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Spurious correlation #2,801 · 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 Aubrey and the second variable is Justin Upton's yearly run total.  The chart goes from 2007 to 2022, and the two variables track closely in value over that time. Small Image
Download png
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AI explanation

As the popularity of the name Aubrey decreased, so did the number of people doing the "Aubrey Shuffle" dance trend. This ultimately led to a nationwide shortage of dance partners, and without people to dance with, Justin Upton's yearly run total also decreased. The correlation is crystal clear: fewer Aubreys, fewer shuffles, fewer runs for Upton!

Model: dalle-3
Prompt: Generate an image of a charming 3D Pixar-style scene set in a vibrant and sunny baseball stadium. Justin Upton, with a joyful and beaming expression, sprints energetically around the bases, his accomplishment indicated by the victorious scoreboard flashing a record-breaking run total. As Upton crosses home plate, the surrounding crowd erupts with excitement. In the stands, families delight in the game, capturing the joy and cheering on the remarkable athlete. Meanwhile, a heartwarming sight unfolds around the stadium as an increasing number of fresh-faced babies, named Aubrey, captivate the attention of even the opposing team's players, who are clearly drawn to their lovable charm. The correlation between the rising popularity of the name "Aubrey" and Upton's heightened run total is apparent as Aubs of all ages contribute to his success. The scene is filled with a lively and jubilant atmosphere as the crowd and adorable Aubs come together to celebrate the game. 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 Aubrey and Justin Upton's yearly run total. 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 scene from Skyrim Cubism 3D Pixar Style 3D Pixar Style Photorealism
ChatGPT: 3D Pixar Style

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 Aubrey and Justin Upton's yearly run total, in the following situation: Because as Aubrey became a more popular name, it led to an increase in the number of Aubs in the world. These Aubs, with their charm and good looks, distracted the opposing baseball teams, allowing Justin Upton to score more runs. The correlation is crystal clear - more Aubs, more distractions, more runs for Upton. It's simple math in the game of love and baseball.. Keep the description simple.
ChatGPT: In a sunny baseball stadium, we see Justin Upton sprinting around the bases with a big grin on his face, as the scoreboard flashes a record-breaking run total. Surrounding the stadium, we spot an increasing number of babies being named Aubrey, their adorable faces drawing the attention of the opposing team's players, who are clearly distracted by their charm. The correlation between the rising popularity of the name Aubrey and Upton's increased run total is evident as he crosses home plate, with Aubs all around the field adding to his success.

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: [ 3D Pixar Style ] and depicting this scene: In a sunny baseball stadium, we see Justin Upton sprinting around the bases with a big grin on his face, as the scoreboard flashes a record-breaking run total. Surrounding the stadium, we spot an increasing number of babies being named Aubrey, their adorable faces drawing the attention of the opposing team's players, who are clearly distracted by their charm. The correlation between the rising popularity of the name Aubrey and Upton's increased run total is evident as he crosses home plate, with Aubs all around the field adding to his success. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a charming 3D Pixar-style scene set in a vibrant and sunny baseball stadium. Justin Upton, with a joyful and beaming expression, sprints energetically around the bases, his accomplishment indicated by the victorious scoreboard flashing a record-breaking run total. As Upton crosses home plate, the surrounding crowd erupts with excitement. In the stands, families delight in the game, capturing the joy and cheering on the remarkable athlete. Meanwhile, a heartwarming sight unfolds around the stadium as an increasing number of fresh-faced babies, named Aubrey, captivate the attention of even the opposing team's players, who are clearly drawn to their lovable charm. The correlation between the rising popularity of the name "Aubrey" and Upton's heightened run total is apparent as Aubs of all ages contribute to his success. The scene is filled with a lively and jubilant atmosphere as the crowd and adorable Aubs come together to celebrate the game.

*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.

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 a decrease in Popularity of the first name Aubrey caused Justin Upton's yearly run total to decrease.

AI academic paper

(Because p < 0.01)
Swinging for the Fences: The Aubrey Factor and Its Impact on Justin Upton's Yearly Run Totals

Journal of Sports Analytics

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
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, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Popularity of the first name Aubrey and Justin Upton's yearly run total. Make lots of jokes, goofy observations, and puns.

Make the title seem clever.

Your research team used data from US Social Security Administration and Baseball Reference to assess this nagging question. You found a correlation coefficient of 0.8358957 and p < 0.01 for 2007 to 2022.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
"Swinging for the Fences: The Aubrey Factor and Its Impact on Justin Upton's Yearly Run Totals"

[[ABSTRACT]]
The relationship between one's name and their success in life has long been a topic of fascination and speculation. In this paper, we delve into the quirky world of baseball and baby names to investigate the peculiar connection between the popularity of the name Aubrey and Major League Baseball player Justin Upton's annual run totals. Drawing on data from the US Social Security Administration and Baseball Reference, our research team has unveiled a surprising correlation coefficient of 0.8358957, with a p-value of less than 0.01, for the years 2007 to 2022. The evidence indicates that the prevalence of the name Aubrey coincides with the highs and lows of Upton's performance on the field. We invite readers to step up to the plate and explore this quirky correlation with us as we take a swing at unraveling the mysterious link between the "Aubrey factor" and Justin Upton's run production. With statistical significance and a dash of whimsy, our findings may just be a home run in uncovering the amusing influence of baby names on baseball prowess.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction 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 introduction section of an academic research paper presenting the findings of the connection between Popularity of the first name Aubrey and Justin Upton's yearly run total. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
"Swinging for the Fences: The Aubrey Factor and Its Impact on Justin Upton's Yearly Run Totals"

