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Spurious correlation #4,273 · 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 Sonora, California and the second variable is Total annual sales of Ford Motors in the United States.  The chart goes from 1999 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the air in Sonora got cleaner, people no longer felt the need to escape in their Fords, leading to a nationwide decrease in Ford sales. It's like the cars lost their appeal without the smoggy, cinematic backdrop.

Model: dalle-3
Prompt: Generate an image of a serene Sonora, California landscape with a prominent Ford dealership in the background. Show a clear sky with the beauty of the landscape, but also depict fewer people driving cars and the decline in Ford Motors' sales, possibly by showing empty parking lots or cars being left to gather dust. The setting should convey a sense of calm and beauty in contrast to the declining trend in car sales and usage. 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 Sonora, California and Total annual sales of Ford Motors in the United States. 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: Futuristic inspired by bauhaus A Discovery magazine cover image Parallax art Vaporwave
ChatGPT: A Discovery magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Sonora, California and Total annual sales of Ford Motors in the United States, in the following situation: As the air in Sonora got cleaner, people no longer felt the need to escape in their Fords, leading to a nationwide decrease in Ford sales. It's like the cars lost their appeal without the smoggy, cinematic backdrop.. Keep the description simple.
ChatGPT: In Sonora, California, the sky clears as the air becomes fresher, giving way to a serene view of the landscape. However, in the United States, the annual sales of Ford Motors decline noticeably, with fewer people seen driving their cars.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A Discovery magazine cover image ] and depicting this scene: In Sonora, California, the sky clears as the air becomes fresher, giving way to a serene view of the landscape. However, in the United States, the annual sales of Ford Motors decline noticeably, with fewer people seen driving their cars. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a serene Sonora, California landscape with a prominent Ford dealership in the background. Show a clear sky with the beauty of the landscape, but also depict fewer people driving cars and the decline in Ford Motors' sales, possibly by showing empty parking lots or cars being left to gather dust. The setting should convey a sense of calm and beauty in contrast to the declining trend in car sales and usage.

*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 Sonora, California caused Total annual sales of Ford Motors in the United States to decrease. Make it feel plausible.

AI academic paper

(Because p < 0.01)
Clearing the Air: Examining the Impact of Air Pollution in Sonora, California on Ford Motor's Sales in the United States

Journal of Environmental Economics and Corporate Performance

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 Sonora, California and Total annual sales of Ford Motors in the United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title a clever pun.

Your research team used data from Environmental Protection Agency and Wikipedia to assess this nagging question. You found a correlation coefficient of 0.8041542 and p < 0.01 for 1999 to 2021.

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]]
"Clearing the Air: Examining the Impact of Air Pollution in Sonora, California on Ford Motor's Sales in the United States"

[[ABSTRACT]]
This study delves into the often-overlooked relationship between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. While the topic may seem flighty at first glance, our rigorous analysis of data from the Environmental Protection Agency and Wikipedia has revealed a surprisingly strong correlation. With a correlation coefficient of 0.8041542 and p < 0.01 for the years 1999 to 2021, the evidence of an association between these seemingly unrelated phenomena is hard to brush off. It appears that the pollutant particles may not just cloud the horizon, but also have an impact on the sales figures of Ford vehicles. However, before we jump to any hasty conclusions, further investigation is needed to discern the precise mechanisms at play and to avoid getting "exhaust"ed by this curious relationship.


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 Sonora, California and Total annual sales of Ford Motors in the United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Clearing the Air: Examining the Impact of Air Pollution in Sonora, California on Ford Motor's Sales in the United States"

[[ABSTRACT]]
This study delves into the often-overlooked relationship between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. While the topic may seem flighty at first glance, our rigorous analysis of data from the Environmental Protection Agency and Wikipedia has revealed a surprisingly strong correlation. With a correlation coefficient of 0.8041542 and p < 0.01 for the years 1999 to 2021, the evidence of an association between these seemingly unrelated phenomena is hard to brush off. It appears that the pollutant particles may not just cloud the horizon, but also have an impact on the sales figures of Ford vehicles. However, before we jump to any hasty conclusions, further investigation is needed to discern the precise mechanisms at play and to avoid getting "exhaust"ed by this curious relationship.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

As we traverse the intricate landscape of environmental influence on consumer behavior, a peculiar link has emerged between the hazy atmospheres of Sonora, California, and the soaring or plummeting sales figures of Ford Motors in the United States. The notion that air pollution could hold sway over the purchasing decisions of automotive enthusiasts may seem like a "wild exhaust" of the imagination, but science often thrives on uncovering improbable connections. This study aims to unravel the enigmatic relationship between these divergent variables, employing the quintessential tools of statistical analysis and empirical observation to discern any lurking patterns in the nebulous expanse of data.

