Download png, svg
AI explanation
With the air cleared up, the city finally made the switch to modern technology, leaving the operators hanging on the line for a new career path.Model: dalle-3
Prompt: [ A photo-realistic image ] Create an image of Weirton, West Virginia, with clear blue skies and a sense of modernity in the cityscape. Show the switchboard operators transitioning away from their old jobs, with a nostalgic touch, while indicating a transition towards new opportunities. The image should capture the spirit of technological progress and the promise of a new era without losing the human element of change. 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 Weirton, West Virginia and The number of switchboard operators in West Virginia. 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: Pop art A photo-realistic image Cyberpunk Macabre Oragami
ChatGPT: A photo-realistic image
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Weirton, West Virginia and The number of switchboard operators in West Virginia, in the following situation: With the air cleared up, the city finally made the switch to modern technology, leaving the operators hanging on the line for a new career path.. Keep the description simple.
ChatGPT: In Weirton, West Virginia, the clear blue sky heralded a new era as the city embraced modern technology. With the air pollution significantly reduced, the old switchboard operators found themselves hanging up their headsets, signaling the end of their era as they navigated towards new career paths.
Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A photo-realistic image ] and depicting this scene: In Weirton, West Virginia, the clear blue sky heralded a new era as the city embraced modern technology. With the air pollution significantly reduced, the old switchboard operators found themselves hanging up their headsets, signaling the end of their era as they navigated towards new career paths. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A photo-realistic image ] Create an image of Weirton, West Virginia, with clear blue skies and a sense of modernity in the cityscape. Show the switchboard operators transitioning away from their old jobs, with a nostalgic touch, while indicating a transition towards new opportunities. The image should capture the spirit of technological progress and the promise of a new era without losing the human element of change.
*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.
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 Weirton, West Virginia caused The number of switchboard operators in West Virginia to decrease. Include one good pun.
AI academic paper
Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State The Journal of Unlikely Correlations Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Air pollution in Weirton, West Virginia and The number of switchboard operators in West Virginia. Make lots of jokes, goofy observations, and puns.
Include a pun in the title.
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 0.8122729 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]]
Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State
[[ABSTRACT]]
This paper investigates the unexpected relationship between air pollution levels in Weirton, West Virginia, and the number of switchboard operators in the entire state. By combining air quality data from the Environmental Protection Agency with employment statistics from the Bureau of Labor Statistics, our research team conducted a comprehensive analysis spanning the years 2003 to 2022. Our findings reveal a notable correlation coefficient of 0.8122729 and a p-value less than 0.01, demonstrating a significant association between air pollution levels in Weirton and the decline of switchboard operators in West Virginia. Our results suggest that, just like air pollution can clog up the atmosphere, it seems to have clogged the demand for switchboard operators in the state. This unexpected connection sheds light on the broader impact of environmental factors on labor markets and prompts further investigation into the potential consequences of air pollution on occupational trends.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Air pollution in Weirton, West Virginia and The number of switchboard operators in West Virginia. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Here is the title and abstract of the paper:
[[TITLE]]
Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State
[[ABSTRACT]]
This paper investigates the unexpected relationship between air pollution levels in Weirton, West Virginia, and the number of switchboard operators in the entire state. By combining air quality data from the Environmental Protection Agency with employment statistics from the Bureau of Labor Statistics, our research team conducted a comprehensive analysis spanning the years 2003 to 2022. Our findings reveal a notable correlation coefficient of 0.8122729 and a p-value less than 0.01, demonstrating a significant association between air pollution levels in Weirton and the decline of switchboard operators in West Virginia. Our results suggest that, just like air pollution can clog up the atmosphere, it seems to have clogged the demand for switchboard operators in the state. This unexpected connection sheds light on the broader impact of environmental factors on labor markets and prompts further investigation into the potential consequences of air pollution on occupational trends.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
The study of unexpected connections in the realm of research is like playing a game of scientific connect-the-dots. Sometimes, when you least expect it, two seemingly unrelated variables can suddenly reveal a surprising link, leaving you to connect the dots between them. In this paper, we delve into the peculiar relationship between the level of air pollution in Weirton, West Virginia, and the dwindling numbers of switchboard operators across the entire state. It's a story of science and circumstance, where statistical analysis meets telecommunication trends in a way that is sure to dial up your interest.
Air pollution has long been the villain in the atmospheric tale – the unwelcome guest at the global environmental party. Meanwhile, switchboard operators, once the unsung heroes of communication, have been fading into obscurity faster than you can say "operator, can you connect me to a pun?" Yet, little did we know that these two seemingly disparate threads would weave together to form a tapestry of statistical curiosity.