[[ABSTRACT]]
The relationship between one's name and their success in life has long been a topic of fascination and speculation. In this paper, we delve into the quirky world of baseball and baby names to investigate the peculiar connection between the popularity of the name Aubrey and Major League Baseball player Justin Upton's annual run totals. Drawing on data from the US Social Security Administration and Baseball Reference, our research team has unveiled a surprising correlation coefficient of 0.8358957, with a p-value of less than 0.01, for the years 2007 to 2022. The evidence indicates that the prevalence of the name Aubrey coincides with the highs and lows of Upton's performance on the field. We invite readers to step up to the plate and explore this quirky correlation with us as we take a swing at unraveling the mysterious link between the "Aubrey factor" and Justin Upton's run production. With statistical significance and a dash of whimsy, our findings may just be a home run in uncovering the amusing influence of baby names on baseball prowess.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
Ah, the quirks and curiosities of the academic world! The enigmatic relationship between one's moniker and their life outcomes has been pondered by thinkers and theorists throughout the ages. From the Shakespearean thought-bubble of "What's in a name?" to the modern-day trend of unique baby names (Apple, anyone?), the influence of nomenclature on our destinies remains a topic that baffles and bemuses.

In this merry romp through the realms of baseball and baby names, we embark on a whimsical journey to explore the captivating connection between the popularity of the name Aubrey and the yearly run totals of none other than the dashing Major League Baseball player, Justin Upton. It's a tale of home runs and naming funs, statistical shenanigans, and a dash of scientific whimsy – a hearty feast for the intellect, with a side of jocular musings.

Drawing on findings from the arcane vaults of the US Social Security Administration and the hallowed halls of Baseball Reference, our intrepid research team has stumbled upon a rather unexpected revelation. Lo and behold, a correlation coefficient of 0.8358957, with a p-value of less than 0.01, has emerged from the depths of our data dive, spanning the years 2007 to 2022. Who would have thought that the prevalence of the name Aubrey would dance and prance in such delightful synchrony with Upton's on-field performances?

As we venture forth in this delightful, albeit slightly unconventional expedition, we urge our esteemed readers to don their thinking caps and join us in a merry exploration of the "Aubrey factor" and its curious interplay with Justin Upton's run production. With statistical significance as our trusty guide and a twinkle in our eye, this revelatory romp through the wonders of baby names and baseball promises to be a delightful escapade into uncharted, yet inexplicably linked, territories. So, grab your bats and statistical charts, dear readers, for this is a saga that is bound to hit it out of the park – both figuratively and statistically! Let's play ball!


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Aubrey and Justin Upton's yearly run total. 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
"Swinging for the Fences: The Aubrey Factor and Its Impact on Justin Upton's Yearly Run Totals"

[[ABSTRACT]]
The relationship between one's name and their success in life has long been a topic of fascination and speculation. In this paper, we delve into the quirky world of baseball and baby names to investigate the peculiar connection between the popularity of the name Aubrey and Major League Baseball player Justin Upton's annual run totals. Drawing on data from the US Social Security Administration and Baseball Reference, our research team has unveiled a surprising correlation coefficient of 0.8358957, with a p-value of less than 0.01, for the years 2007 to 2022. The evidence indicates that the prevalence of the name Aubrey coincides with the highs and lows of Upton's performance on the field. We invite readers to step up to the plate and explore this quirky correlation with us as we take a swing at unraveling the mysterious link between the "Aubrey factor" and Justin Upton's run production. With statistical significance and a dash of whimsy, our findings may just be a home run in uncovering the amusing influence of baby names on baseball prowess.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Ah, the quirks and curiosities of the academic world! The enigmatic relationship between one's moniker and their life outcomes has been pondered by thinkers and theorists throughout the ages. From the Shakespearean thought-bubble of "What's in a name?" to the modern-day trend of unique baby names (Apple, anyone?), the influence of nomenclature on our destinies remains a topic that baffles and bemuses.
In this merry romp through the realms of baseball and baby names, we embark on a whimsical journey to explore the captivating connection between the popularity of the name Aubrey and the yearly run totals of none other than the dashing Major League Baseball player, Justin Upton. It's a tale of home runs and naming funs, statistical shenanigans, and a dash of scientific whimsy – a hearty feast for the intellect, with a side of jocular musings.
Drawing on findings from the arcane vaults of the US Social Security Administration and the hallowed halls of Baseball Reference, our intrepid research team has stumbled upon a rather unexpected revelation. Lo and behold, a correlation coefficient of 0.8358957, with a p-value of less than 0.01, has emerged from the depths of our data dive, spanning the years 2007 to 2022. Who would have thought that the prevalence of the name Aubrey would dance and prance in such delightful synchrony with Upton's on-field performances?
As we venture forth in this delightful, albeit slightly unconventional expedition, we urge our esteemed readers to don their thinking caps and join us in a merry exploration of the "Aubrey factor" and its curious interplay with Justin Upton's run production. With statistical significance as our trusty guide and a twinkle in our eye, this revelatory romp through the wonders of baby names and baseball promises to be a delightful escapade into uncharted, yet inexplicably linked, territories. So, grab your bats and statistical charts, dear readers, for this is a saga that is bound to hit it out of the park – both figuratively and statistically! Let's play ball!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In their seminal work, "The Name Game: A Sociolinguistic Analysis," Smith et al. (2010) explored the profound impact of nomenclature on various facets of life, from career choices to social interactions. While their study primarily focused on the implications of naming conventions in everyday settings, it hinted at the tantalizing possibility of names influencing outcomes in unconventional domains, such as sports performance. This curious notion sparked the curiosity of researchers and armchair statisticians alike, paving the way for an offbeat exploration into the intersection of baby names and baseball prowess.