The impetus behind this investigation was not merely a whimsical curiosity, but rather a genuine attempt to fathom the unseen currents that guide consumer preferences. It is an endeavor that, much like traversing through smog-filled avenues, necessitates a keen eye to discern the obscured signals amidst the environmental noise. Delving into the annals of scientific research, we unearthed a trove of statistics and historical records that would make even the most seasoned data miner salivate with delight. Our research hypothesis took flight, soaring through the clouds of uncertainty to uncover the potential links between the particulate matter of Sonora's air and the annual sales figures of Ford Motors.

Throughout this investigation, we must tread cautiously, navigating the treacherous terrain of speculation while remaining firmly anchored in the bedrock of empirical evidence. Although the correlation coefficient has "skyrocketed" to a notable 0.8041542, and our p-value swoops low, our prudence dictates that we remain vigilant against the perils of unwarranted assumptions. The potential influence of air pollution on the sales figures cannot be simply "filtered" out based on this correlation alone, and as diligent researchers, we must acknowledge the need for deeper understanding before we "vent"ure into conclusive claims.

In the ensuing sections, we will embark on an odyssey through the smog-choked highways of Sonora and the boardrooms of Ford Motors, unraveling the intricate tapestry of causation and correlation. As we journey through this web of statistical significance, let us remain steadfast in our pursuit of scientific truth, never "tire-d" by the complexities of our endeavor.


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 Sonora, California and Total annual sales of Ford Motors in the United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then 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]]
"Clearing the Air: Examining the Impact of Air Pollution in Sonora, California on Ford Motor's Sales in the United States"

[[ABSTRACT]]
This study delves into the often-overlooked relationship between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. While the topic may seem flighty at first glance, our rigorous analysis of data from the Environmental Protection Agency and Wikipedia has revealed a surprisingly strong correlation. With a correlation coefficient of 0.8041542 and p < 0.01 for the years 1999 to 2021, the evidence of an association between these seemingly unrelated phenomena is hard to brush off. It appears that the pollutant particles may not just cloud the horizon, but also have an impact on the sales figures of Ford vehicles. However, before we jump to any hasty conclusions, further investigation is needed to discern the precise mechanisms at play and to avoid getting "exhaust"ed by this curious relationship.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As we traverse the intricate landscape of environmental influence on consumer behavior, a peculiar link has emerged between the hazy atmospheres of Sonora, California, and the soaring or plummeting sales figures of Ford Motors in the United States. The notion that air pollution could hold sway over the purchasing decisions of automotive enthusiasts may seem like a "wild exhaust" of the imagination, but science often thrives on uncovering improbable connections. This study aims to unravel the enigmatic relationship between these divergent variables, employing the quintessential tools of statistical analysis and empirical observation to discern any lurking patterns in the nebulous expanse of data.
The impetus behind this investigation was not merely a whimsical curiosity, but rather a genuine attempt to fathom the unseen currents that guide consumer preferences. It is an endeavor that, much like traversing through smog-filled avenues, necessitates a keen eye to discern the obscured signals amidst the environmental noise. Delving into the annals of scientific research, we unearthed a trove of statistics and historical records that would make even the most seasoned data miner salivate with delight. Our research hypothesis took flight, soaring through the clouds of uncertainty to uncover the potential links between the particulate matter of Sonora's air and the annual sales figures of Ford Motors.
Throughout this investigation, we must tread cautiously, navigating the treacherous terrain of speculation while remaining firmly anchored in the bedrock of empirical evidence. Although the correlation coefficient has "skyrocketed" to a notable 0.8041542, and our p-value swoops low, our prudence dictates that we remain vigilant against the perils of unwarranted assumptions. The potential influence of air pollution on the sales figures cannot be simply "filtered" out based on this correlation alone, and as diligent researchers, we must acknowledge the need for deeper understanding before we "vent"ure into conclusive claims.
In the ensuing sections, we will embark on an odyssey through the smog-choked highways of Sonora and the boardrooms of Ford Motors, unraveling the intricate tapestry of causation and correlation. As we journey through this web of statistical significance, let us remain steadfast in our pursuit of scientific truth, never "tire-d" by the complexities of our endeavor.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

As we delve into the murky depths of research exploring the puzzling link between air pollution in Sonora, California, and the annual sales of Ford Motors in the United States, we must first acknowledge the scholarly foundation upon which this study is built. Smith's groundbreaking work, "Atmospheric Effects on Consumer Behavior," initially sparked this line of inquiry. Smith's thorough analysis of environmental factors and their impact on purchasing decisions provided a solid groundwork for our investigation. Seemingly unrelated, Doe's study, "The Economics of Air Quality," unexpectedly shed light on the potential socioeconomic implications of air pollution, prompting us to broaden our scope of inquiry.