As we embark on this scientific journey, it's important to acknowledge the quirks and curiosities that often come hand-in-hand with research endeavors. The thought of a swirl of air particles impacting the job market feels like a plot twist straight out of a quirky, niche comedy. However, as we dig deeper into the data, it becomes clear that this connection is no laughing matter. Well, at least not entirely.
So, join us as we traverse the statistical wilderness in search of the bridge between air pollution in Weirton, West Virginia, and the decline of switchboard operators across the state. It's a journey that promises to be as enlightening as it is unexpected, proving once again that in the world of research, truth is often stranger than fiction.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Weirton, West Virginia and The number of switchboard operators in West Virginia. Make lots of jokes, goofy observations, and puns.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then you might move on to cartoons and children's shows that you watched for research.
Here is the title and abstract of the paper:
[[TITLE]]
Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State
[[ABSTRACT]]
This paper investigates the unexpected relationship between air pollution levels in Weirton, West Virginia, and the number of switchboard operators in the entire state. By combining air quality data from the Environmental Protection Agency with employment statistics from the Bureau of Labor Statistics, our research team conducted a comprehensive analysis spanning the years 2003 to 2022. Our findings reveal a notable correlation coefficient of 0.8122729 and a p-value less than 0.01, demonstrating a significant association between air pollution levels in Weirton and the decline of switchboard operators in West Virginia. Our results suggest that, just like air pollution can clog up the atmosphere, it seems to have clogged the demand for switchboard operators in the state. This unexpected connection sheds light on the broader impact of environmental factors on labor markets and prompts further investigation into the potential consequences of air pollution on occupational trends.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The study of unexpected connections in the realm of research is like playing a game of scientific connect-the-dots. Sometimes, when you least expect it, two seemingly unrelated variables can suddenly reveal a surprising link, leaving you to connect the dots between them. In this paper, we delve into the peculiar relationship between the level of air pollution in Weirton, West Virginia, and the dwindling numbers of switchboard operators across the entire state. It's a story of science and circumstance, where statistical analysis meets telecommunication trends in a way that is sure to dial up your interest.
Air pollution has long been the villain in the atmospheric tale – the unwelcome guest at the global environmental party. Meanwhile, switchboard operators, once the unsung heroes of communication, have been fading into obscurity faster than you can say "operator, can you connect me to a pun?" Yet, little did we know that these two seemingly disparate threads would weave together to form a tapestry of statistical curiosity.
As we embark on this scientific journey, it's important to acknowledge the quirks and curiosities that often come hand-in-hand with research endeavors. The thought of a swirl of air particles impacting the job market feels like a plot twist straight out of a quirky, niche comedy. However, as we dig deeper into the data, it becomes clear that this connection is no laughing matter. Well, at least not entirely.
So, join us as we traverse the statistical wilderness in search of the bridge between air pollution in Weirton, West Virginia, and the decline of switchboard operators across the state. It's a journey that promises to be as enlightening as it is unexpected, proving once again that in the world of research, truth is often stranger than fiction.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The interplay between environmental factors and labor market trends has long been a source of fascination among researchers. The unexpected connections that emerge from such investigations often challenge conventional wisdom and provoke a sense of scholarly curiosity. In the realm of air pollution and its impact on occupational trends, the literature provides a range of insights, from the serious to the surprisingly whimsical.
In their seminal work, Smith and Doe (2010) delve into the effects of industrial air pollution on local labor markets, offering a comprehensive analysis of the relationship between pollutant levels and employment patterns. Their findings highlight the far-reaching consequences of environmental degradation on occupational dynamics, laying the groundwork for subsequent research in this domain.
Jones et al. (2015) further illuminate the complex interplay between air quality and workforce trends, underscoring the need for a nuanced understanding of how environmental factors shape employment opportunities. Their study not only underscores the tangible impact of air pollution on labor market dynamics but also paves the way for exploring unconventional correlations that may challenge conventional wisdom.
While these scholarly contributions have undoubtedly enriched our understanding of the broader implications of air pollution, the literature also takes an unexpectedly humorous turn. In "Air Pollution and Occupational Oddities" by R. Witty (2018), the author offers a lighthearted exploration of the peculiar occupational shifts that coincide with changes in air quality. From the decline of chimney sweeps to the rise of air purifier salesmen, Witty's work humorously underscores the whimsical side of environmental influences on occupational trends.
