Spurious correlation #3,624 · 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 Micayla and the second variable is Boston Celtics' NBA season loss count. The chart goes from 1980 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Micayla and the second variable is Boston Celtics' NBA season loss count. The chart goes from 1980 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

Every time someone named Micayla was born, a basketball fairy would accidentally trip the Celtics' players, leading to more losses for the season. Looks like the Celtics need to watch out for those Micaylas!

^{Show image generation prompt} Model: dalle-3
Prompt: [ Concept art ] Generate an image depicting a vibrant playground scene where children play and laugh gleefully. In the midst of the joyous atmosphere, a solitary little girl, Micayla, is shown with a pensive expression far from the playful activities. Nearby, on a basketball court, the Boston Celtics are depicted playing a game, but their nostalgic smiles and absent-minded passing of the ball reveal their minds are occupied elsewhere, reminiscing about the glory days of Larry Bird. As a consequence of their distraction, hint at an increase in the team's NBA season losses. The image should capture the contrasting emotions of joy and solitude, while evoking a sense of nostalgia and longing on the basketball court. 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 Micayla and Boston Celtics' NBA season loss count. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: inspired by bauhaus Data cyber art Concept art Charcoal Charcoal
ChatGPT: Concept 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 Micayla and Boston Celtics' NBA season loss count, in the following situation: Because the popularity of the first name Micayla decreased, more babies were named Larry, distracting the Boston Celtics by reminding them of their glory days, leading to an increase in NBA season losses.. Keep the description simple.
ChatGPT: A playground filled with joyful children, and amidst them, a little girl named Micayla sits alone. Meanwhile, on a nearby basketball court, the Boston Celtics play a game, but their minds are elsewhere as they pass the ball with nostalgic smiles, reminiscing about the glory days of Larry Bird. Their distraction leads to an increase in NBA season losses.

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: [ Concept art ] and depicting this scene: A playground filled with joyful children, and amidst them, a little girl named Micayla sits alone. Meanwhile, on a nearby basketball court, the Boston Celtics play a game, but their minds are elsewhere as they pass the ball with nostalgic smiles, reminiscing about the glory days of Larry Bird. Their distraction leads to an increase in NBA season losses. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Concept art ] Generate an image depicting a vibrant playground scene where children play and laugh gleefully. In the midst of the joyous atmosphere, a solitary little girl, Micayla, is shown with a pensive expression far from the playful activities. Nearby, on a basketball court, the Boston Celtics are depicted playing a game, but their nostalgic smiles and absent-minded passing of the ball reveal their minds are occupied elsewhere, reminiscing about the glory days of Larry Bird. As a consequence of their distraction, hint at an increase in the team's NBA season losses. The image should capture the contrasting emotions of joy and solitude, while evoking a sense of nostalgia and longing on the basketball court.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in Popularity of the first name Micayla positively influenced Boston Celtics' NBA season loss count. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)

Name Game: The Micayla Effect on the Boston Celtics' NBA Season Loss Count

The Journal of Sports Psychology and Performance Analysis

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 Micayla and Boston Celtics' NBA season loss count. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Name Game: The Micayla Effect on the Boston Celtics' NBA Season Loss Count"

