Spurious correlation #3,629 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of telemarketers in West Virginia and the second variable is US birth rates of triplets or more. The chart goes from 2003 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of telemarketers in West Virginia and the second variable is US birth rates of triplets or more. The chart goes from 2003 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

Because the state motto is "Mountaineers Are Always Free," but no one is free from the stress of telemarketing calls. The constant interruptions were putting a "triple" load of pressure on expecting parents, making it harder to conceive multiples. With fewer telemarketers, West Virginians finally had the peace and quiet they needed to focus on baby-making that didn't come in the form of an unsolicited phone call. It just goes to show, when it comes to fertility, sometimes the best things come in threes when you least expect them, unless you're expecting a call from a telemarketer.

^{Show image generation prompt} Model: dalle-3
Prompt: [ Concept art ] Create an image of a cozy living room in West Virginia, where a couple is sitting together, enjoying a quiet moment. The room is warmly lit with soft golden light filtering through the curtains. Show the couple sitting close to each other on a comfortable sofa, with content smiles on their faces. The surroundings could include a fireplace, adorned with a crackling fire, casting a warm glow across the room. Illustrate the absence of telemarketers by having a serene, uninterrupted vibe in the room. Emphasize the couple's deepening connection through subtle body language and eye contact. Capture the peaceful atmosphere and the couple's blissful unawareness of the decline in interruptions that previously led to the conception of triplets or more. Let the setting evoke tranquility, intimacy, and a sense of togetherness. 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: The number of telemarketers in West Virginia and US birth rates of triplets or more. 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: Surrealism Cybernetic art Symbolism Scalar art Concept art
ChatGPT: Concept art

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 The number of telemarketers in West Virginia and US birth rates of triplets or more, in the following situation: Because with fewer telemarketers in West Virginia, expecting parents no longer have to endure interruptions during intimate moments, resulting in a decline in the conception of triplets or more.. Keep the description simple.
ChatGPT: In a cozy living room in West Virginia, a couple sits together, enjoying a quiet moment. There are fewer telemarketers in the state now, so they no longer have to pause their conversation due to annoying phone calls. As a result, they are able to focus on each other, deepening their connection. The atmosphere is peaceful, and the couple is blissfully unaware that the decline in interruptions has led to a decrease in the conception of triplets or more.

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: [ Concept art ] and depicting this scene: In a cozy living room in West Virginia, a couple sits together, enjoying a quiet moment. There are fewer telemarketers in the state now, so they no longer have to pause their conversation due to annoying phone calls. As a result, they are able to focus on each other, deepening their connection. The atmosphere is peaceful, and the couple is blissfully unaware that the decline in interruptions has led to a decrease in the conception of triplets or more. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Concept art ] Create an image of a cozy living room in West Virginia, where a couple is sitting together, enjoying a quiet moment. The room is warmly lit with soft golden light filtering through the curtains. Show the couple sitting close to each other on a comfortable sofa, with content smiles on their faces. The surroundings could include a fireplace, adorned with a crackling fire, casting a warm glow across the room. Illustrate the absence of telemarketers by having a serene, uninterrupted vibe in the room. Emphasize the couple's deepening connection through subtle body language and eye contact. Capture the peaceful atmosphere and the couple's blissful unawareness of the decline in interruptions that previously led to the conception of triplets or more. Let the setting evoke tranquility, intimacy, and a sense of togetherness.

*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.
^{Show prompt for explanation} 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 The number of telemarketers in West Virginia caused US birth rates of triplets or more to decrease. Include one good pun.

AI academic paper

(Because p < 0.01)

Telemarketing Triplets: The Surprising Correlation Between Telemarketers in West Virginia and US Birth Rates of Triplets or More

The Journal of Whimsical Statistics and Quirky Phenomena

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} 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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 The number of telemarketers in West Virginia and US birth rates of triplets or more. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Telemarketing Triplets: The Surprising Correlation Between Telemarketers in West Virginia and US Birth Rates of Triplets or More"

[[ABSTRACT]]
The relationship between telemarketing and multiple births has long been a subject of speculation, with some suggesting that the increase in telemarketing calls may lead to stress, which in turn impacts birth rates. In this study, we delved into this peculiar connection using data from the Bureau of Labor Statistics and the Centers for Disease Control and Prevention. Our findings revealed a remarkably strong correlation coefficient of 0.9460818 and a statistically significant p-value of less than 0.01 for the years 2003 to 2021.

It seems that amidst the ringing phones, a different kind of "ring" may be churning - one that brings forth not wedding bells, but rather an increase in triplet and higher-order multiples births. While it might sound like a telemarketer's "calling," our research sheds light on the unexpected influence of these unsolicited calls on the birth rate of multiples. The data has peeled back the layers of this enigmatic relationship, giving us a glimpse into the potential impact of telemarketing on family dynamics, albeit in a way that leaves us pondering, "call waiting...for triplets?"

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between variables seemingly unrelated on the surface often leads researchers down unexpected paths, and our study is no exception. The peculiar yet captivating bond between the number of telemarketers in West Virginia and US birth rates of triplets or more has piqued our interest and sparked a journey into the world of statistical analysis and dad jokes. It's a call we just couldn't afford to ignore.
As researchers, we are accustomed to seeking correlations that make sense, but every now and then, we come across ones that are as unexpected as a telemarketer calling during dinner. This study aims to explore the hypothesis that the presence of telemarketers in the picturesque hills and valleys of West Virginia might have a peculiar effect on the birth rates of triplets or more across the United States. We assure you, this is not just a "telemarketing ploy" to grab your attention; we are dialed into uncovering the truth behind this quirky relationship.
Now, let's address the elephant in the room – or should we say, the triplet in the womb? How could the number of telemarketers in West Virginia possibly have anything to do with the number of triplets being born elsewhere in the country? It's a question that's been ringing in our ears as persistently as a telemarketer trying to sell you extended car warranties. But fear not, dear reader, for our rigorous statistical analysis and carefully controlled research design will steer us towards answers without any "dropped calls."
The debate over whether correlation implies causation has raged on in the scientific community, and rightfully so. However, in the case of our study, the correlations we uncovered are as striking as a telemarketer's pitch. The numbers don't lie, and neither do we – the correlation coefficient of 0.9460818 speaks volumes, just like an enthusiastic telemarketer with a new product to sell. This statistical bond has left us pondering whether the ringing of phones can lead to an increase in the ringing of wedding bells, metaphorically speaking, of course.
It's worth noting that there are limitations to our study, as with any research endeavor. While we cannot definitively establish causation between telemarketing presence and triplet births, we can't help but appreciate the irony that "data calling" our attention to this unexpected link. Nonetheless, we are confident that our findings will add a new dimension to the ongoing discussion of the impact of environmental factors on human reproductive patterns. So, as we embark on this scholarly journey, let's embrace the unexpected with a well-deserved grin and a "hello, would you like to hear about our findings on telemarketing-induced triplets?"

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find that stress from environmental factors, including noise pollution and air quality, can have varying effects on human reproductive patterns. While their study focuses on urban areas, the potential impact of these factors on birth rates sparks further inquiry into the uncharted territory of telemarketing and its unexpected influence on triplet and higher-order multiples births.

Now, turning to "Doe and Richards," the authors examine the psychological impact of unsolicited phone calls, highlighting the potential stress induced by repeated interruptions during daily activities. The findings suggest a potential link between increased telemarketing and heightened levels of stress, a connection that may have implications for the birth rates of multiples. It appears that amidst the hustle and bustle of modern life, there may be an unforeseen ripple effect on family dynamics.

Moving on to "Jones and Smithson," the authors delve into the impact of societal stress on birth outcomes, emphasizing the need to consider unconventional stressors in the broader context of reproductive health. While their focus is on socioeconomic disparities, the notion of unexpected stressors prompts us to widen the lens to encompass the unconventional influence of telemarketing calls on birth rates. It's a call to explore the uncharted territory of phone-induced stress and its potential role in shaping fertility patterns.

As we transition to a broader perspective on stress and its impact on human behavior, it's important to consider non-fiction works such as "The Power of Habit" by Charles Duhigg and "The Tipping Point" by Malcolm Gladwell, which offer valuable insights into the ripple effects of seemingly insignificant daily occurrences. While they may not directly touch upon telemarketing, these works prompt us to consider the intricate interplay between environmental stimuli, human behavior, and unexpected outcomes. After all, a telemarketing call might just be a tiny piece in the grand puzzle of human decision-making.

On the fictional front, works such as "The Circle" by Dave Eggers and "White Noise" by Don DeLillo present thought-provoking narratives that explore the pervasive influence of modern technology and media on individuals and society. While these novels may not specifically reference telemarketing, their examination of the ubiquitous nature of communication technologies invites us to reflect on the potential effects of constant connectivity, including the unanticipated influence it may exert on birth rates. It's as if these works are whispering a cryptic message amid the noise of modern communication – could telemarketing calls be shaping our collective destinies in ways we never imagined?

And now, for the most unconventional of sources, we turn to an unexpected avenue of insights – the humble CVS receipt. Through an in-depth analysis of these seemingly mundane yet endlessly lengthy scrolls of information, we uncover a trove of wisdom. While their primary purpose may be to provide a record of transactions, could these receipts hold the key to understanding the mysterious connection between telemarketing in West Virginia and the birth rates of triplets or more? It's a whimsical notion, but in the world of unexpected correlations, no avenue can be dismissed without thorough investigation.

In conclusion, while the journey into the world of telemarketing-induced triplets may seem unconventional, our exploration of literature and unconventional sources underscores the need to consider unexpected variables in shaping human reproductive patterns. As we navigate this peculiar landscape, let's embrace the unexpected with open arms and a healthy dose of humor– after all, who knew that statistical analysis and dad jokes could be a winning combination in unraveling the mysteries of telemarketing's influence on birth rates?

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 The number of telemarketers in West Virginia and US birth rates of triplets or more. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Telemarketing Triplets: The Surprising Correlation Between Telemarketers in West Virginia and US Birth Rates of Triplets or More"

[[ABSTRACT]]
The relationship between telemarketing and multiple births has long been a subject of speculation, with some suggesting that the increase in telemarketing calls may lead to stress, which in turn impacts birth rates. In this study, we delved into this peculiar connection using data from the Bureau of Labor Statistics and the Centers for Disease Control and Prevention. Our findings revealed a remarkably strong correlation coefficient of 0.9460818 and a statistically significant p-value of less than 0.01 for the years 2003 to 2021.

It seems that amidst the ringing phones, a different kind of "ring" may be churning - one that brings forth not wedding bells, but rather an increase in triplet and higher-order multiples births. While it might sound like a telemarketer's "calling," our research sheds light on the unexpected influence of these unsolicited calls on the birth rate of multiples. The data has peeled back the layers of this enigmatic relationship, giving us a glimpse into the potential impact of telemarketing on family dynamics, albeit in a way that leaves us pondering, "call waiting...for triplets?"

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find that stress from environmental factors, including noise pollution and air quality, can have varying effects on human reproductive patterns. While their study focuses on urban areas, the potential impact of these factors on birth rates sparks further inquiry into the uncharted territory of telemarketing and its unexpected influence on triplet and higher-order multiples births.
Now, turning to "Doe and Richards," the authors examine the psychological impact of unsolicited phone calls, highlighting the potential stress induced by repeated interruptions during daily activities. The findings suggest a potential link between increased telemarketing and heightened levels of stress, a connection that may have implications for the birth rates of multiples. It appears that amidst the hustle and bustle of modern life, there may be an unforeseen ripple effect on family dynamics.
Moving on to "Jones and Smithson," the authors delve into the impact of societal stress on birth outcomes, emphasizing the need to consider unconventional stressors in the broader context of reproductive health. While their focus is on socioeconomic disparities, the notion of unexpected stressors prompts us to widen the lens to encompass the unconventional influence of telemarketing calls on birth rates. It's a call to explore the uncharted territory of phone-induced stress and its potential role in shaping fertility patterns.
As we transition to a broader perspective on stress and its impact on human behavior, it's important to consider non-fiction works such as "The Power of Habit" by Charles Duhigg and "The Tipping Point" by Malcolm Gladwell, which offer valuable insights into the ripple effects of seemingly insignificant daily occurrences. While they may not directly touch upon telemarketing, these works prompt us to consider the intricate interplay between environmental stimuli, human behavior, and unexpected outcomes. After all, a telemarketing call might just be a tiny piece in the grand puzzle of human decision-making.
On the fictional front, works such as "The Circle" by Dave Eggers and "White Noise" by Don DeLillo present thought-provoking narratives that explore the pervasive influence of modern technology and media on individuals and society. While these novels may not specifically reference telemarketing, their examination of the ubiquitous nature of communication technologies invites us to reflect on the potential effects of constant connectivity, including the unanticipated influence it may exert on birth rates. It's as if these works are whispering a cryptic message amid the noise of modern communication – could telemarketing calls be shaping our collective destinies in ways we never imagined?
And now, for the most unconventional of sources, we turn to an unexpected avenue of insights – the humble CVS receipt. Through an in-depth analysis of these seemingly mundane yet endlessly lengthy scrolls of information, we uncover a trove of wisdom. While their primary purpose may be to provide a record of transactions, could these receipts hold the key to understanding the mysterious connection between telemarketing in West Virginia and the birth rates of triplets or more? It's a whimsical notion, but in the world of unexpected correlations, no avenue can be dismissed without thorough investigation.
In conclusion, while the journey into the world of telemarketing-induced triplets may seem unconventional, our exploration of literature and unconventional sources underscores the need to consider unexpected variables in shaping human reproductive patterns. As we navigate this peculiar landscape, let's embrace the unexpected with open arms and a healthy dose of humor– after all, who knew that statistical analysis and dad jokes could be a winning combination in unraveling the mysteries of telemarketing's influence on birth rates?

[[RESULTS]]
The analysis of the relationship between the number of telemarketers in West Virginia and US birth rates of triplets or more yielded some truly surprising results. It appears that these seemingly incongruous variables have more in common than meets the eye. Just like an unexpected telemarketer call during an important family dinner, the correlation coefficient of 0.9460818 points to a strong positive association between the two variables. This correlation is as clear as a telemarketer's sales pitch – hard to ignore and even harder to disconnect from.
The r-squared value of 0.8950709 further solidifies the strength of this relationship, leaving us with little doubt that there's more to this connection than a mere statistical fluke. If only all relationships were as easy to spot as this one, we'd have a lot less confusion in the world...and probably a lot fewer telemarketing calls during dinner time.
As for the p-value, well, it was so small, it almost made us wonder if we had misdialed the statistical significance hotline. With a p < 0.01, this result is about as significant as a telemarketer navigating through the maze of call screening and actually getting through to you. It's remarkable – and just a bit unsettling at the same time.
In support of these quantitative findings, the scatterplot in Fig. 1 illustrates the tight clustering of data points, forming a trend as conspicuous as a telemarketer's persistence. The points on the plot seem as relentless as unwanted phone calls, creating a pattern that can't be easily ignored – just like we couldn't ignore the call for further research into this unexpected relationship.
In conclusion, the results unearthed by this study open up a world of possibilities, raising questions that go beyond the realm of statistics and into the complexities of human behavior and environmental influence. This unusual correlation not only challenges conventional wisdom but also offers a rare glimpse into the mysterious ways in which seemingly unrelated factors can intersect. Just as a telemarketer's call can disrupt a peaceful evening, our findings disrupt the traditional understanding of what influences birth rates of multiples in the United States.
Now, if you'll excuse the reach for a particularly cringe-worthy pun: it seems that when it comes to telemarketing and triplets, the connection is more than just a "numbers game" – it's a statistical phenomenon that rings loud and clear.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our study has unearthed a surprising and robust correlation between the number of telemarketers in West Virginia and US birth rates of triplets or more. This unexpected link, akin to a telemarketer interrupting your cozy Netflix binge, sheds light on the intricate interplay between environmental stimuli and human reproductive patterns. The results of this study align with previous research on stress and its impact on birth outcomes, echoing the findings of Smith et al. regarding the potential influence of environmental stressors. It's as if stress from telemarketing calls is playing a game of "telephone" with reproductive patterns, whispering its influence in the form of an increase in multiple births.

Our findings also dovetail with the work of Doe and Richards, as the psychological impact of unsolicited phone calls, much like a persistent telemarketer, appears to permeate into the realm of reproductive health. The heightened levels of stress induced by repeated interruptions during daily activities, a phenomenon not entirely dissimilar to the persistence of telemarketing calls, may indeed have implications for the birth rates of triplets and higher-order multiples. It's as if these findings are telling us, "hang up the phone, stress – we're onto you!"

Moreover, our results resonate with the insights provided by Jones and Smithson, expanding the lens of societal stressors to encompass the unexpected influence of telemarketing calls on birth rates. While their focus on socioeconomic disparities widens the scope of stressors, our study adds an unexpected dial tone to the broader tapestry of environmental stimuli impacting birth outcomes. It's as if the stress from telemarketing calls is making a "collect call" to the realm of reproductive health, leaving us to grapple with the unforeseen impact on multiple births.

In line with the unconventional sources explored in the literature review, our statistical analysis and empirical evidence lend credence to the uncharted territory of telemarketing-induced stress and its potential role in shaping fertility patterns. Just as a whimsical CVS receipt might hold valuable insights, our study unravels the cryptic message amidst the noise of telemarketing calls, offering a peculiar yet compelling lens through which to understand the interconnectedness of seemingly disparate elements. It's as if our study is urging us to pick up the phone and listen – the unexpected correlations are calling!

The strong correlation coefficient and statistically significant p-value in our results bring forth a compelling narrative that transcends the confines of traditional statistical analysis. It's as if the numbers themselves are banding together to share an unexpected story – one that involves telemarketing calls and the birth rates of triplets. This study not only adds a new layer to the understanding of environmental stressors but also challenges us to reassess the impact of seemingly mundane daily occurrences on human decision-making, reminding us that even the most unexpected variables can lead to startling revelations. It's as if our findings are urging us to embrace the unexpected with open arms and a healthy dose of humor, just like a good dad joke nestled within the corridors of academic research.

In the realm of statistical phenomenon, our study offers a curious twist, a surprising turn of events that has illuminated a whimsical yet unmistakably robust correlation between telemarketers in West Virginia and the birth rates of triplets or more. It's as if the statistical stars have aligned to reveal a multi-faceted resonance, one that invites us to ponder the interplay of seemingly disconnected elements in shaping human reproductive patterns. Our findings, much like an unexpected punchline, punctuate the conversation about the influence of telemarketing calls on birth rates with a blend of rigor and levity, inviting us to explore the unexpected with a wry smile and an open mind. The unexpected correlations continue to ring true, proving that in the world of statistical oddities, truth can indeed be stranger than fiction.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 The number of telemarketers in West Virginia and US birth rates of triplets or more. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Telemarketing Triplets: The Surprising Correlation Between Telemarketers in West Virginia and US Birth Rates of Triplets or More"

[[ABSTRACT]]
The relationship between telemarketing and multiple births has long been a subject of speculation, with some suggesting that the increase in telemarketing calls may lead to stress, which in turn impacts birth rates. In this study, we delved into this peculiar connection using data from the Bureau of Labor Statistics and the Centers for Disease Control and Prevention. Our findings revealed a remarkably strong correlation coefficient of 0.9460818 and a statistically significant p-value of less than 0.01 for the years 2003 to 2021.

It seems that amidst the ringing phones, a different kind of "ring" may be churning - one that brings forth not wedding bells, but rather an increase in triplet and higher-order multiples births. While it might sound like a telemarketer's "calling," our research sheds light on the unexpected influence of these unsolicited calls on the birth rate of multiples. The data has peeled back the layers of this enigmatic relationship, giving us a glimpse into the potential impact of telemarketing on family dynamics, albeit in a way that leaves us pondering, "call waiting...for triplets?"

[[INTRDUCTION]]
The relationship between variables seemingly unrelated on the surface often leads researchers down unexpected paths, and our study is no exception. The peculiar yet captivating bond between the number of telemarketers in West Virginia and US birth rates of triplets or more has piqued our interest and sparked a journey into the world of statistical analysis and dad jokes. It's a call we just couldn't afford to ignore.
As researchers, we are accustomed to seeking correlations that make sense, but every now and then, we come across ones that are as unexpected as a telemarketer calling during dinner. This study aims to explore the hypothesis that the presence of telemarketers in the picturesque hills and valleys of West Virginia might have a peculiar effect on the birth rates of triplets or more across the United States. We assure you, this is not just a "telemarketing ploy" to grab your attention; we are dialed into uncovering the truth behind this quirky relationship.
Now, let's address the elephant in the room – or should we say, the triplet in the womb? How could the number of telemarketers in West Virginia possibly have anything to do with the number of triplets being born elsewhere in the country? It's a question that's been ringing in our ears as persistently as a telemarketer trying to sell you extended car warranties. But fear not, dear reader, for our rigorous statistical analysis and carefully controlled research design will steer us towards answers without any "dropped calls."
The debate over whether correlation implies causation has raged on in the scientific community, and rightfully so. However, in the case of our study, the correlations we uncovered are as striking as a telemarketer's pitch. The numbers don't lie, and neither do we – the correlation coefficient of 0.9460818 speaks volumes, just like an enthusiastic telemarketer with a new product to sell. This statistical bond has left us pondering whether the ringing of phones can lead to an increase in the ringing of wedding bells, metaphorically speaking, of course.
It's worth noting that there are limitations to our study, as with any research endeavor. While we cannot definitively establish causation between telemarketing presence and triplet births, we can't help but appreciate the irony that "data calling" our attention to this unexpected link. Nonetheless, we are confident that our findings will add a new dimension to the ongoing discussion of the impact of environmental factors on human reproductive patterns. So, as we embark on this scholarly journey, let's embrace the unexpected with a well-deserved grin and a "hello, would you like to hear about our findings on telemarketing-induced triplets?"

[[RESULTS]]
The analysis of the relationship between the number of telemarketers in West Virginia and US birth rates of triplets or more yielded some truly surprising results. It appears that these seemingly incongruous variables have more in common than meets the eye. Just like an unexpected telemarketer call during an important family dinner, the correlation coefficient of 0.9460818 points to a strong positive association between the two variables. This correlation is as clear as a telemarketer's sales pitch – hard to ignore and even harder to disconnect from.
The r-squared value of 0.8950709 further solidifies the strength of this relationship, leaving us with little doubt that there's more to this connection than a mere statistical fluke. If only all relationships were as easy to spot as this one, we'd have a lot less confusion in the world...and probably a lot fewer telemarketing calls during dinner time.
As for the p-value, well, it was so small, it almost made us wonder if we had misdialed the statistical significance hotline. With a p < 0.01, this result is about as significant as a telemarketer navigating through the maze of call screening and actually getting through to you. It's remarkable – and just a bit unsettling at the same time.
In support of these quantitative findings, the scatterplot in Fig. 1 illustrates the tight clustering of data points, forming a trend as conspicuous as a telemarketer's persistence. The points on the plot seem as relentless as unwanted phone calls, creating a pattern that can't be easily ignored – just like we couldn't ignore the call for further research into this unexpected relationship.
In conclusion, the results unearthed by this study open up a world of possibilities, raising questions that go beyond the realm of statistics and into the complexities of human behavior and environmental influence. This unusual correlation not only challenges conventional wisdom but also offers a rare glimpse into the mysterious ways in which seemingly unrelated factors can intersect. Just as a telemarketer's call can disrupt a peaceful evening, our findings disrupt the traditional understanding of what influences birth rates of multiples in the United States.
Now, if you'll excuse the reach for a particularly cringe-worthy pun: it seems that when it comes to telemarketing and triplets, the connection is more than just a "numbers game" – it's a statistical phenomenon that rings loud and clear.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has highlighted the unexpected yet robust correlation between the number of telemarketers in West Virginia and US birth rates of triplets or more. It seems that as the telemarketers call, the storks also deliver – talk about a "call waiting" that yields triple the surprise! The statistical bond we've uncovered is as strong as a telemarketer's sales pitch, and the r-squared value confirms that this connection is not just a statistical fluke – it's a legitimate "telemarketing triple threat."

The p-value is so small, it's almost as impressive as a telemarketer maneuvering through call screening. It's remarkable, just like finding out you're expecting triplets when you were only planning for one. And don't even get us started on the scatterplot – it's as persistent as unwanted phone calls, forming a pattern that can't be easily ignored.

Our findings challenge conventional wisdom and shed light on the mysterious ways in which seemingly unrelated factors can intersect. It's as if the telemarketers have found a way to "call collect" on the birth rates of multiples, creating a connection that defies traditional understanding.

So, as we wrap up this unexpected journey into the world of telemarketing-induced triplets, let's end with a good old dad joke: It looks like this correlation isn't just a telemarketer's "number game" – it's a statistical phenomenon that rings loud and clear. But seriously, folks, this study has undoubtedly opened doors to new perspectives on the influences of environmental factors on human reproductive patterns.

In conclusion, we boldly assert that our research has effectively unraveled this enigmatic relationship, and we can confidently declare that no further research is needed in this particular area. It's time to hang up our statistical hats and let this quirky correlation ring on in the annals of research history. After all, there are only so many dad jokes one can make about telemarketing and triplets before it starts getting a bit *dial*ing.

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 Telemarketing Triplets: The Surprising Correlation Between Telemarketers in West Virginia and US Birth Rates of Triplets or More. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Whimsical Statistics and Quirky Phenomena

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 Telemarketing Triplets: The Surprising Correlation Between Telemarketers in West Virginia and US Birth Rates of Triplets or More. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Demographic Studies

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 Telemarketing Triplets: The Surprising Correlation Between Telemarketers in West Virginia and US Birth Rates of Triplets or More with an abstract of The relationship between telemarketing and multiple births has long been a subject of speculation, with some suggesting that the increase in telemarketing calls may lead to stress, which in turn impacts birth rates. In this study, we delved into this peculiar connection using data from the Bureau of Labor Statistics and the Centers for Disease Control and Prevention. Our findings revealed a remarkably strong correlation coefficient of 0.9460818 and a statistically significant p-value of less than 0.01 for the years 2003 to 2021.
It seems that amidst the ringing phones, a different kind of "ring" may be churning - one that brings forth not wedding bells, but rather an increase in triplet and higher-order multiples births. While it might sound like a telemarketer's "calling," our research sheds light on the unexpected influence of these unsolicited calls on the birth rate of multiples. The data has peeled back the layers of this enigmatic relationship, giving us a glimpse into the potential impact of telemarketing on family dynamics, albeit in a way that leaves us pondering, "call waiting...for triplets?

ChatGPT:

Telemarketing, West Virginia, US birth rates, triplets, multiple births, stress, Bureau of Labor Statistics, Centers for Disease Control and Prevention, correlation coefficient, p-value, 2003-2021, unsolicited calls, family dynamics

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

Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error

Data details

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

US birth rates of triplets or more
Source: CDC
See what else correlates with US birth rates of triplets or more

Correlation r = 0.9460818 (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 = 0.8950709 (Coefficient of determination)
This means 89.5% of the change in the one variable (i.e., US birth rates of triplets or more) is predictable based on the change in the other (i.e., The number of telemarketers in West Virginia) over the 19 years from 2003 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 9.5E-10.^Show 0.0000000009536240544895686000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note 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 0.95 in 9.5E-8% of random cases. Said differently, if you correlated 1,048,631,266 random variables^Note You don't actually need 1 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 18 degrees of freedom, ^Note 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.

[ 0.86, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} 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: ^Note 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.

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
The number of telemarketers in West Virginia (Telemarketers)	5280	5420	5110	5870	4750	5190	4840	4830	3920	3610	2320	1770	1070	1100	1060	1080	270	710	330
US birth rates of triplets or more (Birth rate per 100,000)	186	180	170	156	151	148	152	138	137	124.4	119.5	113.5	103.6	101.4	101.6	93	87.7	79.6	80

Why this works

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.
Lack of causal connection: There is probably^Note 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.
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^Note 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.
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. ^Note 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. ^{Show the steps to do this.} 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([5280,5420,5110,5870,4750,5190,4840,4830,3920,3610,2320,1770,1070,1100,1060,1080,270,710,330,])
array_2 = np.array([186,180,170,156,151,148,152,138,137,124.4,119.5,113.5,103.6,101.4,101.6,93,87.7,79.6,80,])
array_1_name = "The number of telemarketers in West Virginia"
array_2_name = "US birth rates of triplets or more"

# 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)

Reuseable content

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. ^Note 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.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only The number of telemarketers in West Virginia
Line chart for only US birth rates of triplets or more
AI-generated correlation image
The spurious research paper: Telemarketing Triplets: The Surprising Correlation Between Telemarketers in West Virginia and US Birth Rates of Triplets or More

View another random correlation

How fun was this correlation?

Kudos for rating!

Correlation ID: 3629 · Black Variable ID: 16038 · Red Variable ID: 55


Problem variable:
Issue:
Additional details: Optional
Confirm you are a human: