Spurious correlation #2,491 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air quality in St. Louis and the second variable is Google searches for 'how to immigrate to canada'. The chart goes from 2004 to 2023, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air quality in St. Louis and the second variable is Google searches for 'how to immigrate to canada'. The chart goes from 2004 to 2023, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The higher air quality in St. Louis led to an influx of Canadian geese, who, in a strange turn of events, started a national campaign promoting the benefits of living in Canada. As more and more people were honked into considering the Great White North, the Google searches for 'how to immigrate to Canada' took flight. It seems like those geese were really spreading their wings and influencing the human newcomers to migrate for a better gander at life in Canada.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a futuristic St. Louis skyline with a hazy sky hanging over the iconic Gateway Arch. Within the cityscape, people are depicted busily typing into their smartphones, with a sense of longing and anticipation. The aroma of toasted ravioli fills the air, while a group of locals engage in animated conversation, their thoughts turning towards the lush maple syrup and the savory poutine of Canada, creating a palpable contrast and yearning for the crisp Canadian delicacies. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Air quality in St. Louis and Google searches for 'how to immigrate to canada'. 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: Cyber folk Celtic art Symbolism Futuristic An image that looks like it is a scene from A Disney Movie
ChatGPT: Futuristic

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air quality in St. Louis and Google searches for 'how to immigrate to canada', in the following situation: The abundant and exceptional aroma of toasted ravioli in St. Louis is a powerful motivator to seek out a land with poutine and maple syrup instead. The siren call of Canadian delicacies proved too strong to resist, leading to a mass exodus in pursuit of a more gastronomically satisfying atmosphere.. Keep the description simple.
ChatGPT: In St. Louis, a hazy sky blankets the iconic Gateway Arch as people busily type "how to immigrate to canada" into their smartphones, surrounded by the irresistible scent of toasted ravioli. Meanwhile, a group of locals share stories of poutine and maple syrup, their mouths watering at the thought of exchanging St. Louis air for crisp Canadian delicacies.

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: [ Futuristic ] and depicting this scene: In St. Louis, a hazy sky blankets the iconic Gateway Arch as people busily type "how to immigrate to canada" into their smartphones, surrounded by the irresistible scent of toasted ravioli. Meanwhile, a group of locals share stories of poutine and maple syrup, their mouths watering at the thought of exchanging St. Louis air for crisp Canadian delicacies. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a futuristic St. Louis skyline with a hazy sky hanging over the iconic Gateway Arch. Within the cityscape, people are depicted busily typing into their smartphones, with a sense of longing and anticipation. The aroma of toasted ravioli fills the air, while a group of locals engage in animated conversation, their thoughts turning towards the lush maple syrup and the savory poutine of Canada, creating a palpable contrast and yearning for the crisp Canadian delicacies.

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

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

AI academic paper

(Because p < 0.01)

St. Louis Smog's Effect on Canadian Yearns: A Correlations Rhyme

The International Journal of Atmospheric Oddities

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air quality in St. Louis and Google searches for 'how to immigrate to canada'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
St. Louis Smog's Effect on Canadian Yearns: A Correlations Rhyme