Shifting gears to the literary world, works such as "Breathless in Weirton" by A. Novel (2005) and "Smoke Signals and Employment Markets" by F. Iction (2012) provide fictional narratives that tantalizingly hint at the intriguing connection between air pollution and occupational shifts. While these works may straddle the line between reality and whimsy, they serve as a reminder of the unexpected ways in which storytelling can mirror the curious nature of empirical research.
As the investigation delves deeper into the realm of unexpected connections, it would be remiss not to acknowledge the whimsical insights that emerge from unconventional sources. Cartoons such as "Captain Planet and the Planeteers" and children's shows like "The Magic School Bus" offer a delightful, albeit fictional, exploration of the environmental influences that transcend into the realm of the fantastical. While these lighthearted portrayals may diverge from scholarly rigor, they nevertheless offer a charming perspective on the intersection of environmental factors and societal dynamics.
In navigating the literature on air pollution and occupational trends, it becomes apparent that the unexpected relationship between air pollution in Weirton, West Virginia, and the decline of switchboard operators in the state is a topic that both challenges and amuses the scholarly mind. As the present study seeks to unravel this intriguing connection, it is clear that the journey promises to be as insightful as it is unexpectedly delightful.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between Air pollution in Weirton, West Virginia and The number of switchboard operators in West Virginia. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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]]
Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State
[[ABSTRACT]]
This paper investigates the unexpected relationship between air pollution levels in Weirton, West Virginia, and the number of switchboard operators in the entire state. By combining air quality data from the Environmental Protection Agency with employment statistics from the Bureau of Labor Statistics, our research team conducted a comprehensive analysis spanning the years 2003 to 2022. Our findings reveal a notable correlation coefficient of 0.8122729 and a p-value less than 0.01, demonstrating a significant association between air pollution levels in Weirton and the decline of switchboard operators in West Virginia. Our results suggest that, just like air pollution can clog up the atmosphere, it seems to have clogged the demand for switchboard operators in the state. This unexpected connection sheds light on the broader impact of environmental factors on labor markets and prompts further investigation into the potential consequences of air pollution on occupational trends.
[[INTRODUCTION]]
The study of unexpected connections in the realm of research is like playing a game of scientific connect-the-dots. Sometimes, when you least expect it, two seemingly unrelated variables can suddenly reveal a surprising link, leaving you to connect the dots between them. In this paper, we delve into the peculiar relationship between the level of air pollution in Weirton, West Virginia, and the dwindling numbers of switchboard operators across the entire state. It's a story of science and circumstance, where statistical analysis meets telecommunication trends in a way that is sure to dial up your interest.
Air pollution has long been the villain in the atmospheric tale – the unwelcome guest at the global environmental party. Meanwhile, switchboard operators, once the unsung heroes of communication, have been fading into obscurity faster than you can say "operator, can you connect me to a pun?" Yet, little did we know that these two seemingly disparate threads would weave together to form a tapestry of statistical curiosity.
As we embark on this scientific journey, it's important to acknowledge the quirks and curiosities that often come hand-in-hand with research endeavors. The thought of a swirl of air particles impacting the job market feels like a plot twist straight out of a quirky, niche comedy. However, as we dig deeper into the data, it becomes clear that this connection is no laughing matter. Well, at least not entirely.
So, join us as we traverse the statistical wilderness in search of the bridge between air pollution in Weirton, West Virginia, and the decline of switchboard operators across the state. It's a journey that promises to be as enlightening as it is unexpected, proving once again that in the world of research, truth is often stranger than fiction.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
This study employed a concoction of statistical and empirical methods to unravel the peculiar correlation between air pollution levels in Weirton, West Virginia, and the dwindling numbers of switchboard operators across West Virginia. Our data retrieval process was akin to embarking on a quest for buried treasure, with the Environmental Protection Agency (EPA) and Bureau of Labor Statistics (BLS) serving as our digital treasure maps.
To kick off our investigation, we combed through the EPA's air quality monitoring data from 2003 to 2022, seeking out the atmospheric musings of Weirton, West Virginia. We carefully selected pollutants such as fine particulate matter (PM2.5), ozone, sulfur dioxide, and nitrogen dioxide, encapsulating the mélange of airborne shenanigans peculiar to Weirton. This process was akin to peering through a microscope at a mishmash of airborne particles, attempting to discern a visual symphony amidst the chaos.
On the flip side, we delved into the realm of BLS employment statistics, meticulously perusing the occupational landscape of West Virginia for the humble switchboard operator. We peered through the dusty annals of employment data, tracing the gradual decline of switchboard operators amidst the cacophony of technological progress. We wanted to make sure our data collection process was as thorough as a squirrel's search for nuts in autumn – leaving no statistical acorn unturned.
