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Spurious correlation #2,924 · 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 Tanisha and the second variable is Robberies in New York.  The chart goes from 1985 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

People realized that being named Tanisha didn't guarantee success in life, so they decided to pursue more honest career paths. And as the saying goes, "As Tanisha's star wanes, crime in New York wanes."

Model: dalle-3
Prompt: [Realistic] Create an image of a colorful playground filled with exuberant kids playing, each wearing a name tag that reads "Tanisha." Capture the bustling energy of the playful children as some of them start to leave, creating a sense of movement and activity. Meanwhile, in the city, depict a few daring heists taking place, but with fewer energetic individuals visible in the scene. This contrast should portray the diminishing liveliness in both the playground and the city. 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 Tanisha and Robberies in New York. 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: Psychedelic Cyber folk Realistic a meme Cubism
ChatGPT: Realistic

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 Tanisha and Robberies in New York, in the following situation: Because as the popularity of the name Tanisha decreased, so did the number of people named Tanisha. With fewer Tanishas, there were fewer energetic individuals available to pull off daring heists in New York.. Keep the description simple.
ChatGPT: A playground bustling with energetic kids, each with a name tag saying "Tanisha," becomes less crowded as some children leave. Meanwhile, in the city, fewer daring heists take place as the energetic individuals become scarcer.

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: [ Realistic ] and depicting this scene: A playground bustling with energetic kids, each with a name tag saying "Tanisha," becomes less crowded as some children leave. Meanwhile, in the city, fewer daring heists take place as the energetic individuals become scarcer. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [Realistic] Create an image of a colorful playground filled with exuberant kids playing, each wearing a name tag that reads "Tanisha." Capture the bustling energy of the playful children as some of them start to leave, creating a sense of movement and activity. Meanwhile, in the city, depict a few daring heists taking place, but with fewer energetic individuals visible in the scene. This contrast should portray the diminishing liveliness in both the playground and the city.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in Popularity of the first name Tanisha caused Robberies in New York to decrease.

AI academic paper

(Because p < 0.01)
Name Game: The Tantalizing Connection Between the Name Tanisha and Burglary in the Big Apple

The Journal of Quirky Anthropological Findings

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 silly 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 Tanisha and Robberies in New York. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Include a pun in the title.

Your research team used data from US Social Security Administration and FBI Criminal Justice Information Services to assess this nagging question. You found a correlation coefficient of 0.9885772 and p < 0.01 for 1985 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 Tantalizing Connection Between the Name Tanisha and Burglary in the Big Apple

[[ABSTRACT]]
In this study, we investigate the peculiar relationship between the popularity of the first name Tanisha and the occurrence of robberies in New York. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a rigorous analysis spanning from 1985 to 2022. Our findings reveal a striking correlation coefficient of 0.9885772 and a significance level of p < 0.01, pointing to a tantalizing correlation between the name Tanisha and the prevalence of robberies in the city that never sleeps. This leads us to ponder whether the "Tanisha effect" has a magnetic pull on criminal activities or if it's simply a curious coincidence. The implications of these findings are as intriguing as they are unexpected, shedding light on the intersection of nomenclature and nefarious activities.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Tanisha and Robberies in New York. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
Name Game: The Tantalizing Connection Between the Name Tanisha and Burglary in the Big Apple

[[ABSTRACT]]
In this study, we investigate the peculiar relationship between the popularity of the first name Tanisha and the occurrence of robberies in New York. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a rigorous analysis spanning from 1985 to 2022. Our findings reveal a striking correlation coefficient of 0.9885772 and a significance level of p < 0.01, pointing to a tantalizing correlation between the name Tanisha and the prevalence of robberies in the city that never sleeps. This leads us to ponder whether the "Tanisha effect" has a magnetic pull on criminal activities or if it's simply a curious coincidence. The implications of these findings are as intriguing as they are unexpected, shedding light on the intersection of nomenclature and nefarious activities.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The relationship between societal trends and nomenclature has long piqued the curiosity of researchers across various disciplines. From the impact of names on career choices to their influence on social dynamics, the significance of nomenclature cannot be understated. In this peculiar study, we pivot to the intersection of a specific first name and criminal activities, as we delve into the tantalizing relationship between the name Tanisha and the occurrence of robberies in the bustling metropolis of New York.

As we embark on this journey, it is important to note that the field of onomastics, the study of names and their origins, offers a trove of fascination. The allure of discovering patterns and associations within the realm of nomenclature often leads researchers to unexpected and, at times, whimsical findings. This study is no exception, as we aim to unravel the enigmatic correlation between the popularity of the name Tanisha and the frequency of robberies in the city that never sleeps.

While the notion of a linguistic moniker exerting an influence on criminal behavior may seem far-fetched at first glance, our preliminary investigation has unearthed a compelling link that raises eyebrows and fosters contemplation. The repercussions of unraveling this correlation extend beyond the realm of statistical analysis into the nebulous terrain of sociolinguistics and criminology, creating a confluence of disciplines that sparks intellectual curiosity and captivates the mind.

As we delve further into this unconventional foray, it is imperative to employ a balanced approach that acknowledges both the statistical nuances and the potential sociocultural underpinnings. The findings of this study may not only shed light on the curious connection between a name and criminal occurrences but also prompt us to ponder the broader implications of nomenclature in shaping societal phenomena.

In the ensuing sections of this paper, we will navigate through the labyrinth of data analysis and theoretical contemplation to unravel the perplexing knot that ties the name Tanisha to the prevalence of burglaries in the urban landscape of New York. Our inquiry seeks to strike a delicate balance between rigorous empirical scrutiny and the whimsical intrigue that accompanies the investigation of seemingly improbable connections.

With this in mind, let us embark on this intellectually stimulating journey to decipher the cryptic relationship between the name Tanisha and the propensity for criminal activity, as we endeavor to unravel the tantalizing puzzle that lies at the crux of the name game.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Tanisha and Robberies in New York. 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 a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
Name Game: The Tantalizing Connection Between the Name Tanisha and Burglary in the Big Apple

[[ABSTRACT]]
In this study, we investigate the peculiar relationship between the popularity of the first name Tanisha and the occurrence of robberies in New York. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a rigorous analysis spanning from 1985 to 2022. Our findings reveal a striking correlation coefficient of 0.9885772 and a significance level of p < 0.01, pointing to a tantalizing correlation between the name Tanisha and the prevalence of robberies in the city that never sleeps. This leads us to ponder whether the "Tanisha effect" has a magnetic pull on criminal activities or if it's simply a curious coincidence. The implications of these findings are as intriguing as they are unexpected, shedding light on the intersection of nomenclature and nefarious activities.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between societal trends and nomenclature has long piqued the curiosity of researchers across various disciplines. From the impact of names on career choices to their influence on social dynamics, the significance of nomenclature cannot be understated. In this peculiar study, we pivot to the intersection of a specific first name and criminal activities, as we delve into the tantalizing relationship between the name Tanisha and the occurrence of robberies in the bustling metropolis of New York.
As we embark on this journey, it is important to note that the field of onomastics, the study of names and their origins, offers a trove of fascination. The allure of discovering patterns and associations within the realm of nomenclature often leads researchers to unexpected and, at times, whimsical findings. This study is no exception, as we aim to unravel the enigmatic correlation between the popularity of the name Tanisha and the frequency of robberies in the city that never sleeps.
While the notion of a linguistic moniker exerting an influence on criminal behavior may seem far-fetched at first glance, our preliminary investigation has unearthed a compelling link that raises eyebrows and fosters contemplation. The repercussions of unraveling this correlation extend beyond the realm of statistical analysis into the nebulous terrain of sociolinguistics and criminology, creating a confluence of disciplines that sparks intellectual curiosity and captivates the mind.
As we delve further into this unconventional foray, it is imperative to employ a balanced approach that acknowledges both the statistical nuances and the potential sociocultural underpinnings. The findings of this study may not only shed light on the curious connection between a name and criminal occurrences but also prompt us to ponder the broader implications of nomenclature in shaping societal phenomena.
In the ensuing sections of this paper, we will navigate through the labyrinth of data analysis and theoretical contemplation to unravel the perplexing knot that ties the name Tanisha to the prevalence of burglaries in the urban landscape of New York. Our inquiry seeks to strike a delicate balance between rigorous empirical scrutiny and the whimsical intrigue that accompanies the investigation of seemingly improbable connections.
With this in mind, let us embark on this intellectually stimulating journey to decipher the cryptic relationship between the name Tanisha and the propensity for criminal activity, as we endeavor to unravel the tantalizing puzzle that lies at the crux of the name game.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The correlation between first names and societal phenomena has been a topic of interest across a myriad of academic disciplines. While initial exploration pertained to less dubious connections, such as names' influence on career advancement and social interactions, recent studies have delved into more unorthodox associations. Smith (2010) conducted a comprehensive analysis of the impact of first names on behavioral patterns, shedding light on the subtle influence of nomenclature. Meanwhile, Doe (2015) explored the societal implications of naming conventions, emphasizing the nuanced interplay between nomenclature and human conduct.

Turning attention to the specific case of the name Tanisha, Jones (2018) provided a thought-provoking examination of the cultural significance of this nomenclature, unveiling the intricate tapestry of meanings and connotations woven through its usage. These serious scholarly investigations set the stage for our curious exploration into the intriguing correlation between the name Tanisha and the occurrence of robberies in New York.

Venturing beyond the realm of academic literature, non-fiction works such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner and "Thinking, Fast and Slow" by Daniel Kahneman offer insights into the unexpected connections and hidden patterns that underpin various societal phenomena. The relevance of these works lies in their exploration of unconventional correlations and the complex web of causality that defines human behavior and societal trends.

In the realm of fiction, books such as "The Name of the Rose" by Umberto Eco and "The Shadow of the Wind" by Carlos Ruiz Zafón, while not directly pertinent to our investigation, underscore the enigmatic allure that names and their associations possess. These narratives, albeit fictional, draw attention to the mystique surrounding the power of names and their potential to shape destinies, albeit in more fantastical contexts.

In a playful departure from conventional scholarly sources, internet memes such as the "This is For Rachel" trend offer a lighthearted yet pertinent commentary on the cultural significance of names and their influence on social dynamics. This modern manifestation of the fascination with nomenclature encapsulates the whimsical, albeit relevant, nature of our inquiry.

As we embark on this scholarly expedition, it is imperative to maintain a discerning eye for the unexpected and the unconventional, as we navigate through the rich tapestry of literature that sets the stage for unraveling the tantalizing connection between the name Tanisha and the prevalence of robberies in the urban landscape of New York.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Tanisha and Robberies in New York. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and FBI Criminal Justice Information Services . You used data from 1985 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 Tantalizing Connection Between the Name Tanisha and Burglary in the Big Apple

[[ABSTRACT]]
In this study, we investigate the peculiar relationship between the popularity of the first name Tanisha and the occurrence of robberies in New York. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a rigorous analysis spanning from 1985 to 2022. Our findings reveal a striking correlation coefficient of 0.9885772 and a significance level of p < 0.01, pointing to a tantalizing correlation between the name Tanisha and the prevalence of robberies in the city that never sleeps. This leads us to ponder whether the "Tanisha effect" has a magnetic pull on criminal activities or if it's simply a curious coincidence. The implications of these findings are as intriguing as they are unexpected, shedding light on the intersection of nomenclature and nefarious activities.

[[INTRODUCTION]]
The relationship between societal trends and nomenclature has long piqued the curiosity of researchers across various disciplines. From the impact of names on career choices to their influence on social dynamics, the significance of nomenclature cannot be understated. In this peculiar study, we pivot to the intersection of a specific first name and criminal activities, as we delve into the tantalizing relationship between the name Tanisha and the occurrence of robberies in the bustling metropolis of New York.
As we embark on this journey, it is important to note that the field of onomastics, the study of names and their origins, offers a trove of fascination. The allure of discovering patterns and associations within the realm of nomenclature often leads researchers to unexpected and, at times, whimsical findings. This study is no exception, as we aim to unravel the enigmatic correlation between the popularity of the name Tanisha and the frequency of robberies in the city that never sleeps.
While the notion of a linguistic moniker exerting an influence on criminal behavior may seem far-fetched at first glance, our preliminary investigation has unearthed a compelling link that raises eyebrows and fosters contemplation. The repercussions of unraveling this correlation extend beyond the realm of statistical analysis into the nebulous terrain of sociolinguistics and criminology, creating a confluence of disciplines that sparks intellectual curiosity and captivates the mind.
As we delve further into this unconventional foray, it is imperative to employ a balanced approach that acknowledges both the statistical nuances and the potential sociocultural underpinnings. The findings of this study may not only shed light on the curious connection between a name and criminal occurrences but also prompt us to ponder the broader implications of nomenclature in shaping societal phenomena.
In the ensuing sections of this paper, we will navigate through the labyrinth of data analysis and theoretical contemplation to unravel the perplexing knot that ties the name Tanisha to the prevalence of burglaries in the urban landscape of New York. Our inquiry seeks to strike a delicate balance between rigorous empirical scrutiny and the whimsical intrigue that accompanies the investigation of seemingly improbable connections.
With this in mind, let us embark on this intellectually stimulating journey to decipher the cryptic relationship between the name Tanisha and the propensity for criminal activity, as we endeavor to unravel the tantalizing puzzle that lies at the crux of the name game.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Sample Selection:
The first step in our investigation involved obtaining data on the frequency of the first name Tanisha from the US Social Security Administration, spanning the years 1985 to 2022. Given that the popularity of names may vary across different regions, we made sure to incorporate data from various states to ensure a representative sample. After all, we wouldn't want our findings to be biased towards a specific geographical stronghold of Tanishas.

Data on robberies in New York was sourced from the FBI Criminal Justice Information Services, covering the same time period. It is worth noting that obtaining this data involved sifting through myriad reports and databases, like searching for a needle in a haystack, or in this case, evidence of a correlation amidst the data haystack.

Statistical Analysis:
Once the data was gathered, we employed rigorous statistical methods to scrutinize the relationship between the frequency of the name Tanisha and the incidence of robberies in New York. Utilizing the tried and tested tools of correlation analysis, we computed the correlation coefficient between the two variables. This involved number-crunching sessions that rivaled the cognitive workout of solving a Rubik's cube, all in the pursuit of uncovering the tantalizing connection.

To assess the strength and significance of this correlation, we subjected our data to hypothesis testing, setting the significance level at p < 0.01. This allowed us to discern whether the observed correlation was a genuine phenomenon or merely a whimsical aberration. After all, one must always be wary of the mischievous play of chance in statistical analyses.

Control Variables:
In our efforts to ensure a robust and nuanced analysis, we recognized the importance of controlling for potential confounding variables that could sway the observed correlation. Factors such as socioeconomic indicators and demographic characteristics were factored into our analysis to minimize the possibility of spurious correlations. Much like a chef meticulously selecting ingredients for a gourmet dish, we carefully curated and accounted for various elements that could contribute to the complex flavor of our analysis.

Ethical Considerations:
Throughout this study, the ethical implications of investigating the connection between a name and criminal activities were at the forefront of our minds. We were mindful of the potential stigmatization associated with drawing conclusions based on names, and thus, we approached our analysis with sensitivity and caution, much like tip-toeing through a minefield of potential implications.

In summary, our methodology harnessed the precision of statistical analysis, the scrutiny of control variables, and the ethical awareness required to navigate the intriguing correlation between the name Tanisha and the prevalence of robberies in the urban expanse of New York. Through this methodological cocktail, we aimed to shed light on a correlation that is as captivating as it is unexpected, all the while infusing a splash of academic whimsy into our investigative odyssey.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Tanisha and Robberies in New York. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and FBI Criminal Justice Information Services .

For the time period 1985 to 2022, you found a correlation 0.9885772, r-squared of 0.9772850, 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 Tantalizing Connection Between the Name Tanisha and Burglary in the Big Apple

[[ABSTRACT]]
In this study, we investigate the peculiar relationship between the popularity of the first name Tanisha and the occurrence of robberies in New York. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a rigorous analysis spanning from 1985 to 2022. Our findings reveal a striking correlation coefficient of 0.9885772 and a significance level of p < 0.01, pointing to a tantalizing correlation between the name Tanisha and the prevalence of robberies in the city that never sleeps. This leads us to ponder whether the "Tanisha effect" has a magnetic pull on criminal activities or if it's simply a curious coincidence. The implications of these findings are as intriguing as they are unexpected, shedding light on the intersection of nomenclature and nefarious activities.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The relationship between societal trends and nomenclature has long piqued the curiosity of researchers across various disciplines. From the impact of names on career choices to their influence on social dynamics, the significance of nomenclature cannot be understated. In this peculiar study, we pivot to the intersection of a specific first name and criminal activities, as we delve into the tantalizing relationship between the name Tanisha and the occurrence of robberies in the bustling metropolis of New York.
As we embark on this journey, it is important to note that the field of onomastics, the study of names and their origins, offers a trove of fascination. The allure of discovering patterns and associations within the realm of nomenclature often leads researchers to unexpected and, at times, whimsical findings. This study is no exception, as we aim to unravel the enigmatic correlation between the popularity of the name Tanisha and the frequency of robberies in the city that never sleeps.
While the notion of a linguistic moniker exerting an influence on criminal behavior may seem far-fetched at first glance, our preliminary investigation has unearthed a compelling link that raises eyebrows and fosters contemplation. The repercussions of unraveling this correlation extend beyond the realm of statistical analysis into the nebulous terrain of sociolinguistics and criminology, creating a confluence of disciplines that sparks intellectual curiosity and captivates the mind.
As we delve further into this unconventional foray, it is imperative to employ a balanced approach that acknowledges both the statistical nuances and the potential sociocultural underpinnings. The findings of this study may not only shed light on the curious connection between a name and criminal occurrences but also prompt us to ponder the broader implications of nomenclature in shaping societal phenomena.
In the ensuing sections of this paper, we will navigate through the labyrinth of data analysis and theoretical contemplation to unravel the perplexing knot that ties the name Tanisha to the prevalence of burglaries in the urban landscape of New York. Our inquiry seeks to strike a delicate balance between rigorous empirical scrutiny and the whimsical intrigue that accompanies the investigation of seemingly improbable connections.
With this in mind, let us embark on this intellectually stimulating journey to decipher the cryptic relationship between the name Tanisha and the propensity for criminal activity, as we endeavor to unravel the tantalizing puzzle that lies at the crux of the name game.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The data analysis revealed a remarkably strong correlation between the popularity of the first name Tanisha and the occurrence of robberies in New York. Over the period of 1985 to 2022, our research team found a correlation coefficient of 0.9885772, indicating a nearly perfect positive correlation between the two variables. This eyebrow-raising correlation was further supported by an r-squared value of 0.9772850, implying that approximately 97.73% of the variation in robbery occurrences can be explained by the popularity of the name Tanisha.

Intriguingly, the significance level (p < 0.01) underscores the statistical robustness of our findings, providing compelling evidence for the tantalizing correlation between the name Tanisha and the prevalence of robberies in the Big Apple. The linear relationship between the popularity of the name Tanisha and the incidence of robberies is poignantly illustrated in Fig. 1, a scatterplot that vividly captures the strong positive association between these variables. This finding challenges conventional wisdom and ignites contemplation on the intricate interplay between nomenclature and criminal activities. The implications of these results are as thought-provoking as they are unexpected, beckoning us to ponder the enigmatic forces at play in the world of onomastics and criminology.

These results bring to light a peculiar yet compelling correlation, prompting us to delve deeper into the complex web of sociolinguistic and criminological factors that underpin the connection between a name and criminal occurrences. The unexpected nexus between a seemingly innocuous name and criminal propensities opens new avenues for exploration and invites further inquiry into the often overlooked influence of nomenclature on societal phenomena. This serendipitous discovery challenges our preconceived notions and urges us to confront the poetic irony that lies at the heart of the name game.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Tanisha and Robberies in New York. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Name Game: The Tantalizing Connection Between the Name Tanisha and Burglary in the Big Apple

[[ABSTRACT]]
In this study, we investigate the peculiar relationship between the popularity of the first name Tanisha and the occurrence of robberies in New York. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a rigorous analysis spanning from 1985 to 2022. Our findings reveal a striking correlation coefficient of 0.9885772 and a significance level of p < 0.01, pointing to a tantalizing correlation between the name Tanisha and the prevalence of robberies in the city that never sleeps. This leads us to ponder whether the "Tanisha effect" has a magnetic pull on criminal activities or if it's simply a curious coincidence. The implications of these findings are as intriguing as they are unexpected, shedding light on the intersection of nomenclature and nefarious activities.

[[LITERATURE REVIEW]]
The correlation between first names and societal phenomena has been a topic of interest across a myriad of academic disciplines. While initial exploration pertained to less dubious connections, such as names' influence on career advancement and social interactions, recent studies have delved into more unorthodox associations. Smith (2010) conducted a comprehensive analysis of the impact of first names on behavioral patterns, shedding light on the subtle influence of nomenclature. Meanwhile, Doe (2015) explored the societal implications of naming conventions, emphasizing the nuanced interplay between nomenclature and human conduct.
Turning attention to the specific case of the name Tanisha, Jones (2018) provided a thought-provoking examination of the cultural significance of this nomenclature, unveiling the intricate tapestry of meanings and connotations woven through its usage. These serious scholarly investigations set the stage for our curious exploration into the intriguing correlation between the name Tanisha and the occurrence of robberies in New York.
Venturing beyond the realm of academic literature, non-fiction works such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner and "Thinking, Fast and Slow" by Daniel Kahneman offer insights into the unexpected connections and hidden patterns that underpin various societal phenomena. The relevance of these works lies in their exploration of unconventional correlations and the complex web of causality that defines human behavior and societal trends.
In the realm of fiction, books such as "The Name of the Rose" by Umberto Eco and "The Shadow of the Wind" by Carlos Ruiz Zafón, while not directly pertinent to our investigation, underscore the enigmatic allure that names and their associations possess. These narratives, albeit fictional, draw attention to the mystique surrounding the power of names and their potential to shape destinies, albeit in more fantastical contexts.
In a playful departure from conventional scholarly sources, internet memes such as the "This is For Rachel" trend offer a lighthearted yet pertinent commentary on the cultural significance of names and their influence on social dynamics. This modern manifestation of the fascination with nomenclature encapsulates the whimsical, albeit relevant, nature of our inquiry.
As we embark on this scholarly expedition, it is imperative to maintain a discerning eye for the unexpected and the unconventional, as we navigate through the rich tapestry of literature that sets the stage for unraveling the tantalizing connection between the name Tanisha and the prevalence of robberies in the urban landscape of New York.

[[RESULTS]]
The data analysis revealed a remarkably strong correlation between the popularity of the first name Tanisha and the occurrence of robberies in New York. Over the period of 1985 to 2022, our research team found a correlation coefficient of 0.9885772, indicating a nearly perfect positive correlation between the two variables. This eyebrow-raising correlation was further supported by an r-squared value of 0.9772850, implying that approximately 97.73% of the variation in robbery occurrences can be explained by the popularity of the name Tanisha.
Intriguingly, the significance level (p < 0.01) underscores the statistical robustness of our findings, providing compelling evidence for the tantalizing correlation between the name Tanisha and the prevalence of robberies in the Big Apple. The linear relationship between the popularity of the name Tanisha and the incidence of robberies is poignantly illustrated in Fig. 1, a scatterplot that vividly captures the strong positive association between these variables. This finding challenges conventional wisdom and ignites contemplation on the intricate interplay between nomenclature and criminal activities. The implications of these results are as thought-provoking as they are unexpected, beckoning us to ponder the enigmatic forces at play in the world of onomastics and criminology.
These results bring to light a peculiar yet compelling correlation, prompting us to delve deeper into the complex web of sociolinguistic and criminological factors that underpin the connection between a name and criminal occurrences. The unexpected nexus between a seemingly innocuous name and criminal propensities opens new avenues for exploration and invites further inquiry into the often overlooked influence of nomenclature on societal phenomena. This serendipitous discovery challenges our preconceived notions and urges us to confront the poetic irony that lies at the heart of the name game.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

Our investigation into the connection between the popularity of the first name Tanisha and the prevalence of robberies in New York has yielded results of a rather striking nature. Building upon the foundations laid by previous research, including the scholarly work of Smith, Doe, and Jones, as well as the unconventional insights of Levitt and Dubner and Kahneman, we embarked on this journey with an open mind and a keen eye for the unexpected. The tantalizing correlation coefficient of 0.9885772 uncovered in our study consistently reinforces the notion that there might truly be more than meets the eye when it comes to the influence of nomenclature on societal phenomena.

The robust correlation we've observed not only supports the findings of our predecessors but also lends substantial weight to the theory that the name Tanisha may indeed exhibit a magnetic pull on the occurrence of robberies in the heart of the city that never sleeps. This, of course, reminds one of the old quip about "putting the 'tan' in 'tantalizing,'" as our findings certainly weave a web of mystery and intrigue around the name game.

Fig. 1, our captivating scatterplot, paints a vivid picture of the strong positive association between the popularity of the name Tanisha and the incidence of robberies, capturing the attention much like a suspenseful plot twist in a classic noir film. It appears that the enigmatic allure surrounding names and their potential to shape destinies, as depicted in the likes of "The Name of the Rose" and "The Shadow of the Wind," may not merely be the stuff of fiction. Instead, it may reflect a subtler yet tangible force lurking beneath the surface of the urban landscape.

While the implications of our discovery are indeed thought-provoking and unexpected, perhaps it was, after all, only a matter of time before the "Tanisha effect" came under the microscope of empirical inquiry. The interplay between nomenclature and criminal propensities challenges traditional notions and prompts us to confront the paradoxical forces at work in the name game.

As we conclude this discussion, one cannot help but think of the old adage, "What's in a name? That which we call a rose, by any other name would smell as sweet." While Shakespeare may have spoken truly, our findings tantalizingly suggest that, in the world of criminology, there may indeed be more to a name than meets the eye.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Tanisha and Robberies in New York. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Name Game: The Tantalizing Connection Between the Name Tanisha and Burglary in the Big Apple

[[ABSTRACT]]
In this study, we investigate the peculiar relationship between the popularity of the first name Tanisha and the occurrence of robberies in New York. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a rigorous analysis spanning from 1985 to 2022. Our findings reveal a striking correlation coefficient of 0.9885772 and a significance level of p < 0.01, pointing to a tantalizing correlation between the name Tanisha and the prevalence of robberies in the city that never sleeps. This leads us to ponder whether the "Tanisha effect" has a magnetic pull on criminal activities or if it's simply a curious coincidence. The implications of these findings are as intriguing as they are unexpected, shedding light on the intersection of nomenclature and nefarious activities.

[[INTRDUCTION]]
The relationship between societal trends and nomenclature has long piqued the curiosity of researchers across various disciplines. From the impact of names on career choices to their influence on social dynamics, the significance of nomenclature cannot be understated. In this peculiar study, we pivot to the intersection of a specific first name and criminal activities, as we delve into the tantalizing relationship between the name Tanisha and the occurrence of robberies in the bustling metropolis of New York.
As we embark on this journey, it is important to note that the field of onomastics, the study of names and their origins, offers a trove of fascination. The allure of discovering patterns and associations within the realm of nomenclature often leads researchers to unexpected and, at times, whimsical findings. This study is no exception, as we aim to unravel the enigmatic correlation between the popularity of the name Tanisha and the frequency of robberies in the city that never sleeps.
While the notion of a linguistic moniker exerting an influence on criminal behavior may seem far-fetched at first glance, our preliminary investigation has unearthed a compelling link that raises eyebrows and fosters contemplation. The repercussions of unraveling this correlation extend beyond the realm of statistical analysis into the nebulous terrain of sociolinguistics and criminology, creating a confluence of disciplines that sparks intellectual curiosity and captivates the mind.
As we delve further into this unconventional foray, it is imperative to employ a balanced approach that acknowledges both the statistical nuances and the potential sociocultural underpinnings. The findings of this study may not only shed light on the curious connection between a name and criminal occurrences but also prompt us to ponder the broader implications of nomenclature in shaping societal phenomena.
In the ensuing sections of this paper, we will navigate through the labyrinth of data analysis and theoretical contemplation to unravel the perplexing knot that ties the name Tanisha to the prevalence of burglaries in the urban landscape of New York. Our inquiry seeks to strike a delicate balance between rigorous empirical scrutiny and the whimsical intrigue that accompanies the investigation of seemingly improbable connections.
With this in mind, let us embark on this intellectually stimulating journey to decipher the cryptic relationship between the name Tanisha and the propensity for criminal activity, as we endeavor to unravel the tantalizing puzzle that lies at the crux of the name game.

[[RESULTS]]
The data analysis revealed a remarkably strong correlation between the popularity of the first name Tanisha and the occurrence of robberies in New York. Over the period of 1985 to 2022, our research team found a correlation coefficient of 0.9885772, indicating a nearly perfect positive correlation between the two variables. This eyebrow-raising correlation was further supported by an r-squared value of 0.9772850, implying that approximately 97.73% of the variation in robbery occurrences can be explained by the popularity of the name Tanisha.
Intriguingly, the significance level (p < 0.01) underscores the statistical robustness of our findings, providing compelling evidence for the tantalizing correlation between the name Tanisha and the prevalence of robberies in the Big Apple. The linear relationship between the popularity of the name Tanisha and the incidence of robberies is poignantly illustrated in Fig. 1, a scatterplot that vividly captures the strong positive association between these variables. This finding challenges conventional wisdom and ignites contemplation on the intricate interplay between nomenclature and criminal activities. The implications of these results are as thought-provoking as they are unexpected, beckoning us to ponder the enigmatic forces at play in the world of onomastics and criminology.
These results bring to light a peculiar yet compelling correlation, prompting us to delve deeper into the complex web of sociolinguistic and criminological factors that underpin the connection between a name and criminal occurrences. The unexpected nexus between a seemingly innocuous name and criminal propensities opens new avenues for exploration and invites further inquiry into the often overlooked influence of nomenclature on societal phenomena. This serendipitous discovery challenges our preconceived notions and urges us to confront the poetic irony that lies at the heart of the name game.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the curious link between the popularity of the first name Tanisha and the prevalence of robberies in New York has unearthed a remarkably strong correlation, much like finding a needle in a haystack, or in this case, a Tanisha in a sea of names. The statistically robust correlation coefficient of 0.9885772 and the significance level of p < 0.01 leave little room for doubt, reminiscent of Sherlock Holmes unraveling a perplexing mystery.

This research not only highlights the compelling statistical association but also raises thought-provoking questions about the intricate interplay between nomenclature and criminal activities. The implications of the "Tanisha effect" beckon us to tread the thin line between whimsical curiosity and academic rigor, much like a tightrope walker navigating the enigmatic forces at play in the world of onomastics and criminology.

However, despite the tantalizing nature of this correlation and the allure of further exploration, it seems that the name game has revealed its secrets. It is our firm assertion and recommendation that, much like a magician never reveals their secrets, it is time to bid adieu to the perplexing puzzle of Tanisha and robberies in New York. Though the results are undeniably intriguing, it appears that no further research is needed in this area, and it is best to leave this particular conundrum to rest alongside other curiosities of the name game.


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 Tantalizing Connection Between the Name Tanisha and Burglary in the Big Apple. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Anthropological Findings


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 Tantalizing Connection Between the Name Tanisha and Burglary in the Big Apple. Respond only with the name of a fictional organization.

ChatGPT:

Institute for Urban 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 Tantalizing Connection Between the Name Tanisha and Burglary in the Big Apple with an abstract of In this study, we investigate the peculiar relationship between the popularity of the first name Tanisha and the occurrence of robberies in New York. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a rigorous analysis spanning from 1985 to 2022. Our findings reveal a striking correlation coefficient of 0.9885772 and a significance level of p < 0.01, pointing to a tantalizing correlation between the name Tanisha and the prevalence of robberies in the city that never sleeps. This leads us to ponder whether the "Tanisha effect" has a magnetic pull on criminal activities or if it's simply a curious coincidence. The implications of these findings are as intriguing as they are unexpected, shedding light on the intersection of nomenclature and nefarious activities.

ChatGPT:

"Tanisha name popularity," "crime rate Tanisha name correlation," "Tanisha name and burglary connection," "nomenclature and criminal activities," "Social Security Administration name data," "FBI crime statistics," "robberies in New York City," "correlation coefficient significance," "criminal activities and 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 Tanisha
Detailed data title: Babies of all sexes born in the US named Tanisha
Source: US Social Security Administration
See what else correlates with Popularity of the first name Tanisha

Robberies in New York
Detailed data title: The robbery rate per 100,000 residents in New York
Source: FBI Criminal Justice Information Services
See what else correlates with Robberies in New York

Correlation r = 0.9885772 (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 = 0.9772850 (Coefficient of determination)
This means 97.7% of the change in the one variable (i.e., Robberies in New York) is predictable based on the change in the other (i.e., Popularity of the first name Tanisha) over the 38 years from 1985 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0. 0.0000000000000000000000000000
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 0.99 in 0% of random cases. Said differently, if you correlated
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inf random variables
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You don't actually need
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INF variables to find a correlation like this one.
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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.
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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 37 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 37 because we have two variables measured over a period of 38 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.

[ 0.98, 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.
19851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010201120122013201420152016201720182019202020212022
Popularity of the first name Tanisha (Babies born)63867968561862368168166857957344742129224918016516514213513614113613013184107947258495344393740242419
Robberies in New York (Robbery rate)504.4514.1503.3544.4579.3624.7622.1596.9561.2476.7399.7340309.3270.3240.8213.6191.5191.6186.3173.8182.1178.5161.1163.1144147.6145.7146.3138.3121.7120.9112.5102.793.193.390.690.6112




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([638,679,685,618,623,681,681,668,579,573,447,421,292,249,180,165,165,142,135,136,141,136,130,131,84,107,94,72,58,49,53,44,39,37,40,24,24,19,])
array_2 = np.array([504.4,514.1,503.3,544.4,579.3,624.7,622.1,596.9,561.2,476.7,399.7,340,309.3,270.3,240.8,213.6,191.5,191.6,186.3,173.8,182.1,178.5,161.1,163.1,144,147.6,145.7,146.3,138.3,121.7,120.9,112.5,102.7,93.1,93.3,90.6,90.6,112,])
array_1_name = "Popularity of the first name Tanisha"
array_2_name = "Robberies in New York"

# 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: 2924 · Black Variable ID: 3010 · Red Variable ID: 20207
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