Spurious correlation #3,502 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Moses and the second variable is The number of costume attendants in Washington. The chart goes from 2003 to 2021, 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 Popularity of the first name Moses and the second variable is The number of costume attendants in Washington. The chart goes from 2003 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the name Moses gained popularity, more and more parents were inspired to dress their children in adorable little baby Moses costumes for Halloween and other events. This sudden demand for tiny tunics, robes, and sandals led to a boom in the costume attendant industry in Washington, as they scrambled to keep up with the trend. Who knew that a baby name could part the sea of costume sales in the capital!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a vibrant costume shop in Washington, bustling with activity. Within the shop, rows of tiny flowing robes, intricate staffs, and epic beards are being meticulously crafted by a team of energetic costume attendants. Among the customers, parents proudly peruse the racks for the perfect Moses outfit for their beloved baby boy, as the popularity of the name Moses has caused a surge in demand for biblical costumes. The scene is filled with lively energy and creativity as the attendants cater to the growing demand for these elaborate and historical costumes. 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: Popularity of the first name Moses and The number of costume attendants in Washington. 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 comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s A Discovery magazine cover image Vaporwave Steampunk An image that looks like it is a scene from A Disney Movie
ChatGPT: A Discovery magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Popularity of the first name Moses and The number of costume attendants in Washington, in the following situation: Because the popularity of the first name Moses has been parting the seas of fashion trends, leading to a surge in costume attendants in Washington. As more babies are named Moses, parents want to celebrate by dressing them up as the biblical figure, causing a demand for costume attendants to create tiny staffs, flowing robes, and epic beards. This has led to a Red Sea of opportunities for costume shops and creative individuals, resulting in an increase in costume attendants in the state.. Keep the description simple.
ChatGPT: A bustling costume shop in Washington, with rows of tiny flowing robes, intricate staffs, and epic beards being meticulously crafted by a team of energetic costume attendants. Among the customers, parents proudly peruse the racks for the perfect Moses outfit for their beloved baby boy, as the popularity of the name Moses has caused a celebratory surge in demand for biblical costumes.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A Discovery magazine cover image ] and depicting this scene: A bustling costume shop in Washington, with rows of tiny flowing robes, intricate staffs, and epic beards being meticulously crafted by a team of energetic costume attendants. Among the customers, parents proudly peruse the racks for the perfect Moses outfit for their beloved baby boy, as the popularity of the name Moses has caused a celebratory surge in demand for biblical costumes. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a vibrant costume shop in Washington, bustling with activity. Within the shop, rows of tiny flowing robes, intricate staffs, and epic beards are being meticulously crafted by a team of energetic costume attendants. Among the customers, parents proudly peruse the racks for the perfect Moses outfit for their beloved baby boy, as the popularity of the name Moses has caused a surge in demand for biblical costumes. The scene is filled with lively energy and creativity as the attendants cater to the growing demand for these elaborate and historical costumes.

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

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

AI academic paper

(Because p < 0.01)

Splitting Hairs and Sparing Robes: The Moses Metaphor in Costume Attendant Numbers

Journal of Biblical Costume 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 Popularity of the first name Moses and The number of costume attendants in Washington. 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]]
Splitting Hairs and Sparing Robes: The Moses Metaphor in Costume Attendant Numbers

[[ABSTRACT]]
This study delves into the whimsical correlation between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. With an unconventional approach, we utilized data from the US Social Security Administration and the Bureau of Labor Statistics to assess this seemingly far-fetched relationship. In a surprising turn of events, our research team uncovered a correlation coefficient of 0.6759677 and p < 0.01 for the period spanning from 2003 to 2021. This investigation does not part the Red Sea of rationale for this association, but it does provide an enchanting glimpse into the unintended connections that can arise from the oddest of sources. While the motivations for such a correlation remain intriguingly elusive, our findings reveal a peculiar parallel that beckons for further study and perhaps a spot in the annals of mirthful statistical curiosities.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The relationship between a first name and the number of individuals employed as costume attendants is a peculiar area of inquiry. Traditionally, such research endeavors tend to gravitate toward more conventional factors such as economic indicators, demographic trends, or labor market conditions. However, in a departure from the norm, this study scrutinizes the connection between the popularity of the first name Moses and the number of costume attendants in Washington, D.C.
Moses, a name with a storied history and a wealth of cultural significance, often brings to mind biblical imagery, parting seas, and delivering commandments. It may seem inconceivable that the popularity of this particular name could be intertwined with the employment levels of those who assist with the attire needs of theatrical productions, theme parks, and other events requiring costume management.
Nonetheless, armed with an arsenal of statistical techniques and an irrepressible sense of curiosity, the research team set out to unravel this enigmatic web of correlation. Drawing on data from the US Social Security Administration and the Bureau of Labor Statistics, we ventured into uncharted waters to explore this seemingly whimsical association.
The intent behind this endeavor is not to glibly suggest causation where none exists; rather, it is to unearth and elucidate the intriguing patterns that may arise from unexpected quarters. We approach this investigation with the understanding that correlation does not necessarily imply causation, but it does prompt a lighthearted contemplation of the potential underlying forces driving this connection.
Perplexing as it may be, the undeniable statistical relationship unveiled in our analysis invites mirthful speculation and promises to enrich the scholarly landscape with an unconventional, if not downright amusing, thread of inquiry. As we delve into the data, we invite readers to partake in the lighthearted journey of discovery, one that underscores the captivating serendipity and levity that can be found in the most unanticipated of places.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The literature reviewed for this investigation includes an array of scholarly inquiries into the patterns and correlates of names, as well as the employment dynamics in the realm of costume attendants. Smith (2015) examined the socioeconomic and cultural influences on the popularity of first names, providing a comprehensive analysis of naming trends across different demographic groups. Doe and Jones (2018) delved into the labor market dynamics of the entertainment industry, shedding light on the occupational composition and employment patterns within the realm of costume design and management.

However, as we wade into the more esoteric depths of this peculiar correlation between the frequency of the name Moses and the cadre of costume attendants in the nation's capital, it is pertinent to consider alternative sources of insight. Works such as "The Moses Paradox: A Linguistic and Cultural Investigation" by Linguist et al. (2016) and "The Red Sea Dilemma: An Analysis of Name-Based Anomalies" by Historian and Allegorist (2019) provide intriguing, if tangentially related, perspectives that contribute to the broader contextualization of our inquiry.

Turning to the realm of fiction, the literary explorations of Moses in narratives can also provide subtle insights into the mystique that surrounds this name. Titles such as "Moses and the Wardrobe: A Tale of Biblical Couture" by Fictioneer (2012) and "The Costume Chronicles: A Moses Mystery" by Story Weaver (2016) offer a whimsical foray into the intersection of nomenclature and costume-related adventures, although their direct applicability to our empirical study may be dubious.

Furthermore, in the spirit of embracing the contemporary Zeitgeist, several social media posts have come to our attention that seem to touch upon the curious nexus of Moses and costumes. For instance, in a Twitter thread by @PunnyPundit, a user humorously juxtaposed the biblical gravitas of Moses with the sartorial spectacle of haute couture, implying a tantalizing parallel to our present investigation. Another viral TikTok video features a comedian musing about the potential correlation between the proliferation of Moses-themed Halloween costumes and the escalation of costume attendant numbers, sparking fervent but lighthearted online debate.

The academic and the anecdotal sources reviewed herein underscore the multifaceted nature of our inquiry, weaving a tapestry of scholarly, literary, and contemporary elucidations around the whimsical correlation that animates our investigation.

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 Popularity of the first name Moses and The number of costume attendants in Washington. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Bureau of Larbor Statistics . You used data from 2003 to 2021

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Splitting Hairs and Sparing Robes: The Moses Metaphor in Costume Attendant Numbers

[[ABSTRACT]]
This study delves into the whimsical correlation between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. With an unconventional approach, we utilized data from the US Social Security Administration and the Bureau of Labor Statistics to assess this seemingly far-fetched relationship. In a surprising turn of events, our research team uncovered a correlation coefficient of 0.6759677 and p < 0.01 for the period spanning from 2003 to 2021. This investigation does not part the Red Sea of rationale for this association, but it does provide an enchanting glimpse into the unintended connections that can arise from the oddest of sources. While the motivations for such a correlation remain intriguingly elusive, our findings reveal a peculiar parallel that beckons for further study and perhaps a spot in the annals of mirthful statistical curiosities.

[[INTRODUCTION]]
INTRODUCTION
The relationship between a first name and the number of individuals employed as costume attendants is a peculiar area of inquiry. Traditionally, such research endeavors tend to gravitate toward more conventional factors such as economic indicators, demographic trends, or labor market conditions. However, in a departure from the norm, this study scrutinizes the connection between the popularity of the first name Moses and the number of costume attendants in Washington, D.C.
Moses, a name with a storied history and a wealth of cultural significance, often brings to mind biblical imagery, parting seas, and delivering commandments. It may seem inconceivable that the popularity of this particular name could be intertwined with the employment levels of those who assist with the attire needs of theatrical productions, theme parks, and other events requiring costume management.
Nonetheless, armed with an arsenal of statistical techniques and an irrepressible sense of curiosity, the research team set out to unravel this enigmatic web of correlation. Drawing on data from the US Social Security Administration and the Bureau of Labor Statistics, we ventured into uncharted waters to explore this seemingly whimsical association.
The intent behind this endeavor is not to glibly suggest causation where none exists; rather, it is to unearth and elucidate the intriguing patterns that may arise from unexpected quarters. We approach this investigation with the understanding that correlation does not necessarily imply causation, but it does prompt a lighthearted contemplation of the potential underlying forces driving this connection.
Perplexing as it may be, the undeniable statistical relationship unveiled in our analysis invites mirthful speculation and promises to enrich the scholarly landscape with an unconventional, if not downright amusing, thread of inquiry. As we delve into the data, we invite readers to partake in the lighthearted journey of discovery, one that underscores the captivating serendipity and levity that can be found in the most unanticipated of places.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

METHODOLOGY

To investigate the ostensibly whimsical correlation between the popularity of the first name Moses and the number of costume attendants in Washington, D.C., our research team embarked on a methodologically rigorous yet delightfully unconventional research endeavor.

Data Collection:
We gathered data from a variety of sources, including the US Social Security Administration and the Bureau of Labor Statistics, for the years 2003 to 2021. The US Social Security Administration provided information on the frequency of the first name Moses, while the Bureau of Labor Statistics furnished data on the number of individuals employed as costume attendants in Washington, D.C. The dual reliance on these seemingly divergent datasets allowed for a comprehensive exploration of the purported connection between nomenclature and occupational choices.

Statistical Analysis:
Employing cutting-edge statistical techniques, including correlation analysis and regression modeling, we teased out the relationship between the popularity of the name Moses and the number of costume attendants in Washington, D.C. Our analysis involved calculating correlation coefficients, p-values, and confidence intervals with an exacting attention to detail. While the veritable sea of data might have seemed daunting, our research team navigated its complexities with the precision of Moses parting the Red Sea.

Control Variables:
Recognizing the import of controlling for potential confounding factors, we incorporated demographic characteristics, economic indicators, and regional employment trends into our analysis. Additionally, we conducted sensitivity analyses to assess the robustness of our findings and to ensure that our results were not unduly influenced by extraneous variables that might obscure the true relationship between the popularity of the name Moses and the number of costume attendants.

Ethical Considerations:
In adherence to the highest ethical standards, our research team obtained all data from reputable and publicly available sources. We ensured the anonymity of individuals represented in the datasets and upheld the principles of data privacy and confidentiality.

Limitations:
It is imperative to acknowledge the limitations inherent in our approach. While our study offers an illuminating glimpse into the unexpected nexus between the name Moses and the vocation of costume attendants, it is essential to exercise caution in inferring causation from the observed correlation. Furthermore, the generalizability of our findings beyond the specific context of Washington, D.C. warrants further scrutiny.

In summary, our methodological framework, though imbued with a touch of whimsy, epitomizes the confluence of meticulous analysis and unyielding investigative spirit. With this robust approach, we set the stage for the revelatory examination of the curious correspondence between nomenclature and occupational predilections, thereby affirming the inherent levity and intrigue within the realm of empirical inquiry.

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 Popularity of the first name Moses and The number of costume attendants in Washington. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Bureau of Larbor Statistics .

For the time period 2003 to 2021, you found a correlation 0.6759677, r-squared of 0.4569324, 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]]
Splitting Hairs and Sparing Robes: The Moses Metaphor in Costume Attendant Numbers

[[ABSTRACT]]
This study delves into the whimsical correlation between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. With an unconventional approach, we utilized data from the US Social Security Administration and the Bureau of Labor Statistics to assess this seemingly far-fetched relationship. In a surprising turn of events, our research team uncovered a correlation coefficient of 0.6759677 and p < 0.01 for the period spanning from 2003 to 2021. This investigation does not part the Red Sea of rationale for this association, but it does provide an enchanting glimpse into the unintended connections that can arise from the oddest of sources. While the motivations for such a correlation remain intriguingly elusive, our findings reveal a peculiar parallel that beckons for further study and perhaps a spot in the annals of mirthful statistical curiosities.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
The relationship between a first name and the number of individuals employed as costume attendants is a peculiar area of inquiry. Traditionally, such research endeavors tend to gravitate toward more conventional factors such as economic indicators, demographic trends, or labor market conditions. However, in a departure from the norm, this study scrutinizes the connection between the popularity of the first name Moses and the number of costume attendants in Washington, D.C.
Moses, a name with a storied history and a wealth of cultural significance, often brings to mind biblical imagery, parting seas, and delivering commandments. It may seem inconceivable that the popularity of this particular name could be intertwined with the employment levels of those who assist with the attire needs of theatrical productions, theme parks, and other events requiring costume management.
Nonetheless, armed with an arsenal of statistical techniques and an irrepressible sense of curiosity, the research team set out to unravel this enigmatic web of correlation. Drawing on data from the US Social Security Administration and the Bureau of Labor Statistics, we ventured into uncharted waters to explore this seemingly whimsical association.
The intent behind this endeavor is not to glibly suggest causation where none exists; rather, it is to unearth and elucidate the intriguing patterns that may arise from unexpected quarters. We approach this investigation with the understanding that correlation does not necessarily imply causation, but it does prompt a lighthearted contemplation of the potential underlying forces driving this connection.
Perplexing as it may be, the undeniable statistical relationship unveiled in our analysis invites mirthful speculation and promises to enrich the scholarly landscape with an unconventional, if not downright amusing, thread of inquiry. As we delve into the data, we invite readers to partake in the lighthearted journey of discovery, one that underscores the captivating serendipity and levity that can be found in the most unanticipated of places.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of data collected from the US Social Security Administration and the Bureau of Labor Statistics revealed a rather unexpected and, some might even say, whimsical, connection between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. For the time period spanning from 2003 to 2021, a correlation coefficient of 0.6759677 and an r-squared value of 0.4569324 were calculated, indicating a moderate to strong positive relationship between the two variables. Additionally, the p-value was found to be less than 0.01, suggesting that this correlation is statistically significant.

Figure 1 presents a scatterplot illustrating the notable correlation between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. The points on the scatterplot are tightly clustered around a best-fit line, demonstrating the strength of the relationship between these seemingly unrelated variables.

We must acknowledge that while we found this correlation to be statistically significant, it is important to maintain a degree of caution in interpreting these findings. Correlation does not imply causation, and it would be rather far-fetched to suggest that the popularity of the name Moses directly affects the demand for costume attendants. These results should therefore be approached with a lighthearted sense of humor and scholarly curiosity, as they speak to the unexpected and delightful coincidences that can emerge from the most unlikely of sources.

The discovery of this correlation neither parts the Red Sea of rationale for this association nor delivers a set of commandments for its understanding. Rather, it offers a playful glimpse into the serendipitous connections that can arise from the most amusing of sources. The motivations behind this curious correlation remain delightfully elusive, prompting further exploration and a touch of scholarly whimsy. Therefore, we invite readers to join us in this endeavor, as we unravel and appreciate the lighthearted statistical curiosities that pepper the academic landscape.

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 Popularity of the first name Moses and The number of costume attendants in Washington. 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]]
Splitting Hairs and Sparing Robes: The Moses Metaphor in Costume Attendant Numbers

[[ABSTRACT]]
This study delves into the whimsical correlation between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. With an unconventional approach, we utilized data from the US Social Security Administration and the Bureau of Labor Statistics to assess this seemingly far-fetched relationship. In a surprising turn of events, our research team uncovered a correlation coefficient of 0.6759677 and p < 0.01 for the period spanning from 2003 to 2021. This investigation does not part the Red Sea of rationale for this association, but it does provide an enchanting glimpse into the unintended connections that can arise from the oddest of sources. While the motivations for such a correlation remain intriguingly elusive, our findings reveal a peculiar parallel that beckons for further study and perhaps a spot in the annals of mirthful statistical curiosities.

[[LITERATURE REVIEW]]
The literature reviewed for this investigation includes an array of scholarly inquiries into the patterns and correlates of names, as well as the employment dynamics in the realm of costume attendants. Smith (2015) examined the socioeconomic and cultural influences on the popularity of first names, providing a comprehensive analysis of naming trends across different demographic groups. Doe and Jones (2018) delved into the labor market dynamics of the entertainment industry, shedding light on the occupational composition and employment patterns within the realm of costume design and management.
However, as we wade into the more esoteric depths of this peculiar correlation between the frequency of the name Moses and the cadre of costume attendants in the nation's capital, it is pertinent to consider alternative sources of insight. Works such as "The Moses Paradox: A Linguistic and Cultural Investigation" by Linguist et al. (2016) and "The Red Sea Dilemma: An Analysis of Name-Based Anomalies" by Historian and Allegorist (2019) provide intriguing, if tangentially related, perspectives that contribute to the broader contextualization of our inquiry.
Turning to the realm of fiction, the literary explorations of Moses in narratives can also provide subtle insights into the mystique that surrounds this name. Titles such as "Moses and the Wardrobe: A Tale of Biblical Couture" by Fictioneer (2012) and "The Costume Chronicles: A Moses Mystery" by Story Weaver (2016) offer a whimsical foray into the intersection of nomenclature and costume-related adventures, although their direct applicability to our empirical study may be dubious.
Furthermore, in the spirit of embracing the contemporary Zeitgeist, several social media posts have come to our attention that seem to touch upon the curious nexus of Moses and costumes. For instance, in a Twitter thread by @PunnyPundit, a user humorously juxtaposed the biblical gravitas of Moses with the sartorial spectacle of haute couture, implying a tantalizing parallel to our present investigation. Another viral TikTok video features a comedian musing about the potential correlation between the proliferation of Moses-themed Halloween costumes and the escalation of costume attendant numbers, sparking fervent but lighthearted online debate.
The academic and the anecdotal sources reviewed herein underscore the multifaceted nature of our inquiry, weaving a tapestry of scholarly, literary, and contemporary elucidations around the whimsical correlation that animates our investigation.

[[RESULTS]]
The analysis of data collected from the US Social Security Administration and the Bureau of Labor Statistics revealed a rather unexpected and, some might even say, whimsical, connection between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. For the time period spanning from 2003 to 2021, a correlation coefficient of 0.6759677 and an r-squared value of 0.4569324 were calculated, indicating a moderate to strong positive relationship between the two variables. Additionally, the p-value was found to be less than 0.01, suggesting that this correlation is statistically significant.
Figure 1 presents a scatterplot illustrating the notable correlation between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. The points on the scatterplot are tightly clustered around a best-fit line, demonstrating the strength of the relationship between these seemingly unrelated variables.
We must acknowledge that while we found this correlation to be statistically significant, it is important to maintain a degree of caution in interpreting these findings. Correlation does not imply causation, and it would be rather far-fetched to suggest that the popularity of the name Moses directly affects the demand for costume attendants. These results should therefore be approached with a lighthearted sense of humor and scholarly curiosity, as they speak to the unexpected and delightful coincidences that can emerge from the most unlikely of sources.
The discovery of this correlation neither parts the Red Sea of rationale for this association nor delivers a set of commandments for its understanding. Rather, it offers a playful glimpse into the serendipitous connections that can arise from the most amusing of sources. The motivations behind this curious correlation remain delightfully elusive, prompting further exploration and a touch of scholarly whimsy. Therefore, we invite readers to join us in this endeavor, as we unravel and appreciate the lighthearted statistical curiosities that pepper the academic landscape.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The curious correlation we have unearthed between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. presents a fascinating enigma that demands consideration. Our findings not only support prior research on the socioeconomic and cultural influences on naming trends, but they also add a whimsical twist to the occupational composition and employment patterns within the entertainment industry.

The literature review teased us with the linguistic and cultural investigation of the "Moses Paradox," and our results have lent credence to the notion that this paradox may not be purely hypothetical. Similar to the tongue-in-cheek "Moses and the Wardrobe" tale, it appears that there may indeed be a subtle connection between the titular biblical figure and the sartorial spectacle of costume attendants. It seems the Moses metaphor in the realm of names and employment dynamics is not just a whimsical flight of fancy but a statistically significant phenomenon.

Our findings are reminiscent of the amusing Twitter thread by @PunnyPundit, where the juxtaposition of biblical gravitas and haute couture takes on a new meaning. Furthermore, the online debate sparked by a viral TikTok video pondering Moses-themed Halloween costumes and costume attendant numbers seems to have unwittingly tapped into an unexpected reality with our empirical findings.

While the link between the popularity of the name Moses and the demand for costume attendants remains delightfully elusive, our investigation has illuminated an intriguing connection. This, in turn, resonates with the multifaceted nature of our inquiry, echoing the scholarly, literary, and contemporary elucidations encountered in the literature review.

Our results not only highlight the capricious nature of statistical correlations but also underscore the enchanting serendipity that can manifest from the most improbable of sources. As we dance through this whimsical statistical wonderland, our invitation to scholars and enthusiasts alike is to appreciate and explore the delightful statistical curiosities that pepper the academic landscape. The unintended connections that arise from the oddest of sources may not part the Red Sea of rationale, but they do certainly part the academic seriousness with a whimsical and enigmatic twinkle.

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 Popularity of the first name Moses and The number of costume attendants in Washington. 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]]
Splitting Hairs and Sparing Robes: The Moses Metaphor in Costume Attendant Numbers

[[ABSTRACT]]
This study delves into the whimsical correlation between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. With an unconventional approach, we utilized data from the US Social Security Administration and the Bureau of Labor Statistics to assess this seemingly far-fetched relationship. In a surprising turn of events, our research team uncovered a correlation coefficient of 0.6759677 and p < 0.01 for the period spanning from 2003 to 2021. This investigation does not part the Red Sea of rationale for this association, but it does provide an enchanting glimpse into the unintended connections that can arise from the oddest of sources. While the motivations for such a correlation remain intriguingly elusive, our findings reveal a peculiar parallel that beckons for further study and perhaps a spot in the annals of mirthful statistical curiosities.

[[INTRDUCTION]]
INTRODUCTION
The relationship between a first name and the number of individuals employed as costume attendants is a peculiar area of inquiry. Traditionally, such research endeavors tend to gravitate toward more conventional factors such as economic indicators, demographic trends, or labor market conditions. However, in a departure from the norm, this study scrutinizes the connection between the popularity of the first name Moses and the number of costume attendants in Washington, D.C.
Moses, a name with a storied history and a wealth of cultural significance, often brings to mind biblical imagery, parting seas, and delivering commandments. It may seem inconceivable that the popularity of this particular name could be intertwined with the employment levels of those who assist with the attire needs of theatrical productions, theme parks, and other events requiring costume management.
Nonetheless, armed with an arsenal of statistical techniques and an irrepressible sense of curiosity, the research team set out to unravel this enigmatic web of correlation. Drawing on data from the US Social Security Administration and the Bureau of Labor Statistics, we ventured into uncharted waters to explore this seemingly whimsical association.
The intent behind this endeavor is not to glibly suggest causation where none exists; rather, it is to unearth and elucidate the intriguing patterns that may arise from unexpected quarters. We approach this investigation with the understanding that correlation does not necessarily imply causation, but it does prompt a lighthearted contemplation of the potential underlying forces driving this connection.
Perplexing as it may be, the undeniable statistical relationship unveiled in our analysis invites mirthful speculation and promises to enrich the scholarly landscape with an unconventional, if not downright amusing, thread of inquiry. As we delve into the data, we invite readers to partake in the lighthearted journey of discovery, one that underscores the captivating serendipity and levity that can be found in the most unanticipated of places.

[[RESULTS]]
The analysis of data collected from the US Social Security Administration and the Bureau of Labor Statistics revealed a rather unexpected and, some might even say, whimsical, connection between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. For the time period spanning from 2003 to 2021, a correlation coefficient of 0.6759677 and an r-squared value of 0.4569324 were calculated, indicating a moderate to strong positive relationship between the two variables. Additionally, the p-value was found to be less than 0.01, suggesting that this correlation is statistically significant.
Figure 1 presents a scatterplot illustrating the notable correlation between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. The points on the scatterplot are tightly clustered around a best-fit line, demonstrating the strength of the relationship between these seemingly unrelated variables.
We must acknowledge that while we found this correlation to be statistically significant, it is important to maintain a degree of caution in interpreting these findings. Correlation does not imply causation, and it would be rather far-fetched to suggest that the popularity of the name Moses directly affects the demand for costume attendants. These results should therefore be approached with a lighthearted sense of humor and scholarly curiosity, as they speak to the unexpected and delightful coincidences that can emerge from the most unlikely of sources.
The discovery of this correlation neither parts the Red Sea of rationale for this association nor delivers a set of commandments for its understanding. Rather, it offers a playful glimpse into the serendipitous connections that can arise from the most amusing of sources. The motivations behind this curious correlation remain delightfully elusive, prompting further exploration and a touch of scholarly whimsy. Therefore, we invite readers to join us in this endeavor, as we unravel and appreciate the lighthearted statistical curiosities that pepper the academic landscape.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the correlation between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. has unearthed a statistically significant, albeit delightfully perplexing, association. The robust correlation coefficient of 0.6759677 and the p-value of less than 0.01 not only raised eyebrows but also elicited a fair share of chuckles from our research team.

Despite the veritable Red Sea of data at our disposal, we must exercise caution in inferring causation based on this correlation. While the idea of parents naming their offspring Moses leading to a surge in demand for costume attendants is a whimsical notion, a more prudent explanation likely lies beyond the tablets of statistical analysis.

Nonetheless, the allure of this unexpected correlation beckons further exploration. The peculiar parallel between a biblical moniker and the sartorial guardians of the nation’s capital warrants a spot in the annals of mirthful statistical curiosities. While our findings may not redefine the academic Pantheon, they certainly add a kooky twist to the scholarly tapestry.

In summary, the mirthful statistical curiosities engendered by this correlation entreatingly prompt further inquiry and perhaps a nod of playful recognition in the hallowed halls of academia. With a twinkle in our eye and a raised eyebrow, we invite fellow scholars to appreciate the whimsical randomness that is part and parcel of statistical exploration.

In concluding this pseudo-scientific romp, we assert that no more research is needed in this area. After all, sometimes the most entertaining statistical curiosities are best enjoyed as enigmatic anomalies, without the burden of unwrapping their every mysterious layer.

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 Splitting Hairs and Sparing Robes: The Moses Metaphor in Costume Attendant Numbers. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Biblical Costume 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 Splitting Hairs and Sparing Robes: The Moses Metaphor in Costume Attendant Numbers. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Biblical Fashion Studies

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 Splitting Hairs and Sparing Robes: The Moses Metaphor in Costume Attendant Numbers with an abstract of This study delves into the whimsical correlation between the popularity of the first name Moses and the number of costume attendants in Washington, D.C. With an unconventional approach, we utilized data from the US Social Security Administration and the Bureau of Labor Statistics to assess this seemingly far-fetched relationship. In a surprising turn of events, our research team uncovered a correlation coefficient of 0.6759677 and p < 0.01 for the period spanning from 2003 to 2021. This investigation does not part the Red Sea of rationale for this association, but it does provide an enchanting glimpse into the unintended connections that can arise from the oddest of sources. While the motivations for such a correlation remain intriguingly elusive, our findings reveal a peculiar parallel that beckons for further study and perhaps a spot in the annals of mirthful statistical curiosities.

ChatGPT:

"Moses popularity", "costume attendants Washington DC", "US Social Security Administration data", "Bureau of Labor Statistics", "correlation coefficient Moses costume attendants", "Moses name popularity correlation"

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

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Data details

Popularity of the first name Moses
Detailed data title: Babies of all sexes born in the US named Moses
Source: US Social Security Administration
See what else correlates with Popularity of the first name Moses

The number of costume attendants in Washington
Detailed data title: BLS estimate of costume attendants in Washington
Source: Bureau of Larbor Statistics
See what else correlates with The number of costume attendants in Washington

Correlation r = 0.6759677 (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 = 0.4569324 (Coefficient of determination)
This means 45.7% of the change in the one variable (i.e., The number of costume attendants in Washington) is predictable based on the change in the other (i.e., Popularity of the first name Moses) over the 19 years from 2003 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.0015.^Show 0.0014878157799293116000000000
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 0.15% of random cases. Said differently, if you correlated 672 random variables^Note Which I absolutely did.
with the same 18 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 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.

[ 0.32, 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
Popularity of the first name Moses (Babies born)	503	493	478	617	606	562	543	515	504	484	604	586	642	668	629	584	560	587	569
The number of costume attendants in Washington (Costume Attendants)	60	40	30	70	60	70	80	70	60	40	80	70	110	80	100	50	60	70	30

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.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

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([503,493,478,617,606,562,543,515,504,484,604,586,642,668,629,584,560,587,569,])
array_2 = np.array([60,40,30,70,60,70,80,70,60,40,80,70,110,80,100,50,60,70,30,])
array_1_name = "Popularity of the first name Moses"
array_2_name = "The number of costume attendants in Washington"

# 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.
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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 Popularity of the first name Moses
Line chart for only The number of costume attendants in Washington
AI-generated correlation image
The spurious research paper: Splitting Hairs and Sparing Robes: The Moses Metaphor in Costume Attendant Numbers

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Correlation ID: 3502 · Black Variable ID: 3101 · Red Variable ID: 15764


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