As we traverse this intellectual terrain, it is essential to consider the broader literature on environmental impact and consumer behavior. Jones et al. ("The Invisible Hand of Smog: Unveiling the Unseen Influence") artfully navigate the complex interplay of atmospheric pollutants and consumer choices, underscoring the need for meticulous scrutiny when drawing correlations between a locality's air quality and national sales figures. Similarly, in "Clearing the Air: Economic Ramifications of Environmental Factors," Brown and Johnson expound upon the less tangible effects of air pollution on market performance, connecting the dots between environmental blight and economic vitality.

Venturing beyond the confines of academic literature, we can draw inspiration from non-fiction works such as "Breathless: The Environmental Crisis Unveiled" by Green and "Wheezing Through the Economic Chords" by Gray, which offer deeper insights into the intersection of environmental degradation and economic outcomes. The ominous clouds of pollution appear to cast a shadow over the narratives presented in these texts, urging readers to contemplate the gravity of these interconnected phenomena.

On a more whimsical note, fictional works such as "Smog City Slickers" by Lumbridge and "The Diesel Dilemma" by Crankshaft, though they may not bear directly on our research, prompt us to reflect on the cultural implications of automotive emissions and environmental degradation. While perhaps not traditional sources of academic insight, these literary pieces offer a unique perspective on the broader societal discourse surrounding our subject matter.

In the pursuit of a comprehensive understanding, it would be remiss not to acknowledge the unconventional wells of knowledge that have informed this research. Deviating from the conventional scholarly path, this investigation involved drawing on the insights of children's shows, such as "Captain Planet and the Planeteers" and "The Magic School Bus." These seemingly lighthearted sources provided unexpected nuggets of wisdom, aligning with our dedication to exploring every avenue, no matter how unconventional, in our quest for enlightenment.

Armed with a rich tapestry of academic, non-fiction, and even fictional sources, we embark on this journey with a fervent sense of curiosity tempered by methodological rigor. In the chapters that follow, we will unravel the enigmatic threads connecting Sonora's polluted skies and the sales fortunes of Ford Motors, plumbing the depths of data with a tenacity that could rival even the hardiest of environmental activists.


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 Sonora, California and Total annual sales of Ford Motors in the United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 Wikipedia . You used data from 1999 to 2021

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Clearing the Air: Examining the Impact of Air Pollution in Sonora, California on Ford Motor's Sales in the United States"

[[ABSTRACT]]
This study delves into the often-overlooked relationship between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. While the topic may seem flighty at first glance, our rigorous analysis of data from the Environmental Protection Agency and Wikipedia has revealed a surprisingly strong correlation. With a correlation coefficient of 0.8041542 and p < 0.01 for the years 1999 to 2021, the evidence of an association between these seemingly unrelated phenomena is hard to brush off. It appears that the pollutant particles may not just cloud the horizon, but also have an impact on the sales figures of Ford vehicles. However, before we jump to any hasty conclusions, further investigation is needed to discern the precise mechanisms at play and to avoid getting "exhaust"ed by this curious relationship.

[[INTRODUCTION]]
As we traverse the intricate landscape of environmental influence on consumer behavior, a peculiar link has emerged between the hazy atmospheres of Sonora, California, and the soaring or plummeting sales figures of Ford Motors in the United States. The notion that air pollution could hold sway over the purchasing decisions of automotive enthusiasts may seem like a "wild exhaust" of the imagination, but science often thrives on uncovering improbable connections. This study aims to unravel the enigmatic relationship between these divergent variables, employing the quintessential tools of statistical analysis and empirical observation to discern any lurking patterns in the nebulous expanse of data.
The impetus behind this investigation was not merely a whimsical curiosity, but rather a genuine attempt to fathom the unseen currents that guide consumer preferences. It is an endeavor that, much like traversing through smog-filled avenues, necessitates a keen eye to discern the obscured signals amidst the environmental noise. Delving into the annals of scientific research, we unearthed a trove of statistics and historical records that would make even the most seasoned data miner salivate with delight. Our research hypothesis took flight, soaring through the clouds of uncertainty to uncover the potential links between the particulate matter of Sonora's air and the annual sales figures of Ford Motors.
Throughout this investigation, we must tread cautiously, navigating the treacherous terrain of speculation while remaining firmly anchored in the bedrock of empirical evidence. Although the correlation coefficient has "skyrocketed" to a notable 0.8041542, and our p-value swoops low, our prudence dictates that we remain vigilant against the perils of unwarranted assumptions. The potential influence of air pollution on the sales figures cannot be simply "filtered" out based on this correlation alone, and as diligent researchers, we must acknowledge the need for deeper understanding before we "vent"ure into conclusive claims.
In the ensuing sections, we will embark on an odyssey through the smog-choked highways of Sonora and the boardrooms of Ford Motors, unraveling the intricate tapestry of causation and correlation. As we journey through this web of statistical significance, let us remain steadfast in our pursuit of scientific truth, never "tire-d" by the complexities of our endeavor.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

In this study, we employed a multifaceted approach to disentangle the relationship between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. To gather pertinent data on air quality, we turned to the Environmental Protection Agency's (EPA) Air Quality System database, which provided a comprehensive source of information on ambient air pollutant levels in Sonora. Additionally, Wikipedia proved to be a valuable resource for historical sales data of Ford Motors spanning from 1999 to 2021.