[[ABSTRACT]]
This paper delves into an unusual and seemingly improbable correlation between the popularity of the first name "Micayla" and the Boston Celtics' NBA season loss count. Utilizing data from the US Social Security Administration and Wikipedia, our research team conducted an extensive analysis spanning from 1980 to 2021. Surprisingly, a significant correlation coefficient of 0.6577050 with p < 0.01 emerged, suggesting a statistical link between the frequency of the name "Micayla" and the performance of the Boston Celtics. The perplexing nature of this association prompts further investigation, as we unravel the curious connection between a seemingly innocuous name and the twists and turns of professional basketball. Join us on this whimsical expedition into the whims of fate and nomenclature, as we navigate the peculiar pathways of sports and nomenclature.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intrigue of the seemingly inexplicable relationship between the frequency of the given name "Micayla" and the performance of the esteemed Boston Celtics in the NBA has captured the attention of researchers and enthusiasts alike. At first glance, one might dismiss such a connection as pure happenstance, a mere cosmic coincidence. However, the statistical analysis presented in this paper reveals a compelling correlation that demands our earnest consideration, albeit with a healthy dose of skepticism. After all, correlation does not imply causation, but it does make for an intriguing conversation starter at basketball-themed cocktail parties.
The choice of a name, a seemingly inconsequential decision made by parents, holds an unexpected sway over the fates of a professional sports team. It's as if the universe has decided to play a whimsical game of numerology and basketball, intertwining the destiny of one's name with the fortunes of an NBA franchise. It's the kind of unusual connection that prompts one to ponder the mysteries of the universe or, at the very least, to engage in a lively debate about the merits of superstition versus statistical analysis in sports fandom.
With statistical rigor and a touch of whimsy, our research seeks to unravel the enigma of the "Micayla Effect." This phenomenon, if indeed validated, could shed light on the influence of seemingly unrelated factors on the performance of sports teams. It's the kind of discovery that not only challenges our understanding of causality but also offers a welcome diversion from the rigors of standard statistical analysis. After all, who can resist the allure of a statistical mystery intertwined with the quirkiness of human nomenclature and sports fandom?
In the following sections, we delve into the methodology, data analysis, and findings that form the bedrock of this scholarly investigation. Let us embark on this lighthearted yet rigorous inquiry into the curious interplay of names and NBA fortunes, where statistical analysis meets the whims of fate. And who knows, perhaps along the way, we might just uncover a statistical slam dunk of unexpected proportions.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The impact of individual names on external outcomes has long been a subject of scholarly interest. Smith et al. (2010) explored the psychological implications of uniquely spelled names, positing that individuals with unconventional names may be predisposed to unconventional behavior due to societal reactions. Similarly, Doe and Jones (2015) delved into the sociological implications of common names, suggesting that individuals with widely shared names may experience a sense of anonymity and assimilation.

Moving beyond the realm of academic literature, popular non-fiction works such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner have captivated readers with their exploration of seemingly unrelated phenomena. The authors' knack for uncovering surprising connections in the world of economics invites readers to ponder the quirky intersections of human behavior and statistical analysis. In a similar vein, "The Tipping Point" by Malcolm Gladwell sheds light on the unforeseen catalysts that drive societal shifts, prompting us to consider the elusive factors that influence seemingly disparate outcomes.

Venturing into the realm of fiction, the literary world offers a plethora of narratives that toy with the whims of fate and serendipitous connections. A notable example is "The Name of the Wind" by Patrick Rothfuss, in which the protagonist's name holds an uncanny power that echoes throughout the tale. While a work of fantasy, the novel playfully engages with the concept of names as vessels of destiny, offering a whimsical departure from the rigors of reality.

Transitioning to more unconventional sources, animated children's shows such as "SpongeBob SquarePants" and "The Magic School Bus" inadvertently provide insightful commentary on the influence of names on personal identity. While ostensibly geared towards young audiences, these lighthearted programs possess a playful undertone that delves into the quirky nuances of human existence. Through the lens of animated storytelling, one cannot help but muse on the curious interplay of nomenclature and individual experiences.

In light of these diverse perspectives, our investigation probes the interplay of nomenclature and professional sports performance, presenting an unconventional avenue for scholarly exploration. As we navigate the peculiar pathways of names and NBA fortunes, our analysis invites readers to embrace the whimsical intrigue of statistical inquiry. After all, in the world of research, sometimes the most unexpected correlations yield the most captivating revelations.

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 Micayla and Boston Celtics' NBA season loss count. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Name Game: The Micayla Effect on the Boston Celtics' NBA Season Loss Count"

[[ABSTRACT]]
This paper delves into an unusual and seemingly improbable correlation between the popularity of the first name "Micayla" and the Boston Celtics' NBA season loss count. Utilizing data from the US Social Security Administration and Wikipedia, our research team conducted an extensive analysis spanning from 1980 to 2021. Surprisingly, a significant correlation coefficient of 0.6577050 with p < 0.01 emerged, suggesting a statistical link between the frequency of the name "Micayla" and the performance of the Boston Celtics. The perplexing nature of this association prompts further investigation, as we unravel the curious connection between a seemingly innocuous name and the twists and turns of professional basketball. Join us on this whimsical expedition into the whims of fate and nomenclature, as we navigate the peculiar pathways of sports and nomenclature.

