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Spurious correlation #1,196 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is NFL broadcast TV viewership and the second variable is Customer satisfaction with USATODAY.com.  The chart goes from 2003 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

The more football people watched, the happier they were, leading to a general sense of positivity and contentment when visiting USATODAY.com, where even the news seemed just a little bit better after a big game. Remember, happiness is just a touchdown away!

Model: dalle-3
Prompt: Prompt: Style: Cybernetic art Description: Generate an image of a futuristic football stadium with a reduced number of spectators in the stands. As the game unfolds, more attendees can be seen diverting their attention to their smartphones, creating a visual representation of an escalating flow of internet data. This leads to the formation of a bustling virtual highway filled with information, causing the USA TODAY website to experience a significant slowdown. Frustrated users on the website can be observed impatiently tapping their fingers as they await the loading of news articles and entertainment content, clearly expressing their dissatisfaction with the delays. Please ensure that the visual depiction remains simple and does not incorporate any words or speech bubbles. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: Fewer people watching NFL games means more people browsing the internet, leading to increased traffic and slower load times on USATODAY.com. As a result, customer satisfaction with the website decreased as users had to wait longer for articles to load and were unable to quickly access their daily dose of news and entertainment. It's a classic case of football fans inadvertently sabotaging the online news experience for everyone else.. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: Steampunk Cybernetic art Low poly Hyper-realistic inspired by bauhaus
ChatGPT: Cybernetic art

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. Fewer people watching NFL games means more people browsing the internet, leading to increased traffic and slower load times on USATODAY.com. As a result, customer satisfaction with the website decreased as users had to wait longer for articles to load and were unable to quickly access their daily dose of news and entertainment. It's a classic case of football fans inadvertently sabotaging the online news experience for everyone else.
ChatGPT: Picture this: A football stadium with fewer spectators in the stands than usual. As the game progresses, more and more people in the stands start looking at their smartphones, causing a buildup of internet traffic. This leads to a jam-packed virtual highway of information, slowing down the load times for the USA TODAY website. On the website, frustrated users are seen tapping their fingers impatiently as they wait for news articles and entertainment to load, clearly dissatisfied with the delay.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Cybernetic art ] and depicting this scene: Picture this: A football stadium with fewer spectators in the stands than usual. As the game progresses, more and more people in the stands start looking at their smartphones, causing a buildup of internet traffic. This leads to a jam-packed virtual highway of information, slowing down the load times for the USA TODAY website. On the website, frustrated users are seen tapping their fingers impatiently as they wait for news articles and entertainment to load, clearly dissatisfied with the delay. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Style: Cybernetic art Description: Generate an image of a futuristic football stadium with a reduced number of spectators in the stands. As the game unfolds, more attendees can be seen diverting their attention to their smartphones, creating a visual representation of an escalating flow of internet data. This leads to the formation of a bustling virtual highway filled with information, causing the USA TODAY website to experience a significant slowdown. Frustrated users on the website can be observed impatiently tapping their fingers as they await the loading of news articles and entertainment content, clearly expressing their dissatisfaction with the delays. Please ensure that the visual depiction remains simple and does not incorporate any words or speech bubbles.

*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 increases in NFL broadcast TV viewership positively influenced Customer satisfaction with USATODAY.com. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)
Tackling the Touchdowns: The Gridiron Grin of NFL Broadcast TV Viewership and USATODAY.com Customer Satisfaction

The Journal of Sports Media and Consumer Behavior

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 witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 NFL broadcast TV viewership and Customer satisfaction with USATODAY.com. Make lots of jokes, goofy observations, and puns.

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

Your research team used data from Zap2it and American Customer Satisfaction Index to assess this nagging question. You found a correlation coefficient of 0.7936866 and p < 0.01 for 2003 to 2021.

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]]
Tackling the Touchdowns: The Gridiron Grin of NFL Broadcast TV Viewership and USATODAY.com Customer Satisfaction

[[ABSTRACT]]
This paper investigates the playful connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. Leveraging data from Zap2it and the American Customer Satisfaction Index, we revealed a strong positive relationship between the two, with a correlation coefficient of 0.7936866 and p < 0.01 from 2003 to 2021. Our findings suggest that as football fans tune in to their favorite gridiron matchups, they may also turn their attention to USATODAY.com, bringing a smile to their digital experience. So, next time you catch a touchdown, remember to go for the digital extra point with USATODAY.com!


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 NFL broadcast TV viewership and Customer satisfaction with USATODAY.com. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
Tackling the Touchdowns: The Gridiron Grin of NFL Broadcast TV Viewership and USATODAY.com Customer Satisfaction

[[ABSTRACT]]
This paper investigates the playful connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. Leveraging data from Zap2it and the American Customer Satisfaction Index, we revealed a strong positive relationship between the two, with a correlation coefficient of 0.7936866 and p < 0.01 from 2003 to 2021. Our findings suggest that as football fans tune in to their favorite gridiron matchups, they may also turn their attention to USATODAY.com, bringing a smile to their digital experience. So, next time you catch a touchdown, remember to go for the digital extra point with USATODAY.com!

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The realm of sports and media is as intertwined as a quarterback and his favorite receiver. In this research paper, we delve into the curious relationship between NFL broadcast TV viewership and customer satisfaction with USATODAY.com, aiming to shed light on the interconnectedness of these seemingly disparate entities. As researchers, we often find ourselves in the end zone of curiosity, ready to tackle complex interactions with the finesse of a seasoned linebacker.

The National Football League (NFL) and its gripping games have long captured the imaginations of millions of viewers, drawing them into a world of bone-crunching tackles, Hail-Mary passes, and nail-biting finishes. Concurrently, the digital realm of news and information has evolved, offering a smorgasbord of content to satiate the ever-growing appetite for real-time updates and punditry. USATODAY.com stands as a charismatic player in this digital arena, drawing in readers with its dynamic blend of news, sports, and the occasional cat video – a touchdown of internet browsing, if you will.

Employing a statistical playbook rivaling that of a seasoned head coach, we delve into the immense dataset gathered from Zap2it and the American Customer Satisfaction Index. Our goal is to unravel the statistical dance of NFL broadcast TV viewership and USATODAY.com customer satisfaction, seeking patterns and connections that dance in the end zone of statistical significance.

This paper is not only a deep dive into the numbers but also a tribute to the joy of scientific discovery. As we embark on this statistical odyssey, we encourage our fellow researchers to enjoy the thrill of the pursuit and savor the touchdowns of insightful data analysis. So, grab your helmet and strap on your cleats, as we set out to uncover the gridiron grin of NFL broadcast TV viewership and USATODAY.com customer satisfaction. It's time to huddle up and tackle this research challenge with a winning spirit and a sprinkle of statistical stardust.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 NFL broadcast TV viewership and Customer satisfaction with USATODAY.com. Make lots of jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
Tackling the Touchdowns: The Gridiron Grin of NFL Broadcast TV Viewership and USATODAY.com Customer Satisfaction

[[ABSTRACT]]
This paper investigates the playful connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. Leveraging data from Zap2it and the American Customer Satisfaction Index, we revealed a strong positive relationship between the two, with a correlation coefficient of 0.7936866 and p < 0.01 from 2003 to 2021. Our findings suggest that as football fans tune in to their favorite gridiron matchups, they may also turn their attention to USATODAY.com, bringing a smile to their digital experience. So, next time you catch a touchdown, remember to go for the digital extra point with USATODAY.com!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The realm of sports and media is as intertwined as a quarterback and his favorite receiver. In this research paper, we delve into the curious relationship between NFL broadcast TV viewership and customer satisfaction with USATODAY.com, aiming to shed light on the interconnectedness of these seemingly disparate entities. As researchers, we often find ourselves in the end zone of curiosity, ready to tackle complex interactions with the finesse of a seasoned linebacker.
The National Football League (NFL) and its gripping games have long captured the imaginations of millions of viewers, drawing them into a world of bone-crunching tackles, Hail-Mary passes, and nail-biting finishes. Concurrently, the digital realm of news and information has evolved, offering a smorgasbord of content to satiate the ever-growing appetite for real-time updates and punditry. USATODAY.com stands as a charismatic player in this digital arena, drawing in readers with its dynamic blend of news, sports, and the occasional cat video – a touchdown of internet browsing, if you will.
Employing a statistical playbook rivaling that of a seasoned head coach, we delve into the immense dataset gathered from Zap2it and the American Customer Satisfaction Index. Our goal is to unravel the statistical dance of NFL broadcast TV viewership and USATODAY.com customer satisfaction, seeking patterns and connections that dance in the end zone of statistical significance.
This paper is not only a deep dive into the numbers but also a tribute to the joy of scientific discovery. As we embark on this statistical odyssey, we encourage our fellow researchers to enjoy the thrill of the pursuit and savor the touchdowns of insightful data analysis. So, grab your helmet and strap on your cleats, as we set out to uncover the gridiron grin of NFL broadcast TV viewership and USATODAY.com customer satisfaction. It's time to huddle up and tackle this research challenge with a winning spirit and a sprinkle of statistical stardust.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The investigation of the interplay between NFL broadcast TV viewership and customer satisfaction with USATODAY.com has invoked various scholarly discussions and inquiries on the subject. Smith et al. (2015) indulges in a quantitative analysis of televised NFL games and its impact on digital media engagement, observing a discernible influence of touchdown celebrations on subsequent visits to news websites. Straying slightly from the usual jargon-filled corridors of academia, the authors find that a riveting touchdown reportedly triggers a surge in online browsing, as fervent fans seek to extend their gridiron euphoria through the digital realm.

Furthermore, Doe and Jones (2018) present a compelling exploration into the psychological underpinnings of sports-induced euphoria and its correlation with online news consumption. Their findings, wrapped in layers of elaborate statistical analysis, reveal a whimsical connection between catching a thrilling game-winning play and subsequently perusing online news portals. It appears that the adrenaline rush from witnessing an astonishing play may serve as a catalyst for delving into a treasure trove of digital content, with USATODAY.com standing out as a beacon of choice for many aficionados.

Navigating through the brooding waters of academia and venturing into the realm of non-fiction literature, "The Business of Sports Broadcasting" by Gaudelli (2020) and "Digital Customer Experience in Football Season" by Thompson (2019) endeavor to untangle the threads of televised sports viewership and its impact on digital customer satisfaction. While their narratives exude academic sobriety, they subtly hint at the magnetic allure that NFL games exude, ultimately leading viewers down the glittering path of digital news consumption.

In a surprising twist, fictional literature also offers uncanny parallels to our scholarly pursuit. "Gridiron Gazette: A Tale of Touchdowns and Tackles" by Summers (2016) and "The News-Hungry Tailback" by Manning (2017) seamlessly weave elements of sports fervor and digital media engagement into their narratives, mimicking the very phenomenon we seek to decipher in this research endeavor. Although relegated to the imaginative realms of storytelling, these works carry an air of authenticity, mirroring the intricate dance between televised sports and digital news platforms.

Beyond the conventional realms of academic discourse, our literature review took an unexpected turn to uncover unconventional sources of insight. In a playfully audacious maneuver, we ventured into the uncharted territory of bathroom literature, embarking on a thorough investigation of the captivating prose adorning the backs of shampoo bottles. Alas, while these vibrant narratives regaled us with tales of lustrous locks and promised untold vitality, they regrettably offered no substantive insights into the interplay between NFL broadcast TV viewership and USATODAY.com customer satisfaction. Nevertheless, our quest for knowledge remains untarnished, fueled by the indomitable spirit of scholarly exploration.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 NFL broadcast TV viewership and Customer satisfaction with USATODAY.com. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Zap2it and American Customer Satisfaction Index . You used data from 2003 to 2021

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]]
Tackling the Touchdowns: The Gridiron Grin of NFL Broadcast TV Viewership and USATODAY.com Customer Satisfaction

[[ABSTRACT]]
This paper investigates the playful connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. Leveraging data from Zap2it and the American Customer Satisfaction Index, we revealed a strong positive relationship between the two, with a correlation coefficient of 0.7936866 and p < 0.01 from 2003 to 2021. Our findings suggest that as football fans tune in to their favorite gridiron matchups, they may also turn their attention to USATODAY.com, bringing a smile to their digital experience. So, next time you catch a touchdown, remember to go for the digital extra point with USATODAY.com!

[[INTRODUCTION]]
The realm of sports and media is as intertwined as a quarterback and his favorite receiver. In this research paper, we delve into the curious relationship between NFL broadcast TV viewership and customer satisfaction with USATODAY.com, aiming to shed light on the interconnectedness of these seemingly disparate entities. As researchers, we often find ourselves in the end zone of curiosity, ready to tackle complex interactions with the finesse of a seasoned linebacker.
The National Football League (NFL) and its gripping games have long captured the imaginations of millions of viewers, drawing them into a world of bone-crunching tackles, Hail-Mary passes, and nail-biting finishes. Concurrently, the digital realm of news and information has evolved, offering a smorgasbord of content to satiate the ever-growing appetite for real-time updates and punditry. USATODAY.com stands as a charismatic player in this digital arena, drawing in readers with its dynamic blend of news, sports, and the occasional cat video – a touchdown of internet browsing, if you will.
Employing a statistical playbook rivaling that of a seasoned head coach, we delve into the immense dataset gathered from Zap2it and the American Customer Satisfaction Index. Our goal is to unravel the statistical dance of NFL broadcast TV viewership and USATODAY.com customer satisfaction, seeking patterns and connections that dance in the end zone of statistical significance.
This paper is not only a deep dive into the numbers but also a tribute to the joy of scientific discovery. As we embark on this statistical odyssey, we encourage our fellow researchers to enjoy the thrill of the pursuit and savor the touchdowns of insightful data analysis. So, grab your helmet and strap on your cleats, as we set out to uncover the gridiron grin of NFL broadcast TV viewership and USATODAY.com customer satisfaction. It's time to huddle up and tackle this research challenge with a winning spirit and a sprinkle of statistical stardust.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

In this study, we employed a hybrid methodology that combined elements of data mining, regression analysis, and a touch of statistical alchemy. Our data, collected from 2003 to 2021, was sourced primarily from Zap2it and the American Customer Satisfaction Index, forming a robust foundation for our analytical foray.

To commence our statistical scrimmage, we first conducted a comprehensive data cleaning process, akin to precision grooming of a prized show dog, to ensure that our dataset was devoid of any anomalies, outliers, or erroneous entries. Following this, we performed a clever stratification of the data, grouping NFL broadcast TV viewership metrics and USATODAY.com customer satisfaction ratings into precise categories, much like organizing a colorful array of LEGO bricks into neat, thematic piles.

After the meticulous preparatory efforts, we launched into the statistical battlefield by wielding the formidable tools of regression analysis, employing both simple linear regression and multiple regression techniques. This allowed us to untangle the intricate knot of relationships between NFL broadcast TV viewership and USATODAY.com customer satisfaction, painting a vivid portrait of their interconnectedness akin to a captivating game of Pictionary.

To gauge the strength and direction of the relationship, we calculated correlation coefficients with the precision of a master watchmaker, unveiling the degree of co-movement between the variables. The resulting correlation coefficient of 0.7936866 pranced into the realm of statistical significance with a p-value of < 0.01, leaving us as giddy as a researcher finding a hidden Easter egg in their data analysis software.

To account for potential confounding factors and lurking variables, we donned our metaphorical Sherlock Holmes hat and engaged in covariate adjustment, ensuring that our findings stood firm against potential ambush by lurking statistical villains. We also performed robustness tests to validate the resilience of our results, likening it to a rigorous stress test for the statistical fortitude of our findings.

Our methodology, akin to a delightful fusion cuisine, blended the flavors of traditional statistical analyses with a dash of innovative techniques, resulting in a sumptuous feast of empirical evidence. This rigorous yet jovial approach allowed us to elevate our understanding of the interplay between NFL broadcast TV viewership and USATODAY.com customer satisfaction, offering insights that resonate with the harmonious symphony of statistical truth-seeking and a touch of whimsical wonder.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 NFL broadcast TV viewership and Customer satisfaction with USATODAY.com. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Zap2it and American Customer Satisfaction Index .

For the time period 2003 to 2021, you found a correlation 0.7936866, r-squared of 0.6299384, 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]]
Tackling the Touchdowns: The Gridiron Grin of NFL Broadcast TV Viewership and USATODAY.com Customer Satisfaction

[[ABSTRACT]]
This paper investigates the playful connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. Leveraging data from Zap2it and the American Customer Satisfaction Index, we revealed a strong positive relationship between the two, with a correlation coefficient of 0.7936866 and p < 0.01 from 2003 to 2021. Our findings suggest that as football fans tune in to their favorite gridiron matchups, they may also turn their attention to USATODAY.com, bringing a smile to their digital experience. So, next time you catch a touchdown, remember to go for the digital extra point with USATODAY.com!

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The realm of sports and media is as intertwined as a quarterback and his favorite receiver. In this research paper, we delve into the curious relationship between NFL broadcast TV viewership and customer satisfaction with USATODAY.com, aiming to shed light on the interconnectedness of these seemingly disparate entities. As researchers, we often find ourselves in the end zone of curiosity, ready to tackle complex interactions with the finesse of a seasoned linebacker.
The National Football League (NFL) and its gripping games have long captured the imaginations of millions of viewers, drawing them into a world of bone-crunching tackles, Hail-Mary passes, and nail-biting finishes. Concurrently, the digital realm of news and information has evolved, offering a smorgasbord of content to satiate the ever-growing appetite for real-time updates and punditry. USATODAY.com stands as a charismatic player in this digital arena, drawing in readers with its dynamic blend of news, sports, and the occasional cat video – a touchdown of internet browsing, if you will.
Employing a statistical playbook rivaling that of a seasoned head coach, we delve into the immense dataset gathered from Zap2it and the American Customer Satisfaction Index. Our goal is to unravel the statistical dance of NFL broadcast TV viewership and USATODAY.com customer satisfaction, seeking patterns and connections that dance in the end zone of statistical significance.
This paper is not only a deep dive into the numbers but also a tribute to the joy of scientific discovery. As we embark on this statistical odyssey, we encourage our fellow researchers to enjoy the thrill of the pursuit and savor the touchdowns of insightful data analysis. So, grab your helmet and strap on your cleats, as we set out to uncover the gridiron grin of NFL broadcast TV viewership and USATODAY.com customer satisfaction. It's time to huddle up and tackle this research challenge with a winning spirit and a sprinkle of statistical stardust.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Our analysis revealed a robust and positive correlation between NFL broadcast TV viewership and customer satisfaction with USATODAY.com from 2003 to 2021. The correlation coefficient of 0.7936866 indicates a strong relationship between these two variables, reminiscent of a well-executed touchdown pass. The r-squared value of 0.6299384 further underscores the impact of NFL broadcast TV viewership on customer satisfaction with USATODAY.com, akin to a perfectly executed end zone celebration dance.

Our findings indicate that as NFL fans tuned in to witness heart-stopping plays and game-winning drives, there was a corresponding boost in customer satisfaction with USATODAY.com, as if a digital touchdown had been scored. The p-value of less than 0.01 lends statistical weight to this connection, as rare as a flea-flicker play in a football game.

To visually depict the strong relationship we uncovered, we present Figure 1, a scatterplot resembling a well-drawn play diagram, showcasing the positive correlation between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. It's a graph that shows just how seamlessly these two variables move down the field together, like a well-coordinated offensive line protecting their quarterback.

Our research not only highlights the statistical significance of the connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com, but it also emphasizes the joyous serendipity of scientific inquiry. The intertwined nature of these variables echoes the dynamic and ever-changing landscape of sports and media, underscoring the need for continued exploration and analysis in this vibrant field.

In sum, our study underscores the touchdown-worthy connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com, shedding light on the shared joy that football and digital news consumption can bring. So, as football enthusiasts revel in the thrill of the game, they may find an equally satisfying experience awaiting them at USATODAY.com, offering a taste of victory in the digital arena.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 NFL broadcast TV viewership and Customer satisfaction with USATODAY.com. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Tackling the Touchdowns: The Gridiron Grin of NFL Broadcast TV Viewership and USATODAY.com Customer Satisfaction

[[ABSTRACT]]
This paper investigates the playful connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. Leveraging data from Zap2it and the American Customer Satisfaction Index, we revealed a strong positive relationship between the two, with a correlation coefficient of 0.7936866 and p < 0.01 from 2003 to 2021. Our findings suggest that as football fans tune in to their favorite gridiron matchups, they may also turn their attention to USATODAY.com, bringing a smile to their digital experience. So, next time you catch a touchdown, remember to go for the digital extra point with USATODAY.com!

[[LITERATURE REVIEW]]
The investigation of the interplay between NFL broadcast TV viewership and customer satisfaction with USATODAY.com has invoked various scholarly discussions and inquiries on the subject. Smith et al. (2015) indulges in a quantitative analysis of televised NFL games and its impact on digital media engagement, observing a discernible influence of touchdown celebrations on subsequent visits to news websites. Straying slightly from the usual jargon-filled corridors of academia, the authors find that a riveting touchdown reportedly triggers a surge in online browsing, as fervent fans seek to extend their gridiron euphoria through the digital realm.
Furthermore, Doe and Jones (2018) present a compelling exploration into the psychological underpinnings of sports-induced euphoria and its correlation with online news consumption. Their findings, wrapped in layers of elaborate statistical analysis, reveal a whimsical connection between catching a thrilling game-winning play and subsequently perusing online news portals. It appears that the adrenaline rush from witnessing an astonishing play may serve as a catalyst for delving into a treasure trove of digital content, with USATODAY.com standing out as a beacon of choice for many aficionados.
Navigating through the brooding waters of academia and venturing into the realm of non-fiction literature, "The Business of Sports Broadcasting" by Gaudelli (2020) and "Digital Customer Experience in Football Season" by Thompson (2019) endeavor to untangle the threads of televised sports viewership and its impact on digital customer satisfaction. While their narratives exude academic sobriety, they subtly hint at the magnetic allure that NFL games exude, ultimately leading viewers down the glittering path of digital news consumption.
In a surprising twist, fictional literature also offers uncanny parallels to our scholarly pursuit. "Gridiron Gazette: A Tale of Touchdowns and Tackles" by Summers (2016) and "The News-Hungry Tailback" by Manning (2017) seamlessly weave elements of sports fervor and digital media engagement into their narratives, mimicking the very phenomenon we seek to decipher in this research endeavor. Although relegated to the imaginative realms of storytelling, these works carry an air of authenticity, mirroring the intricate dance between televised sports and digital news platforms.
Beyond the conventional realms of academic discourse, our literature review took an unexpected turn to uncover unconventional sources of insight. In a playfully audacious maneuver, we ventured into the uncharted territory of bathroom literature, embarking on a thorough investigation of the captivating prose adorning the backs of shampoo bottles. Alas, while these vibrant narratives regaled us with tales of lustrous locks and promised untold vitality, they regrettably offered no substantive insights into the interplay between NFL broadcast TV viewership and USATODAY.com customer satisfaction. Nevertheless, our quest for knowledge remains untarnished, fueled by the indomitable spirit of scholarly exploration.

[[RESULTS]]
Our analysis revealed a robust and positive correlation between NFL broadcast TV viewership and customer satisfaction with USATODAY.com from 2003 to 2021. The correlation coefficient of 0.7936866 indicates a strong relationship between these two variables, reminiscent of a well-executed touchdown pass. The r-squared value of 0.6299384 further underscores the impact of NFL broadcast TV viewership on customer satisfaction with USATODAY.com, akin to a perfectly executed end zone celebration dance.
Our findings indicate that as NFL fans tuned in to witness heart-stopping plays and game-winning drives, there was a corresponding boost in customer satisfaction with USATODAY.com, as if a digital touchdown had been scored. The p-value of less than 0.01 lends statistical weight to this connection, as rare as a flea-flicker play in a football game.
To visually depict the strong relationship we uncovered, we present Figure 1, a scatterplot resembling a well-drawn play diagram, showcasing the positive correlation between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. It's a graph that shows just how seamlessly these two variables move down the field together, like a well-coordinated offensive line protecting their quarterback.
Our research not only highlights the statistical significance of the connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com, but it also emphasizes the joyous serendipity of scientific inquiry. The intertwined nature of these variables echoes the dynamic and ever-changing landscape of sports and media, underscoring the need for continued exploration and analysis in this vibrant field.
In sum, our study underscores the touchdown-worthy connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com, shedding light on the shared joy that football and digital news consumption can bring. So, as football enthusiasts revel in the thrill of the game, they may find an equally satisfying experience awaiting them at USATODAY.com, offering a taste of victory in the digital arena.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our findings corroborate previous research that has hinted at the playful correlation between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. Smith et al.'s (2015) revelatory analysis of touchdown celebrations leading to increased digital media engagement now finds resonance in our robust correlation coefficient, which stood tall and strong like a victorious goal-line stand. It's as if our statistical findings were executing a perfectly timed flea-flicker play, catching the audience off guard with their power and precision.

Similarly, the psychological underpinnings of sports-induced euphoria and its link to online news consumption, as unearthed by Doe and Jones (2018), are further illuminated by our results, akin to a dazzling long bomb connecting with a wide receiver in stride. The impact of adrenaline rushes from astonishing sports plays on subsequent digital content exploration seems to echo the unspoken yet undeniable connection between televised sports and digital news portals.

Gaudelli's (2020) and Thompson's (2019) scholarly treatises on the magnetic allure of NFL games magnetically attracting viewers toward digital news consumption parallel our own findings, illustrating a dynamic relationship reminiscent of a well-coordinated offensive line protecting their quarterback. In a twist worthy of gridiron intrigue, our results thereby offer a touchdown-worthy validation of these scholarly musings, reaffirming the delightful dance between televised sports and digital news platforms.

However, it is crucial to acknowledge the unexpected role of fictional literature in providing bizarre yet surprisingly parallel insights into our research subject. Summers (2016) and Manning (2017) surreptitiously mirror the phenomenon we scrutinize; their fictional narratives almost as enigmatic as a quarterback's pre-snap audibles, aligning with the intricate connection between televised sports and digital media engagement. It appears that even the imaginative realms of storytelling can offer authentic reflections of the interplay between these variables.

Moreover, while our daring exploit into the world of bathroom literature yielded no tangible insights, our journey stands as a testament to the relentless pursuit of knowledge, undeterred by the lack of substantive findings. Just as a tenacious fullback charges through the defensive line, we remained undeterred in our scholarly exploration of the interwoven dynamics of televised sports viewership and digital customer satisfaction.

In closing, our study not only affirms the whimsical connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com but also underscores the buoyant spirit of scientific inquiry. Just as a well-executed game plan yields victory on the field, our findings serve as a rallying cry for continued exploration and analysis in this dynamic field, showcasing the vivacity and joy that adorn the nexus of sports and digital media engagement. So, next time you catch a touchdown, remember to go for the digital extra point with USATODAY.com!


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 NFL broadcast TV viewership and Customer satisfaction with USATODAY.com. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Tackling the Touchdowns: The Gridiron Grin of NFL Broadcast TV Viewership and USATODAY.com Customer Satisfaction

[[ABSTRACT]]
This paper investigates the playful connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. Leveraging data from Zap2it and the American Customer Satisfaction Index, we revealed a strong positive relationship between the two, with a correlation coefficient of 0.7936866 and p < 0.01 from 2003 to 2021. Our findings suggest that as football fans tune in to their favorite gridiron matchups, they may also turn their attention to USATODAY.com, bringing a smile to their digital experience. So, next time you catch a touchdown, remember to go for the digital extra point with USATODAY.com!

[[INTRDUCTION]]
The realm of sports and media is as intertwined as a quarterback and his favorite receiver. In this research paper, we delve into the curious relationship between NFL broadcast TV viewership and customer satisfaction with USATODAY.com, aiming to shed light on the interconnectedness of these seemingly disparate entities. As researchers, we often find ourselves in the end zone of curiosity, ready to tackle complex interactions with the finesse of a seasoned linebacker.
The National Football League (NFL) and its gripping games have long captured the imaginations of millions of viewers, drawing them into a world of bone-crunching tackles, Hail-Mary passes, and nail-biting finishes. Concurrently, the digital realm of news and information has evolved, offering a smorgasbord of content to satiate the ever-growing appetite for real-time updates and punditry. USATODAY.com stands as a charismatic player in this digital arena, drawing in readers with its dynamic blend of news, sports, and the occasional cat video – a touchdown of internet browsing, if you will.
Employing a statistical playbook rivaling that of a seasoned head coach, we delve into the immense dataset gathered from Zap2it and the American Customer Satisfaction Index. Our goal is to unravel the statistical dance of NFL broadcast TV viewership and USATODAY.com customer satisfaction, seeking patterns and connections that dance in the end zone of statistical significance.
This paper is not only a deep dive into the numbers but also a tribute to the joy of scientific discovery. As we embark on this statistical odyssey, we encourage our fellow researchers to enjoy the thrill of the pursuit and savor the touchdowns of insightful data analysis. So, grab your helmet and strap on your cleats, as we set out to uncover the gridiron grin of NFL broadcast TV viewership and USATODAY.com customer satisfaction. It's time to huddle up and tackle this research challenge with a winning spirit and a sprinkle of statistical stardust.

[[RESULTS]]
Our analysis revealed a robust and positive correlation between NFL broadcast TV viewership and customer satisfaction with USATODAY.com from 2003 to 2021. The correlation coefficient of 0.7936866 indicates a strong relationship between these two variables, reminiscent of a well-executed touchdown pass. The r-squared value of 0.6299384 further underscores the impact of NFL broadcast TV viewership on customer satisfaction with USATODAY.com, akin to a perfectly executed end zone celebration dance.
Our findings indicate that as NFL fans tuned in to witness heart-stopping plays and game-winning drives, there was a corresponding boost in customer satisfaction with USATODAY.com, as if a digital touchdown had been scored. The p-value of less than 0.01 lends statistical weight to this connection, as rare as a flea-flicker play in a football game.
To visually depict the strong relationship we uncovered, we present Figure 1, a scatterplot resembling a well-drawn play diagram, showcasing the positive correlation between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. It's a graph that shows just how seamlessly these two variables move down the field together, like a well-coordinated offensive line protecting their quarterback.
Our research not only highlights the statistical significance of the connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com, but it also emphasizes the joyous serendipity of scientific inquiry. The intertwined nature of these variables echoes the dynamic and ever-changing landscape of sports and media, underscoring the need for continued exploration and analysis in this vibrant field.
In sum, our study underscores the touchdown-worthy connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com, shedding light on the shared joy that football and digital news consumption can bring. So, as football enthusiasts revel in the thrill of the game, they may find an equally satisfying experience awaiting them at USATODAY.com, offering a taste of victory in the digital arena.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In wrapping up our statistical exploration, it's clear that the link between NFL broadcast TV viewership and customer satisfaction with USATODAY.com is as strong as a linebacker's grip on a football. Our findings underscored a positive correlation that's as striking as a well-executed end zone celebration dance, with a correlation coefficient that would make any quarterback proud.

As we dug deeper into the data, it became apparent that the partnership between football fandom and digital news consumption is more than just a Hail-Mary pass – it's a meticulous play that yields touchdown-worthy results. Like a perfectly timed flea-flicker play, the statistical weight of this connection left no room for doubt. Our scatterplot, resembling a well-drawn play diagram, depicted the seamless movement of these variables down the field, akin to a well-coordinated offensive line protecting their quarterback from the rush of statistical noise.

It's clear that as football fans bask in the euphoria of exhilarating games, they're turning to USATODAY.com for an equally thrilling digital experience, scoring a digital touchdown in the process. So, next time you witness a game-winning drive, don't forget to go for the digital extra point at USATODAY.com – it's a win-win situation!

In conclusion, our research not only emphasizes the statistical significance of this relationship but also underscores the joyous serendipity of scientific inquiry. It's a reminder that amidst the complex web of statistics and data, there's an undeniable charm and delight in uncovering meaningful connections – a bit like finding a hidden gem in a sea of numbers.

With the touchdown-worthy findings of our study, it's safe to say that we've reached the end zone of inquiry in this area. Further research in this domain may be as unnecessary as icing on a cake – unnecessary but still sweet. Therefore, we assert with confidence that no more research is needed in this area.


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 Tackling the Touchdowns: The Gridiron Grin of NFL Broadcast TV Viewership and USATODAY.com Customer Satisfaction. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Sports Media and Consumer Behavior


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 Tackling the Touchdowns: The Gridiron Grin of NFL Broadcast TV Viewership and USATODAY.com Customer Satisfaction. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Sports Media and Consumer Engagement


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 Tackling the Touchdowns: The Gridiron Grin of NFL Broadcast TV Viewership and USATODAY.com Customer Satisfaction with an abstract of This paper investigates the playful connection between NFL broadcast TV viewership and customer satisfaction with USATODAY.com. Leveraging data from Zap2it and the American Customer Satisfaction Index, we revealed a strong positive relationship between the two, with a correlation coefficient of 0.7936866 and p < 0.01 from 2003 to 2021. Our findings suggest that as football fans tune in to their favorite gridiron matchups, they may also turn their attention to USATODAY.com, bringing a smile to their digital experience. So, next time you catch a touchdown, remember to go for the digital extra point with USATODAY.com!

ChatGPT:

NFL broadcast TV viewership, USATODAY.com customer satisfaction, Zap2it, American Customer Satisfaction Index, football fans, gridiron matchups, digital experience, correlation coefficient, p value, touchdown, extra point, NFL fans, sports viewership

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



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Data details

NFL broadcast TV viewership
Detailed data title: Average NFL broadcast TV viewership
Source: Zap2it
See what else correlates with NFL broadcast TV viewership

Customer satisfaction with USATODAY.com
Source: American Customer Satisfaction Index
See what else correlates with Customer satisfaction with USATODAY.com

Correlation r = 0.7936866 (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 = 0.6299384 (Coefficient of determination)
This means 63% of the change in the one variable (i.e., Customer satisfaction with USATODAY.com) is predictable based on the change in the other (i.e., NFL broadcast TV viewership) over the 19 years from 2003 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.0E-5. 0.0000499351618822214200000000
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 0.79 in 0.005% of random cases. Said differently, if you correlated 20,026 random variables You don't actually need 20 thousand variables to find a correlation like this one. 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.

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 18 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 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.

[ 0.53, 0.92 ] 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.
2003200420052006200720082009201020112012201320142015201620172018201920202021
NFL broadcast TV viewership (Viewership)15500000154000001560000016300000166000001660000018400000200000001790000017500000166000001760000017600000179000001650000015000000156000001680000014900000
Customer satisfaction with USATODAY.com (Consumer Satisfaction)72727274727374777675737674767471747172




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([15500000,15400000,15600000,16300000,16600000,16600000,18400000,20000000,17900000,17500000,16600000,17600000,17600000,17900000,16500000,15000000,15600000,16800000,14900000,])
array_2 = np.array([72,72,72,74,72,73,74,77,76,75,73,76,74,76,74,71,74,71,72,])
array_1_name = "NFL broadcast TV viewership"
array_2_name = "Customer satisfaction with USATODAY.com"

# 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: 1196 · Black Variable ID: 393 · Red Variable ID: 19863
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