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Spurious correlation #3,979 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Super Bowl point difference and the second variable is Highest sale price for a single-family home in Connecticut.  The chart goes from 2006 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As Super Bowl point differences widen, more players invest in luxury real estate, driving up demand and prices in affluent areas like Connecticut. Remember, in the game of real estate, it's all about that super buying power!

Model: dalle-3
Prompt: Generate an image that looks like it is a scene from a Pixar movie with the following details: A football player wearing a victorious expression, celebrating a Super Bowl win. They are surrounded by team members, all displaying jubilation. In the background, there's a giant scoreboard with a significant point difference, indicating their resounding victory. Concurrently, a group of well-dressed real estate agents joyfully hoist a "Sold" sign in front of a lavish mansion, signifying a record-breaking sale in Connecticut. The atmosphere radiates triumph and success, conveying the culmination of hard work and achievement. 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: Super Bowl point difference and Highest sale price for a single-family home in Connecticut. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: An image that looks like it is a scene from a Pixar movie a funny image macro Woodblock painting Concept art Futuristic
ChatGPT: An image that looks like it is a scene from a Pixar movie

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 Super Bowl point difference and Highest sale price for a single-family home in Connecticut, in the following situation: Because when Super Bowl point differences increase, more players invest in real estate, driving up housing prices, including the highest sale price for a single-family home in Connecticut.. Keep the description simple.
ChatGPT: A football player celebrates winning the Super Bowl as the scoreboard behind them shows a large point difference. At the same time, a group of real estate agents raise a "Sold" sign in front of a luxurious mansion in Connecticut, indicating it has just sold for the highest price ever.

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: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: A football player celebrates winning the Super Bowl as the scoreboard behind them shows a large point difference. At the same time, a group of real estate agents raise a "Sold" sign in front of a luxurious mansion in Connecticut, indicating it has just sold for the highest price ever. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that looks like it is a scene from a Pixar movie with the following details: A football player wearing a victorious expression, celebrating a Super Bowl win. They are surrounded by team members, all displaying jubilation. In the background, there's a giant scoreboard with a significant point difference, indicating their resounding victory. Concurrently, a group of well-dressed real estate agents joyfully hoist a "Sold" sign in front of a lavish mansion, signifying a record-breaking sale in Connecticut. The atmosphere radiates triumph and success, conveying the culmination of hard work and achievement.

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

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

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Super Bowl point difference caused Highest sale price for a single-family home in Connecticut to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)
A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread

The Journal of Recreational Statistics

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 Super Bowl point difference and Highest sale price for a single-family home in Connecticut. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Rhyme words in the title.

Your research team used data from Wikipedia and CT OPM to assess this nagging question. You found a correlation coefficient of 0.7873385 and p < 0.01 for 2006 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]]
A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread

[[ABSTRACT]]
This paper delves into the unexpected and perhaps, inexplicable relationship between the point difference in Super Bowl games and the highest sale price for a single-family home in the fine state of Connecticut. Using data sourced from Wikipedia and the Connecticut Office of Policy and Management (CT OPM), a comprehensive analysis spanning the years 2006 to 2021 was undertaken. The findings revealed a remarkably robust correlation coefficient of 0.7873385 with a statistically significant p-value of less than 0.01. Surprisingly, it seems that the spectacle of the Super Bowl may indeed have a palpable impact on the real estate market in the Constitution State. Whether this correlation is merely fortuitous fluke or a reflection of some deeper cultural phenomenon remains a question as intriguing as the game of football itself. This study not only sheds light on an unusual statistical relationship but also offers a lighthearted glimpse into the unpredictable world of interdisciplinary research.


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 Super Bowl point difference and Highest sale price for a single-family home in Connecticut. 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]]
A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread

[[ABSTRACT]]
This paper delves into the unexpected and perhaps, inexplicable relationship between the point difference in Super Bowl games and the highest sale price for a single-family home in the fine state of Connecticut. Using data sourced from Wikipedia and the Connecticut Office of Policy and Management (CT OPM), a comprehensive analysis spanning the years 2006 to 2021 was undertaken. The findings revealed a remarkably robust correlation coefficient of 0.7873385 with a statistically significant p-value of less than 0.01. Surprisingly, it seems that the spectacle of the Super Bowl may indeed have a palpable impact on the real estate market in the Constitution State. Whether this correlation is merely fortuitous fluke or a reflection of some deeper cultural phenomenon remains a question as intriguing as the game of football itself. This study not only sheds light on an unusual statistical relationship but also offers a lighthearted glimpse into the unpredictable world of interdisciplinary research.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
INTRODUCTION

The field of economics and urban analysis has long been inhabited by practitioners seeking to uncover the hidden connections and underlying influences that shape real estate markets. These endeavors often involve rigorous statistical analysis, hypothesis testing, and modeling techniques to ascertain the myriad factors affecting property prices. In this vein, the present study endeavors to probe an unconventional and purportedly whimsical link between the outcome of the Super Bowl and the highest sale price for a single-family home in the northeastern enclave of Connecticut.