Once we had amassed our troves of EPA air quality and BLS employment data, we donned our metaphorical lab coats and set about concocting complex statistical analyses. We dabbled in the wondrous world of correlation coefficients and regression analyses, seeking to unveil the patterns that tethered Weirton's air pollution to the statewide plight of switchboard operators. This phase was akin to mixing a scientific potion, hoping to unlock the secrets of the statistical cauldron.
In a bid to ensure the robustness of our findings, we also factored in various demographic and socioeconomic variables, akin to adding a dash of seasoning to a culinary masterpiece. We scrutinized factors such as population density, income levels, and technological advancements, aiming to distill the essence of Weirton's environmental influences and their impact on the telecommunication workforce.
Our statistical odyssey culminated in the examination of the correlation coefficient and p-values, serving as the grand reveal in our quest for the elusive link between air pollution and switchboard operator employment. With bated breath, we confronted the analytical tempest, seeking to unravel the enigmatic dance between Weirton's airborne intricacies and the state's telecommunication labor market.
In summary, our research utilized a blend of data excavation, statistical modeling, and analytical rigor to untangle the web of connections between air pollution in Weirton, West Virginia, and the diminishing numbers of switchboard operators across the state. This journey was equal parts scientific inquiry and statistical escapade, underscoring the unexpected twists and turns that await those who dare to venture into the realm of quirky research endeavors.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Weirton, West Virginia and The number of switchboard operators in West Virginia. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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 0.8122729, r-squared of 0.6597873, 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]]
Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State
[[ABSTRACT]]
This paper investigates the unexpected relationship between air pollution levels in Weirton, West Virginia, and the number of switchboard operators in the entire state. By combining air quality data from the Environmental Protection Agency with employment statistics from the Bureau of Labor Statistics, our research team conducted a comprehensive analysis spanning the years 2003 to 2022. Our findings reveal a notable correlation coefficient of 0.8122729 and a p-value less than 0.01, demonstrating a significant association between air pollution levels in Weirton and the decline of switchboard operators in West Virginia. Our results suggest that, just like air pollution can clog up the atmosphere, it seems to have clogged the demand for switchboard operators in the state. This unexpected connection sheds light on the broader impact of environmental factors on labor markets and prompts further investigation into the potential consequences of air pollution on occupational trends.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
The study of unexpected connections in the realm of research is like playing a game of scientific connect-the-dots. Sometimes, when you least expect it, two seemingly unrelated variables can suddenly reveal a surprising link, leaving you to connect the dots between them. In this paper, we delve into the peculiar relationship between the level of air pollution in Weirton, West Virginia, and the dwindling numbers of switchboard operators across the entire state. It's a story of science and circumstance, where statistical analysis meets telecommunication trends in a way that is sure to dial up your interest.
Air pollution has long been the villain in the atmospheric tale – the unwelcome guest at the global environmental party. Meanwhile, switchboard operators, once the unsung heroes of communication, have been fading into obscurity faster than you can say "operator, can you connect me to a pun?" Yet, little did we know that these two seemingly disparate threads would weave together to form a tapestry of statistical curiosity.
As we embark on this scientific journey, it's important to acknowledge the quirks and curiosities that often come hand-in-hand with research endeavors. The thought of a swirl of air particles impacting the job market feels like a plot twist straight out of a quirky, niche comedy. However, as we dig deeper into the data, it becomes clear that this connection is no laughing matter. Well, at least not entirely.
So, join us as we traverse the statistical wilderness in search of the bridge between air pollution in Weirton, West Virginia, and the decline of switchboard operators across the state. It's a journey that promises to be as enlightening as it is unexpected, proving once again that in the world of research, truth is often stranger than fiction.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The data analysis revealed a substantial correlation coefficient of 0.8122729 between air pollution levels in Weirton, West Virginia, and the number of switchboard operators in the state. This finding suggests a strong positive association between the two variables, indicating that as air pollution levels rise, the number of switchboard operators declines. It's like the air pollution was saying, "I'm sorry, the demand you are trying to connect doesn't exist anymore!"
Furthermore, the coefficient of determination (r-squared) of 0.6597873 indicates that approximately 66% of the variability in the number of switchboard operators can be explained by the variation in air pollution levels. That's a high percentage, indicating that air pollution has a significant impact on the decline of switchboard operators. It's as if air pollution is orchestrating a mass exodus of switchboard operators, leaving the communication lines a bit tangled.
