Spurious correlation #4,578 · 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 Urban Honolulu, Hawaii and the second variable is The number of paralegals in Hawaii. The chart goes from 2004 to 2020, 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 Urban Honolulu, Hawaii and the second variable is The number of paralegals in Hawaii. The chart goes from 2004 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The clean air led to clearer thinking, and more people decided to pursue careers in law. As the smog lifted, so did the interest in legal proceedings, creating a breath of fresh air for the paralegal industry in Hawaii.

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image of Honolulu, Hawaii under a clear blue sky, depicting people engaging in the legal profession. In the foreground, a diverse group of individuals eagerly discussing legal documents and court cases. In the background, young professionals enrolling in paralegal training programs, with the fresh, clean air symbolizing the growing interest in the legal field. The scene should convey the hustle and bustle of the city and the enthusiasm for legal education, while capturing the tranquil and inspirational beauty of the surroundings. 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 Urban Honolulu, Hawaii and The number of paralegals in Hawaii. 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 Discovery magazine cover image Minimalism a Polaroid photo Vaporwave Cute 2D animation
ChatGPT: A Discovery magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air quality in Urban Honolulu, Hawaii and The number of paralegals in Hawaii, in the following situation: The clean air led to clearer thinking, and more people decided to pursue careers in law. As the smog lifted, so did the interest in legal proceedings, creating a breath of fresh air for the paralegal industry in Hawaii.. Keep the description simple.
ChatGPT: A clear blue sky over Honolulu, Hawaii, with people walking around the bustling city. In the foreground, a group of individuals eagerly discussing legal documents and court cases. In the background, a growing number of young professionals enrolling in paralegal training programs, inspired by the fresh, clean air that symbolizes the increasing interest in the legal field.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A Discovery magazine cover image ] and depicting this scene: A clear blue sky over Honolulu, Hawaii, with people walking around the bustling city. In the foreground, a group of individuals eagerly discussing legal documents and court cases. In the background, a growing number of young professionals enrolling in paralegal training programs, inspired by the fresh, clean air that symbolizes the increasing interest in the legal field. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of Honolulu, Hawaii under a clear blue sky, depicting people engaging in the legal profession. In the foreground, a diverse group of individuals eagerly discussing legal documents and court cases. In the background, young professionals enrolling in paralegal training programs, with the fresh, clean air symbolizing the growing interest in the legal field. The scene should convey the hustle and bustle of the city and the enthusiasm for legal education, while capturing the tranquil and inspirational beauty of the surroundings.

*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 increases in Air quality in Urban Honolulu, Hawaii positively influenced The number of paralegals in Hawaii. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Breath of Fresh Careers: Unmasking the Air Quality-Paralegal Paradox in Urban Honolulu, Hawaii

The Journal of Atmospheric Legal Studies

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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Urban Honolulu, Hawaii and The number of paralegals in Hawaii. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Bureau of Larbor Statistics . You used data from 2004 to 2020

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]]
"Breath of Fresh Careers: Unmasking the Air Quality-Paralegal Paradox in Urban Honolulu, Hawaii"

[[ABSTRACT]]
In this study, we delve into the hazy intersection between air quality in Urban Honolulu, Hawaii and the number of paralegals populating the islands. Utilizing data from the Environmental Protection Agency and the Bureau of Labor Statistics for the period spanning 2004 to 2020, we set out to clear the air surrounding this enigmatic relationship. Our findings reveal a surprising correlation coefficient of 0.8248279 with p < 0.01, indicating a remarkably robust connection between the two variables. Not only do we uncover this statistical significance, but we also embark on an exploration of the potential causal pathways, attempting to sift through the murkiness and breathe new life into the discussion. Join us as we metaphorically don our gas masks, ready to unpack this conundrum lurking in the mists of island life.

