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Spurious correlation #3,443 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Annual US household spending on alcoholic beverages and the second variable is The number of septic tank servicers and sewer pipe cleaners in New Hampshire.  The chart goes from 2003 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As household spending on alcoholic beverages increased, more people experienced a pressing need for the services of septic tank servicers and sewer pipe cleaners in New Hampshire. Remember, when it rains, it pours – especially for those in the septic tank industry!

Model: dalle-3
Prompt: An image generation prompt likely to create an interesting visual using DALLE-3 in photorealism style, depicting a cozy New Hampshire neighborhood, would be: "Generate an image of a bustling house party in a cozy New Hampshire neighborhood. The scene is filled with the sound of laughter and music, as friends and family enjoy each other's company. In the background, a team of busy sewer pipe cleaners and septic tank servicers are hard at work, ensuring that the increased flow of liquids from the festivities doesn't cause any plumbing issues. Capture the coziness of the neighborhood and the vibrant activity of the party, with a focus on the hardworking sewer maintenance team in the background. Highlight the seamless coexistence of the lively gathering and the diligent workers keeping the sewer system well-maintained." The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Annual US household spending on alcoholic beverages and The number of septic tank servicers and sewer pipe cleaners in New Hampshire. 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: Cyber folk Cybernetic art a meme Magic realism Photorealism
ChatGPT: Photorealism

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Annual US household spending on alcoholic beverages and The number of septic tank servicers and sewer pipe cleaners in New Hampshire, in the following situation: Because as household spending on alcoholic beverages increases, more people are hosting parties and events, leading to an increase in the need for septic tank and sewer pipe cleaning services due to the higher volume of merry-making and festive activities. Plus, with more alcohol consumption, it's no surprise that more pipes and tanks need a little extra TLC. Cheers to a booming sewer industry in New Hampshire!. Keep the description simple.
ChatGPT: In a cozy New Hampshire neighborhood, a bustling house party is in full swing. The sound of laughter and music fills the air as friends and family enjoy each other's company. As the evening progresses, a team of busy sewer pipe cleaners and septic tank servicers are hard at work, ensuring that the increased flow of liquids from the festivities doesn't cause any plumbing issues. Cheers to a well-maintained sewer system keeping the party going!

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: [ Photorealism ] and depicting this scene: In a cozy New Hampshire neighborhood, a bustling house party is in full swing. The sound of laughter and music fills the air as friends and family enjoy each other's company. As the evening progresses, a team of busy sewer pipe cleaners and septic tank servicers are hard at work, ensuring that the increased flow of liquids from the festivities doesn't cause any plumbing issues. Cheers to a well-maintained sewer system keeping the party going! Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: An image generation prompt likely to create an interesting visual using DALLE-3 in photorealism style, depicting a cozy New Hampshire neighborhood, would be: "Generate an image of a bustling house party in a cozy New Hampshire neighborhood. The scene is filled with the sound of laughter and music, as friends and family enjoy each other's company. In the background, a team of busy sewer pipe cleaners and septic tank servicers are hard at work, ensuring that the increased flow of liquids from the festivities doesn't cause any plumbing issues. Capture the coziness of the neighborhood and the vibrant activity of the party, with a focus on the hardworking sewer maintenance team in the background. Highlight the seamless coexistence of the lively gathering and the diligent workers keeping the sewer system well-maintained."

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

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

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Annual US household spending on alcoholic beverages caused The number of septic tank servicers and sewer pipe cleaners in New Hampshire to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)
Pouring More Bucks on Booze: The Boozy Blues and Septic Tank Crews

The Journal of Inebriation and Sanitation Engineering

Jan 2024

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




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Annual US household spending on alcoholic beverages and The number of septic tank servicers and sewer pipe cleaners in New Hampshire. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Rhyme words in the title.

Your research team used data from Bureau of Labor Statistics and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.8860970 and p < 0.01 for 2003 to 2022.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Pouring More Bucks on Booze: The Boozy Blues and Septic Tank Crews

[[ABSTRACT]]
This paper delves into the obscure yet tantalizing connection between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire. The research team utilized data from the Bureau of Labor Statistics and the Bureau of Labor Statistics to address this rather peculiar question. Our findings revealed a striking correlation coefficient of 0.8860970 and a p-value of less than 0.01 for the time period spanning from 2003 to 2022. We attempt to uncork the underlying factors contributing to this correlation and discuss potential implications, all while sprinkling in some lighthearted observations. So, grab a drink and wade through the murky waters of this unexpected, yet curious relationship. Cheers!


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Annual US household spending on alcoholic beverages and The number of septic tank servicers and sewer pipe cleaners in New Hampshire. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
Pouring More Bucks on Booze: The Boozy Blues and Septic Tank Crews

[[ABSTRACT]]
This paper delves into the obscure yet tantalizing connection between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire. The research team utilized data from the Bureau of Labor Statistics and the Bureau of Labor Statistics to address this rather peculiar question. Our findings revealed a striking correlation coefficient of 0.8860970 and a p-value of less than 0.01 for the time period spanning from 2003 to 2022. We attempt to uncork the underlying factors contributing to this correlation and discuss potential implications, all while sprinkling in some lighthearted observations. So, grab a drink and wade through the murky waters of this unexpected, yet curious relationship. Cheers!

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire might initially seem as unrelated as a cocktail umbrella and a plunger. However, as researchers, it is our duty to dive into unconventional correlations with the same enthusiasm as a bartender diving into a cocktail shaker.

As the saying goes, "In wine, there's truth," and in this study, we aim to uncover the truth behind the statistically robust association between these seemingly disparate variables. Our interest in this offbeat connection was piqued by the intriguing observation of an apparent synchrony between the consumption of libations and the maintenance of subterranean sewage systems.

While some may find this topic as dry as a martini, we assure you that our findings are anything but watered down. The data we collected from the Bureau of Labor Statistics and the Bureau of Economic Analysis allowed us to perform a rigorous analysis, with the results revealing a correlation coefficient that was anything but sobering. With a correlation coefficient of 0.8860970 and a p-value practically screaming for attention, there is certainly more to this connection than meets the eye.

We believe it is worth raising a glass to these unexpected findings, and in the pages that follow, we will attempt to distill the factors driving this intriguing correlation. From the idyllic vineyards of Napa Valley to the intricacies of septic tank maintenance, our investigation seeks to shed light on this peculiar relationship.

So, let us embark on this unconventional scholarly journey, brimming with statistical rigor and a dash of whimsy. As we unravel the entwined strands of alcohol consumption and the handling of underground waste, we invite you to join us in savoring the unexpected flavors of this scholarly cocktail. Cheers to unraveling the enigmatic connections that lie beneath the surface!


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Annual US household spending on alcoholic beverages and The number of septic tank servicers and sewer pipe cleaners in New Hampshire. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
Pouring More Bucks on Booze: The Boozy Blues and Septic Tank Crews

[[ABSTRACT]]
This paper delves into the obscure yet tantalizing connection between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire. The research team utilized data from the Bureau of Labor Statistics and the Bureau of Labor Statistics to address this rather peculiar question. Our findings revealed a striking correlation coefficient of 0.8860970 and a p-value of less than 0.01 for the time period spanning from 2003 to 2022. We attempt to uncork the underlying factors contributing to this correlation and discuss potential implications, all while sprinkling in some lighthearted observations. So, grab a drink and wade through the murky waters of this unexpected, yet curious relationship. Cheers!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire might initially seem as unrelated as a cocktail umbrella and a plunger. However, as researchers, it is our duty to dive into unconventional correlations with the same enthusiasm as a bartender diving into a cocktail shaker.
As the saying goes, "In wine, there's truth," and in this study, we aim to uncover the truth behind the statistically robust association between these seemingly disparate variables. Our interest in this offbeat connection was piqued by the intriguing observation of an apparent synchrony between the consumption of libations and the maintenance of subterranean sewage systems.
While some may find this topic as dry as a martini, we assure you that our findings are anything but watered down. The data we collected from the Bureau of Labor Statistics and the Bureau of Economic Analysis allowed us to perform a rigorous analysis, with the results revealing a correlation coefficient that was anything but sobering. With a correlation coefficient of 0.8860970 and a p-value practically screaming for attention, there is certainly more to this connection than meets the eye.
We believe it is worth raising a glass to these unexpected findings, and in the pages that follow, we will attempt to distill the factors driving this intriguing correlation. From the idyllic vineyards of Napa Valley to the intricacies of septic tank maintenance, our investigation seeks to shed light on this peculiar relationship.
So, let us embark on this unconventional scholarly journey, brimming with statistical rigor and a dash of whimsy. As we unravel the entwined strands of alcohol consumption and the handling of underground waste, we invite you to join us in savoring the unexpected flavors of this scholarly cocktail. Cheers to unraveling the enigmatic connections that lie beneath the surface!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Our extensive literature review unearthed a surprising dearth of scholarly works exploring the peculiar relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire. However, a few notable studies have ventured into related territory.

Smith and colleagues in "The Economic Impact of Alcohol Consumption" analyze the macroeconomic effects of alcohol expenditure, though their focus largely centers on aggregate consumption patterns rather than the specific link to waste management professions. Similarly, Doe et al. in "Waste Not, Want Not: A Study of Sewer Infrastructure" delve into the intricacies of sewage systems but regrettably make no mention of libation-related expenditures as a contributing factor to the demand for their maintenance.

Despite the scarceness of empirical research directly tackling the interplay between booze and septic tank crews, we plowed through an array of tangentially relevant literature to fertilize our understanding of this curious correlation. Of note are works such as "Wine and Civilization" by John Doe, and "Beeronomics" by Jim Jones, both of which scrutinize the historical, cultural, and economic facets of alcohol consumption, arousing our academic and libational interests alike.

Additionally, we unearthed a trove of compelling fiction works that, although not grounded in empirical evidence, lend a certain speculative narrative charm to our explorations. For example, in "The Grapes of Wrath" by John Steinbeck, the portrayal of agricultural toil prompts ruminations on the interconnectedness of livelihoods, including the maintenance of vital infrastructure. Meanwhile, the ethereal realms of Terry Pratchett's "Guards! Guards!" offer a fanciful spin on the dynamic between ale and unlikely vocational encounters.

One cannot overlook the influence of internet culture on our scholarly pursuits, as we stumbled upon the viral "Success Kid" meme, which humorously juxtaposes the triumph of an everyday achievement with the consequential aftermath—likely prompting introspection on the implications of celebratory libations for our dear septic laborers.

With our literature review in tow, we stand ready to further scrutinize the nexus between alcohol spending and the septic profession, embracing the unanticipated twists and turns that lie ahead. As we raise our glasses (both literally and metaphorically) to this idiosyncratic inquiry, we invite the reader to savor the tangy aroma of unconventional scholarship and the frothy intrigue of unexpected correlations. Prost!


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Annual US household spending on alcoholic beverages and The number of septic tank servicers and sewer pipe cleaners in New Hampshire. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Labor Statistics and Bureau of Larbor Statistics . You used data from 2003 to 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Pouring More Bucks on Booze: The Boozy Blues and Septic Tank Crews

[[ABSTRACT]]
This paper delves into the obscure yet tantalizing connection between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire. The research team utilized data from the Bureau of Labor Statistics and the Bureau of Labor Statistics to address this rather peculiar question. Our findings revealed a striking correlation coefficient of 0.8860970 and a p-value of less than 0.01 for the time period spanning from 2003 to 2022. We attempt to uncork the underlying factors contributing to this correlation and discuss potential implications, all while sprinkling in some lighthearted observations. So, grab a drink and wade through the murky waters of this unexpected, yet curious relationship. Cheers!

[[INTRODUCTION]]
The relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire might initially seem as unrelated as a cocktail umbrella and a plunger. However, as researchers, it is our duty to dive into unconventional correlations with the same enthusiasm as a bartender diving into a cocktail shaker.
As the saying goes, "In wine, there's truth," and in this study, we aim to uncover the truth behind the statistically robust association between these seemingly disparate variables. Our interest in this offbeat connection was piqued by the intriguing observation of an apparent synchrony between the consumption of libations and the maintenance of subterranean sewage systems.
While some may find this topic as dry as a martini, we assure you that our findings are anything but watered down. The data we collected from the Bureau of Labor Statistics and the Bureau of Economic Analysis allowed us to perform a rigorous analysis, with the results revealing a correlation coefficient that was anything but sobering. With a correlation coefficient of 0.8860970 and a p-value practically screaming for attention, there is certainly more to this connection than meets the eye.
We believe it is worth raising a glass to these unexpected findings, and in the pages that follow, we will attempt to distill the factors driving this intriguing correlation. From the idyllic vineyards of Napa Valley to the intricacies of septic tank maintenance, our investigation seeks to shed light on this peculiar relationship.
So, let us embark on this unconventional scholarly journey, brimming with statistical rigor and a dash of whimsy. As we unravel the entwined strands of alcohol consumption and the handling of underground waste, we invite you to join us in savoring the unexpected flavors of this scholarly cocktail. Cheers to unraveling the enigmatic connections that lie beneath the surface!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

In order to uncork the mystery behind the relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire, our research team embarked on a data-driven journey that took us through statistical mazes and digital labyrinths. Our methodology hilariously combined the precision of a sommelier selecting the finest vintage with the tenacity of a scientist studying the behaviors of microorganisms in a petri dish.

First, we diligently scoured the virtual vineyards of the Bureau of Labor Statistics and the Bureau of Labor Statistics, collecting a bountiful harvest of data from 2003 to 2022. These databases provided us with a rich bouquet of information, allowing us to ferment our analysis with a robust blend of statistics and trends. We then sieved through this data like a seasoned winemaker, separating the sweet nectar of relevant variables from the grape skins of irrelevant noise.

To extract the essence of the relationship between household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners, we employed a series of sophisticated statistical analyses. Like a chemist concocting a potion, we employed regression models, time series analyses, and correlation calculations to distill the underlying patterns and associations. The goal was to unearth the hidden flavors of this curious interplay, revealing whether there was a genuine connection or if we were merely intoxicated by spurious correlations.

Additionally, we conducted thorough sensitivity analyses to ensure that our findings were as stable as a well-aged bourbon. These analyses tested our results under various conditions, examining the robustness of our inferences and ensuring that our conclusions were not as flimsy as a cocktail umbrella in a gust of wind. Our approach aimed to leave no statistical stone unturned, ensuring that we were not merely raising a toast to statistical noise and randomness.

Ultimately, our methodology sought to blend the rigorous precision of statistical analysis with the light-hearted curiosity of uncovering unexpected connections. Through this approach, we endeavored to serve up findings that were as rich and complex as a fine wine, converting data into a palatable symphony of scholarly insights and perhaps a few unexpected laughs along the way. Cheers to the art and science of unraveling the enigmatic connections that lie beneath the surface!


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

Please make up the results section of an academic research paper presenting the findings of the connection between Annual US household spending on alcoholic beverages and The number of septic tank servicers and sewer pipe cleaners in New Hampshire. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

For the time period 2003 to 2022, you found a correlation 0.8860970, r-squared of 0.7851679, 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]]
Pouring More Bucks on Booze: The Boozy Blues and Septic Tank Crews

[[ABSTRACT]]
This paper delves into the obscure yet tantalizing connection between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire. The research team utilized data from the Bureau of Labor Statistics and the Bureau of Labor Statistics to address this rather peculiar question. Our findings revealed a striking correlation coefficient of 0.8860970 and a p-value of less than 0.01 for the time period spanning from 2003 to 2022. We attempt to uncork the underlying factors contributing to this correlation and discuss potential implications, all while sprinkling in some lighthearted observations. So, grab a drink and wade through the murky waters of this unexpected, yet curious relationship. Cheers!

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire might initially seem as unrelated as a cocktail umbrella and a plunger. However, as researchers, it is our duty to dive into unconventional correlations with the same enthusiasm as a bartender diving into a cocktail shaker.
As the saying goes, "In wine, there's truth," and in this study, we aim to uncover the truth behind the statistically robust association between these seemingly disparate variables. Our interest in this offbeat connection was piqued by the intriguing observation of an apparent synchrony between the consumption of libations and the maintenance of subterranean sewage systems.
While some may find this topic as dry as a martini, we assure you that our findings are anything but watered down. The data we collected from the Bureau of Labor Statistics and the Bureau of Economic Analysis allowed us to perform a rigorous analysis, with the results revealing a correlation coefficient that was anything but sobering. With a correlation coefficient of 0.8860970 and a p-value practically screaming for attention, there is certainly more to this connection than meets the eye.
We believe it is worth raising a glass to these unexpected findings, and in the pages that follow, we will attempt to distill the factors driving this intriguing correlation. From the idyllic vineyards of Napa Valley to the intricacies of septic tank maintenance, our investigation seeks to shed light on this peculiar relationship.
So, let us embark on this unconventional scholarly journey, brimming with statistical rigor and a dash of whimsy. As we unravel the entwined strands of alcohol consumption and the handling of underground waste, we invite you to join us in savoring the unexpected flavors of this scholarly cocktail. Cheers to unraveling the enigmatic connections that lie beneath the surface!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of the relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire unveiled a captivating correlation coefficient of 0.8860970, signaling a rather intimate connection that may rival that of a bartender and their favorite cocktail shaker. This substantial correlation was accompanied by an r-squared value of 0.7851679, suggesting that approximately 78.52% of the variance in the number of septic tank servicers and sewer pipe cleaners can be explained by fluctuations in household spending on alcoholic beverages.

Furthermore, the p-value of less than 0.01 all but raises a neon sign, proclaiming the statistical significance of this association. It appears that this peculiar pairing is more than a mere happenstance, leaving us with no choice but to raise our glasses and toast to the unexpected.

The visual representation of this relationship is encapsulated in Figure 1, where a scatterplot graphically depicts the tightly intertwined nature of these variables. The plot is akin to a well-crafted cocktail – mixed with precision and garnished with a twist, visually stimulating and leaving an impression that lingers.

In summary, our findings not only bring to light the obscure connection between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire but also reinforce the notion that statistical exploration can yield unexpected and thought-provoking insights. The peculiar interplay between imbibing and underground waste management beckons further investigation and invites scholars and enthusiasts alike to ponder the intersection of these seemingly incongruous phenomena.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Annual US household spending on alcoholic beverages and The number of septic tank servicers and sewer pipe cleaners in New Hampshire. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
Pouring More Bucks on Booze: The Boozy Blues and Septic Tank Crews

[[ABSTRACT]]
This paper delves into the obscure yet tantalizing connection between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire. The research team utilized data from the Bureau of Labor Statistics and the Bureau of Labor Statistics to address this rather peculiar question. Our findings revealed a striking correlation coefficient of 0.8860970 and a p-value of less than 0.01 for the time period spanning from 2003 to 2022. We attempt to uncork the underlying factors contributing to this correlation and discuss potential implications, all while sprinkling in some lighthearted observations. So, grab a drink and wade through the murky waters of this unexpected, yet curious relationship. Cheers!

[[LITERATURE REVIEW]]
Our extensive literature review unearthed a surprising dearth of scholarly works exploring the peculiar relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire. However, a few notable studies have ventured into related territory.
Smith and colleagues in "The Economic Impact of Alcohol Consumption" analyze the macroeconomic effects of alcohol expenditure, though their focus largely centers on aggregate consumption patterns rather than the specific link to waste management professions. Similarly, Doe et al. in "Waste Not, Want Not: A Study of Sewer Infrastructure" delve into the intricacies of sewage systems but regrettably make no mention of libation-related expenditures as a contributing factor to the demand for their maintenance.
Despite the scarceness of empirical research directly tackling the interplay between booze and septic tank crews, we plowed through an array of tangentially relevant literature to fertilize our understanding of this curious correlation. Of note are works such as "Wine and Civilization" by John Doe, and "Beeronomics" by Jim Jones, both of which scrutinize the historical, cultural, and economic facets of alcohol consumption, arousing our academic and libational interests alike.
Additionally, we unearthed a trove of compelling fiction works that, although not grounded in empirical evidence, lend a certain speculative narrative charm to our explorations. For example, in "The Grapes of Wrath" by John Steinbeck, the portrayal of agricultural toil prompts ruminations on the interconnectedness of livelihoods, including the maintenance of vital infrastructure. Meanwhile, the ethereal realms of Terry Pratchett's "Guards! Guards!" offer a fanciful spin on the dynamic between ale and unlikely vocational encounters.
One cannot overlook the influence of internet culture on our scholarly pursuits, as we stumbled upon the viral "Success Kid" meme, which humorously juxtaposes the triumph of an everyday achievement with the consequential aftermath—likely prompting introspection on the implications of celebratory libations for our dear septic laborers.
With our literature review in tow, we stand ready to further scrutinize the nexus between alcohol spending and the septic profession, embracing the unanticipated twists and turns that lie ahead. As we raise our glasses (both literally and metaphorically) to this idiosyncratic inquiry, we invite the reader to savor the tangy aroma of unconventional scholarship and the frothy intrigue of unexpected correlations. Prost!

[[RESULTS]]
The analysis of the relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire unveiled a captivating correlation coefficient of 0.8860970, signaling a rather intimate connection that may rival that of a bartender and their favorite cocktail shaker. This substantial correlation was accompanied by an r-squared value of 0.7851679, suggesting that approximately 78.52% of the variance in the number of septic tank servicers and sewer pipe cleaners can be explained by fluctuations in household spending on alcoholic beverages.
Furthermore, the p-value of less than 0.01 all but raises a neon sign, proclaiming the statistical significance of this association. It appears that this peculiar pairing is more than a mere happenstance, leaving us with no choice but to raise our glasses and toast to the unexpected.
The visual representation of this relationship is encapsulated in Figure 1, where a scatterplot graphically depicts the tightly intertwined nature of these variables. The plot is akin to a well-crafted cocktail – mixed with precision and garnished with a twist, visually stimulating and leaving an impression that lingers.
In summary, our findings not only bring to light the obscure connection between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire but also reinforce the notion that statistical exploration can yield unexpected and thought-provoking insights. The peculiar interplay between imbibing and underground waste management beckons further investigation and invites scholars and enthusiasts alike to ponder the intersection of these seemingly incongruous phenomena.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of our investigation into the entangled relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire have surfaced with inebriating implications. Our findings provide tangible support for the earlier theoretical underpinnings, demonstrating a statistically significant correlation that is as robust as a well-aged bourbon.

Our correlation coefficient of 0.8860970 reflects a remarkably strong positive relationship, akin to the bond between hops and barley in a finely crafted beer. This result echoes the anecdotal observations and untested hypotheses playfully alluded to in our literature review, suggesting that the influence of libations on the demand for sewage services goes beyond mere speculation, much like how a bottle of champagne goes beyond the mere popping of a cork.

The r-squared value of 0.7851679 implies that approximately 78.52% of the variability in the number of septic tank servicers and sewer pipe cleaners in New Hampshire can be attributed to fluctuations in household spending on alcoholic beverages. This echoes the thematic complexity explored by the likes of John Steinbeck and Terry Pratchett, illustrating the interconnected nature of worldly affairs, including the curious dance between tipplers and technicians.

The statistically significant p-value reinforces the solemnity of our findings, akin to a resounding chorus of clinking glasses in a jestful toast. It suggests that the relationship we have unearthed is not a mere boozy mirage but a tangible and substantiated phenomenon, reminiscent of the fervent debates that bubble up in the wake of potently flavored libations.

Our study's robustness in reinforcing the previously elusive connection between imbibing and underground waste management transcends the boundaries of conventional scholarly pursuits. As we navigate this uncharted terrain, we are compelled to tip our hats to the unconventional sources of inspiration that nudged us down this whimsical path, reminiscent of the unexpected inspiration drawn from internet memes such as "Success Kid."

In essence, our findings serve as a compelling invitation for further investigations into this unexpected correlation, an invitation that is perhaps best accepted with a light-hearted spirit and a hearty chuckle. As we raise a glass to celebrate our findings, we look optimistically towards future research endeavors that may uncover the intoxicating depth of this correlation and perhaps even discover other hidden connections amid the cocktail of quirks that permeate everyday life. Cheers to the unexpected and the whimsical twists that await in the realm of empirical discovery!


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Annual US household spending on alcoholic beverages and The number of septic tank servicers and sewer pipe cleaners in New Hampshire. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
Pouring More Bucks on Booze: The Boozy Blues and Septic Tank Crews

[[ABSTRACT]]
This paper delves into the obscure yet tantalizing connection between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire. The research team utilized data from the Bureau of Labor Statistics and the Bureau of Labor Statistics to address this rather peculiar question. Our findings revealed a striking correlation coefficient of 0.8860970 and a p-value of less than 0.01 for the time period spanning from 2003 to 2022. We attempt to uncork the underlying factors contributing to this correlation and discuss potential implications, all while sprinkling in some lighthearted observations. So, grab a drink and wade through the murky waters of this unexpected, yet curious relationship. Cheers!

[[INTRDUCTION]]
The relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire might initially seem as unrelated as a cocktail umbrella and a plunger. However, as researchers, it is our duty to dive into unconventional correlations with the same enthusiasm as a bartender diving into a cocktail shaker.
As the saying goes, "In wine, there's truth," and in this study, we aim to uncover the truth behind the statistically robust association between these seemingly disparate variables. Our interest in this offbeat connection was piqued by the intriguing observation of an apparent synchrony between the consumption of libations and the maintenance of subterranean sewage systems.
While some may find this topic as dry as a martini, we assure you that our findings are anything but watered down. The data we collected from the Bureau of Labor Statistics and the Bureau of Economic Analysis allowed us to perform a rigorous analysis, with the results revealing a correlation coefficient that was anything but sobering. With a correlation coefficient of 0.8860970 and a p-value practically screaming for attention, there is certainly more to this connection than meets the eye.
We believe it is worth raising a glass to these unexpected findings, and in the pages that follow, we will attempt to distill the factors driving this intriguing correlation. From the idyllic vineyards of Napa Valley to the intricacies of septic tank maintenance, our investigation seeks to shed light on this peculiar relationship.
So, let us embark on this unconventional scholarly journey, brimming with statistical rigor and a dash of whimsy. As we unravel the entwined strands of alcohol consumption and the handling of underground waste, we invite you to join us in savoring the unexpected flavors of this scholarly cocktail. Cheers to unraveling the enigmatic connections that lie beneath the surface!

[[RESULTS]]
The analysis of the relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire unveiled a captivating correlation coefficient of 0.8860970, signaling a rather intimate connection that may rival that of a bartender and their favorite cocktail shaker. This substantial correlation was accompanied by an r-squared value of 0.7851679, suggesting that approximately 78.52% of the variance in the number of septic tank servicers and sewer pipe cleaners can be explained by fluctuations in household spending on alcoholic beverages.
Furthermore, the p-value of less than 0.01 all but raises a neon sign, proclaiming the statistical significance of this association. It appears that this peculiar pairing is more than a mere happenstance, leaving us with no choice but to raise our glasses and toast to the unexpected.
The visual representation of this relationship is encapsulated in Figure 1, where a scatterplot graphically depicts the tightly intertwined nature of these variables. The plot is akin to a well-crafted cocktail – mixed with precision and garnished with a twist, visually stimulating and leaving an impression that lingers.
In summary, our findings not only bring to light the obscure connection between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire but also reinforce the notion that statistical exploration can yield unexpected and thought-provoking insights. The peculiar interplay between imbibing and underground waste management beckons further investigation and invites scholars and enthusiasts alike to ponder the intersection of these seemingly incongruous phenomena.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

Having conducted a thorough analysis of the relationship between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire, we can confidently say that the connection between libations and sanitation runs as deep as a well-aged merlot. Our findings offer a robust correlation coefficient of 0.8860970, indicating a bond stronger than the adhesive on a PVC pipe.

The statistical significance of this association, reflected in the p-value of less than 0.01, leaves little room for skepticism and much room for spirited discussions among both scholars and casual observers. With an r-squared value of 0.7851679, it's clear that this affiliation is not to be dismissed as a mere fluke, much like a joke that lands just right.

In essence, our research illuminates an unexpected relationship that, much like a clever pun, tickles the intellect and invites further exploration. The scatterplot, akin to a composition of harmonious notes in a symphony, visually encapsulates the entwined dance of these variables – a testament to the artistry of statistical analysis.

As we raise our glasses to this unanticipated convergence of indulgence and infrastructure maintenance, we are left with a satisfying aftertaste of discovery and an appetite for unraveling more enigmatic connections in the future. Our findings provide a delightful twist to the scholarly discourse, demonstrating that statistical exploration can lead to intriguing and unforeseen revelations.

In closing, we assert that no further research in this area is needed – quite like when one has reached the perfect balance of spirits in a cocktail. With that, let's clink our glasses to unconventional correlations and bid adieu to this scholarly intoxication. Cheers to statistical surprises and the mysteries that lie beneath the surface!


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 Pouring More Bucks on Booze: The Boozy Blues and Septic Tank Crews. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Inebriation and Sanitation Engineering


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 Pouring More Bucks on Booze: The Boozy Blues and Septic Tank Crews. Respond only with the name of a fictional organization.

ChatGPT:

The Amalgamated Institute for the Study of Curious Phenomena


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 Pouring More Bucks on Booze: The Boozy Blues and Septic Tank Crews with an abstract of This paper delves into the obscure yet tantalizing connection between annual US household spending on alcoholic beverages and the number of septic tank servicers and sewer pipe cleaners in New Hampshire. The research team utilized data from the Bureau of Labor Statistics and the Bureau of Labor Statistics to address this rather peculiar question. Our findings revealed a striking correlation coefficient of 0.8860970 and a p-value of less than 0.01 for the time period spanning from 2003 to 2022. We attempt to uncork the underlying factors contributing to this correlation and discuss potential implications, all while sprinkling in some lighthearted observations. So, grab a drink and wade through the murky waters of this unexpected, yet curious relationship. Cheers!

ChatGPT:

US household spending on alcoholic beverages, septic tank servicers, sewer pipe cleaners, New Hampshire, correlation coefficient, Bureau of Labor Statistics, implications, annual spending, lighthearted observations

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



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Data details

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

The number of septic tank servicers and sewer pipe cleaners in New Hampshire
Detailed data title: BLS estimate of septic tank servicers and sewer pipe cleaners in New Hampshire
Source: Bureau of Larbor Statistics
See what else correlates with The number of septic tank servicers and sewer pipe cleaners in New Hampshire

Correlation r = 0.8860970 (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 = 0.7851679 (Coefficient of determination)
This means 78.5% of the change in the one variable (i.e., The number of septic tank servicers and sewer pipe cleaners in New Hampshire) is predictable based on the change in the other (i.e., Annual US household spending on alcoholic beverages) over the 20 years from 2003 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.01E-7. 0.0000002013339428298907400000
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 0.89 in 2.01E-5% of random cases. Said differently, if you correlated 4,966,872 random variables You don't actually need 4 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 19 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 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.

[ 0.73, 0.95 ] 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.
20032004200520062007200820092010201120122013201420152016201720182019202020212022
Annual US household spending on alcoholic beverages (Household spend)391459426497457444435412456451445463515484558583579478554583
The number of septic tank servicers and sewer pipe cleaners in New Hampshire (Laborers)40140110210110100807011090130130130110170210190160190230




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([391,459,426,497,457,444,435,412,456,451,445,463,515,484,558,583,579,478,554,583,])
array_2 = np.array([40,140,110,210,110,100,80,70,110,90,130,130,130,110,170,210,190,160,190,230,])
array_1_name = "Annual US household spending on alcoholic beverages"
array_2_name = "The number of septic tank servicers and sewer pipe cleaners in New Hampshire"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)



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You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

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Correlation ID: 3443 · Black Variable ID: 19902 · Red Variable ID: 11454
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