The p-value of less than 0.01 suggests that the observed correlation is statistically significant, providing strong evidence to reject the null hypothesis that there is no relationship between air pollution and the number of switchboard operators. It's as if the statistics were shouting, "Hang up the idea that this is just a fluke – the connection is real!"
The scatterplot (Fig. 1) illustrates the robust positive correlation between air pollution levels in Weirton, West Virginia, and the declining number of switchboard operators in the state. It's a visual representation that echoes the strong statistical relationship between these two seemingly unrelated variables. It's like witnessing a cosmic dance between air pollution and occupational trends, with switchboard operators caught in the middle of an atmospheric tango.
In conclusion, our research has unveiled an unforeseen link between air pollution levels in Weirton and the decline of switchboard operators in West Virginia. The findings highlight the broader impact of environmental factors on labor markets and underscore the need for further exploration into the consequences of air pollution on occupational trends. As researchers, we are constantly reminded that the world of statistics is full of surprises, and this unexpected connection between air pollution and switchboard operators is certainly a testament to that!
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Weirton, West Virginia and The number of switchboard operators in West Virginia. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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]]
Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State
[[ABSTRACT]]
This paper investigates the unexpected relationship between air pollution levels in Weirton, West Virginia, and the number of switchboard operators in the entire state. By combining air quality data from the Environmental Protection Agency with employment statistics from the Bureau of Labor Statistics, our research team conducted a comprehensive analysis spanning the years 2003 to 2022. Our findings reveal a notable correlation coefficient of 0.8122729 and a p-value less than 0.01, demonstrating a significant association between air pollution levels in Weirton and the decline of switchboard operators in West Virginia. Our results suggest that, just like air pollution can clog up the atmosphere, it seems to have clogged the demand for switchboard operators in the state. This unexpected connection sheds light on the broader impact of environmental factors on labor markets and prompts further investigation into the potential consequences of air pollution on occupational trends.
[[LITERATURE REVIEW]]
The interplay between environmental factors and labor market trends has long been a source of fascination among researchers. The unexpected connections that emerge from such investigations often challenge conventional wisdom and provoke a sense of scholarly curiosity. In the realm of air pollution and its impact on occupational trends, the literature provides a range of insights, from the serious to the surprisingly whimsical.
In their seminal work, Smith and Doe (2010) delve into the effects of industrial air pollution on local labor markets, offering a comprehensive analysis of the relationship between pollutant levels and employment patterns. Their findings highlight the far-reaching consequences of environmental degradation on occupational dynamics, laying the groundwork for subsequent research in this domain.
Jones et al. (2015) further illuminate the complex interplay between air quality and workforce trends, underscoring the need for a nuanced understanding of how environmental factors shape employment opportunities. Their study not only underscores the tangible impact of air pollution on labor market dynamics but also paves the way for exploring unconventional correlations that may challenge conventional wisdom.
While these scholarly contributions have undoubtedly enriched our understanding of the broader implications of air pollution, the literature also takes an unexpectedly humorous turn. In "Air Pollution and Occupational Oddities" by R. Witty (2018), the author offers a lighthearted exploration of the peculiar occupational shifts that coincide with changes in air quality. From the decline of chimney sweeps to the rise of air purifier salesmen, Witty's work humorously underscores the whimsical side of environmental influences on occupational trends.
Shifting gears to the literary world, works such as "Breathless in Weirton" by A. Novel (2005) and "Smoke Signals and Employment Markets" by F. Iction (2012) provide fictional narratives that tantalizingly hint at the intriguing connection between air pollution and occupational shifts. While these works may straddle the line between reality and whimsy, they serve as a reminder of the unexpected ways in which storytelling can mirror the curious nature of empirical research.
As the investigation delves deeper into the realm of unexpected connections, it would be remiss not to acknowledge the whimsical insights that emerge from unconventional sources. Cartoons such as "Captain Planet and the Planeteers" and children's shows like "The Magic School Bus" offer a delightful, albeit fictional, exploration of the environmental influences that transcend into the realm of the fantastical. While these lighthearted portrayals may diverge from scholarly rigor, they nevertheless offer a charming perspective on the intersection of environmental factors and societal dynamics.
In navigating the literature on air pollution and occupational trends, it becomes apparent that the unexpected relationship between air pollution in Weirton, West Virginia, and the decline of switchboard operators in the state is a topic that both challenges and amuses the scholarly mind. As the present study seeks to unravel this intriguing connection, it is clear that the journey promises to be as insightful as it is unexpectedly delightful.
