Spurious correlation #1,922 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Score of the US Open Golf Winner and the second variable is The number of receptionists in Hawaii. 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 Score of the US Open Golf Winner and the second variable is The number of receptionists in Hawaii. The chart goes from 2003 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the US Open Golf Winner's score improves, so does their mood. This heightened sense of achievement and happiness emanates outward, creating a ripple effect that inexplicably boosts the demand for receptionists in Hawaii. It's as if their victory put everyone in a frenzied state of needing more pleasant voices to answer phones and greet guests, especially in the land of aloha. The correlation is clear: better golf performance leads to a sudden spike in the paradise's receptionist employment. It's tee-rific for the winner and the job market in Hawaii!

^{Show image generation prompt} Model: dalle-3
Prompt: [A photo-realistic image] The US Open Golf Winner, holding a trophy, stands on the lush green golf course of a Hawaiian paradise. Surrounding the winner are a group of welcoming receptionists, each adorned with vibrant and colorful leis. The winner, with an elated expression, engages in a joyful conversation with the receptionists, commemorating the victory in the picturesque island setting. 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: Score of the US Open Golf Winner and The number of receptionists in Hawaii. 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: inspired by bauhaus Minimalism Realistic A photo-realistic image High-tech
ChatGPT: A photo-realistic image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Score of the US Open Golf Winner and The number of receptionists in Hawaii together. Keep the description simple.
ChatGPT: The US Open Golf Winner, holding a trophy, stands on the beautiful green golf course in Hawaii. Surrounding the winner are the island's receptionists, all wearing colorful leis and smiling as they greet guests. The winner happily chats with the receptionists, celebrating the victory in the stunning island setting.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A photo-realistic image ] and depicting this scene: The US Open Golf Winner, holding a trophy, stands on the beautiful green golf course in Hawaii. Surrounding the winner are the island's receptionists, all wearing colorful leis and smiling as they greet guests. The winner happily chats with the receptionists, celebrating the victory in the stunning island setting. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [A photo-realistic image] The US Open Golf Winner, holding a trophy, stands on the lush green golf course of a Hawaiian paradise. Surrounding the winner are a group of welcoming receptionists, each adorned with vibrant and colorful leis. The winner, with an elated expression, engages in a joyful conversation with the receptionists, commemorating the victory in the picturesque island setting.

*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 Score of the US Open Golf Winner positively influenced The number of receptionists in Hawaii.

AI academic paper

(Because p < 0.01)

Swinging with Stats: Teeing Up the Relationship Between US Open Golf Scores and the Receptionist Workforce in Hawaii

The International Journal of Statistical Sports Studies

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 Score of the US Open Golf Winner and The number of receptionists in Hawaii. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
"Swinging with Stats: Teeing Up the Relationship Between US Open Golf Scores and the Receptionist Workforce in Hawaii"

[[ABSTRACT]]
The widespread fascination with golf and the curious world of statistics collide in this study, as we delve into the connection between the score of the US Open Golf winner and the number of receptionists in Hawaii. Utilizing data spanning from 2003 to 2022 sourced from Golfstats and the Bureau of Labor Statistics, our research team conducted a detailed analysis. An intriguing correlation coefficient of 0.6823408 emerged, with a statistically significant p-value of less than 0.01, shedding light on the surprising relationship between these two seemingly unrelated variables. Despite the initial skepticism regarding the possible relevance of golf scores to receptionist employment in Hawaii, the results provide compelling evidence to the contrary.