Our methodology began with the meticulous collation and organization of data, akin to piecing together a complex jigsaw puzzle in a dense fog. We carefully selected a range of air pollutants, including particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3), to capture the full spectrum of the atmospheric milieu in Sonora. These variables, much like the disparate pieces of a scientific puzzle, were then scrutinized for patterns and interrelationships with sales figures.

Next, statistical analysis took center stage in our methodological repertoire. We performed a series of correlation analyses to assess the strength and direction of the relationship between air pollutant levels in Sonora and Ford Motors' annual sales. The Pearson correlation coefficient emerged as our lighthouse in the statistical haze, guiding us to a robust understanding of the association between these seemingly incongruous variables. Moreover, we conducted regression analyses to unearth potential predictive models that could illuminate the impact of air pollution on Ford Motors' sales dynamics.

An essential component of our methodology involved the consideration of confounding variables, which could potentially cloud the observed relationship. Economic indicators, such as fuel prices, GDP fluctuations, and industry-specific factors, were carefully weighed to ensure that the detected associations were not a mirage conjured by lurking extraneous influences.

It is important to note that, like any scientific endeavor, our methodology was not devoid of challenges. The voluminous nature of the dataset, coupled with the inherent complexity of environmental and economic variables, frequently posed formidable obstacles akin to navigating a labyrinthine maze. Nevertheless, we navigated these challenges with the unwavering resolve of intrepid explorers in pursuit of scientific enlightenment.

In summary, our methodology combined the robust navigation of data sources, the astute application of statistical analyses, and the meticulous consideration of potential confounders to unearth the buried relationship between air pollution in Sonora and the sales trajectory of Ford Motors.

It's crystal clear that this research endeavor was high-octane, chock-full of data "exhaust"ion, and astute statistical maneuvers. Our methodology, much like a hybrid vehicle, integrated multiple components to propel us forward, navigating through the convoluted pathways of research with precision and rigor. The "airtight" nature of our statistical analyses left no room for ambiguity, ensuring that our findings were firmly rooted in the bedrock of empirical evidence.


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 Sonora, California and Total annual sales of Ford Motors in the United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 Wikipedia .

For the time period 1999 to 2021, you found a correlation 0.8041542, r-squared of 0.6466639, 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]]
"Clearing the Air: Examining the Impact of Air Pollution in Sonora, California on Ford Motor's Sales in the United States"

[[ABSTRACT]]
This study delves into the often-overlooked relationship between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. While the topic may seem flighty at first glance, our rigorous analysis of data from the Environmental Protection Agency and Wikipedia has revealed a surprisingly strong correlation. With a correlation coefficient of 0.8041542 and p < 0.01 for the years 1999 to 2021, the evidence of an association between these seemingly unrelated phenomena is hard to brush off. It appears that the pollutant particles may not just cloud the horizon, but also have an impact on the sales figures of Ford vehicles. However, before we jump to any hasty conclusions, further investigation is needed to discern the precise mechanisms at play and to avoid getting "exhaust"ed by this curious relationship.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
As we traverse the intricate landscape of environmental influence on consumer behavior, a peculiar link has emerged between the hazy atmospheres of Sonora, California, and the soaring or plummeting sales figures of Ford Motors in the United States. The notion that air pollution could hold sway over the purchasing decisions of automotive enthusiasts may seem like a "wild exhaust" of the imagination, but science often thrives on uncovering improbable connections. This study aims to unravel the enigmatic relationship between these divergent variables, employing the quintessential tools of statistical analysis and empirical observation to discern any lurking patterns in the nebulous expanse of data.
The impetus behind this investigation was not merely a whimsical curiosity, but rather a genuine attempt to fathom the unseen currents that guide consumer preferences. It is an endeavor that, much like traversing through smog-filled avenues, necessitates a keen eye to discern the obscured signals amidst the environmental noise. Delving into the annals of scientific research, we unearthed a trove of statistics and historical records that would make even the most seasoned data miner salivate with delight. Our research hypothesis took flight, soaring through the clouds of uncertainty to uncover the potential links between the particulate matter of Sonora's air and the annual sales figures of Ford Motors.
Throughout this investigation, we must tread cautiously, navigating the treacherous terrain of speculation while remaining firmly anchored in the bedrock of empirical evidence. Although the correlation coefficient has "skyrocketed" to a notable 0.8041542, and our p-value swoops low, our prudence dictates that we remain vigilant against the perils of unwarranted assumptions. The potential influence of air pollution on the sales figures cannot be simply "filtered" out based on this correlation alone, and as diligent researchers, we must acknowledge the need for deeper understanding before we "vent"ure into conclusive claims.
In the ensuing sections, we will embark on an odyssey through the smog-choked highways of Sonora and the boardrooms of Ford Motors, unraveling the intricate tapestry of causation and correlation. As we journey through this web of statistical significance, let us remain steadfast in our pursuit of scientific truth, never "tire-d" by the complexities of our endeavor.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our analysis leave little room for doubt regarding the curious connection between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. Our rigorous examination of the data from 1999 to 2021 yielded a correlation coefficient of 0.8041542, an r-squared value of 0.6466639, and a p-value of less than 0.01. In human terms: there is a strong relationship between these variables, and it's not just a fluke!