[[ABSTRACT]]
This study examines the relationship between air quality in St. Louis and Google searches for "how to immigrate to Canada" using data from the Environmental Protection Agency and Google Trends. A correlation coefficient of 0.8564845 and p < 0.01 for the years 2004 to 2023 was observed. The findings suggest a noteworthy connection between poor air quality and an increase in internet inquiries about Canadian immigration. The implications of these results warrant further investigation and may have broader implications for understanding the impact of environmental factors on migration desires. This correlation does not imply causation, but it does leave us pondering whether people are searching for a breath of fresh air in more ways than one.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Air pollution is a pervasive and persistent issue in urban areas, with detrimental effects on both public health and the environment. The city of St. Louis, Missouri, is no stranger to this challenge, as it grapples with elevated levels of particulate matter, nitrogen dioxide, and other air pollutants. Concurrently, the lure of the Great White North beckons to those seeking refuge from the haze of pollution, with Canada's pristine landscapes and fresh air serving as a siren song for many. This study delves into the intriguing relationship between St. Louis' smog and the tendency of individuals to turn to their web browsers with inquiries on how to immigrate to Canada.
While the notion of seeking a new home due to environmental concerns may seem like a folkloric tale, the digital age has provided us with a window into the collective consciousness of the populace. Enter Google Trends, a treasure trove of search data revealing the queries and quandaries of internet users. It is here that we find a peculiar pattern - a surge in searches for "how to immigrate to Canada" during periods of poor air quality in St. Louis. Could it be that the denizens of this city are not only yearning for cleaner air, but are also contemplating a geographical leap to the land of maple syrup and moose?
The intersection of environmental quality and migration desires is a topic ripe for exploration. While correlation does not imply causation, the compelling statistical relationship uncovered in this study prompts us to ponder the enigmatic ways in which the environment influences human decisions. As we proceed to unravel the nuances of this correlation, it becomes evident that the conversation regarding air quality transcends the confines of public health and veers into the realm of migration patterns. Our investigation sheds light on the possibility of environmental factors serving as catalysts for reimagining one's geographic roots, or perhaps, as prompts for seeking a breath of fresh air in more ways than one.
In the pages that follow, we embark on a journey through empirical data and statistical analyses, unraveling the tale of St. Louis smog and Canadian yearns - a correlation that may just rhyme its way into the annals of migration studies.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In their study "Pollution and Migration," Smith and Doe (2016) examine the association between air quality and migration tendencies. The authors elucidate the impact of environmental factors on individuals' inclinations to seek residency in areas with superior air quality. Moreover, Jones et al. (2019) delve into the psychological aspects of environmental migration in their work "Mind Over Smog," positing that deteriorating air quality can prompt individuals to contemplate relocation to regions with cleaner atmospheres.

Moving on from the established literature, the analysis expands to encompass works that may not be explicitly focused on environmental migration but offer insight into human responses to environmental challenges. In "The Uninhabitable Earth," David Wallace-Wells paints a dire picture of the consequences of environmental degradation, with vivid descriptions of polluted air pushing individuals towards reconsidering their dwelling places. On a lighter note, Amy Poehler's "Yes Please" may seem unrelated, but amidst the humor and wit, there is an underlying theme of seeking refuge in more favorable environments, be it physical or metaphorical.

In the realm of fiction, Margaret Atwood's "Oryx and Crake" provides a dystopian narrative that subtly touches on the theme of environmental migration, with characters grappling with an ecologically devastated world. Similarly, the protagonist of Douglas Adams' "The Hitchhiker's Guide to the Galaxy" embarks on an intergalactic journey in pursuit of cleaner air, albeit in a comedic and satirical context.

Furthermore, informal sources on social media platforms contribute anecdotal evidence related to our research topic. A Twitter user observed, "Every time the haze settles in St. Louis, I start browsing immigration websites like I'm preparing for a sabbatical in the Tundra. Can't deal with this smog anymore #CanadaDreams." This sentiment aligns with the patterns uncovered in our study, underscoring the resonance of our findings with real-world experiences.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Air quality in St. Louis and Google searches for 'how to immigrate to canada'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Google Trends . You used data from 2004 to 2023

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]]
St. Louis Smog's Effect on Canadian Yearns: A Correlations Rhyme

[[ABSTRACT]]
This study examines the relationship between air quality in St. Louis and Google searches for "how to immigrate to Canada" using data from the Environmental Protection Agency and Google Trends. A correlation coefficient of 0.8564845 and p < 0.01 for the years 2004 to 2023 was observed. The findings suggest a noteworthy connection between poor air quality and an increase in internet inquiries about Canadian immigration. The implications of these results warrant further investigation and may have broader implications for understanding the impact of environmental factors on migration desires. This correlation does not imply causation, but it does leave us pondering whether people are searching for a breath of fresh air in more ways than one.

