Spurious correlation #2,722 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Number of public school students in 1st grade and the second variable is The number of insurance claims adjusters in Illinois. The chart goes from 2003 to 2022, 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 Number of public school students in 1st grade and the second variable is The number of insurance claims adjusters in Illinois. The chart goes from 2003 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As more and more 1st graders entered public schools, there was a sudden surge in finger painting related insurance claims. This created a demand for additional insurance claims adjusters in Illinois who specialized in assessing the finger painting related damages. The 1st graders were unknowingly crafting a masterpiece of mayhem, leading to a boom in the insurance industry, and a colorful conundrum for the state.

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Generate an image in the style of data cyber art that juxtaposes the energetic 1st-grade students eagerly chatting and laughing outside their school with a group of focused insurance claims adjusters gathering outside an office building, preparing to assist clients. Set the scene on a sunny morning in Illinois with a futuristic yet harmonious blend of the youthful energy of the children and the professional demeanor of the insurance professionals. Capture the contrast in their activities and the anticipation of the day ahead in a visually engaging and balanced composition. 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: Number of public school students in 1st grade and The number of insurance claims adjusters in Illinois. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: A photo-realistic image Data cyber art Oragami High-tech Psychedelic
ChatGPT: Data cyber art

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 Number of public school students in 1st grade and The number of insurance claims adjusters in Illinois together. Keep the description simple.
ChatGPT: On a sunny morning in Illinois, a group of energetic 1st-grade students stands eagerly outside their school, chatting and laughing as they eagerly await the start of their day. Nearby, a cluster of insurance claims adjusters gathers outside an office building, equipped with their laptops and paperwork, ready to head out to assist clients with their claims.

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: [ Data cyber art ] and depicting this scene: On a sunny morning in Illinois, a group of energetic 1st-grade students stands eagerly outside their school, chatting and laughing as they eagerly await the start of their day. Nearby, a cluster of insurance claims adjusters gathers outside an office building, equipped with their laptops and paperwork, ready to head out to assist clients with their claims. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image in the style of data cyber art that juxtaposes the energetic 1st-grade students eagerly chatting and laughing outside their school with a group of focused insurance claims adjusters gathering outside an office building, preparing to assist clients. Set the scene on a sunny morning in Illinois with a futuristic yet harmonious blend of the youthful energy of the children and the professional demeanor of the insurance professionals. Capture the contrast in their activities and the anticipation of the day ahead in a visually engaging and balanced composition.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in Number of public school students in 1st grade positively influenced The number of insurance claims adjusters in Illinois. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Counting Kids and Calculating Claims: An Examination of the Relationship Between 1st Grade Enrollment and Insurance Adjusters in Illinois

Journal of Early Childhood Enrollment and Actuarial Affairs

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 Number of public school students in 1st grade and The number of insurance claims adjusters in Illinois. Make lots of jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
Counting Kids and Calculating Claims: An Examination of the Relationship Between 1st Grade Enrollment and Insurance Adjusters in Illinois

[[ABSTRACT]]
The relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois has long been an enigma. This study delves into the often overlooked correlation between these two seemingly unrelated variables, using data from the National Center for Education Statistics and the Bureau of Labor Statistics. Our research reveals a surprisingly strong positive correlation, with a correlation coefficient of 0.9020167 and a p-value of less than 0.01 from 2003 to 2022. The implications of this unexpected connection are truly mind-boggling, challenging conventional wisdom and prompting further investigation into the whimsical ways in which elementary school enrollment and insurance adjuster populations might be interlinked.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The cultural fascination with correlation is akin to peanut butter and jelly—some combinations just seem to click, while others leave a sour taste in the mouth. In the world of statistical analysis, uncovering unexpected connections can be as surprising as finding a chocolate chip in what you thought was a plain cookie.
The relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois is one such surprising connection. At first glance, these two variables appear about as related as a fish and a bicycle. However, as we dive into the depths of this statistical sea, we find ourselves reeling in some rather curious findings. Our study aims to untangle this web of numbers and unveil the peculiar link between the innocence of youth and the complexities of insurance claims.
While the underlying causes for such a correlation may not be immediately obvious, the implications of this relationship are nothing short of fascinating. The steadfast rise and fall of 1st grade enrollment has managed to mirror the undulating waves of insurance adjusters in the state of Illinois with a synchronicity that defies traditional notions of cause and effect.
As we embark on this statistical journey, we aim to shed light on this unlikely statistical kinship and explore how a surge in 1st grade enrollment might just nudge the population of insurance claims adjusters in a different direction. The consequences of uncovering this correlation extend beyond the numerical realm, challenging our preconceived notions and inviting us to consider the hidden intricacies of these seemingly incongruous domains.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The scholarly exploration of the relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois has been a topic often overlooked in traditional academic inquiry. As the quest for understanding this curious correlation continues, it is imperative to examine the existing literature on this obscure juxtaposition of seemingly unrelated variables.

In "Smith et al.," the authors find no direct evidence to suggest a linkage between the enrollment of 1st grade students and the number of insurance claims adjusters in Illinois. However, the study does acknowledge the potential for unforeseen connections to exist in the realm of societal dynamics, which piques the curiosity of the academic community.

Contrary to the findings of Smith et al., "Doe and Johnson" present a compelling argument for a tentative association between the demographics of 1st grade students and the professional landscape of insurance claims adjusters in Illinois. Their analysis suggests a subtle interplay between the two seemingly disparate phenomena, sparking a renewed interest in this intriguing line of inquiry.

The theoretical groundwork for understanding such an unconventional relationship is further enriched by the work of "Jones and White," who propose a framework for exploring unanticipated correlations across diverse domains. Their comprehensive review of statistical anomalies in societal systems serves as a scholarly springboard for investigating the unexpected link between 1st grade enrollment and insurance adjuster population.

In the world of non-fiction literature, works such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner offer unconventional perspectives on the underlying forces that drive seemingly unrelated phenomena, stimulating critical thinking about the enigmatic connections that permeate our daily lives. Furthermore, "Super Freakonomics" by the same authors delves into the intricacies of unorthodox correlations, inspiring a reconsideration of conventional assumptions about cause and effect.

Turning to the realm of fiction, books like "The Curious Incident of the Dog in the Night-Time" by Mark Haddon and "The Girl with the Dragon Tattoo" by Stieg Larsson provide a whimsical exploration of unexpected correlations and hidden patterns, encouraging readers to embrace the unconventional and unearth the extraordinary within the mundane.

In addition to these literary sources, thought-provoking social media posts have also contributed to the discourse surrounding the improbable relationship between 1st grade enrollment and insurance claims adjusters in Illinois. Tweets such as "Who would've thought that the number of 1st graders could influence insurance jobs? #StatisticalSurprises" and "Just discovered a correlation between 1st grade attendance and insurance claims adjusters. Mind. Blown. #StatisticsRocks" have sparked online conversations about the unanticipated entanglement of these two seemingly disparate aspects of society.

The eclectic tapestry of scholarly, literary, and online discourse surrounding this peculiar correlation invites us to embrace an unconventional perspective and venture into the lighthearted realm of statistical whimsy. As we delve into the unexpected nexus between 1st grade enrollment and insurance claims adjusters, it becomes clear that the world of statistics is replete with delightful surprises and improbable connections, challenging our understanding of causality and inviting us to revel in the enigmatic interplay of numbers and societal phenomena.

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 Number of public school students in 1st grade and The number of insurance claims adjusters in Illinois. Make lots of 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]]
Counting Kids and Calculating Claims: An Examination of the Relationship Between 1st Grade Enrollment and Insurance Adjusters in Illinois

[[ABSTRACT]]
The relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois has long been an enigma. This study delves into the often overlooked correlation between these two seemingly unrelated variables, using data from the National Center for Education Statistics and the Bureau of Labor Statistics. Our research reveals a surprisingly strong positive correlation, with a correlation coefficient of 0.9020167 and a p-value of less than 0.01 from 2003 to 2022. The implications of this unexpected connection are truly mind-boggling, challenging conventional wisdom and prompting further investigation into the whimsical ways in which elementary school enrollment and insurance adjuster populations might be interlinked.

[[LITERATURE REVIEW]]
The scholarly exploration of the relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois has been a topic often overlooked in traditional academic inquiry. As the quest for understanding this curious correlation continues, it is imperative to examine the existing literature on this obscure juxtaposition of seemingly unrelated variables.
In "Smith et al.," the authors find no direct evidence to suggest a linkage between the enrollment of 1st grade students and the number of insurance claims adjusters in Illinois. However, the study does acknowledge the potential for unforeseen connections to exist in the realm of societal dynamics, which piques the curiosity of the academic community.
Contrary to the findings of Smith et al., "Doe and Johnson" present a compelling argument for a tentative association between the demographics of 1st grade students and the professional landscape of insurance claims adjusters in Illinois. Their analysis suggests a subtle interplay between the two seemingly disparate phenomena, sparking a renewed interest in this intriguing line of inquiry.
The theoretical groundwork for understanding such an unconventional relationship is further enriched by the work of "Jones and White," who propose a framework for exploring unanticipated correlations across diverse domains. Their comprehensive review of statistical anomalies in societal systems serves as a scholarly springboard for investigating the unexpected link between 1st grade enrollment and insurance adjuster population.
In the world of non-fiction literature, works such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner offer unconventional perspectives on the underlying forces that drive seemingly unrelated phenomena, stimulating critical thinking about the enigmatic connections that permeate our daily lives. Furthermore, "Super Freakonomics" by the same authors delves into the intricacies of unorthodox correlations, inspiring a reconsideration of conventional assumptions about cause and effect.
Turning to the realm of fiction, books like "The Curious Incident of the Dog in the Night-Time" by Mark Haddon and "The Girl with the Dragon Tattoo" by Stieg Larsson provide a whimsical exploration of unexpected correlations and hidden patterns, encouraging readers to embrace the unconventional and unearth the extraordinary within the mundane.
In addition to these literary sources, thought-provoking social media posts have also contributed to the discourse surrounding the improbable relationship between 1st grade enrollment and insurance claims adjusters in Illinois. Tweets such as "Who would've thought that the number of 1st graders could influence insurance jobs? #StatisticalSurprises" and "Just discovered a correlation between 1st grade attendance and insurance claims adjusters. Mind. Blown. #StatisticsRocks" have sparked online conversations about the unanticipated entanglement of these two seemingly disparate aspects of society.
The eclectic tapestry of scholarly, literary, and online discourse surrounding this peculiar correlation invites us to embrace an unconventional perspective and venture into the lighthearted realm of statistical whimsy. As we delve into the unexpected nexus between 1st grade enrollment and insurance claims adjusters, it becomes clear that the world of statistics is replete with delightful surprises and improbable connections, challenging our understanding of causality and inviting us to revel in the enigmatic interplay of numbers and societal phenomena.

[[RESULTS]]
The results of our investigation into the curious relationship between 1st grade enrollment and the number of insurance claims adjusters in Illinois yielded some intriguing findings. From 2003 to 2022, we observed a remarkably strong positive correlation between these two variables, with a correlation coefficient of 0.9020167 and an r-squared value of 0.8136342. The p-value of less than 0.01 further substantiates the robustness of this correlation, indicating a high level of statistical significance.
Figure 1 illustrates the relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois. The scatterplot depicts a strikingly linear pattern, emphasizing the coherence between these seemingly disparate factors.
Remarkably, the rise and fall of 1st grade enrollment mirrored the fluctuations in the population of insurance claims adjusters in Illinois with an unexpectedly high degree of fidelity. The implications of this revelatory discovery challenge conventional wisdom and prompt contemplation of the intricate, albeit whimsical, ways in which elementary school enrollment and insurance adjuster populations may be interlinked.
The strength of the correlation implies a rather surprising rapport between these variables, defying the expectations of traditional statistical analyses. While the precise mechanisms underlying this relationship remain elusive, the robustness of the statistical findings cannot be overlooked. The alignment of these two seemingly unrelated domains calls for further investigation into the whimsical interplay of numerical entities with distinct societal roles. Our findings invite the academic community to reevaluate their understanding of the hidden dynamics that underpin what initially appear to be unrelated phenomena, reminding us that statistical surprises can be as delightful as finding unexpected toppings on a pizza.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study offer compelling evidence in support of the previously overlooked and often derided relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois. Our findings corroborate the initial inklings of "Doe and Johnson," hinting at a tentative association between these two variables. This unexpected concordance challenges the skepticism expressed in the work of "Smith et al.," underscoring the relevance of exploring unanticipated correlations and their broader societal implications.

The discovery of a remarkably strong positive correlation between 1st grade enrollment and the population of insurance claims adjusters prompts us to reconsider conventional perspectives on the dynamics of societal phenomena. While the mechanisms underlying this relationship remain shrouded in mystery, the robust statistical support for this unexpected nexus demands a reevaluation of traditional assumptions about causal linkages between disparate domains. It seems that the whimsy of statistical anomalies can rival the delight of stumbling upon a particularly cheesy pun.

The linear pattern depicted in the scatterplot between the number of 1st grade students and the population of insurance claims adjusters highlights the surprising coherence between these ostensibly unrelated variables. The uncanny fidelity with which the ebb and flow of 1st grade enrollment mimic the fluctuations in the insurance claims adjuster population reinforces the striking parallelism between these domains. This unexpected mirroring of trends reminds us of the intricate dance of numbers and societal dynamics, akin to the harmonious yet unexpected fusion of flavors in a delicious entree.

The stellar statistical significance indicated by a p-value of less than 0.01 accentuates the robustness of this correlation, leaving little room for doubt regarding the substantive connection between these two seemingly incongruous entities. Our findings beckon the scholarly community to embrace a more whimsical interpretation of statistical relationships, reminding us that life's surprises can be as unexpected and delightful as discovering an unexpected treat buried within a seemingly mundane snack.

As we peek behind the statistical curtain to uncover the delightful twists and turns of these numerical entanglements, we are compelled to recognize the potential for unlikely correlations to permeate the fabric of our daily lives. This revelatory exploration of the unanticipated relationship between 1st grade enrollment and insurance claims adjuster population invites us to embrace the whimsical intricacies that underlie the seemingly disparate facets of our societal tapestry and reminds us that even the most unexpected connections can yield intriguing and intellectually stimulating insights.

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 Number of public school students in 1st grade and The number of insurance claims adjusters in Illinois. Make lots of 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]]
Counting Kids and Calculating Claims: An Examination of the Relationship Between 1st Grade Enrollment and Insurance Adjusters in Illinois

[[ABSTRACT]]
The relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois has long been an enigma. This study delves into the often overlooked correlation between these two seemingly unrelated variables, using data from the National Center for Education Statistics and the Bureau of Labor Statistics. Our research reveals a surprisingly strong positive correlation, with a correlation coefficient of 0.9020167 and a p-value of less than 0.01 from 2003 to 2022. The implications of this unexpected connection are truly mind-boggling, challenging conventional wisdom and prompting further investigation into the whimsical ways in which elementary school enrollment and insurance adjuster populations might be interlinked.

[[INTRDUCTION]]
The cultural fascination with correlation is akin to peanut butter and jelly—some combinations just seem to click, while others leave a sour taste in the mouth. In the world of statistical analysis, uncovering unexpected connections can be as surprising as finding a chocolate chip in what you thought was a plain cookie.
The relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois is one such surprising connection. At first glance, these two variables appear about as related as a fish and a bicycle. However, as we dive into the depths of this statistical sea, we find ourselves reeling in some rather curious findings. Our study aims to untangle this web of numbers and unveil the peculiar link between the innocence of youth and the complexities of insurance claims.
While the underlying causes for such a correlation may not be immediately obvious, the implications of this relationship are nothing short of fascinating. The steadfast rise and fall of 1st grade enrollment has managed to mirror the undulating waves of insurance adjusters in the state of Illinois with a synchronicity that defies traditional notions of cause and effect.
As we embark on this statistical journey, we aim to shed light on this unlikely statistical kinship and explore how a surge in 1st grade enrollment might just nudge the population of insurance claims adjusters in a different direction. The consequences of uncovering this correlation extend beyond the numerical realm, challenging our preconceived notions and inviting us to consider the hidden intricacies of these seemingly incongruous domains.

[[RESULTS]]
The results of our investigation into the curious relationship between 1st grade enrollment and the number of insurance claims adjusters in Illinois yielded some intriguing findings. From 2003 to 2022, we observed a remarkably strong positive correlation between these two variables, with a correlation coefficient of 0.9020167 and an r-squared value of 0.8136342. The p-value of less than 0.01 further substantiates the robustness of this correlation, indicating a high level of statistical significance.
Figure 1 illustrates the relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois. The scatterplot depicts a strikingly linear pattern, emphasizing the coherence between these seemingly disparate factors.
Remarkably, the rise and fall of 1st grade enrollment mirrored the fluctuations in the population of insurance claims adjusters in Illinois with an unexpectedly high degree of fidelity. The implications of this revelatory discovery challenge conventional wisdom and prompt contemplation of the intricate, albeit whimsical, ways in which elementary school enrollment and insurance adjuster populations may be interlinked.
The strength of the correlation implies a rather surprising rapport between these variables, defying the expectations of traditional statistical analyses. While the precise mechanisms underlying this relationship remain elusive, the robustness of the statistical findings cannot be overlooked. The alignment of these two seemingly unrelated domains calls for further investigation into the whimsical interplay of numerical entities with distinct societal roles. Our findings invite the academic community to reevaluate their understanding of the hidden dynamics that underpin what initially appear to be unrelated phenomena, reminding us that statistical surprises can be as delightful as finding unexpected toppings on a pizza.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has shed light on the perplexing yet entertaining relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois. The strikingly strong positive correlation uncovered between these seemingly incongruous variables has left us contemplating the whimsical ways in which elementary school enrollment and insurance adjuster populations might be intertwined.

The robustness of this correlation, with a correlation coefficient of 0.9020167 and a p-value of less than 0.01, defies traditional statistical expectations and challenges us to reconsider the seemingly disparate spheres of education and insurance claims.

Despite the statistical rigor and significance of our findings, we must acknowledge the limitations of observational studies in establishing causality. While we've uncovered a surprising parallel between these two domains, we cannot definitively ascribe a causative link. Perhaps this correlation is merely a statistical quirk, or there may be underlying factors at play that we have yet to uncover. After all, correlation does not necessarily imply causation, but it certainly invites speculation and further inquiry.

In the spirit of statistical curiosity, one can't help but wonder if a surge in 1st grade enrollment leads to an influx of insurance claims adjusters or vice versa. Could the innocence of youth be influencing the population of adjusters, or are the complexities of insurance claims shaping the decisions of parents enrolling their children in 1st grade? These questions linger like the aroma of freshly baked hypotheses, tantalizing our intellectual appetites.

Nevertheless, the implications of this correlation are as intriguing as stumbling upon a unexpected bonus fry at the bottom of the fast-food bag. This study beckons further investigation into the humorous intricacies of our numerical world, encouraging researchers to consider the delightful surprises hidden in the most unlikely of statistical pairings.

While we relish in the amusement of this statistical conundrum, we must also acknowledge that, much like a well-timed punchline, this investigation has run its course. No more research is needed in this area, for we have unraveled the enigmatic connection between 1st grade students and insurance claims adjusters in Illinois as much as is necessary for the time being.

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 Counting Kids and Calculating Claims: An Examination of the Relationship Between 1st Grade Enrollment and Insurance Adjusters in Illinois. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Early Childhood Enrollment and Actuarial Affairs

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 Counting Kids and Calculating Claims: An Examination of the Relationship Between 1st Grade Enrollment and Insurance Adjusters in Illinois. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Educational Research (SQER)

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 Counting Kids and Calculating Claims: An Examination of the Relationship Between 1st Grade Enrollment and Insurance Adjusters in Illinois with an abstract of The relationship between the number of 1st grade students in public schools and the population of insurance claims adjusters in Illinois has long been an enigma. This study delves into the often overlooked correlation between these two seemingly unrelated variables, using data from the National Center for Education Statistics and the Bureau of Labor Statistics. Our research reveals a surprisingly strong positive correlation, with a correlation coefficient of 0.9020167 and a p-value of less than 0.01 from 2003 to 2022. The implications of this unexpected connection are truly mind-boggling, challenging conventional wisdom and prompting further investigation into the whimsical ways in which elementary school enrollment and insurance adjuster populations might be interlinked.

ChatGPT:

1st grade enrollment, insurance adjusters, Illinois, correlation, National Center for Education Statistics, Bureau of Labor Statistics

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

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Data details

Number of public school students in 1st grade
Detailed data title: 1st grade enrollment in public elementary and secondary schools
Source: National Center for Education Statistics
See what else correlates with Number of public school students in 1st grade

The number of insurance claims adjusters in Illinois
Detailed data title: BLS estimate of claims adjusters, examiners, and investigators in Illinois
Source: Bureau of Larbor Statistics
See what else correlates with The number of insurance claims adjusters in Illinois

Correlation r = 0.9020167 (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 = 0.8136342 (Coefficient of determination)
This means 81.4% of the change in the one variable (i.e., The number of insurance claims adjusters in Illinois) is predictable based on the change in the other (i.e., Number of public school students in 1st grade) over the 20 years from 2003 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.5E-8.^Show 0.0000000551447652013883800000
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 0.9 in 5.5E-6% of random cases. Said differently, if you correlated 18,134,088 random variables^Note You don't actually need 18 million 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.

[ 0.76, 0.96 ] 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.

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Number of public school students in 1st grade (Students)	3612510	3663000	3690850	3751140	3750070	3708480	3728770	3753950	3772640	3823600	3884820	3863490	3768140	3693850	3667170	3640650	3646680	3522210	3457730	3648740
The number of insurance claims adjusters in Illinois (Laborers)	11990	12180	11130	13600	13150	12580	13990	13920	13790	13500	15390	14810	13410	11180	11270	12450	12090	10750	9480	11610

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([3612510,3663000,3690850,3751140,3750070,3708480,3728770,3753950,3772640,3823600,3884820,3863490,3768140,3693850,3667170,3640650,3646680,3522210,3457730,3648740,])
array_2 = np.array([11990,12180,11130,13600,13150,12580,13990,13920,13790,13500,15390,14810,13410,11180,11270,12450,12090,10750,9480,11610,])
array_1_name = "Number of public school students in 1st grade"
array_2_name = "The number of insurance claims adjusters in Illinois"

# 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 Number of public school students in 1st grade
Line chart for only The number of insurance claims adjusters in Illinois
AI-generated correlation image
The spurious research paper: Counting Kids and Calculating Claims: An Examination of the Relationship Between 1st Grade Enrollment and Insurance Adjusters in Illinois

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Correlation ID: 2722 · Black Variable ID: 1298 · Red Variable ID: 7313


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