Fig. 1 provides a visual representation of the relationship between air pollution in Sonora and Ford Motors' sales. The scatterplot reveals a striking pattern that would make any statistician's heart race. The data points are not just scattered randomly across the plot like debris in the wind; they form a discernible pattern, akin to the orderly march of vehicles on a congested highway.

In light of these findings, it seems that the quality of the air in Sonora may have a "direct drive" effect on the total annual sales figures of Ford Motors in the United States, contrary to popular belief. The air pollution in Sonora, California, perhaps, creates such a "fuel odor" that it impacts the purchasing decisions of consumers across the nation. However, let's not "race" to conclusions just yet. We must shift gears and modestly acknowledge that correlation does not imply causation, and further investigation is necessary to unveil the behind-the-scenes machinations of this surprising relationship. After all, we don't want to "exhaust" ourselves prematurely.

These results challenge the conventional wisdom and warrant a more comprehensive exploration of the potential mechanisms underpinning this unexpected association. We must peel back the layers of this correlation like the layers of an onion, taking care not to shed tears of confusion in the process. While our findings may seem like a serendipitous discovery, we must embrace the scientific ethos of skepticism and inquiry as we navigate the territory of unanticipated connections.


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 Sonora, California and Total annual sales of Ford Motors in the United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Clearing the Air: Examining the Impact of Air Pollution in Sonora, California on Ford Motor's Sales in the United States"

[[ABSTRACT]]
This study delves into the often-overlooked relationship between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. While the topic may seem flighty at first glance, our rigorous analysis of data from the Environmental Protection Agency and Wikipedia has revealed a surprisingly strong correlation. With a correlation coefficient of 0.8041542 and p < 0.01 for the years 1999 to 2021, the evidence of an association between these seemingly unrelated phenomena is hard to brush off. It appears that the pollutant particles may not just cloud the horizon, but also have an impact on the sales figures of Ford vehicles. However, before we jump to any hasty conclusions, further investigation is needed to discern the precise mechanisms at play and to avoid getting "exhaust"ed by this curious relationship.

[[LITERATURE REVIEW]]
As we delve into the murky depths of research exploring the puzzling link between air pollution in Sonora, California, and the annual sales of Ford Motors in the United States, we must first acknowledge the scholarly foundation upon which this study is built. Smith's groundbreaking work, "Atmospheric Effects on Consumer Behavior," initially sparked this line of inquiry. Smith's thorough analysis of environmental factors and their impact on purchasing decisions provided a solid groundwork for our investigation. Seemingly unrelated, Doe's study, "The Economics of Air Quality," unexpectedly shed light on the potential socioeconomic implications of air pollution, prompting us to broaden our scope of inquiry.
As we traverse this intellectual terrain, it is essential to consider the broader literature on environmental impact and consumer behavior. Jones et al. ("The Invisible Hand of Smog: Unveiling the Unseen Influence") artfully navigate the complex interplay of atmospheric pollutants and consumer choices, underscoring the need for meticulous scrutiny when drawing correlations between a locality's air quality and national sales figures. Similarly, in "Clearing the Air: Economic Ramifications of Environmental Factors," Brown and Johnson expound upon the less tangible effects of air pollution on market performance, connecting the dots between environmental blight and economic vitality.
Venturing beyond the confines of academic literature, we can draw inspiration from non-fiction works such as "Breathless: The Environmental Crisis Unveiled" by Green and "Wheezing Through the Economic Chords" by Gray, which offer deeper insights into the intersection of environmental degradation and economic outcomes. The ominous clouds of pollution appear to cast a shadow over the narratives presented in these texts, urging readers to contemplate the gravity of these interconnected phenomena.
On a more whimsical note, fictional works such as "Smog City Slickers" by Lumbridge and "The Diesel Dilemma" by Crankshaft, though they may not bear directly on our research, prompt us to reflect on the cultural implications of automotive emissions and environmental degradation. While perhaps not traditional sources of academic insight, these literary pieces offer a unique perspective on the broader societal discourse surrounding our subject matter.
In the pursuit of a comprehensive understanding, it would be remiss not to acknowledge the unconventional wells of knowledge that have informed this research. Deviating from the conventional scholarly path, this investigation involved drawing on the insights of children's shows, such as "Captain Planet and the Planeteers" and "The Magic School Bus." These seemingly lighthearted sources provided unexpected nuggets of wisdom, aligning with our dedication to exploring every avenue, no matter how unconventional, in our quest for enlightenment.
Armed with a rich tapestry of academic, non-fiction, and even fictional sources, we embark on this journey with a fervent sense of curiosity tempered by methodological rigor. In the chapters that follow, we will unravel the enigmatic threads connecting Sonora's polluted skies and the sales fortunes of Ford Motors, plumbing the depths of data with a tenacity that could rival even the hardiest of environmental activists.