[[INTRODUCTION]]
Air pollution is a pervasive and persistent issue in urban areas, with detrimental effects on both public health and the environment. The city of St. Louis, Missouri, is no stranger to this challenge, as it grapples with elevated levels of particulate matter, nitrogen dioxide, and other air pollutants. Concurrently, the lure of the Great White North beckons to those seeking refuge from the haze of pollution, with Canada's pristine landscapes and fresh air serving as a siren song for many. This study delves into the intriguing relationship between St. Louis' smog and the tendency of individuals to turn to their web browsers with inquiries on how to immigrate to Canada.
While the notion of seeking a new home due to environmental concerns may seem like a folkloric tale, the digital age has provided us with a window into the collective consciousness of the populace. Enter Google Trends, a treasure trove of search data revealing the queries and quandaries of internet users. It is here that we find a peculiar pattern - a surge in searches for "how to immigrate to Canada" during periods of poor air quality in St. Louis. Could it be that the denizens of this city are not only yearning for cleaner air, but are also contemplating a geographical leap to the land of maple syrup and moose?
The intersection of environmental quality and migration desires is a topic ripe for exploration. While correlation does not imply causation, the compelling statistical relationship uncovered in this study prompts us to ponder the enigmatic ways in which the environment influences human decisions. As we proceed to unravel the nuances of this correlation, it becomes evident that the conversation regarding air quality transcends the confines of public health and veers into the realm of migration patterns. Our investigation sheds light on the possibility of environmental factors serving as catalysts for reimagining one's geographic roots, or perhaps, as prompts for seeking a breath of fresh air in more ways than one.
In the pages that follow, we embark on a journey through empirical data and statistical analyses, unraveling the tale of St. Louis smog and Canadian yearns - a correlation that may just rhyme its way into the annals of migration studies.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection:
The data for this investigation was sourced from the Environmental Protection Agency (EPA) and Google Trends. The EPA provided air quality measurements, including levels of particulate matter, nitrogen dioxide, and other pollutants, from air quality monitoring stations in the St. Louis metropolitan area for the years 2004 to 2023. Google Trends data were utilized to track the relative search interest for the term "how to immigrate to Canada" over the same timeframe. The decision to focus on Google searches for inquiries related to Canadian immigration was made with the recognition that it serves as a digital barometer of migration desires, however whimsical the query may seem.

Data Analysis:
To establish a basis for comparison, the air quality data from the EPA were subjected to rigorous statistical analysis. This involved the calculation of various air quality indices and the determination of periods characterized by poor air quality. The Google Trends data, on the other hand, underwent relative search interest normalization to allow for comparison over the study period. The aim was to identify temporal patterns and potential associations between the fluctuations in St. Louis air quality and the frequency of Google searches for information on immigrating to Canada.

Correlation Analysis:
Utilizing advanced statistical techniques, including Pearson correlation coefficients and time series analyses, we sought to discern the degree of association between air quality in St. Louis and the volume of Google searches pertaining to Canadian immigration. To account for potential confounding variables and mitigating factors, sensitivity analyses were performed to assess the robustness of the observed correlations. The resulting correlation coefficient, accompanied by a p-value below the conventional threshold of 0.01, provided compelling evidence of a strong relationship between the two seemingly disparate phenomena.

Outlier Detection:
In recognizing the unpredictability of human behavior and the myriad influences on internet search patterns, special attention was given to identifying outlier events or anomalous spikes in search activity. These outliers, whether driven by environmental events, cultural phenomena, or the capricious nature of internet users, were subjected to meticulous scrutiny to avoid unwarranted conclusions or misinterpretations of the data.

Limitations and Assumptions:
It is essential to acknowledge the inherent limitations and assumptions associated with this study. While the correlation observed between St. Louis air quality and searches for Canadian immigration information is statistically robust, it does not establish a causal relationship. Moreover, the reliance on Google search data as a proxy for migration desires presupposes an inherent connection between internet query behavior and real-world migration intentions, which warrants cautious interpretation.

Overall, the methodological approach adopted in this study combines the rigor of empirical analysis with the quirkiness of internet search patterns, yielding a unique lens through which to explore the intersection of environmental quality and migration aspirations.

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

Please make up the results section of an academic research paper presenting the findings of the connection between Air quality in St. Louis and Google searches for 'how to immigrate to canada'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Google Trends .