[[INTRODUCTION]]
Introduction
The pursuit of understanding the intricate web of factors shaping urban livelihoods has led researchers to explore a myriad of unconventional and at times, peculiar relationships. In this vein, our study delves into the mystifying intersection between two seemingly unrelated phenomena: air quality in Urban Honolulu, Hawaii and the prevalence of paralegal professionals within the state. The juxtaposition of the breathtaking landscapes of Honolulu and the intricacies of the legal profession may at first glance appear as disparate as a snorkeler and a sumo wrestler engaging in a tug-of-war, but our investigation aims to unveil the invisible threads weaving these disparate elements together.
The allure of Honolulu, with its balmy breezes and swaying palms, is juxtaposed against the legal labyrinth inhabited by paralegals, creating a rich tapestry of contrasts. One might imagine that the air quality and legal acumen are as unlikely bedfellows as a pineapple and a pizza, yet our preliminary analysis suggests a potential correlation that is as unexpected as finding a coconut in a snowstorm.
As we embark on this academic escapade, it is vital to acknowledge the growing importance of understanding the myriad factors influencing both environmental conditions and professional pursuits. Perhaps, as we uncover the invisible hands guiding the levels of air pollutants and the number of paralegals, we may stumble upon a revelation as startling as stumbling upon an octopus wearing a business suit.
In the following pages, we elucidate our methodological approach, unearth our findings, and attempt to carve a path through the intellectual undergrowth that this peculiar correlation has introduced. So, dear reader, fasten your seatbelt as we prepare to navigate the juncture where clean air and legal expertise intersect. For it is in this unlikely crossroads that we may unravel a conundrum as confounding as a detective trying to solve a case with a magic eight ball.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Sampling Strategy
In order to grasp the elusive relationship between air quality in Urban Honolulu, Hawaii and the number of paralegals populating the islands, we embarked on a data collection journey as thrilling as a treasure hunt, albeit with less pirates and more spreadsheets. Our sampling strategy involved gathering data from the Environmental Protection Agency (EPA) and the Bureau of Labor Statistics (BLS), utilizing their online databases like scholarly pirates navigating the high seas of information. We selected data from the years 2004 to 2020, casting a wide net to capture the ebb and flow of air quality and paralegal presence over time. It's important to note that our research team didn't actually wear eyepatches or say "Arr matey!" during this process, but the mental image might make the methodology section slightly more exciting.

Air Quality Metrics
To measure the invisible particles suspended in the Honolulan atmosphere, we accessed air quality data from the EPA, akin to gazing through a microscope at the intricate dance of pollen grains and industrial emissions. We focused on pollutants such as particulate matter (PM10 and PM2.5), ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and lead (Pb), navigating the labyrinth of data with a precision as delicate as a trapeze artist's balancing act. The choice of pollutants may seem as niche as a pop-up book about quantum physics, but it allowed us to capture the multidimensional nature of air quality and its potential impact on legal career pathways.

Paralegal Census
In parallel, we delved into the BLS repository, combing through occupational data like detectives on the scent of a clue. We meticulously gathered information on the number of paralegals employed in Hawaii, examining trends and fluctuations as attentively as a botanist observing the blossom of a rare orchid. The BLS records, while not as dramatic as a soap opera, provided a panoramic view of the paralegal panorama, guiding us through the peaks and valleys of their professional landscape.

Data Analysis
To whisk our data into comprehensible insights, we enlisted the aid of statistical software resembling a culinary maestro crafting a delectable dish from an array of exotic ingredients. We computed correlation coefficients, p-values, and constructed scatterplots, treating our data with the reverence one would afford a delicate porcelain vase. Our approach was as meticulous as a detective reconstructing a crime scene, piecing together the puzzle of air quality and paralegal presence with the intent of proving causation rather than mere correlation, like the intrepid detective in a mystery novel determined to unmask the true culprit.

Limitations
As with any undulating voyage of inquiry, our expedition faced limitations akin to storm clouds on the horizon. The data, while robust, may not encapsulate every nuance of air quality or paralegal employment, leaving room for as many unresolved questions as a riddle wrapped in an enigma. Furthermore, the potential influence of external variables remained as elusive as a chameleon at a Mardi Gras parade, adding layers of complexity to our exploration.

In conclusion, our methodological approach seeks to provide a sturdy bridge between the ethereal realms of air quality and the professional habitat of paralegals, grounding our investigation in a solid framework as stable as a mathematician's theorem. Join us as we continue our journey through the dusty tomes of data analysis and embark on the exhilarating quest to shine a light on this peculiar correlation, with all the academic zeal of a detective chasing down a lead in a film noir.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Urban Honolulu, Hawaii and The number of paralegals in Hawaii. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Breath of Fresh Careers: Unmasking the Air Quality-Paralegal Paradox in Urban Honolulu, Hawaii"

[[ABSTRACT]]
In this study, we delve into the hazy intersection between air quality in Urban Honolulu, Hawaii and the number of paralegals populating the islands. Utilizing data from the Environmental Protection Agency and the Bureau of Labor Statistics for the period spanning 2004 to 2020, we set out to clear the air surrounding this enigmatic relationship. Our findings reveal a surprising correlation coefficient of 0.8248279 with p < 0.01, indicating a remarkably robust connection between the two variables. Not only do we uncover this statistical significance, but we also embark on an exploration of the potential causal pathways, attempting to sift through the murkiness and breathe new life into the discussion. Join us as we metaphorically don our gas masks, ready to unpack this conundrum lurking in the mists of island life.

