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Spurious correlation #3,486 · 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 nonalcoholic beverages and the second variable is DexCom's stock price (DXCM).  The chart goes from 2006 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As households guzzled more nonalcoholic beverages, they unknowingly created a surge in demand for DexCom's continuous glucose monitoring systems. It turns out, the constant sipping on sugary drinks led to more people developing a sweet tooth for DexCom's innovative products, leading to a spike in the company's stock price. It's a fizz-ical manifestation of the beverage-spending boomerang effect!

Model: dalle-3
Prompt: Sure! Here's a refined prompt for DALLE-3 to generate an image as per your request: [An image that resembles a scene from a beloved animated feature film] Depict a vibrant kitchen scene where a family is gathered around a table. On the table, there's a colorful grocery bill for nonalcoholic beverages, prominently showing a significant increase. Nearby, a computer screen displays DexCom's stock price chart, portraying a sharp upward trend. The family members are depicted as lively and rejuvenated, engaging in various activities, visibly fueled by the energy from consuming the beverages. The scene is filled with warmth and dynamism, capturing the joyous atmosphere of the family interacting in the bustling kitchen. The illustration should capture the heartwarming essence of a Pixar movie while cleverly incorporating the elements of the grocery bill, stock price chart, and the family's energetic activities. 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 nonalcoholic beverages and DexCom's stock price (DXCM). 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: Whimsical illustration An image that looks like it is a scene from a Pixar movie a meme Voxel art Oragami
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 Annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM), in the following situation: Because as American households spent more on nonalcoholic beverages, they were able to stay more alert and focused throughout the day. This improved cognitive function led to increased productivity, resulting in higher disposable income and therefore more investment in companies like DexCom, which in turn drove up the stock price. In essence, a well-caffeinated population led to a stock boost for DexCom.. Keep the description simple.
ChatGPT: In a bustling kitchen, a family's grocery bill for nonalcoholic beverages is displayed on the table, showing a significant increase. Meanwhile, on a nearby computer screen, DexCom's stock price chart shows a sharp upward trend, indicating a substantial rise. The family members, looking rejuvenated and lively, are happily engaging in various activities, fueled by the energy from consuming the beverages.

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: In a bustling kitchen, a family's grocery bill for nonalcoholic beverages is displayed on the table, showing a significant increase. Meanwhile, on a nearby computer screen, DexCom's stock price chart shows a sharp upward trend, indicating a substantial rise. The family members, looking rejuvenated and lively, are happily engaging in various activities, fueled by the energy from consuming the beverages. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Sure! Here's a refined prompt for DALLE-3 to generate an image as per your request: [An image that resembles a scene from a beloved animated feature film] Depict a vibrant kitchen scene where a family is gathered around a table. On the table, there's a colorful grocery bill for nonalcoholic beverages, prominently showing a significant increase. Nearby, a computer screen displays DexCom's stock price chart, portraying a sharp upward trend. The family members are depicted as lively and rejuvenated, engaging in various activities, visibly fueled by the energy from consuming the beverages. The scene is filled with warmth and dynamism, capturing the joyous atmosphere of the family interacting in the bustling kitchen. The illustration should capture the heartwarming essence of a Pixar movie while cleverly incorporating the elements of the grocery bill, stock price chart, and the family's energetic activities.

*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 nonalcoholic beverages caused DexCom's stock price (DXCM) to increase.

AI academic paper

(Because p < 0.01)
Bubbly Beverages and Biometric Bourse: A Bizarre and Bodacious Examination of Annual US Household Spending on Nonalcoholic Beverages and DexCom's Stock Price

The Journal of Quirky Quantitative 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 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 Annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM). Make lots of jokes, goofy observations, and puns.

Make the title an alliteration.

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 0.9301610 and p < 0.01 for 2006 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]]
Bubbly Beverages and Biometric Bourse: A Bizarre and Bodacious Examination of Annual US Household Spending on Nonalcoholic Beverages and DexCom's Stock Price

[[ABSTRACT]]
This paper presents a whimsical and wacky investigation into the relationship between the annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team embarked on a lighthearted journey to uncover the link between America's thirst for beverages that don't intoxicate and the whims and fancies of the stock market. Through rigorous statistical analysis, we discovered a staggering correlation coefficient of 0.9301610 and a p-value less than 0.01 for the time period spanning from 2006 to 2022. Our findings suggest that the ebb and flow of household beverage expenditures may indeed bear an uncanny relationship with DexCom's stock price, supporting the notion that when it comes to market trends, even the tiniest bubbles can make a big splash. We hope this study brings a dose of fizz and fun to the academic discourse on economic trends and stock market influences.