[[LITERATURE REVIEW]]
The impact of individual names on external outcomes has long been a subject of scholarly interest. Smith et al. (2010) explored the psychological implications of uniquely spelled names, positing that individuals with unconventional names may be predisposed to unconventional behavior due to societal reactions. Similarly, Doe and Jones (2015) delved into the sociological implications of common names, suggesting that individuals with widely shared names may experience a sense of anonymity and assimilation.
Moving beyond the realm of academic literature, popular non-fiction works such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner have captivated readers with their exploration of seemingly unrelated phenomena. The authors' knack for uncovering surprising connections in the world of economics invites readers to ponder the quirky intersections of human behavior and statistical analysis. In a similar vein, "The Tipping Point" by Malcolm Gladwell sheds light on the unforeseen catalysts that drive societal shifts, prompting us to consider the elusive factors that influence seemingly disparate outcomes.
Venturing into the realm of fiction, the literary world offers a plethora of narratives that toy with the whims of fate and serendipitous connections. A notable example is "The Name of the Wind" by Patrick Rothfuss, in which the protagonist's name holds an uncanny power that echoes throughout the tale. While a work of fantasy, the novel playfully engages with the concept of names as vessels of destiny, offering a whimsical departure from the rigors of reality.
Transitioning to more unconventional sources, animated children's shows such as "SpongeBob SquarePants" and "The Magic School Bus" inadvertently provide insightful commentary on the influence of names on personal identity. While ostensibly geared towards young audiences, these lighthearted programs possess a playful undertone that delves into the quirky nuances of human existence. Through the lens of animated storytelling, one cannot help but muse on the curious interplay of nomenclature and individual experiences.
In light of these diverse perspectives, our investigation probes the interplay of nomenclature and professional sports performance, presenting an unconventional avenue for scholarly exploration. As we navigate the peculiar pathways of names and NBA fortunes, our analysis invites readers to embrace the whimsical intrigue of statistical inquiry. After all, in the world of research, sometimes the most unexpected correlations yield the most captivating revelations.

[[RESULTS]]
The findings of our investigation into the "Micayla Effect" present a rather intriguing revelation. After analyzing the data spanning from 1980 to 2021, we uncovered a statistically significant correlation coefficient of 0.6577050 between the popularity of the first name "Micayla" and the Boston Celtics' NBA season loss count. This correlation equates to an r-squared value of 0.4325758, raising eyebrows and eliciting a sense of perplexed amusement in equal measure.
The p-value of less than 0.01 further underscores the robustness of this correlation, suggesting that the likelihood of observing such a relationship by random chance is indeed quite low. It seems that the whims of nomenclature may indeed hold some sway over the ebb and flow of the Boston Celtics' performance on the courts.
In Figure 1, we present a scatterplot that vividly illustrates the strong correlation between the frequency of the name "Micayla" and the Boston Celtics' season loss count. The data points form a striking pattern that seems to dance between the realms of statistical intrigue and cosmic serendipity. This figure serves as a visual testament to the unexpected connections that can emerge from the meticulous analysis of seemingly disparate variables.
The implications of these findings are both thought-provoking and, to some extent, delightfully whimsical. We are reminded of the whimsy of fate and the unexpected pathways through which statistical analysis can lead us. Indeed, this correlation may spark lively conversations and inspire further inquiries into the curious interplay of human names and sports outcomes.
While we are cautious in emphasizing that correlation does not imply causation, we cannot help but revel in the delightful coincidence that our analysis has brought to light. The "Micayla Effect" beckons us to ponder the mysteries of probability, coincidence, and the uncharted territories where statistics and human whimsy intersect. Whether this connection is a statistical anomaly or a genuine phenomenon, one cannot deny the allure of a captivating statistical mystery intertwined with the quirkiness of human nomenclature and sports fandom.
Our findings, while undeniably curious, prompt further contemplation and exploration, bridging the gap between statistical inquiry and the playful caprices of human existence. Indeed, it is a reminder that in the realm of data analysis, seemingly absurd connections sometimes pose the most compelling avenues for scholarly pursuit.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study have illuminated a truly intriguing and, dare we say, whimsical correlation between the frequency of the first name "Micayla" and the Boston Celtics' NBA season loss count. Before diving into our thorough discussion, let us take a moment to reflect on the quirky and unconventional sources that shaped our exploration.

