Spurious correlation #2,179 · 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 Alma and the second variable is Lennar's stock price (LEN). The chart goes from 2002 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 Popularity of the first name Alma and the second variable is Lennar's stock price (LEN). The chart goes from 2002 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

Every time a baby was named Alma, a secret code was activated in the stock market, causing a surge in demand for Lennar's homes. The company had no idea why this was happening, but they were loving the baby name trend.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image that captures a bustling cybernetic cityscape with a focus on a striking digital display showcasing the stock price of Lennar Corporation. Adjacent to the digital screen, illustrate a vibrant playground scene with parents engaged in conversation about the growing popularity of the name Alma for their newborn daughters. The artwork should effectively blend the futuristic elements of the city with the more intimate everyday interactions at the playground, creating a dynamic and visually compelling composition. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

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

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Popularity of the first name Alma and Lennar's stock price. 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: Photorealism Cute 2D animation A scene from Skyrim Cybernetic art Symbolism
ChatGPT: Cybernetic art

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Popularity of the first name Alma and Lennar's stock price together. Keep the description simple.
ChatGPT: In a bustling city, a large digital screen is showing the latest stock price of Lennar Corporation, while nearby, a group of parents at a playground chat about the popularity of the name Alma for their newborn daughters.

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: [ Cybernetic art ] and depicting this scene: In a bustling city, a large digital screen is showing the latest stock price of Lennar Corporation, while nearby, a group of parents at a playground chat about the popularity of the name Alma for their newborn daughters. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that captures a bustling cybernetic cityscape with a focus on a striking digital display showcasing the stock price of Lennar Corporation. Adjacent to the digital screen, illustrate a vibrant playground scene with parents engaged in conversation about the growing popularity of the name Alma for their newborn daughters. The artwork should effectively blend the futuristic elements of the city with the more intimate everyday interactions at the playground, creating a dynamic and visually compelling composition.

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

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

AI academic paper

(Because p < 0.01)

The Alma-Matter Effect: An Alma-nac of Name Popularity and Stock Performance

The Journal of Quirky Economics

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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Alma and Lennar's stock price (LEN). 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 you might move on to cartoons and children's shows that you watched for research.

Here is the title and abstract of the paper:
[[TITLE]]
"The Alma-Matter Effect: An Alma-nac of Name Popularity and Stock Performance"

[[ABSTRACT]]
This study examines the surprising connection between the popularity of the first name "Alma" and the stock price of Lennar Corporation (LEN) from 2002 to 2022. Leveraging data from the US Social Security Administration and LSEG Analytics (Refinitiv), our research team set out to unravel this peculiar correlation. Our findings revealed a correlation coefficient of 0.8253924 and p < 0.01, highlighting a statistically significant relationship between the two variables. This unexpected relationship prompts further investigation and has potential implications for both the financial markets and expectant parents searching for auspicious baby names.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the curious and convoluted world of stock market research, it is not uncommon to stumble upon unexpected correlations and peculiar relationships. While most analysts pore over financial statements and economic indicators, we, as intrepid researchers, have set our sights on a rather unconventional pair of variables – the popularity of the first name "Alma" and the stock price of Lennar Corporation (LEN).
As we embarked on this odyssey of data analysis, we couldn't help but marvel at the sheer whimsy of our chosen subjects. A name synonymous with nurturing and strength, "Alma," and a residential construction company, Lennar Corporation, seem like an unlikely duo destined for an entangled waltz through statistical analysis.
The allure of uncovering this enigmatic correlation was not lost on us, as we navigated through data sets and regression analyses with a mix of trepidation and unbridled curiosity. Our pursuit was not simply an academic exercise, but a quest to shed light on a mystifying association that beckoned to be explored.
In this paper, we present our findings on what we have affectionately coined the "Alma-Matter Effect," a play on the alma mater concept and the profound impact of a seemingly innocuous name on the performance of Lennar's stock. Through meticulous scrutiny of historical records and statistical methods, we aim to unravel the perplexing link between the popularity of the name "Alma" and the fluctuations in Lennar's stock price.
But before we delve into the labyrinth of statistics and financial conjecture, it is important to acknowledge the sheer whimsy of our inquiry. After all, who would have thought that a delightful moniker like "Alma" could hold sway over the machinations of the stock market? Join us as we unravel this captivating tale of names and numbers, and perhaps, uncover the quirky nuances of the financial world along the way.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

As we delve into the peculiar correlation between the popularity of the first name "Alma" and the stock performance of Lennar Corporation (LEN), we turn to the existing body of literature on unusual name effects and unorthodox stock market predictors. Smith et al. (2010) speculated on the potential influence of moniker magnetism in their study "Name Games: Unconventional Factors Affecting Stock Prices," where they proposed that certain names may exude a mysterious aura that impacts market dynamics. Following this train of thought, Doe (2015) examined the psychological implications of unique names in "The Psychology of Peculiar Names and Their Financial Fallout," delving into the subconscious biases associated with uncommon appellations.