The notion that a sporting event steeped in spectacle and athleticism could have any bearing on the housing market may appear preposterous at first glance. However, as renowned economist John Maynard Keynes once quipped, "The market can remain irrational longer than you can remain solvent." With this in mind, we set out to explore whether the ebbs and flows of gridiron triumphs and defeats have any tangible impact on the ebb and flow of real estate fortunes in the Nutmeg State.

The title of this study, "A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread," alludes to both the competitive essence of the Super Bowl and the potential implications for homeowners in the state of Connecticut. As we wade into this uncharted territory, it is crucial to maintain a balanced and methodical approach, acknowledging the fantastical premise of our inquiry while anchored firmly to the principles of empirical analysis.

The pursuit of this endeavor became all the more compelling when initial explorations of available data exhibited a correlation that few could have anticipated. It is our hope that by detailing the methodology, results, and implications of this investigation, we can not only elucidate this peculiar correlation but also perhaps inspire a touch of whimsy and wonder in the often stern countenance of academic inquiry. For, after all, as the comedienne Lily Tomlin once quipped, "Reality is the leading cause of stress among those in touch with it." With that in mind, let us embark on a lighthearted odyssey through the realm of statistics and surprises.


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 Super Bowl point difference and Highest sale price for a single-family home in Connecticut. 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.

Here is the title and abstract of the paper:
[[TITLE]]
A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread

[[ABSTRACT]]
This paper delves into the unexpected and perhaps, inexplicable relationship between the point difference in Super Bowl games and the highest sale price for a single-family home in the fine state of Connecticut. Using data sourced from Wikipedia and the Connecticut Office of Policy and Management (CT OPM), a comprehensive analysis spanning the years 2006 to 2021 was undertaken. The findings revealed a remarkably robust correlation coefficient of 0.7873385 with a statistically significant p-value of less than 0.01. Surprisingly, it seems that the spectacle of the Super Bowl may indeed have a palpable impact on the real estate market in the Constitution State. Whether this correlation is merely fortuitous fluke or a reflection of some deeper cultural phenomenon remains a question as intriguing as the game of football itself. This study not only sheds light on an unusual statistical relationship but also offers a lighthearted glimpse into the unpredictable world of interdisciplinary research.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The field of economics and urban analysis has long been inhabited by practitioners seeking to uncover the hidden connections and underlying influences that shape real estate markets. These endeavors often involve rigorous statistical analysis, hypothesis testing, and modeling techniques to ascertain the myriad factors affecting property prices. In this vein, the present study endeavors to probe an unconventional and purportedly whimsical link between the outcome of the Super Bowl and the highest sale price for a single-family home in the northeastern enclave of Connecticut.
The notion that a sporting event steeped in spectacle and athleticism could have any bearing on the housing market may appear preposterous at first glance. However, as renowned economist John Maynard Keynes once quipped, "The market can remain irrational longer than you can remain solvent." With this in mind, we set out to explore whether the ebbs and flows of gridiron triumphs and defeats have any tangible impact on the ebb and flow of real estate fortunes in the Nutmeg State.
The title of this study, "A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread," alludes to both the competitive essence of the Super Bowl and the potential implications for homeowners in the state of Connecticut. As we wade into this uncharted territory, it is crucial to maintain a balanced and methodical approach, acknowledging the fantastical premise of our inquiry while anchored firmly to the principles of empirical analysis.
The pursuit of this endeavor became all the more compelling when initial explorations of available data exhibited a correlation that few could have anticipated. It is our hope that by detailing the methodology, results, and implications of this investigation, we can not only elucidate this peculiar correlation but also perhaps inspire a touch of whimsy and wonder in the often stern countenance of academic inquiry. For, after all, as the comedienne Lily Tomlin once quipped, "Reality is the leading cause of stress among those in touch with it." With that in mind, let us embark on a lighthearted odyssey through the realm of statistics and surprises.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The authors found that the connection between the point difference in Super Bowl games and the highest sale price for a single-family home in Connecticut has been, unsurprisingly, a neglected area of inquiry in the realm of economic analysis. Nonetheless, a few authors have ventured into this peculiar domain. Smith et al. (2015) attempted to draw parallels between the margin of victory in professional football games and the fluctuations in housing prices, ultimately suggesting a tenuous link. Doe and Jones (2018) took a more innovative approach, proposing a potential correlation between Super Bowl outcomes and luxury property sales in select U.S. states. While their findings presented some suggestive trends, the robustness of the association remained in question.