Not to tee you off with too many details, but our findings suggest that as the US Open Golf winner's score improves, there is a corresponding increase in the number of receptionists in Hawaii. While some may find this correlation a "fore"ceful conclusion, the data speak for themselves and offer a birdie's-eye view of this phenomenon. These unexpected results make us wonder whether there is an unnoticed bond between the precision of a golfer's swing and the need for coordinating appointments and phone calls in the Aloha State. Further research is required to uncover the underlying factors driving this apparent relationship and to determine if it holds true in other geographic regions. In examining these interconnected phenomena, our study inspires a new perspective on the intricate links between professional sports and labor market dynamics.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between sporting events and labor market dynamics has long been an area of interest for economists and statisticians alike. While some may view these pursuits as being as unrelated as a golf ball to a receptionist's phone call, our study seeks to explore the surprising connection between the score of the US Open Golf winner and the number of receptionists in Hawaii. As we delve into this unlikely correlation, we aim to provide a detailed analysis that goes beyond mere conjecture and attempts to drive a wedge into understanding the underlying mechanisms at play.
Before we dive into the rough of our findings, it is worth pondering a question: What do you call a receptionist at a golf course? A "tee-rific" multitasker! This playful jest aside, our research takes on the task of unraveling the enigma behind the statistically significant correlation coefficient of 0.6823408 that emerged from our meticulous examination of the data set spanning nearly two decades.
In the spirit of full transparency, our initial skepticism led us to question whether these findings were truly on par with the laws of statistical probability. However, as the evidence irons itself out, it becomes clear that there is a compelling case for further investigation. It appears that the golf course and the reception area may not be as distant as one might assume.
Proceeding with caution, we are reminded of the old adage: "It's not whether you win or lose, it's how you play the game." Perhaps in the world of statistics, it's not just about the numbers, but the unexpected connections they reveal. This study is set to unravel the mystery behind this curious connection and offer insights that expand our understanding of the intricate dance between seemingly disparate variables.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Golfstats: The Official Guide to the US Open," Smith and Jones provide an in-depth analysis of the performance of US Open Golf winners over the years, detailing their scores and strategies. Meanwhile, in "Labor Market Dynamics in Hawaii" by Doe, the authors examine the trends in various occupational sectors, including administrative support roles such as receptionists, within the Hawaiian labor market.

However, as we step onto the green and into the world of receptionist work, it's crucial to consider the unexpected twists and turns that may come our way. Much like a golf ball taking an unexpected bounce on the fairway, the correlation we have unearthed between the US Open Golf winner's score and the number of receptionists in Hawaii seems to defy conventional expectations.

Turning from the fairway to the library, the works of "Freakonomics: A Rogue Economist Explores the Hidden Side of Everything" by Levitt and Dubner and "Nudge: Improving Decisions About Health, Wealth, and Happiness" by Thaler and Sunstein shed light on how seemingly unrelated factors can intersect in surprising ways, much like our findings regarding golf scores and receptionist employment.

On a slightly more whimsical note, the world of fiction offers "The Secret Life of Walter Mitty" by James Thurber and "The Hitchhiker's Guide to the Galaxy" by Douglas Adams, both of which celebrate the joy of unexpected adventures and the discovery of unconventional connections. Much like these literary works, our study invites readers to embark on a journey of unexpected correlations and peculiar revelations.

In the realm of popular internet culture, the meme of the "Distracted Boyfriend" provides a humorous parallel to our study, as it playfully illustrates the concept of being drawn to unexpected alternatives. Similarly, the "Doge" meme captures the essence of lighthearted and whimsical connections, much like the unexpected relationship between golf scores and receptionist employment in Hawaii that our research has brought to light.

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 Score of the US Open Golf Winner and The number of receptionists in Hawaii. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 Golfstats and Bureau of Larbor Statistics . You used data from 2003 to 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Swinging with Stats: Teeing Up the Relationship Between US Open Golf Scores and the Receptionist Workforce in Hawaii"

[[ABSTRACT]]
The widespread fascination with golf and the curious world of statistics collide in this study, as we delve into the connection between the score of the US Open Golf winner and the number of receptionists in Hawaii. Utilizing data spanning from 2003 to 2022 sourced from Golfstats and the Bureau of Labor Statistics, our research team conducted a detailed analysis. An intriguing correlation coefficient of 0.6823408 emerged, with a statistically significant p-value of less than 0.01, shedding light on the surprising relationship between these two seemingly unrelated variables. Despite the initial skepticism regarding the possible relevance of golf scores to receptionist employment in Hawaii, the results provide compelling evidence to the contrary.

Not to tee you off with too many details, but our findings suggest that as the US Open Golf winner's score improves, there is a corresponding increase in the number of receptionists in Hawaii. While some may find this correlation a "fore"ceful conclusion, the data speak for themselves and offer a birdie's-eye view of this phenomenon. These unexpected results make us wonder whether there is an unnoticed bond between the precision of a golfer's swing and the need for coordinating appointments and phone calls in the Aloha State. Further research is required to uncover the underlying factors driving this apparent relationship and to determine if it holds true in other geographic regions. In examining these interconnected phenomena, our study inspires a new perspective on the intricate links between professional sports and labor market dynamics.

[[INTRODUCTION]]
The relationship between sporting events and labor market dynamics has long been an area of interest for economists and statisticians alike. While some may view these pursuits as being as unrelated as a golf ball to a receptionist's phone call, our study seeks to explore the surprising connection between the score of the US Open Golf winner and the number of receptionists in Hawaii. As we delve into this unlikely correlation, we aim to provide a detailed analysis that goes beyond mere conjecture and attempts to drive a wedge into understanding the underlying mechanisms at play.
Before we dive into the rough of our findings, it is worth pondering a question: What do you call a receptionist at a golf course? A "tee-rific" multitasker! This playful jest aside, our research takes on the task of unraveling the enigma behind the statistically significant correlation coefficient of 0.6823408 that emerged from our meticulous examination of the data set spanning nearly two decades.
In the spirit of full transparency, our initial skepticism led us to question whether these findings were truly on par with the laws of statistical probability. However, as the evidence irons itself out, it becomes clear that there is a compelling case for further investigation. It appears that the golf course and the reception area may not be as distant as one might assume.
Proceeding with caution, we are reminded of the old adage: "It's not whether you win or lose, it's how you play the game." Perhaps in the world of statistics, it's not just about the numbers, but the unexpected connections they reveal. This study is set to unravel the mystery behind this curious connection and offer insights that expand our understanding of the intricate dance between seemingly disparate variables.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the relationship between the score of the US Open Golf winner and the number of receptionists in Hawaii, a multifaceted approach was employed. The data collection process involved sourcing information from Golfstats and the Bureau of Labor Statistics, spanning the years from 2003 to 2022. The dataset was scrubbed meticulously, ensuring that the integrity of the information was not compromised, avoiding any mulligans in the analysis.

Utilizing advanced statistical methods, including regression analysis and time series modeling, we endeavored to discern any underlying patterns and identify potential causal relationships between the variables under scrutiny. The statistical techniques employed were chosen after careful consideration of their compatibility with the nature of the data and the research objectives. Our choice of statistical methods was akin to selecting the appropriate club for the right shot, ensuring that the analysis was carried out with precision and finesse.

In addition, a series of sensitivity analyses were conducted to ascertain the robustness of the findings and mitigate the impact of any potential outliers or confounding factors. Sensitivity analyses were essential in ensuring that the conclusions drawn were not unduly influenced by unforeseen circumstances, acting as a safeguard against the hazards of spurious correlations.

Furthermore, a geographical segmentation analysis was performed to explore the regional variations in the relationship between golf scores and receptionist employment. This analysis aimed to elucidate whether the observed correlation was unique to Hawaii or exhibited a broader applicability across different locations.

To maintain methodological rigor and uphold the standards of academic inquiry, the research team engaged in rigorous peer discussions and review processes, akin to the peer review process in academic publishing. This constructive exchange of ideas and feedback played a pivotal role in refining the research methods, adding an extra layer of assurance to the validity and reliability of the study's findings.

In handling the data with the utmost care and applying a variety of analytical techniques, our research sought to uncover the nuanced interplay between the score of the US Open Golf winner and the number of receptionists in Hawaii. While humor may not be par for the course in academic methodology sections, we strive to infuse a touch of lightheartedness to keep the reader engaged. After all, as any golfer will affirm, a well-timed jest can be the perfect remedy for a slice of seriousness in scholarly discourse.

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 Score of the US Open Golf Winner and The number of receptionists in Hawaii. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 Golfstats and Bureau of Larbor Statistics .

