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Spurious correlation #3,839 · 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 Maeve and the second variable is Taiwan Semiconductor Manufacturing Company's stock price (TSM).  The chart goes from 2002 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the name Maeve gained popularity, more parents were inspired by the Celtic heritage and unique sound. This led to a surge in demand for baby name consultation services, causing a shortage in consultants. To cope with the shortage, these consultants turned to advanced technology for efficiency, increasing their reliance on electronic devices. This unexpected demand for electronics prompted a sudden need for semiconductor chips, with Taiwan Semiconductor Manufacturing Company (TSM) being a key supplier. The ripple effect of the Maeve naming trend ultimately contributed to TSM's stock price increase. Remember, while this connection may seem far-fetched, in the world of stock prices, even the most unexpected factors can play a role!

Model: dalle-3
Prompt: [ Cutsy art illustration ] Generate an image of a group of charmingly animated characters gathered around a retro-style TV screen with exaggerated expressions of excitement as they watch the show "Sex Education." In the background, display a stock market ticker showing the TSM stock price rising steadily, with a clear visual indication of upward graph movement. Additionally, subtly integrate the name "Maeve" on a name tag worn by one of the characters in the TV show, communicating the increasing trend of the name and its impact on the rising demand for electronic devices, contributing to the surge in TSM's stock price. The focus should be on the characters' reactions and the inclusion of the subtle background elements. 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 Maeve and Taiwan Semiconductor Manufacturing Company's stock price (TSM). 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: An image that looks like it is a scene from 'Star Wars' inspired by bauhaus Cute 2D animation Cutsy art illustration A scene from Skyrim
ChatGPT: Cutsy art illustration

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 Maeve and Taiwan Semiconductor Manufacturing Company's stock price (TSM), in the following situation: Because more people named Maeve means more fans of Maeve from the TV show "Sex Education," leading to increased demand for electronic devices and boosting TSM's stock.. Keep the description simple.
ChatGPT: In the scene, we see a group of people gathered around a TV screen, all watching the show "Sex Education" with excitement. In the background, a stock market ticker is shown, with the TSM stock price rising steadily. The name "Maeve" appears on a name tag worn by one of the characters on the TV show, indicating a growing popularity of the name and its influence on the increased demand for electronic devices, driving up TSM's stock price.

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: [ Cutsy art illustration ] and depicting this scene: In the scene, we see a group of people gathered around a TV screen, all watching the show "Sex Education" with excitement. In the background, a stock market ticker is shown, with the TSM stock price rising steadily. The name "Maeve" appears on a name tag worn by one of the characters on the TV show, indicating a growing popularity of the name and its influence on the increased demand for electronic devices, driving up TSM's stock price. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Cutsy art illustration ] Generate an image of a group of charmingly animated characters gathered around a retro-style TV screen with exaggerated expressions of excitement as they watch the show "Sex Education." In the background, display a stock market ticker showing the TSM stock price rising steadily, with a clear visual indication of upward graph movement. Additionally, subtly integrate the name "Maeve" on a name tag worn by one of the characters in the TV show, communicating the increasing trend of the name and its impact on the rising demand for electronic devices, contributing to the surge in TSM's stock price. The focus should be on the characters' reactions and the inclusion of the subtle background elements.

*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 an increase in Popularity of the first name Maeve caused Taiwan Semiconductor Manufacturing Company's stock price (TSM) to increase.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)
Name Game: The Maeve Effect on TSM Stock Price

The Journal of Quirky Economics

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 Maeve and Taiwan Semiconductor Manufacturing Company's stock price (TSM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, just make it sound clever.

Your research team used data from US Social Security Administration and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9847163 and p < 0.01 for 2002 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]]
"Name Game: The Maeve Effect on TSM Stock Price"

[[ABSTRACT]]
This paper scrutinizes the potential influence of the first name Maeve on the stock price of Taiwan Semiconductor Manufacturing Company (TSM). Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv) spanning the years 2002 to 2022, our research team conducted a comprehensive analysis. The correlation coefficient of 0.9847163 revealed a remarkable connection between the prevalence of the name Maeve and the stock performance of TSM, with a p-value of less than 0.01 further underscoring the significance of this relationship. Our findings shed light on an unexpected yet intriguing aspect of stock market behavior, proving that sometimes, the seemingly arbitrary can hold unforeseen sway over financial markets.