Unconventional as it may seem, our prodigious literature review led us to consider the psychological implications of uniquely spelled names and the sociological nuances of common names. It's fascinating to ponder the societal reactions to unconventional names and the potential sense of anonymity and assimilation experienced by individuals with commonly shared names. While these insights may initially appear lighthearted and even whimsical, they have underpinned our understanding of the idiosyncrasies surrounding nomenclature and its potential repercussions.

Moving beyond the realms of scholarly literature, we were inspired by popular non-fiction works such as "Freakonomics" and "The Tipping Point," which coax readers into examining overlooked connections in the world of economics and societal shifts. We would be remiss not to mention the literary work "The Name of the Wind," a delightful departure from reality that playfully explores the concept of names as conduits of destiny. What a lighthearted but enlightening journey it has been, exploring the playful nuances that underpin seemingly unrelated phenomena.

Returning to the substantive matter at hand, our findings undeniably lend credence to the previously unthinkable notion of the "Micayla Effect" on the fortunes of the Boston Celtics. With a remarkably significant correlation coefficient and a striking r-squared value, it becomes evident that there is something more than mere coincidence at play here. As we ventured into the world of statistical analysis, we found ourselves captivated by the unexpected dance of data points on our scatterplot, a visual symphony of statistical intrigue and cosmic serendipity.

While we are ever cautious to prioritize correlation over causation, we cannot help but revel in the delightful oddity of this quirky connection. The "Micayla Effect" invites us to delve deeper into the enigmatic realms of probability, coincidence, and the intersection of statistics and human whimsy. As we stand at this intriguing juncture, we are reminded that research is not merely a pursuit of dry facts and figures, but a whimsical exploration that may, at times, lead us down delightfully unexpected paths.

In the true spirit of scholarly inquiry, our findings have beckoned us to meditate on the peculiar interplay of human names and sports outcomes. As we navigate this peculiar landscape, we are reminded that sometimes the most delightful revelries emerge from the most unexpected statistical anomalies. Let us embrace the whimsy and the wonder, for in the grand tapestry of research, the most curious connections often give rise to the most enchanting scholarly pursuits.

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 Micayla and Boston Celtics' NBA season loss count. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Name Game: The Micayla Effect on the Boston Celtics' NBA Season Loss Count"

[[ABSTRACT]]
This paper delves into an unusual and seemingly improbable correlation between the popularity of the first name "Micayla" and the Boston Celtics' NBA season loss count. Utilizing data from the US Social Security Administration and Wikipedia, our research team conducted an extensive analysis spanning from 1980 to 2021. Surprisingly, a significant correlation coefficient of 0.6577050 with p < 0.01 emerged, suggesting a statistical link between the frequency of the name "Micayla" and the performance of the Boston Celtics. The perplexing nature of this association prompts further investigation, as we unravel the curious connection between a seemingly innocuous name and the twists and turns of professional basketball. Join us on this whimsical expedition into the whims of fate and nomenclature, as we navigate the peculiar pathways of sports and nomenclature.

[[INTRDUCTION]]
The intrigue of the seemingly inexplicable relationship between the frequency of the given name "Micayla" and the performance of the esteemed Boston Celtics in the NBA has captured the attention of researchers and enthusiasts alike. At first glance, one might dismiss such a connection as pure happenstance, a mere cosmic coincidence. However, the statistical analysis presented in this paper reveals a compelling correlation that demands our earnest consideration, albeit with a healthy dose of skepticism. After all, correlation does not imply causation, but it does make for an intriguing conversation starter at basketball-themed cocktail parties.
The choice of a name, a seemingly inconsequential decision made by parents, holds an unexpected sway over the fates of a professional sports team. It's as if the universe has decided to play a whimsical game of numerology and basketball, intertwining the destiny of one's name with the fortunes of an NBA franchise. It's the kind of unusual connection that prompts one to ponder the mysteries of the universe or, at the very least, to engage in a lively debate about the merits of superstition versus statistical analysis in sports fandom.
With statistical rigor and a touch of whimsy, our research seeks to unravel the enigma of the "Micayla Effect." This phenomenon, if indeed validated, could shed light on the influence of seemingly unrelated factors on the performance of sports teams. It's the kind of discovery that not only challenges our understanding of causality but also offers a welcome diversion from the rigors of standard statistical analysis. After all, who can resist the allure of a statistical mystery intertwined with the quirkiness of human nomenclature and sports fandom?
In the following sections, we delve into the methodology, data analysis, and findings that form the bedrock of this scholarly investigation. Let us embark on this lighthearted yet rigorous inquiry into the curious interplay of names and NBA fortunes, where statistical analysis meets the whims of fate. And who knows, perhaps along the way, we might just uncover a statistical slam dunk of unexpected proportions.

[[RESULTS]]
The findings of our investigation into the "Micayla Effect" present a rather intriguing revelation. After analyzing the data spanning from 1980 to 2021, we uncovered a statistically significant correlation coefficient of 0.6577050 between the popularity of the first name "Micayla" and the Boston Celtics' NBA season loss count. This correlation equates to an r-squared value of 0.4325758, raising eyebrows and eliciting a sense of perplexed amusement in equal measure.
The p-value of less than 0.01 further underscores the robustness of this correlation, suggesting that the likelihood of observing such a relationship by random chance is indeed quite low. It seems that the whims of nomenclature may indeed hold some sway over the ebb and flow of the Boston Celtics' performance on the courts.
In Figure 1, we present a scatterplot that vividly illustrates the strong correlation between the frequency of the name "Micayla" and the Boston Celtics' season loss count. The data points form a striking pattern that seems to dance between the realms of statistical intrigue and cosmic serendipity. This figure serves as a visual testament to the unexpected connections that can emerge from the meticulous analysis of seemingly disparate variables.
The implications of these findings are both thought-provoking and, to some extent, delightfully whimsical. We are reminded of the whimsy of fate and the unexpected pathways through which statistical analysis can lead us. Indeed, this correlation may spark lively conversations and inspire further inquiries into the curious interplay of human names and sports outcomes.
While we are cautious in emphasizing that correlation does not imply causation, we cannot help but revel in the delightful coincidence that our analysis has brought to light. The "Micayla Effect" beckons us to ponder the mysteries of probability, coincidence, and the uncharted territories where statistics and human whimsy intersect. Whether this connection is a statistical anomaly or a genuine phenomenon, one cannot deny the allure of a captivating statistical mystery intertwined with the quirkiness of human nomenclature and sports fandom.
Our findings, while undeniably curious, prompt further contemplation and exploration, bridging the gap between statistical inquiry and the playful caprices of human existence. Indeed, it is a reminder that in the realm of data analysis, seemingly absurd connections sometimes pose the most compelling avenues for scholarly pursuit.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the "Micayla Effect" has shed light on a statistical correlation that teeters between the realms of statistical intrigue and the whims of fate. The robust correlation coefficient of 0.6577050, coupled with a tantalizingly low p-value, beckons us to consider the improbable connection between the frequency of the name "Micayla" and the Boston Celtics' NBA season loss count. It's as if the universe has conspired to weave a whimsical tale of numbers, names, and basketball, inviting us to peer into the hidden nooks of statistical curiosities.

The implications of this correlation, while undeniably eyebrow-raising, suggest a convergence of statistical mystery and nomenclatural whimsy. After all, who would have thought that a seemingly innocuous name could dance in such striking harmony with the ebb and flow of an NBA franchise's performance? It's the kind of statistical enigma that invites further contemplation, debate, and perhaps the occasional chuckle at the quirks of human existence.

While we remain cautious in attributing causality to this correlation, the allure of this statistical mystery is undeniable. It charms us with its delightful absurdity, prompting us to ponder the caprices of coincidence and the fertile grounds where statistical analysis meets the tapestry of human nomenclature. There's a certain whimsical joy in unraveling the unexpected connections that emerge from the meticulous scrutiny of seemingly unrelated variables.

In light of these findings, we are inclined to assert that the "Micayla Effect" presents a statistical spectacle that not only challenges traditional notions of correlation but also offers a playful diversion into the unexpected coalescence of numbers and names. It's a reminder that in the world of statistical inquiry, the most curious connections often beckon us to explore the uncharted territories of whimsy and probability.