For the time period 2003 to 2022, you found a correlation 0.6823408, r-squared of 0.4655890, 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]]
"Swinging with Stats: Teeing Up the Relationship Between US Open Golf Scores and the Receptionist Workforce in Hawaii"

[[ABSTRACT]]
The widespread fascination with golf and the curious world of statistics collide in this study, as we delve into the connection between the score of the US Open Golf winner and the number of receptionists in Hawaii. Utilizing data spanning from 2003 to 2022 sourced from Golfstats and the Bureau of Labor Statistics, our research team conducted a detailed analysis. An intriguing correlation coefficient of 0.6823408 emerged, with a statistically significant p-value of less than 0.01, shedding light on the surprising relationship between these two seemingly unrelated variables. Despite the initial skepticism regarding the possible relevance of golf scores to receptionist employment in Hawaii, the results provide compelling evidence to the contrary.

Not to tee you off with too many details, but our findings suggest that as the US Open Golf winner's score improves, there is a corresponding increase in the number of receptionists in Hawaii. While some may find this correlation a "fore"ceful conclusion, the data speak for themselves and offer a birdie's-eye view of this phenomenon. These unexpected results make us wonder whether there is an unnoticed bond between the precision of a golfer's swing and the need for coordinating appointments and phone calls in the Aloha State. Further research is required to uncover the underlying factors driving this apparent relationship and to determine if it holds true in other geographic regions. In examining these interconnected phenomena, our study inspires a new perspective on the intricate links between professional sports and labor market dynamics.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The relationship between sporting events and labor market dynamics has long been an area of interest for economists and statisticians alike. While some may view these pursuits as being as unrelated as a golf ball to a receptionist's phone call, our study seeks to explore the surprising connection between the score of the US Open Golf winner and the number of receptionists in Hawaii. As we delve into this unlikely correlation, we aim to provide a detailed analysis that goes beyond mere conjecture and attempts to drive a wedge into understanding the underlying mechanisms at play.
Before we dive into the rough of our findings, it is worth pondering a question: What do you call a receptionist at a golf course? A "tee-rific" multitasker! This playful jest aside, our research takes on the task of unraveling the enigma behind the statistically significant correlation coefficient of 0.6823408 that emerged from our meticulous examination of the data set spanning nearly two decades.
In the spirit of full transparency, our initial skepticism led us to question whether these findings were truly on par with the laws of statistical probability. However, as the evidence irons itself out, it becomes clear that there is a compelling case for further investigation. It appears that the golf course and the reception area may not be as distant as one might assume.
Proceeding with caution, we are reminded of the old adage: "It's not whether you win or lose, it's how you play the game." Perhaps in the world of statistics, it's not just about the numbers, but the unexpected connections they reveal. This study is set to unravel the mystery behind this curious connection and offer insights that expand our understanding of the intricate dance between seemingly disparate variables.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The primary aim of this study was to investigate the relationship between the score of the US Open Golf winner and the number of receptionists in Hawaii. Through the rigorous analysis of data collected from Golfstats and the Bureau of Labor Statistics for the period of 2003 to 2022, a statistically significant correlation coefficient of 0.6823408 was uncovered. This coefficient, coupled with an r-squared value of 0.4655890 and a p-value lower than 0.01, indicates a robust association between the two variables.

Fig. 1 illustrates the strong correlation observed between the score of the US Open Golf winner and the number of receptionists in Hawaii. It is evident that as the golf score improves, there is a corresponding increase in the count of receptionists in Hawaii. It's almost as if the receptionist workforce in Hawaii is "driving for show and putting for dough," mirroring the performance of the US Open Golf winner.

These findings might prompt one to wonder if there is an unspoken language between the precision of a golfer's swing and the demand for receptionist services in Hawaii. It seems that the golf course and the front desk are not as far apart as one might initially believe.

This unexpected correlation serves as a reminder that in the world of statistics, the most unexpected connections often yield the most intriguing insights. Despite initial skepticism, the results of this study reinforce the need for further investigation into the underlying mechanisms driving this seemingly unrelated relationship.

In summary, the results of this study reveal a compelling and statistically significant correlation between the score of the US Open Golf winner and the number of receptionists in Hawaii, shedding light on the unanticipated connection between professional sports and labor market dynamics. These findings invite further research to explore the broader implications of this relationship and its potential relevance beyond the shores of Hawaii.

As we ponder the unexpected union between golf scores and receptionist numbers, it is worth remembering the wise words of Mark Twain: "Golf is a good walk spoiled." However, in this case, it seems that golf may have also led to an unforeseen workforce trend in the Aloha State.

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 Score of the US Open Golf Winner and The number of receptionists in Hawaii. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Swinging with Stats: Teeing Up the Relationship Between US Open Golf Scores and the Receptionist Workforce in Hawaii"

[[ABSTRACT]]
The widespread fascination with golf and the curious world of statistics collide in this study, as we delve into the connection between the score of the US Open Golf winner and the number of receptionists in Hawaii. Utilizing data spanning from 2003 to 2022 sourced from Golfstats and the Bureau of Labor Statistics, our research team conducted a detailed analysis. An intriguing correlation coefficient of 0.6823408 emerged, with a statistically significant p-value of less than 0.01, shedding light on the surprising relationship between these two seemingly unrelated variables. Despite the initial skepticism regarding the possible relevance of golf scores to receptionist employment in Hawaii, the results provide compelling evidence to the contrary.

Not to tee you off with too many details, but our findings suggest that as the US Open Golf winner's score improves, there is a corresponding increase in the number of receptionists in Hawaii. While some may find this correlation a "fore"ceful conclusion, the data speak for themselves and offer a birdie's-eye view of this phenomenon. These unexpected results make us wonder whether there is an unnoticed bond between the precision of a golfer's swing and the need for coordinating appointments and phone calls in the Aloha State. Further research is required to uncover the underlying factors driving this apparent relationship and to determine if it holds true in other geographic regions. In examining these interconnected phenomena, our study inspires a new perspective on the intricate links between professional sports and labor market dynamics.

[[LITERATURE REVIEW]]
In "Golfstats: The Official Guide to the US Open," Smith and Jones provide an in-depth analysis of the performance of US Open Golf winners over the years, detailing their scores and strategies. Meanwhile, in "Labor Market Dynamics in Hawaii" by Doe, the authors examine the trends in various occupational sectors, including administrative support roles such as receptionists, within the Hawaiian labor market.
However, as we step onto the green and into the world of receptionist work, it's crucial to consider the unexpected twists and turns that may come our way. Much like a golf ball taking an unexpected bounce on the fairway, the correlation we have unearthed between the US Open Golf winner's score and the number of receptionists in Hawaii seems to defy conventional expectations.
Turning from the fairway to the library, the works of "Freakonomics: A Rogue Economist Explores the Hidden Side of Everything" by Levitt and Dubner and "Nudge: Improving Decisions About Health, Wealth, and Happiness" by Thaler and Sunstein shed light on how seemingly unrelated factors can intersect in surprising ways, much like our findings regarding golf scores and receptionist employment.
On a slightly more whimsical note, the world of fiction offers "The Secret Life of Walter Mitty" by James Thurber and "The Hitchhiker's Guide to the Galaxy" by Douglas Adams, both of which celebrate the joy of unexpected adventures and the discovery of unconventional connections. Much like these literary works, our study invites readers to embark on a journey of unexpected correlations and peculiar revelations.
In the realm of popular internet culture, the meme of the "Distracted Boyfriend" provides a humorous parallel to our study, as it playfully illustrates the concept of being drawn to unexpected alternatives. Similarly, the "Doge" meme captures the essence of lighthearted and whimsical connections, much like the unexpected relationship between golf scores and receptionist employment in Hawaii that our research has brought to light.

[[RESULTS]]
The primary aim of this study was to investigate the relationship between the score of the US Open Golf winner and the number of receptionists in Hawaii. Through the rigorous analysis of data collected from Golfstats and the Bureau of Labor Statistics for the period of 2003 to 2022, a statistically significant correlation coefficient of 0.6823408 was uncovered. This coefficient, coupled with an r-squared value of 0.4655890 and a p-value lower than 0.01, indicates a robust association between the two variables.
Fig. 1 illustrates the strong correlation observed between the score of the US Open Golf winner and the number of receptionists in Hawaii. It is evident that as the golf score improves, there is a corresponding increase in the count of receptionists in Hawaii. It's almost as if the receptionist workforce in Hawaii is "driving for show and putting for dough," mirroring the performance of the US Open Golf winner.
These findings might prompt one to wonder if there is an unspoken language between the precision of a golfer's swing and the demand for receptionist services in Hawaii. It seems that the golf course and the front desk are not as far apart as one might initially believe.
This unexpected correlation serves as a reminder that in the world of statistics, the most unexpected connections often yield the most intriguing insights. Despite initial skepticism, the results of this study reinforce the need for further investigation into the underlying mechanisms driving this seemingly unrelated relationship.
In summary, the results of this study reveal a compelling and statistically significant correlation between the score of the US Open Golf winner and the number of receptionists in Hawaii, shedding light on the unanticipated connection between professional sports and labor market dynamics. These findings invite further research to explore the broader implications of this relationship and its potential relevance beyond the shores of Hawaii.
As we ponder the unexpected union between golf scores and receptionist numbers, it is worth remembering the wise words of Mark Twain: "Golf is a good walk spoiled." However, in this case, it seems that golf may have also led to an unforeseen workforce trend in the Aloha State.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The significant correlation observed in this study between the score of the US Open Golf winner and the number of receptionists in Hawaii provides an unexpected and thought-provoking insight into the interplay between professional sports and labor market dynamics. The results of this investigation align with prior research by Smith and Jones, who meticulously documented the performance of US Open Golf winners. While their focus was on golf strategy and performance, our study extends their findings, demonstrating a compelling association between golf scores and labor market trends. Similarly, Doe's analysis of occupational sectors in Hawaii offered a broader context for understanding our results, further substantiating the relevance of our findings within the local labor market. As expected, the unexpected connection noted in the literature review has been borne out by our rigorous analysis.

The statistically significant relationship uncovered in our study reinforces the notion that seemingly unrelated factors may intersect in meaningful ways, echoing the insights put forth in the works of Levitt and Dubner, as well as Thaler and Sunstein. Indeed, the unanticipated bond between the precision of a golfer's swing and the demand for receptionist services in Hawaii calls to mind the concept of "nudging" explored by Thaler and Sunstein, where subtle influences can drive decision-making processes. Much like a well-timed putt, our findings offer a stroke of insight into the nuanced dynamics underlying labor market trends.

The illustration of the strong correlation between the golf score and the count of receptionists in Hawaii serves as a vivid example of how statistical analyses can uncover unexpected connections, reminiscent of the delightful serendipity found in the works of James Thurber and Douglas Adams. As our research tees up a new perspective on the intricate links between professional sports and labor market dynamics, it prompts the academic community to embrace the playful spirit of unexpected correlations and peculiar revelations, akin to the whimsical themes in "The Secret Life of Walter Mitty" and "The Hitchhiker's Guide to the Galaxy."

In summary, our study underlines the value of approaching data analysis with an open mind, recognizing that the most unconventional connections can yield valuable insights. As Mark Twain wryly noted, "Golf is a good walk spoiled," yet it appears that in this instance, the world of golf has led to a surprising workforce trend in the Aloha State. These findings invite further exploration into the broader implications of this unexpected relationship and serve as a delightful reminder of the boundless potential for discovery within the realm of statistical analysis.

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 Score of the US Open Golf Winner and The number of receptionists in Hawaii. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Swinging with Stats: Teeing Up the Relationship Between US Open Golf Scores and the Receptionist Workforce in Hawaii"

[[ABSTRACT]]
The widespread fascination with golf and the curious world of statistics collide in this study, as we delve into the connection between the score of the US Open Golf winner and the number of receptionists in Hawaii. Utilizing data spanning from 2003 to 2022 sourced from Golfstats and the Bureau of Labor Statistics, our research team conducted a detailed analysis. An intriguing correlation coefficient of 0.6823408 emerged, with a statistically significant p-value of less than 0.01, shedding light on the surprising relationship between these two seemingly unrelated variables. Despite the initial skepticism regarding the possible relevance of golf scores to receptionist employment in Hawaii, the results provide compelling evidence to the contrary.

Not to tee you off with too many details, but our findings suggest that as the US Open Golf winner's score improves, there is a corresponding increase in the number of receptionists in Hawaii. While some may find this correlation a "fore"ceful conclusion, the data speak for themselves and offer a birdie's-eye view of this phenomenon. These unexpected results make us wonder whether there is an unnoticed bond between the precision of a golfer's swing and the need for coordinating appointments and phone calls in the Aloha State. Further research is required to uncover the underlying factors driving this apparent relationship and to determine if it holds true in other geographic regions. In examining these interconnected phenomena, our study inspires a new perspective on the intricate links between professional sports and labor market dynamics.

[[INTRDUCTION]]
The relationship between sporting events and labor market dynamics has long been an area of interest for economists and statisticians alike. While some may view these pursuits as being as unrelated as a golf ball to a receptionist's phone call, our study seeks to explore the surprising connection between the score of the US Open Golf winner and the number of receptionists in Hawaii. As we delve into this unlikely correlation, we aim to provide a detailed analysis that goes beyond mere conjecture and attempts to drive a wedge into understanding the underlying mechanisms at play.
Before we dive into the rough of our findings, it is worth pondering a question: What do you call a receptionist at a golf course? A "tee-rific" multitasker! This playful jest aside, our research takes on the task of unraveling the enigma behind the statistically significant correlation coefficient of 0.6823408 that emerged from our meticulous examination of the data set spanning nearly two decades.
In the spirit of full transparency, our initial skepticism led us to question whether these findings were truly on par with the laws of statistical probability. However, as the evidence irons itself out, it becomes clear that there is a compelling case for further investigation. It appears that the golf course and the reception area may not be as distant as one might assume.
Proceeding with caution, we are reminded of the old adage: "It's not whether you win or lose, it's how you play the game." Perhaps in the world of statistics, it's not just about the numbers, but the unexpected connections they reveal. This study is set to unravel the mystery behind this curious connection and offer insights that expand our understanding of the intricate dance between seemingly disparate variables.

[[RESULTS]]
The primary aim of this study was to investigate the relationship between the score of the US Open Golf winner and the number of receptionists in Hawaii. Through the rigorous analysis of data collected from Golfstats and the Bureau of Labor Statistics for the period of 2003 to 2022, a statistically significant correlation coefficient of 0.6823408 was uncovered. This coefficient, coupled with an r-squared value of 0.4655890 and a p-value lower than 0.01, indicates a robust association between the two variables.
Fig. 1 illustrates the strong correlation observed between the score of the US Open Golf winner and the number of receptionists in Hawaii. It is evident that as the golf score improves, there is a corresponding increase in the count of receptionists in Hawaii. It's almost as if the receptionist workforce in Hawaii is "driving for show and putting for dough," mirroring the performance of the US Open Golf winner.
These findings might prompt one to wonder if there is an unspoken language between the precision of a golfer's swing and the demand for receptionist services in Hawaii. It seems that the golf course and the front desk are not as far apart as one might initially believe.
This unexpected correlation serves as a reminder that in the world of statistics, the most unexpected connections often yield the most intriguing insights. Despite initial skepticism, the results of this study reinforce the need for further investigation into the underlying mechanisms driving this seemingly unrelated relationship.
In summary, the results of this study reveal a compelling and statistically significant correlation between the score of the US Open Golf winner and the number of receptionists in Hawaii, shedding light on the unanticipated connection between professional sports and labor market dynamics. These findings invite further research to explore the broader implications of this relationship and its potential relevance beyond the shores of Hawaii.
As we ponder the unexpected union between golf scores and receptionist numbers, it is worth remembering the wise words of Mark Twain: "Golf is a good walk spoiled." However, in this case, it seems that golf may have also led to an unforeseen workforce trend in the Aloha State.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has elucidated a significant correlation between the score of the US Open Golf winner and the number of receptionists in Hawaii. The evidence has driven home the notion that there is indeed a compelling relationship between these seemingly unrelated variables. As we "putter" through the data, it becomes clear that this unusual correlation warrants further exploration.

These unexpected findings may prompt the question: Why did the golfer bring two pairs of pants? In case they got a "hole in one"! Such light-hearted moments aside, the robust statistical evidence underscores the need for deeper investigation into the underlying mechanisms at play.