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 Maeve and Taiwan Semiconductor Manufacturing Company's stock price (TSM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
"Name Game: The Maeve Effect on TSM Stock Price"

[[ABSTRACT]]
This paper scrutinizes the potential influence of the first name Maeve on the stock price of Taiwan Semiconductor Manufacturing Company (TSM). Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv) spanning the years 2002 to 2022, our research team conducted a comprehensive analysis. The correlation coefficient of 0.9847163 revealed a remarkable connection between the prevalence of the name Maeve and the stock performance of TSM, with a p-value of less than 0.01 further underscoring the significance of this relationship. Our findings shed light on an unexpected yet intriguing aspect of stock market behavior, proving that sometimes, the seemingly arbitrary can hold unforeseen sway over financial markets.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

In the labyrinthine world of stock market analysis, uncovering the myriad factors that sway stock prices is akin to solving a Rubik's cube blindfolded—challenging, yet oddly exhilarating. Among the plethora of indispensable data points and indicators, there exist unexpected and seemingly unrelated variables that dance through the market like uninvited guests at a grand soirée. In this capricious waltz of market forces, we embark on a curious exploration into the potential impact of the first name Maeve on the stock price of the Taiwan Semiconductor Manufacturing Company (TSM).

One might question, "What, pray tell, does a name have to do with a company's stock performance?" Well, dear reader, that is the very question that has tickled our academic fancy and led us down this whimsical rabbit hole of conjecture and analysis. As we dust off our data sets and buckle up for this intellectual rodeo, we invite you to join us on this zany venture—a journey replete with statistical wizardry, market musings, and perhaps a sprinkling of serendipity.

The Maeve Effect, as we affectionately dub it, introduces a novel and intriguing facet to the mosaic of stock market anomalies. Our endeavor is not merely a peering into the idiosyncrasies of nomenclature, but rather a peek behind the proverbial curtain of financial markets—a realm where the eccentric and the conventional converge in a beguiling tango. And indeed, we aim to shed light on this rather peculiar intersection, where the ebb and flow of stock prices intersects with the ebb and flow of appellations.

As we delve into this investigation, we embark with equal parts earnestness and jocularity—after all, what is academia without a dash of levity? Through rigorous analysis and a sprinkling of good-humored banter, we aim to unravel the enigmatic interplay between the popularity of the name Maeve and the stock price of TSM. So, fasten your seatbelts and stow away your preconceptions as we traverse this delightfully unconventional expedition into the enigmatic corridors of market behavior.


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 Maeve and Taiwan Semiconductor Manufacturing Company's stock price (TSM). 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 name some movies that you watched that are tangentially related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
"Name Game: The Maeve Effect on TSM Stock Price"

[[ABSTRACT]]
This paper scrutinizes the potential influence of the first name Maeve on the stock price of Taiwan Semiconductor Manufacturing Company (TSM). Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv) spanning the years 2002 to 2022, our research team conducted a comprehensive analysis. The correlation coefficient of 0.9847163 revealed a remarkable connection between the prevalence of the name Maeve and the stock performance of TSM, with a p-value of less than 0.01 further underscoring the significance of this relationship. Our findings shed light on an unexpected yet intriguing aspect of stock market behavior, proving that sometimes, the seemingly arbitrary can hold unforeseen sway over financial markets.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the labyrinthine world of stock market analysis, uncovering the myriad factors that sway stock prices is akin to solving a Rubik's cube blindfolded—challenging, yet oddly exhilarating. Among the plethora of indispensable data points and indicators, there exist unexpected and seemingly unrelated variables that dance through the market like uninvited guests at a grand soirée. In this capricious waltz of market forces, we embark on a curious exploration into the potential impact of the first name Maeve on the stock price of the Taiwan Semiconductor Manufacturing Company (TSM).
One might question, "What, pray tell, does a name have to do with a company's stock performance?" Well, dear reader, that is the very question that has tickled our academic fancy and led us down this whimsical rabbit hole of conjecture and analysis. As we dust off our data sets and buckle up for this intellectual rodeo, we invite you to join us on this zany venture—a journey replete with statistical wizardry, market musings, and perhaps a sprinkling of serendipity.
The Maeve Effect, as we affectionately dub it, introduces a novel and intriguing facet to the mosaic of stock market anomalies. Our endeavor is not merely a peering into the idiosyncrasies of nomenclature, but rather a peek behind the proverbial curtain of financial markets—a realm where the eccentric and the conventional converge in a beguiling tango. And indeed, we aim to shed light on this rather peculiar intersection, where the ebb and flow of stock prices intersects with the ebb and flow of appellations.
As we delve into this investigation, we embark with equal parts earnestness and jocularity—after all, what is academia without a dash of levity? Through rigorous analysis and a sprinkling of good-humored banter, we aim to unravel the enigmatic interplay between the popularity of the name Maeve and the stock price of TSM. So, fasten your seatbelts and stow away your preconceptions as we traverse this delightfully unconventional expedition into the enigmatic corridors of market behavior.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Historical research on the influence of names in various contexts has yielded insightful findings. Smith and Doe, in their seminal work "The Impact of Names," uncover the psychological implications of names and their societal reverberations. Meanwhile, Jones et al. explore the intricate dance between nomenclature and cultural predispositions in "Names and Narratives: A Sociolinguistic Perspective." These studies, albeit not directly related to the financial domain, provide a foundational understanding of the multifaceted roles that names play in human interactions and decision-making processes.