[[LITERATURE REVIEW]]
The study of the correlation between air quality and professional demographics has been a complex and multifaceted area of research. Smith (2015) explores the impact of urban air pollution on occupational health, shedding light on the potentially far-reaching consequences of poor air quality on various professions. Meanwhile, Doe and Jones (2017) delve into the dynamics of regional labor markets, uncovering intriguing patterns in the distribution of different professions across geographical areas. These studies showcase the breadth of considerations at play when examining the interplay between environmental conditions and the composition of the workforce.
Turning to the realm of non-fiction literature, works such as "Air Pollution and Its Effects on Health" by Environmental Health Perspectives offer comprehensive insights into the detrimental effects of air pollution on human well-being. Likewise, "Legal Eagles: Stories of Success in the Law" by Legal Practice Press presents a collection of narratives from paralegal professionals, providing glimpses into the diverse and multifaceted world of legal support services.
Expanding beyond the confines of non-fiction, fictional works such as John Grisham's legal thrillers and Janet Evanovich's comedic mysteries weave tales of legal intricacies and investigative pursuits. While these fictional narratives may not offer direct empirical insights, they contribute to the broader cultural milieu surrounding legal professions, adding a layer of richness to the context within which real-world phenomena unfold.
In the pursuit of comprehensive understanding, the researchers have also ventured into unconventional sources, including perusing CVS receipts and deciphering the cryptic messages hidden within. While these endeavors may not adhere to traditional scholarly practices, they have provided intriguing glimpses into the purchasing habits of individuals in relation to air quality and its potential influence on career choices. The researchers must, however, caution against using CVS receipts as primary data sources in future academic endeavors, as the correlation between Airborne Cold Remedy purchases and paralegal prevalence remains tenuous at best.
As the academic quest for knowledge unfurls, it is essential to consider the breadth of sources that contribute to the tapestry of understanding. From scholarly articles to fictional escapades and even the humble CVS receipt, each piece adds a layer to the enigmatic puzzle at hand. In the subsequent sections, we delve into the methodological framework employed to ferret out the realities underlying the air quality-paralegal paradox in Urban Honolulu, Hawaii.

[[RESULTS]]
Correlation Analysis
The analysis of the relationship between air quality in Urban Honolulu, Hawaii and the number of paralegals revealed a correlation coefficient of 0.8248279, accompanied by an r-squared value of 0.6803410, demonstrating a substantial proportion of the variance in the number of paralegals being explained by the air quality in Urban Honolulu. The level of statistical significance was particularly noteworthy, with a p-value less than 0.01, indicating a high degree of confidence in the observed correlation.
This correlation can be represented visually in Figure 1, a scatterplot displaying the conspicuous relationship between the air quality index and the number of paralegals in Urban Honolulu. The striking alignment of data points in the scatterplot serves as a compelling visual testament to the robust correlation unearthed in our analysis. It's almost as clear as the blue skies over Honolulu on a pristine day – although, we should remember that correlation does not imply causation, and while the connection is robust, the reasons behind it remain shrouded in mystery, much like the deep sea off the Kewalo Basin.
While the correlation speaks volumes about the connection between air quality and the number of paralegals, it piques our curiosity to dig deeper into the potential mechanisms at play, much like a detective sifting through clues to crack a case. The resounding statistical significance of our findings beckons us to embark on a journey to unravel the causal pathways linking the two seemingly unrelated variables, akin to navigating a tangled web of legal jargon and atmospheric intricacies.
Given the unexpected nature of this correlation, it is imperative to approach the interpretation of these results with caution and academic rigor. Nevertheless, the strength of the relationship between air quality and the number of paralegals in Urban Honolulu is as palpable as the trade winds blowing across the islands, leaving us with an intriguing conundrum that demands further exploration and scrutiny.
The robustness of this correlation challenges conventional wisdom, inviting researchers and policymakers to delve into the depths of this curious juxtaposition. It is akin to finding a hidden message in a bottle washed ashore – an unexpected discovery amidst the vast expanse of the empirical ocean, sparking both wonder and a thirst for understanding the profound implications of this unexpected relationship.
The potential implications of this correlation extend beyond the realms of statistical analysis, beckoning us to ponder the intricate interplay between occupational choices and environmental conditions. As we cautiously navigate through this uncharted territory, it is our hope that this study serves as a clarion call for further investigation into this intriguing amalgamation of atmospheric nuances and professional pursuits.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study have unveiled a compelling relationship between air quality in Urban Honolulu, Hawaii and the number of paralegals, shedding light on an unexpected interplay between atmospheric conditions and occupational demographics. This unanticipated correlation brings to mind the intricate dance of Honolulu's hula, where seemingly disparate elements come together to form a harmonious whole. Our findings not only align with prior research emphasizing the impact of environmental factors on occupational health and regional labor markets, but they also serve as a testament to the captivating complexity of real-world phenomena.

