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Spurious correlation #4,662 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Johnstown, Pennsylvania and the second variable is The number of floral designers in Pennsylvania.  The chart goes from 2003 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the air became cleaner, flowers no longer felt the need to hire designers for their petals, ultimately leading to a decrease in floral designers in the state. With no more smoggy competition, the floral industry wilted away, leaving Pennsylvania's floral designers out of a job.

Model: dalle-3
Prompt: Style: A whimsical and colorful illustration with a touch of humor, like something you'd see on r/HumorousArt Description: In a quirky and surreal art piece, we see Johnstown, Pennsylvania depicted with whimsical, larger-than-life flowers bursting through streets and buildings. As the smog dissipates, the once struggling flowers bloom in vibrant colors, creating a whimsical, almost psychedelic scene. Amidst this floral explosion, a line of dejected floral designers is comically depicted shrinking in size, dwindling away, and eventually melting into the burst of flowers. This visually represents the decline in demand for their skills, adding a touch of playful humor to the wilted state of the flower industry. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Air pollution in Johnstown, Pennsylvania and The number of floral designers in Pennsylvania. 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: Concept art Cybernetic art Celtic art Minimalism a funny image you would see on reddit
ChatGPT: a funny image you would see on reddit

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Johnstown, Pennsylvania and The number of floral designers in Pennsylvania, in the following situation: As the air became cleaner, flowers no longer felt the need to hire designers for their petals, ultimately leading to a decrease in floral designers in the state. With no more smoggy competition, the floral industry wilted away, leaving Pennsylvania's floral designers out of a job.. Keep the description simple.
ChatGPT: In Johnstown, Pennsylvania, the air clears up as factories and cars cut down on pollution. As the smog dissipates, the once struggling flowers begin to thrive. However, as the flowers no longer struggle to bloom in the polluted air, the demand for floral designers decreases. With the decrease in demand, the number of floral designers in Pennsylvania dwindles, leaving the once lively flower industry in a wilted state.

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 funny image you would see on reddit ] and depicting this scene: In Johnstown, Pennsylvania, the air clears up as factories and cars cut down on pollution. As the smog dissipates, the once struggling flowers begin to thrive. However, as the flowers no longer struggle to bloom in the polluted air, the demand for floral designers decreases. With the decrease in demand, the number of floral designers in Pennsylvania dwindles, leaving the once lively flower industry in a wilted state. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Style: A whimsical and colorful illustration with a touch of humor, like something you'd see on r/HumorousArt Description: In a quirky and surreal art piece, we see Johnstown, Pennsylvania depicted with whimsical, larger-than-life flowers bursting through streets and buildings. As the smog dissipates, the once struggling flowers bloom in vibrant colors, creating a whimsical, almost psychedelic scene. Amidst this floral explosion, a line of dejected floral designers is comically depicted shrinking in size, dwindling away, and eventually melting into the burst of flowers. This visually represents the decline in demand for their skills, adding a touch of playful humor to the wilted state of the flower industry.

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

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

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in Air pollution in Johnstown, Pennsylvania caused The number of floral designers in Pennsylvania to decrease.

AI academic paper

(Because p < 0.01)
The Pollen Paradox: Examining the Relationship Between Air Pollution in Johnstown, Pennsylvania and the Number of Floral Designers in Pennsylvania

The Journal of Ecological Quirks

Jan 2024

Reminder: This paper is AI-generated. Not real!
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Air pollution in Johnstown, Pennsylvania and The number of floral designers in Pennsylvania. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

Your research team used data from Environmental Protection Agency and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.8221353 and p < 0.01 for 2003 to 2022.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
The Pollen Paradox: Examining the Relationship Between Air Pollution in Johnstown, Pennsylvania and the Number of Floral Designers in Pennsylvania

[[ABSTRACT]]
The connection between environmental factors and employment trends is a blooming area of interest. In this study, we delve into the correlation between air pollution levels in Johnstown, Pennsylvania, and the count of floral designers in the larger state, using data from the Environmental Protection Agency and the Bureau of Labor Statistics. Our analysis yielded a striking correlation coefficient of 0.8221353 with a p-value less than 0.01 for the period spanning 2003 to 2022.

Our findings suggest a noteworthy relationship between air pollution and the demand for floral designers, remarkably budding insights into how environmental conditions may impact the labor market. It appears that higher levels of air pollution have a "pollen-tial" to stimulate the demand for floral designers in Pennsylvania, perhaps reflecting a heightened appreciation for nature's beauty amidst urban environmental challenges. The unique connection between the purity of air and the abundance of floral artistry is certainly nothing to "sniff" at.

This research contributes not only to the understanding of ecological influences on occupational trends but also to the appreciation of unexpected correlations that may "blossom" in the realm of labor economics. Future studies could further explore the intricate interplay between environmental factors and vocational preferences, continuing to uncover the "roots" of such fascinating associations.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between Air pollution in Johnstown, Pennsylvania and The number of floral designers in Pennsylvania. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Here is the title and abstract of the paper:
[[TITLE]]
The Pollen Paradox: Examining the Relationship Between Air Pollution in Johnstown, Pennsylvania and the Number of Floral Designers in Pennsylvania

[[ABSTRACT]]
The connection between environmental factors and employment trends is a blooming area of interest. In this study, we delve into the correlation between air pollution levels in Johnstown, Pennsylvania, and the count of floral designers in the larger state, using data from the Environmental Protection Agency and the Bureau of Labor Statistics. Our analysis yielded a striking correlation coefficient of 0.8221353 with a p-value less than 0.01 for the period spanning 2003 to 2022.