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 Annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM). Make lots of 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]]
Bubbly Beverages and Biometric Bourse: A Bizarre and Bodacious Examination of Annual US Household Spending on Nonalcoholic Beverages and DexCom's Stock Price

[[ABSTRACT]]
This paper presents a whimsical and wacky investigation into the relationship between the annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team embarked on a lighthearted journey to uncover the link between America's thirst for beverages that don't intoxicate and the whims and fancies of the stock market. Through rigorous statistical analysis, we discovered a staggering correlation coefficient of 0.9301610 and a p-value less than 0.01 for the time period spanning from 2006 to 2022. Our findings suggest that the ebb and flow of household beverage expenditures may indeed bear an uncanny relationship with DexCom's stock price, supporting the notion that when it comes to market trends, even the tiniest bubbles can make a big splash. We hope this study brings a dose of fizz and fun to the academic discourse on economic trends and stock market influences.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The intersection of consumer behavior and stock market dynamics has long intrigued researchers, investors, and anyone with a penchant for peering into the peculiarities of market trends. In this zany and zesty study, we set out to explore the curious connection between annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). We embarked on this bizarre and bodacious adventure with an ardent desire to infuse some levity and lightheartedness into the often stern and stoic world of economic analysis.

The impetus for this peculiar inquiry stemmed from the observation that in the landscape of consumer spending, nonalcoholic beverages occupy a peculiar and prominent place. From the effervescent allure of carbonated concoctions to the artful sophistication of designer coffees, the array of nonalcoholic libations available to the American consumer is nothing short of staggering. Yet, amidst this shimmering sea of sippable selections, one cannot help but wonder: could the ebb and flow of household expenditure on nonalcoholic beverages harbor some clandestine influence on the capricious undulations of stock prices?

At the heart of our curious caper lies the enigmatic stock price of DexCom (DXCM), a company renowned for its innovative biometric technologies. As the astute investor is well aware, the stock market is an arena where fortunes are won and lost with the whimsy of a carnival game. Against this backdrop, the notion of untangling the relationship between household beverage spending and stock prices might seem as lighthearted as a clown juggling watermelons – and yet, as we shall see, there may be more at play than meets the eye.

So, with a twinkle in our eyes and a stratagem in our statistical arsenal, we dove headfirst into the tumultuous sea of data, armed with a fervent hope that our findings would not only entertain but also enlighten. Through this unorthodox study, we endeavor to add a touch of fizz and fun to the academically austere discourse on economic trends and stock market influences. Now, let us embark on this whimsical whirlwind of wacky correlations and buoyant bubbles, and see what unexpected delights may effervesce from the depths of our analysis. As we shall soon discover, in the delightful dance of consumer expenditures and stock market sway, even the most unexpected connections may indeed hold water - or perhaps, in the case of nonalcoholic beverages, a refreshing splash of sparkling surprise.


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 Annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM). Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then you might move on to cartoons and children's shows that you watched for research.

Here is the title and abstract of the paper:
[[TITLE]]
Bubbly Beverages and Biometric Bourse: A Bizarre and Bodacious Examination of Annual US Household Spending on Nonalcoholic Beverages and DexCom's Stock Price

[[ABSTRACT]]
This paper presents a whimsical and wacky investigation into the relationship between the annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team embarked on a lighthearted journey to uncover the link between America's thirst for beverages that don't intoxicate and the whims and fancies of the stock market. Through rigorous statistical analysis, we discovered a staggering correlation coefficient of 0.9301610 and a p-value less than 0.01 for the time period spanning from 2006 to 2022. Our findings suggest that the ebb and flow of household beverage expenditures may indeed bear an uncanny relationship with DexCom's stock price, supporting the notion that when it comes to market trends, even the tiniest bubbles can make a big splash. We hope this study brings a dose of fizz and fun to the academic discourse on economic trends and stock market influences.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of consumer behavior and stock market dynamics has long intrigued researchers, investors, and anyone with a penchant for peering into the peculiarities of market trends. In this zany and zesty study, we set out to explore the curious connection between annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). We embarked on this bizarre and bodacious adventure with an ardent desire to infuse some levity and lightheartedness into the often stern and stoic world of economic analysis.
The impetus for this peculiar inquiry stemmed from the observation that in the landscape of consumer spending, nonalcoholic beverages occupy a peculiar and prominent place. From the effervescent allure of carbonated concoctions to the artful sophistication of designer coffees, the array of nonalcoholic libations available to the American consumer is nothing short of staggering. Yet, amidst this shimmering sea of sippable selections, one cannot help but wonder: could the ebb and flow of household expenditure on nonalcoholic beverages harbor some clandestine influence on the capricious undulations of stock prices?
At the heart of our curious caper lies the enigmatic stock price of DexCom (DXCM), a company renowned for its innovative biometric technologies. As the astute investor is well aware, the stock market is an arena where fortunes are won and lost with the whimsy of a carnival game. Against this backdrop, the notion of untangling the relationship between household beverage spending and stock prices might seem as lighthearted as a clown juggling watermelons – and yet, as we shall see, there may be more at play than meets the eye.
So, with a twinkle in our eyes and a stratagem in our statistical arsenal, we dove headfirst into the tumultuous sea of data, armed with a fervent hope that our findings would not only entertain but also enlighten. Through this unorthodox study, we endeavor to add a touch of fizz and fun to the academically austere discourse on economic trends and stock market influences. Now, let us embark on this whimsical whirlwind of wacky correlations and buoyant bubbles, and see what unexpected delights may effervesce from the depths of our analysis. As we shall soon discover, in the delightful dance of consumer expenditures and stock market sway, even the most unexpected connections may indeed hold water - or perhaps, in the case of nonalcoholic beverages, a refreshing splash of sparkling surprise.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The literature on the connection between annual US household spending on nonalcoholic beverages and stock market movements is as varied and sparkling as a freshly poured glass of soda. Smith (2010) meticulously analyzed consumer expenditure patterns and their potential impact on market trends, laying the groundwork for our own quirky investigation. Building upon this foundation, Doe (2015) delved into the intricate web of consumer behavior and its ripple effect on stock prices, paving the way for our offbeat exploration into the world of nonalcoholic beverages and market whimsies.

Turning the pages from the serious to the sensational, we saunter into the realm of popular non-fiction works that provide both insight and amusement. In "The Economics of Coffee," the authors tantalizingly traverse the landscape of coffee consumption, awakening our senses to the multifaceted world of nonalcoholic libations. Meanwhile, "The Psychology of Thirst" immerses readers in the enthralling psychology behind beverage preferences, offering a refreshing perspective on the intersection of human desires and consumer trends.

Venturing further into the land of literature, we encounter fictional works that, although not directly related to economic analysis, nevertheless titillate the imagination with their thematic resonance. In "The Brewmaster's Bounty," a whimsical tale of a mystical brewery entices us with its frothy fables, weaving a captivating narrative around the enchanting allure of nonalcoholic drinks. Concurrently, "The Tea Leaf Mysteries" beckons with its aromatic intrigue, inspiring us to ponder the enigmatic allure of nonalcoholic elixirs from a different angle altogether.

As if the literary world could not sate our thirst for unconventional inspiration, we turned to the realm of animation and children’s programming for a splash of levity in our research pursuits. From the fizzy antics of animated soda cans in "The Quirky Adventures of Fizzy and Friends" to the whimsical jingles of a cartoony lemonade stand in "Sippin' Shenanigans," we immersed ourselves in a bubbly barrage of visual stimuli that sparked our creative ruminations and incited giggles amid the scholarly seriousness.

In synthesizing this eclectic array of sources, we aim to infuse our own study with a lighthearted spirit that captures the essence of our peculiar pursuit, bridging the realms of academia and amusement in a delightful dance of analytical insight and beguiling banter. With a wink and a nod to the unconventional, our literature review sets the stage for the eccentric investigation that follows, inviting readers to partake in the mirthful medley of curious correlations and anecdotal absurdities that await.


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 Annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM). Make lots of 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 Bureau of Labor Statistics and LSEG Analytics (Refinitiv) . You used data from 2006 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]]
Bubbly Beverages and Biometric Bourse: A Bizarre and Bodacious Examination of Annual US Household Spending on Nonalcoholic Beverages and DexCom's Stock Price

[[ABSTRACT]]
This paper presents a whimsical and wacky investigation into the relationship between the annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team embarked on a lighthearted journey to uncover the link between America's thirst for beverages that don't intoxicate and the whims and fancies of the stock market. Through rigorous statistical analysis, we discovered a staggering correlation coefficient of 0.9301610 and a p-value less than 0.01 for the time period spanning from 2006 to 2022. Our findings suggest that the ebb and flow of household beverage expenditures may indeed bear an uncanny relationship with DexCom's stock price, supporting the notion that when it comes to market trends, even the tiniest bubbles can make a big splash. We hope this study brings a dose of fizz and fun to the academic discourse on economic trends and stock market influences.

[[INTRODUCTION]]
The intersection of consumer behavior and stock market dynamics has long intrigued researchers, investors, and anyone with a penchant for peering into the peculiarities of market trends. In this zany and zesty study, we set out to explore the curious connection between annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). We embarked on this bizarre and bodacious adventure with an ardent desire to infuse some levity and lightheartedness into the often stern and stoic world of economic analysis.
The impetus for this peculiar inquiry stemmed from the observation that in the landscape of consumer spending, nonalcoholic beverages occupy a peculiar and prominent place. From the effervescent allure of carbonated concoctions to the artful sophistication of designer coffees, the array of nonalcoholic libations available to the American consumer is nothing short of staggering. Yet, amidst this shimmering sea of sippable selections, one cannot help but wonder: could the ebb and flow of household expenditure on nonalcoholic beverages harbor some clandestine influence on the capricious undulations of stock prices?
At the heart of our curious caper lies the enigmatic stock price of DexCom (DXCM), a company renowned for its innovative biometric technologies. As the astute investor is well aware, the stock market is an arena where fortunes are won and lost with the whimsy of a carnival game. Against this backdrop, the notion of untangling the relationship between household beverage spending and stock prices might seem as lighthearted as a clown juggling watermelons – and yet, as we shall see, there may be more at play than meets the eye.
So, with a twinkle in our eyes and a stratagem in our statistical arsenal, we dove headfirst into the tumultuous sea of data, armed with a fervent hope that our findings would not only entertain but also enlighten. Through this unorthodox study, we endeavor to add a touch of fizz and fun to the academically austere discourse on economic trends and stock market influences. Now, let us embark on this whimsical whirlwind of wacky correlations and buoyant bubbles, and see what unexpected delights may effervesce from the depths of our analysis. As we shall soon discover, in the delightful dance of consumer expenditures and stock market sway, even the most unexpected connections may indeed hold water - or perhaps, in the case of nonalcoholic beverages, a refreshing splash of sparkling surprise.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To commence this mirthful investigation into the delightfully odd connection between annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM), our research team ventured forth with an ardent zeal mixed with a dash of whimsy and a sprinkle of statistical rigor. We waded through the vast expanse of data available from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), akin to intrepid explorers navigating a jungle of numbers and trends, armed with a trusty keyboard and an unwavering commitment to maintain the sanctity of our statistical dance.

The primary data source for annual US household spending on nonalcoholic beverages was the Bureau of Labor Statistics, offering a smorgasbord of expenditure categories that encompassed the gamut of bottled bliss – from the effervescent escapades of carbonated quenchers to the tranquil tribulations of tea and coffee. With meticulous precision, we curated data spanning the years 2006 to 2022, capturing the frolicking fluctuations of consumer whims and tendencies in their quest to satiate their thirst with nary an intoxicating tipple in sight.

On the parallel promenade of stock prices, we danced with the data supplied by LSEG Analytics (Refinitiv), tracing the capricious meanderings of DexCom's (DXCM) stock price from 2006 to 2022 with the dexterity of a watchful circus performer on a tightrope. We treaded through the labyrinthine maze of market machinations, deftly sifting through the chimes and clangs of the stock ticker tape to distill the essence of DexCom's stock price movements into our data repository.

Having harvested this bounty of data from the digital vineyards and market pastures, we embarked on a valiant voyage to meld these distinct domains into a harmonious synthesis of market merriment and beverage banter. Our statistical arsenal included the venerable tools of correlation analysis, culminating in the earnest computation of correlation coefficients and p-values to tease out the intriguing relationship between annual US household spending on nonalcoholic beverages and DexCom's stock price. The mathematical machinery of regression analysis also played a pivotal role, dissecting the dancing dynamics of these peculiar partners in the economic tango with the precision of a maestro orchestrating a symphony of statistical salvation.

It is with the buoyancy of bubbly beverages and the gravity of stock market gravitas that we spun this curious yarn of correlation and causation, mindful of the whimsical nature of our endeavor even as we held fast to the pillars of scholarly inquiry. And so, armed with data aplenty and statistical bravado, we delved into the heart of this beguiling conundrum, seeking to shed light on the perplexing perturbations of nonalcoholic libations and stock price shenanigans.

In the ensuing sections, we shall peel back the layers of our findings, buoyed by the certitude that even in the seemingly whimsical intersection of consumer delights and market caprices, the discerning eye of statistical scrutiny may uncover gleaming nuggets of insight. Let us tiptoe forth into the realm of results, where the bubbles of beverage spending and the booms of stock prices do an unexpected yet delightful dance of correlation.


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 Annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM). Make lots of 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 Bureau of Labor Statistics and LSEG Analytics (Refinitiv) .

For the time period 2006 to 2022, you found a correlation 0.9301610, r-squared of 0.8651995, 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]]
Bubbly Beverages and Biometric Bourse: A Bizarre and Bodacious Examination of Annual US Household Spending on Nonalcoholic Beverages and DexCom's Stock Price

[[ABSTRACT]]
This paper presents a whimsical and wacky investigation into the relationship between the annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team embarked on a lighthearted journey to uncover the link between America's thirst for beverages that don't intoxicate and the whims and fancies of the stock market. Through rigorous statistical analysis, we discovered a staggering correlation coefficient of 0.9301610 and a p-value less than 0.01 for the time period spanning from 2006 to 2022. Our findings suggest that the ebb and flow of household beverage expenditures may indeed bear an uncanny relationship with DexCom's stock price, supporting the notion that when it comes to market trends, even the tiniest bubbles can make a big splash. We hope this study brings a dose of fizz and fun to the academic discourse on economic trends and stock market influences.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intersection of consumer behavior and stock market dynamics has long intrigued researchers, investors, and anyone with a penchant for peering into the peculiarities of market trends. In this zany and zesty study, we set out to explore the curious connection between annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). We embarked on this bizarre and bodacious adventure with an ardent desire to infuse some levity and lightheartedness into the often stern and stoic world of economic analysis.
The impetus for this peculiar inquiry stemmed from the observation that in the landscape of consumer spending, nonalcoholic beverages occupy a peculiar and prominent place. From the effervescent allure of carbonated concoctions to the artful sophistication of designer coffees, the array of nonalcoholic libations available to the American consumer is nothing short of staggering. Yet, amidst this shimmering sea of sippable selections, one cannot help but wonder: could the ebb and flow of household expenditure on nonalcoholic beverages harbor some clandestine influence on the capricious undulations of stock prices?
At the heart of our curious caper lies the enigmatic stock price of DexCom (DXCM), a company renowned for its innovative biometric technologies. As the astute investor is well aware, the stock market is an arena where fortunes are won and lost with the whimsy of a carnival game. Against this backdrop, the notion of untangling the relationship between household beverage spending and stock prices might seem as lighthearted as a clown juggling watermelons – and yet, as we shall see, there may be more at play than meets the eye.
So, with a twinkle in our eyes and a stratagem in our statistical arsenal, we dove headfirst into the tumultuous sea of data, armed with a fervent hope that our findings would not only entertain but also enlighten. Through this unorthodox study, we endeavor to add a touch of fizz and fun to the academically austere discourse on economic trends and stock market influences. Now, let us embark on this whimsical whirlwind of wacky correlations and buoyant bubbles, and see what unexpected delights may effervesce from the depths of our analysis. As we shall soon discover, in the delightful dance of consumer expenditures and stock market sway, even the most unexpected connections may indeed hold water - or perhaps, in the case of nonalcoholic beverages, a refreshing splash of sparkling surprise.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

In our zany and zesty quest to uncover the enthralling interplay between annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM), we have stumbled upon a correlation coefficient that would make any statistician do a double take. Drumroll, please! We found a staggering correlation of 0.9301610, indicating an extraordinarily strong positive relationship between these seemingly unrelated variables. It seems that the fizz in household beverage spending may indeed hold more market sway than we ever anticipated!

Our intrepid research team also calculated an r-squared value of 0.8651995, suggesting that a whopping 86.52% of the variance in DexCom's stock price can be explained by the annual US household spending on nonalcoholic beverages. Talk about a statistical quirk! Additionally, with a p-value less than 0.01, we can confidently declare that this relationship is not just a statistical fluke. It seems that the connection between America's thirst for nonalcoholic quenchers and the gyrations of DexCom's stock price is no laughing matter - well, maybe just a little bit!

To visually capture this astonishing correlation, we present in Fig. 1 a scatterplot illustrating the robust relationship between annual US household spending on nonalcoholic beverages and DexCom's stock price. Behold the whimsical wonder of statistical synergy!

The findings of this peculiar investigation add a splash of levity to the often parched and pedestrian discussions of market influences. It appears that in the convoluted world of economic trends and stock market caprices, even the most unassuming of bubbles can buoyantly influence the movements of the financial tides. We hope these results bring a refreshing dose of irreverent insight into the intriguing dynamics of consumer spending and stock market fluctuations.


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 Annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM). Make lots of 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]]
Bubbly Beverages and Biometric Bourse: A Bizarre and Bodacious Examination of Annual US Household Spending on Nonalcoholic Beverages and DexCom's Stock Price

[[ABSTRACT]]
This paper presents a whimsical and wacky investigation into the relationship between the annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team embarked on a lighthearted journey to uncover the link between America's thirst for beverages that don't intoxicate and the whims and fancies of the stock market. Through rigorous statistical analysis, we discovered a staggering correlation coefficient of 0.9301610 and a p-value less than 0.01 for the time period spanning from 2006 to 2022. Our findings suggest that the ebb and flow of household beverage expenditures may indeed bear an uncanny relationship with DexCom's stock price, supporting the notion that when it comes to market trends, even the tiniest bubbles can make a big splash. We hope this study brings a dose of fizz and fun to the academic discourse on economic trends and stock market influences.

[[LITERATURE REVIEW]]
The literature on the connection between annual US household spending on nonalcoholic beverages and stock market movements is as varied and sparkling as a freshly poured glass of soda. Smith (2010) meticulously analyzed consumer expenditure patterns and their potential impact on market trends, laying the groundwork for our own quirky investigation. Building upon this foundation, Doe (2015) delved into the intricate web of consumer behavior and its ripple effect on stock prices, paving the way for our offbeat exploration into the world of nonalcoholic beverages and market whimsies.
Turning the pages from the serious to the sensational, we saunter into the realm of popular non-fiction works that provide both insight and amusement. In "The Economics of Coffee," the authors tantalizingly traverse the landscape of coffee consumption, awakening our senses to the multifaceted world of nonalcoholic libations. Meanwhile, "The Psychology of Thirst" immerses readers in the enthralling psychology behind beverage preferences, offering a refreshing perspective on the intersection of human desires and consumer trends.
Venturing further into the land of literature, we encounter fictional works that, although not directly related to economic analysis, nevertheless titillate the imagination with their thematic resonance. In "The Brewmaster's Bounty," a whimsical tale of a mystical brewery entices us with its frothy fables, weaving a captivating narrative around the enchanting allure of nonalcoholic drinks. Concurrently, "The Tea Leaf Mysteries" beckons with its aromatic intrigue, inspiring us to ponder the enigmatic allure of nonalcoholic elixirs from a different angle altogether.
As if the literary world could not sate our thirst for unconventional inspiration, we turned to the realm of animation and children’s programming for a splash of levity in our research pursuits. From the fizzy antics of animated soda cans in "The Quirky Adventures of Fizzy and Friends" to the whimsical jingles of a cartoony lemonade stand in "Sippin' Shenanigans," we immersed ourselves in a bubbly barrage of visual stimuli that sparked our creative ruminations and incited giggles amid the scholarly seriousness.
In synthesizing this eclectic array of sources, we aim to infuse our own study with a lighthearted spirit that captures the essence of our peculiar pursuit, bridging the realms of academia and amusement in a delightful dance of analytical insight and beguiling banter. With a wink and a nod to the unconventional, our literature review sets the stage for the eccentric investigation that follows, inviting readers to partake in the mirthful medley of curious correlations and anecdotal absurdities that await.

[[RESULTS]]
In our zany and zesty quest to uncover the enthralling interplay between annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM), we have stumbled upon a correlation coefficient that would make any statistician do a double take. Drumroll, please! We found a staggering correlation of 0.9301610, indicating an extraordinarily strong positive relationship between these seemingly unrelated variables. It seems that the fizz in household beverage spending may indeed hold more market sway than we ever anticipated!
Our intrepid research team also calculated an r-squared value of 0.8651995, suggesting that a whopping 86.52% of the variance in DexCom's stock price can be explained by the annual US household spending on nonalcoholic beverages. Talk about a statistical quirk! Additionally, with a p-value less than 0.01, we can confidently declare that this relationship is not just a statistical fluke. It seems that the connection between America's thirst for nonalcoholic quenchers and the gyrations of DexCom's stock price is no laughing matter - well, maybe just a little bit!
To visually capture this astonishing correlation, we present in Fig. 1 a scatterplot illustrating the robust relationship between annual US household spending on nonalcoholic beverages and DexCom's stock price. Behold the whimsical wonder of statistical synergy!
The findings of this peculiar investigation add a splash of levity to the often parched and pedestrian discussions of market influences. It appears that in the convoluted world of economic trends and stock market caprices, even the most unassuming of bubbles can buoyantly influence the movements of the financial tides. We hope these results bring a refreshing dose of irreverent insight into the intriguing dynamics of consumer spending and stock market fluctuations.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our findings have unmasked a flavor-packed correlation between annual US household spending on nonalcoholic beverages and DexCom's stock price, leaving us with a taste of statistical euphoria. The remarkable correlation coefficient of 0.9301610 and the r-squared value of 0.8651995 whet our appetite for uncovering the quenching quirk of this relationship. These results not only corroborate previous scholarly brews on the subject, but they also add a zesty twist to the ever-bubbling discourse on economic influences.

Returning to the whims and wonders of the literature review, our discovery aligns with Smith's (2010) meticulous investigation and Doe's (2015) contemplation of consumer behavior's ripple effect on stock prices. Who would have thought that the wibbly-wobbly world of household beverage spending could have such a pronounced impact on the stock market's jiggly gyrations? It seems that our findings have infused a newfound fervor into the notion that consumer preferences extend beyond mere personal whims to sway the grand tempo of market trends.

But let us not overlook the bubbly realm of popular non-fiction works and fictional attractions that tantalized our senses and stimulated our curiosity. The lighthearted spirit of "The Brewmaster's Bounty" and the aromatic allure of "The Tea Leaf Mysteries" have perhaps lent a whimsical touch to our own scholarly pursuit. And who can dismiss the fizzy antics of "The Quirky Adventures of Fizzy and Friends"? As our findings affirm, even the most offbeat sources of inspiration can fuel the flames of academic inquiry.

Our results, captured vividly in the visually delectable scatterplot of Fig. 1, illustrate a charmingly robust relationship between annual US household spending on nonalcoholic beverages and DexCom's stock price. This visual feast of statistical synergy serves as a delightful testament to the potent influence of even the most seemingly innocuous consumer behaviors on the market dynamics. It appears that amidst the numbers and trend lines, there lurks a spirited undercurrent that binds the whims of the thirsty consumer to the fancies of the stock exchange.

In effect, our research thrusts the buoyant effervescence of nonalcoholic beverages squarely into the spotlight, demonstrating that in the financial arena, even the tiniest bubbles can pack a significant punch. With an irreverent wink to the unconventional, we hope our findings impart a refreshing understanding of consumer spending's unexpected clout in shaping the undulating terrain of stock prices. From a scholarly standpoint, this discovery serves as both a testament to the quirkiness of economic trends and a friendly reminder to take our statistical investigations with a grain of humor. Cheers to the tantalizing tang of unexpected correlations and the frothy fun of academic inquiry!


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 Annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM). Make lots of 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]]
Bubbly Beverages and Biometric Bourse: A Bizarre and Bodacious Examination of Annual US Household Spending on Nonalcoholic Beverages and DexCom's Stock Price

[[ABSTRACT]]
This paper presents a whimsical and wacky investigation into the relationship between the annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team embarked on a lighthearted journey to uncover the link between America's thirst for beverages that don't intoxicate and the whims and fancies of the stock market. Through rigorous statistical analysis, we discovered a staggering correlation coefficient of 0.9301610 and a p-value less than 0.01 for the time period spanning from 2006 to 2022. Our findings suggest that the ebb and flow of household beverage expenditures may indeed bear an uncanny relationship with DexCom's stock price, supporting the notion that when it comes to market trends, even the tiniest bubbles can make a big splash. We hope this study brings a dose of fizz and fun to the academic discourse on economic trends and stock market influences.

[[INTRDUCTION]]
The intersection of consumer behavior and stock market dynamics has long intrigued researchers, investors, and anyone with a penchant for peering into the peculiarities of market trends. In this zany and zesty study, we set out to explore the curious connection between annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). We embarked on this bizarre and bodacious adventure with an ardent desire to infuse some levity and lightheartedness into the often stern and stoic world of economic analysis.
The impetus for this peculiar inquiry stemmed from the observation that in the landscape of consumer spending, nonalcoholic beverages occupy a peculiar and prominent place. From the effervescent allure of carbonated concoctions to the artful sophistication of designer coffees, the array of nonalcoholic libations available to the American consumer is nothing short of staggering. Yet, amidst this shimmering sea of sippable selections, one cannot help but wonder: could the ebb and flow of household expenditure on nonalcoholic beverages harbor some clandestine influence on the capricious undulations of stock prices?
At the heart of our curious caper lies the enigmatic stock price of DexCom (DXCM), a company renowned for its innovative biometric technologies. As the astute investor is well aware, the stock market is an arena where fortunes are won and lost with the whimsy of a carnival game. Against this backdrop, the notion of untangling the relationship between household beverage spending and stock prices might seem as lighthearted as a clown juggling watermelons – and yet, as we shall see, there may be more at play than meets the eye.
So, with a twinkle in our eyes and a stratagem in our statistical arsenal, we dove headfirst into the tumultuous sea of data, armed with a fervent hope that our findings would not only entertain but also enlighten. Through this unorthodox study, we endeavor to add a touch of fizz and fun to the academically austere discourse on economic trends and stock market influences. Now, let us embark on this whimsical whirlwind of wacky correlations and buoyant bubbles, and see what unexpected delights may effervesce from the depths of our analysis. As we shall soon discover, in the delightful dance of consumer expenditures and stock market sway, even the most unexpected connections may indeed hold water - or perhaps, in the case of nonalcoholic beverages, a refreshing splash of sparkling surprise.

[[RESULTS]]
In our zany and zesty quest to uncover the enthralling interplay between annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM), we have stumbled upon a correlation coefficient that would make any statistician do a double take. Drumroll, please! We found a staggering correlation of 0.9301610, indicating an extraordinarily strong positive relationship between these seemingly unrelated variables. It seems that the fizz in household beverage spending may indeed hold more market sway than we ever anticipated!
Our intrepid research team also calculated an r-squared value of 0.8651995, suggesting that a whopping 86.52% of the variance in DexCom's stock price can be explained by the annual US household spending on nonalcoholic beverages. Talk about a statistical quirk! Additionally, with a p-value less than 0.01, we can confidently declare that this relationship is not just a statistical fluke. It seems that the connection between America's thirst for nonalcoholic quenchers and the gyrations of DexCom's stock price is no laughing matter - well, maybe just a little bit!
To visually capture this astonishing correlation, we present in Fig. 1 a scatterplot illustrating the robust relationship between annual US household spending on nonalcoholic beverages and DexCom's stock price. Behold the whimsical wonder of statistical synergy!
The findings of this peculiar investigation add a splash of levity to the often parched and pedestrian discussions of market influences. It appears that in the convoluted world of economic trends and stock market caprices, even the most unassuming of bubbles can buoyantly influence the movements of the financial tides. We hope these results bring a refreshing dose of irreverent insight into the intriguing dynamics of consumer spending and stock market fluctuations.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our whimsical and wacky investigation into the linkage between annual US household spending on nonalcoholic beverages and DexCom's stock price (DXCM) has yielded a treasure trove of statistical quirkiness. With a correlation coefficient that practically leaps off the charts at 0.9301610 and an r-squared value suggesting that 86.52% of DexCom's stock price variance can be attributed to the ebbs and flows of nonalcoholic beverage spending, it's clear that even the tiniest bubbles in consumer preferences can make a big splash in the stock market. This study serves as a lighthearted reminder that in the realm of economic trends and stock market influences, one should never underestimate the power of a refreshing fizzy drink to shake things up.

As we bid adieu to this merry escapade into the curious correlation between household beverage spending and stock prices, we are left both bemused and enlightened. The synergy between these seemingly divergent variables tickles the fancy of the statistical mind and beckons us to consider the whimsical dance of consumer preferences and market dynamics in a whole new light.

With our findings in hand, we suggest that future research endeavors take note of the potential for further exploration into the intersection of seemingly unrelated consumer behaviors and financial market phenomena. However, as for the specific link between nonalcoholic beverage expenditures and DexCom's stock price, it seems that we've quenched our thirst for insight. Perhaps it's time to raise a glass – of statistical significance, that is – to the intriguing discoveries that can bubble up from the most unexpected of correlations. It appears that when it comes to market trends, even the most effervescent of influences should never be underestimated. So, with a twinkle in our eyes and a dash of statistical zest, we raise our beakers to the delightfully quirky findings of this study and declare that no further research is needed in this particular area of inquiry. Cheers to statistical serendipity!


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 Bubbly Beverages and Biometric Bourse: A Bizarre and Bodacious Examination of Annual US Household Spending on Nonalcoholic Beverages and DexCom's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Quantitative 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 Bubbly Beverages and Biometric Bourse: A Bizarre and Bodacious Examination of Annual US Household Spending on Nonalcoholic Beverages and DexCom's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Quenchables Research


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 Bubbly Beverages and Biometric Bourse: A Bizarre and Bodacious Examination of Annual US Household Spending on Nonalcoholic Beverages and DexCom's Stock Price with an abstract of This paper presents a whimsical and wacky investigation into the relationship between the annual US household spending on nonalcoholic beverages and the stock price of DexCom (DXCM). Using data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), our research team embarked on a lighthearted journey to uncover the link between America's thirst for beverages that don't intoxicate and the whims and fancies of the stock market. Through rigorous statistical analysis, we discovered a staggering correlation coefficient of 0.9301610 and a p-value less than 0.01 for the time period spanning from 2006 to 2022. Our findings suggest that the ebb and flow of household beverage expenditures may indeed bear an uncanny relationship with DexCom's stock price, supporting the notion that when it comes to market trends, even the tiniest bubbles can make a big splash. We hope this study brings a dose of fizz and fun to the academic discourse on economic trends and stock market influences.

ChatGPT:

"US household spending, nonalcoholic beverages, DexCom stock price, annual spending trends, Bureau of Labor Statistics data, LSEG Analytics, Refinitiv, correlation coefficient, statistical analysis, market trends, economic influences, stock market analysis"

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

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

See what else correlates with DexCom's stock price (DXCM)

Correlation r = 0.9301610 (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 = 0.8651995 (Coefficient of determination)
This means 86.5% of the change in the one variable (i.e., DexCom's stock price (DXCM)) is predictable based on the change in the other (i.e., Annual US household spending on nonalcoholic beverages) over the 17 years from 2006 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.4E-8. 0.0000000641041034342058200000
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 6.4E-6% of random cases. Said differently, if you correlated 15,599,625 random variables You don't actually need 15 million 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 16 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 16 because we have two variables measured over a period of 17 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.

[ 0.81, 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.
20062007200820092010201120122013201420152016201720182019202020212022
Annual US household spending on nonalcoholic beverages (Household spend)332333342337333361370384375374393423438455455515584
DexCom's stock price (DXCM) (Stock price)3.752.492.260.692.053.442.383.478.8113.9120.0714.8814.4129.2554.6491.52132.95




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.




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([332,333,342,337,333,361,370,384,375,374,393,423,438,455,455,515,584,])
array_2 = np.array([3.75,2.49,2.26,0.69,2.05,3.44,2.38,3.47,8.81,13.91,20.07,14.88,14.41,29.25,54.64,91.52,132.95,])
array_1_name = "Annual US household spending on nonalcoholic beverages"
array_2_name = "DexCom's stock price (DXCM)"

# 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: 3486 · Black Variable ID: 19901 · Red Variable ID: 1782
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