Turning to more tangentially related works, "The Economics of Super Bowl Spectacles" by Johnson (2017) provides a comprehensive examination of the economic impacts of hosting the Super Bowl, albeit focusing primarily on host cities rather than distant residential markets such as those in Connecticut. On a more speculative note, "Touchdowns and Townhouses: A Comparative Analysis" by Anderson (2013) briefly touches upon the intersection of sports events and real estate, inviting readers on an imaginative journey to envision the potential interplay between touchdowns and townhouses.

In the realm of fiction, there are no direct references to the Super Bowl and real estate in Connecticut, but one cannot overlook the thematic intersection of competitive fervor and housing in literary classics. "The Great Gatsby" by F. Scott Fitzgerald and "A Man Called Ove" by Fredrik Backman both offer nuanced portrayals of the relationship between social events and the dynamics of property ownership. While their settings are a far cry from the football frenzy of the Super Bowl, their underlying themes of aspiration and societal norms are not entirely dissimilar.

Stepping into more whimsical territories, this research must also acknowledge the unorthodox methods of inquiry that have been undertaken in the pursuit of understanding the Super Bowl's influence on Connecticut's real estate. Anecdotal evidence and casual observations, including perusing obscure blog posts, deciphering fortune cookie messages, and even scrutinizing CVS receipts, have all contributed to the collective imagination on this peculiar crossroads of sports and housing. While these sources are not conventional by academic standards, they provide a peculiar lens through which to ponder the enigmatic relationship between the Super Bowl and the Connecticut housing market.


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 Super Bowl point difference and Highest sale price for a single-family home in Connecticut. 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 Wikipedia and CT OPM . You used data from 2006 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]]
A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread

[[ABSTRACT]]
This paper delves into the unexpected and perhaps, inexplicable relationship between the point difference in Super Bowl games and the highest sale price for a single-family home in the fine state of Connecticut. Using data sourced from Wikipedia and the Connecticut Office of Policy and Management (CT OPM), a comprehensive analysis spanning the years 2006 to 2021 was undertaken. The findings revealed a remarkably robust correlation coefficient of 0.7873385 with a statistically significant p-value of less than 0.01. Surprisingly, it seems that the spectacle of the Super Bowl may indeed have a palpable impact on the real estate market in the Constitution State. Whether this correlation is merely fortuitous fluke or a reflection of some deeper cultural phenomenon remains a question as intriguing as the game of football itself. This study not only sheds light on an unusual statistical relationship but also offers a lighthearted glimpse into the unpredictable world of interdisciplinary research.

[[INTRODUCTION]]
INTRODUCTION
The field of economics and urban analysis has long been inhabited by practitioners seeking to uncover the hidden connections and underlying influences that shape real estate markets. These endeavors often involve rigorous statistical analysis, hypothesis testing, and modeling techniques to ascertain the myriad factors affecting property prices. In this vein, the present study endeavors to probe an unconventional and purportedly whimsical link between the outcome of the Super Bowl and the highest sale price for a single-family home in the northeastern enclave of Connecticut.
The notion that a sporting event steeped in spectacle and athleticism could have any bearing on the housing market may appear preposterous at first glance. However, as renowned economist John Maynard Keynes once quipped, "The market can remain irrational longer than you can remain solvent." With this in mind, we set out to explore whether the ebbs and flows of gridiron triumphs and defeats have any tangible impact on the ebb and flow of real estate fortunes in the Nutmeg State.
The title of this study, "A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread," alludes to both the competitive essence of the Super Bowl and the potential implications for homeowners in the state of Connecticut. As we wade into this uncharted territory, it is crucial to maintain a balanced and methodical approach, acknowledging the fantastical premise of our inquiry while anchored firmly to the principles of empirical analysis.
The pursuit of this endeavor became all the more compelling when initial explorations of available data exhibited a correlation that few could have anticipated. It is our hope that by detailing the methodology, results, and implications of this investigation, we can not only elucidate this peculiar correlation but also perhaps inspire a touch of whimsy and wonder in the often stern countenance of academic inquiry. For, after all, as the comedienne Lily Tomlin once quipped, "Reality is the leading cause of stress among those in touch with it." With that in mind, let us embark on a lighthearted odyssey through the realm of statistics and surprises.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Data Collection:
The data for this study was collected from various sources, including Wikipedia and the Connecticut Office of Policy and Management (CT OPM). The years 2006 to 2021 were selected as the time frame for analysis, encompassing fifteen Super Bowl events and corresponding real estate market trends within the state of Connecticut. While these data sources may raise some skeptical eyebrows due to their potentially less scholarly nature, it is worth noting that they served as the most comprehensive and accessible repositories for the specific variables under investigation. The use of such unconventional sources infuses this research with a certain quirkiness, reflective of the subject matter it explores.

Super Bowl Point Difference Measurement:
To quantify the outcome of each Super Bowl game, the point difference between the winning and losing teams was recorded. This variable was chosen as an indicator of the magnitude of victory or defeat, encapsulating the competitive dynamics of the game. As a lighthearted aside, it could be argued that these point differentials also signify the emotional ups and downs experienced by fans, akin to the roller coaster of emotions that awaits homeowners in the tumultuous real estate market.

Highest Sale Price for a Single-Family Home in Connecticut:
The primary focus of this study was on the highest sale price for a single-family home within the boundaries of Connecticut during the aforementioned years. This variable served as a proxy for the overall state of the real estate market, capturing the pinnacle of property transactions and offering insights into the upper echelons of residential property values. The very notion of a "highest sale price" inherently evokes imagery of the zenith of real estate triumph - a notion that finds an unexpected parallel in the triumphs and defeats witnessed on the gridiron.

Statistical Analysis:
Upon assembling the data, a comprehensive statistical analysis was conducted to explore the potential relationship between the Super Bowl point difference and the highest sale price for single-family homes in Connecticut. Correlation coefficients, regression analyses, and significance tests were the tools employed to unravel the mysteries underlying this improbable association. The use of these conventional statistical methodologies amidst the unorthodox premise of the study creates a delightful juxtaposition, underscoring the playfulness inherent in academic investigations of unusual phenomena.

Limitations:
It is important to acknowledge that the utilization of unconventional data sources and the seemingly whimsical nature of the research question posed certain limitations. As with any scholarly endeavor, the constraints of data availability and the interpretive scope of the study necessitate a degree of caution when interpreting the findings. Nevertheless, it is our hope that this study will serve as an invitation to embrace the unexpected and to find delight in the unlikeliest of statistical phenomena.


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 Super Bowl point difference and Highest sale price for a single-family home in Connecticut. 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 Wikipedia and CT OPM .

For the time period 2006 to 2021, you found a correlation 0.7873385, r-squared of 0.6199020, 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]]
A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread

[[ABSTRACT]]
This paper delves into the unexpected and perhaps, inexplicable relationship between the point difference in Super Bowl games and the highest sale price for a single-family home in the fine state of Connecticut. Using data sourced from Wikipedia and the Connecticut Office of Policy and Management (CT OPM), a comprehensive analysis spanning the years 2006 to 2021 was undertaken. The findings revealed a remarkably robust correlation coefficient of 0.7873385 with a statistically significant p-value of less than 0.01. Surprisingly, it seems that the spectacle of the Super Bowl may indeed have a palpable impact on the real estate market in the Constitution State. Whether this correlation is merely fortuitous fluke or a reflection of some deeper cultural phenomenon remains a question as intriguing as the game of football itself. This study not only sheds light on an unusual statistical relationship but also offers a lighthearted glimpse into the unpredictable world of interdisciplinary research.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
The field of economics and urban analysis has long been inhabited by practitioners seeking to uncover the hidden connections and underlying influences that shape real estate markets. These endeavors often involve rigorous statistical analysis, hypothesis testing, and modeling techniques to ascertain the myriad factors affecting property prices. In this vein, the present study endeavors to probe an unconventional and purportedly whimsical link between the outcome of the Super Bowl and the highest sale price for a single-family home in the northeastern enclave of Connecticut.
The notion that a sporting event steeped in spectacle and athleticism could have any bearing on the housing market may appear preposterous at first glance. However, as renowned economist John Maynard Keynes once quipped, "The market can remain irrational longer than you can remain solvent." With this in mind, we set out to explore whether the ebbs and flows of gridiron triumphs and defeats have any tangible impact on the ebb and flow of real estate fortunes in the Nutmeg State.
The title of this study, "A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread," alludes to both the competitive essence of the Super Bowl and the potential implications for homeowners in the state of Connecticut. As we wade into this uncharted territory, it is crucial to maintain a balanced and methodical approach, acknowledging the fantastical premise of our inquiry while anchored firmly to the principles of empirical analysis.
The pursuit of this endeavor became all the more compelling when initial explorations of available data exhibited a correlation that few could have anticipated. It is our hope that by detailing the methodology, results, and implications of this investigation, we can not only elucidate this peculiar correlation but also perhaps inspire a touch of whimsy and wonder in the often stern countenance of academic inquiry. For, after all, as the comedienne Lily Tomlin once quipped, "Reality is the leading cause of stress among those in touch with it." With that in mind, let us embark on a lighthearted odyssey through the realm of statistics and surprises.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of the data collected from the years 2006 to 2021 yielded an unexpected and intriguing result. The correlation coefficient between the point difference in Super Bowl games and the highest sale price for a single-family home in Connecticut was found to be 0.7873385, indicating a strong positive relationship between these two seemingly disparate phenomena. The coefficient of determination (r-squared) was determined to be 0.6199020, signifying that approximately 61.99% of the variance in home sale prices can be explained by the variation in Super Bowl point differences. Moreover, the obtained p-value of less than 0.01 underscores the statistical significance of this correlation, corroborating the strength of the relationship observed.

Figure 1 illustrates the scatterplot depicting the positive correlation between the Super Bowl point difference and the highest sale price for a single-family home in Connecticut. The figure visually encapsulates the surprising connection uncovered by our analysis, showcasing the intriguing trend between these two variables.

The robustness of the correlation coefficient suggests that there may indeed be a discernible impact of Super Bowl outcomes on the real estate market in Connecticut. While this finding may raise eyebrows and prompt a skeptical chuckle, the statistical evidence speaks for itself. The implications of this connection, whether rooted in cultural phenomena or happenstance, beckon further examination and contemplation, much like an unexpected twist in an enthralling gridiron match.

It is worth noting that while the observed correlation is substantial, it does not imply causation. The tantalizing question of whether the vicissitudes of football fortunes directly influence property prices, or if an unseen variable underpins both phenomena, remains an enigma that warrants deeper exploration. This study not only sheds light on a unique statistical relationship but also invites speculation, mirth, and curiosity in equal measure, akin to the unpredictability of a captivating championship game.


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 Super Bowl point difference and Highest sale price for a single-family home in Connecticut. 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]]
A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread

[[ABSTRACT]]
This paper delves into the unexpected and perhaps, inexplicable relationship between the point difference in Super Bowl games and the highest sale price for a single-family home in the fine state of Connecticut. Using data sourced from Wikipedia and the Connecticut Office of Policy and Management (CT OPM), a comprehensive analysis spanning the years 2006 to 2021 was undertaken. The findings revealed a remarkably robust correlation coefficient of 0.7873385 with a statistically significant p-value of less than 0.01. Surprisingly, it seems that the spectacle of the Super Bowl may indeed have a palpable impact on the real estate market in the Constitution State. Whether this correlation is merely fortuitous fluke or a reflection of some deeper cultural phenomenon remains a question as intriguing as the game of football itself. This study not only sheds light on an unusual statistical relationship but also offers a lighthearted glimpse into the unpredictable world of interdisciplinary research.

[[LITERATURE REVIEW]]
The authors found that the connection between the point difference in Super Bowl games and the highest sale price for a single-family home in Connecticut has been, unsurprisingly, a neglected area of inquiry in the realm of economic analysis. Nonetheless, a few authors have ventured into this peculiar domain. Smith et al. (2015) attempted to draw parallels between the margin of victory in professional football games and the fluctuations in housing prices, ultimately suggesting a tenuous link. Doe and Jones (2018) took a more innovative approach, proposing a potential correlation between Super Bowl outcomes and luxury property sales in select U.S. states. While their findings presented some suggestive trends, the robustness of the association remained in question.
Turning to more tangentially related works, "The Economics of Super Bowl Spectacles" by Johnson (2017) provides a comprehensive examination of the economic impacts of hosting the Super Bowl, albeit focusing primarily on host cities rather than distant residential markets such as those in Connecticut. On a more speculative note, "Touchdowns and Townhouses: A Comparative Analysis" by Anderson (2013) briefly touches upon the intersection of sports events and real estate, inviting readers on an imaginative journey to envision the potential interplay between touchdowns and townhouses.
In the realm of fiction, there are no direct references to the Super Bowl and real estate in Connecticut, but one cannot overlook the thematic intersection of competitive fervor and housing in literary classics. "The Great Gatsby" by F. Scott Fitzgerald and "A Man Called Ove" by Fredrik Backman both offer nuanced portrayals of the relationship between social events and the dynamics of property ownership. While their settings are a far cry from the football frenzy of the Super Bowl, their underlying themes of aspiration and societal norms are not entirely dissimilar.
Stepping into more whimsical territories, this research must also acknowledge the unorthodox methods of inquiry that have been undertaken in the pursuit of understanding the Super Bowl's influence on Connecticut's real estate. Anecdotal evidence and casual observations, including perusing obscure blog posts, deciphering fortune cookie messages, and even scrutinizing CVS receipts, have all contributed to the collective imagination on this peculiar crossroads of sports and housing. While these sources are not conventional by academic standards, they provide a peculiar lens through which to ponder the enigmatic relationship between the Super Bowl and the Connecticut housing market.

[[RESULTS]]
The analysis of the data collected from the years 2006 to 2021 yielded an unexpected and intriguing result. The correlation coefficient between the point difference in Super Bowl games and the highest sale price for a single-family home in Connecticut was found to be 0.7873385, indicating a strong positive relationship between these two seemingly disparate phenomena. The coefficient of determination (r-squared) was determined to be 0.6199020, signifying that approximately 61.99% of the variance in home sale prices can be explained by the variation in Super Bowl point differences. Moreover, the obtained p-value of less than 0.01 underscores the statistical significance of this correlation, corroborating the strength of the relationship observed.
Figure 1 illustrates the scatterplot depicting the positive correlation between the Super Bowl point difference and the highest sale price for a single-family home in Connecticut. The figure visually encapsulates the surprising connection uncovered by our analysis, showcasing the intriguing trend between these two variables.
The robustness of the correlation coefficient suggests that there may indeed be a discernible impact of Super Bowl outcomes on the real estate market in Connecticut. While this finding may raise eyebrows and prompt a skeptical chuckle, the statistical evidence speaks for itself. The implications of this connection, whether rooted in cultural phenomena or happenstance, beckon further examination and contemplation, much like an unexpected twist in an enthralling gridiron match.
It is worth noting that while the observed correlation is substantial, it does not imply causation. The tantalizing question of whether the vicissitudes of football fortunes directly influence property prices, or if an unseen variable underpins both phenomena, remains an enigma that warrants deeper exploration. This study not only sheds light on a unique statistical relationship but also invites speculation, mirth, and curiosity in equal measure, akin to the unpredictability of a captivating championship game.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The findings of this study provide compelling evidence supporting the long-neglected relationship between the point difference in Super Bowl games and the highest sale price for single-family homes in Connecticut. The striking correlation coefficient of 0.7873385 and the statistically significant p-value of less than 0.01 offer robust support for the notion that Super Bowl outcomes may indeed exert a discernible influence on the real estate market in the Constitution State. The results not only align with, but also surpass the implications of prior research, thus showcasing the palpable impact of Super Bowl spectacles on the residential property market.

Our results are in concordance with the work of Smith et al. (2015), who drew parallels between the margin of victory in professional football games and housing price fluctuations. It appears that the tenuous link proposed by Smith et al. (2015) is, in fact, more robust than previously appreciated. Furthermore, the suggestive trends identified by Doe and Jones (2018) regarding the correlation between Super Bowl outcomes and luxury property sales find substantial empirical support in the present study. The substantial correlation coefficient and the visually captivating scatterplot further corroborate the potential interconnectedness of these seemingly unrelated domains.

This study builds upon the scholarly foundations laid by Johnson (2017) and Anderson (2013), elucidating the potential ramifications of Super Bowl dynamics on distant residential markets. While Johnson (2017) primarily focused on host cities, the findings of our study extend the economic impacts of the Super Bowl to distant residential markets, exemplified by the discernible influence on the Connecticut real estate landscape. The whimsical realms of literary classics, such as "The Great Gatsby" and "A Man Called Ove," are not as far removed from contemporary statistical observations as one might initially surmise. The thematic intersection of competitive fervor and housing in literature finds a parallel in the palpable influence of football outcomes on residential property prices in modern-day Connecticut.

Moreover, the unorthodox methods of inquiry that have been adopted in this research deserve a reevaluation. Anecdotal evidence and casual observations, often dismissed in academia, have played an unexpected role in shaping the conclusions of this study. The eccentricity of these methods has unexpectedly magnified the robustness of the correlation identified, underscoring the unquestionable statistical significance of this unusual relationship. It is a striking reminder that unconventional sources can unravel profound insights, much like a hidden yardage gain in the final moments of a thrilling football game.

While the observed correlation is substantial, it is important to emphasize that this study does not imply causation. The tantalizing question of whether the vicissitudes of football fortunes directly influence property prices, or if an unseen variable underpins both phenomena, remains an enigmatic puzzle warranting deeper exploration. This study enhances our understanding of a truly unique statistical relationship while inviting a sense of contemplative mirth and scholarly curiosity, akin to the multifaceted unpredictability of a captivating championship game.


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 Super Bowl point difference and Highest sale price for a single-family home in Connecticut. 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]]
A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread

[[ABSTRACT]]
This paper delves into the unexpected and perhaps, inexplicable relationship between the point difference in Super Bowl games and the highest sale price for a single-family home in the fine state of Connecticut. Using data sourced from Wikipedia and the Connecticut Office of Policy and Management (CT OPM), a comprehensive analysis spanning the years 2006 to 2021 was undertaken. The findings revealed a remarkably robust correlation coefficient of 0.7873385 with a statistically significant p-value of less than 0.01. Surprisingly, it seems that the spectacle of the Super Bowl may indeed have a palpable impact on the real estate market in the Constitution State. Whether this correlation is merely fortuitous fluke or a reflection of some deeper cultural phenomenon remains a question as intriguing as the game of football itself. This study not only sheds light on an unusual statistical relationship but also offers a lighthearted glimpse into the unpredictable world of interdisciplinary research.

[[INTRDUCTION]]
INTRODUCTION
The field of economics and urban analysis has long been inhabited by practitioners seeking to uncover the hidden connections and underlying influences that shape real estate markets. These endeavors often involve rigorous statistical analysis, hypothesis testing, and modeling techniques to ascertain the myriad factors affecting property prices. In this vein, the present study endeavors to probe an unconventional and purportedly whimsical link between the outcome of the Super Bowl and the highest sale price for a single-family home in the northeastern enclave of Connecticut.
The notion that a sporting event steeped in spectacle and athleticism could have any bearing on the housing market may appear preposterous at first glance. However, as renowned economist John Maynard Keynes once quipped, "The market can remain irrational longer than you can remain solvent." With this in mind, we set out to explore whether the ebbs and flows of gridiron triumphs and defeats have any tangible impact on the ebb and flow of real estate fortunes in the Nutmeg State.
The title of this study, "A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread," alludes to both the competitive essence of the Super Bowl and the potential implications for homeowners in the state of Connecticut. As we wade into this uncharted territory, it is crucial to maintain a balanced and methodical approach, acknowledging the fantastical premise of our inquiry while anchored firmly to the principles of empirical analysis.
The pursuit of this endeavor became all the more compelling when initial explorations of available data exhibited a correlation that few could have anticipated. It is our hope that by detailing the methodology, results, and implications of this investigation, we can not only elucidate this peculiar correlation but also perhaps inspire a touch of whimsy and wonder in the often stern countenance of academic inquiry. For, after all, as the comedienne Lily Tomlin once quipped, "Reality is the leading cause of stress among those in touch with it." With that in mind, let us embark on a lighthearted odyssey through the realm of statistics and surprises.

[[RESULTS]]
The analysis of the data collected from the years 2006 to 2021 yielded an unexpected and intriguing result. The correlation coefficient between the point difference in Super Bowl games and the highest sale price for a single-family home in Connecticut was found to be 0.7873385, indicating a strong positive relationship between these two seemingly disparate phenomena. The coefficient of determination (r-squared) was determined to be 0.6199020, signifying that approximately 61.99% of the variance in home sale prices can be explained by the variation in Super Bowl point differences. Moreover, the obtained p-value of less than 0.01 underscores the statistical significance of this correlation, corroborating the strength of the relationship observed.
Figure 1 illustrates the scatterplot depicting the positive correlation between the Super Bowl point difference and the highest sale price for a single-family home in Connecticut. The figure visually encapsulates the surprising connection uncovered by our analysis, showcasing the intriguing trend between these two variables.
The robustness of the correlation coefficient suggests that there may indeed be a discernible impact of Super Bowl outcomes on the real estate market in Connecticut. While this finding may raise eyebrows and prompt a skeptical chuckle, the statistical evidence speaks for itself. The implications of this connection, whether rooted in cultural phenomena or happenstance, beckon further examination and contemplation, much like an unexpected twist in an enthralling gridiron match.
It is worth noting that while the observed correlation is substantial, it does not imply causation. The tantalizing question of whether the vicissitudes of football fortunes directly influence property prices, or if an unseen variable underpins both phenomena, remains an enigma that warrants deeper exploration. This study not only sheds light on a unique statistical relationship but also invites speculation, mirth, and curiosity in equal measure, akin to the unpredictability of a captivating championship game.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study into the perplexing nexus between the point difference in Super Bowl games and the highest sale price for a single-family home in Connecticut has yielded an unexpected and robust correlation coefficient of 0.7873385, with a statistically significant p-value of less than 0.01. This peculiar relationship, while initially met with skepticism and raised eyebrows, has withstood rigorous statistical scrutiny, much like the unexpected resilience of an underdog football team. These findings, like a well-executed touchdown play, highlight the intricate and often confounding interplay between seemingly unrelated phenomena in the realm of economic and housing markets.

The implications of our results beckon further contemplation, akin to the suspense of an overtime period in a championship game. While causality cannot be inferred from our findings, the statistical evidence presents an intriguing avenue for future inquiry. As famed economist Milton Friedman once postulated, "Casual empiricism is no more useful in a scientist than casual reading in a scholar," we must approach the enigmatic relationship between Super Bowl outcomes and property prices with meticulous rigor and an unquenchable spirit of inquiry.

The implications of this study extend beyond the confines of statistical analysis, inviting a touch of whimsy and wonder into the often stern countenance of academic research. This unexpected correlation serves as a reminder that, in the words of renowned philosopher Friedrich Nietzsche, "There are no facts, only interpretations," prompting us to reconsider the multifaceted nature of economic influences and cultural reverberations.

In light of these notable findings, it is our assertion that no further research is needed in this area. The statistical evidence presented in this study stands as a testament to the unpredictability and hidden connections that underpin our world, much like the exhilarating unpredictability of a Super Bowl game. As we bid adieu to this lighthearted odyssey, we leave the door ajar for future researchers to explore the whimsical and uncharted territories that enrich our understanding of the intricate tapestry of economic and cultural phenomena.


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 A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Recreational Statistics


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 A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Sports Analytics and Behavioral Economics


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 A Game of Points: The Super Bowl Spread and Connecticut's Homestead Dread with an abstract of This paper delves into the unexpected and perhaps, inexplicable relationship between the point difference in Super Bowl games and the highest sale price for a single-family home in the fine state of Connecticut. Using data sourced from Wikipedia and the Connecticut Office of Policy and Management (CT OPM), a comprehensive analysis spanning the years 2006 to 2021 was undertaken. The findings revealed a remarkably robust correlation coefficient of 0.7873385 with a statistically significant p-value of less than 0.01. Surprisingly, it seems that the spectacle of the Super Bowl may indeed have a palpable impact on the real estate market in the Constitution State. Whether this correlation is merely fortuitous fluke or a reflection of some deeper cultural phenomenon remains a question as intriguing as the game of football itself. This study not only sheds light on an unusual statistical relationship but also offers a lighthearted glimpse into the unpredictable world of interdisciplinary research.

ChatGPT:

Super Bowl, point difference, Connecticut, homestead prices, real estate market, statistical analysis, correlation coefficient, data analysis, interdisciplinary research

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



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Data details

Super Bowl point difference
Source: Wikipedia
See what else correlates with Super Bowl point difference

Highest sale price for a single-family home in Connecticut
Source: CT OPM
See what else correlates with Highest sale price for a single-family home in Connecticut

Correlation r = 0.7873385 (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 = 0.6199020 (Coefficient of determination)
This means 62% of the change in the one variable (i.e., Highest sale price for a single-family home in Connecticut) is predictable based on the change in the other (i.e., Super Bowl point difference) over the 16 years from 2006 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00029. 0.0002943083482789766000000000
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 0.029% of random cases. Said differently, if you correlated 3,398 random variables Which I absolutely did.
with the same 15 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 15 because we have two variables measured over a period of 16 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.48, 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.
2006200720082009201020112012201320142015201620172018201920202021
Super Bowl point difference (Points)1112341464335141468101122
Highest sale price for a single-family home in Connecticut (House sale price)308303002842360030000000225000003137500016000000205000002500000012000000026000000148200004752450021500000480000004217500045000000




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([11,12,3,4,14,6,4,3,35,14,14,6,8,10,11,22,])
array_2 = np.array([30830300,28423600,30000000,22500000,31375000,16000000,20500000,25000000,120000000,26000000,14820000,47524500,21500000,48000000,42175000,45000000,])
array_1_name = "Super Bowl point difference"
array_2_name = "Highest sale price for a single-family home in Connecticut"

# 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: 3979 · Black Variable ID: 541 · Red Variable ID: 900
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