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Spurious correlation #2,127 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Associates degrees awarded in Architecture and the second variable is The number of truck drivers in District of Columbia.  The chart goes from 2011 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As more people became interested in building stuff, they also developed a passion for trucking it around. It's like they couldn't handle just designing the buildings, they had to 'drive' home their love for construction. It's a concrete example of how one degree can 'elevate' an entire industry!

Model: dalle-3
Prompt: Create an image of a grand, ancient city nestled among snow-capped mountains, reminiscent of a scene from Skyrim. In the foreground, a group of students stand outside an architectural school in the District of Columbia, holding up their Associates degrees with expressions of pride on their faces. The architecture of the school should reflect the grandeur of the city, and the surrounding scenery should convey a sense of bustling urban life. In the background, several truck drivers should be depicted, transporting goods and materials through the city streets to construction sites, adding a sense of vibrant activity to the scene. 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: Associates degrees awarded in Architecture and related services and The number of truck drivers in District of Columbia. 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: Psychedelic Cutsy graphics Parallax art Futuristic A scene from Skyrim
ChatGPT: A scene from Skyrim

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Associates degrees awarded in Architecture and related services and The number of truck drivers in District of Columbia together. Keep the description simple.
ChatGPT: A group of students in architectural drafting programs proudly hold up their Associates degrees outside their school in the District of Columbia. As they celebrate their achievement, a number of truck drivers can be seen passing by, transporting goods and materials to construction sites across the bustling city.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A scene from Skyrim ] and depicting this scene: A group of students in architectural drafting programs proudly hold up their Associates degrees outside their school in the District of Columbia. As they celebrate their achievement, a number of truck drivers can be seen passing by, transporting goods and materials to construction sites across the bustling city. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a grand, ancient city nestled among snow-capped mountains, reminiscent of a scene from Skyrim. In the foreground, a group of students stand outside an architectural school in the District of Columbia, holding up their Associates degrees with expressions of pride on their faces. The architecture of the school should reflect the grandeur of the city, and the surrounding scenery should convey a sense of bustling urban life. In the background, several truck drivers should be depicted, transporting goods and materials through the city streets to construction sites, adding a sense of vibrant activity to the scene.

*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 Associates degrees awarded in Architecture and related services caused The number of truck drivers in District of Columbia to increase. Include one good pun.

AI academic paper

(Because p < 0.01)
Building Bridges: Exploring the Architectural Association Between Associates Degrees and Truck Driving in the District of Columbia

The Journal of Vocational Integration and Urban Mobility

Jan 2024

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




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Associates degrees awarded in Architecture and related services and The number of truck drivers in District of Columbia. Make lots of jokes, goofy observations, and puns.

Make the title a clever pun.

Your research team used data from National Center for Education Statistics and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.9353130 and p < 0.01 for 2011 to 2021.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
"Building Bridges: Exploring the Architectural Association Between Associates Degrees and Truck Driving in the District of Columbia"

[[ABSTRACT]]
In this study, we embarked on a journey through the concrete jungle of academia to investigate the unexpected relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. Armed with statistical tools and a firm grasp of puns, our team delved into data from the National Center for Education Statistics and the Bureau of Labor Statistics to unravel this enigmatic connection.

Surprisingly, our findings revealed a strong correlation coefficient of 0.9353130 and p < 0.01 over the period from 2011 to 2021, indicating a striking association between the two seemingly disparate fields. Our results not only build a sturdy bridge between these divergent domains but also highlight the need for further investigation into the unexpected intersections of education and employment.

So, buckle up and join us as we navigate the unexpected twists and turns of this architectural odyssey, where the road to understanding leads to some unexpected destinations—not unlike a truck driver navigating the streets of the nation's capital.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Associates degrees awarded in Architecture and related services and The number of truck drivers in District of Columbia. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
"Building Bridges: Exploring the Architectural Association Between Associates Degrees and Truck Driving in the District of Columbia"

[[ABSTRACT]]
In this study, we embarked on a journey through the concrete jungle of academia to investigate the unexpected relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. Armed with statistical tools and a firm grasp of puns, our team delved into data from the National Center for Education Statistics and the Bureau of Labor Statistics to unravel this enigmatic connection.

Surprisingly, our findings revealed a strong correlation coefficient of 0.9353130 and p < 0.01 over the period from 2011 to 2021, indicating a striking association between the two seemingly disparate fields. Our results not only build a sturdy bridge between these divergent domains but also highlight the need for further investigation into the unexpected intersections of education and employment.

So, buckle up and join us as we navigate the unexpected twists and turns of this architectural odyssey, where the road to understanding leads to some unexpected destinations—not unlike a truck driver navigating the streets of the nation's capital.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Ladies and gentlemen, scholars and truckers, fasten your seatbelts as we embark on a journey through the tangled web of academia to explore the peculiar relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. This unusual pairing may seem as mismatched as a bricklayer at a ballet, but our research uncovers the surprising connections lurking beneath the surface.

As we delve into this conundrum, we encounter a peculiar narrative that unfolds like a plot twist in a classic movie. One might expect that the unmistakable aroma of diesel fuel and the graceful designs of architectural blueprints would have little in common, like mismatched roommates in a cramped New York City apartment. However, the statistical data offers a different tale—a tale that begs us to scrutinize the conventional wisdom and seek patterns in the seeming chaos.

Imagine the bewildered looks and raised eyebrows when we first proposed this study. Picture the thoughtful strokes of the chin and the questioning glances—wouldn't it be easier to explore the connectivity of, say, fish farming and urban planning? But no, dear reader, we set our sights on this unconventional pairing, armed with nothing but our wits, an abundance of coffee, and a statistical toolbox fit for Sherlock Holmes himself.

While the academic ivory tower may seem far removed from the rumbling engines of truck cabs and the hum of hydraulic lifts, our findings suggest otherwise. Our exploration has uncovered a correlation coefficient so compelling that it would make even the most stoic mathematician nod in appreciation. The numbers speak for themselves, revealing a linkage as profound as the shared appreciation of hard hats and vehicular mirrors.

So, as we journey through this curious labyrinth of academia, let us remember that in the vast expanse of knowledge, unexpected connections lie waiting to be uncovered. What may initially appear as distant as a skyscraper from a highway overpass could, in fact, be as closely intertwined as the gears of a transmission. Join us in our quest to unravel this enigmatic relationship and discover the hidden threads that weave together seemingly unrelated landscapes.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Associates degrees awarded in Architecture and related services and The number of truck drivers in District of Columbia. Make lots of jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Building Bridges: Exploring the Architectural Association Between Associates Degrees and Truck Driving in the District of Columbia"

[[ABSTRACT]]
In this study, we embarked on a journey through the concrete jungle of academia to investigate the unexpected relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. Armed with statistical tools and a firm grasp of puns, our team delved into data from the National Center for Education Statistics and the Bureau of Labor Statistics to unravel this enigmatic connection.

Surprisingly, our findings revealed a strong correlation coefficient of 0.9353130 and p < 0.01 over the period from 2011 to 2021, indicating a striking association between the two seemingly disparate fields. Our results not only build a sturdy bridge between these divergent domains but also highlight the need for further investigation into the unexpected intersections of education and employment.

So, buckle up and join us as we navigate the unexpected twists and turns of this architectural odyssey, where the road to understanding leads to some unexpected destinations—not unlike a truck driver navigating the streets of the nation's capital.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Ladies and gentlemen, scholars and truckers, fasten your seatbelts as we embark on a journey through the tangled web of academia to explore the peculiar relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. This unusual pairing may seem as mismatched as a bricklayer at a ballet, but our research uncovers the surprising connections lurking beneath the surface.
As we delve into this conundrum, we encounter a peculiar narrative that unfolds like a plot twist in a classic movie. One might expect that the unmistakable aroma of diesel fuel and the graceful designs of architectural blueprints would have little in common, like mismatched roommates in a cramped New York City apartment. However, the statistical data offers a different tale—a tale that begs us to scrutinize the conventional wisdom and seek patterns in the seeming chaos.
Imagine the bewildered looks and raised eyebrows when we first proposed this study. Picture the thoughtful strokes of the chin and the questioning glances—wouldn't it be easier to explore the connectivity of, say, fish farming and urban planning? But no, dear reader, we set our sights on this unconventional pairing, armed with nothing but our wits, an abundance of coffee, and a statistical toolbox fit for Sherlock Holmes himself.
While the academic ivory tower may seem far removed from the rumbling engines of truck cabs and the hum of hydraulic lifts, our findings suggest otherwise. Our exploration has uncovered a correlation coefficient so compelling that it would make even the most stoic mathematician nod in appreciation. The numbers speak for themselves, revealing a linkage as profound as the shared appreciation of hard hats and vehicular mirrors.
So, as we journey through this curious labyrinth of academia, let us remember that in the vast expanse of knowledge, unexpected connections lie waiting to be uncovered. What may initially appear as distant as a skyscraper from a highway overpass could, in fact, be as closely intertwined as the gears of a transmission. Join us in our quest to unravel this enigmatic relationship and discover the hidden threads that weave together seemingly unrelated landscapes.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In "The Architectural Digest," Smith et al.explores the trends in Associates degrees awarded in Architecture and related services from 2011 to 2015. The authors find a steady increase in the number of students pursuing architectural degrees during this period, suggesting a growing interest in the field. Meanwhile, in "Truckin' Tales," Doe investigates the demographics and employment patterns of truck drivers in the District of Columbia. The study reveals a diverse workforce, indicating that truck driving is not just a man's world, contrary to popular belief.

As we delve deeper into the relationship between these seemingly incongruent domains, it's important to consider the potential influences of popular culture and media. In "Bridges of Madison County," Jones illustrates the power of unexpected connections, hinting at the notion that our preconceived notions of what fits together may not always align with reality. Furthermore, "The Hitchhiker's Guide to the Galaxy" by Douglas Adams provides a whimsical take on the interplay of transportation and the cosmos, offering a lighthearted perspective on the interconnectedness of seemingly disparate elements.

However, it's essential to recognize that the internet age has also left its mark on this discussion. The "Truck Driver and Architecture Cat" meme, known for its portrayal of a cat maneuvering a truck through a cityscape while pondering architectural blueprints, serves as a humorous reminder that unexpected connections can be found even in the most unlikely places.

As we navigate this scholarly terrain, it becomes evident that the road to understanding may take us through uncharted territories, much like a truck driver navigating the bustling streets of the nation's capital. The rich tapestry of academia and the working world intertwine in ways that surprise, provoke, and, perhaps, even amuse.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Associates degrees awarded in Architecture and related services and The number of truck drivers in District of Columbia. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from National Center for Education Statistics and Bureau of Larbor Statistics . You used data from 2011 to 2021

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Building Bridges: Exploring the Architectural Association Between Associates Degrees and Truck Driving in the District of Columbia"

[[ABSTRACT]]
In this study, we embarked on a journey through the concrete jungle of academia to investigate the unexpected relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. Armed with statistical tools and a firm grasp of puns, our team delved into data from the National Center for Education Statistics and the Bureau of Labor Statistics to unravel this enigmatic connection.

Surprisingly, our findings revealed a strong correlation coefficient of 0.9353130 and p < 0.01 over the period from 2011 to 2021, indicating a striking association between the two seemingly disparate fields. Our results not only build a sturdy bridge between these divergent domains but also highlight the need for further investigation into the unexpected intersections of education and employment.

So, buckle up and join us as we navigate the unexpected twists and turns of this architectural odyssey, where the road to understanding leads to some unexpected destinations—not unlike a truck driver navigating the streets of the nation's capital.

[[INTRODUCTION]]
Ladies and gentlemen, scholars and truckers, fasten your seatbelts as we embark on a journey through the tangled web of academia to explore the peculiar relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. This unusual pairing may seem as mismatched as a bricklayer at a ballet, but our research uncovers the surprising connections lurking beneath the surface.
As we delve into this conundrum, we encounter a peculiar narrative that unfolds like a plot twist in a classic movie. One might expect that the unmistakable aroma of diesel fuel and the graceful designs of architectural blueprints would have little in common, like mismatched roommates in a cramped New York City apartment. However, the statistical data offers a different tale—a tale that begs us to scrutinize the conventional wisdom and seek patterns in the seeming chaos.
Imagine the bewildered looks and raised eyebrows when we first proposed this study. Picture the thoughtful strokes of the chin and the questioning glances—wouldn't it be easier to explore the connectivity of, say, fish farming and urban planning? But no, dear reader, we set our sights on this unconventional pairing, armed with nothing but our wits, an abundance of coffee, and a statistical toolbox fit for Sherlock Holmes himself.
While the academic ivory tower may seem far removed from the rumbling engines of truck cabs and the hum of hydraulic lifts, our findings suggest otherwise. Our exploration has uncovered a correlation coefficient so compelling that it would make even the most stoic mathematician nod in appreciation. The numbers speak for themselves, revealing a linkage as profound as the shared appreciation of hard hats and vehicular mirrors.
So, as we journey through this curious labyrinth of academia, let us remember that in the vast expanse of knowledge, unexpected connections lie waiting to be uncovered. What may initially appear as distant as a skyscraper from a highway overpass could, in fact, be as closely intertwined as the gears of a transmission. Join us in our quest to unravel this enigmatic relationship and discover the hidden threads that weave together seemingly unrelated landscapes.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

The methodology employed in this study was as rigorous and painstaking as a construction crew laying the foundation for a towering skyscraper. We harnessed the power of data mining and statistical analysis to navigate the complex terrain of educational and occupational trends, striving to illuminate the enigmatic relationship between Associates degrees in Architecture and related services and the number of truck drivers traversing the roads of the District of Columbia. Our approach was structured to account for the multifaceted nature of the research question, incorporating both quantitative and qualitative components to capture the essence of this unlikely association.

Data Collection:
Our team scoured the digital landscape, much like intrepid treasure hunters seeking elusive gems of information, to source relevant data. We turned to the National Center for Education Statistics and the Bureau of Labor Statistics as our primary suppliers of raw data, extracting information on the number of Associates degrees awarded in Architecture and related services and the employment statistics for truck drivers in the District of Columbia over the period from 2011 to 2021. This endeavor required the patience of a saint and the perseverance of a determined explorer, as we sifted through vast datasets to uncover the hidden correlations waiting to be unearthed.

Statistical Analysis:
With our treasure trove of data in hand, we set about employing a range of statistical methods to disentangle the complex web of associations. From correlation analysis to regression modeling, our toolkit resembled a Swiss Army knife of statistical techniques, each method serving as a unique instrument in our quest for understanding. We calculated correlation coefficients, p-values, and confidence intervals with the meticulous precision of a master craftsman fine-tuning his tools, seeking to reveal the subtle nuances and robust patterns underlying the seemingly disparate realms of architecture education and truck driving.

Variable Consideration:
As we constructed our analytical framework, we carefully considered the variables at play, akin to an architect meticulously designing the blueprint for a new edifice. We accounted for factors such as the annual number of Associates degrees awarded in Architecture and related services and the fluctuating demand for truck drivers in the District of Columbia. We embraced the complexity of this array of variables, acknowledging the interplay between educational attainment and employment opportunities, much like the interlocking gears of a sophisticated machinery.

Qualitative Insights:
In addition to our quantitative analysis, we sought qualitative insights through interviews and surveys with stakeholders in the architecture and transportation industries. These interactions provided a human element to our investigation, allowing us to glean firsthand perspectives on the potential links between educational pathways and career trajectories. Our endeavors resembled a dialogue between the architects shaping the skylines and the truck drivers navigating the urban sprawl, revealing anecdotes and perspectives that enriched our understanding of the interwoven fabric of these seemingly distinct domains.

Ethical Considerations:
Throughout our research, we maintained a steadfast commitment to ethical conduct, ensuring the confidentiality and privacy of individuals whose data contributed to our findings. We upheld the principles of integrity and transparency, precluding any temptations to embellish our results with a lick of paint or a decorative flourish. The foundation of our study was built upon a bedrock of ethical responsibility, embodying the integrity that underpins scholarly inquiry.

Akin to the construction of a grand edifice, our methodology was structured, meticulous, and imbued with a dash of creativity—an approach designed to navigate the labyrinthine corridors of academia and illuminate the unexpected connections that define our scholarly landscape.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Associates degrees awarded in Architecture and related services and The number of truck drivers in District of Columbia. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

For the time period 2011 to 2021, you found a correlation 0.9353130, r-squared of 0.8748104, 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]]
"Building Bridges: Exploring the Architectural Association Between Associates Degrees and Truck Driving in the District of Columbia"

[[ABSTRACT]]
In this study, we embarked on a journey through the concrete jungle of academia to investigate the unexpected relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. Armed with statistical tools and a firm grasp of puns, our team delved into data from the National Center for Education Statistics and the Bureau of Labor Statistics to unravel this enigmatic connection.

Surprisingly, our findings revealed a strong correlation coefficient of 0.9353130 and p < 0.01 over the period from 2011 to 2021, indicating a striking association between the two seemingly disparate fields. Our results not only build a sturdy bridge between these divergent domains but also highlight the need for further investigation into the unexpected intersections of education and employment.

So, buckle up and join us as we navigate the unexpected twists and turns of this architectural odyssey, where the road to understanding leads to some unexpected destinations—not unlike a truck driver navigating the streets of the nation's capital.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Ladies and gentlemen, scholars and truckers, fasten your seatbelts as we embark on a journey through the tangled web of academia to explore the peculiar relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. This unusual pairing may seem as mismatched as a bricklayer at a ballet, but our research uncovers the surprising connections lurking beneath the surface.
As we delve into this conundrum, we encounter a peculiar narrative that unfolds like a plot twist in a classic movie. One might expect that the unmistakable aroma of diesel fuel and the graceful designs of architectural blueprints would have little in common, like mismatched roommates in a cramped New York City apartment. However, the statistical data offers a different tale—a tale that begs us to scrutinize the conventional wisdom and seek patterns in the seeming chaos.
Imagine the bewildered looks and raised eyebrows when we first proposed this study. Picture the thoughtful strokes of the chin and the questioning glances—wouldn't it be easier to explore the connectivity of, say, fish farming and urban planning? But no, dear reader, we set our sights on this unconventional pairing, armed with nothing but our wits, an abundance of coffee, and a statistical toolbox fit for Sherlock Holmes himself.
While the academic ivory tower may seem far removed from the rumbling engines of truck cabs and the hum of hydraulic lifts, our findings suggest otherwise. Our exploration has uncovered a correlation coefficient so compelling that it would make even the most stoic mathematician nod in appreciation. The numbers speak for themselves, revealing a linkage as profound as the shared appreciation of hard hats and vehicular mirrors.
So, as we journey through this curious labyrinth of academia, let us remember that in the vast expanse of knowledge, unexpected connections lie waiting to be uncovered. What may initially appear as distant as a skyscraper from a highway overpass could, in fact, be as closely intertwined as the gears of a transmission. Join us in our quest to unravel this enigmatic relationship and discover the hidden threads that weave together seemingly unrelated landscapes.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The statistical analysis of the data obtained from the National Center for Education Statistics and the Bureau of Labor Statistics unveiled a surprising correlation between the number of Associates degrees awarded in Architecture and related services and the thriving cohort of truck drivers in the District of Columbia, resembling the interplay of form and function in a carefully designed building.

The correlation coefficient of 0.9353130, with an r-squared value of 0.8748104, and a p-value of less than 0.01, depicts a compelling relationship, akin to the symmetry of a well-constructed suspension bridge. It is as if the streets of data and the avenues of analysis have converged, leading us to a metaphorical roundabout where academia and employment intersect with unexpected harmony.

Fig. 1 showcases a scatterplot that unequivocally illustrates this robust correlation, painting a picture as vivid as the murals adorning the sides of the delivery trucks navigating the bustling streets of the District of Columbia.

This unexpected alliance between the world of architectural academia and the professional realm of truck driving defies conventional categorizations and beckons us to ponder the hidden alignments amidst a seemingly disparate landscape. It is a realization that transcends mere statistical significance and delves into the intricacies of societal and occupational patterns, unfurling before us like an architect's blueprint brought to life.

Our findings challenge the conventional boundaries of occupational connections, perhaps serving as a reminder that in the vast landscape of education and employment, unanticipated intersections await discovery, much like stumbling upon a hidden alleyway while navigating a bustling urban district.

So, as we wrap up the results section of this academic voyage, let us marvel at the unexpected camaraderie between these two domains, appreciating the enigmatic dance of academia and employment that mirrors the harmonious orchestration of traffic on a meticulously designed road network.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Associates degrees awarded in Architecture and related services and The number of truck drivers in District of Columbia. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Building Bridges: Exploring the Architectural Association Between Associates Degrees and Truck Driving in the District of Columbia"

[[ABSTRACT]]
In this study, we embarked on a journey through the concrete jungle of academia to investigate the unexpected relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. Armed with statistical tools and a firm grasp of puns, our team delved into data from the National Center for Education Statistics and the Bureau of Labor Statistics to unravel this enigmatic connection.

Surprisingly, our findings revealed a strong correlation coefficient of 0.9353130 and p < 0.01 over the period from 2011 to 2021, indicating a striking association between the two seemingly disparate fields. Our results not only build a sturdy bridge between these divergent domains but also highlight the need for further investigation into the unexpected intersections of education and employment.

So, buckle up and join us as we navigate the unexpected twists and turns of this architectural odyssey, where the road to understanding leads to some unexpected destinations—not unlike a truck driver navigating the streets of the nation's capital.

[[LITERATURE REVIEW]]
In "The Architectural Digest," Smith et al.explores the trends in Associates degrees awarded in Architecture and related services from 2011 to 2015. The authors find a steady increase in the number of students pursuing architectural degrees during this period, suggesting a growing interest in the field. Meanwhile, in "Truckin' Tales," Doe investigates the demographics and employment patterns of truck drivers in the District of Columbia. The study reveals a diverse workforce, indicating that truck driving is not just a man's world, contrary to popular belief.
As we delve deeper into the relationship between these seemingly incongruent domains, it's important to consider the potential influences of popular culture and media. In "Bridges of Madison County," Jones illustrates the power of unexpected connections, hinting at the notion that our preconceived notions of what fits together may not always align with reality. Furthermore, "The Hitchhiker's Guide to the Galaxy" by Douglas Adams provides a whimsical take on the interplay of transportation and the cosmos, offering a lighthearted perspective on the interconnectedness of seemingly disparate elements.
However, it's essential to recognize that the internet age has also left its mark on this discussion. The "Truck Driver and Architecture Cat" meme, known for its portrayal of a cat maneuvering a truck through a cityscape while pondering architectural blueprints, serves as a humorous reminder that unexpected connections can be found even in the most unlikely places.
As we navigate this scholarly terrain, it becomes evident that the road to understanding may take us through uncharted territories, much like a truck driver navigating the bustling streets of the nation's capital. The rich tapestry of academia and the working world intertwine in ways that surprise, provoke, and, perhaps, even amuse.

[[RESULTS]]
The statistical analysis of the data obtained from the National Center for Education Statistics and the Bureau of Labor Statistics unveiled a surprising correlation between the number of Associates degrees awarded in Architecture and related services and the thriving cohort of truck drivers in the District of Columbia, resembling the interplay of form and function in a carefully designed building.
The correlation coefficient of 0.9353130, with an r-squared value of 0.8748104, and a p-value of less than 0.01, depicts a compelling relationship, akin to the symmetry of a well-constructed suspension bridge. It is as if the streets of data and the avenues of analysis have converged, leading us to a metaphorical roundabout where academia and employment intersect with unexpected harmony.
Fig. 1 showcases a scatterplot that unequivocally illustrates this robust correlation, painting a picture as vivid as the murals adorning the sides of the delivery trucks navigating the bustling streets of the District of Columbia.
This unexpected alliance between the world of architectural academia and the professional realm of truck driving defies conventional categorizations and beckons us to ponder the hidden alignments amidst a seemingly disparate landscape. It is a realization that transcends mere statistical significance and delves into the intricacies of societal and occupational patterns, unfurling before us like an architect's blueprint brought to life.
Our findings challenge the conventional boundaries of occupational connections, perhaps serving as a reminder that in the vast landscape of education and employment, unanticipated intersections await discovery, much like stumbling upon a hidden alleyway while navigating a bustling urban district.
So, as we wrap up the results section of this academic voyage, let us marvel at the unexpected camaraderie between these two domains, appreciating the enigmatic dance of academia and employment that mirrors the harmonious orchestration of traffic on a meticulously designed road network.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

Through our thorough investigation into the correlation between the number of Associates degrees awarded in Architecture and related services and the population of truck drivers in the District of Columbia, we unearthed a connection that is as fascinating as it is surprising. Our results not only provide empirical support for the unexpected relationship between these seemingly divergent fields but also contribute to a deeper understanding of the nuanced interplay between education and employment. In delving into the implications of our findings, let us first journey back to the literature review, where we encountered some unexpected yet crucial insights that have piqued our curiosity.

The work of Smith et al. on the increase in the number of students pursuing architectural degrees led us to expect some interesting trends in the educational landscape, but we were not prepared for the sheer magnitude of the connection we uncovered. Similarly, while Doe's exploration of the demographics and employment patterns of truck drivers in the District of Columbia offered valuable insights into the composition of this workforce, it did not fully prepare us for the strong statistical association we discovered. It is as if the road we traveled in our literature review had unexpected intersections, much like navigating the streets of a bustling city.

Our results echo the unanticipated connections highlighted in popular culture and media, such as the bridging of seemingly incongruent domains in "The Hitchhiker's Guide to the Galaxy." The statistical correlations in our study acted as the guide in our expedition through the vast and perplexing universe of data, prompting us to rethink our preconceived notions of what fits together in the educational and occupational spheres. Furthermore, the pervasive influence of the "Truck Driver and Architecture Cat" meme is a lighthearted reminder of the unexpected connections we encountered, prompting both amusement and contemplation in equal measure.

In light of the unexpected intersections our study has revealed, we cannot help but marvel at the remarkable correlation coefficient of 0.9353130 and the persuasive p-value of less than 0.01, which provide robust support for the association between Associates degrees in Architecture and the population of truck drivers. These statistical parameters serve as the foundation upon which our findings rest, much like the solid infrastructure of a well-constructed building supporting the bustling activity within.

As we journey through this unexplored terrain of associations and correlations, it becomes evident that the road to understanding may take us through uncharted territories, much like a truck driver navigating the bustling streets of the nation's capital. The enigmatic dance of academia and employment that our findings unveil beckons us to ponder the hidden alignments in an ostensibly disparate landscape, much like stumbling upon a hidden alleyway while navigating a bustling urban district.

Our investigation has paved the way for further exploration into the intertwined realms of education and employment, underscored by the unexpected camaraderie between these two domains. It is a realization that transcends mere statistical significance and delves into the intricacies of societal and occupational patterns, unfurling before us like an architect's blueprint brought to life. The architectural odyssey we embarked on has brought us to an unexpected intersection, where the road to understanding leads to some unexpected destinations—not unlike a truck driver navigating the streets of the nation's capital.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Associates degrees awarded in Architecture and related services and The number of truck drivers in District of Columbia. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Building Bridges: Exploring the Architectural Association Between Associates Degrees and Truck Driving in the District of Columbia"

[[ABSTRACT]]
In this study, we embarked on a journey through the concrete jungle of academia to investigate the unexpected relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. Armed with statistical tools and a firm grasp of puns, our team delved into data from the National Center for Education Statistics and the Bureau of Labor Statistics to unravel this enigmatic connection.

Surprisingly, our findings revealed a strong correlation coefficient of 0.9353130 and p < 0.01 over the period from 2011 to 2021, indicating a striking association between the two seemingly disparate fields. Our results not only build a sturdy bridge between these divergent domains but also highlight the need for further investigation into the unexpected intersections of education and employment.

So, buckle up and join us as we navigate the unexpected twists and turns of this architectural odyssey, where the road to understanding leads to some unexpected destinations—not unlike a truck driver navigating the streets of the nation's capital.

[[INTRDUCTION]]
Ladies and gentlemen, scholars and truckers, fasten your seatbelts as we embark on a journey through the tangled web of academia to explore the peculiar relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. This unusual pairing may seem as mismatched as a bricklayer at a ballet, but our research uncovers the surprising connections lurking beneath the surface.
As we delve into this conundrum, we encounter a peculiar narrative that unfolds like a plot twist in a classic movie. One might expect that the unmistakable aroma of diesel fuel and the graceful designs of architectural blueprints would have little in common, like mismatched roommates in a cramped New York City apartment. However, the statistical data offers a different tale—a tale that begs us to scrutinize the conventional wisdom and seek patterns in the seeming chaos.
Imagine the bewildered looks and raised eyebrows when we first proposed this study. Picture the thoughtful strokes of the chin and the questioning glances—wouldn't it be easier to explore the connectivity of, say, fish farming and urban planning? But no, dear reader, we set our sights on this unconventional pairing, armed with nothing but our wits, an abundance of coffee, and a statistical toolbox fit for Sherlock Holmes himself.
While the academic ivory tower may seem far removed from the rumbling engines of truck cabs and the hum of hydraulic lifts, our findings suggest otherwise. Our exploration has uncovered a correlation coefficient so compelling that it would make even the most stoic mathematician nod in appreciation. The numbers speak for themselves, revealing a linkage as profound as the shared appreciation of hard hats and vehicular mirrors.
So, as we journey through this curious labyrinth of academia, let us remember that in the vast expanse of knowledge, unexpected connections lie waiting to be uncovered. What may initially appear as distant as a skyscraper from a highway overpass could, in fact, be as closely intertwined as the gears of a transmission. Join us in our quest to unravel this enigmatic relationship and discover the hidden threads that weave together seemingly unrelated landscapes.

[[RESULTS]]
The statistical analysis of the data obtained from the National Center for Education Statistics and the Bureau of Labor Statistics unveiled a surprising correlation between the number of Associates degrees awarded in Architecture and related services and the thriving cohort of truck drivers in the District of Columbia, resembling the interplay of form and function in a carefully designed building.
The correlation coefficient of 0.9353130, with an r-squared value of 0.8748104, and a p-value of less than 0.01, depicts a compelling relationship, akin to the symmetry of a well-constructed suspension bridge. It is as if the streets of data and the avenues of analysis have converged, leading us to a metaphorical roundabout where academia and employment intersect with unexpected harmony.
Fig. 1 showcases a scatterplot that unequivocally illustrates this robust correlation, painting a picture as vivid as the murals adorning the sides of the delivery trucks navigating the bustling streets of the District of Columbia.
This unexpected alliance between the world of architectural academia and the professional realm of truck driving defies conventional categorizations and beckons us to ponder the hidden alignments amidst a seemingly disparate landscape. It is a realization that transcends mere statistical significance and delves into the intricacies of societal and occupational patterns, unfurling before us like an architect's blueprint brought to life.
Our findings challenge the conventional boundaries of occupational connections, perhaps serving as a reminder that in the vast landscape of education and employment, unanticipated intersections await discovery, much like stumbling upon a hidden alleyway while navigating a bustling urban district.
So, as we wrap up the results section of this academic voyage, let us marvel at the unexpected camaraderie between these two domains, appreciating the enigmatic dance of academia and employment that mirrors the harmonious orchestration of traffic on a meticulously designed road network.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our expedition through the intertwined realms of Associates degrees in Architecture and related services and the populous cohort of truck drivers in the District of Columbia has left us with a profound appreciation for the unexpected connections that underpin our society. Although one might argue that the likeness of an architect and a truck driver feels as mismatched as a high-rise building and a speed bump, our statistical analysis unveiled a correlation so strong it could transport a load of wit and wisdom across even the bumpiest of roads.

The correlation coefficient of 0.9353130 was as clear as the view from the top of the Washington Monument. It seems the academic and vocational worlds have crossed paths, much like a city driver's erratic routes through the streets of D.C. Our findings suggest that the landscape of education and employment is not as disjointed as a Lego piece in a pile of jigsaw puzzles; rather, it resembles a well-orchestrated symphony, where the sound of a truck's horn harmonizes with the refrain of architectural innovation.

As we put the brakes on this investigation, it is evident that the bridge we have constructed between these two seemingly distinct fields is as sturdy as the foundation of the Lincoln Memorial. Therefore, we confidently assert that no further research is required in this area. After all, understanding the architectural association between Associates degrees and truck driving in the District of Columbia is as crystal clear as the windshield of a freshly washed semi-truck – no need to muddy the waters further.


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 Building Bridges: Exploring the Architectural Association Between Associates Degrees and Truck Driving in the District of Columbia. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Vocational Integration and Urban Mobility


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 Building Bridges: Exploring the Architectural Association Between Associates Degrees and Truck Driving in the District of Columbia. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Transportation and Degree 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 Building Bridges: Exploring the Architectural Association Between Associates Degrees and Truck Driving in the District of Columbia with an abstract of In this study, we embarked on a journey through the concrete jungle of academia to investigate the unexpected relationship between the number of truck drivers in the District of Columbia and the confounding world of Associates degrees in Architecture and related services. Armed with statistical tools and a firm grasp of puns, our team delved into data from the National Center for Education Statistics and the Bureau of Labor Statistics to unravel this enigmatic connection.
Surprisingly, our findings revealed a strong correlation coefficient of 0.9353130 and p < 0.01 over the period from 2011 to 2021, indicating a striking association between the two seemingly disparate fields. Our results not only build a sturdy bridge between these divergent domains but also highlight the need for further investigation into the unexpected intersections of education and employment.
So, buckle up and join us as we navigate the unexpected twists and turns of this architectural odyssey, where the road to understanding leads to some unexpected destinations—not unlike a truck driver navigating the streets of the nation's capital.

ChatGPT:

Associates degrees, Architecture, Truck Driving, District of Columbia, statistical analysis, correlation coefficient, education, employment intersections, National Center for Education Statistics, Bureau of Labor Statistics, Washington D.C., unexpected relationships, academic study

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



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Data details

Associates degrees awarded in Architecture
Detailed data title: Associate's degrees conferred by postsecondary institutions with a field of study of Architecture and related services
Source: National Center for Education Statistics
See what else correlates with Associates degrees awarded in Architecture

The number of truck drivers in District of Columbia
Detailed data title: BLS estimate of heavy and tractor-trailer truck drivers in District of Columbia
Source: Bureau of Larbor Statistics
See what else correlates with The number of truck drivers in District of Columbia

Correlation r = 0.9353130 (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 = 0.8748104 (Coefficient of determination)
This means 87.5% of the change in the one variable (i.e., The number of truck drivers in District of Columbia) is predictable based on the change in the other (i.e., Associates degrees awarded in Architecture) over the 11 years from 2011 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.4E-5. 0.0000237340844896591620000000
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 0.94 in 0.0024% of random cases. Said differently, if you correlated 42,133 random variables You don't actually need 42 thousand variables to find a correlation like this one. 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.

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 10 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 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.

[ 0.76, 0.98 ] 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.
20112012201320142015201620172018201920202021
Associates degrees awarded in Architecture (Degrees awarded)569593468425491478503539585631615
The number of truck drivers in District of Columbia (Laborers)580590400430480500510530640730620




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.




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([569,593,468,425,491,478,503,539,585,631,615,])
array_2 = np.array([580,590,400,430,480,500,510,530,640,730,620,])
array_1_name = "Associates degrees awarded in Architecture"
array_2_name = "The number of truck drivers in District of Columbia"

# 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: 2127 · Black Variable ID: 1209 · Red Variable ID: 17939
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