For the time period 2004 to 2023, you found a correlation 0.8564845, r-squared of 0.7335657, 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]]
St. Louis Smog's Effect on Canadian Yearns: A Correlations Rhyme

[[ABSTRACT]]
This study examines the relationship between air quality in St. Louis and Google searches for "how to immigrate to Canada" using data from the Environmental Protection Agency and Google Trends. A correlation coefficient of 0.8564845 and p < 0.01 for the years 2004 to 2023 was observed. The findings suggest a noteworthy connection between poor air quality and an increase in internet inquiries about Canadian immigration. The implications of these results warrant further investigation and may have broader implications for understanding the impact of environmental factors on migration desires. This correlation does not imply causation, but it does leave us pondering whether people are searching for a breath of fresh air in more ways than one.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Air pollution is a pervasive and persistent issue in urban areas, with detrimental effects on both public health and the environment. The city of St. Louis, Missouri, is no stranger to this challenge, as it grapples with elevated levels of particulate matter, nitrogen dioxide, and other air pollutants. Concurrently, the lure of the Great White North beckons to those seeking refuge from the haze of pollution, with Canada's pristine landscapes and fresh air serving as a siren song for many. This study delves into the intriguing relationship between St. Louis' smog and the tendency of individuals to turn to their web browsers with inquiries on how to immigrate to Canada.
While the notion of seeking a new home due to environmental concerns may seem like a folkloric tale, the digital age has provided us with a window into the collective consciousness of the populace. Enter Google Trends, a treasure trove of search data revealing the queries and quandaries of internet users. It is here that we find a peculiar pattern - a surge in searches for "how to immigrate to Canada" during periods of poor air quality in St. Louis. Could it be that the denizens of this city are not only yearning for cleaner air, but are also contemplating a geographical leap to the land of maple syrup and moose?
The intersection of environmental quality and migration desires is a topic ripe for exploration. While correlation does not imply causation, the compelling statistical relationship uncovered in this study prompts us to ponder the enigmatic ways in which the environment influences human decisions. As we proceed to unravel the nuances of this correlation, it becomes evident that the conversation regarding air quality transcends the confines of public health and veers into the realm of migration patterns. Our investigation sheds light on the possibility of environmental factors serving as catalysts for reimagining one's geographic roots, or perhaps, as prompts for seeking a breath of fresh air in more ways than one.
In the pages that follow, we embark on a journey through empirical data and statistical analyses, unraveling the tale of St. Louis smog and Canadian yearns - a correlation that may just rhyme its way into the annals of migration studies.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The examination of the relationship between air quality in St. Louis and Google searches for "how to immigrate to Canada" for the time period of 2004 to 2023 revealed a strong correlation coefficient of 0.8564845, an r-squared of 0.7335657, and a p-value of less than 0.01. These statistical indicators point to a robust association between poor air quality in St. Louis and increased interest in Canadian immigration as reflected in internet search behavior.

Fig. 1 illustrates the compelling correlation between air quality in St. Louis and the frequency of Google searches for information on immigrating to Canada. The scatterplot clearly demonstrates the upward trend in Canadian immigration inquiries during periods of worsened air quality in St. Louis, depicting a relationship that raises intriguing questions about the interplay between environmental factors and migration aspirations.

These findings underscore the potential influence of environmental conditions on individuals' considerations of migration, while also prompting lighthearted musings about the possibility of people seeking a geographical escape from the haze of pollutants. While the data cannot establish a causal link, it does prompt contemplation about the overlap of environmental concerns and aspirations for a change in scenery.

The results of this study contribute to the understanding of the multifaceted impact of air quality on human behavior and migration patterns. While the correlation cannot single-handedly explain the complexities of migration decisions, it does present a thought-provoking connection that invites further scrutiny.

The implications of these findings extend beyond the realm of environmental research, hinting at the whimsical ways in which individuals may envision a literal and metaphorical "fresh start" in the face of environmental challenges. The correlation, while statistically robust, also serves as a poignant reminder of the human inclination to seek refuge in greener pastures, both literally and figuratively.

In summary, the results of this study shed light on the intriguing correlation between air quality in St. Louis and the inclination to explore Canadian immigration options, leaving us with a lingering question: are people really yearning for cleaner air or simply dreaming of donning a toque and sipping maple syrup in the midst of pristine Canadian landscapes?

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Air quality in St. Louis and Google searches for 'how to immigrate to canada'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
St. Louis Smog's Effect on Canadian Yearns: A Correlations Rhyme

[[ABSTRACT]]
This study examines the relationship between air quality in St. Louis and Google searches for "how to immigrate to Canada" using data from the Environmental Protection Agency and Google Trends. A correlation coefficient of 0.8564845 and p < 0.01 for the years 2004 to 2023 was observed. The findings suggest a noteworthy connection between poor air quality and an increase in internet inquiries about Canadian immigration. The implications of these results warrant further investigation and may have broader implications for understanding the impact of environmental factors on migration desires. This correlation does not imply causation, but it does leave us pondering whether people are searching for a breath of fresh air in more ways than one.

[[LITERATURE REVIEW]]
In their study "Pollution and Migration," Smith and Doe (2016) examine the association between air quality and migration tendencies. The authors elucidate the impact of environmental factors on individuals' inclinations to seek residency in areas with superior air quality. Moreover, Jones et al. (2019) delve into the psychological aspects of environmental migration in their work "Mind Over Smog," positing that deteriorating air quality can prompt individuals to contemplate relocation to regions with cleaner atmospheres.
Moving on from the established literature, the analysis expands to encompass works that may not be explicitly focused on environmental migration but offer insight into human responses to environmental challenges. In "The Uninhabitable Earth," David Wallace-Wells paints a dire picture of the consequences of environmental degradation, with vivid descriptions of polluted air pushing individuals towards reconsidering their dwelling places. On a lighter note, Amy Poehler's "Yes Please" may seem unrelated, but amidst the humor and wit, there is an underlying theme of seeking refuge in more favorable environments, be it physical or metaphorical.
In the realm of fiction, Margaret Atwood's "Oryx and Crake" provides a dystopian narrative that subtly touches on the theme of environmental migration, with characters grappling with an ecologically devastated world. Similarly, the protagonist of Douglas Adams' "The Hitchhiker's Guide to the Galaxy" embarks on an intergalactic journey in pursuit of cleaner air, albeit in a comedic and satirical context.
Furthermore, informal sources on social media platforms contribute anecdotal evidence related to our research topic. A Twitter user observed, "Every time the haze settles in St. Louis, I start browsing immigration websites like I'm preparing for a sabbatical in the Tundra. Can't deal with this smog anymore #CanadaDreams." This sentiment aligns with the patterns uncovered in our study, underscoring the resonance of our findings with real-world experiences.

[[RESULTS]]
The examination of the relationship between air quality in St. Louis and Google searches for "how to immigrate to Canada" for the time period of 2004 to 2023 revealed a strong correlation coefficient of 0.8564845, an r-squared of 0.7335657, and a p-value of less than 0.01. These statistical indicators point to a robust association between poor air quality in St. Louis and increased interest in Canadian immigration as reflected in internet search behavior.
Fig. 1 illustrates the compelling correlation between air quality in St. Louis and the frequency of Google searches for information on immigrating to Canada. The scatterplot clearly demonstrates the upward trend in Canadian immigration inquiries during periods of worsened air quality in St. Louis, depicting a relationship that raises intriguing questions about the interplay between environmental factors and migration aspirations.
These findings underscore the potential influence of environmental conditions on individuals' considerations of migration, while also prompting lighthearted musings about the possibility of people seeking a geographical escape from the haze of pollutants. While the data cannot establish a causal link, it does prompt contemplation about the overlap of environmental concerns and aspirations for a change in scenery.
The results of this study contribute to the understanding of the multifaceted impact of air quality on human behavior and migration patterns. While the correlation cannot single-handedly explain the complexities of migration decisions, it does present a thought-provoking connection that invites further scrutiny.
The implications of these findings extend beyond the realm of environmental research, hinting at the whimsical ways in which individuals may envision a literal and metaphorical "fresh start" in the face of environmental challenges. The correlation, while statistically robust, also serves as a poignant reminder of the human inclination to seek refuge in greener pastures, both literally and figuratively.
In summary, the results of this study shed light on the intriguing correlation between air quality in St. Louis and the inclination to explore Canadian immigration options, leaving us with a lingering question: are people really yearning for cleaner air or simply dreaming of donning a toque and sipping maple syrup in the midst of pristine Canadian landscapes?

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study resonate with prior research that has examined the influence of environmental factors on migration inclinations. The substantial correlation between poor air quality in St. Louis and heightened interest in Canadian immigration, as evidenced by Google search patterns, aligns with the assertions of Smith and Doe (2016) regarding the impact of environmental conditions on migration tendencies. Furthermore, the results also echo the sentiment expressed by the Twitter user, emphasizing the real-world relevance of our findings. In this light, the data not only confirm existing literature but also add quantitative support to anecdotal observations.

The literature review, with its seemingly unconventional selections, offers a rich backdrop for interpreting the implications of our results. The works of Wallace-Wells and Poehler, though not explicitly focused on environmental migration, lend a nuanced understanding of individuals' responses to environmental challenges and aspirations for relocation. Additionally, the dystopian narratives of Atwood and Adams, mentioned in a somewhat lighthearted vein in the literature review, inadvertently capture the essence of the human desire to seek refuge in more favorable environments, be it within or beyond national boundaries. This subtle interplay between the academic and the anecdotal adds a layer of depth to the interpretation of our findings, highlighting the intricate web of influences that underlie migration considerations.

From a statistical standpoint, the robust correlation coefficients and significant p-values provide empirical support for the hypothesized relationship between air quality and Canadian immigration searches. The r-squared value further underscores the strength of this association and accentuates the potential impact of poor air quality on migration contemplations. Although the data cannot establish causation, the compelling statistical indicators reaffirm the plausibility of a genuine connection between environmental discomfort and aspirations for a change in residency.

The implications of these results extend beyond the realm of environmental research, evoking whimsical contemplations about the human proclivity to seek solace in idyllic landscapes and fresher atmospheres. This juxtaposition of the serious and the lighthearted underscores the multifaceted nature of migration aspirations and invites a broader reflection on the underlying motivations for geographical relocations. The statistical robustness of the correlation, combined with the broader resonance of our findings with real-world experiences, positions this study as a catalyst for further inquiries into the interplay between environmental conditions and migration desires, infusing a touch of levity into the often solemn discourse on migration determinants.

The correlation identified in this study cannot singularly unravel the complexities of migration decisions, but it does illuminate the captivating intersection of environmental concerns and aspirations for a literal and metaphorical "fresh start." Thus, as we conclude this discussion, we are left to ponder whether individuals are genuinely yearning for cleaner air or simply longing for a metaphorical breath of fresh air, co-existing in a world caught between the hazy smog of reality and the alluring promise of Canadian landscapes.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air quality in St. Louis and Google searches for 'how to immigrate to canada'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
St. Louis Smog's Effect on Canadian Yearns: A Correlations Rhyme

[[ABSTRACT]]
This study examines the relationship between air quality in St. Louis and Google searches for "how to immigrate to Canada" using data from the Environmental Protection Agency and Google Trends. A correlation coefficient of 0.8564845 and p < 0.01 for the years 2004 to 2023 was observed. The findings suggest a noteworthy connection between poor air quality and an increase in internet inquiries about Canadian immigration. The implications of these results warrant further investigation and may have broader implications for understanding the impact of environmental factors on migration desires. This correlation does not imply causation, but it does leave us pondering whether people are searching for a breath of fresh air in more ways than one.

[[INTRDUCTION]]
Air pollution is a pervasive and persistent issue in urban areas, with detrimental effects on both public health and the environment. The city of St. Louis, Missouri, is no stranger to this challenge, as it grapples with elevated levels of particulate matter, nitrogen dioxide, and other air pollutants. Concurrently, the lure of the Great White North beckons to those seeking refuge from the haze of pollution, with Canada's pristine landscapes and fresh air serving as a siren song for many. This study delves into the intriguing relationship between St. Louis' smog and the tendency of individuals to turn to their web browsers with inquiries on how to immigrate to Canada.
While the notion of seeking a new home due to environmental concerns may seem like a folkloric tale, the digital age has provided us with a window into the collective consciousness of the populace. Enter Google Trends, a treasure trove of search data revealing the queries and quandaries of internet users. It is here that we find a peculiar pattern - a surge in searches for "how to immigrate to Canada" during periods of poor air quality in St. Louis. Could it be that the denizens of this city are not only yearning for cleaner air, but are also contemplating a geographical leap to the land of maple syrup and moose?
The intersection of environmental quality and migration desires is a topic ripe for exploration. While correlation does not imply causation, the compelling statistical relationship uncovered in this study prompts us to ponder the enigmatic ways in which the environment influences human decisions. As we proceed to unravel the nuances of this correlation, it becomes evident that the conversation regarding air quality transcends the confines of public health and veers into the realm of migration patterns. Our investigation sheds light on the possibility of environmental factors serving as catalysts for reimagining one's geographic roots, or perhaps, as prompts for seeking a breath of fresh air in more ways than one.
In the pages that follow, we embark on a journey through empirical data and statistical analyses, unraveling the tale of St. Louis smog and Canadian yearns - a correlation that may just rhyme its way into the annals of migration studies.

[[RESULTS]]
The examination of the relationship between air quality in St. Louis and Google searches for "how to immigrate to Canada" for the time period of 2004 to 2023 revealed a strong correlation coefficient of 0.8564845, an r-squared of 0.7335657, and a p-value of less than 0.01. These statistical indicators point to a robust association between poor air quality in St. Louis and increased interest in Canadian immigration as reflected in internet search behavior.
Fig. 1 illustrates the compelling correlation between air quality in St. Louis and the frequency of Google searches for information on immigrating to Canada. The scatterplot clearly demonstrates the upward trend in Canadian immigration inquiries during periods of worsened air quality in St. Louis, depicting a relationship that raises intriguing questions about the interplay between environmental factors and migration aspirations.
These findings underscore the potential influence of environmental conditions on individuals' considerations of migration, while also prompting lighthearted musings about the possibility of people seeking a geographical escape from the haze of pollutants. While the data cannot establish a causal link, it does prompt contemplation about the overlap of environmental concerns and aspirations for a change in scenery.
The results of this study contribute to the understanding of the multifaceted impact of air quality on human behavior and migration patterns. While the correlation cannot single-handedly explain the complexities of migration decisions, it does present a thought-provoking connection that invites further scrutiny.
The implications of these findings extend beyond the realm of environmental research, hinting at the whimsical ways in which individuals may envision a literal and metaphorical "fresh start" in the face of environmental challenges. The correlation, while statistically robust, also serves as a poignant reminder of the human inclination to seek refuge in greener pastures, both literally and figuratively.
In summary, the results of this study shed light on the intriguing correlation between air quality in St. Louis and the inclination to explore Canadian immigration options, leaving us with a lingering question: are people really yearning for cleaner air or simply dreaming of donning a toque and sipping maple syrup in the midst of pristine Canadian landscapes?

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

The correlation between poor air quality in St. Louis and the surge in Google searches for "how to immigrate to Canada" has been established with statistical rigor. The robust correlation coefficient and p-value below 0.01 point to a compelling association that warrants attention. The findings hint at the possibility of individuals contemplating a change in their geographic roots in response to environmental challenges, with Canada's pristine landscapes and fresh air serving as an alluring alternative. The data do not establish causation, but they do beckon us to entertain whimsical musings about the interplay between polluted skies and dreams of maple syrup-scented breezes.

These results uncover a correlation that may tickle the fancy of migration scholars and environmental enthusiasts alike, prompting a light-hearted contemplation of whether St. Louis smog is inadvertently invoking visions of Mounties and beavers. While the study offers valuable insights, it also invokes a chuckle as one envisions individuals gazing at the grey horizon of St. Louis and spontaneously breaking into an acapella rendition of "O Canada."

In light of the amusing yet thought-provoking findings, we are compelled to proclaim that this investigation has taken us on a journey through empirical data and subtle humor, providing a glimpse into the enigmatic ways in which the environment influences human wanderlust. There seems to be no need for further research in this area, as the results have left us with a cheeky smile and a nod to the whimsy of human behavior in the face of environmental phenomena.

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 St. Louis Smog's Effect on Canadian Yearns: A Correlations Rhyme. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of Atmospheric Oddities

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 St. Louis Smog's Effect on Canadian Yearns: A Correlations Rhyme. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Atmospheric Inquiry and Research (SAIR)

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 St. Louis Smog's Effect on Canadian Yearns: A Correlations Rhyme with an abstract of This study examines the relationship between air quality in St. Louis and Google searches for "how to immigrate to Canada" using data from the Environmental Protection Agency and Google Trends. A correlation coefficient of 0.8564845 and p < 0.01 for the years 2004 to 2023 was observed. The findings suggest a noteworthy connection between poor air quality and an increase in internet inquiries about Canadian immigration. The implications of these results warrant further investigation and may have broader implications for understanding the impact of environmental factors on migration desires. This correlation does not imply causation, but it does leave us pondering whether people are searching for a breath of fresh air in more ways than one.

ChatGPT:

St. Louis air quality, Canadian immigration searches, correlation, environmental factors, migration desires, Google Trends, Environmental Protection Agency, air pollution impact

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

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Data details

Air quality in St. Louis
Detailed data title: Percentage of days with good air quality in St. Louis, MO-IL
Source: Environmental Protection Agency
See what else correlates with Air quality in St. Louis

Google searches for 'how to immigrate to canada'
Detailed data title: Relative volume of Google searches for 'how to immigrate to canada' (Worldwide, without quotes)
Source: Google Trends
Additional Info: ^{See full details} Relative search volume (not absolute numbers)

See what else correlates with Google searches for 'how to immigrate to canada'

Correlation r = 0.8564845 (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 = 0.7335657 (Coefficient of determination)
This means 73.4% of the change in the one variable (i.e., Google searches for 'how to immigrate to canada') is predictable based on the change in the other (i.e., Air quality in St. Louis) over the 20 years from 2004 through 2023.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.4E-6.^Show 0.0000014397184787729740000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.86 in 0.00014% of random cases. Said differently, if you correlated 694,580 random variables^Note You don't actually need 694 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, ^Note 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.

[ 0.67, 0.94 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022	2023
Air quality in St. Louis (Good air quality)	24.5902	12.0548	9.31507	17.8082	21.5847	25.2055	15.0685	21.9178	22.6776	34.7945	38.9041	36.4384	49.1803	46.3014	43.5616	38.3562	43.9891	38.0822	42.1918	35.1648
Google searches for 'how to immigrate to canada' (Rel. search volume)	25.8333	19.0833	10.3333	9.75	15.5	17.9167	20.4167	21.9167	19.75	23.5833	25.75	22.0833	31.25	28.8333	32	32.1667	35.5833	29.8333	33.6667	29.5

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([24.5902,12.0548,9.31507,17.8082,21.5847,25.2055,15.0685,21.9178,22.6776,34.7945,38.9041,36.4384,49.1803,46.3014,43.5616,38.3562,43.9891,38.0822,42.1918,35.1648,])
array_2 = np.array([25.8333,19.0833,10.3333,9.75,15.5,17.9167,20.4167,21.9167,19.75,23.5833,25.75,22.0833,31.25,28.8333,32,32.1667,35.5833,29.8333,33.6667,29.5,])
array_1_name = "Air quality in St. Louis"
array_2_name = "Google searches for 'how to immigrate to canada'"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Air quality in St. Louis
Line chart for only Google searches for 'how to immigrate to canada'
AI-generated correlation image
The spurious research paper: St. Louis Smog's Effect on Canadian Yearns: A Correlations Rhyme

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Correlation ID: 2491 · Black Variable ID: 21312 · Red Variable ID: 1349


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