Jones (2018) contributed to the discourse with "Beyond Bar Charts: Unorthodox Indicators of Market Movements," in which the author explored the enigmatic world of unconventional predictors, including but not limited to peculiar name popularity. This eclectic body of research paved the way for our investigation into the "Alma-Matter Effect," a term we have coined to encapsulate the improbable interplay between a name steeped in history and a conglomerate shaping the future of residential development.

As we meander through the labyrinth of academia, it is paramount to acknowledge the tangential sources that have inadvertently shed light on our unconventional pursuit. In "Freakonomics" by Steven D. Levitt and Stephen J. Dubner, the authors tiptoed around the outskirts of quirky correlations, seeding our fascination with the unexpected and the unorthodox. Likewise, "Superforecasting" by Philip E. Tetlock and Dan Gardner provided anecdotal evidence of uncanny predictors and outliers, lending credence to our seemingly absurd endeavor.

Venturing into the realm of fiction, "The Da Vinci Code" by Dan Brown and "The Name of the Rose" by Umberto Eco may appear largely unrelated to our study. However, their narrative on unraveling mysteries and delving into cryptic enigmas served as a source of inspiration, reminding us that serendipity often lurks in the unlikeliest of places.

Unabashedly embracing a light-hearted approach to our academic pursuit, we cannot discount the subtle influence of childhood cartoons and whimsical literature on our perspective. Hours spent unraveling the zany antics of "Scooby-Doo" and the surreal adventures of "Alice in Wonderland" have inadvertently nurtured a keen eye for the absurd and the unexpected, qualities that have undoubtedly colored our interpretation of our findings.

As we chart our course through this uncharted terrain, it is our hope that our scholarly escapade through the odd and the offbeat will offer not only academic credence but also a measure of whimsy to the otherwise staid landscape of financial research.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Alma and Lennar's stock price (LEN). Make lots of jokes, goofy observations, and puns.

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]]
"The Alma-Matter Effect: An Alma-nac of Name Popularity and Stock Performance"

[[ABSTRACT]]
This study examines the surprising connection between the popularity of the first name "Alma" and the stock price of Lennar Corporation (LEN) from 2002 to 2022. Leveraging data from the US Social Security Administration and LSEG Analytics (Refinitiv), our research team set out to unravel this peculiar correlation. Our findings revealed a correlation coefficient of 0.8253924 and p < 0.01, highlighting a statistically significant relationship between the two variables. This unexpected relationship prompts further investigation and has potential implications for both the financial markets and expectant parents searching for auspicious baby names.

[[LITERATURE REVIEW]]
As we delve into the peculiar correlation between the popularity of the first name "Alma" and the stock performance of Lennar Corporation (LEN), we turn to the existing body of literature on unusual name effects and unorthodox stock market predictors. Smith et al. (2010) speculated on the potential influence of moniker magnetism in their study "Name Games: Unconventional Factors Affecting Stock Prices," where they proposed that certain names may exude a mysterious aura that impacts market dynamics. Following this train of thought, Doe (2015) examined the psychological implications of unique names in "The Psychology of Peculiar Names and Their Financial Fallout," delving into the subconscious biases associated with uncommon appellations.
Jones (2018) contributed to the discourse with "Beyond Bar Charts: Unorthodox Indicators of Market Movements," in which the author explored the enigmatic world of unconventional predictors, including but not limited to peculiar name popularity. This eclectic body of research paved the way for our investigation into the "Alma-Matter Effect," a term we have coined to encapsulate the improbable interplay between a name steeped in history and a conglomerate shaping the future of residential development.
As we meander through the labyrinth of academia, it is paramount to acknowledge the tangential sources that have inadvertently shed light on our unconventional pursuit. In "Freakonomics" by Steven D. Levitt and Stephen J. Dubner, the authors tiptoed around the outskirts of quirky correlations, seeding our fascination with the unexpected and the unorthodox. Likewise, "Superforecasting" by Philip E. Tetlock and Dan Gardner provided anecdotal evidence of uncanny predictors and outliers, lending credence to our seemingly absurd endeavor.
Venturing into the realm of fiction, "The Da Vinci Code" by Dan Brown and "The Name of the Rose" by Umberto Eco may appear largely unrelated to our study. However, their narrative on unraveling mysteries and delving into cryptic enigmas served as a source of inspiration, reminding us that serendipity often lurks in the unlikeliest of places.
Unabashedly embracing a light-hearted approach to our academic pursuit, we cannot discount the subtle influence of childhood cartoons and whimsical literature on our perspective. Hours spent unraveling the zany antics of "Scooby-Doo" and the surreal adventures of "Alice in Wonderland" have inadvertently nurtured a keen eye for the absurd and the unexpected, qualities that have undoubtedly colored our interpretation of our findings.
As we chart our course through this uncharted terrain, it is our hope that our scholarly escapade through the odd and the offbeat will offer not only academic credence but also a measure of whimsy to the otherwise staid landscape of financial research.

[[RESULTS]]
The results of our analysis unveiled a striking correlation between the popularity of the first name "Alma" and the stock price of Lennar Corporation (LEN) from 2002 to 2022. The correlation coefficient of 0.8253924 indicates a strong positive relationship between the two variables. In other words, as the popularity of the name "Alma" waxed or waned, the stock price of Lennar seemed to dance in synchrony, reminiscent of a whimsical duet between unexpected partners.
The r-squared value of 0.6812726 further validates the robustness of this correlation, capturing over 68% of the variation in Lennar's stock price attributable to the popularity of the name "Alma." It's as if the name "Alma" whispered sweet somethings to Lennar's stock price, influencing its movements with an air of mysterious enchantment.
Moreover, the p-value of less than 0.01 indicates that this correlation is not just some fluke of statistical happenstance. No, dear reader, this is a bona fide, statistically significant connection that begs for further scrutiny and contemplation. It's as if the fates themselves conspired to entwine the destiny of "Alma" with the fortunes of Lennar, creating a saga that defies conventional logic and beckons us to ponder the capricious nature of correlations.
In Figure 1, our scatterplot adds a dash of visual flair, showcasing the unmistakable alignment of "Alma" popularity and Lennar's stock price. Behold, as the data points dance across the Cartesian plane, engaging in a harmonious choreography that defies the limits of reason and plunges headlong into the realm of delightful peculiarity.
These findings not only raise eyebrows in the world of financial analysis but also hint at a profound connection between the seemingly mundane choice of a name and the vicissitudes of the stock market. As we savor this astonishing revelation, we are reminded that in the labyrinthine landscape of statistical inquiry, even the most improbable pairings can yield unexpected insights and provoke a chuckle or two along the way.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our findings have unraveled a truly extraordinary connection between the popularity of the first name "Alma" and the stock performance of Lennar Corporation (LEN) that challenges conventional wisdom and tickles the fancy of both the financial and the fantastical. As we journey back through the literary musings in our literature review, we find ourselves traversing the terrain of whimsy and wonder, discovering unexpected allies in our pursuit of the improbable.

First, let us ponder the implications of Smith et al.'s (2010) proposition of moniker magnetism. Our results align with their speculative conjecture, albeit in a manner that can only be described as enchantingly unforeseen. The aura of "Alma" appears to have woven itself into the esoteric fabric of Lennar's stock price, exerting an influence that defies conventional explanation. It's as if the name "Alma" whispered sweet somethings to Lennar's stock price, influencing its movements with an air of mysterious enchantment—much like a fantastical tale spun from the loom of serendipity.

Furthermore, Doe's (2015) exploration of the psychological implications of unique names takes on an entirely unexpected resonance in light of our findings. The subconscious biases associated with uncommon appellations seem to have transcended the mundane realm of nomenclature, transforming into a captivating dance of statistical significance. Our results not only bolster Doe's conjecture but elevate it to an extraordinary symphony of name-centric influence that orchestrates itself across the stage of Lennar's stock performance.

In complementing Jones' (2018) venture into the enigmatic world of unconventional predictors, our study veers into uncharted eccentricity, elevating the discourse to an operatic crescendo of statistical intrigue and improbable correlations. Indeed, the peculiarity of our findings serves as a reminder that the pursuit of knowledge is not merely a solemn march through the hallowed halls of academia, but a whimsical romp where the unexpected tickles our intellectual fancy and leaves us gasping in delightful disbelief.

Venturing into the realm of fiction, our study's revelatory unveiling is akin to deciphering a cryptic enigma in the pages of "The Da Vinci Code," where the seemingly disparate threads coalesce into a tapestry of intrigue and revelation. In the spirit of intrigue and serendipity, our findings beckon us to embrace the whimsy of statistical inquiry and marvel at the unfathomable connections that lay veiled beneath the surface of rational analysis.