[[RESULTS]]
The data analysis revealed a substantial correlation coefficient of 0.8122729 between air pollution levels in Weirton, West Virginia, and the number of switchboard operators in the state. This finding suggests a strong positive association between the two variables, indicating that as air pollution levels rise, the number of switchboard operators declines. It's like the air pollution was saying, "I'm sorry, the demand you are trying to connect doesn't exist anymore!"
Furthermore, the coefficient of determination (r-squared) of 0.6597873 indicates that approximately 66% of the variability in the number of switchboard operators can be explained by the variation in air pollution levels. That's a high percentage, indicating that air pollution has a significant impact on the decline of switchboard operators. It's as if air pollution is orchestrating a mass exodus of switchboard operators, leaving the communication lines a bit tangled.
The p-value of less than 0.01 suggests that the observed correlation is statistically significant, providing strong evidence to reject the null hypothesis that there is no relationship between air pollution and the number of switchboard operators. It's as if the statistics were shouting, "Hang up the idea that this is just a fluke – the connection is real!"
The scatterplot (Fig. 1) illustrates the robust positive correlation between air pollution levels in Weirton, West Virginia, and the declining number of switchboard operators in the state. It's a visual representation that echoes the strong statistical relationship between these two seemingly unrelated variables. It's like witnessing a cosmic dance between air pollution and occupational trends, with switchboard operators caught in the middle of an atmospheric tango.
In conclusion, our research has unveiled an unforeseen link between air pollution levels in Weirton and the decline of switchboard operators in West Virginia. The findings highlight the broader impact of environmental factors on labor markets and underscore the need for further exploration into the consequences of air pollution on occupational trends. As researchers, we are constantly reminded that the world of statistics is full of surprises, and this unexpected connection between air pollution and switchboard operators is certainly a testament to that!
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The results of our study unearth a striking correlation between air pollution levels in Weirton, West Virginia, and the diminishing number of switchboard operators in the state. The substantial correlation coefficient of 0.8122729, along with a p-value of less than 0.01, solidly corroborates the unanticipated relationship between these seemingly unrelated variables. It's as if we stumbled upon the unlikely duo of a devious smog and a vanishing act in the world of occupational dynamics.
Our findings align with prior research that delved into the multifaceted interplay between environmental factors and employment trends. Smith and Doe's (2010) comprehensive analysis of industrial air pollution's impact on local labor markets set the stage for our investigation, and it seems that we've now added another layer to the intricate tapestry of environmental influences on occupational landscapes. It's like our study is the unexpected plot twist in a series of scholarly narratives – a true page-turner in the academic saga of peculiar correlations.
Building on the surprisingly whimsical insights from R. Witty's (2018) "Air Pollution and Occupational Oddities," our work corroborates the notion that environmental influences can precipitate unexpected occupational shifts. Much like a whimsical science experiment gone awry, the correlation between air pollution and the decline of switchboard operators in West Virginia has injected a sense of intrigue into the empirical exploration of labor market dynamics. It's as if Mother Nature is playing a game of occupational musical chairs, and the switchboard operators are left scrambling for a seat when the music stops.
The resounding statistical significance of our findings mirrors the tangible impact of air pollution on the labor market, emphasizing the need for a nuanced understanding of environmental influences on occupational trends. Our study adds a whimsical yet robust dimension to the scholarly discourse on environmental factors and societal dynamics, akin to stumbling upon a valuable nugget of insight in a field of statistical haystacks.
In a nutshell, our research offers more than just a statistical lens – it presents a captivating narrative of an unforeseen connection between air pollution and the occupation of switchboard operators. As we venture further into this unexpected territory, the journey promises to be as enlightening as it is unexpectedly delightful. It's like our study has upgraded from a dry science paper to a whimsical statistical odyssey, where the variables take on a life of their own and lead us on a merry dance through the enigmatic realm of empirical research.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Weirton, West Virginia and The number of switchboard operators in West Virginia. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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]]
Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State
[[ABSTRACT]]
This paper investigates the unexpected relationship between air pollution levels in Weirton, West Virginia, and the number of switchboard operators in the entire state. By combining air quality data from the Environmental Protection Agency with employment statistics from the Bureau of Labor Statistics, our research team conducted a comprehensive analysis spanning the years 2003 to 2022. Our findings reveal a notable correlation coefficient of 0.8122729 and a p-value less than 0.01, demonstrating a significant association between air pollution levels in Weirton and the decline of switchboard operators in West Virginia. Our results suggest that, just like air pollution can clog up the atmosphere, it seems to have clogged the demand for switchboard operators in the state. This unexpected connection sheds light on the broader impact of environmental factors on labor markets and prompts further investigation into the potential consequences of air pollution on occupational trends.
[[INTRDUCTION]]
The study of unexpected connections in the realm of research is like playing a game of scientific connect-the-dots. Sometimes, when you least expect it, two seemingly unrelated variables can suddenly reveal a surprising link, leaving you to connect the dots between them. In this paper, we delve into the peculiar relationship between the level of air pollution in Weirton, West Virginia, and the dwindling numbers of switchboard operators across the entire state. It's a story of science and circumstance, where statistical analysis meets telecommunication trends in a way that is sure to dial up your interest.
Air pollution has long been the villain in the atmospheric tale – the unwelcome guest at the global environmental party. Meanwhile, switchboard operators, once the unsung heroes of communication, have been fading into obscurity faster than you can say "operator, can you connect me to a pun?" Yet, little did we know that these two seemingly disparate threads would weave together to form a tapestry of statistical curiosity.
As we embark on this scientific journey, it's important to acknowledge the quirks and curiosities that often come hand-in-hand with research endeavors. The thought of a swirl of air particles impacting the job market feels like a plot twist straight out of a quirky, niche comedy. However, as we dig deeper into the data, it becomes clear that this connection is no laughing matter. Well, at least not entirely.
So, join us as we traverse the statistical wilderness in search of the bridge between air pollution in Weirton, West Virginia, and the decline of switchboard operators across the state. It's a journey that promises to be as enlightening as it is unexpected, proving once again that in the world of research, truth is often stranger than fiction.
[[RESULTS]]
The data analysis revealed a substantial correlation coefficient of 0.8122729 between air pollution levels in Weirton, West Virginia, and the number of switchboard operators in the state. This finding suggests a strong positive association between the two variables, indicating that as air pollution levels rise, the number of switchboard operators declines. It's like the air pollution was saying, "I'm sorry, the demand you are trying to connect doesn't exist anymore!"
Furthermore, the coefficient of determination (r-squared) of 0.6597873 indicates that approximately 66% of the variability in the number of switchboard operators can be explained by the variation in air pollution levels. That's a high percentage, indicating that air pollution has a significant impact on the decline of switchboard operators. It's as if air pollution is orchestrating a mass exodus of switchboard operators, leaving the communication lines a bit tangled.
The p-value of less than 0.01 suggests that the observed correlation is statistically significant, providing strong evidence to reject the null hypothesis that there is no relationship between air pollution and the number of switchboard operators. It's as if the statistics were shouting, "Hang up the idea that this is just a fluke – the connection is real!"
The scatterplot (Fig. 1) illustrates the robust positive correlation between air pollution levels in Weirton, West Virginia, and the declining number of switchboard operators in the state. It's a visual representation that echoes the strong statistical relationship between these two seemingly unrelated variables. It's like witnessing a cosmic dance between air pollution and occupational trends, with switchboard operators caught in the middle of an atmospheric tango.
In conclusion, our research has unveiled an unforeseen link between air pollution levels in Weirton and the decline of switchboard operators in West Virginia. The findings highlight the broader impact of environmental factors on labor markets and underscore the need for further exploration into the consequences of air pollution on occupational trends. As researchers, we are constantly reminded that the world of statistics is full of surprises, and this unexpected connection between air pollution and switchboard operators is certainly a testament to that!
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In wrapping up this quirky journey through the statistical wilderness, we can't help but marvel at the surprising link we've uncovered between air pollution in Weirton, West Virginia, and the decline of switchboard operators in the state. It's as though the air pollution was playing a game of "operator, operator, who's leaving the job now?" and the switchboard operators were dialing out of the industry faster than a rapid redial.
This unexpected connection has certainly dialed up our curiosity, leaving us pondering the cosmic dance between atmospheric pollutants and occupational trends. It seems that air pollution wasn't content with simply clouding the skies; it also decided to influence the labor market, weaving a tale of statistical intrigue that even the most seasoned researcher couldn't have predicted.
As we reflect on the robust correlation coefficient and the statistically significant p-value, it's clear that this finding isn't just a statistical blip on the radar. With an r-squared value of approximately 66%, it's as if the air pollution saw the switchboard operators and decided to "connect" with them in a way nobody saw coming.
The scatterplot, our visual aid in this tale of statistical zaniness, serves as a testament to the undeniable relationship between these two seemingly unrelated variables. The air pollution and switchboard operators are engaged in a telecommunication tango more intricate than any quantum entanglement, leaving us to marvel at the twists and turns of the statistical universe.
In the grand finale of our scientific sitcom, we can confidently conclude that the connection between air pollution and the decline of switchboard operators in West Virginia is as real as it is unexpected. At this point, it's clear that further research ventures in this particular area may leave us all reaching for the punny 'hang up,' as we've already 'connected' the dots in a way that's left us all laughing in statistical astonishment. It's time to let this research call it a wrap and hang up our lab coats in this area of 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 Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Unlikely Correlations
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 Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State. Respond only with the name of a fictional organization.
ChatGPT:
The Society for Unconventional Research and Scientific Eccentricities (SURSE)
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 Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State with an abstract of This paper investigates the unexpected relationship between air pollution levels in Weirton, West Virginia, and the number of switchboard operators in the entire state. By combining air quality data from the Environmental Protection Agency with employment statistics from the Bureau of Labor Statistics, our research team conducted a comprehensive analysis spanning the years 2003 to 2022. Our findings reveal a notable correlation coefficient of 0.8122729 and a p-value less than 0.01, demonstrating a significant association between air pollution levels in Weirton and the decline of switchboard operators in West Virginia. Our results suggest that, just like air pollution can clog up the atmosphere, it seems to have clogged the demand for switchboard operators in the state. This unexpected connection sheds light on the broader impact of environmental factors on labor markets and prompts further investigation into the potential consequences of air pollution on occupational trends.
ChatGPT:
air pollution, Weirton, West Virginia, switchboard operators, decline, correlation coefficient, p-value, environmental impact, labor markets, occupational trends, air quality data, employment statistics, Bureau of Labor Statistics, Environmental Protection Agency
*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 Weirton, West VirginiaDetailed data title: Percentage of days 'unhealthy' or worse air quality in Weirton-Steubenville, WV-OH
Source: Environmental Protection Agency
See what else correlates with Air pollution in Weirton, West Virginia
The number of switchboard operators in West Virginia
Detailed data title: BLS estimate of switchboard operators, including answering service in West Virginia
Source: Bureau of Larbor Statistics
See what else correlates with The number of switchboard operators in West Virginia
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 = 0.6597873 (Coefficient of determination)
This means 66% of the change in the one variable (i.e., The number of switchboard operators in West Virginia) is predictable based on the change in the other (i.e., Air pollution in Weirton, West Virginia) over the 20 years from 2003 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.4E-5. 0.0000136055004767688480000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.
But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.
Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.81 in 0.0014% of random cases. Said differently, if you correlated 73,500 random variables You don't actually need 73 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.
[ 0.58, 0.92 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | |
Air pollution in Weirton, West Virginia (Bad air quality days) | 1.09589 | 0.546448 | 1.09589 | 0.273973 | 0 | 0 | 0.273973 | 0.273973 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.273973 | 0 |
The number of switchboard operators in West Virginia (Laborers) | 1200 | 1250 | 1190 | 970 | 710 | 590 | 580 | 560 | 570 | 550 | 510 | 490 | 410 | 430 | 380 | 390 | 350 | 310 | 260 | 260 |
Why this works
- Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
- 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. - Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple
Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.Step 2: Open a plaintext editor like Notepad and paste the code below into it.
Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"
Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.
Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.
Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.
Step 7: Run the Python script by typing "python calculate_correlation.py"
If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:
"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."
# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats
# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):
# Calculate Pearson correlation coefficient and p-value
correlation, p_value = stats.pearsonr(array1, array2)
# Calculate R-squared as the square of the correlation coefficient
r_squared = correlation**2
return correlation, r_squared, p_value
# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([1.09589,0.546448,1.09589,0.273973,0,0,0.273973,0.273973,0,0,0,0,0,0,0,0,0,0,0.273973,0,])
array_2 = np.array([1200,1250,1190,970,710,590,580,560,570,550,510,490,410,430,380,390,350,310,260,260,])
array_1_name = "Air pollution in Weirton, West Virginia"
array_2_name = "The number of switchboard operators in West Virginia"
# 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. 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.
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Download images for these variables:
- High resolution line chart
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 pollution in Weirton, West Virginia
- Line chart for only The number of switchboard operators in West Virginia
- AI-generated correlation image
- The spurious research paper: Dialing in on the Polluted Connection: Air Pollution in Weirton, West Virginia and the Decline of Switchboard Operators in the State
I'm grateful for your review!
Correlation ID: 5391 · Black Variable ID: 21429 · Red Variable ID: 16039