussion in academic circles. Nevertheless, the silent yet omnipresent influence of air quality on consumer sentiments toward Apple products beckoned our attention. As consumers flock to the sleek and tantalizing offerings of Apple, the breeze in Arkadelphia unfurls its own narrative, weaving a tale of invisible yet palpable impact.
The empirical backbone of our investigation is derived from the comprehensive datasets provided by the Environmental Protection Agency and the American Customer Satisfaction Index. Spanning nearly three decades, these troves of information offer a rare glimpse into the ebb and flow of the air quality in Arkadelphia and the undulating tides of Apple aficionado approval. Through the lens of statistical analyses, we navigate the tempestuous seas of data, seeking to discern patterns and relationships that elude casual observation.
As we navigate this juncture where atmospheric musings and technological fervor converge, we invite the reader to embark on this intellectual escapade with an open mind. The results of our inquiry promise to paint a landscape where the gusts of air quality and the allure of Apple intermingle in unexpected harmony, fostering a newfound appreciation for the whimsical interplay of consumer sentiments.

[[RESULTS]]
The statistical analyses applied to the data revealed a correlation coefficient of 0.8070970, indicating a strong and positive relationship between air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. The r-squared value of 0.6514055 further elucidated that approximately 65.14% of the variance in Apple customer satisfaction could be explained by the variance in air quality. Moreover, with a p-value of less than 0.01, the association between these two seemingly unrelated variables proved to be statistically significant.
The figure (Fig. 1) depicts a scatterplot illustrating the robust correlation between air quality and Apple customer satisfaction. The data points form a strikingly upward-sloping pattern, resembling the ascent of an Apple product launch's hype.
These findings, while initially surprising, underscore the intricate interplay between the atmospheric conditions of Arkadelphia and the sentiments of Apple enthusiasts. The influence of air quality, akin to the subtle aroma of a freshly unboxed iPhone, permeates the backdrop of consumer preferences, contributing to the overarching tapestry of satisfaction and delight.
In summary, our investigation has brought to light the unanticipated concordance between local air quality and the allure of Apple, emphasizing the interconnectedness of environmental factors and consumer sentiments. This revelation, akin to stumbling upon a hidden gem in a digital orchard, invites further contemplation on the diverse influences that shape consumer satisfaction.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

The empirical evidence presented in this study establishes a compelling association between air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. The robust correlation coefficient and statistically significant p-value unveil a surprising bond between these seemingly incongruent variables. It appears that the air quality in Arkadelphia has a notable impact on the sentiment towards Apple, underscoring the pervasive nature of environmental influences on consumer preferences. This unexpected finding, akin to stumbling upon a hidden gem in a digital orchard, invites further contemplation on the diverse influences that shape consumer satisfaction.

The interplay between the invisible tendrils of air quality and the tangible allure of Apple products exemplifies the multifaceted nature of consumer behavior. As consumers bask in the ethereal glow of their sleek gadgets, the atmospheric conditions of Arkadelphia subtly weave their own narrative, contributing to the symphony of consumer sentiments. This revelation, much like the crisp sound of biting into a freshly picked apple, adds a layer of complexity to the understanding of consumer preferences.

While the significance of this association may seem as clear as the Retina display of an iPhone, further research in this domain is not warranted. The findings of this inquiry provide a robust foundation, leaving little room for additional exploration. Therefore, it is with utmost confidence that we assert the conclusion of this study: the interwoven dynamics of air quality in Arkadelphia and customer satisfaction with Apple products have been thoroughly elucidated, and no further research is necessitated in this 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 Astonishing Air Quality and Apple Affinity: Analyzing the Association Between Air Quality in Arkadelphia, Arkansas and Customer Satisfaction with Apple. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Environmental Aesthetics and Fruit-Based Technology

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 Astonishing Air Quality and Apple Affinity: Analyzing the Association Between Air Quality in Arkadelphia, Arkansas and Customer Satisfaction with Apple. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Applicatory Atmosphere 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 Astonishing Air Quality and Apple Affinity: Analyzing the Association Between Air Quality in Arkadelphia, Arkansas and Customer Satisfaction with Apple with an abstract of This paper investigates the relationship between the air quality in Arkadelphia, Arkansas, and customer satisfaction with Apple products. Utilizing data from the Environmental Protection Agency and the American Customer Satisfaction Index spanning from 1994 to 2021, we applied statistical analyses to uncover the potential connection between these seemingly disparate entities. The correlation coefficient of 0.8070970 with a p-value of less than 0.01 indicated a noteworthy association between the two variables. Our findings suggest an intriguing interplay between local air quality and the sentiment towards Apple, thereby shedding light on the unexpected influences on consumer satisfaction. While the link between air quality and customer preferences may appear transparent, our research fosters a deeper understanding of the nuanced factors that shape consumer perceptions.

ChatGPT:

Arkadelphia, Arkansas, air quality, environmental protection agency data, American Customer Satisfaction Index, customer satisfaction, Apple products, statistical analysis, correlation coefficient, consumer satisfaction, consumer preferences, consumer perceptions

*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 Arkadelphia, Arkansas
Detailed data title: Percentage of days with good or moderate air quality in Arkadelphia, AR
Source: Environmental Protection Agency
See what else correlates with Air quality in Arkadelphia, Arkansas

Customer satisfaction with Apple
Source: American Customer Satisfaction Index
See what else correlates with Customer satisfaction with Apple

Correlation r = 0.8070970 (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 = 0.6514055 (Coefficient of determination)
This means 65.1% of the change in the one variable (i.e., Customer satisfaction with Apple) is predictable based on the change in the other (i.e., Air quality in Arkadelphia, Arkansas) over the 28 years from 1994 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.1E-7.^Show 0.0000002116201304291619000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.81 in 2.1E-5% of random cases. Said differently, if you correlated 4,725,448 random variables^Note You don't actually need 4 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 27 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 27 because we have two variables measured over a period of 28 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.

[ 0.62, 0.91 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Air quality in Arkadelphia, Arkansas (Good air quality)	0.963889	0.951128	0.976303	0.972376	0.921788	0.916427	0.927954	0.977901	0.958791	0.989362	0.994253	0.976744	1	0.994413	1	1	0.988858	1	0.996764	0.996855	1	1	1	1	1	1	1	1
Customer satisfaction with Apple (Consumer Satisfaction)	77	75	76	70	69	72	75	73	73	77	81	81	83	79	85	84	86	87	86	87	84	84	84	83	83	83	82	82

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([0.963889,0.951128,0.976303,0.972376,0.921788,0.916427,0.927954,0.977901,0.958791,0.989362,0.994253,0.976744,1,0.994413,1,1,0.988858,1,0.996764,0.996855,1,1,1,1,1,1,1,1,])
array_2 = np.array([77,75,76,70,69,72,75,73,73,77,81,81,83,79,85,84,86,87,86,87,84,84,84,83,83,83,82,82,])
array_1_name = "Air quality in Arkadelphia, Arkansas"
array_2_name = "Customer satisfaction with Apple"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Air quality in Arkadelphia, Arkansas
Line chart for only Customer satisfaction with Apple
AI-generated correlation image
The spurious research paper: Astonishing Air Quality and Apple Affinity: Analyzing the Association Between Air Quality in Arkadelphia, Arkansas and Customer Satisfaction with Apple

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Correlation ID: 4690 · Black Variable ID: 22153 · Red Variable ID: 19869


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