At this juncture, it is pertinent to assert that no further research is needed in this area. The evidence presented is a "fairway" to understanding the interconnectedness of seemingly disparate phenomena. We encourage future researchers to tee up new inquiries and drive forward the boundaries of knowledge in this unconventional realm. After all, in the world of statistics, sometimes all it takes is a "beverage cart" of unexpected correlations to spark new insights.

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 Swinging with Stats: Teeing Up the Relationship Between US Open Golf Scores and the Receptionist Workforce in Hawaii. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of Statistical Sports Studies

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 Swinging with Stats: Teeing Up the Relationship Between US Open Golf Scores and the Receptionist Workforce in Hawaii. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Applied Statistical Research in Recreational Activities

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 Swinging with Stats: Teeing Up the Relationship Between US Open Golf Scores and the Receptionist Workforce in Hawaii with an abstract of The widespread fascination with golf and the curious world of statistics collide in this study, as we delve into the connection between the score of the US Open Golf winner and the number of receptionists in Hawaii. Utilizing data spanning from 2003 to 2022 sourced from Golfstats and the Bureau of Labor Statistics, our research team conducted a detailed analysis. An intriguing correlation coefficient of 0.6823408 emerged, with a statistically significant p-value of less than 0.01, shedding light on the surprising relationship between these two seemingly unrelated variables. Despite the initial skepticism regarding the possible relevance of golf scores to receptionist employment in Hawaii, the results provide compelling evidence to the contrary.
Not to tee you off with too many details, but our findings suggest that as the US Open Golf winner's score improves, there is a corresponding increase in the number of receptionists in Hawaii. While some may find this correlation a "fore"ceful conclusion, the data speak for themselves and offer a birdie's-eye view of this phenomenon. These unexpected results make us wonder whether there is an unnoticed bond between the precision of a golfer's swing and the need for coordinating appointments and phone calls in the Aloha State. Further research is required to uncover the underlying factors driving this apparent relationship and to determine if it holds true in other geographic regions. In examining these interconnected phenomena, our study inspires a new perspective on the intricate links between professional sports and labor market dynamics.

ChatGPT:

US Open Golf, Golf scores, Receptionist workforce, Hawaii, Golfstats, Bureau of Labor Statistics, Correlation coefficient, P-value, Professional sports, Labor market dynamics

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

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Data details

Score of the US Open Golf Winner
Detailed data title: Total US Open Golf Winner Score
Source: Golfstats
See what else correlates with Score of the US Open Golf Winner

The number of receptionists in Hawaii
Detailed data title: BLS estimate of receptionists and information clerks in Hawaii
Source: Bureau of Larbor Statistics
See what else correlates with The number of receptionists in Hawaii

Correlation r = 0.6823408 (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 = 0.4655890 (Coefficient of determination)
This means 46.6% of the change in the one variable (i.e., The number of receptionists in Hawaii) is predictable based on the change in the other (i.e., Score of the US Open Golf Winner) over the 20 years from 2003 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00092.^Show 0.0009180064525360326000000000
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 0.68 in 0.092% of random cases. Said differently, if you correlated 1,089 random variables^Note Which I absolutely did.
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.

[ 0.34, 0.86 ] 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
Score of the US Open Golf Winner (Score)	272	276	280	285	285	283	276	284	268	281	281	271	275	276	272	281	271	274	278	274
The number of receptionists in Hawaii (Laborers)	3770	4110	4320	4510	4380	4160	3950	3900	3540	3910	4050	3730	3400	3440	3680	4040	3940	3570	3540	3720

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([272,276,280,285,285,283,276,284,268,281,281,271,275,276,272,281,271,274,278,274,])
array_2 = np.array([3770,4110,4320,4510,4380,4160,3950,3900,3540,3910,4050,3730,3400,3440,3680,4040,3940,3570,3540,3720,])
array_1_name = "Score of the US Open Golf Winner"
array_2_name = "The number of receptionists in Hawaii"

# 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
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Line chart for only Score of the US Open Golf Winner
Line chart for only The number of receptionists in Hawaii
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The spurious research paper: Swinging with Stats: Teeing Up the Relationship Between US Open Golf Scores and the Receptionist Workforce in Hawaii

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Correlation ID: 1922 · Black Variable ID: 135 · Red Variable ID: 7063


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