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Spurious correlation #3,756 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Annual US household spending on home maintenance and the second variable is Microsoft's stock price (MSFT).  The chart goes from 2002 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As Americans invested more in fixing up their homes, the demand for Windows (the glass kind) skyrocketed, leading to a surge in profits for glass manufacturers. This positive growth in the glass industry directly reflected on the stock market, boosting Microsoft's stock price as investors saw the company as a pane-ful opportunity.

Model: dalle-3
Prompt: Generate an image featuring a minimalist scene of a family gathered around a sleek, modern compact computer. The focus is on the family members engaging in various activities related to home maintenance and technology. One member is leaning forward, watching a DIY repair video on the computer, with a tool in hand. Another family member is in the frame, casually browsing through different computer options, showcasing the technological aspect. Meanwhile, in the background on the computer screen, display a minimalist representation of Microsoft's stock price graph with a sharp and evident upward trend, indicating the increased demand for new computers due to the rise in household spending on home maintenance. The color palette should be clean and contemporary, with a sense of space and simplicity. 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: Annual US household spending on home maintenance and Microsoft's stock price (MSFT). 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: Low poly inspired by bauhaus Vaporwave Minimalism Pop art
ChatGPT: Minimalism

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 Annual US household spending on home maintenance and Microsoft's stock price (MSFT), in the following situation: Because the more money people spent on home maintenance, the more they realized they needed to upgrade their computers to avoid doing any actual work around the house. This increased demand for new computers caused Microsoft's stock price to soar.. Keep the description simple.
ChatGPT: A family is gathered around their computer, discussing home maintenance projects. One person is looking up DIY repair videos, while another is browsing for new computer options. In the background, Microsoft's stock price graph is seen on the computer screen, showing a sharp upward trend as demand for new computers increases due to the increased household spending on home maintenance.

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: [ Minimalism ] and depicting this scene: A family is gathered around their computer, discussing home maintenance projects. One person is looking up DIY repair videos, while another is browsing for new computer options. In the background, Microsoft's stock price graph is seen on the computer screen, showing a sharp upward trend as demand for new computers increases due to the increased household spending on home maintenance. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image featuring a minimalist scene of a family gathered around a sleek, modern compact computer. The focus is on the family members engaging in various activities related to home maintenance and technology. One member is leaning forward, watching a DIY repair video on the computer, with a tool in hand. Another family member is in the frame, casually browsing through different computer options, showcasing the technological aspect. Meanwhile, in the background on the computer screen, display a minimalist representation of Microsoft's stock price graph with a sharp and evident upward trend, indicating the increased demand for new computers due to the rise in household spending on home maintenance. The color palette should be clean and contemporary, with a sense of space and simplicity.

*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 Annual US household spending on home maintenance caused Microsoft's stock price (MSFT) to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)
The Home is Where the Stock is Effect: Understanding the Relationship Between Annual US Household Spending on Home Maintenance and Microsoft's Stock Price

The Journal of Quirky Economic Research

Jan 2024

Reminder: This paper is AI-generated. Not real!
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Annual US household spending on home maintenance and Microsoft's stock price (MSFT). 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 Bureau of Labor Statistics and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9325046 and p < 0.01 for 2002 to 2022.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
The "Home is Where the Stock is" Effect: Understanding the Relationship Between Annual US Household Spending on Home Maintenance and Microsoft's Stock Price

[[ABSTRACT]]
In this paper, we investigate the often-overlooked connection between household spending on home maintenance and the stock price of a certain tech giant, Microsoft. While it may seem like a stretch to link fixing leaky faucets with the fluctuation of a company's stock price, our analysis reveals a surprising correlation. Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we found a correlation coefficient of 0.9325046 with p < 0.01 for the period from 2002 to 2022. Our findings suggest that there may be a previously unnoticed relationship between the two variables, prompting further inquiry into the economic and psychological factors at play. Join us as we delve into the wacky world of household maintenance and stock market dynamics, and ponder the possibility that perhaps it's not just the roof that needs fixing during turbulent market times!


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between Annual US household spending on home maintenance and Microsoft's stock price (MSFT). Make lots of jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
The "Home is Where the Stock is" Effect: Understanding the Relationship Between Annual US Household Spending on Home Maintenance and Microsoft's Stock Price

[[ABSTRACT]]
In this paper, we investigate the often-overlooked connection between household spending on home maintenance and the stock price of a certain tech giant, Microsoft. While it may seem like a stretch to link fixing leaky faucets with the fluctuation of a company's stock price, our analysis reveals a surprising correlation. Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we found a correlation coefficient of 0.9325046 with p < 0.01 for the period from 2002 to 2022. Our findings suggest that there may be a previously unnoticed relationship between the two variables, prompting further inquiry into the economic and psychological factors at play. Join us as we delve into the wacky world of household maintenance and stock market dynamics, and ponder the possibility that perhaps it's not just the roof that needs fixing during turbulent market times!

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Welcome, dear readers, to a curiously quirky investigation into the intriguing world of household spending on home maintenance and its peculiar connection to the stock price of none other than the tech behemoth, Microsoft. In this research paper, we invite you to join us on a journey through leaky roofs, wobbly shelves, and fluctuating stock prices as we unpack the "Home is Where the Stock is" effect – a delightful dance between domestic handiwork and Wall Street wizardry.

When one contemplates the notion of tying together the seemingly unrelated concepts of home repair expenses and stock price movements, it may elicit a raised eyebrow or two. But fear not, skeptical scholars, for our findings are nothing short of sensational. We have diligently combed through a treasure trove of data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv) to unravel this enigmatic connection. Lo and behold, our analysis has unveiled a remarkable correlation coefficient of 0.9325046, with p < 0.01, spanning the time span from 2002 to 2022. It's a statistical tango that demands attention and prompts us to dig deeper into the fascinating interplay of economics, human behavior, and perhaps just a sprinkle of cosmic absurdity.

As we embark on this peculiar expedition, we encourage a suspension of disbelief and a willingness to explore the uncharted territories of economic whimsy. Yes, dear reader, you may find yourself pondering the possibility that tightening loose screws and fine-tuning investment strategies could be more intertwined than initially thought. So, fasten your seatbelts, double-check your home insurance policy, and get ready to navigate the unconventional terrain where property repairs and stock market fluctuations converge – because, as it turns out, perhaps it's not just the foundation of the house that requires shoring up during market tumult!


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Annual US household spending on home maintenance and Microsoft's stock price (MSFT). 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
The "Home is Where the Stock is" Effect: Understanding the Relationship Between Annual US Household Spending on Home Maintenance and Microsoft's Stock Price

[[ABSTRACT]]
In this paper, we investigate the often-overlooked connection between household spending on home maintenance and the stock price of a certain tech giant, Microsoft. While it may seem like a stretch to link fixing leaky faucets with the fluctuation of a company's stock price, our analysis reveals a surprising correlation. Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we found a correlation coefficient of 0.9325046 with p < 0.01 for the period from 2002 to 2022. Our findings suggest that there may be a previously unnoticed relationship between the two variables, prompting further inquiry into the economic and psychological factors at play. Join us as we delve into the wacky world of household maintenance and stock market dynamics, and ponder the possibility that perhaps it's not just the roof that needs fixing during turbulent market times!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Welcome, dear readers, to a curiously quirky investigation into the intriguing world of household spending on home maintenance and its peculiar connection to the stock price of none other than the tech behemoth, Microsoft. In this research paper, we invite you to join us on a journey through leaky roofs, wobbly shelves, and fluctuating stock prices as we unpack the "Home is Where the Stock is" effect – a delightful dance between domestic handiwork and Wall Street wizardry.
When one contemplates the notion of tying together the seemingly unrelated concepts of home repair expenses and stock price movements, it may elicit a raised eyebrow or two. But fear not, skeptical scholars, for our findings are nothing short of sensational. We have diligently combed through a treasure trove of data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv) to unravel this enigmatic connection. Lo and behold, our analysis has unveiled a remarkable correlation coefficient of 0.9325046, with p < 0.01, spanning the time span from 2002 to 2022. It's a statistical tango that demands attention and prompts us to dig deeper into the fascinating interplay of economics, human behavior, and perhaps just a sprinkle of cosmic absurdity.
As we embark on this peculiar expedition, we encourage a suspension of disbelief and a willingness to explore the uncharted territories of economic whimsy. Yes, dear reader, you may find yourself pondering the possibility that tightening loose screws and fine-tuning investment strategies could be more intertwined than initially thought. So, fasten your seatbelts, double-check your home insurance policy, and get ready to navigate the unconventional terrain where property repairs and stock market fluctuations converge – because, as it turns out, perhaps it's not just the foundation of the house that requires shoring up during market tumult!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Smith and Doe (2010) conducted a comprehensive study on household spending patterns and their impact on personal finance. They focused on the allocation of funds for home maintenance and how it relates to overall economic well-being. Their work provides a solid foundation for understanding the financial decisions individuals make with regards to maintaining their residences. However, what Smith and Doe failed to consider is the potential ripple effect of these home maintenance expenditures on the stock market.

Jones (2015) explored the psychological factors influencing stock price movements, delving into investor behavior and market sentiment. While his research sheds light on the human element in financial markets, it overlooks the peculiar influence that household maintenance expenses may wield on the stock price of a particular technology company, such as Microsoft. It's an uncharted territory that begs further exploration – for even the most astute investor might not realize that a leaky pipe could be impacting their portfolio.

Now, before we delve into the more offbeat contributions to the understanding of this quirky connection, let's take a moment to acknowledge some influential non-fiction works related to household maintenance and finance. "The Millionaire Next Door" by Thomas J. Stanley and William D. Danko offers valuable insights into the spending habits of the wealthy, although unfortunately not the correlation between their home repairs and tech stock performances. Similarly, "Freakonomics" by Steven D. Levitt and Stephen J. Dubner provides intriguing economic analyses, but the authors seem to have missed the memo on the potential co-movement of home maintenance costs and stock prices.

Moving into the realm of fiction that seems oddly applicable to our study, we can't help but draw tentative connections to "The Money Pit" by Grover M. Jones. While the titular residence in the movie may not be a direct proxy for the average American household, its trials and tribulations with home maintenance could metaphorically mirror the financial rollercoaster experienced by investors. And let's not forget the classic "The Hitchhiker's Guide to the Galaxy" by Douglas Adams – for in the zany universe of this literary work, one might serendipitously stumble upon insights into the enigmatic relationship between domestic upkeep and stock market shenanigans.

Finally, a nod to the lesser-known but surely pertinent board games that may have subliminally influenced our endeavor. "Monopoly" and "Life" both provide players with opportunities to consider financial decision-making, albeit in a less empirical manner. Perhaps hidden within the gameplay lies a parable about the interconnectedness of home maintenance and stock price movements – or maybe we're just grasping at straws in our quest for thematic relevance.

Stay tuned as we unravel the mystifying and comically surreal truths behind the "Home is Where the Stock is" effect, where the household and the stock market collide in a quixotic dance of data and domesticity.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Annual US household spending on home maintenance and Microsoft's stock price (MSFT). Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Labor Statistics and LSEG Analytics (Refinitiv) . You used data from 2002 to 2022

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
The "Home is Where the Stock is" Effect: Understanding the Relationship Between Annual US Household Spending on Home Maintenance and Microsoft's Stock Price

[[ABSTRACT]]
In this paper, we investigate the often-overlooked connection between household spending on home maintenance and the stock price of a certain tech giant, Microsoft. While it may seem like a stretch to link fixing leaky faucets with the fluctuation of a company's stock price, our analysis reveals a surprising correlation. Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we found a correlation coefficient of 0.9325046 with p < 0.01 for the period from 2002 to 2022. Our findings suggest that there may be a previously unnoticed relationship between the two variables, prompting further inquiry into the economic and psychological factors at play. Join us as we delve into the wacky world of household maintenance and stock market dynamics, and ponder the possibility that perhaps it's not just the roof that needs fixing during turbulent market times!

[[INTRODUCTION]]
Welcome, dear readers, to a curiously quirky investigation into the intriguing world of household spending on home maintenance and its peculiar connection to the stock price of none other than the tech behemoth, Microsoft. In this research paper, we invite you to join us on a journey through leaky roofs, wobbly shelves, and fluctuating stock prices as we unpack the "Home is Where the Stock is" effect – a delightful dance between domestic handiwork and Wall Street wizardry.
When one contemplates the notion of tying together the seemingly unrelated concepts of home repair expenses and stock price movements, it may elicit a raised eyebrow or two. But fear not, skeptical scholars, for our findings are nothing short of sensational. We have diligently combed through a treasure trove of data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv) to unravel this enigmatic connection. Lo and behold, our analysis has unveiled a remarkable correlation coefficient of 0.9325046, with p < 0.01, spanning the time span from 2002 to 2022. It's a statistical tango that demands attention and prompts us to dig deeper into the fascinating interplay of economics, human behavior, and perhaps just a sprinkle of cosmic absurdity.
As we embark on this peculiar expedition, we encourage a suspension of disbelief and a willingness to explore the uncharted territories of economic whimsy. Yes, dear reader, you may find yourself pondering the possibility that tightening loose screws and fine-tuning investment strategies could be more intertwined than initially thought. So, fasten your seatbelts, double-check your home insurance policy, and get ready to navigate the unconventional terrain where property repairs and stock market fluctuations converge – because, as it turns out, perhaps it's not just the foundation of the house that requires shoring up during market tumult!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

Ah, the moment we've all been waiting for - the nitty-gritty details of how we unraveled the tangled web of household spending and stock market shenanigans. It's time to peel back the layers of statistical sorcery and computational capers, and showcase the tools and techniques that led us to crack the cryptic code of the "Home is Where the Stock is" effect.

First and foremost, our ragtag team of research enthusiasts scoured the uncharted depths of the internet, armed with an insatiable thirst for data and a caffeinated fervor that would make even the most dedicated barista blush. We plundered the hallowed archives of the Bureau of Labor Statistics, embracing the chaos of Excel spreadsheets and the charm of pie charts, in our quest to unearth the intricate details of annual US household spending on home maintenance. You'd be amazed at the riveting tales that can be spun from tables of plumbing expenses and paint purchases - it's a veritable saga of domestic upkeep and fiscal fortitude.

But wait, there's more! In our pursuit of knowledge, we turned our eyes to the shimmering expanse of LSEG Analytics (Refinitiv), where the enchanting allure of financial data beckoned to us like a siren song. Armed with a dash of spreadsheet sorcery and a sprinkle of algorithmic alacrity, we delved into the labyrinthine labyrinth of numerical nuances, seeking to unravel the enigma of Microsoft's stock price over the years.

Now, for the uninitiated, you might be wondering, "But how did you actually analyze the data? Surely, there must be wizardry at play!" Fear not, dear reader, for our process was guided by the time-honored principles of statistical sages and the sage advice of number-crunching gurus. We employed the formidable forces of correlation analysis, unleashing the mighty powers of Pearson's correlation coefficient to unveil the hidden connections between our two seemingly disparate variables.

And lo and behold, the results did not disappoint! Our trusty statistical wizardry revealed a correlation coefficient of 0.9325046, with a p-value of less than 0.01, spanning the years from 2002 to 2022. It was a revelation that set our academic hearts aflutter and had us pondering the delightful dalliance of household maintenance and stock market prowess.

So there you have it, a rollercoaster ride through the whimsical world of household spending, stock market endeavors, and the statistical fortitude that brought them together. As we saunter forth into the realm of results and discussion, buckle up and brace yourselves for the wild and wonderful findings that wait just around the corner. And remember, dear reader, when it comes to the curious conundrums of home maintenance and stock prices, sometimes the most surprising connections are hiding in plain sight, just waiting to be revealed.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Annual US household spending on home maintenance and Microsoft's stock price (MSFT). Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Labor Statistics and LSEG Analytics (Refinitiv) .

For the time period 2002 to 2022, you found a correlation 0.9325046, r-squared of 0.8695649, 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]]
The "Home is Where the Stock is" Effect: Understanding the Relationship Between Annual US Household Spending on Home Maintenance and Microsoft's Stock Price

[[ABSTRACT]]
In this paper, we investigate the often-overlooked connection between household spending on home maintenance and the stock price of a certain tech giant, Microsoft. While it may seem like a stretch to link fixing leaky faucets with the fluctuation of a company's stock price, our analysis reveals a surprising correlation. Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we found a correlation coefficient of 0.9325046 with p < 0.01 for the period from 2002 to 2022. Our findings suggest that there may be a previously unnoticed relationship between the two variables, prompting further inquiry into the economic and psychological factors at play. Join us as we delve into the wacky world of household maintenance and stock market dynamics, and ponder the possibility that perhaps it's not just the roof that needs fixing during turbulent market times!

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Welcome, dear readers, to a curiously quirky investigation into the intriguing world of household spending on home maintenance and its peculiar connection to the stock price of none other than the tech behemoth, Microsoft. In this research paper, we invite you to join us on a journey through leaky roofs, wobbly shelves, and fluctuating stock prices as we unpack the "Home is Where the Stock is" effect – a delightful dance between domestic handiwork and Wall Street wizardry.
When one contemplates the notion of tying together the seemingly unrelated concepts of home repair expenses and stock price movements, it may elicit a raised eyebrow or two. But fear not, skeptical scholars, for our findings are nothing short of sensational. We have diligently combed through a treasure trove of data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv) to unravel this enigmatic connection. Lo and behold, our analysis has unveiled a remarkable correlation coefficient of 0.9325046, with p < 0.01, spanning the time span from 2002 to 2022. It's a statistical tango that demands attention and prompts us to dig deeper into the fascinating interplay of economics, human behavior, and perhaps just a sprinkle of cosmic absurdity.
As we embark on this peculiar expedition, we encourage a suspension of disbelief and a willingness to explore the uncharted territories of economic whimsy. Yes, dear reader, you may find yourself pondering the possibility that tightening loose screws and fine-tuning investment strategies could be more intertwined than initially thought. So, fasten your seatbelts, double-check your home insurance policy, and get ready to navigate the unconventional terrain where property repairs and stock market fluctuations converge – because, as it turns out, perhaps it's not just the foundation of the house that requires shoring up during market tumult!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Our analysis of the connection between annual US household spending on home maintenance and Microsoft's stock price from 2002 to 2022 has unearthed some jaw-dropping results. Picture this: a correlation coefficient of 0.9325046, an r-squared of 0.8695649, and a p-value of less than 0.01. It's like discovering a secret passage between the world of DIY home repairs and the bustling streets of Wall Street!

To visually encapsulate this mind-bending correlation, we bestow upon you Fig. 1 – a scatterplot that screams "kaleidoscopic conundrum" as you gaze upon the dance of data points that seem to mirror the intricate patterns of a patchwork quilt. It's a tapestry of financial intrigue woven from the threads of spick-and-span homes and booming stock prices.

Imagine, if you will, a scenario where every time a family decides to splurge on a new coat of paint for their living room, Microsoft's stock price does a little happy dance. And when the nation collectively embarks on a quest to fix rickety fences and creaky doors, lo and behold, the stock markets echo with a faint but discernible rumble. It's a quirky tale of two seemingly unrelated entities, joined at the hip in a way that leaves even the most astute economists scratching their heads in bewilderment.

In the realm of correlation coefficients, a value of 0.9325046 is akin to uncovering a pot of gold at the end of an obscure statistical rainbow. It's as if the digits on your calculator suddenly decided to boogie to the salsa beat of financial harmony.

But let's not get ahead of ourselves; this tantalizing find calls for a moment of reflection. Perhaps it's a nudge from the universe itself, urging us to explore the interconnectedness of the most unexpected bedfellows – from leaky faucets to stock market rockets. We stand at the precipice of a wondrous journey, ready to unravel the mysterious interplay of dollars spent on home repairs and the fluctuating fortunes of a tech titan.

So, dear readers, buckle up as we venture forth into the uncharted landscapes of quirky economic relationships, armed with nothing but a spirit of curiosity and a handful of statistical tools. It's a thrilling ride through a landscape where the mundane and the financially monumental collide, inspiring us to ponder the age-old question: is the key to a robust stock portfolio just a well-maintained roof away?


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Annual US household spending on home maintenance and Microsoft's stock price (MSFT). Make lots of jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
The "Home is Where the Stock is" Effect: Understanding the Relationship Between Annual US Household Spending on Home Maintenance and Microsoft's Stock Price

[[ABSTRACT]]
In this paper, we investigate the often-overlooked connection between household spending on home maintenance and the stock price of a certain tech giant, Microsoft. While it may seem like a stretch to link fixing leaky faucets with the fluctuation of a company's stock price, our analysis reveals a surprising correlation. Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we found a correlation coefficient of 0.9325046 with p < 0.01 for the period from 2002 to 2022. Our findings suggest that there may be a previously unnoticed relationship between the two variables, prompting further inquiry into the economic and psychological factors at play. Join us as we delve into the wacky world of household maintenance and stock market dynamics, and ponder the possibility that perhaps it's not just the roof that needs fixing during turbulent market times!

[[LITERATURE REVIEW]]
Smith and Doe (2010) conducted a comprehensive study on household spending patterns and their impact on personal finance. They focused on the allocation of funds for home maintenance and how it relates to overall economic well-being. Their work provides a solid foundation for understanding the financial decisions individuals make with regards to maintaining their residences. However, what Smith and Doe failed to consider is the potential ripple effect of these home maintenance expenditures on the stock market.
Jones (2015) explored the psychological factors influencing stock price movements, delving into investor behavior and market sentiment. While his research sheds light on the human element in financial markets, it overlooks the peculiar influence that household maintenance expenses may wield on the stock price of a particular technology company, such as Microsoft. It's an uncharted territory that begs further exploration – for even the most astute investor might not realize that a leaky pipe could be impacting their portfolio.
Now, before we delve into the more offbeat contributions to the understanding of this quirky connection, let's take a moment to acknowledge some influential non-fiction works related to household maintenance and finance. "The Millionaire Next Door" by Thomas J. Stanley and William D. Danko offers valuable insights into the spending habits of the wealthy, although unfortunately not the correlation between their home repairs and tech stock performances. Similarly, "Freakonomics" by Steven D. Levitt and Stephen J. Dubner provides intriguing economic analyses, but the authors seem to have missed the memo on the potential co-movement of home maintenance costs and stock prices.
Moving into the realm of fiction that seems oddly applicable to our study, we can't help but draw tentative connections to "The Money Pit" by Grover M. Jones. While the titular residence in the movie may not be a direct proxy for the average American household, its trials and tribulations with home maintenance could metaphorically mirror the financial rollercoaster experienced by investors. And let's not forget the classic "The Hitchhiker's Guide to the Galaxy" by Douglas Adams – for in the zany universe of this literary work, one might serendipitously stumble upon insights into the enigmatic relationship between domestic upkeep and stock market shenanigans.
Finally, a nod to the lesser-known but surely pertinent board games that may have subliminally influenced our endeavor. "Monopoly" and "Life" both provide players with opportunities to consider financial decision-making, albeit in a less empirical manner. Perhaps hidden within the gameplay lies a parable about the interconnectedness of home maintenance and stock price movements – or maybe we're just grasping at straws in our quest for thematic relevance.
Stay tuned as we unravel the mystifying and comically surreal truths behind the "Home is Where the Stock is" effect, where the household and the stock market collide in a quixotic dance of data and domesticity.

[[RESULTS]]
Our analysis of the connection between annual US household spending on home maintenance and Microsoft's stock price from 2002 to 2022 has unearthed some jaw-dropping results. Picture this: a correlation coefficient of 0.9325046, an r-squared of 0.8695649, and a p-value of less than 0.01. It's like discovering a secret passage between the world of DIY home repairs and the bustling streets of Wall Street!
To visually encapsulate this mind-bending correlation, we bestow upon you Fig. 1 – a scatterplot that screams "kaleidoscopic conundrum" as you gaze upon the dance of data points that seem to mirror the intricate patterns of a patchwork quilt. It's a tapestry of financial intrigue woven from the threads of spick-and-span homes and booming stock prices.
Imagine, if you will, a scenario where every time a family decides to splurge on a new coat of paint for their living room, Microsoft's stock price does a little happy dance. And when the nation collectively embarks on a quest to fix rickety fences and creaky doors, lo and behold, the stock markets echo with a faint but discernible rumble. It's a quirky tale of two seemingly unrelated entities, joined at the hip in a way that leaves even the most astute economists scratching their heads in bewilderment.
In the realm of correlation coefficients, a value of 0.9325046 is akin to uncovering a pot of gold at the end of an obscure statistical rainbow. It's as if the digits on your calculator suddenly decided to boogie to the salsa beat of financial harmony.
But let's not get ahead of ourselves; this tantalizing find calls for a moment of reflection. Perhaps it's a nudge from the universe itself, urging us to explore the interconnectedness of the most unexpected bedfellows – from leaky faucets to stock market rockets. We stand at the precipice of a wondrous journey, ready to unravel the mysterious interplay of dollars spent on home repairs and the fluctuating fortunes of a tech titan.
So, dear readers, buckle up as we venture forth into the uncharted landscapes of quirky economic relationships, armed with nothing but a spirit of curiosity and a handful of statistical tools. It's a thrilling ride through a landscape where the mundane and the financially monumental collide, inspiring us to ponder the age-old question: is the key to a robust stock portfolio just a well-maintained roof away?

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our findings have stirred up quite a tempest in a teapot, or should we say, in a cauldron of statistical enchantment? The correlation we uncovered between annual US household spending on home maintenance and Microsoft's stock price reignites the age-old debate over causation versus correlation. Could it be that a fresh coat of paint on the walls somehow triggers a surge in Microsoft's stock price, or are we just witnessing an elaborate waltz of random coincidence? Let's delve into this bewitching brew of data and ponder the implications of our startling discovery.

First and foremost, our results provide empirical support for the eccentric insights brought forth by Smith and Doe (2010) and Jones (2015), albeit in a manner that might have raised an eyebrow or two. While Smith and Doe's work underscored the financial implications of home maintenance, our findings take it a step further, revealing an unexpected linkage between these household expenditures and the stock performance of a specific company. It's as if we've stumbled upon a financial Aladdin's cave where the treasures of DIY wizardry and stock market sorcery converge in a mesmerizing display of numerical prowess.

Paying homage to the offbeat contributions in the literature review, one cannot ignore the serendipitous relevance of "The Money Pit" by Grover M. Jones. What was once seen as a lighthearted portrayal of homeownership tribulations emerges as a symbolic ode to the tumultuous journey of investment in the stock market. Indeed, the trials and tribulations of maintaining a household mirror the financial tumult experienced by investors, and perhaps there lies the secret sauce of our correlation – a fusion of the mundane and the momentous.

Furthermore, the unexpected nature of our findings invites a shift in perspective on the dynamics of market sentiment and psychological triggers. Jones (2015) may have overlooked the possibility of household maintenance costs subtly influencing investor behavior, unearthing a hidden tango between the comforts of home and the complexities of stock market dynamics.

Our study's results, represented acrobatically through statistical indicators, beckon us to question the very fabric of economic interconnectedness. The correlation coefficient of 0.9325046 is not just a numerical escapade; it's a beckoning finger pointing towards unexplored dimensions of economic symbiosis. It's as if we stumbled upon a unraveling mystery, a gravitational force pulling home maintenance and stock prices into an enigmatic embrace.

As we pause to ponder the implications of our curious findings, we can't help but wonder: Are we mere statistical fortune-tellers peering into the crystal ball of household expenditures and stock fortunes, or are we on the precipice of a paradigm-altering revelation? Our study opens the door to a whimsical world where leaky faucets and stock market rockets perform an unexpected dance of numerical harmony. And oh, what a merry dance it is.

So, fellow adventurous minds, let us embark on a journey of reflection and inquiry, armed with curiosity as our compass and statistical tools as our trusty mapmakers. The "Home is Where the Stock is" effect challenges the very essence of economic interconnectedness, beckoning us to decipher the riddles of financial serendipity with every stroke of the paintbrush and every twist of the stock ticker tape.

Stay tuned as we venture forth into the labyrinth of causation versus correlation in the wondrous world where the comforts of home and the enigma of stock market highs converge in a quirky symphony of financial revelation.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Annual US household spending on home maintenance and Microsoft's stock price (MSFT). Make lots of jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The "Home is Where the Stock is" Effect: Understanding the Relationship Between Annual US Household Spending on Home Maintenance and Microsoft's Stock Price

[[ABSTRACT]]
In this paper, we investigate the often-overlooked connection between household spending on home maintenance and the stock price of a certain tech giant, Microsoft. While it may seem like a stretch to link fixing leaky faucets with the fluctuation of a company's stock price, our analysis reveals a surprising correlation. Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we found a correlation coefficient of 0.9325046 with p < 0.01 for the period from 2002 to 2022. Our findings suggest that there may be a previously unnoticed relationship between the two variables, prompting further inquiry into the economic and psychological factors at play. Join us as we delve into the wacky world of household maintenance and stock market dynamics, and ponder the possibility that perhaps it's not just the roof that needs fixing during turbulent market times!

[[INTRDUCTION]]
Welcome, dear readers, to a curiously quirky investigation into the intriguing world of household spending on home maintenance and its peculiar connection to the stock price of none other than the tech behemoth, Microsoft. In this research paper, we invite you to join us on a journey through leaky roofs, wobbly shelves, and fluctuating stock prices as we unpack the "Home is Where the Stock is" effect – a delightful dance between domestic handiwork and Wall Street wizardry.
When one contemplates the notion of tying together the seemingly unrelated concepts of home repair expenses and stock price movements, it may elicit a raised eyebrow or two. But fear not, skeptical scholars, for our findings are nothing short of sensational. We have diligently combed through a treasure trove of data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv) to unravel this enigmatic connection. Lo and behold, our analysis has unveiled a remarkable correlation coefficient of 0.9325046, with p < 0.01, spanning the time span from 2002 to 2022. It's a statistical tango that demands attention and prompts us to dig deeper into the fascinating interplay of economics, human behavior, and perhaps just a sprinkle of cosmic absurdity.
As we embark on this peculiar expedition, we encourage a suspension of disbelief and a willingness to explore the uncharted territories of economic whimsy. Yes, dear reader, you may find yourself pondering the possibility that tightening loose screws and fine-tuning investment strategies could be more intertwined than initially thought. So, fasten your seatbelts, double-check your home insurance policy, and get ready to navigate the unconventional terrain where property repairs and stock market fluctuations converge – because, as it turns out, perhaps it's not just the foundation of the house that requires shoring up during market tumult!

[[RESULTS]]
Our analysis of the connection between annual US household spending on home maintenance and Microsoft's stock price from 2002 to 2022 has unearthed some jaw-dropping results. Picture this: a correlation coefficient of 0.9325046, an r-squared of 0.8695649, and a p-value of less than 0.01. It's like discovering a secret passage between the world of DIY home repairs and the bustling streets of Wall Street!
To visually encapsulate this mind-bending correlation, we bestow upon you Fig. 1 – a scatterplot that screams "kaleidoscopic conundrum" as you gaze upon the dance of data points that seem to mirror the intricate patterns of a patchwork quilt. It's a tapestry of financial intrigue woven from the threads of spick-and-span homes and booming stock prices.
Imagine, if you will, a scenario where every time a family decides to splurge on a new coat of paint for their living room, Microsoft's stock price does a little happy dance. And when the nation collectively embarks on a quest to fix rickety fences and creaky doors, lo and behold, the stock markets echo with a faint but discernible rumble. It's a quirky tale of two seemingly unrelated entities, joined at the hip in a way that leaves even the most astute economists scratching their heads in bewilderment.
In the realm of correlation coefficients, a value of 0.9325046 is akin to uncovering a pot of gold at the end of an obscure statistical rainbow. It's as if the digits on your calculator suddenly decided to boogie to the salsa beat of financial harmony.
But let's not get ahead of ourselves; this tantalizing find calls for a moment of reflection. Perhaps it's a nudge from the universe itself, urging us to explore the interconnectedness of the most unexpected bedfellows – from leaky faucets to stock market rockets. We stand at the precipice of a wondrous journey, ready to unravel the mysterious interplay of dollars spent on home repairs and the fluctuating fortunes of a tech titan.
So, dear readers, buckle up as we venture forth into the uncharted landscapes of quirky economic relationships, armed with nothing but a spirit of curiosity and a handful of statistical tools. It's a thrilling ride through a landscape where the mundane and the financially monumental collide, inspiring us to ponder the age-old question: is the key to a robust stock portfolio just a well-maintained roof away?

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research unearthed a correlation coefficient so astronomical, it's like discovering a pot of gold at the end of an obscure statistical rainbow. Who knew that tightening loose screws and sprucing up the homestead could potentially send the stock market into a tizzy? It's a delightfully dizzying waltz between home maintenance and Microsoft's stock price, a tale that leaves even the most astute economists scratching their heads in sheer bewilderment. Our findings encourage us to ponder the notion that perhaps a well-maintained abode holds the elusive key to a robust stock portfolio.

In the vibrant tapestry of financial intrigue, our paper presents a kaleidoscopic conundrum, inviting scholars to question the peculiar partnership between the domestic sphere and Wall Street. But fear not, dear reader, for this paper serves as the pièce de résistance in this particular peculiar teatime conversation. It's time to put a bow on this delightful discourse and assert that further research in this domain may be akin to flogging a thoroughly painted horse – needless and likely to elicit a few puzzled gazes. Let's leave this capricious correlation to rest and turn our scholarly gaze toward more conventional economic phenomena. After all, even the quirkiest discoveries need an eternal weekend from relentless inquiry!


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 The Home is Where the Stock is Effect: Understanding the Relationship Between Annual US Household Spending on Home Maintenance and Microsoft's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Economic Research


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 The Home is Where the Stock is Effect: Understanding the Relationship Between Annual US Household Spending on Home Maintenance and Microsoft's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Domestic Economics and Financial Analysis


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 The Home is Where the Stock is Effect: Understanding the Relationship Between Annual US Household Spending on Home Maintenance and Microsoft's Stock Price with an abstract of In this paper, we investigate the often-overlooked connection between household spending on home maintenance and the stock price of a certain tech giant, Microsoft. While it may seem like a stretch to link fixing leaky faucets with the fluctuation of a company's stock price, our analysis reveals a surprising correlation. Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we found a correlation coefficient of 0.9325046 with p < 0.01 for the period from 2002 to 2022. Our findings suggest that there may be a previously unnoticed relationship between the two variables, prompting further inquiry into the economic and psychological factors at play. Join us as we delve into the wacky world of household maintenance and stock market dynamics, and ponder the possibility that perhaps it's not just the roof that needs fixing during turbulent market times!

ChatGPT:

"household spending, home maintenance, stock price correlation, tech giant, Microsoft, annual spending, household maintenance, stock market dynamics, correlation coefficient, economic factors, psychological factors, Bureau of Labor Statistics, LSEG Analytics, Refinitiv, 2002-2022"

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



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Data details

Annual US household spending on home maintenance
Detailed data title: Average annual household spend on home maintenance
Source: Bureau of Labor Statistics
See what else correlates with Annual US household spending on home maintenance

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

See what else correlates with Microsoft's stock price (MSFT)

Correlation r = 0.9325046 (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 = 0.8695649 (Coefficient of determination)
This means 87% of the change in the one variable (i.e., Microsoft's stock price (MSFT)) is predictable based on the change in the other (i.e., Annual US household spending on home maintenance) over the 21 years from 2002 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 7.6E-10. 0.0000000007592677545545262000
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 0.93 in 7.6E-8% of random cases. Said differently, if you correlated 1,317,058,434 random variables You don't actually need 1 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

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

[ 0.84, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!


All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
200220032004200520062007200820092010201120122013201420152016201720182019202020212022
Annual US household spending on home maintenance (Household spend)960965997110111151131117611381112112011531182129314381437161617031879215823352559
Microsoft's stock price (MSFT) (Stock price)33.3326.1527.5826.826.2529.9135.7919.5330.6228.0526.5527.2537.3546.6654.3262.7986.1399.55158.78222.53335.35




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.
  4. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.
  5. Outlandish outliers: There are "outliers" in this data. In concept, "outlier" just means "way different than the rest of your dataset." When calculating a correlation like this, they are particularly impactful because a single outlier can substantially increase your correlation.

    For the purposes of this project, I counted a point as an outlier if it the residual was two standard deviations from the mean.

    (This bullet point only shows up in the details page on charts that do, in fact, have outliers.)
    They stand out on the scatterplot above: notice the dots that are far away from any other dots. I intentionally mishandeled outliers, which makes the correlation look extra strong.




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([960,965,997,1101,1115,1131,1176,1138,1112,1120,1153,1182,1293,1438,1437,1616,1703,1879,2158,2335,2559,])
array_2 = np.array([33.33,26.15,27.58,26.8,26.25,29.91,35.79,19.53,30.62,28.05,26.55,27.25,37.35,46.66,54.32,62.79,86.13,99.55,158.78,222.53,335.35,])
array_1_name = "Annual US household spending on home maintenance"
array_2_name = "Microsoft's stock price (MSFT)"

# 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: 3756 · Black Variable ID: 19906 · Red Variable ID: 1541
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