Expanding beyond the realm of academic literature, non-fiction works such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner offer compelling perspectives on unconventional factors that shape markets and human behavior. The authors' examination of seemingly counterintuitive influences on various phenomena underscores the significance of probing unusual variables, setting the stage for our unconventional investigation.

Further afield, fictional narratives such as Jeffrey Eugenides' "Middlesex" and Colm Toibin's "Brooklyn" weave compelling stories around characters with distinctive names, tantalizing the imagination with tangential connections to our studious pursuit. While these narratives remain divorced from financial markets in their thematic content, the nuanced portrayal of personal identities and societal norms serves as an intriguing backdrop to our exploration of the Maeve-TSM nexus.

To add a touch of cinematic tangibility to our avant-garde inquiry, movies such as "The Social Network" and "Moneyball" offer insightful portrayals of the capricious nature of market dynamics and the unassuming variables that often underpin financial success. Though these celluloid creations do not broach the subject of name influences on stock performance, they serve as engaging reminders of the multifarious elements at play within the opaque sphere of financial markets.

Our foray into the realm of empirical inquiry is not without its whimsical diversions, and we beckon the reader to traverse this labyrinth of literary and visual touchpoints with an open mind and a keen sense of humor – for in the pulsating heartbeat of academia, curiosity and joviality are often the perfect dance partners.


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 Maeve and Taiwan Semiconductor Manufacturing Company's stock price (TSM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and LSEG Analytics (Refinitiv) . You used data from 2002 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]]
"Name Game: The Maeve Effect on TSM Stock Price"

[[ABSTRACT]]
This paper scrutinizes the potential influence of the first name Maeve on the stock price of Taiwan Semiconductor Manufacturing Company (TSM). Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv) spanning the years 2002 to 2022, our research team conducted a comprehensive analysis. The correlation coefficient of 0.9847163 revealed a remarkable connection between the prevalence of the name Maeve and the stock performance of TSM, with a p-value of less than 0.01 further underscoring the significance of this relationship. Our findings shed light on an unexpected yet intriguing aspect of stock market behavior, proving that sometimes, the seemingly arbitrary can hold unforeseen sway over financial markets.

[[INTRODUCTION]]
In the labyrinthine world of stock market analysis, uncovering the myriad factors that sway stock prices is akin to solving a Rubik's cube blindfolded—challenging, yet oddly exhilarating. Among the plethora of indispensable data points and indicators, there exist unexpected and seemingly unrelated variables that dance through the market like uninvited guests at a grand soirée. In this capricious waltz of market forces, we embark on a curious exploration into the potential impact of the first name Maeve on the stock price of the Taiwan Semiconductor Manufacturing Company (TSM).
One might question, "What, pray tell, does a name have to do with a company's stock performance?" Well, dear reader, that is the very question that has tickled our academic fancy and led us down this whimsical rabbit hole of conjecture and analysis. As we dust off our data sets and buckle up for this intellectual rodeo, we invite you to join us on this zany venture—a journey replete with statistical wizardry, market musings, and perhaps a sprinkling of serendipity.
The Maeve Effect, as we affectionately dub it, introduces a novel and intriguing facet to the mosaic of stock market anomalies. Our endeavor is not merely a peering into the idiosyncrasies of nomenclature, but rather a peek behind the proverbial curtain of financial markets—a realm where the eccentric and the conventional converge in a beguiling tango. And indeed, we aim to shed light on this rather peculiar intersection, where the ebb and flow of stock prices intersects with the ebb and flow of appellations.
As we delve into this investigation, we embark with equal parts earnestness and jocularity—after all, what is academia without a dash of levity? Through rigorous analysis and a sprinkling of good-humored banter, we aim to unravel the enigmatic interplay between the popularity of the name Maeve and the stock price of TSM. So, fasten your seatbelts and stow away your preconceptions as we traverse this delightfully unconventional expedition into the enigmatic corridors of market behavior.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

In order to unravel the enigmatic connection between the popularity of the first name Maeve and the stock price of Taiwan Semiconductor Manufacturing Company (TSM), our research team undertook a methodic and slightly ludicrous research approach. The primary data sources for this investigation were the US Social Security Administration, from which we obtained historical data on the prevalence of the name Maeve, and LSEG Analytics (Refinitiv) to procure extensive financial data related to TSM from the years 2002 to 2022. Our methodology can be likened to a culinary concoction, employing a mix of tried-and-true ingredients and a dash of serendipitous flavor.

First, we combed through the annals of the US Social Security Administration's birth name database with the meticulousness of a librarian hunting for a misplaced tome. We collected data on the frequency of the name Maeve across the years, meticulously tracing its rise and fall like a stock chart in its own right. Once we gathered this treasure trove of nomenclature, we held it up to the light of statistical scrutiny, keen to discern any correlation between the ebb and flow of Maeves and the vicissitudes of stock trading.

Simultaneously, utilizing LSEG Analytics (Refinitiv), we delved into sundry financial metrics surrounding TSM, navigating through seas of stock prices, trading volumes, and market valuations. We cast our nets wide, reeling in copious amounts of financial data akin to a fisherman bringing in a bountiful haul. With these datasets in hand, we set about weaving a narrative that would do justice to the topsy-turvy tale of Maeve and TSM.

To analyze this eclectic mix of data, we employed a diverse suite of statistical tools, including correlation analysis, time series modeling, and even a sprinkling of Monte Carlo simulations for good measure. Our approach was akin to a symphony conductor deftly orchestrating a melodious blend of instruments, each statistical technique harmonizing with the next to compose a resonant melody of data insights.

It is important to note that this research endeavor was not without its quirks and surprises. The very nature of studying the correlation between a name's popularity and a company's stock price lends itself to an air of whimsy and the unexpected. As such, our methodology embraced this ambiguity, welcoming the unpredictability of our subject matter with open arms and a healthy dose of scholarly curiosity.

In sum, our methodology was an intricate dance of data collection, statistical analysis, and the occasional leap of faith—all in pursuit of untangling the curious and serendipitous connection between Maeve and TSM. With a fair share of academic rigor and a sprinkling of whimsical charm, our methodology strived to do justice to our offbeat subject matter, embodying the scholarly spirit of adventure and inquisition.

------
I included goofy analogies, whimsical language and a mix of complicated statistics and unorthodox research techniques. Let me know if you need something else!


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 Maeve and Taiwan Semiconductor Manufacturing Company's stock price (TSM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and LSEG Analytics (Refinitiv) .

For the time period 2002 to 2022, you found a correlation 0.9847163, r-squared of 0.9696661, 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]]
"Name Game: The Maeve Effect on TSM Stock Price"

[[ABSTRACT]]
This paper scrutinizes the potential influence of the first name Maeve on the stock price of Taiwan Semiconductor Manufacturing Company (TSM). Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv) spanning the years 2002 to 2022, our research team conducted a comprehensive analysis. The correlation coefficient of 0.9847163 revealed a remarkable connection between the prevalence of the name Maeve and the stock performance of TSM, with a p-value of less than 0.01 further underscoring the significance of this relationship. Our findings shed light on an unexpected yet intriguing aspect of stock market behavior, proving that sometimes, the seemingly arbitrary can hold unforeseen sway over financial markets.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the labyrinthine world of stock market analysis, uncovering the myriad factors that sway stock prices is akin to solving a Rubik's cube blindfolded—challenging, yet oddly exhilarating. Among the plethora of indispensable data points and indicators, there exist unexpected and seemingly unrelated variables that dance through the market like uninvited guests at a grand soirée. In this capricious waltz of market forces, we embark on a curious exploration into the potential impact of the first name Maeve on the stock price of the Taiwan Semiconductor Manufacturing Company (TSM).
One might question, "What, pray tell, does a name have to do with a company's stock performance?" Well, dear reader, that is the very question that has tickled our academic fancy and led us down this whimsical rabbit hole of conjecture and analysis. As we dust off our data sets and buckle up for this intellectual rodeo, we invite you to join us on this zany venture—a journey replete with statistical wizardry, market musings, and perhaps a sprinkling of serendipity.
The Maeve Effect, as we affectionately dub it, introduces a novel and intriguing facet to the mosaic of stock market anomalies. Our endeavor is not merely a peering into the idiosyncrasies of nomenclature, but rather a peek behind the proverbial curtain of financial markets—a realm where the eccentric and the conventional converge in a beguiling tango. And indeed, we aim to shed light on this rather peculiar intersection, where the ebb and flow of stock prices intersects with the ebb and flow of appellations.
As we delve into this investigation, we embark with equal parts earnestness and jocularity—after all, what is academia without a dash of levity? Through rigorous analysis and a sprinkling of good-humored banter, we aim to unravel the enigmatic interplay between the popularity of the name Maeve and the stock price of TSM. So, fasten your seatbelts and stow away your preconceptions as we traverse this delightfully unconventional expedition into the enigmatic corridors of market behavior.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The statistical analysis unveiled a striking correlation between the prevalence of the first name Maeve and the stock performance of Taiwan Semiconductor Manufacturing Company (TSM) over the period from 2002 to 2022. The correlation coefficient of 0.9847163 indicates a near-perfect positive relationship between the popularity of the name Maeve and the stock price of TSM. This finding provides empirical support for the notion that the name Maeve holds a peculiar influence over the stock performance of TSM, much like an unseen hand guiding the market through tumultuous waves.

Furthermore, the high R-squared value of 0.9696661 suggests that a substantial proportion of the variance in TSM stock prices can be explained by the prevalence of the name Maeve. This implies that the ebb and flow of Maeves in the world is intricately intertwined with the ebb and flow of TSM stock prices, creating a curious dance of market dynamics and nomenclature.

The p-value being less than 0.01 reinforces the robustness and significance of this relationship, lending further credibility to the Maeve Effect on TSM stock prices. It seems that the name Maeve is not just a moniker, but a silent maestro conducting the market movements with an elegant yet inexplicable finesse.

Figure 1 provides a visual representation of the strong correlation between the prevalence of the name Maeve and TSM stock prices, further underscoring the remarkable nature of this unexpected relationship. The scatterplot depicts a clear and discernible pattern, akin to a constellation of market movements that align with the celestial influence of the name Maeve.

These findings illuminate an unconventional and whimsical aspect of stock market behavior, challenging conventional wisdom and reminding us that in the complex tapestry of market dynamics, even the most unassuming variables can wield surprising clout. This revelatory connection between the first name Maeve and TSM stock prices offers a delightful twist in the saga of market predictability, infusing a touch of levity in an otherwise stoic arena of financial analysis.


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 Maeve and Taiwan Semiconductor Manufacturing Company's stock price (TSM). 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 Maeve Effect on TSM Stock Price"

[[ABSTRACT]]
This paper scrutinizes the potential influence of the first name Maeve on the stock price of Taiwan Semiconductor Manufacturing Company (TSM). Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv) spanning the years 2002 to 2022, our research team conducted a comprehensive analysis. The correlation coefficient of 0.9847163 revealed a remarkable connection between the prevalence of the name Maeve and the stock performance of TSM, with a p-value of less than 0.01 further underscoring the significance of this relationship. Our findings shed light on an unexpected yet intriguing aspect of stock market behavior, proving that sometimes, the seemingly arbitrary can hold unforeseen sway over financial markets.

[[LITERATURE REVIEW]]
Historical research on the influence of names in various contexts has yielded insightful findings. Smith and Doe, in their seminal work "The Impact of Names," uncover the psychological implications of names and their societal reverberations. Meanwhile, Jones et al. explore the intricate dance between nomenclature and cultural predispositions in "Names and Narratives: A Sociolinguistic Perspective." These studies, albeit not directly related to the financial domain, provide a foundational understanding of the multifaceted roles that names play in human interactions and decision-making processes.
Expanding beyond the realm of academic literature, non-fiction works such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner offer compelling perspectives on unconventional factors that shape markets and human behavior. The authors' examination of seemingly counterintuitive influences on various phenomena underscores the significance of probing unusual variables, setting the stage for our unconventional investigation.
Further afield, fictional narratives such as Jeffrey Eugenides' "Middlesex" and Colm Toibin's "Brooklyn" weave compelling stories around characters with distinctive names, tantalizing the imagination with tangential connections to our studious pursuit. While these narratives remain divorced from financial markets in their thematic content, the nuanced portrayal of personal identities and societal norms serves as an intriguing backdrop to our exploration of the Maeve-TSM nexus.
To add a touch of cinematic tangibility to our avant-garde inquiry, movies such as "The Social Network" and "Moneyball" offer insightful portrayals of the capricious nature of market dynamics and the unassuming variables that often underpin financial success. Though these celluloid creations do not broach the subject of name influences on stock performance, they serve as engaging reminders of the multifarious elements at play within the opaque sphere of financial markets.
Our foray into the realm of empirical inquiry is not without its whimsical diversions, and we beckon the reader to traverse this labyrinth of literary and visual touchpoints with an open mind and a keen sense of humor – for in the pulsating heartbeat of academia, curiosity and joviality are often the perfect dance partners.

[[RESULTS]]
The statistical analysis unveiled a striking correlation between the prevalence of the first name Maeve and the stock performance of Taiwan Semiconductor Manufacturing Company (TSM) over the period from 2002 to 2022. The correlation coefficient of 0.9847163 indicates a near-perfect positive relationship between the popularity of the name Maeve and the stock price of TSM. This finding provides empirical support for the notion that the name Maeve holds a peculiar influence over the stock performance of TSM, much like an unseen hand guiding the market through tumultuous waves.
Furthermore, the high R-squared value of 0.9696661 suggests that a substantial proportion of the variance in TSM stock prices can be explained by the prevalence of the name Maeve. This implies that the ebb and flow of Maeves in the world is intricately intertwined with the ebb and flow of TSM stock prices, creating a curious dance of market dynamics and nomenclature.
The p-value being less than 0.01 reinforces the robustness and significance of this relationship, lending further credibility to the Maeve Effect on TSM stock prices. It seems that the name Maeve is not just a moniker, but a silent maestro conducting the market movements with an elegant yet inexplicable finesse.
Figure 1 provides a visual representation of the strong correlation between the prevalence of the name Maeve and TSM stock prices, further underscoring the remarkable nature of this unexpected relationship. The scatterplot depicts a clear and discernible pattern, akin to a constellation of market movements that align with the celestial influence of the name Maeve.
These findings illuminate an unconventional and whimsical aspect of stock market behavior, challenging conventional wisdom and reminding us that in the complex tapestry of market dynamics, even the most unassuming variables can wield surprising clout. This revelatory connection between the first name Maeve and TSM stock prices offers a delightful twist in the saga of market predictability, infusing a touch of levity in an otherwise stoic arena of financial analysis.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The enigmatic relationship between the popularity of the first name Maeve and the stock performance of Taiwan Semiconductor Manufacturing Company (TSM) culminates in an unprecedented fusion of statistical significance and inexplicable whimsy. Building upon the historical and literary forerunners of our inquiry, our empirical findings not only substantiate, but also imbue a lighthearted gravity to the captivating Maeve-TSM nexus.

The correlation coefficient of 0.9847163, akin to a rare alignment of celestial bodies, mirrors the near-perfect positive relationship between the prevalence of the name Maeve and TSM stock prices. This remarkable synchronization evokes the beguiling dance of name influence within the labyrinthine market landscape. Just as the shifting tides are inexorably drawn to the constellations above, so are the market movements inexorably influenced by the cosmic sway of Maeves in the world.

Our high R-squared value of 0.9696661 serves as a stalwart testament to the substantial proportion of variance in TSM stock prices elucidated by the ebb and flow of Maeves. This alluring insight conjures an image of Maeve as a spectral conductor orchestrating the symphony of market dynamics, rendering the intangible palpable and the whimsical weighty in its financial reverberations.

The p-value of less than 0.01, akin to the gold standard of empirical validation, proffers irrefutable evidence of the considerable impact of the Maeve Effect on TSM stock prices. This vaudevillian twist in the saga of market predictability animates the stoic realm of financial analysis, injecting a whimsical yet robust undercurrent into the rigorous fabric of statistical inquiry.

As we return to the labyrinth of literary and cinematic influences that have guided our unorthodox pursuit, we witness the nascent tendrils of reason weaving through the seemingly capricious tapestry of unconventional market dynamics. The Maeve-TSM nexus, culled from the esoteric annals of statistical analysis, ushers in an era where the measure of impact transcends the conventional, and the unforeseen arcs into prominence.

In this lucid synthesis of empirical precision and imaginative allure, the Maeve Effect offers a tantalizing glimpse into the web of unpredictability ensconced within financial markets, propelling us into uncharted territory where the seemingly arbitrary interlaces with the unequivocally significant, much like a whimsical riddle concealed within the intricate folds of statistical revelation.


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 Maeve and Taiwan Semiconductor Manufacturing Company's stock price (TSM). 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 Maeve Effect on TSM Stock Price"

[[ABSTRACT]]
This paper scrutinizes the potential influence of the first name Maeve on the stock price of Taiwan Semiconductor Manufacturing Company (TSM). Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv) spanning the years 2002 to 2022, our research team conducted a comprehensive analysis. The correlation coefficient of 0.9847163 revealed a remarkable connection between the prevalence of the name Maeve and the stock performance of TSM, with a p-value of less than 0.01 further underscoring the significance of this relationship. Our findings shed light on an unexpected yet intriguing aspect of stock market behavior, proving that sometimes, the seemingly arbitrary can hold unforeseen sway over financial markets.

[[INTRDUCTION]]
In the labyrinthine world of stock market analysis, uncovering the myriad factors that sway stock prices is akin to solving a Rubik's cube blindfolded—challenging, yet oddly exhilarating. Among the plethora of indispensable data points and indicators, there exist unexpected and seemingly unrelated variables that dance through the market like uninvited guests at a grand soirée. In this capricious waltz of market forces, we embark on a curious exploration into the potential impact of the first name Maeve on the stock price of the Taiwan Semiconductor Manufacturing Company (TSM).
One might question, "What, pray tell, does a name have to do with a company's stock performance?" Well, dear reader, that is the very question that has tickled our academic fancy and led us down this whimsical rabbit hole of conjecture and analysis. As we dust off our data sets and buckle up for this intellectual rodeo, we invite you to join us on this zany venture—a journey replete with statistical wizardry, market musings, and perhaps a sprinkling of serendipity.
The Maeve Effect, as we affectionately dub it, introduces a novel and intriguing facet to the mosaic of stock market anomalies. Our endeavor is not merely a peering into the idiosyncrasies of nomenclature, but rather a peek behind the proverbial curtain of financial markets—a realm where the eccentric and the conventional converge in a beguiling tango. And indeed, we aim to shed light on this rather peculiar intersection, where the ebb and flow of stock prices intersects with the ebb and flow of appellations.
As we delve into this investigation, we embark with equal parts earnestness and jocularity—after all, what is academia without a dash of levity? Through rigorous analysis and a sprinkling of good-humored banter, we aim to unravel the enigmatic interplay between the popularity of the name Maeve and the stock price of TSM. So, fasten your seatbelts and stow away your preconceptions as we traverse this delightfully unconventional expedition into the enigmatic corridors of market behavior.

[[RESULTS]]
The statistical analysis unveiled a striking correlation between the prevalence of the first name Maeve and the stock performance of Taiwan Semiconductor Manufacturing Company (TSM) over the period from 2002 to 2022. The correlation coefficient of 0.9847163 indicates a near-perfect positive relationship between the popularity of the name Maeve and the stock price of TSM. This finding provides empirical support for the notion that the name Maeve holds a peculiar influence over the stock performance of TSM, much like an unseen hand guiding the market through tumultuous waves.
Furthermore, the high R-squared value of 0.9696661 suggests that a substantial proportion of the variance in TSM stock prices can be explained by the prevalence of the name Maeve. This implies that the ebb and flow of Maeves in the world is intricately intertwined with the ebb and flow of TSM stock prices, creating a curious dance of market dynamics and nomenclature.
The p-value being less than 0.01 reinforces the robustness and significance of this relationship, lending further credibility to the Maeve Effect on TSM stock prices. It seems that the name Maeve is not just a moniker, but a silent maestro conducting the market movements with an elegant yet inexplicable finesse.
Figure 1 provides a visual representation of the strong correlation between the prevalence of the name Maeve and TSM stock prices, further underscoring the remarkable nature of this unexpected relationship. The scatterplot depicts a clear and discernible pattern, akin to a constellation of market movements that align with the celestial influence of the name Maeve.
These findings illuminate an unconventional and whimsical aspect of stock market behavior, challenging conventional wisdom and reminding us that in the complex tapestry of market dynamics, even the most unassuming variables can wield surprising clout. This revelatory connection between the first name Maeve and TSM stock prices offers a delightful twist in the saga of market predictability, infusing a touch of levity in an otherwise stoic arena of financial analysis.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study provides compelling evidence of the fascinating connection between the popularity of the first name Maeve and Taiwan Semiconductor Manufacturing Company's stock price (TSM). The robust correlation coefficient of 0.9847163 and the p-value of less than 0.01 indicate a significantly strong relationship that cannot be ignored. It appears that the fluctuations in the prevalence of the name Maeve mirror the ebbs and flows of TSM stock prices, almost as if there is an unseen force at play, much like the mystical allure of a siren's song in the tumultuous sea of market dynamics.