Doe's provocative study, "Monikers and Magic: Unraveling the Hidden Potentials of Naming," delved deep into the psychological underpinnings of moniker effects (2015). Their examination of the subconscious associations and biases linked to specific names sent ripples through the academic community, prompting discussions about the potential ramifications of names in domains where individual performance takes center stage. Little did they know that their intellectual musings would eventually intersect with the world of professional sports, sparking a humorous yet intriguing quest to uncover the enigma behind the Aubrey-Upton phenomenon.

Jones et al. (2018), in "The Name Chronicles: An Ode to Identity," delved into the rich tapestry of names and their symbolic significance across cultures and time periods. Their comprehensive survey of naming practices and traditions shed light on the depth of meaning woven into individuals' identities through their names. While the context of sports may seem worlds apart from this profound exploration of human nomenclature, the unforeseen linking of the name Aubrey to a professional athlete's performance adds an unexpected, whimsical layer to the age-old dialogue on the power of names.

As we wade further into the whimsical waters of our inquiry, it is worth noting the influence of popular non-fiction titles that have indirectly shaped the discourse surrounding our investigation. The works of Malcolm Gladwell, in "Outliers: The Story of Success," have long captivated readers with their exploration of unconventional factors that may influence achievement. While Gladwell's focus may not explicitly touch on the correlation between baby names and sports statistics, the ethos of unexpected influences on success permeates his writings, inspiring us to consider the potential role of the "Aubrey factor" in the kaleidoscope of variables that underpin athletic performance.

On a lighter note, the fictional universes of "Moneyball" by Michael Lewis and "The Art of Fielding" by Chad Harbach offer playful yet insightful portrayals of the quirky and unpredictable world of baseball. While these novels may not explicitly address the phenomenon of name popularity and its interplay with on-field achievements, their spirited depictions of the baseball subculture infuse our exploration with a sense of whimsy and wonder.

In our quest to unravel the enigmatic connection between the name Aubrey and Justin Upton's yearly run totals, we cannot overlook the inspiration drawn from the humorous twists and turns of board games such as "Baseball Highlights 2045." The whimsical nature of these gaming experiences mirrors the lighthearted yet compelling spirit of our research, reminding us that even the most curious and unexpected connections can shape our understanding of human experiences – both in the realms of reality and play.

As we meander through the mystifying landscape of name popularity and professional athletic performance, it becomes evident that our journey is one filled with curious detours, unexpected revelations, and a healthy dose of whimsical mirth. The fusion of rigorous statistical analyses with the offbeat charm of our chosen subject matter promises a literature review that is bound to elicit both scholarly contemplation and a good-natured chuckle, making it a tour de force in the annals of offbeat academic pursuits.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Aubrey and Justin Upton's yearly run total. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Baseball Reference . You used data from 2007 to 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Swinging for the Fences: The Aubrey Factor and Its Impact on Justin Upton's Yearly Run Totals"

[[ABSTRACT]]
The relationship between one's name and their success in life has long been a topic of fascination and speculation. In this paper, we delve into the quirky world of baseball and baby names to investigate the peculiar connection between the popularity of the name Aubrey and Major League Baseball player Justin Upton's annual run totals. Drawing on data from the US Social Security Administration and Baseball Reference, our research team has unveiled a surprising correlation coefficient of 0.8358957, with a p-value of less than 0.01, for the years 2007 to 2022. The evidence indicates that the prevalence of the name Aubrey coincides with the highs and lows of Upton's performance on the field. We invite readers to step up to the plate and explore this quirky correlation with us as we take a swing at unraveling the mysterious link between the "Aubrey factor" and Justin Upton's run production. With statistical significance and a dash of whimsy, our findings may just be a home run in uncovering the amusing influence of baby names on baseball prowess.

[[INTRODUCTION]]
Ah, the quirks and curiosities of the academic world! The enigmatic relationship between one's moniker and their life outcomes has been pondered by thinkers and theorists throughout the ages. From the Shakespearean thought-bubble of "What's in a name?" to the modern-day trend of unique baby names (Apple, anyone?), the influence of nomenclature on our destinies remains a topic that baffles and bemuses.
In this merry romp through the realms of baseball and baby names, we embark on a whimsical journey to explore the captivating connection between the popularity of the name Aubrey and the yearly run totals of none other than the dashing Major League Baseball player, Justin Upton. It's a tale of home runs and naming funs, statistical shenanigans, and a dash of scientific whimsy – a hearty feast for the intellect, with a side of jocular musings.
Drawing on findings from the arcane vaults of the US Social Security Administration and the hallowed halls of Baseball Reference, our intrepid research team has stumbled upon a rather unexpected revelation. Lo and behold, a correlation coefficient of 0.8358957, with a p-value of less than 0.01, has emerged from the depths of our data dive, spanning the years 2007 to 2022. Who would have thought that the prevalence of the name Aubrey would dance and prance in such delightful synchrony with Upton's on-field performances?
As we venture forth in this delightful, albeit slightly unconventional expedition, we urge our esteemed readers to don their thinking caps and join us in a merry exploration of the "Aubrey factor" and its curious interplay with Justin Upton's run production. With statistical significance as our trusty guide and a twinkle in our eye, this revelatory romp through the wonders of baby names and baseball promises to be a delightful escapade into uncharted, yet inexplicably linked, territories. So, grab your bats and statistical charts, dear readers, for this is a saga that is bound to hit it out of the park – both figuratively and statistically! Let's play ball!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Our research endeavor began with a spirited quest for data, scouring the nooks and crannies of the vast expanse known as the Internet. We assembled a crack team of statisticians, baseball enthusiasts, and name aficionados, armed with laptops, calculators, and an unquenchable thirst for discovery. Aided by copious amounts of coffee and the occasional indulgence in baseball-themed snacks, we dove headfirst into the labyrinthine archives of the US Social Security Administration and Baseball Reference.

To establish the foundation of our investigation, we harnessed the power of time-travel – not in the literal sense, of course, but through the ancient and revered methodology known as "historical data gathering." We meticulously combed through the annals of baby names, charting the millennial rise and fall of the moniker Aubrey from 2007 to 2022. This involved wading through countless scrolls of birth records, tallying the frequency of Aubreys bursting onto the scene, and mapping their ebbs and flows across the years.

Simultaneously, we set our sights on the towering citadel of baseball statistics, embarking on a grueling expedition to mine the essential nuggets of wisdom from the annals of Justin Upton's career. Every home run, stolen base, and run batted in was scrutinized with the scholarly intensity of a hawk-eyed umpire, as we meticulously tracked Upton's annual run totals from 2007 to 2022.

Armed with this trove of data, we summoned the cryptic arts of statistical analysis – an enchanting blend of correlations, regressions, and p-values that would impress even the most persnickety of numerologists. Our trusty abacus was cast aside in favor of cutting-edge statistical software, unleashing the formidable powers of regression analysis to unravel the enigma of the Aubrey-Upton nexus.

By employing the majestic machinery of correlation coefficients and p-values, we peeled back the layers of coincidence and causation, seeking the elusive thread that ties the proliferation of Aubreys to the ebbs and flows of Upton's run production. Our methods were not only robust but imbued with an infectious spirit of curiosity, sprinkled with flying puns and the occasional bout of statistical tomfoolery.

With a generous dollop of scientific rigor and an irrepressible sense of whimsy, our methodology grasped the baton of research and sprinted along the basepaths of discovery, hurtling toward the hallowed halls of revelation in the delightful game of "Aubrey and Upton's Statistical Symphony."


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Aubrey and Justin Upton's yearly run total. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Baseball Reference .

For the time period 2007 to 2022, you found a correlation 0.8358957, r-squared of 0.6987216, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"Swinging for the Fences: The Aubrey Factor and Its Impact on Justin Upton's Yearly Run Totals"

[[ABSTRACT]]
The relationship between one's name and their success in life has long been a topic of fascination and speculation. In this paper, we delve into the quirky world of baseball and baby names to investigate the peculiar connection between the popularity of the name Aubrey and Major League Baseball player Justin Upton's annual run totals. Drawing on data from the US Social Security Administration and Baseball Reference, our research team has unveiled a surprising correlation coefficient of 0.8358957, with a p-value of less than 0.01, for the years 2007 to 2022. The evidence indicates that the prevalence of the name Aubrey coincides with the highs and lows of Upton's performance on the field. We invite readers to step up to the plate and explore this quirky correlation with us as we take a swing at unraveling the mysterious link between the "Aubrey factor" and Justin Upton's run production. With statistical significance and a dash of whimsy, our findings may just be a home run in uncovering the amusing influence of baby names on baseball prowess.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Ah, the quirks and curiosities of the academic world! The enigmatic relationship between one's moniker and their life outcomes has been pondered by thinkers and theorists throughout the ages. From the Shakespearean thought-bubble of "What's in a name?" to the modern-day trend of unique baby names (Apple, anyone?), the influence of nomenclature on our destinies remains a topic that baffles and bemuses.
In this merry romp through the realms of baseball and baby names, we embark on a whimsical journey to explore the captivating connection between the popularity of the name Aubrey and the yearly run totals of none other than the dashing Major League Baseball player, Justin Upton. It's a tale of home runs and naming funs, statistical shenanigans, and a dash of scientific whimsy – a hearty feast for the intellect, with a side of jocular musings.
Drawing on findings from the arcane vaults of the US Social Security Administration and the hallowed halls of Baseball Reference, our intrepid research team has stumbled upon a rather unexpected revelation. Lo and behold, a correlation coefficient of 0.8358957, with a p-value of less than 0.01, has emerged from the depths of our data dive, spanning the years 2007 to 2022. Who would have thought that the prevalence of the name Aubrey would dance and prance in such delightful synchrony with Upton's on-field performances?
As we venture forth in this delightful, albeit slightly unconventional expedition, we urge our esteemed readers to don their thinking caps and join us in a merry exploration of the "Aubrey factor" and its curious interplay with Justin Upton's run production. With statistical significance as our trusty guide and a twinkle in our eye, this revelatory romp through the wonders of baby names and baseball promises to be a delightful escapade into uncharted, yet inexplicably linked, territories. So, grab your bats and statistical charts, dear readers, for this is a saga that is bound to hit it out of the park – both figuratively and statistically! Let's play ball!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The moment you've all been waiting for – drumroll, please! Our data analysis has unveiled a striking correlation between the prevalence of the name Aubrey and the yearly run totals of the inimitable Justin Upton. With a jaw-dropping correlation coefficient of 0.8358957 and an r-squared value of 0.6987216, it seems the "Aubrey factor" and Upton's run production are engaged in a flamboyant dance, much like a pitcher and catcher executing a perfectly synchronized double play.

But wait, there's more! The p-value of less than 0.01 further solidifies the significance of this seemingly whimsical correlation. It's as if our statistical analysis took a leisurely stroll through the hallowed halls of baseball history, adorned in a cape of undeniable statistical significance and wielding a sword of empirical evidence, and triumphantly emerged with a bevy of fascinating findings to regale us with.

Ladies and gentlemen, feast your eyes upon the scatterplot – Fig. 1, in all its glory – showcasing the delightful synchrony between the popularity of the name Aubrey and Mr. Upton's run production. The dots on this scatterplot practically pirouette across the xy-plane, showcasing a mesmerizing choreography of name popularity and on-field prowess.

In conclusion, our results have dazzled and bemused us in equal measure. The Aubrey-Upton connection is not merely a figment of statistical whimsy; it stands as a whimsical testament to the confounding and enchanting ways of the universe. With statistical significance as our trusty guide and a twinkle in our eye, we boldly present these findings as a delightful testament to the playful interplay of baby names and baseball. After all, who knew that the moniker Aubrey could hold such sway over the realms of batting averages and home run totals? Indeed, this is a saga that has truly hit it out of the park – both figuratively and statistically!


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Aubrey and Justin Upton's yearly run total. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Swinging for the Fences: The Aubrey Factor and Its Impact on Justin Upton's Yearly Run Totals"

[[ABSTRACT]]
The relationship between one's name and their success in life has long been a topic of fascination and speculation. In this paper, we delve into the quirky world of baseball and baby names to investigate the peculiar connection between the popularity of the name Aubrey and Major League Baseball player Justin Upton's annual run totals. Drawing on data from the US Social Security Administration and Baseball Reference, our research team has unveiled a surprising correlation coefficient of 0.8358957, with a p-value of less than 0.01, for the years 2007 to 2022. The evidence indicates that the prevalence of the name Aubrey coincides with the highs and lows of Upton's performance on the field. We invite readers to step up to the plate and explore this quirky correlation with us as we take a swing at unraveling the mysterious link between the "Aubrey factor" and Justin Upton's run production. With statistical significance and a dash of whimsy, our findings may just be a home run in uncovering the amusing influence of baby names on baseball prowess.

[[LITERATURE REVIEW]]
In their seminal work, "The Name Game: A Sociolinguistic Analysis," Smith et al. (2010) explored the profound impact of nomenclature on various facets of life, from career choices to social interactions. While their study primarily focused on the implications of naming conventions in everyday settings, it hinted at the tantalizing possibility of names influencing outcomes in unconventional domains, such as sports performance. This curious notion sparked the curiosity of researchers and armchair statisticians alike, paving the way for an offbeat exploration into the intersection of baby names and baseball prowess.
Doe's provocative study, "Monikers and Magic: Unraveling the Hidden Potentials of Naming," delved deep into the psychological underpinnings of moniker effects (2015). Their examination of the subconscious associations and biases linked to specific names sent ripples through the academic community, prompting discussions about the potential ramifications of names in domains where individual performance takes center stage. Little did they know that their intellectual musings would eventually intersect with the world of professional sports, sparking a humorous yet intriguing quest to uncover the enigma behind the Aubrey-Upton phenomenon.
Jones et al. (2018), in "The Name Chronicles: An Ode to Identity," delved into the rich tapestry of names and their symbolic significance across cultures and time periods. Their comprehensive survey of naming practices and traditions shed light on the depth of meaning woven into individuals' identities through their names. While the context of sports may seem worlds apart from this profound exploration of human nomenclature, the unforeseen linking of the name Aubrey to a professional athlete's performance adds an unexpected, whimsical layer to the age-old dialogue on the power of names.
As we wade further into the whimsical waters of our inquiry, it is worth noting the influence of popular non-fiction titles that have indirectly shaped the discourse surrounding our investigation. The works of Malcolm Gladwell, in "Outliers: The Story of Success," have long captivated readers with their exploration of unconventional factors that may influence achievement. While Gladwell's focus may not explicitly touch on the correlation between baby names and sports statistics, the ethos of unexpected influences on success permeates his writings, inspiring us to consider the potential role of the "Aubrey factor" in the kaleidoscope of variables that underpin athletic performance.
On a lighter note, the fictional universes of "Moneyball" by Michael Lewis and "The Art of Fielding" by Chad Harbach offer playful yet insightful portrayals of the quirky and unpredictable world of baseball. While these novels may not explicitly address the phenomenon of name popularity and its interplay with on-field achievements, their spirited depictions of the baseball subculture infuse our exploration with a sense of whimsy and wonder.
In our quest to unravel the enigmatic connection between the name Aubrey and Justin Upton's yearly run totals, we cannot overlook the inspiration drawn from the humorous twists and turns of board games such as "Baseball Highlights 2045." The whimsical nature of these gaming experiences mirrors the lighthearted yet compelling spirit of our research, reminding us that even the most curious and unexpected connections can shape our understanding of human experiences – both in the realms of reality and play.
As we meander through the mystifying landscape of name popularity and professional athletic performance, it becomes evident that our journey is one filled with curious detours, unexpected revelations, and a healthy dose of whimsical mirth. The fusion of rigorous statistical analyses with the offbeat charm of our chosen subject matter promises a literature review that is bound to elicit both scholarly contemplation and a good-natured chuckle, making it a tour de force in the annals of offbeat academic pursuits.

[[RESULTS]]
The moment you've all been waiting for – drumroll, please! Our data analysis has unveiled a striking correlation between the prevalence of the name Aubrey and the yearly run totals of the inimitable Justin Upton. With a jaw-dropping correlation coefficient of 0.8358957 and an r-squared value of 0.6987216, it seems the "Aubrey factor" and Upton's run production are engaged in a flamboyant dance, much like a pitcher and catcher executing a perfectly synchronized double play.
But wait, there's more! The p-value of less than 0.01 further solidifies the significance of this seemingly whimsical correlation. It's as if our statistical analysis took a leisurely stroll through the hallowed halls of baseball history, adorned in a cape of undeniable statistical significance and wielding a sword of empirical evidence, and triumphantly emerged with a bevy of fascinating findings to regale us with.
Ladies and gentlemen, feast your eyes upon the scatterplot – Fig. 1, in all its glory – showcasing the delightful synchrony between the popularity of the name Aubrey and Mr. Upton's run production. The dots on this scatterplot practically pirouette across the xy-plane, showcasing a mesmerizing choreography of name popularity and on-field prowess.
In conclusion, our results have dazzled and bemused us in equal measure. The Aubrey-Upton connection is not merely a figment of statistical whimsy; it stands as a whimsical testament to the confounding and enchanting ways of the universe. With statistical significance as our trusty guide and a twinkle in our eye, we boldly present these findings as a delightful testament to the playful interplay of baby names and baseball. After all, who knew that the moniker Aubrey could hold such sway over the realms of batting averages and home run totals? Indeed, this is a saga that has truly hit it out of the park – both figuratively and statistically!

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

Ah, the whimsical intersection of names and numbers has brought us to this captivating juncture. As we delve into the peculiar correlation between the name Aubrey's popularity and Justin Upton's annual run totals, it almost feels like we're uncovering the secret recipe for turning baseball diamonds into the dazzling world of statistical stardom.

Building upon the thought-provoking literature we encountered, it's fascinating to see how our results echo the musings of Smith et al. (2010), who teased at the possibility of names influencing performance in unconventional domains. Our findings not only support this notion but also elevate it to a league of its own – one where the Aubrey factor plays the role of the unexpected MVP in Upton's run production. Imagine a game where the leadoff batter is none other than the name Aubrey, setting the stage for a statistical grand slam of correlations and significance.

In a surprising twist, our results also align with Doe's work on the psychological underpinnings of moniker effects (2015). The subconscious associations and biases linked to specific names seem to transcend the realms of everyday life and trickle into the universe of professional sports, where a simple name like Aubrey wields an unexpected influence over Upton's on-field performances.

It's as if the spirited universes of "Moneyball" and "The Art of Fielding" have colluded to enshroud our findings in a cloak of whimsy and wonder, infusing our exploration with a sense of playfulness reminiscent of a good-natured game of statistical leapfrog. Who says the journey from data to discussion can't be a scenic route through the joyous landscapes of statistical mirth and marvelous musings?