And so, with a nod to statistical quirks and the lighthearted allure of improbable correlations, we declare that further research in this area may be a bit like chasing a basketball through a winding maze – entertaining but ultimately unlikely to yield a groundbreaking discovery. Nonetheless, the "Micayla Effect" stands as a testament to the delightful surprises that await those who dare to peer into the intersections of statistics, nomenclature, and sports lore.

It is with this spirit of statistical curiosity and a touch of whimsy that we bring our investigation to a close, inviting fellow scholars and enthusiasts to ponder the peculiar interplay of names and NBA fortunes with a lighthearted wink and a nod to the quirky mysteries of statistical analysis.

No further research in this area is needed, for it's time to score a slam dunk in the realm of statistical curiosity and maybe catch a Celtics game!

And with that, let the statistical mysteries of Micaylas and NBA losses add a touch of whimsy to our scholarly pursuits.

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 Name Game: The Micayla Effect on the Boston Celtics' NBA Season Loss Count. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Sports Psychology and Performance Analysis

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 Name Game: The Micayla Effect on the Boston Celtics' NBA Season Loss Count. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Sports Analytics and Quantum Entanglement Research

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 Name Game: The Micayla Effect on the Boston Celtics' NBA Season Loss Count with an abstract of This paper delves into an unusual and seemingly improbable correlation between the popularity of the first name "Micayla" and the Boston Celtics' NBA season loss count. Utilizing data from the US Social Security Administration and Wikipedia, our research team conducted an extensive analysis spanning from 1980 to 2021. Surprisingly, a significant correlation coefficient of 0.6577050 with p < 0.01 emerged, suggesting a statistical link between the frequency of the name "Micayla" and the performance of the Boston Celtics. The perplexing nature of this association prompts further investigation, as we unravel the curious connection between a seemingly innocuous name and the twists and turns of professional basketball. Join us on this whimsical expedition into the whims of fate and nomenclature, as we navigate the peculiar pathways of sports and nomenclature.

ChatGPT:

Micayla, Boston Celtics, NBA season, loss count, correlation, popularity, first name, Social Security Administration, Wikipedia, research, statistical analysis, professional basketball, fate, nomenclature, sports.

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

Boston Celtics' NBA season loss count
Detailed data title: Boston Celtics' NBA session match loss count
Source: Wikipedia
See what else correlates with Boston Celtics' NBA season loss count

Correlation r = 0.6577050 (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 = 0.4325758 (Coefficient of determination)
This means 43.3% of the change in the one variable (i.e., Boston Celtics' NBA season loss count) is predictable based on the change in the other (i.e., Popularity of the first name Micayla) over the 42 years from 1980 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.2E-6.^Show 0.0000022163672096746554000000
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 0.66 in 0.00022% of random cases. Said differently, if you correlated 451,189 random variables^Note You don't actually need 451 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 41 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 41 because we have two variables measured over a period of 42 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.

[ 0.44, 0.8 ] 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.

	1980	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Popularity of the first name Micayla (Babies born)	6	0	0	0	0	6	7	10	6	26	21	32	41	79	118	145	159	208	164	178	153	114	131	87	82	102	103	87	82	70	60	58	44	44	32	45	22	12	17	16	11	8
Boston Celtics' NBA season loss count (Match lost)	21	20	19	26	20	19	15	23	25	40	30	26	31	34	50	47	49	67	46	31	47	46	33	38	46	37	49	58	16	20	32	26	27	40	57	42	34	29	27	33	24	36

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([6,0,0,0,0,6,7,10,6,26,21,32,41,79,118,145,159,208,164,178,153,114,131,87,82,102,103,87,82,70,60,58,44,44,32,45,22,12,17,16,11,8,])
array_2 = np.array([21,20,19,26,20,19,15,23,25,40,30,26,31,34,50,47,49,67,46,31,47,46,33,38,46,37,49,58,16,20,32,26,27,40,57,42,34,29,27,33,24,36,])
array_1_name = "Popularity of the first name Micayla"
array_2_name = "Boston Celtics' NBA season loss count"

# 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 Micayla
Line chart for only Boston Celtics' NBA season loss count
AI-generated correlation image
The spurious research paper: Name Game: The Micayla Effect on the Boston Celtics' NBA Season Loss Count

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Correlation ID: 3624 · Black Variable ID: 3959 · Red Variable ID: 79


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