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Spurious correlation #3,480 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Milk consumption and the second variable is The number of telemarketers in West Virginia.  The chart goes from 2003 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As milk consumption decreased, the calcium deficiency in the population led to weaker bones. This, in turn, resulted in a significant decline in the ability to handle the mountainous terrain of West Virginia. As a result, telemarketers, known for their door-to-door sales tactics, found it increasingly difficult to navigate the hilly regions, ultimately leading to a decrease in their numbers.

Model: dalle-3
Prompt: Create an image of a serene West Virginia village with a deserted telemarketer call center. The abandoned call center, adorned with vibrant lights, sits in the center of the village. Among the empty desks, suited telemarketers roam aimlessly. The townspeople, enjoying the peace and quiet, are seen leisurely walking under the warm West Virginia sun. The lack of milk consumption has brought a quiet and tranquil atmosphere to the village. 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: Milk consumption and The number of telemarketers in West Virginia. 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: 3D Pixar Style Steampunk Sci-fi fantacy A TIME magazine cover image A scene from Skyrim
ChatGPT: A scene from Skyrim

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 Milk consumption and The number of telemarketers in West Virginia, in the following situation: Because as Milk consumption decreased, people became "udderly" disinterested in getting calls from telemarketers. The lack of dairy in their diets led to a "moo-ve" away from annoying sales pitches, as they had no "patience" for them without their daily dose of calcium. The telemarketers had to find other "pasture"-s for their work, grazing on different demographics to make their sales pitches.. Keep the description simple.
ChatGPT: In a serene West Virginia village, the townspeople's milk consumption dwindled. As a result, the usual bustling telemarketer call center with its vibrant lights and ringing phones sat abandoned. The telemarketers, dressed in suits, roamed the empty space, searching for new pastures to pitch their sales. The dairy-deprived villagers, no longer tolerant of sales calls, enjoyed their peace and quiet under the warm West Virginia sun.

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: [ A scene from Skyrim ] and depicting this scene: In a serene West Virginia village, the townspeople's milk consumption dwindled. As a result, the usual bustling telemarketer call center with its vibrant lights and ringing phones sat abandoned. The telemarketers, dressed in suits, roamed the empty space, searching for new pastures to pitch their sales. The dairy-deprived villagers, no longer tolerant of sales calls, enjoyed their peace and quiet under the warm West Virginia sun. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a serene West Virginia village with a deserted telemarketer call center. The abandoned call center, adorned with vibrant lights, sits in the center of the village. Among the empty desks, suited telemarketers roam aimlessly. The townspeople, enjoying the peace and quiet, are seen leisurely walking under the warm West Virginia sun. The lack of milk consumption has brought a quiet and tranquil atmosphere to the village.

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

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

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

AI academic paper

(Because p < 0.01)
Got Milked? A Moo-ving Connection: The Correlation Between Milk Consumption and Telemarketers in West Virginia

The Journal of Bovine Behavior and Appalachian Economics

Jan 2024

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




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Milk consumption and The number of telemarketers in West Virginia. 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 USDA and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.9771181 and p < 0.01 for 2003 to 2021.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Got Milked? A Moo-ving Connection: The Correlation Between Milk Consumption and Telemarketers in West Virginia

[[ABSTRACT]]
The milk industry has long been a source of fascination and controversy. In this paper, we explore a rather unusual aspect of milk consumption - its potential impact on the number of telemarketers in West Virginia. Utilizing data from the USDA and Bureau of Labor Statistics spanning from 2003 to 2021, our research team uncovered a correlation coefficient of 0.9771181 and a p-value of less than 0.01, indicating a statistically significant relationship. While the connection between milk and telemarketers may seem utterly bizarre, our findings suggest that there may indeed be a strong association. This paper presents a whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Milk consumption and The number of telemarketers in West Virginia. Make lots of jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
Got Milked? A Moo-ving Connection: The Correlation Between Milk Consumption and Telemarketers in West Virginia

[[ABSTRACT]]
The milk industry has long been a source of fascination and controversy. In this paper, we explore a rather unusual aspect of milk consumption - its potential impact on the number of telemarketers in West Virginia. Utilizing data from the USDA and Bureau of Labor Statistics spanning from 2003 to 2021, our research team uncovered a correlation coefficient of 0.9771181 and a p-value of less than 0.01, indicating a statistically significant relationship. While the connection between milk and telemarketers may seem utterly bizarre, our findings suggest that there may indeed be a strong association. This paper presents a whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
Ah, the dairy dilemma - a subject that has churned up endless debates over the years. While the virtues of milk have been extolled in numerous contexts, our research takes a rather udderly unusual approach by examining its potential link to the number of telemarketers in West Virginia. You might be thinking, "What in the name of calcium and cold calls does milk have to do with telemarketing?" Well, dear reader, prepare to be utterly amazed as we delve into this utterly bizarre yet intriguing correlation.

As we embark on this study, it is important to acknowledge the delightful absurdity of this topic. The idea of milk consumption influencing the proliferation of telemarketers may seem as far-fetched as a cow jumping over the moon. However, armed with a passion for unconventional inquiry and a willingness to embrace quirky hypotheses, we boldly ventured into uncharted territories of statistical analysis.

In the delightful state of West Virginia, where the rolling hills and country charm mingle with the echoes of friendly "howdy's," our research sought to uncover any semblance of an association between the white elixir and the ceaseless ring of telemarketing calls. Picture this: dairy farmers mulling over cows while telemarketers chatter away in their headsets - quite the juxtaposition, isn't it?

Thus, we invite you to join us on this whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales. So, grab a glass of milk, take a seat, and prepare to be utterly fascinated by the unexpected correlation we stumbled upon. Let's milk this topic for all it's worth and see just how dairy consumption may have a moo-ving connection to the world of telemarketers in West Virginia.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Milk consumption and The number of telemarketers in West Virginia. 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 name some cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
Got Milked? A Moo-ving Connection: The Correlation Between Milk Consumption and Telemarketers in West Virginia

[[ABSTRACT]]
The milk industry has long been a source of fascination and controversy. In this paper, we explore a rather unusual aspect of milk consumption - its potential impact on the number of telemarketers in West Virginia. Utilizing data from the USDA and Bureau of Labor Statistics spanning from 2003 to 2021, our research team uncovered a correlation coefficient of 0.9771181 and a p-value of less than 0.01, indicating a statistically significant relationship. While the connection between milk and telemarketers may seem utterly bizarre, our findings suggest that there may indeed be a strong association. This paper presents a whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Ah, the dairy dilemma - a subject that has churned up endless debates over the years. While the virtues of milk have been extolled in numerous contexts, our research takes a rather udderly unusual approach by examining its potential link to the number of telemarketers in West Virginia. You might be thinking, "What in the name of calcium and cold calls does milk have to do with telemarketing?" Well, dear reader, prepare to be utterly amazed as we delve into this utterly bizarre yet intriguing correlation.
As we embark on this study, it is important to acknowledge the delightful absurdity of this topic. The idea of milk consumption influencing the proliferation of telemarketers may seem as far-fetched as a cow jumping over the moon. However, armed with a passion for unconventional inquiry and a willingness to embrace quirky hypotheses, we boldly ventured into uncharted territories of statistical analysis.
In the delightful state of West Virginia, where the rolling hills and country charm mingle with the echoes of friendly "howdy's," our research sought to uncover any semblance of an association between the white elixir and the ceaseless ring of telemarketing calls. Picture this: dairy farmers mulling over cows while telemarketers chatter away in their headsets - quite the juxtaposition, isn't it?
Thus, we invite you to join us on this whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales. So, grab a glass of milk, take a seat, and prepare to be utterly fascinated by the unexpected correlation we stumbled upon. Let's milk this topic for all it's worth and see just how dairy consumption may have a moo-ving connection to the world of telemarketers in West Virginia.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

As we embark on our whimsical journey into the uncharted territories of bovine beverage influence on the world of telemarketing, we first seek to ground our exploration in existing literature that delves into seemingly unrelated connections. Smith et al. (2015) conducted a study on dairy consumption patterns and societal trends, unraveling intriguing correlations between the consumption of milk and unexpected social phenomena. Likewise, Doe and Jones (2018) investigated the impact of dairy product sales on regional economic indicators, presenting thought-provoking findings that piqued our interest in the potential influence of milk on unanticipated realms.

However, as we ventured deeper into the research landscape, we stumbled upon a rather unexpected array of sources that, while not directly related to our topic, inspired a lighthearted exploration of the milk-telemarketer connection. In "The Big Moo" by Seth Godin and "Milk! A 10,000-Year Food Fracas" by Mark Kurlansky, the authors muse on the cultural, economic, and culinary significance of milk, setting the stage for a jovial romp through the dairy aisle of academia.

Further drawing from the realms of fiction, the works of "The Catcher in the Rye" by J.D. Salinger and "The Cattle Raid of Cooley" from Irish mythology presented allegorical themes of rebellion and unexpected consequences, offering a playful nod to the serendipitous nature of our research endeavors.

Turning to the world of animated entertainment, the escapades of Cow and Chicken as well as the misadventures of The Powerpuff Girls lent a lighthearted perspective on bovine references and unexpected correlations - reminding us that even the most offbeat connections can lead to delightful insights.

Armed with a curious spirit and an appetite for unconventional musings, we set forth into this literature review, bringing together a delightful medley of serious inquiry, whimsical fiction, and animated whimsy to milk our research topic for all it's worth.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Milk consumption and The number of telemarketers in West Virginia. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from USDA and Bureau of Larbor Statistics . You used data from 2003 to 2021

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Got Milked? A Moo-ving Connection: The Correlation Between Milk Consumption and Telemarketers in West Virginia

[[ABSTRACT]]
The milk industry has long been a source of fascination and controversy. In this paper, we explore a rather unusual aspect of milk consumption - its potential impact on the number of telemarketers in West Virginia. Utilizing data from the USDA and Bureau of Labor Statistics spanning from 2003 to 2021, our research team uncovered a correlation coefficient of 0.9771181 and a p-value of less than 0.01, indicating a statistically significant relationship. While the connection between milk and telemarketers may seem utterly bizarre, our findings suggest that there may indeed be a strong association. This paper presents a whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales.

[[INTRODUCTION]]
Ah, the dairy dilemma - a subject that has churned up endless debates over the years. While the virtues of milk have been extolled in numerous contexts, our research takes a rather udderly unusual approach by examining its potential link to the number of telemarketers in West Virginia. You might be thinking, "What in the name of calcium and cold calls does milk have to do with telemarketing?" Well, dear reader, prepare to be utterly amazed as we delve into this utterly bizarre yet intriguing correlation.
As we embark on this study, it is important to acknowledge the delightful absurdity of this topic. The idea of milk consumption influencing the proliferation of telemarketers may seem as far-fetched as a cow jumping over the moon. However, armed with a passion for unconventional inquiry and a willingness to embrace quirky hypotheses, we boldly ventured into uncharted territories of statistical analysis.
In the delightful state of West Virginia, where the rolling hills and country charm mingle with the echoes of friendly "howdy's," our research sought to uncover any semblance of an association between the white elixir and the ceaseless ring of telemarketing calls. Picture this: dairy farmers mulling over cows while telemarketers chatter away in their headsets - quite the juxtaposition, isn't it?
Thus, we invite you to join us on this whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales. So, grab a glass of milk, take a seat, and prepare to be utterly fascinated by the unexpected correlation we stumbled upon. Let's milk this topic for all it's worth and see just how dairy consumption may have a moo-ving connection to the world of telemarketers in West Virginia.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To uncover the potential link between milk consumption and the number of telemarketers in West Virginia, we employed an udderly eclectic mix of research methods that may seem as wild as a cow on roller skates. Our data collection spanned from 2003 to 2021 and predominantly involved leveraging publicly available data from the United States Department of Agriculture (USDA) and the Bureau of Labor Statistics. Now, let me milk-splain how we went about this moo-ving investigation!

First and foremost, we initiated a thorough extraction of milk consumption data from USDA sources. This involved skimming through countless datasets, as dense as a dairy farm's morning fog, to capture the annual per capita milk consumption in West Virginia. We diligently moo-ved through these figures, ensuring that not even a drop of data was left unturned.

Simultaneously, we mooo-sied on over to the Bureau of Labor Statistics to reap information on the number of telemarketers in West Virginia. Wrangling with this data was akin to herding cats in a pasture, but we persevered with the tenacity of a determined cowhand. We evaluated the employment figures within the telemarketing industry, striving to encapsulate the full extent of telephonic sales personnel in the state.

With our barn full of data, we employed a statistical approach that was as robust as an ox and as precise as a bovine ballet dancer. Utilizing software packages that are as sophisticated as a high-tech milking machine, we calculated the correlation coefficient between milk consumption and the number of telemarketers.

Our analysis was designed to milk the data for every last drop of insight, scrutinizing every statistical nook and cranny to identify any hint of a relationship between these seemingly disparate variables. Through regression analyses and time series modeling, we sifted through the data with the focus and determination of a dairy cow eyeing a fresh patch of clover.

Additionally, we conducted subgroup analyses to ascertain whether the observed correlation varied across different demographic segments within West Virginia. Our objective was to ensure that our findings were as applicable to the bustling urban centers as they were to the serene rural landscapes, leaving no cud unchewed in our pursuit of comprehensive insight.

In summarizing, our methodology entailed a blend of data sorcery and statistical acrobatics to elucidate the potential relationship between milk consumption and the prevalence of telemarketers in West Virginia. Although our methods may prompt a raised eyebrow or two, we embraced the whimsy of this inquiry with the gusto of a heifer frolicking in a sunlit meadow.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Milk consumption and The number of telemarketers in West Virginia. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from USDA and Bureau of Larbor Statistics .

For the time period 2003 to 2021, you found a correlation 0.9771181, r-squared of 0.9547598, 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]]
Got Milked? A Moo-ving Connection: The Correlation Between Milk Consumption and Telemarketers in West Virginia

[[ABSTRACT]]
The milk industry has long been a source of fascination and controversy. In this paper, we explore a rather unusual aspect of milk consumption - its potential impact on the number of telemarketers in West Virginia. Utilizing data from the USDA and Bureau of Labor Statistics spanning from 2003 to 2021, our research team uncovered a correlation coefficient of 0.9771181 and a p-value of less than 0.01, indicating a statistically significant relationship. While the connection between milk and telemarketers may seem utterly bizarre, our findings suggest that there may indeed be a strong association. This paper presents a whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Ah, the dairy dilemma - a subject that has churned up endless debates over the years. While the virtues of milk have been extolled in numerous contexts, our research takes a rather udderly unusual approach by examining its potential link to the number of telemarketers in West Virginia. You might be thinking, "What in the name of calcium and cold calls does milk have to do with telemarketing?" Well, dear reader, prepare to be utterly amazed as we delve into this utterly bizarre yet intriguing correlation.
As we embark on this study, it is important to acknowledge the delightful absurdity of this topic. The idea of milk consumption influencing the proliferation of telemarketers may seem as far-fetched as a cow jumping over the moon. However, armed with a passion for unconventional inquiry and a willingness to embrace quirky hypotheses, we boldly ventured into uncharted territories of statistical analysis.
In the delightful state of West Virginia, where the rolling hills and country charm mingle with the echoes of friendly "howdy's," our research sought to uncover any semblance of an association between the white elixir and the ceaseless ring of telemarketing calls. Picture this: dairy farmers mulling over cows while telemarketers chatter away in their headsets - quite the juxtaposition, isn't it?
Thus, we invite you to join us on this whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales. So, grab a glass of milk, take a seat, and prepare to be utterly fascinated by the unexpected correlation we stumbled upon. Let's milk this topic for all it's worth and see just how dairy consumption may have a moo-ving connection to the world of telemarketers in West Virginia.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Our analysis revealed a remarkably strong correlation between milk consumption and the number of telemarketers in West Virginia, with a correlation coefficient of 0.9771181. The r-squared value of 0.9547598 indicates that approximately 95.48% of the variability in the number of telemarketers can be explained by the variance in milk consumption, showcasing a truly "moo-ving" relationship. Furthermore, the p-value of less than 0.01 provides strong evidence to support the statistical significance of this connection, udderly captivating our attention.

As depicted in Figure 1, our scatterplot illustrates the compelling linear relationship between milk consumption and the number of telemarketers, reinforcing the notion that this unexpected correlation is not merely a result of chance.

The implications of these findings are as unexpected as a cow doing calculus. While the link between milk consumption and telemarketing may seem utterly ludicrous at first glance, our data suggests a need for further investigation into the bovine beverage's influence on the prevalence of unsolicited phone calls. The implications go beyond mere statistical curiosity and may have practical implications for the telemarketing industry, as well as for the dairy farmers of West Virginia.

In conclusion, our research unveils a captivating correlation that raises intriguing questions about the interplay between dietary habits and the labor market. This exploration of the whimsical connection between milk and telemarketers underscores the potential for serendipitous discoveries in even the most unassuming of subject matters.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Milk consumption and The number of telemarketers in West Virginia. 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]]
Got Milked? A Moo-ving Connection: The Correlation Between Milk Consumption and Telemarketers in West Virginia

[[ABSTRACT]]
The milk industry has long been a source of fascination and controversy. In this paper, we explore a rather unusual aspect of milk consumption - its potential impact on the number of telemarketers in West Virginia. Utilizing data from the USDA and Bureau of Labor Statistics spanning from 2003 to 2021, our research team uncovered a correlation coefficient of 0.9771181 and a p-value of less than 0.01, indicating a statistically significant relationship. While the connection between milk and telemarketers may seem utterly bizarre, our findings suggest that there may indeed be a strong association. This paper presents a whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales.

[[LITERATURE REVIEW]]
As we embark on our whimsical journey into the uncharted territories of bovine beverage influence on the world of telemarketing, we first seek to ground our exploration in existing literature that delves into seemingly unrelated connections. Smith et al. (2015) conducted a study on dairy consumption patterns and societal trends, unraveling intriguing correlations between the consumption of milk and unexpected social phenomena. Likewise, Doe and Jones (2018) investigated the impact of dairy product sales on regional economic indicators, presenting thought-provoking findings that piqued our interest in the potential influence of milk on unanticipated realms.
However, as we ventured deeper into the research landscape, we stumbled upon a rather unexpected array of sources that, while not directly related to our topic, inspired a lighthearted exploration of the milk-telemarketer connection. In "The Big Moo" by Seth Godin and "Milk! A 10,000-Year Food Fracas" by Mark Kurlansky, the authors muse on the cultural, economic, and culinary significance of milk, setting the stage for a jovial romp through the dairy aisle of academia.
Further drawing from the realms of fiction, the works of "The Catcher in the Rye" by J.D. Salinger and "The Cattle Raid of Cooley" from Irish mythology presented allegorical themes of rebellion and unexpected consequences, offering a playful nod to the serendipitous nature of our research endeavors.
Turning to the world of animated entertainment, the escapades of Cow and Chicken as well as the misadventures of The Powerpuff Girls lent a lighthearted perspective on bovine references and unexpected correlations - reminding us that even the most offbeat connections can lead to delightful insights.
Armed with a curious spirit and an appetite for unconventional musings, we set forth into this literature review, bringing together a delightful medley of serious inquiry, whimsical fiction, and animated whimsy to milk our research topic for all it's worth.

[[RESULTS]]
Our analysis revealed a remarkably strong correlation between milk consumption and the number of telemarketers in West Virginia, with a correlation coefficient of 0.9771181. The r-squared value of 0.9547598 indicates that approximately 95.48% of the variability in the number of telemarketers can be explained by the variance in milk consumption, showcasing a truly "moo-ving" relationship. Furthermore, the p-value of less than 0.01 provides strong evidence to support the statistical significance of this connection, udderly captivating our attention.
As depicted in Figure 1, our scatterplot illustrates the compelling linear relationship between milk consumption and the number of telemarketers, reinforcing the notion that this unexpected correlation is not merely a result of chance.
The implications of these findings are as unexpected as a cow doing calculus. While the link between milk consumption and telemarketing may seem utterly ludicrous at first glance, our data suggests a need for further investigation into the bovine beverage's influence on the prevalence of unsolicited phone calls. The implications go beyond mere statistical curiosity and may have practical implications for the telemarketing industry, as well as for the dairy farmers of West Virginia.
In conclusion, our research unveils a captivating correlation that raises intriguing questions about the interplay between dietary habits and the labor market. This exploration of the whimsical connection between milk and telemarketers underscores the potential for serendipitous discoveries in even the most unassuming of subject matters.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

The results of our study have left us utterly astounded but udderly delighted by the unexpected correlation between milk consumption and the number of telemarketers in West Virginia. Our findings have lent support to the prior research, emphasizing the significance of seemingly unrelated connections in the world of academia and beyond. The correlation coefficient of 0.9771181, a statistical rarity akin to finding a four-leaf clover in a milk pitcher, indicated a robust relationship between milk consumption and the abundance of telemarketers, demonstrating that this fanciful correlation is not merely a result of happenstance.

Drawing on the literature review, we're reminded of the whimsical musings of Seth Godin and Mark Kurlansky, whose insights into the manifold significance of milk paved the way for our surprising findings. The unexpected parallels explored by Salinger and in Irish mythology now seem less fantastical, serving as amusing precursors to our own remarkable discovery. It seems that even fiction and folklore can offer insight into real-world connections, reminding us that truth can indeed be stranger than fiction.

Our results support the notion that there is "moo-re" to milk than meets the eye. The strong association revealed in our study not only adds a quirky twist to the annals of academic research but also warrants further exploration into the potential mechanisms underpinning this unusual correlation. It's an utter mystery worthy of Sherlock Holmes himself - or perhaps Sherlock Hooves in this case!

While the connection between milk consumption and telemarketers may initially elicit a chuckle, our findings underscore the far-reaching implications of examining seemingly unrelated phenomena. The economic and social implications of this correlation are as vast as a hayfield, extending into realms we never anticipated. This lighthearted yet thought-provoking exploration of the bovine beverage's unexpected influence has inspired us to contemplate the broader implications of offbeat connections in research.

In unraveling the whimsically unexpected correlation between milk consumption and telemarketers, we invite researchers to embrace a "cowincidental" approach to inquiry. Who knows what other delightfully incongruous connections might lie waiting to be unearthed in the fertile pastures of academic curiosity? As we mull over our findings, we can't help but wonder what other unexpected correlations may be lurking in the most unlikely corners of human experience. If milk and telemarketers can have a "moo-tual" association, what other surprising relationships might be waiting to be discovered?

In conclusion, our study has not only shed light on the quirky connection between milk consumption and telemarketers in West Virginia but also serves as a whimsical reminder that even the most offbeat connections can offer valuable insights into the intricate tapestry of human experience. We wax poetic in our delight, for our findings have not only discerned a surprising correlation but also offered a playful nod to the serendipitous nature of research itself. With an "udder"ly good sense of humor and an inquisitive spirit, we eagerly await further explorations into the plenitude of unexpected connections that await in the world of academic inquiry.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Milk consumption and The number of telemarketers in West Virginia. 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]]
Got Milked? A Moo-ving Connection: The Correlation Between Milk Consumption and Telemarketers in West Virginia

[[ABSTRACT]]
The milk industry has long been a source of fascination and controversy. In this paper, we explore a rather unusual aspect of milk consumption - its potential impact on the number of telemarketers in West Virginia. Utilizing data from the USDA and Bureau of Labor Statistics spanning from 2003 to 2021, our research team uncovered a correlation coefficient of 0.9771181 and a p-value of less than 0.01, indicating a statistically significant relationship. While the connection between milk and telemarketers may seem utterly bizarre, our findings suggest that there may indeed be a strong association. This paper presents a whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales.

[[INTRDUCTION]]
Ah, the dairy dilemma - a subject that has churned up endless debates over the years. While the virtues of milk have been extolled in numerous contexts, our research takes a rather udderly unusual approach by examining its potential link to the number of telemarketers in West Virginia. You might be thinking, "What in the name of calcium and cold calls does milk have to do with telemarketing?" Well, dear reader, prepare to be utterly amazed as we delve into this utterly bizarre yet intriguing correlation.
As we embark on this study, it is important to acknowledge the delightful absurdity of this topic. The idea of milk consumption influencing the proliferation of telemarketers may seem as far-fetched as a cow jumping over the moon. However, armed with a passion for unconventional inquiry and a willingness to embrace quirky hypotheses, we boldly ventured into uncharted territories of statistical analysis.
In the delightful state of West Virginia, where the rolling hills and country charm mingle with the echoes of friendly "howdy's," our research sought to uncover any semblance of an association between the white elixir and the ceaseless ring of telemarketing calls. Picture this: dairy farmers mulling over cows while telemarketers chatter away in their headsets - quite the juxtaposition, isn't it?
Thus, we invite you to join us on this whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales. So, grab a glass of milk, take a seat, and prepare to be utterly fascinated by the unexpected correlation we stumbled upon. Let's milk this topic for all it's worth and see just how dairy consumption may have a moo-ving connection to the world of telemarketers in West Virginia.

[[RESULTS]]
Our analysis revealed a remarkably strong correlation between milk consumption and the number of telemarketers in West Virginia, with a correlation coefficient of 0.9771181. The r-squared value of 0.9547598 indicates that approximately 95.48% of the variability in the number of telemarketers can be explained by the variance in milk consumption, showcasing a truly "moo-ving" relationship. Furthermore, the p-value of less than 0.01 provides strong evidence to support the statistical significance of this connection, udderly captivating our attention.
As depicted in Figure 1, our scatterplot illustrates the compelling linear relationship between milk consumption and the number of telemarketers, reinforcing the notion that this unexpected correlation is not merely a result of chance.
The implications of these findings are as unexpected as a cow doing calculus. While the link between milk consumption and telemarketing may seem utterly ludicrous at first glance, our data suggests a need for further investigation into the bovine beverage's influence on the prevalence of unsolicited phone calls. The implications go beyond mere statistical curiosity and may have practical implications for the telemarketing industry, as well as for the dairy farmers of West Virginia.
In conclusion, our research unveils a captivating correlation that raises intriguing questions about the interplay between dietary habits and the labor market. This exploration of the whimsical connection between milk and telemarketers underscores the potential for serendipitous discoveries in even the most unassuming of subject matters.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research elucidates a delightfully bizarre yet statistically robust connection between milk consumption and the number of telemarketers in West Virginia. The correlation coefficient we uncovered is as strong as the scent of freshly baked cookies wafting from a dairy farm. The implications of our findings are as tantalizing as a dairy-themed amusement park!

Who would have thought that the creamy elixir could have such a profound impact on the world of telephonic sales? It appears that the cows are not the only ones with noteworthy salesmanship skills! This unexpected correlation certainly adds a splash of whimsy to the typically mundane world of statistical analysis.

The implications of this research are as unexpected as a cow doing calculus. While the initial reaction may be one of incredulity, our findings suggest that there may indeed be a need for further probing into the enigmatic interplay between milk consumption and the proliferation of telemarketers.

However, as much as we would relish the opportunity to dive deeper into this utterly fascinating correlation, we must assert that no further research is needed in this area. It seems that we have utterly milked this topic dry, and any more investigation might border on the utterly absurd!


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 Got Milked? A Moo-ving Connection: The Correlation Between Milk Consumption and Telemarketers in West Virginia. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Bovine Behavior and Appalachian Economics


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 Got Milked? A Moo-ving Connection: The Correlation Between Milk Consumption and Telemarketers in West Virginia. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Dairy Economics and Rural Outcomes (SDERO)


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 Got Milked? A Moo-ving Connection: The Correlation Between Milk Consumption and Telemarketers in West Virginia with an abstract of The milk industry has long been a source of fascination and controversy. In this paper, we explore a rather unusual aspect of milk consumption - its potential impact on the number of telemarketers in West Virginia. Utilizing data from the USDA and Bureau of Labor Statistics spanning from 2003 to 2021, our research team uncovered a correlation coefficient of 0.9771181 and a p-value of less than 0.01, indicating a statistically significant relationship. While the connection between milk and telemarketers may seem utterly bizarre, our findings suggest that there may indeed be a strong association. This paper presents a whimsical yet thought-provoking exploration of the bovine beverage's unexpected influence on the world of telephonic sales.

ChatGPT:

milk consumption, telemarketers, West Virginia, USDA data, Bureau of Labor Statistics, correlation coefficient, statistical significance, milk industry, telephonic sales

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



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Data details

Milk consumption
Detailed data title: Per capita consumption of Fluid beverage milk in the US
Source: USDA
See what else correlates with Milk consumption

The number of telemarketers in West Virginia
Detailed data title: BLS estimate of telemarketers in West Virginia
Source: Bureau of Larbor Statistics
See what else correlates with The number of telemarketers in West Virginia

Correlation r = 0.9771181 (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 = 0.9547598 (Coefficient of determination)
This means 95.5% of the change in the one variable (i.e., The number of telemarketers in West Virginia) is predictable based on the change in the other (i.e., Milk consumption) over the 19 years from 2003 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 7.3E-13. 0.0000000000007265554078933340
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 0.98 in 7.3E-11% of random cases. Said differently, if you correlated 1,376,357,520,894 random variables You don't actually need 1 trillion 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 18 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.94, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
2003200420052006200720082009201020112012201320142015201620172018201920202021
Milk consumption (Pounds per person)188185185185183181181177173169164158155153149145141141134
The number of telemarketers in West Virginia (Telemarketers)5280542051105870475051904840483039203610232017701070110010601080270710330




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([188,185,185,185,183,181,181,177,173,169,164,158,155,153,149,145,141,141,134,])
array_2 = np.array([5280,5420,5110,5870,4750,5190,4840,4830,3920,3610,2320,1770,1070,1100,1060,1080,270,710,330,])
array_1_name = "Milk consumption"
array_2_name = "The number of telemarketers in West Virginia"

# 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 may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

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: 3480 · Black Variable ID: 554 · Red Variable ID: 16038
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