As the scatterplot unfurls its dazzling tapestry of Aubrey's popularity and Upton's run production, we are reminded that statistics has a whimsical way of weaving together seemingly disparate elements into a cohesive and captivating narrative. The dots on this scatterplot do more than just pirouette; they perform an enchanting statistical ballet, leaving us spellbound by the choreography of name popularity and on-field prowess.

In our quest to uncover the enigmatic connection between the name Aubrey and Justin Upton's yearly run totals, we set out with a fervent dedication to merging rigorous statistical analyses with the offbeat charm of our chosen subject matter. Our findings bear testament to the delightful interplay of baby names and baseball, turning what initially seemed like a statistical wild pitch into a pitch-perfect home run. After all, who knew that the moniker Aubrey could hold such sway over the realms of batting averages and home run totals? It's a statistical saga that has truly hit it out of the park – both figuratively and statistically!


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Aubrey and Justin Upton's yearly run total. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Swinging for the Fences: The Aubrey Factor and Its Impact on Justin Upton's Yearly Run Totals"

[[ABSTRACT]]
The relationship between one's name and their success in life has long been a topic of fascination and speculation. In this paper, we delve into the quirky world of baseball and baby names to investigate the peculiar connection between the popularity of the name Aubrey and Major League Baseball player Justin Upton's annual run totals. Drawing on data from the US Social Security Administration and Baseball Reference, our research team has unveiled a surprising correlation coefficient of 0.8358957, with a p-value of less than 0.01, for the years 2007 to 2022. The evidence indicates that the prevalence of the name Aubrey coincides with the highs and lows of Upton's performance on the field. We invite readers to step up to the plate and explore this quirky correlation with us as we take a swing at unraveling the mysterious link between the "Aubrey factor" and Justin Upton's run production. With statistical significance and a dash of whimsy, our findings may just be a home run in uncovering the amusing influence of baby names on baseball prowess.

[[INTRDUCTION]]
Ah, the quirks and curiosities of the academic world! The enigmatic relationship between one's moniker and their life outcomes has been pondered by thinkers and theorists throughout the ages. From the Shakespearean thought-bubble of "What's in a name?" to the modern-day trend of unique baby names (Apple, anyone?), the influence of nomenclature on our destinies remains a topic that baffles and bemuses.
In this merry romp through the realms of baseball and baby names, we embark on a whimsical journey to explore the captivating connection between the popularity of the name Aubrey and the yearly run totals of none other than the dashing Major League Baseball player, Justin Upton. It's a tale of home runs and naming funs, statistical shenanigans, and a dash of scientific whimsy – a hearty feast for the intellect, with a side of jocular musings.
Drawing on findings from the arcane vaults of the US Social Security Administration and the hallowed halls of Baseball Reference, our intrepid research team has stumbled upon a rather unexpected revelation. Lo and behold, a correlation coefficient of 0.8358957, with a p-value of less than 0.01, has emerged from the depths of our data dive, spanning the years 2007 to 2022. Who would have thought that the prevalence of the name Aubrey would dance and prance in such delightful synchrony with Upton's on-field performances?
As we venture forth in this delightful, albeit slightly unconventional expedition, we urge our esteemed readers to don their thinking caps and join us in a merry exploration of the "Aubrey factor" and its curious interplay with Justin Upton's run production. With statistical significance as our trusty guide and a twinkle in our eye, this revelatory romp through the wonders of baby names and baseball promises to be a delightful escapade into uncharted, yet inexplicably linked, territories. So, grab your bats and statistical charts, dear readers, for this is a saga that is bound to hit it out of the park – both figuratively and statistically! Let's play ball!

[[RESULTS]]
The moment you've all been waiting for – drumroll, please! Our data analysis has unveiled a striking correlation between the prevalence of the name Aubrey and the yearly run totals of the inimitable Justin Upton. With a jaw-dropping correlation coefficient of 0.8358957 and an r-squared value of 0.6987216, it seems the "Aubrey factor" and Upton's run production are engaged in a flamboyant dance, much like a pitcher and catcher executing a perfectly synchronized double play.
But wait, there's more! The p-value of less than 0.01 further solidifies the significance of this seemingly whimsical correlation. It's as if our statistical analysis took a leisurely stroll through the hallowed halls of baseball history, adorned in a cape of undeniable statistical significance and wielding a sword of empirical evidence, and triumphantly emerged with a bevy of fascinating findings to regale us with.
Ladies and gentlemen, feast your eyes upon the scatterplot – Fig. 1, in all its glory – showcasing the delightful synchrony between the popularity of the name Aubrey and Mr. Upton's run production. The dots on this scatterplot practically pirouette across the xy-plane, showcasing a mesmerizing choreography of name popularity and on-field prowess.
In conclusion, our results have dazzled and bemused us in equal measure. The Aubrey-Upton connection is not merely a figment of statistical whimsy; it stands as a whimsical testament to the confounding and enchanting ways of the universe. With statistical significance as our trusty guide and a twinkle in our eye, we boldly present these findings as a delightful testament to the playful interplay of baby names and baseball. After all, who knew that the moniker Aubrey could hold such sway over the realms of batting averages and home run totals? Indeed, this is a saga that has truly hit it out of the park – both figuratively and statistically!

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

As we bid adieu to this enchanting expedition into the whimsical world of baby names and baseball, we find ourselves marveling at the unlikely synchrony between the name Aubrey and the athletic exploits of Justin Upton. Our data has regaled us with statistical shenanigans and empirical eyebrow-raisers, leaving us in awe of the capricious dance between nomenclature and run totals.

The "Aubrey factor" stands as a delightful enigma, akin to the riddle of Schroedinger's cat – a playful conundrum that tickles our scholarly fancies. Much like a curveball that veers unexpectedly, this correlation has thrown us for a loop, infusing our research with a delightful element of surprise.

As we reflect upon this curious correlation, we can't help but marvel at the amusing and oftentimes confounding ways in which the universe unfolds its mysteries. Ah, the capricious whims of statistical significance – it's as if the data itself has donned a cloak of unpredictability, casting a mischievous twinkle upon our scholarly pursuits.

In the grand tapestry of intellectual endeavors, our uncovering of the "Aubrey factor" and its intriguing alliance with Upton's on-field performances represents a delightful anomaly, much like stumbling upon a knuckleball in the midst of a flurry of fastballs. Such charming statistical oddities remind us that the realm of research is not merely a clinical pursuit but a merry dance with the capricious whims of the data.

Now that we've taken a swing at unraveling the curious correlation between nomenclature and run totals, it's safe to say that our findings have rounded the bases of statistical significance with a joyful flourish. As the dust settles on this merry research adventure, we boldly proclaim that no further exploration is needed in this delightful, offbeat territory of baby names and baseball – for the "Aubrey factor" has charmed its way into the annals of whimsical statistical curiosities. And with that, we tip our proverbial hats to the enchanting conundrum of the "Aubrey factor" as we rejoin the delightful diversion of academic exploration.

No need to bat an eye or run any more statistical analyses, for this peculiar correlation has just hit a statistical home run – and as they say, it's game, set, match!


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Swinging for the Fences: The Aubrey Factor and Its Impact on Justin Upton's Yearly Run Totals. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Sports Analytics


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Swinging for the Fences: The Aubrey Factor and Its Impact on Justin Upton's Yearly Run Totals. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Baseball Statistics and Performance 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 Swinging for the Fences: The Aubrey Factor and Its Impact on Justin Upton's Yearly Run Totals with an abstract of The relationship between one's name and their success in life has long been a topic of fascination and speculation. In this paper, we delve into the quirky world of baseball and baby names to investigate the peculiar connection between the popularity of the name Aubrey and Major League Baseball player Justin Upton's annual run totals. Drawing on data from the US Social Security Administration and Baseball Reference, our research team has unveiled a surprising correlation coefficient of 0.8358957, with a p-value of less than 0.01, for the years 2007 to 2022. The evidence indicates that the prevalence of the name Aubrey coincides with the highs and lows of Upton's performance on the field. We invite readers to step up to the plate and explore this quirky correlation with us as we take a swing at unraveling the mysterious link between the "Aubrey factor" and Justin Upton's run production. With statistical significance and a dash of whimsy, our findings may just be a home run in uncovering the amusing influence of baby names on baseball prowess.

ChatGPT:

"Aubrey factor," "Justin Upton run totals," "baseball player names and performance," "US Social Security Administration baby names data," "Baseball Reference statistics," "correlation coefficient in baseball," "name popularity and success," "baby names and sports performance," "Aubrey name trend impact on baseball player."

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

Justin Upton's yearly run total
Source: Baseball Reference
See what else correlates with Justin Upton's yearly run total

Correlation r = 0.8358957 (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 = 0.6987216 (Coefficient of determination)
This means 69.9% of the change in the one variable (i.e., Justin Upton's yearly run total) is predictable based on the change in the other (i.e., Popularity of the first name Aubrey) over the 16 years from 2007 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.5E-5. 0.0000550386587380720200000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. 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 0.84 in 0.0055% of random cases. Said differently, if you correlated 18,169 random variables Which I absolutely did.
with the same 15 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 15 because we have two variables measured over a period of 16 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.

[ 0.58, 0.94 ] 95% correlation confidence interval (using the Fisher z-transformation)
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: 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.
2007200820092010201120122013201420152016201720182019202020212022
Popularity of the first name Aubrey (Babies born)4644570355515506732382088114776675476679606753624737405336663117
Justin Upton's yearly run total (Runs Scored)1752847310510794778581100813420472




Why this works

  1. 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.
  2. Lack of causal connection: There is probably 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.
  3. 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 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.
  4. 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. 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. 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([4644,5703,5551,5506,7323,8208,8114,7766,7547,6679,6067,5362,4737,4053,3666,3117,])
array_2 = np.array([17,52,84,73,105,107,94,77,85,81,100,81,34,20,47,2,])
array_1_name = "Popularity of the first name Aubrey"
array_2_name = "Justin Upton's yearly run total"

# 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)



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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.

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Correlation ID: 2801 · Black Variable ID: 2430 · Red Variable ID: 245
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