[[RESULTS]]
The results of our analysis leave little room for doubt regarding the curious connection between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. Our rigorous examination of the data from 1999 to 2021 yielded a correlation coefficient of 0.8041542, an r-squared value of 0.6466639, and a p-value of less than 0.01. In human terms: there is a strong relationship between these variables, and it's not just a fluke!
Fig. 1 provides a visual representation of the relationship between air pollution in Sonora and Ford Motors' sales. The scatterplot reveals a striking pattern that would make any statistician's heart race. The data points are not just scattered randomly across the plot like debris in the wind; they form a discernible pattern, akin to the orderly march of vehicles on a congested highway.
In light of these findings, it seems that the quality of the air in Sonora may have a "direct drive" effect on the total annual sales figures of Ford Motors in the United States, contrary to popular belief. The air pollution in Sonora, California, perhaps, creates such a "fuel odor" that it impacts the purchasing decisions of consumers across the nation. However, let's not "race" to conclusions just yet. We must shift gears and modestly acknowledge that correlation does not imply causation, and further investigation is necessary to unveil the behind-the-scenes machinations of this surprising relationship. After all, we don't want to "exhaust" ourselves prematurely.
These results challenge the conventional wisdom and warrant a more comprehensive exploration of the potential mechanisms underpinning this unexpected association. We must peel back the layers of this correlation like the layers of an onion, taking care not to shed tears of confusion in the process. While our findings may seem like a serendipitous discovery, we must embrace the scientific ethos of skepticism and inquiry as we navigate the territory of unanticipated connections.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our study has unraveled a hitherto unnoticed connection between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. Our findings stand as a testament to the unexpected intertwining of seemingly disparate variables, reminiscent of the intricate dance of electrons around a nucleus or the interplay of supply and demand in a free market economy. The correlation coefficient of 0.8041542 between air pollution levels and Ford Motors' sales figures is not a mere mirage; it is a tangible thread weaving through the tapestry of commerce and environmental impact. Our results not only echo the assertions of prior research by Smith, Doe, Jones et al., and Brown and Johnson, but they also echo the distant echoes of "The Invisible Hand of Smog," "Clearing the Air," and "Wheezing Through the Economic Chords" in an eerie harmony.

As we reflect on the implications of our findings, we are compelled to acknowledge the crowds of confounding variables jostling for attention, clamoring for recognition like commuters in rush hour traffic. It is imperative to resist the temptation to leap to conclusions and remain mindful of the intricate nuances that underpin statistical associations. Even as this study presents a compelling case, caution must be exercised in attributing causality to the observed relationship, lest we find ourselves stranded in the thick fog of erroneous assumptions.

Furthermore, the challenges inherent in disentangling causation from correlation are akin to navigating a labyrinthine maze, where each step must be taken with measured consideration to avoid stumbling into dead-ends or, worse still, into the snare of spurious inferences. Thus, while our findings paint an intriguing portrait of the interplay between atmospheric pollution and economic performance, the canvas remains incomplete without the brushstrokes of further research to render a comprehensive understanding. Only then can we truly appreciate the intricate fusion of ambient air quality and commercial endeavors, akin to the melding of salt and caramel in a delectable confectionary.

In light of the substantial evidence brought to bear by our analyses, it is clear that the relationship between air pollution in Sonora, California, and Ford Motors' sales in the United States is not an ephemeral wisp of statistical noise, but a substantial confluence of environmental and economic forces. The stakes are high, not merely for the automotive industry but for the broader discourse on the intersection of environmental stewardship and market dynamics. As we venture forward into uncharted territory, endeavoring to untangle the intricate web of factors underlying this surprising linkage, we must tread with cautious confidence, much like a tightrope walker negotiating the delicate balance between boldness and circumspection—a veritable high-wire act of empirical inquiry.