Smith's (2015) exploration of urban air pollution's influence on occupational health reverberates with striking echoes in our investigation. Much like a symphony echoing across Diamond Head, Smith's work highlights the far-reaching repercussions of poor air quality on various professions. Meanwhile, the intriguing patterns observed by Doe and Jones (2017) in the distribution of different professions across geographical areas seem to resonate with the correlation we have unearthed, albeit in a subtler, more melodic key.

The enigmatic puzzle of the air quality-paralegal paradox has unraveled before our eyes, much like a magic act performed amidst the vibrant streets of Waikiki. While our findings denote a strong association, akin to the magnetic allure of the North Shore's waves, they do not conclusively establish causation. The underlying mechanisms governing this correlation remain as elusive as a rare Hawaiian monk seal, inspiring a sense of wonder and the desire to delve deeper into the depths of this scholarly lagoon.

It is noteworthy that our study embraces a multidisciplinary approach, drawing inspiration from diverse sources such as non-fiction literature and even the enigmatic world of CVS receipts. While our engagement with unconventional sources may raise eyebrows, much like a curious sea turtle peeking out from beneath the waves, the insights gathered have enriched our understanding of the complex interplay between atmospheric nuances and professional choices.

As we navigate this uncharted territory, it is crucial to exercise caution in interpreting our findings and to approach them with the same level of scrutiny as one would apply to deciphering ancient petroglyphs. Nevertheless, our study contributes a refreshing breeze to the academic arena, beckoning researchers and policymakers to contemplate the far-reaching implications of this unexpected relationship. Just as a Hawaii vacation brochure promises a myriad of wonders to behold, our research invites further exploration into the captivating juxtaposition of air quality and professional pursuits, weaving a narrative as enthralling as the sunset over the Pacific Ocean.

The potential consequences of this correlation extend beyond the realms of statistical analysis, echoing through the verdant valleys and bustling streets of Honolulu. Our research serves as a clarion call for continued inquiry into this intriguing amalgamation of atmospheric nuances and professional pursuits, amplifying the urgency to decode this riddle wrapped in a mystery inside an enigma.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Urban Honolulu, Hawaii and The number of paralegals in Hawaii. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Breath of Fresh Careers: Unmasking the Air Quality-Paralegal Paradox in Urban Honolulu, Hawaii"

[[ABSTRACT]]
In this study, we delve into the hazy intersection between air quality in Urban Honolulu, Hawaii and the number of paralegals populating the islands. Utilizing data from the Environmental Protection Agency and the Bureau of Labor Statistics for the period spanning 2004 to 2020, we set out to clear the air surrounding this enigmatic relationship. Our findings reveal a surprising correlation coefficient of 0.8248279 with p < 0.01, indicating a remarkably robust connection between the two variables. Not only do we uncover this statistical significance, but we also embark on an exploration of the potential causal pathways, attempting to sift through the murkiness and breathe new life into the discussion. Join us as we metaphorically don our gas masks, ready to unpack this conundrum lurking in the mists of island life.

[[INTRDUCTION]]
Introduction
The pursuit of understanding the intricate web of factors shaping urban livelihoods has led researchers to explore a myriad of unconventional and at times, peculiar relationships. In this vein, our study delves into the mystifying intersection between two seemingly unrelated phenomena: air quality in Urban Honolulu, Hawaii and the prevalence of paralegal professionals within the state. The juxtaposition of the breathtaking landscapes of Honolulu and the intricacies of the legal profession may at first glance appear as disparate as a snorkeler and a sumo wrestler engaging in a tug-of-war, but our investigation aims to unveil the invisible threads weaving these disparate elements together.
The allure of Honolulu, with its balmy breezes and swaying palms, is juxtaposed against the legal labyrinth inhabited by paralegals, creating a rich tapestry of contrasts. One might imagine that the air quality and legal acumen are as unlikely bedfellows as a pineapple and a pizza, yet our preliminary analysis suggests a potential correlation that is as unexpected as finding a coconut in a snowstorm.
As we embark on this academic escapade, it is vital to acknowledge the growing importance of understanding the myriad factors influencing both environmental conditions and professional pursuits. Perhaps, as we uncover the invisible hands guiding the levels of air pollutants and the number of paralegals, we may stumble upon a revelation as startling as stumbling upon an octopus wearing a business suit.
In the following pages, we elucidate our methodological approach, unearth our findings, and attempt to carve a path through the intellectual undergrowth that this peculiar correlation has introduced. So, dear reader, fasten your seatbelt as we prepare to navigate the juncture where clean air and legal expertise intersect. For it is in this unlikely crossroads that we may unravel a conundrum as confounding as a detective trying to solve a case with a magic eight ball.

[[RESULTS]]
Correlation Analysis
The analysis of the relationship between air quality in Urban Honolulu, Hawaii and the number of paralegals revealed a correlation coefficient of 0.8248279, accompanied by an r-squared value of 0.6803410, demonstrating a substantial proportion of the variance in the number of paralegals being explained by the air quality in Urban Honolulu. The level of statistical significance was particularly noteworthy, with a p-value less than 0.01, indicating a high degree of confidence in the observed correlation.
This correlation can be represented visually in Figure 1, a scatterplot displaying the conspicuous relationship between the air quality index and the number of paralegals in Urban Honolulu. The striking alignment of data points in the scatterplot serves as a compelling visual testament to the robust correlation unearthed in our analysis. It's almost as clear as the blue skies over Honolulu on a pristine day – although, we should remember that correlation does not imply causation, and while the connection is robust, the reasons behind it remain shrouded in mystery, much like the deep sea off the Kewalo Basin.
While the correlation speaks volumes about the connection between air quality and the number of paralegals, it piques our curiosity to dig deeper into the potential mechanisms at play, much like a detective sifting through clues to crack a case. The resounding statistical significance of our findings beckons us to embark on a journey to unravel the causal pathways linking the two seemingly unrelated variables, akin to navigating a tangled web of legal jargon and atmospheric intricacies.
Given the unexpected nature of this correlation, it is imperative to approach the interpretation of these results with caution and academic rigor. Nevertheless, the strength of the relationship between air quality and the number of paralegals in Urban Honolulu is as palpable as the trade winds blowing across the islands, leaving us with an intriguing conundrum that demands further exploration and scrutiny.
The robustness of this correlation challenges conventional wisdom, inviting researchers and policymakers to delve into the depths of this curious juxtaposition. It is akin to finding a hidden message in a bottle washed ashore – an unexpected discovery amidst the vast expanse of the empirical ocean, sparking both wonder and a thirst for understanding the profound implications of this unexpected relationship.
The potential implications of this correlation extend beyond the realms of statistical analysis, beckoning us to ponder the intricate interplay between occupational choices and environmental conditions. As we cautiously navigate through this uncharted territory, it is our hope that this study serves as a clarion call for further investigation into this intriguing amalgamation of atmospheric nuances and professional pursuits.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study illuminates the tantalizing link between air quality in Urban Honolulu, Hawaii, and the prevalence of paralegals, a connection as unexpected as a coconut falling from a palm tree. The statistical robustness of the correlation invites further contemplation, much like a captivating mystery novel that leaves readers yearning for the next chapter. While our findings paint a vivid picture of this enigmatic relationship, the causative pathways remain as elusive as a rare bird fluttering through the Hawaiian rainforest.

Like diligent detectives, we have sifted through the evidence and unraveled a correlation that stands as solid as a robust alibi. The strength of this relationship defies traditional logic, akin to a starlit night in the middle of a bustling city. It beckons researchers to venture into unexplored territory, much like intrepid explorers charting their way through unfamiliar terrain.

As we close this chapter, the correlation we've uncovered is a beacon beckoning the academic and professional community to contemplate the mystical dance between air quality and the legal profession, a duet as captivating as a hula under the island moonlight. Yet, just as a dessert menu offers a variety of options, further research in this area might yield as much novelty as an unexpected taste sensation from a Hawaiian shave ice.

In light of this, we assert that the findings of this study suffice to satisfy the curiosity surrounding the air quality-paralegal paradox, much like a fulfilling meal after a long day's work. It is akin to reaching the summit of a challenging hike – no more uphill battles are needed in this area of inquiry. Like a satisfying punchline to a well-crafted joke, this correlation stands as a testament to the delightful unpredictability of empirical inquiry.

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 Breath of Fresh Careers: Unmasking the Air Quality-Paralegal Paradox in Urban Honolulu, Hawaii. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Atmospheric Legal Studies

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 Breath of Fresh Careers: Unmasking the Air Quality-Paralegal Paradox in Urban Honolulu, Hawaii. Respond only with the name of a fictional organization.

ChatGPT:

The Association for Sustainable Urban Planning and Environmental Research

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 Breath of Fresh Careers: Unmasking the Air Quality-Paralegal Paradox in Urban Honolulu, Hawaii with an abstract of In this study, we delve into the hazy intersection between air quality in Urban Honolulu, Hawaii and the number of paralegals populating the islands. Utilizing data from the Environmental Protection Agency and the Bureau of Labor Statistics for the period spanning 2004 to 2020, we set out to clear the air surrounding this enigmatic relationship. Our findings reveal a surprising correlation coefficient of 0.8248279 with p < 0.01, indicating a remarkably robust connection between the two variables. Not only do we uncover this statistical significance, but we also embark on an exploration of the potential causal pathways, attempting to sift through the murkiness and breathe new life into the discussion. Join us as we metaphorically don our gas masks, ready to unpack this conundrum lurking in the mists of island life.

ChatGPT:

"air quality paralegal correlation urban honolulu hawaii", "environmental protection agency data air quality honolulu hawaii", "bureau of labor statistics paralegal employment urban honolulu hawaii", "causal relationship paralegal employment air quality honolulu hawaii", "urban honolulu hawaii air quality impact on careers"

*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 Urban Honolulu, Hawaii
Detailed data title: Percentage of days with good air quality in Urban Honolulu, HI
Source: Environmental Protection Agency
See what else correlates with Air quality in Urban Honolulu, Hawaii

The number of paralegals in Hawaii
Detailed data title: BLS estimate of paralegals and legal assistants in Hawaii
Source: Bureau of Larbor Statistics
See what else correlates with The number of paralegals in Hawaii

Correlation r = 0.8248279 (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 = 0.6803410 (Coefficient of determination)
This means 68% of the change in the one variable (i.e., The number of paralegals in Hawaii) is predictable based on the change in the other (i.e., Air quality in Urban Honolulu, Hawaii) over the 17 years from 2004 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.6E-5.^Show 0.0000461427135715197400000000
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 0.82 in 0.0046% of random cases. Said differently, if you correlated 21,672 random variables^Note You don't actually need 21 thousand variables to find a correlation like this one. 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.

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 16 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 16 because we have two variables measured over a period of 17 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.

[ 0.57, 0.93 ] 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.

	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Air quality in Urban Honolulu, Hawaii (Good air quality)	99.1803	97.2603	98.0822	98.9041	96.9945	95.0685	81.3699	72.8767	91.5301	95.0685	96.9359	90.6849	96.4481	97.2603	99.1781	99.1781	99.7268
The number of paralegals in Hawaii (Laborers)	1120	1160	860	1060	890	950	590	560	1170	1020	1140	910	1050	1130	1070	1090	1150

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([99.1803,97.2603,98.0822,98.9041,96.9945,95.0685,81.3699,72.8767,91.5301,95.0685,96.9359,90.6849,96.4481,97.2603,99.1781,99.1781,99.7268,])
array_2 = np.array([1120,1160,860,1060,890,950,590,560,1170,1020,1140,910,1050,1130,1070,1090,1150,])
array_1_name = "Air quality in Urban Honolulu, Hawaii"
array_2_name = "The number of paralegals in Hawaii"

# 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 Urban Honolulu, Hawaii
Line chart for only The number of paralegals in Hawaii
AI-generated correlation image
The spurious research paper: Breath of Fresh Careers: Unmasking the Air Quality-Paralegal Paradox in Urban Honolulu, Hawaii

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Correlation ID: 4578 · Black Variable ID: 21377 · Red Variable ID: 16998


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