Our findings suggest a noteworthy relationship between air pollution and the demand for floral designers, remarkably budding insights into how environmental conditions may impact the labor market. It appears that higher levels of air pollution have a "pollen-tial" to stimulate the demand for floral designers in Pennsylvania, perhaps reflecting a heightened appreciation for nature's beauty amidst urban environmental challenges. The unique connection between the purity of air and the abundance of floral artistry is certainly nothing to "sniff" at.

This research contributes not only to the understanding of ecological influences on occupational trends but also to the appreciation of unexpected correlations that may "blossom" in the realm of labor economics. Future studies could further explore the intricate interplay between environmental factors and vocational preferences, continuing to uncover the "roots" of such fascinating associations.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Air pollution is a "growing" concern in many urban areas, with detrimental effects on both human health and the environment. The city of Johnstown, Pennsylvania, has not been immune to this issue, facing challenges in maintaining air quality despite efforts to "branch out" with sustainable initiatives. At the same time, the labor market in Pennsylvania has shown interesting "blooms" in the floral design industry, raising questions about the possible role of environmental factors in shaping employment patterns.

The "stem" of this research seeks to explore the "root" cause of a peculiar relationship between air pollution and the number of floral designers in Pennsylvania. Could there be a "pollen-tential" correlation between these seemingly unrelated variables? Our study aims to uncover the "budding" truths behind this intriguing conundrum by digging into the data and planting the seeds for further investigation.

The relationship between air pollution and the employment of floral designers may seem like a "garden variety" topic at first glance, but our findings unveil a "blossoming" connection that "petal" a fascinating story. This study delves deep into the heart of this floral mystery, not just to "twig" the correlation but to shed light on the "scent-sational" interplay between environmental conditions and labor market dynamics.

In this paper, we present a "stem"-ulating analysis of the correlation coefficient and p-value between air pollution levels in Johnstown and the number of floral designers in Pennsylvania, laying the groundwork for a new understanding of the "pollen paradox." By scrutinizing this "pollin-teresting" relationship, we aim to not only enrich the field of labor economics but also to cultivate an appreciation for the unexpected connections that "sprout" from the petals of empirical data.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Johnstown, Pennsylvania and The number of floral designers in Pennsylvania. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
The Pollen Paradox: Examining the Relationship Between Air Pollution in Johnstown, Pennsylvania and the Number of Floral Designers in Pennsylvania

[[ABSTRACT]]
The connection between environmental factors and employment trends is a blooming area of interest. In this study, we delve into the correlation between air pollution levels in Johnstown, Pennsylvania, and the count of floral designers in the larger state, using data from the Environmental Protection Agency and the Bureau of Labor Statistics. Our analysis yielded a striking correlation coefficient of 0.8221353 with a p-value less than 0.01 for the period spanning 2003 to 2022.

Our findings suggest a noteworthy relationship between air pollution and the demand for floral designers, remarkably budding insights into how environmental conditions may impact the labor market. It appears that higher levels of air pollution have a "pollen-tial" to stimulate the demand for floral designers in Pennsylvania, perhaps reflecting a heightened appreciation for nature's beauty amidst urban environmental challenges. The unique connection between the purity of air and the abundance of floral artistry is certainly nothing to "sniff" at.

This research contributes not only to the understanding of ecological influences on occupational trends but also to the appreciation of unexpected correlations that may "blossom" in the realm of labor economics. Future studies could further explore the intricate interplay between environmental factors and vocational preferences, continuing to uncover the "roots" of such fascinating associations.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Air pollution is a "growing" concern in many urban areas, with detrimental effects on both human health and the environment. The city of Johnstown, Pennsylvania, has not been immune to this issue, facing challenges in maintaining air quality despite efforts to "branch out" with sustainable initiatives. At the same time, the labor market in Pennsylvania has shown interesting "blooms" in the floral design industry, raising questions about the possible role of environmental factors in shaping employment patterns.
The "stem" of this research seeks to explore the "root" cause of a peculiar relationship between air pollution and the number of floral designers in Pennsylvania. Could there be a "pollen-tential" correlation between these seemingly unrelated variables? Our study aims to uncover the "budding" truths behind this intriguing conundrum by digging into the data and planting the seeds for further investigation.
The relationship between air pollution and the employment of floral designers may seem like a "garden variety" topic at first glance, but our findings unveil a "blossoming" connection that "petal" a fascinating story. This study delves deep into the heart of this floral mystery, not just to "twig" the correlation but to shed light on the "scent-sational" interplay between environmental conditions and labor market dynamics.
In this paper, we present a "stem"-ulating analysis of the correlation coefficient and p-value between air pollution levels in Johnstown and the number of floral designers in Pennsylvania, laying the groundwork for a new understanding of the "pollen paradox." By scrutinizing this "pollin-teresting" relationship, we aim to not only enrich the field of labor economics but also to cultivate an appreciation for the unexpected connections that "sprout" from the petals of empirical data.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Several studies have investigated the effects of air pollution on various aspects of human life, from health outcomes to economic activities. In "Air Pollution and Human Health: A Review of Recent Findings," Smith et al. present compelling evidence of the detrimental impact of air pollution on respiratory health, citing numerous epidemiological studies that highlight the importance of reducing pollutant levels in urban environments. Similarly, Doe's analysis in "The Economic Consequences of Air Pollution" delves into the economic repercussions of air pollution, emphasizing the need for policy interventions to mitigate environmental degradation and its economic costs.

Now, these serious studies provide a solid foundation for understanding the broader implications of air pollution. However, when we turn our attention specifically to the intriguing case of Johnstown, Pennsylvania, and its unexpectedly whimsical connection to the floral design industry in the state, we stumble upon a truly "rootsy" and "petal-icious" intersection of environmental phenomena and vocational inclinations.

Books like "The Language of Flowers" by Vanessa Diffenbaugh and "Flowers for Algernon" by Daniel Keyes provide insightful narratives about the symbolism and emotional significance of flowers in human life. While not directly related to our research topic, these works underscore the deeply rooted cultural and psychological associations with floral motifs, hinting at the rich tapestry of meanings that flowers weave into our daily experiences - pun intended.

Moving further into the fictitious realm, authors like Jane Bloomfield and Lily Thorne have penned novels such as "Blossoms and Shadows" and "The Rose Garden," respectively, which, although purely works of fiction, capture the essence of horticultural beauty and the enchanting allure of floral landscapes. While we are not examining the fantasy of fiction, these titles serve as a gentle reminder of the enchanting allure and aesthetic appeal of flowers. After all, who wouldn't want to stop and "smell the roses" in a bustling urban environment?

In addition to these literary diversions, our literature review extends to some unexpected sources of inspiration. Despite being outside the conventional realm of academic research, the back of a shampoo bottle can provide surprising insights into the world of flower scents and their intricate relationship with air pollution - after all, it's where we all become amateur chemists, mixing "rosemary mint" or "lavender and chamomile" scents in the comfort of our own showers.

While these sources may initially seem bizarre in the context of a literature review, they add a touch of levity to our exploration of the "pollen paradox," reminding us that the unexpected can "sprout" from the most unlikely places. But fear not - we promise to stick to peer-reviewed sources for the remainder of our analysis, leaving the shampoo bottles firmly on the bathroom shelf.

In the following sections, we will delve into the empirical studies that shed light on the fascinating correlation between air pollution in Johnstown, Pennsylvania, and the number of floral designers in the broader state, demonstrating that even the most unexpected "budding" correlations can "grow" into compelling research questions.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Air pollution in Johnstown, Pennsylvania and The number of floral designers in Pennsylvania. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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 2003 to 2022

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]]
The Pollen Paradox: Examining the Relationship Between Air Pollution in Johnstown, Pennsylvania and the Number of Floral Designers in Pennsylvania

[[ABSTRACT]]
The connection between environmental factors and employment trends is a blooming area of interest. In this study, we delve into the correlation between air pollution levels in Johnstown, Pennsylvania, and the count of floral designers in the larger state, using data from the Environmental Protection Agency and the Bureau of Labor Statistics. Our analysis yielded a striking correlation coefficient of 0.8221353 with a p-value less than 0.01 for the period spanning 2003 to 2022.

Our findings suggest a noteworthy relationship between air pollution and the demand for floral designers, remarkably budding insights into how environmental conditions may impact the labor market. It appears that higher levels of air pollution have a "pollen-tial" to stimulate the demand for floral designers in Pennsylvania, perhaps reflecting a heightened appreciation for nature's beauty amidst urban environmental challenges. The unique connection between the purity of air and the abundance of floral artistry is certainly nothing to "sniff" at.

This research contributes not only to the understanding of ecological influences on occupational trends but also to the appreciation of unexpected correlations that may "blossom" in the realm of labor economics. Future studies could further explore the intricate interplay between environmental factors and vocational preferences, continuing to uncover the "roots" of such fascinating associations.

[[INTRODUCTION]]
Air pollution is a "growing" concern in many urban areas, with detrimental effects on both human health and the environment. The city of Johnstown, Pennsylvania, has not been immune to this issue, facing challenges in maintaining air quality despite efforts to "branch out" with sustainable initiatives. At the same time, the labor market in Pennsylvania has shown interesting "blooms" in the floral design industry, raising questions about the possible role of environmental factors in shaping employment patterns.
The "stem" of this research seeks to explore the "root" cause of a peculiar relationship between air pollution and the number of floral designers in Pennsylvania. Could there be a "pollen-tential" correlation between these seemingly unrelated variables? Our study aims to uncover the "budding" truths behind this intriguing conundrum by digging into the data and planting the seeds for further investigation.
The relationship between air pollution and the employment of floral designers may seem like a "garden variety" topic at first glance, but our findings unveil a "blossoming" connection that "petal" a fascinating story. This study delves deep into the heart of this floral mystery, not just to "twig" the correlation but to shed light on the "scent-sational" interplay between environmental conditions and labor market dynamics.
In this paper, we present a "stem"-ulating analysis of the correlation coefficient and p-value between air pollution levels in Johnstown and the number of floral designers in Pennsylvania, laying the groundwork for a new understanding of the "pollen paradox." By scrutinizing this "pollin-teresting" relationship, we aim to not only enrich the field of labor economics but also to cultivate an appreciation for the unexpected connections that "sprout" from the petals of empirical data.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To investigate the "petal-complex" relationship between air pollution and the employment of floral designers, we utilized data from the Environmental Protection Agency (EPA) on air quality in Johnstown, Pennsylvania, and the Bureau of Labor Statistics (BLS) on the number of floral designers in Pennsylvania. We chose this specific geographical region and occupation to "branch out" into a unique and "rooted" exploration of the ecological impact on labor trends.

Our research team decided to "pollin-ate" the study with data spanning from 2003 to 2022, encompassing a period characterized by various environmental policies and economic fluctuations. We opted for this extensive time frame to capture the "growing" impact of air pollution on the "budding" industry of floral design. Or perhaps we were just "trying to make the data 'grow' on us."

The data from the EPA provided us with comprehensive information on the levels of pollutants such as particulate matter (PM2.5), nitrogen dioxide (NO2), and sulfur dioxide (SO2) in the air, which we used to measure the air quality in Johnstown. We also gathered meteorological data to "sprinkle" into our analysis, aiming to consider the "weathering" effects on air pollution levels and their potential influence on the floral industry. We believe it's important to consider all the "stem-pact" of environmental factors!

As for the BLS data, we conducted a "petal-to-the-metal" examination of the employment statistics for floral designers in Pennsylvania. This detailed information allowed us to study the "stamen-dous" growth or decline in the number of floral designers, providing a "horti-cultured" perspective on the labor market in relation to air pollution.

In analyzing the data, we employed a "gardening" variety of statistical methods, including correlation analysis, regression modeling, and time series analysis. We used specialized software, "Pollin-tics," to conduct our statistical tests, which allowed us to "mow down" the data and expose any "weeds" of confounding variables.

To address the "thorny" issue of potential confounding factors, we also incorporated covariate adjustments in our regression models, aiming to "prune" away any influences that could overshadow the true relationship between air pollution and the employment of floral designers. We were determined to make sure our results were "blossom-proof."

Furthermore, we considered conducting a survey to gather qualitative insights from floral designers on their work preferences and environmental considerations. However, we found ourselves asking, "Would conducting a survey 'flower' into meaningful results?" Nonetheless, we chose not to pursue this approach due to the "petal-ty" of time and resources.

Overall, our approach aimed to "harvest" a comprehensive understanding of the interplay between air pollution in Johnstown, Pennsylvania, and the employment of floral designers in the state. With a "flower-bed" of data at our disposal, we "rose" to the challenge of uncovering the "root" cause of this intriguing correlation, striving to deliver findings that "delivered the 'bud'ing truth."


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Johnstown, Pennsylvania and The number of floral designers in Pennsylvania. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

For the time period 2003 to 2022, you found a correlation 0.8221353, r-squared of 0.6759065, 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]]
The Pollen Paradox: Examining the Relationship Between Air Pollution in Johnstown, Pennsylvania and the Number of Floral Designers in Pennsylvania

[[ABSTRACT]]
The connection between environmental factors and employment trends is a blooming area of interest. In this study, we delve into the correlation between air pollution levels in Johnstown, Pennsylvania, and the count of floral designers in the larger state, using data from the Environmental Protection Agency and the Bureau of Labor Statistics. Our analysis yielded a striking correlation coefficient of 0.8221353 with a p-value less than 0.01 for the period spanning 2003 to 2022.

Our findings suggest a noteworthy relationship between air pollution and the demand for floral designers, remarkably budding insights into how environmental conditions may impact the labor market. It appears that higher levels of air pollution have a "pollen-tial" to stimulate the demand for floral designers in Pennsylvania, perhaps reflecting a heightened appreciation for nature's beauty amidst urban environmental challenges. The unique connection between the purity of air and the abundance of floral artistry is certainly nothing to "sniff" at.

This research contributes not only to the understanding of ecological influences on occupational trends but also to the appreciation of unexpected correlations that may "blossom" in the realm of labor economics. Future studies could further explore the intricate interplay between environmental factors and vocational preferences, continuing to uncover the "roots" of such fascinating associations.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Air pollution is a "growing" concern in many urban areas, with detrimental effects on both human health and the environment. The city of Johnstown, Pennsylvania, has not been immune to this issue, facing challenges in maintaining air quality despite efforts to "branch out" with sustainable initiatives. At the same time, the labor market in Pennsylvania has shown interesting "blooms" in the floral design industry, raising questions about the possible role of environmental factors in shaping employment patterns.
The "stem" of this research seeks to explore the "root" cause of a peculiar relationship between air pollution and the number of floral designers in Pennsylvania. Could there be a "pollen-tential" correlation between these seemingly unrelated variables? Our study aims to uncover the "budding" truths behind this intriguing conundrum by digging into the data and planting the seeds for further investigation.
The relationship between air pollution and the employment of floral designers may seem like a "garden variety" topic at first glance, but our findings unveil a "blossoming" connection that "petal" a fascinating story. This study delves deep into the heart of this floral mystery, not just to "twig" the correlation but to shed light on the "scent-sational" interplay between environmental conditions and labor market dynamics.
In this paper, we present a "stem"-ulating analysis of the correlation coefficient and p-value between air pollution levels in Johnstown and the number of floral designers in Pennsylvania, laying the groundwork for a new understanding of the "pollen paradox." By scrutinizing this "pollin-teresting" relationship, we aim to not only enrich the field of labor economics but also to cultivate an appreciation for the unexpected connections that "sprout" from the petals of empirical data.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Our analysis revealed a strong positive correlation (r = 0.8221353) between air pollution levels in Johnstown, Pennsylvania, and the number of floral designers in Pennsylvania, indicating a notable relationship between these seemingly unrelated variables. The r-squared value of 0.6759065 further emphasizes the "budding" significance of this connection, suggesting that approximately 68% of the variance in the number of floral designers can be explained by variations in air pollution levels. With a p-value less than 0.01, the association between air pollution and the employment of floral designers is statistically significant, providing compelling evidence of this intriguing phenomenon.

Fig. 1 elucidates the captivating correlation we uncovered, presenting a scatterplot that vividly captures the "growing" relationship between air pollution and the number of floral designers. As air pollution levels rise, so does the count of floral designers, painting a "blossom-ing" picture of this unexpected link.

This "pollen paradox" prompts us to reconsider the "roots" of vocational preferences in the midst of environmental challenges, raising intriguing questions about the impact of air quality on the labor market. Our findings suggest that, contrary to conventional wisdom, higher air pollution levels may "pollinate" the demand for floral designers, hinting at a deeper appreciation for nature's beauty amidst urban environmental adversities. This unexpected correlation "photosynthesizes" a fresh perspective on the intricate interplay between ecological conditions and occupational choices.

Our study not only sheds light on this "scent-sational" phenomenon but also opens the door for further exploration of the complexities of environmental influences on employment patterns. It showcases the "petal power" of empirical research in unearthing captivating connections that "blossom" from the shadows of conventional expectations. Our results encourage a "rose-tinted" view of labor market dynamics, emphasizing the "pollen-tial" for unexpected correlations to "sprout" from the fertile soil of data analysis.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Johnstown, Pennsylvania and The number of floral designers in Pennsylvania. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
The Pollen Paradox: Examining the Relationship Between Air Pollution in Johnstown, Pennsylvania and the Number of Floral Designers in Pennsylvania

[[ABSTRACT]]
The connection between environmental factors and employment trends is a blooming area of interest. In this study, we delve into the correlation between air pollution levels in Johnstown, Pennsylvania, and the count of floral designers in the larger state, using data from the Environmental Protection Agency and the Bureau of Labor Statistics. Our analysis yielded a striking correlation coefficient of 0.8221353 with a p-value less than 0.01 for the period spanning 2003 to 2022.

Our findings suggest a noteworthy relationship between air pollution and the demand for floral designers, remarkably budding insights into how environmental conditions may impact the labor market. It appears that higher levels of air pollution have a "pollen-tial" to stimulate the demand for floral designers in Pennsylvania, perhaps reflecting a heightened appreciation for nature's beauty amidst urban environmental challenges. The unique connection between the purity of air and the abundance of floral artistry is certainly nothing to "sniff" at.

This research contributes not only to the understanding of ecological influences on occupational trends but also to the appreciation of unexpected correlations that may "blossom" in the realm of labor economics. Future studies could further explore the intricate interplay between environmental factors and vocational preferences, continuing to uncover the "roots" of such fascinating associations.

[[LITERATURE REVIEW]]
Several studies have investigated the effects of air pollution on various aspects of human life, from health outcomes to economic activities. In "Air Pollution and Human Health: A Review of Recent Findings," Smith et al. present compelling evidence of the detrimental impact of air pollution on respiratory health, citing numerous epidemiological studies that highlight the importance of reducing pollutant levels in urban environments. Similarly, Doe's analysis in "The Economic Consequences of Air Pollution" delves into the economic repercussions of air pollution, emphasizing the need for policy interventions to mitigate environmental degradation and its economic costs.
Now, these serious studies provide a solid foundation for understanding the broader implications of air pollution. However, when we turn our attention specifically to the intriguing case of Johnstown, Pennsylvania, and its unexpectedly whimsical connection to the floral design industry in the state, we stumble upon a truly "rootsy" and "petal-icious" intersection of environmental phenomena and vocational inclinations.
Books like "The Language of Flowers" by Vanessa Diffenbaugh and "Flowers for Algernon" by Daniel Keyes provide insightful narratives about the symbolism and emotional significance of flowers in human life. While not directly related to our research topic, these works underscore the deeply rooted cultural and psychological associations with floral motifs, hinting at the rich tapestry of meanings that flowers weave into our daily experiences - pun intended.
Moving further into the fictitious realm, authors like Jane Bloomfield and Lily Thorne have penned novels such as "Blossoms and Shadows" and "The Rose Garden," respectively, which, although purely works of fiction, capture the essence of horticultural beauty and the enchanting allure of floral landscapes. While we are not examining the fantasy of fiction, these titles serve as a gentle reminder of the enchanting allure and aesthetic appeal of flowers. After all, who wouldn't want to stop and "smell the roses" in a bustling urban environment?
In addition to these literary diversions, our literature review extends to some unexpected sources of inspiration. Despite being outside the conventional realm of academic research, the back of a shampoo bottle can provide surprising insights into the world of flower scents and their intricate relationship with air pollution - after all, it's where we all become amateur chemists, mixing "rosemary mint" or "lavender and chamomile" scents in the comfort of our own showers.
While these sources may initially seem bizarre in the context of a literature review, they add a touch of levity to our exploration of the "pollen paradox," reminding us that the unexpected can "sprout" from the most unlikely places. But fear not - we promise to stick to peer-reviewed sources for the remainder of our analysis, leaving the shampoo bottles firmly on the bathroom shelf.
In the following sections, we will delve into the empirical studies that shed light on the fascinating correlation between air pollution in Johnstown, Pennsylvania, and the number of floral designers in the broader state, demonstrating that even the most unexpected "budding" correlations can "grow" into compelling research questions.

[[RESULTS]]
Our analysis revealed a strong positive correlation (r = 0.8221353) between air pollution levels in Johnstown, Pennsylvania, and the number of floral designers in Pennsylvania, indicating a notable relationship between these seemingly unrelated variables. The r-squared value of 0.6759065 further emphasizes the "budding" significance of this connection, suggesting that approximately 68% of the variance in the number of floral designers can be explained by variations in air pollution levels. With a p-value less than 0.01, the association between air pollution and the employment of floral designers is statistically significant, providing compelling evidence of this intriguing phenomenon.
Fig. 1 elucidates the captivating correlation we uncovered, presenting a scatterplot that vividly captures the "growing" relationship between air pollution and the number of floral designers. As air pollution levels rise, so does the count of floral designers, painting a "blossom-ing" picture of this unexpected link.
This "pollen paradox" prompts us to reconsider the "roots" of vocational preferences in the midst of environmental challenges, raising intriguing questions about the impact of air quality on the labor market. Our findings suggest that, contrary to conventional wisdom, higher air pollution levels may "pollinate" the demand for floral designers, hinting at a deeper appreciation for nature's beauty amidst urban environmental adversities. This unexpected correlation "photosynthesizes" a fresh perspective on the intricate interplay between ecological conditions and occupational choices.
Our study not only sheds light on this "scent-sational" phenomenon but also opens the door for further exploration of the complexities of environmental influences on employment patterns. It showcases the "petal power" of empirical research in unearthing captivating connections that "blossom" from the shadows of conventional expectations. Our results encourage a "rose-tinted" view of labor market dynamics, emphasizing the "pollen-tial" for unexpected correlations to "sprout" from the fertile soil of data analysis.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The "pollen paradox" has certainly "blossomed" into an intriguing area of research, unveiling the unexpected relationship between air pollution in Johnstown, Pennsylvania, and the number of floral designers in the larger state. Our findings provide compelling support for prior research that has underscored the broader ecological and economic implications of air pollution. The correlation coefficient of 0.8221353 identified in our study aligns with previous evidence highlighting the multifaceted impact of environmental factors on human activities.

The work of Smith et al. emphasizing the detrimental effects of air pollution on respiratory health finds an intriguing parallel in our research, as we uncover an unforeseen occupational response to environmental challenges. Our results suggest that the demand for floral designers may indeed "bloom" in the presence of higher air pollution levels, reflecting a unique interplay between environmental conditions and vocational preferences. In a "peta-literal" sense, our study demonstrates that the inhalation of pollutants may paradoxically "pollinate" an increased appreciation for the beauty and vitality of nature, thereby invigorating the floral design industry.

Moreover, our analysis resonates with Doe's emphasis on the economic consequences of air pollution, as we highlight the statistically significant association between air pollution levels and the employment of floral designers. It appears that the influence of air quality on labor market dynamics extends beyond conventional economic costs, evoking a "scent-sible" response in the form of heightened demand for floral artistry. Indeed, our results tout the "pollen-tial" for environmental conditions to foster unexpected occupational trends, transcending the traditional boundaries of labor market analysis.

Returning to our light-hearted literary diversions, our research reaffirms the symbolic and aesthetic significance of flowers as depicted in works like "The Language of Flowers" and "Flowers for Algernon." While these may seem like mere "peta-fictions," our findings lend credence to the notion that the allure of floral motifs can indeed intersect with environmental realities, offering a "blooming" testament to the rich symbolism embedded in our vocational inclinations. One might say that the "floral industry" is truly "in-leaf-itably" intertwined with the fabric of our environmental and economic landscapes!

In conclusion, our study not only unearths the captivating correlation between air pollution in Johnstown and the employment of floral designers but also "petal-icates" the significance of unexpected research questions that "blossom" from the most unlikely connections. It "rose" from the shadows of conventional expectations, encouraging a "tulip-lifting" view of employment dynamics and the remarkable "budding" potential of interdisciplinary investigations. With these "peta-portions" of evidence before us, the "pollen paradox" continues to "sprout" compelling insights into the intricate interplay between environmental conditions and occupational choices.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Johnstown, Pennsylvania and The number of floral designers in Pennsylvania. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
The Pollen Paradox: Examining the Relationship Between Air Pollution in Johnstown, Pennsylvania and the Number of Floral Designers in Pennsylvania

[[ABSTRACT]]
The connection between environmental factors and employment trends is a blooming area of interest. In this study, we delve into the correlation between air pollution levels in Johnstown, Pennsylvania, and the count of floral designers in the larger state, using data from the Environmental Protection Agency and the Bureau of Labor Statistics. Our analysis yielded a striking correlation coefficient of 0.8221353 with a p-value less than 0.01 for the period spanning 2003 to 2022.

Our findings suggest a noteworthy relationship between air pollution and the demand for floral designers, remarkably budding insights into how environmental conditions may impact the labor market. It appears that higher levels of air pollution have a "pollen-tial" to stimulate the demand for floral designers in Pennsylvania, perhaps reflecting a heightened appreciation for nature's beauty amidst urban environmental challenges. The unique connection between the purity of air and the abundance of floral artistry is certainly nothing to "sniff" at.

This research contributes not only to the understanding of ecological influences on occupational trends but also to the appreciation of unexpected correlations that may "blossom" in the realm of labor economics. Future studies could further explore the intricate interplay between environmental factors and vocational preferences, continuing to uncover the "roots" of such fascinating associations.

[[INTRDUCTION]]
Air pollution is a "growing" concern in many urban areas, with detrimental effects on both human health and the environment. The city of Johnstown, Pennsylvania, has not been immune to this issue, facing challenges in maintaining air quality despite efforts to "branch out" with sustainable initiatives. At the same time, the labor market in Pennsylvania has shown interesting "blooms" in the floral design industry, raising questions about the possible role of environmental factors in shaping employment patterns.
The "stem" of this research seeks to explore the "root" cause of a peculiar relationship between air pollution and the number of floral designers in Pennsylvania. Could there be a "pollen-tential" correlation between these seemingly unrelated variables? Our study aims to uncover the "budding" truths behind this intriguing conundrum by digging into the data and planting the seeds for further investigation.
The relationship between air pollution and the employment of floral designers may seem like a "garden variety" topic at first glance, but our findings unveil a "blossoming" connection that "petal" a fascinating story. This study delves deep into the heart of this floral mystery, not just to "twig" the correlation but to shed light on the "scent-sational" interplay between environmental conditions and labor market dynamics.
In this paper, we present a "stem"-ulating analysis of the correlation coefficient and p-value between air pollution levels in Johnstown and the number of floral designers in Pennsylvania, laying the groundwork for a new understanding of the "pollen paradox." By scrutinizing this "pollin-teresting" relationship, we aim to not only enrich the field of labor economics but also to cultivate an appreciation for the unexpected connections that "sprout" from the petals of empirical data.

[[RESULTS]]
Our analysis revealed a strong positive correlation (r = 0.8221353) between air pollution levels in Johnstown, Pennsylvania, and the number of floral designers in Pennsylvania, indicating a notable relationship between these seemingly unrelated variables. The r-squared value of 0.6759065 further emphasizes the "budding" significance of this connection, suggesting that approximately 68% of the variance in the number of floral designers can be explained by variations in air pollution levels. With a p-value less than 0.01, the association between air pollution and the employment of floral designers is statistically significant, providing compelling evidence of this intriguing phenomenon.
Fig. 1 elucidates the captivating correlation we uncovered, presenting a scatterplot that vividly captures the "growing" relationship between air pollution and the number of floral designers. As air pollution levels rise, so does the count of floral designers, painting a "blossom-ing" picture of this unexpected link.
This "pollen paradox" prompts us to reconsider the "roots" of vocational preferences in the midst of environmental challenges, raising intriguing questions about the impact of air quality on the labor market. Our findings suggest that, contrary to conventional wisdom, higher air pollution levels may "pollinate" the demand for floral designers, hinting at a deeper appreciation for nature's beauty amidst urban environmental adversities. This unexpected correlation "photosynthesizes" a fresh perspective on the intricate interplay between ecological conditions and occupational choices.
Our study not only sheds light on this "scent-sational" phenomenon but also opens the door for further exploration of the complexities of environmental influences on employment patterns. It showcases the "petal power" of empirical research in unearthing captivating connections that "blossom" from the shadows of conventional expectations. Our results encourage a "rose-tinted" view of labor market dynamics, emphasizing the "pollen-tial" for unexpected correlations to "sprout" from the fertile soil of data analysis.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has rooted out a captivating connection between air pollution in Johnstown, Pennsylvania, and the employment of floral designers in Pennsylvania. The strong positive correlation we unearthed has certainly "pollen-ated" our understanding of environmental influences on the labor market. It appears that amidst the "fumes" of air pollution, there is a "blooming" demand for floral designers, suggesting that when the air gets "fowled" up, the demand for floral artistry goes up like a "bouquet" of flowers.

Our findings not only provide "petal-centric" insights into this unexpected relationship but also highlight the need to "cultivate" a deeper appreciation for the intertwining factors shaping vocational preferences. It seems that the scent of success for floral designers may be tied to the quality of the air, proving that in the "garden" of labor economics, environmental conditions play a crucial role in planting the seeds of occupational trends.

As we wrap up this "tulip" of research, it is clear that no more "pollen-tical" investigations are needed in this area. We have certainly "rose" to the occasion in uncovering this correlation and "planted" the seeds for future studies to "blossom" in exploring the unexpected interplay between environmental factors and vocational choices. So, let's "leaf" this topic and "branch" out to more "rootsy" research endeavors!


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 The Pollen Paradox: Examining the Relationship Between Air Pollution in Johnstown, Pennsylvania and the Number of Floral Designers in Pennsylvania. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Ecological Quirks


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 The Pollen Paradox: Examining the Relationship Between Air Pollution in Johnstown, Pennsylvania and the Number of Floral Designers in Pennsylvania. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Environmental Aesthetics and Botanical Economics


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 The Pollen Paradox: Examining the Relationship Between Air Pollution in Johnstown, Pennsylvania and the Number of Floral Designers in Pennsylvania with an abstract of The connection between environmental factors and employment trends is a blooming area of interest. In this study, we delve into the correlation between air pollution levels in Johnstown, Pennsylvania, and the count of floral designers in the larger state, using data from the Environmental Protection Agency and the Bureau of Labor Statistics. Our analysis yielded a striking correlation coefficient of 0.8221353 with a p-value less than 0.01 for the period spanning 2003 to 2022.
Our findings suggest a noteworthy relationship between air pollution and the demand for floral designers, remarkably budding insights into how environmental conditions may impact the labor market. It appears that higher levels of air pollution have a "pollen-tial" to stimulate the demand for floral designers in Pennsylvania, perhaps reflecting a heightened appreciation for nature's beauty amidst urban environmental challenges. The unique connection between the purity of air and the abundance of floral artistry is certainly nothing to "sniff" at.
This research contributes not only to the understanding of ecological influences on occupational trends but also to the appreciation of unexpected correlations that may "blossom" in the realm of labor economics. Future studies could further explore the intricate interplay between environmental factors and vocational preferences, continuing to uncover the "roots" of such fascinating associations.

ChatGPT:

air pollution, Johnstown Pennsylvania, floral designers, Pennsylvania, employment trends, environmental factors, correlation, Bureau of Labor Statistics, Environmental Protection Agency, labor market, demand for floral designers, urban environmental challenges, occupational trends, labor economics, ecological influences, vocational preferences

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.



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Data details

Air pollution in Johnstown, Pennsylvania
Detailed data title: Percentage of days with air quality at 'unhealthy for sensitive groups' or worse in Johnstown, PA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Johnstown, Pennsylvania

The number of floral designers in Pennsylvania
Detailed data title: BLS estimate of floral designers in Pennsylvania
Source: Bureau of Larbor Statistics
See what else correlates with The number of floral designers in Pennsylvania

Correlation r = 0.8221353 (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 = 0.6759065 (Coefficient of determination)
This means 67.6% of the change in the one variable (i.e., The number of floral designers in Pennsylvania) is predictable based on the change in the other (i.e., Air pollution in Johnstown, Pennsylvania) over the 20 years from 2003 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 8.7E-6. 0.0000086988322484003360000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.82 in 0.00087% of random cases. Said differently, if you correlated 114,958 random variables You don't actually need 114 thousand 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 19 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 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.

[ 0.6, 0.93 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
20032004200520062007200820092010201120122013201420152016201720182019202020212022
Air pollution in Johnstown, Pennsylvania (Bad air quality days)3.01371.912574.109592.739731.643840.5464480.2739732.739731.662051.912570.8219180.5479450000000.2832860.275482
The number of floral designers in Pennsylvania (Floral Designers)32502830290028102550250023102270224024602430213017001590153016901520136013701930




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
  4. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([3.0137,1.91257,4.10959,2.73973,1.64384,0.546448,0.273973,2.73973,1.66205,1.91257,0.821918,0.547945,0,0,0,0,0,0,0.283286,0.275482,])
array_2 = np.array([3250,2830,2900,2810,2550,2500,2310,2270,2240,2460,2430,2130,1700,1590,1530,1690,1520,1360,1370,1930,])
array_1_name = "Air pollution in Johnstown, Pennsylvania"
array_2_name = "The number of floral designers in Pennsylvania"

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

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



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Correlation ID: 4662 · Black Variable ID: 20761 · Red Variable ID: 13634
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