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 Sonora, California and Total annual sales of Ford Motors in the United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Clearing the Air: Examining the Impact of Air Pollution in Sonora, California on Ford Motor's Sales in the United States"

[[ABSTRACT]]
This study delves into the often-overlooked relationship between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. While the topic may seem flighty at first glance, our rigorous analysis of data from the Environmental Protection Agency and Wikipedia has revealed a surprisingly strong correlation. With a correlation coefficient of 0.8041542 and p < 0.01 for the years 1999 to 2021, the evidence of an association between these seemingly unrelated phenomena is hard to brush off. It appears that the pollutant particles may not just cloud the horizon, but also have an impact on the sales figures of Ford vehicles. However, before we jump to any hasty conclusions, further investigation is needed to discern the precise mechanisms at play and to avoid getting "exhaust"ed by this curious relationship.

[[INTRDUCTION]]
As we traverse the intricate landscape of environmental influence on consumer behavior, a peculiar link has emerged between the hazy atmospheres of Sonora, California, and the soaring or plummeting sales figures of Ford Motors in the United States. The notion that air pollution could hold sway over the purchasing decisions of automotive enthusiasts may seem like a "wild exhaust" of the imagination, but science often thrives on uncovering improbable connections. This study aims to unravel the enigmatic relationship between these divergent variables, employing the quintessential tools of statistical analysis and empirical observation to discern any lurking patterns in the nebulous expanse of data.
The impetus behind this investigation was not merely a whimsical curiosity, but rather a genuine attempt to fathom the unseen currents that guide consumer preferences. It is an endeavor that, much like traversing through smog-filled avenues, necessitates a keen eye to discern the obscured signals amidst the environmental noise. Delving into the annals of scientific research, we unearthed a trove of statistics and historical records that would make even the most seasoned data miner salivate with delight. Our research hypothesis took flight, soaring through the clouds of uncertainty to uncover the potential links between the particulate matter of Sonora's air and the annual sales figures of Ford Motors.
Throughout this investigation, we must tread cautiously, navigating the treacherous terrain of speculation while remaining firmly anchored in the bedrock of empirical evidence. Although the correlation coefficient has "skyrocketed" to a notable 0.8041542, and our p-value swoops low, our prudence dictates that we remain vigilant against the perils of unwarranted assumptions. The potential influence of air pollution on the sales figures cannot be simply "filtered" out based on this correlation alone, and as diligent researchers, we must acknowledge the need for deeper understanding before we "vent"ure into conclusive claims.
In the ensuing sections, we will embark on an odyssey through the smog-choked highways of Sonora and the boardrooms of Ford Motors, unraveling the intricate tapestry of causation and correlation. As we journey through this web of statistical significance, let us remain steadfast in our pursuit of scientific truth, never "tire-d" by the complexities of our endeavor.

[[RESULTS]]
The results of our analysis leave little room for doubt regarding the curious connection between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. Our rigorous examination of the data from 1999 to 2021 yielded a correlation coefficient of 0.8041542, an r-squared value of 0.6466639, and a p-value of less than 0.01. In human terms: there is a strong relationship between these variables, and it's not just a fluke!
Fig. 1 provides a visual representation of the relationship between air pollution in Sonora and Ford Motors' sales. The scatterplot reveals a striking pattern that would make any statistician's heart race. The data points are not just scattered randomly across the plot like debris in the wind; they form a discernible pattern, akin to the orderly march of vehicles on a congested highway.
In light of these findings, it seems that the quality of the air in Sonora may have a "direct drive" effect on the total annual sales figures of Ford Motors in the United States, contrary to popular belief. The air pollution in Sonora, California, perhaps, creates such a "fuel odor" that it impacts the purchasing decisions of consumers across the nation. However, let's not "race" to conclusions just yet. We must shift gears and modestly acknowledge that correlation does not imply causation, and further investigation is necessary to unveil the behind-the-scenes machinations of this surprising relationship. After all, we don't want to "exhaust" ourselves prematurely.
These results challenge the conventional wisdom and warrant a more comprehensive exploration of the potential mechanisms underpinning this unexpected association. We must peel back the layers of this correlation like the layers of an onion, taking care not to shed tears of confusion in the process. While our findings may seem like a serendipitous discovery, we must embrace the scientific ethos of skepticism and inquiry as we navigate the territory of unanticipated connections.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our examination of the relationship between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States has yielded compelling evidence of a surprising correlation. The correlation coefficient of 0.8041542 and the p-value of less than 0.01 suggest a robust link between these seemingly disparate variables. It appears that the polluted air in Sonora may not just be a "breath of fresh air" for statisticians and researchers, but also a significant factor influencing consumer behavior nationwide.

Despite the seemingly strong association, caution is warranted in drawing definitive conclusions. As the saying goes, "Not all that glitters is gold," and not all strong correlations indicate a direct causative relationship. Much like navigating through a dense fog, we must approach this finding with prudence and not get fogged by the allure of hasty generalizations. A deep dive into the intricate mechanisms at play is imperative before we hitch our wagons to the notion of air pollution steering the sales trajectory of Ford Motors.

While our results have unveiled an unexpected connection, further research into the nuanced dynamics of consumer decision-making and the influence of environmental factors remains necessary. Additionally, the potential mediating variables and confounding factors demand scrutiny before we rev up the engines of conclusive interpretation. At this juncture, it behooves us to resist the temptation to leap to premature conclusions and instead embrace the spirit of scientific curiosity and inquiry.

As the dust settles on this investigation, it becomes apparent that while our findings may raise eyebrows and spark intrigue, they also beckon for continued exploration and analysis. Nevertheless, in the spirit of a good pun, we assert that there is "no need to reinvent the wheel" with further research in this area.


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 Clearing the Air: Examining the Impact of Air Pollution in Sonora, California on Ford Motor's Sales in the United States. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Environmental Economics and Corporate Performance


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 Clearing the Air: Examining the Impact of Air Pollution in Sonora, California on Ford Motor's Sales in the United States. Respond only with the name of a fictional organization.

ChatGPT:

Society for Environmental Economic Analysis of Industry (SEEA-I)


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 Clearing the Air: Examining the Impact of Air Pollution in Sonora, California on Ford Motor's Sales in the United States with an abstract of This study delves into the often-overlooked relationship between air pollution in Sonora, California, and the total annual sales of Ford Motors in the United States. While the topic may seem flighty at first glance, our rigorous analysis of data from the Environmental Protection Agency and Wikipedia has revealed a surprisingly strong correlation. With a correlation coefficient of 0.8041542 and p < 0.01 for the years 1999 to 2021, the evidence of an association between these seemingly unrelated phenomena is hard to brush off. It appears that the pollutant particles may not just cloud the horizon, but also have an impact on the sales figures of Ford vehicles. However, before we jump to any hasty conclusions, further investigation is needed to discern the precise mechanisms at play and to avoid getting "exhaust"ed by this curious relationship.

ChatGPT:

Sonora California air pollution, Ford Motors US sales, air pollution impact on car sales, Sonora pollution data, Ford Motors sales analysis, correlation between air pollution and car sales, Environmental Protection Agency air quality Sonora California, relationship between air pollution and car sales, air pollution effects on customer behavior, impact of air pollution on vehicle purchases, pollution impact on auto industry

*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 Sonora, California
Detailed data title: Percentage of days with moderate or worse air quality in Sonora, CA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Sonora, California

Total annual sales of Ford Motors in the United States
Source: Wikipedia
See what else correlates with Total annual sales of Ford Motors in the United States

Correlation r = 0.8041542 (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 = 0.6466639 (Coefficient of determination)
This means 64.7% of the change in the one variable (i.e., Total annual sales of Ford Motors in the United States) is predictable based on the change in the other (i.e., Air pollution in Sonora, California) over the 23 years from 1999 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.8E-6. 0.0000037712462710544710000000
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 0.8 in 0.00038% of random cases. Said differently, if you correlated 265,164 random variables You don't actually need 265 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 22 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 22 because we have two variables measured over a period of 23 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.

[ 0.59, 0.91 ] 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.
19992000200120022003200420052006200720082009201020112012201320142015201620172018201920202021
Air pollution in Sonora, California (Bad air quality days)51.780849.311343.013746.575343.013737.978127.671226.575332.417635.068529.085924.931527.042332.417621.97835.928127.472537.005636.187827.011523.74321.529718.0556
Total annual sales of Ford Motors in the United States (Sales)41633704202820397136036237103483720333168031538802901900250737019883801620890193546021431002250160249392024809402613160261470025867202497320242270020447401905960




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.




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([51.7808,49.3113,43.0137,46.5753,43.0137,37.9781,27.6712,26.5753,32.4176,35.0685,29.0859,24.9315,27.0423,32.4176,21.978,35.9281,27.4725,37.0056,36.1878,27.0115,23.743,21.5297,18.0556,])
array_2 = np.array([4163370,4202820,3971360,3623710,3483720,3331680,3153880,2901900,2507370,1988380,1620890,1935460,2143100,2250160,2493920,2480940,2613160,2614700,2586720,2497320,2422700,2044740,1905960,])
array_1_name = "Air pollution in Sonora, California"
array_2_name = "Total annual sales of Ford Motors in the United States"

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

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



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

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

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

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Correlation ID: 4273 · Black Variable ID: 21275 · Red Variable ID: 337
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