The high R-squared value of 0.9696661 further solidifies the impact of the Maeve Effect on TSM stock prices, serving as a testament to the unanticipated influence of seemingly trivial factors. It seems that the name Maeve possesses an inexplicably elegant sway over the market, akin to a magician conjuring mesmerizing tricks before an astonished audience. It is a whimsical narrative that adds an unexpected element of quirkiness to the seemingly staid world of financial analysis.

With our findings, we have contributed an unconventional yet pertinent perspective to the intricate landscape of stock market studies, highlighting the quirky interplay between nomenclature and market performance. It is a gentle reminder that in the intricate dance of market forces, even the most unassuming participants can hold unexpected sway, much like a mischievous sprite weaving its way through the market tapestry.

As we draw the curtains on this peculiar odyssey of market exploration, we cannot help but marvel at the serendipitous discoveries that often emerge from the most unexpected sources. The Maeve Effect stands as a testament to the delightful unpredictability of the market, beckoning us to embrace the whimsical nuances that lie beneath the austere veneer of financial analysis.

In light of these revelatory findings, we assert that further research into the Maeve Effect on TSM stock prices is unwarranted, as we have illuminated this quirky connection with an effervescent flair that would make even the most seasoned market analysts smirk in mild amusement. Truly, the Maeve Effect is a curious tale that has been spun into the tapestry of stock market anomalies, and we stand at the denouement of this beguiling chapter, finally able to lay to rest the enigmatic connection between a name and stock prices.


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 Maeve Effect on TSM Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Economics


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Name Game: The Maeve Effect on TSM Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Financial and Linguistic Studies


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Name Game: The Maeve Effect on TSM Stock Price with an abstract of This paper scrutinizes the potential influence of the first name Maeve on the stock price of Taiwan Semiconductor Manufacturing Company (TSM). Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv) spanning the years 2002 to 2022, our research team conducted a comprehensive analysis. The correlation coefficient of 0.9847163 revealed a remarkable connection between the prevalence of the name Maeve and the stock performance of TSM, with a p-value of less than 0.01 further underscoring the significance of this relationship. Our findings shed light on an unexpected yet intriguing aspect of stock market behavior, proving that sometimes, the seemingly arbitrary can hold unforeseen sway over financial markets.

ChatGPT:

"Maeve influence on stock price," "Maeve name correlation with TSM stock," "TSM stock performance and name Maeve," "Social Security Administration data analysis," "LSEG Analytics correlation study," "Name influence on stock market behavior," "Unforeseen factors in financial markets," "First name impact on stock price," "Prevalence of name Maeve and TSM stock," "Stock price correlation with names," "Financial market research on name influence"

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

Taiwan Semiconductor Manufacturing Company's stock price (TSM)
Detailed data title: Opening price of Taiwan Semiconductor Manufacturing Company (TSM) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function

See what else correlates with Taiwan Semiconductor Manufacturing Company's stock price (TSM)

Correlation r = 0.9847163 (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 = 0.9696661 (Coefficient of determination)
This means 97% of the change in the one variable (i.e., Taiwan Semiconductor Manufacturing Company's stock price (TSM)) is predictable based on the change in the other (i.e., Popularity of the first name Maeve) over the 21 years from 2002 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.9E-16. 0.0000000000000006937626880602
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 0.98 in 6.9E-14% of random cases. Said differently, if you correlated 1,441,415,079,262,993 random variables You don't actually need 1 quadrillion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 20 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 20 because we have two variables measured over a period of 21 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.96, 0.99 ] 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.
200220032004200520062007200820092010201120122013201420152016201720182019202020212022
Popularity of the first name Maeve (Babies born)3504133783984474804865085464895716256487038208679731303164422532659
Taiwan Semiconductor Manufacturing Company's stock price (TSM) (Stock price)11.765.298.377.789.8510.949.747.7311.4912.5613.1117.7617.3922.4522.2429.2540.5136.259.6111.47124.13




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.




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([350,413,378,398,447,480,486,508,546,489,571,625,648,703,820,867,973,1303,1644,2253,2659,])
array_2 = np.array([11.76,5.29,8.37,7.78,9.85,10.94,9.74,7.73,11.49,12.56,13.11,17.76,17.39,22.45,22.24,29.25,40.51,36.2,59.6,111.47,124.13,])
array_1_name = "Popularity of the first name Maeve"
array_2_name = "Taiwan Semiconductor Manufacturing Company's stock price (TSM)"

# 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: 3839 · Black Variable ID: 4102 · Red Variable ID: 1550
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