Unabashedly reveling in the zany allure of our findings, we are reminded that statistical inquiry is not merely a dispassionate pursuit of numbers, but a dance of discovery where even the most seemingly unassuming variables can twirl into the spotlight, leaving us spellbound by their unexpected performance. As we savor the delightful peculiarity of our results, we extend an open invitation to fellow researchers and merrymakers to join us in reveling in the whimsical landscape of statistical inquiry, where the most improbable pairings may yield unexpected insights and provoke a chuckle or two along the way.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Alma and Lennar's stock price (LEN). Make lots of jokes, goofy observations, and puns.

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]]
"The Alma-Matter Effect: An Alma-nac of Name Popularity and Stock Performance"

[[ABSTRACT]]
This study examines the surprising connection between the popularity of the first name "Alma" and the stock price of Lennar Corporation (LEN) from 2002 to 2022. Leveraging data from the US Social Security Administration and LSEG Analytics (Refinitiv), our research team set out to unravel this peculiar correlation. Our findings revealed a correlation coefficient of 0.8253924 and p < 0.01, highlighting a statistically significant relationship between the two variables. This unexpected relationship prompts further investigation and has potential implications for both the financial markets and expectant parents searching for auspicious baby names.

[[INTRDUCTION]]
In the curious and convoluted world of stock market research, it is not uncommon to stumble upon unexpected correlations and peculiar relationships. While most analysts pore over financial statements and economic indicators, we, as intrepid researchers, have set our sights on a rather unconventional pair of variables – the popularity of the first name "Alma" and the stock price of Lennar Corporation (LEN).
As we embarked on this odyssey of data analysis, we couldn't help but marvel at the sheer whimsy of our chosen subjects. A name synonymous with nurturing and strength, "Alma," and a residential construction company, Lennar Corporation, seem like an unlikely duo destined for an entangled waltz through statistical analysis.
The allure of uncovering this enigmatic correlation was not lost on us, as we navigated through data sets and regression analyses with a mix of trepidation and unbridled curiosity. Our pursuit was not simply an academic exercise, but a quest to shed light on a mystifying association that beckoned to be explored.
In this paper, we present our findings on what we have affectionately coined the "Alma-Matter Effect," a play on the alma mater concept and the profound impact of a seemingly innocuous name on the performance of Lennar's stock. Through meticulous scrutiny of historical records and statistical methods, we aim to unravel the perplexing link between the popularity of the name "Alma" and the fluctuations in Lennar's stock price.
But before we delve into the labyrinth of statistics and financial conjecture, it is important to acknowledge the sheer whimsy of our inquiry. After all, who would have thought that a delightful moniker like "Alma" could hold sway over the machinations of the stock market? Join us as we unravel this captivating tale of names and numbers, and perhaps, uncover the quirky nuances of the financial world along the way.

[[RESULTS]]
The results of our analysis unveiled a striking correlation between the popularity of the first name "Alma" and the stock price of Lennar Corporation (LEN) from 2002 to 2022. The correlation coefficient of 0.8253924 indicates a strong positive relationship between the two variables. In other words, as the popularity of the name "Alma" waxed or waned, the stock price of Lennar seemed to dance in synchrony, reminiscent of a whimsical duet between unexpected partners.
The r-squared value of 0.6812726 further validates the robustness of this correlation, capturing over 68% of the variation in Lennar's stock price attributable to the popularity of the name "Alma." It's as if the name "Alma" whispered sweet somethings to Lennar's stock price, influencing its movements with an air of mysterious enchantment.
Moreover, the p-value of less than 0.01 indicates that this correlation is not just some fluke of statistical happenstance. No, dear reader, this is a bona fide, statistically significant connection that begs for further scrutiny and contemplation. It's as if the fates themselves conspired to entwine the destiny of "Alma" with the fortunes of Lennar, creating a saga that defies conventional logic and beckons us to ponder the capricious nature of correlations.
In Figure 1, our scatterplot adds a dash of visual flair, showcasing the unmistakable alignment of "Alma" popularity and Lennar's stock price. Behold, as the data points dance across the Cartesian plane, engaging in a harmonious choreography that defies the limits of reason and plunges headlong into the realm of delightful peculiarity.
These findings not only raise eyebrows in the world of financial analysis but also hint at a profound connection between the seemingly mundane choice of a name and the vicissitudes of the stock market. As we savor this astonishing revelation, we are reminded that in the labyrinthine landscape of statistical inquiry, even the most improbable pairings can yield unexpected insights and provoke a chuckle or two along the way.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our exploration into the "Alma-Matter Effect" has illuminated a captivating correlation between the popularity of the first name "Alma" and the stock price of Lennar Corporation. The robust correlation coefficient and r-squared value dance a statistical tango that leaves us marveling at the enigmatic sway of a name on financial fortunes. It's as if the spirit of "Alma" whispered sweet nothings to Lennar's stock, nudging it this way and that with a touch of whimsical charm.

As we reflect on this unlikely pairing of name popularity and stock performance, one cannot help but ponder the serendipitous whims of fate that brought these two disparate entities into statistical alignment. The arcane dance of numbers and nomenclature has unveiled a tale of captivating absurdity, reminding us that even in the staid world of finance, there's room for a touch of whimsy and wonder.

With a nod to the capricious nature of correlations and the delightful surprises that lurk within statistical analyses, we deem it unnecessary to delve further into the "Alma-Matter Effect." This uncanny tango of name popularity and stock price has enthralled us enough, and we leave it to future researchers to unravel other mystifying conundrums in the world of financial relationships. After all, there's only so much name-dropping one can do in the world of stock market analysis, and it appears that "Alma" and Lennar have written their own quirky tale of statistical serendipity.

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 The Alma-Matter Effect: An Alma-nac of Name Popularity and Stock Performance. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Economics

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 The Alma-Matter Effect: An Alma-nac of Name Popularity and Stock Performance. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Nameology Research and Analysis

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 The Alma-Matter Effect: An Alma-nac of Name Popularity and Stock Performance with an abstract of This study examines the surprising connection between the popularity of the first name "Alma" and the stock price of Lennar Corporation (LEN) from 2002 to 2022. Leveraging data from the US Social Security Administration and LSEG Analytics (Refinitiv), our research team set out to unravel this peculiar correlation. Our findings revealed a correlation coefficient of 0.8253924 and p < 0.01, highlighting a statistically significant relationship between the two variables. This unexpected relationship prompts further investigation and has potential implications for both the financial markets and expectant parents searching for auspicious baby names.

ChatGPT:

Alma name popularity, Stock performance correlation, Alma stock price correlation, Lennar Corporation stock performance, Social Security Administration data, LSEG Analytics data, Name popularity and stock market, Baby name impact on stock prices

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

Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error

Data details

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

Lennar's stock price (LEN)
Detailed data title: Opening price of Lennar (LEN) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: ^{See full details} Via Microsoft Excel Stockhistory function

See what else correlates with Lennar's stock price (LEN)

Correlation r = 0.8253924 (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 = 0.6812726 (Coefficient of determination)
This means 68.1% of the change in the one variable (i.e., Lennar's stock price (LEN)) is predictable based on the change in the other (i.e., Popularity of the first name Alma) over the 21 years from 2002 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.11E-6.^Show 0.0000041062274302593254000000
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 0.83 in 0.000411% of random cases. Said differently, if you correlated 243,533 random variables^Note You don't actually need 243 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 20 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 20 because we have two variables measured over a period of 21 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.

[ 0.61, 0.93 ] 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.

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Popularity of the first name Alma (Babies born)	520	429	462	479	484	419	375	354	317	304	319	408	420	426	400	466	463	491	525	615	652
Lennar's stock price (LEN) (Stock price)	20.87	22.86	47.18	55.71	60.15	50.67	17.43	8.45	12.59	18.57	19.73	39.27	38.49	44.22	47.33	42.66	63.93	38.56	56.07	76.68	115.84

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([520,429,462,479,484,419,375,354,317,304,319,408,420,426,400,466,463,491,525,615,652,])
array_2 = np.array([20.87,22.86,47.18,55.71,60.15,50.67,17.43,8.45,12.59,18.57,19.73,39.27,38.49,44.22,47.33,42.66,63.93,38.56,56.07,76.68,115.84,])
array_1_name = "Popularity of the first name Alma"
array_2_name = "Lennar's stock price (LEN)"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Popularity of the first name Alma
Line chart for only Lennar's stock price (LEN)
AI-generated correlation image
The spurious research paper: The Alma-Matter Effect: An Alma-nac of Name Popularity and Stock Performance

View another random correlation

How fun was this correlation?

Your correlation inspection deserves a standing ovation!

Correlation ID: 2179 · Black Variable ID: 2813 · Red Variable ID: 1817


Problem variable:
Issue:
Additional details: Optional
Confirm you are a human: