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Spurious correlation #4,090 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Master's degrees awarded in Engineering and the second variable is The number of court and municipal clerks in New Mexico.  The chart goes from 2012 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As more engineers entered the workforce, they realized the need for highly organized systems to keep track of all their innovative blueprints and designs. This sparked a sudden demand for meticulous court and municipal clerks in New Mexico who could bring order to the chaotic world of engineering paperwork. So, the engineers and clerks formed an unintentional partnership, with the engineers building impressive structures and the clerks masterfully organizing the permits and legal documents needed to make it all happen. It's a tale of two seemingly unrelated professions coming together to create a surprisingly harmonious and bureaucratically efficient society.

Model: dalle-3
Prompt: The image generation prompt will have a picture of a bustling town in New Mexico with a group of engineers proudly holding up their freshly awarded Master's degrees in Engineering. In the background, there will be innovative skyscrapers and bridges that they have contributed to creating. Adjacent to them, a team of diligent court and municipal clerks will be depicted efficiently sorting through piles of legal documents. The visual will show the engineers and clerks unknowingly creating a harmonious partnership, with each group contributing to the creation of a marvelously efficient and organized society. 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: Master's degrees awarded in Engineering and The number of court and municipal clerks in New Mexico. 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: Parallax art Woodblock painting Cyber folk Oragami Cubism
ChatGPT: Cyber folk

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 Master's degrees awarded in Engineering and The number of court and municipal clerks in New Mexico, in the following situation: As more engineers entered the workforce, they realized the need for highly organized systems to keep track of all their innovative blueprints and designs. This sparked a sudden demand for meticulous court and municipal clerks in New Mexico who could bring order to the chaotic world of engineering paperwork. So, the engineers and clerks formed an unintentional partnership, with the engineers building impressive structures and the clerks masterfully organizing the permits and legal documents needed to make it all happen. It's a tale of two seemingly unrelated professions coming together to create a surprisingly harmonious and bureaucratically efficient society.. Keep the description simple.
ChatGPT: In a bustling town in New Mexico, a group of engineers proudly hold up their freshly awarded Master's degrees in Engineering as they stand beside a row of innovative skyscrapers and bridges. Nearby, a team of diligent court and municipal clerks efficiently sorts through piles of legal documents, skillfully organizing the paperwork needed for the engineers' projects. The engineers and clerks have unknowingly created a harmonious partnership, with each group contributing to the creation of a marvelously efficient and organized society.

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: [ Cyber folk ] and depicting this scene: In a bustling town in New Mexico, a group of engineers proudly hold up their freshly awarded Master's degrees in Engineering as they stand beside a row of innovative skyscrapers and bridges. Nearby, a team of diligent court and municipal clerks efficiently sorts through piles of legal documents, skillfully organizing the paperwork needed for the engineers' projects. The engineers and clerks have unknowingly created a harmonious partnership, with each group contributing to the creation of a marvelously efficient and organized society. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: The image generation prompt will have a picture of a bustling town in New Mexico with a group of engineers proudly holding up their freshly awarded Master's degrees in Engineering. In the background, there will be innovative skyscrapers and bridges that they have contributed to creating. Adjacent to them, a team of diligent court and municipal clerks will be depicted efficiently sorting through piles of legal documents. The visual will show the engineers and clerks unknowingly creating a harmonious partnership, with each group contributing to the creation of a marvelously efficient and organized society.

*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 Master's degrees awarded in Engineering caused The number of court and municipal clerks in New Mexico to increase.

AI academic paper

(Because p < 0.01)
Mapping the Marvelous Menagerie: Master's Degrees in Engineering and the Mysteriously Multiplying Municipal Clerks in New Mexico

The Journal of Eccentric Engineering and Enigmatic Employment

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 Master's degrees awarded in Engineering and The number of court and municipal clerks in New Mexico. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Make the title an alliteration.

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 0.9306981 and p < 0.01 for 2012 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]]
Mapping the Marvelous Menagerie: Master's Degrees in Engineering and the Mysteriously Multiplying Municipal Clerks in New Mexico

[[ABSTRACT]]
In this research, we explore the surprisingly strong relationship between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the lovely state of New Mexico. We boldly traversed the data from the National Center for Education Statistics and Bureau of Labor Statistics to unlock this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9306981, with a p-value less than 0.01, spanning the years 2012 to 2021.

It seems that the pursuit of knowledge in engineering may be wielding an unexpected influence on the administrative workforce in New Mexico, much like a handyman wielding a hammer – it's quite a striking correlation indeed. Our study sheds light on the intersection of academic pursuits and workforce dynamics, showing that trends in advanced engineering education could be shaping the landscape of employment in administrative roles. You could say that we've unveiled an "engineeriously clerical" connection – it's as if the gears of academia are intricately intertwined with the bureaucratic machinery.


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 Master's degrees awarded in Engineering and The number of court and municipal clerks in New Mexico. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
Mapping the Marvelous Menagerie: Master's Degrees in Engineering and the Mysteriously Multiplying Municipal Clerks in New Mexico

[[ABSTRACT]]
In this research, we explore the surprisingly strong relationship between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the lovely state of New Mexico. We boldly traversed the data from the National Center for Education Statistics and Bureau of Labor Statistics to unlock this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9306981, with a p-value less than 0.01, spanning the years 2012 to 2021.

It seems that the pursuit of knowledge in engineering may be wielding an unexpected influence on the administrative workforce in New Mexico, much like a handyman wielding a hammer – it's quite a striking correlation indeed. Our study sheds light on the intersection of academic pursuits and workforce dynamics, showing that trends in advanced engineering education could be shaping the landscape of employment in administrative roles. You could say that we've unveiled an "engineeriously clerical" connection – it's as if the gears of academia are intricately intertwined with the bureaucratic machinery.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The dissemination of knowledge and the labor market are often viewed as distinct domains, with little interaction between the two. However, our research delves into the peculiar correlation between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the state of New Mexico. It's as if academia and bureaucracy are engaged in a dance of statistical significance, twirling and tangling their data sets in a lively waltz of correlation.

Let's start with a quip: Why did the engineer break up with the court clerk? They just didn’t have compatible filing systems. Much like the complications of compatibility, our research navigates the complexity of data to uncover the relationship between academic achievements in Engineering and the employment landscape in New Mexico's legal and administrative sphere.

The mesmerizing synergy between advanced engineering education and the burgeoning numbers of municipal clerks in New Mexico has caught our attention. It's a bit like discovering a secret code in the matrix of data – a link that seems improbable at first, much like stumbling upon the punchline of a clever jest unexpectedly.

We embarked on this investigation armed with data from the National Center for Education Statistics and Bureau of Labor Statistics, traversing through intricate statistical models to unravel the intricate bond between engineering education and the employment trends of court and municipal clerks. It's akin to decoding a cryptic crossword puzzle – unfurling the connections between seemingly unrelated clues.

Amidst this web of interconnection, let's pause for another jest: Why did the court clerk go to art school? He wanted to improve his filing technique by mastering the fine art of organization. In a similar vein, our study embarked on the quest to master the art of multivariate analysis to untangle the threads of correlation between education and employment in a delightfully unexpected manner.

Through our analytical journey, we've discovered an astounding correlation coefficient of 0.9306981, accompanied by a p-value less than 0.01, spanning the years 2012 to 2021. This revelation is akin to stumbling upon a hidden treasure map – unlocking the path to an intriguing discovery amidst the trove of data signals.

As we delve further into this peculiar relationship between the pursuit of knowledge in engineering and the proliferation of municipal clerks, we illuminate an unprecedented connection, much like turning a light on in a dimly lit room and discovering a dramaturgic flair of surprises. We hope that our findings will inspire further exploration and spark the curiosity of researchers and policymakers alike. After all, who wouldn't be intrigued by the unlikely juxtaposition of academia and bureaucracy, intertwined in an enigmatic dance of statistical significance?



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 Master's degrees awarded in Engineering and The number of court and municipal clerks in New Mexico. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
Mapping the Marvelous Menagerie: Master's Degrees in Engineering and the Mysteriously Multiplying Municipal Clerks in New Mexico

[[ABSTRACT]]
In this research, we explore the surprisingly strong relationship between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the lovely state of New Mexico. We boldly traversed the data from the National Center for Education Statistics and Bureau of Labor Statistics to unlock this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9306981, with a p-value less than 0.01, spanning the years 2012 to 2021.

It seems that the pursuit of knowledge in engineering may be wielding an unexpected influence on the administrative workforce in New Mexico, much like a handyman wielding a hammer – it's quite a striking correlation indeed. Our study sheds light on the intersection of academic pursuits and workforce dynamics, showing that trends in advanced engineering education could be shaping the landscape of employment in administrative roles. You could say that we've unveiled an "engineeriously clerical" connection – it's as if the gears of academia are intricately intertwined with the bureaucratic machinery.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The dissemination of knowledge and the labor market are often viewed as distinct domains, with little interaction between the two. However, our research delves into the peculiar correlation between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the state of New Mexico. It's as if academia and bureaucracy are engaged in a dance of statistical significance, twirling and tangling their data sets in a lively waltz of correlation.
Let's start with a quip: Why did the engineer break up with the court clerk? They just didn’t have compatible filing systems. Much like the complications of compatibility, our research navigates the complexity of data to uncover the relationship between academic achievements in Engineering and the employment landscape in New Mexico's legal and administrative sphere.
The mesmerizing synergy between advanced engineering education and the burgeoning numbers of municipal clerks in New Mexico has caught our attention. It's a bit like discovering a secret code in the matrix of data – a link that seems improbable at first, much like stumbling upon the punchline of a clever jest unexpectedly.
We embarked on this investigation armed with data from the National Center for Education Statistics and Bureau of Labor Statistics, traversing through intricate statistical models to unravel the intricate bond between engineering education and the employment trends of court and municipal clerks. It's akin to decoding a cryptic crossword puzzle – unfurling the connections between seemingly unrelated clues.
Amidst this web of interconnection, let's pause for another jest: Why did the court clerk go to art school? He wanted to improve his filing technique by mastering the fine art of organization. In a similar vein, our study embarked on the quest to master the art of multivariate analysis to untangle the threads of correlation between education and employment in a delightfully unexpected manner.
Through our analytical journey, we've discovered an astounding correlation coefficient of 0.9306981, accompanied by a p-value less than 0.01, spanning the years 2012 to 2021. This revelation is akin to stumbling upon a hidden treasure map – unlocking the path to an intriguing discovery amidst the trove of data signals.
As we delve further into this peculiar relationship between the pursuit of knowledge in engineering and the proliferation of municipal clerks, we illuminate an unprecedented connection, much like turning a light on in a dimly lit room and discovering a dramaturgic flair of surprises. We hope that our findings will inspire further exploration and spark the curiosity of researchers and policymakers alike. After all, who wouldn't be intrigued by the unlikely juxtaposition of academia and bureaucracy, intertwined in an enigmatic dance of statistical significance?


-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

A multitude of studies have explored the granular details of academia-industry relationships and the dynamics of the labor market. Smith et al. (2015) examined the correlation between advanced education in engineering and the occupational landscape, while Doe and Jones (2018) performed an in-depth analysis of employment trends in administrative roles. These serious-minded studies laid the foundation for our exploration into the mysterious correlation between the number of Master's degrees awarded in Engineering and the burgeoning population of court and municipal clerks in New Mexico.

Now, let's steer this discussion towards some relevant literary works that have influenced our thinking. In "The Tipping Point" by Malcolm Gladwell, the author illuminates the concept of contagious behavior and the unexpected ways in which trends spread through society. Similarly, "Freakonomics" by Steven D. Levitt and Stephen J. Dubner challenges conventional wisdom by uncovering surprising connections in diverse spheres of human activity. These influential works have stimulated our curiosity and critical thinking, guiding our investigation into the thought-provoking correlation between academic pursuits in engineering and the employment trajectories of court and municipal clerks in New Mexico.

Turning to fiction, the classic novel "The Fountainhead" by Ayn Rand follows the professional and personal challenges of an aspiring architect, offering a narrative insight into the ambitions and struggles of individuals in the field of design and construction. Furthermore, "The Hitchhiker's Guide to the Galaxy" by Douglas Adams combines whimsical humor with thought-provoking commentary on the absurdities of life, mirroring the unexpected and often comical nature of our research findings. These fictional masterpieces, albeit unrelated to our empirical investigation, provide an entertaining backdrop to our intellectual endeavors.

As our literature review meanders into unconventional realms of inspiration, it's worth noting that our exploratory journey delved into the unlikeliest of sources. In an unconventional twist, the back of a shampoo bottle, with its unanticipated wit and wisdom, offered a moment of muse during a particularly perplexing statistical analysis. While unorthodox, this unearthing exemplifies the serendipitous nature of research, where inspiration can emerge from the unlikeliest of sources – much like finding a hidden message in a bottle, though significantly less maritime in nature.

In this concoction of scholarly texts and fictional reverie, we extract a blend of insight and amusement, shaping our perspective on the enthralling correlation between Master's degrees in Engineering and the proliferation of court and municipal clerks in the vibrant state of New Mexico.


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 Master's degrees awarded in Engineering and The number of court and municipal clerks in New Mexico. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 2012 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]]
Mapping the Marvelous Menagerie: Master's Degrees in Engineering and the Mysteriously Multiplying Municipal Clerks in New Mexico

[[ABSTRACT]]
In this research, we explore the surprisingly strong relationship between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the lovely state of New Mexico. We boldly traversed the data from the National Center for Education Statistics and Bureau of Labor Statistics to unlock this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9306981, with a p-value less than 0.01, spanning the years 2012 to 2021.

It seems that the pursuit of knowledge in engineering may be wielding an unexpected influence on the administrative workforce in New Mexico, much like a handyman wielding a hammer – it's quite a striking correlation indeed. Our study sheds light on the intersection of academic pursuits and workforce dynamics, showing that trends in advanced engineering education could be shaping the landscape of employment in administrative roles. You could say that we've unveiled an "engineeriously clerical" connection – it's as if the gears of academia are intricately intertwined with the bureaucratic machinery.

[[INTRODUCTION]]
The dissemination of knowledge and the labor market are often viewed as distinct domains, with little interaction between the two. However, our research delves into the peculiar correlation between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the state of New Mexico. It's as if academia and bureaucracy are engaged in a dance of statistical significance, twirling and tangling their data sets in a lively waltz of correlation.
Let's start with a quip: Why did the engineer break up with the court clerk? They just didn’t have compatible filing systems. Much like the complications of compatibility, our research navigates the complexity of data to uncover the relationship between academic achievements in Engineering and the employment landscape in New Mexico's legal and administrative sphere.
The mesmerizing synergy between advanced engineering education and the burgeoning numbers of municipal clerks in New Mexico has caught our attention. It's a bit like discovering a secret code in the matrix of data – a link that seems improbable at first, much like stumbling upon the punchline of a clever jest unexpectedly.
We embarked on this investigation armed with data from the National Center for Education Statistics and Bureau of Labor Statistics, traversing through intricate statistical models to unravel the intricate bond between engineering education and the employment trends of court and municipal clerks. It's akin to decoding a cryptic crossword puzzle – unfurling the connections between seemingly unrelated clues.
Amidst this web of interconnection, let's pause for another jest: Why did the court clerk go to art school? He wanted to improve his filing technique by mastering the fine art of organization. In a similar vein, our study embarked on the quest to master the art of multivariate analysis to untangle the threads of correlation between education and employment in a delightfully unexpected manner.
Through our analytical journey, we've discovered an astounding correlation coefficient of 0.9306981, accompanied by a p-value less than 0.01, spanning the years 2012 to 2021. This revelation is akin to stumbling upon a hidden treasure map – unlocking the path to an intriguing discovery amidst the trove of data signals.
As we delve further into this peculiar relationship between the pursuit of knowledge in engineering and the proliferation of municipal clerks, we illuminate an unprecedented connection, much like turning a light on in a dimly lit room and discovering a dramaturgic flair of surprises. We hope that our findings will inspire further exploration and spark the curiosity of researchers and policymakers alike. After all, who wouldn't be intrigued by the unlikely juxtaposition of academia and bureaucracy, intertwined in an enigmatic dance of statistical significance?


-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To elucidate the captivating correlation between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in New Mexico, our research employed a multifaceted methodology designed to uncover the nuanced relationship between these seemingly distinct domains.

First, we conducted a comprehensive review of the collected data from the National Center for Education Statistics and Bureau of Labor Statistics. Our research team meticulously combed through the databases, akin to seasoned detectives seeking clues, capturing minute details and trends from 2012 to 2021. This process involved adeptly navigating the labyrinth of statistics, much akin to conducting a symphony of data analysis – harmonizing disparate figures into a coherent melody of insight.

Brimming with enthusiasm, we then employed a series of esoteric statistical techniques, including multivariate regression analysis, time-series modeling, and spatial-temporal data mapping. These methods were skillfully interwoven like an intricate tapestry of analysis, illuminating the complex web of relationships between academic achievements in Engineering and the labor market for court and municipal clerks in New Mexico. It's as if we were unraveling a mathematical mystery novel, with each statistical model serving as a new chapter, leading us closer to the denouement of correlation.

Now, here's a playful interlude: Why did the engineer bring a pencil to the courtroom? He wanted to draw his own conclusions. In a similar vein, our research harnessed the power of data visualization techniques, crafting captivating graphs and interactive maps to vividly illustrate the connection between Master's degrees in Engineering and the burgeoning numbers of municipal clerks in New Mexico. It's as if we were sketching the contours of correlation with a statistical pencil, drawing our own inferences and conclusions.

Furthermore, we employed an innovative approach by integrating machine learning algorithms to discern hidden patterns and predictive trends within the dataset. This process was akin to training a mathematical sleuth, tasking it with the mission of identifying subtle links and echoes between the educational and labor spheres. The result was an augmented capacity to forecast potential shifts and developments in the workforce landscape, as if we had equipped ourselves with a crystal ball of statistical foresight.

In keeping with the spirit of rigorous inquiry, we also engaged in robust sensitivity and outlier analyses, ensuring that our findings were resilient against potential confounding variables and anomalous data points. This process involved meticulous scrutiny akin to inspecting a puzzle for misfitting pieces, assuring that the puzzle of correlation was assembled with precision and accuracy.

In summary, our methodology represents a harmonious symphony of data collection, statistical modeling, and analytical ingenuity, unveiling the remarkable nexus between engineering education and the dynamic employment landscape of court and municipal clerks in the illustrious state of New Mexico.


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 Master's degrees awarded in Engineering and The number of court and municipal clerks in New Mexico. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 2012 to 2021, you found a correlation 0.9306981, r-squared of 0.8661990, 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]]
Mapping the Marvelous Menagerie: Master's Degrees in Engineering and the Mysteriously Multiplying Municipal Clerks in New Mexico

[[ABSTRACT]]
In this research, we explore the surprisingly strong relationship between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the lovely state of New Mexico. We boldly traversed the data from the National Center for Education Statistics and Bureau of Labor Statistics to unlock this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9306981, with a p-value less than 0.01, spanning the years 2012 to 2021.

It seems that the pursuit of knowledge in engineering may be wielding an unexpected influence on the administrative workforce in New Mexico, much like a handyman wielding a hammer – it's quite a striking correlation indeed. Our study sheds light on the intersection of academic pursuits and workforce dynamics, showing that trends in advanced engineering education could be shaping the landscape of employment in administrative roles. You could say that we've unveiled an "engineeriously clerical" connection – it's as if the gears of academia are intricately intertwined with the bureaucratic machinery.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The dissemination of knowledge and the labor market are often viewed as distinct domains, with little interaction between the two. However, our research delves into the peculiar correlation between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the state of New Mexico. It's as if academia and bureaucracy are engaged in a dance of statistical significance, twirling and tangling their data sets in a lively waltz of correlation.
Let's start with a quip: Why did the engineer break up with the court clerk? They just didn’t have compatible filing systems. Much like the complications of compatibility, our research navigates the complexity of data to uncover the relationship between academic achievements in Engineering and the employment landscape in New Mexico's legal and administrative sphere.
The mesmerizing synergy between advanced engineering education and the burgeoning numbers of municipal clerks in New Mexico has caught our attention. It's a bit like discovering a secret code in the matrix of data – a link that seems improbable at first, much like stumbling upon the punchline of a clever jest unexpectedly.
We embarked on this investigation armed with data from the National Center for Education Statistics and Bureau of Labor Statistics, traversing through intricate statistical models to unravel the intricate bond between engineering education and the employment trends of court and municipal clerks. It's akin to decoding a cryptic crossword puzzle – unfurling the connections between seemingly unrelated clues.
Amidst this web of interconnection, let's pause for another jest: Why did the court clerk go to art school? He wanted to improve his filing technique by mastering the fine art of organization. In a similar vein, our study embarked on the quest to master the art of multivariate analysis to untangle the threads of correlation between education and employment in a delightfully unexpected manner.
Through our analytical journey, we've discovered an astounding correlation coefficient of 0.9306981, accompanied by a p-value less than 0.01, spanning the years 2012 to 2021. This revelation is akin to stumbling upon a hidden treasure map – unlocking the path to an intriguing discovery amidst the trove of data signals.
As we delve further into this peculiar relationship between the pursuit of knowledge in engineering and the proliferation of municipal clerks, we illuminate an unprecedented connection, much like turning a light on in a dimly lit room and discovering a dramaturgic flair of surprises. We hope that our findings will inspire further exploration and spark the curiosity of researchers and policymakers alike. After all, who wouldn't be intrigued by the unlikely juxtaposition of academia and bureaucracy, intertwined in an enigmatic dance of statistical significance?


-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of the relationship between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the charming state of New Mexico revealed a remarkably robust correlation. The correlation coefficient of 0.9306981 suggests a strong positive relationship between these two seemingly disparate variables. It appears that the advanced knowledge and skills acquired through engineering education are intricately linked to the workforce dynamics of court and municipal clerks in New Mexico, much like how a wrench is intricately linked to a toolbox – an indispensable correlation indeed.

The observed correlation is substantiated by an r-squared value of 0.8661990, signifying that approximately 86.62% of the variation in the employment of court and municipal clerks in New Mexico can be explained by the number of Master's degrees awarded in Engineering. One might say that this correlation is as clear as a blueprint, outlining the interconnectedness of academic pursuits and administrative employment.

The significance of this relationship is further underscored by the p-value being less than 0.01, indicating that the observed correlation is unlikely to have occurred by chance. In simpler terms, the likelihood of this correlation being a fluke is smaller than the chances of finding a needle in a haystack, which is to say – it's quite remarkable.

Furthermore, our findings are visually represented in Figure 1, a scatterplot that vividly portrays the strong positive correlation between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in New Mexico. The scatterplot illustrates how the pursuit of advanced engineering education seems to be harmoniously aligned with the employment trends in administrative roles, much like a well-choreographed dance routine – an unexpected yet captivating display of correlation.

In essence, our research unravels an intriguing coherence between the advancement of engineering education and the proliferation of court and municipal clerks in New Mexico. This peculiar correlation is as unexpected as finding a screwdriver in a pencil case – it's unexpected, yet undeniably fitting. Our study sheds light on the interplay of academic achievements and workforce dynamics, offering a unique perspective on the symbiotic relationship between academia and bureaucracy.


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 Master's degrees awarded in Engineering and The number of court and municipal clerks in New Mexico. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
Mapping the Marvelous Menagerie: Master's Degrees in Engineering and the Mysteriously Multiplying Municipal Clerks in New Mexico

[[ABSTRACT]]
In this research, we explore the surprisingly strong relationship between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the lovely state of New Mexico. We boldly traversed the data from the National Center for Education Statistics and Bureau of Labor Statistics to unlock this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9306981, with a p-value less than 0.01, spanning the years 2012 to 2021.

It seems that the pursuit of knowledge in engineering may be wielding an unexpected influence on the administrative workforce in New Mexico, much like a handyman wielding a hammer – it's quite a striking correlation indeed. Our study sheds light on the intersection of academic pursuits and workforce dynamics, showing that trends in advanced engineering education could be shaping the landscape of employment in administrative roles. You could say that we've unveiled an "engineeriously clerical" connection – it's as if the gears of academia are intricately intertwined with the bureaucratic machinery.

[[LITERATURE REVIEW]]
A multitude of studies have explored the granular details of academia-industry relationships and the dynamics of the labor market. Smith et al. (2015) examined the correlation between advanced education in engineering and the occupational landscape, while Doe and Jones (2018) performed an in-depth analysis of employment trends in administrative roles. These serious-minded studies laid the foundation for our exploration into the mysterious correlation between the number of Master's degrees awarded in Engineering and the burgeoning population of court and municipal clerks in New Mexico.
Now, let's steer this discussion towards some relevant literary works that have influenced our thinking. In "The Tipping Point" by Malcolm Gladwell, the author illuminates the concept of contagious behavior and the unexpected ways in which trends spread through society. Similarly, "Freakonomics" by Steven D. Levitt and Stephen J. Dubner challenges conventional wisdom by uncovering surprising connections in diverse spheres of human activity. These influential works have stimulated our curiosity and critical thinking, guiding our investigation into the thought-provoking correlation between academic pursuits in engineering and the employment trajectories of court and municipal clerks in New Mexico.
Turning to fiction, the classic novel "The Fountainhead" by Ayn Rand follows the professional and personal challenges of an aspiring architect, offering a narrative insight into the ambitions and struggles of individuals in the field of design and construction. Furthermore, "The Hitchhiker's Guide to the Galaxy" by Douglas Adams combines whimsical humor with thought-provoking commentary on the absurdities of life, mirroring the unexpected and often comical nature of our research findings. These fictional masterpieces, albeit unrelated to our empirical investigation, provide an entertaining backdrop to our intellectual endeavors.
As our literature review meanders into unconventional realms of inspiration, it's worth noting that our exploratory journey delved into the unlikeliest of sources. In an unconventional twist, the back of a shampoo bottle, with its unanticipated wit and wisdom, offered a moment of muse during a particularly perplexing statistical analysis. While unorthodox, this unearthing exemplifies the serendipitous nature of research, where inspiration can emerge from the unlikeliest of sources – much like finding a hidden message in a bottle, though significantly less maritime in nature.
In this concoction of scholarly texts and fictional reverie, we extract a blend of insight and amusement, shaping our perspective on the enthralling correlation between Master's degrees in Engineering and the proliferation of court and municipal clerks in the vibrant state of New Mexico.

[[RESULTS]]
The analysis of the relationship between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the charming state of New Mexico revealed a remarkably robust correlation. The correlation coefficient of 0.9306981 suggests a strong positive relationship between these two seemingly disparate variables. It appears that the advanced knowledge and skills acquired through engineering education are intricately linked to the workforce dynamics of court and municipal clerks in New Mexico, much like how a wrench is intricately linked to a toolbox – an indispensable correlation indeed.
The observed correlation is substantiated by an r-squared value of 0.8661990, signifying that approximately 86.62% of the variation in the employment of court and municipal clerks in New Mexico can be explained by the number of Master's degrees awarded in Engineering. One might say that this correlation is as clear as a blueprint, outlining the interconnectedness of academic pursuits and administrative employment.
The significance of this relationship is further underscored by the p-value being less than 0.01, indicating that the observed correlation is unlikely to have occurred by chance. In simpler terms, the likelihood of this correlation being a fluke is smaller than the chances of finding a needle in a haystack, which is to say – it's quite remarkable.
Furthermore, our findings are visually represented in Figure 1, a scatterplot that vividly portrays the strong positive correlation between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in New Mexico. The scatterplot illustrates how the pursuit of advanced engineering education seems to be harmoniously aligned with the employment trends in administrative roles, much like a well-choreographed dance routine – an unexpected yet captivating display of correlation.
In essence, our research unravels an intriguing coherence between the advancement of engineering education and the proliferation of court and municipal clerks in New Mexico. This peculiar correlation is as unexpected as finding a screwdriver in a pencil case – it's unexpected, yet undeniably fitting. Our study sheds light on the interplay of academic achievements and workforce dynamics, offering a unique perspective on the symbiotic relationship between academia and bureaucracy.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The findings of our study have unveiled a compelling and surprisingly strong correlation between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the delightful state of New Mexico. This correlation coefficient of 0.9306981 supports the prior research conducted by Smith et al. (2015) and Doe and Jones (2018), confirming the influence of advanced education in engineering on the occupational landscape of administrative roles in a specific geographical area. It's almost as if these two seemingly unrelated entities are engaged in an intricate dance – not unlike a tango between a mathematician and an architect.

Our results, with an r-squared value of 0.8661990, suggest that approximately 86.62% of the variation in the employment of court and municipal clerks in New Mexico can be elucidated by the number of Master's degrees awarded in Engineering. This aligns with the concept of contagious behavior elucidated in "The Tipping Point" by Malcolm Gladwell, as it appears that the pursuit of engineering knowledge has a contagious influence on the administrative workforce, much like a viral meme spreading through the digital cosmos.

The p-value, being less than 0.01, debunks any notion of chance, affirming the authenticity and robustness of the observed correlation. This discovery is as unlikely as stumbling across a treasure map in a textbook on statistical analysis, but the evidence is unequivocal – the connection is as real as a forged steel.

Our visually represented findings in Figure 1 vividly illustrate the strong positive correlation between the pursuit of advanced engineering education and the employment statistics of court and municipal clerks in New Mexico. The scatterplot showcases this bond, much like the intertwined ribbons in a maypole dance – a seemingly unexpected yet harmonious correlation.

In essence, our research corroborates the notion that trends in advanced engineering education could be shaping the administrative employment landscape, bringing forth an "engineeriously clerical" connection that is as surprising as discovering a hidden compartment in a filing cabinet. Our study opens the door to further exploration of the intricate and often unforeseen links between academia and bureaucracy, shedding light on the serendipitous interplay between these two seemingly disparate domains.


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 Master's degrees awarded in Engineering and The number of court and municipal clerks in New Mexico. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
Mapping the Marvelous Menagerie: Master's Degrees in Engineering and the Mysteriously Multiplying Municipal Clerks in New Mexico

[[ABSTRACT]]
In this research, we explore the surprisingly strong relationship between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the lovely state of New Mexico. We boldly traversed the data from the National Center for Education Statistics and Bureau of Labor Statistics to unlock this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9306981, with a p-value less than 0.01, spanning the years 2012 to 2021.

It seems that the pursuit of knowledge in engineering may be wielding an unexpected influence on the administrative workforce in New Mexico, much like a handyman wielding a hammer – it's quite a striking correlation indeed. Our study sheds light on the intersection of academic pursuits and workforce dynamics, showing that trends in advanced engineering education could be shaping the landscape of employment in administrative roles. You could say that we've unveiled an "engineeriously clerical" connection – it's as if the gears of academia are intricately intertwined with the bureaucratic machinery.

[[INTRDUCTION]]
The dissemination of knowledge and the labor market are often viewed as distinct domains, with little interaction between the two. However, our research delves into the peculiar correlation between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the state of New Mexico. It's as if academia and bureaucracy are engaged in a dance of statistical significance, twirling and tangling their data sets in a lively waltz of correlation.
Let's start with a quip: Why did the engineer break up with the court clerk? They just didn’t have compatible filing systems. Much like the complications of compatibility, our research navigates the complexity of data to uncover the relationship between academic achievements in Engineering and the employment landscape in New Mexico's legal and administrative sphere.
The mesmerizing synergy between advanced engineering education and the burgeoning numbers of municipal clerks in New Mexico has caught our attention. It's a bit like discovering a secret code in the matrix of data – a link that seems improbable at first, much like stumbling upon the punchline of a clever jest unexpectedly.
We embarked on this investigation armed with data from the National Center for Education Statistics and Bureau of Labor Statistics, traversing through intricate statistical models to unravel the intricate bond between engineering education and the employment trends of court and municipal clerks. It's akin to decoding a cryptic crossword puzzle – unfurling the connections between seemingly unrelated clues.
Amidst this web of interconnection, let's pause for another jest: Why did the court clerk go to art school? He wanted to improve his filing technique by mastering the fine art of organization. In a similar vein, our study embarked on the quest to master the art of multivariate analysis to untangle the threads of correlation between education and employment in a delightfully unexpected manner.
Through our analytical journey, we've discovered an astounding correlation coefficient of 0.9306981, accompanied by a p-value less than 0.01, spanning the years 2012 to 2021. This revelation is akin to stumbling upon a hidden treasure map – unlocking the path to an intriguing discovery amidst the trove of data signals.
As we delve further into this peculiar relationship between the pursuit of knowledge in engineering and the proliferation of municipal clerks, we illuminate an unprecedented connection, much like turning a light on in a dimly lit room and discovering a dramaturgic flair of surprises. We hope that our findings will inspire further exploration and spark the curiosity of researchers and policymakers alike. After all, who wouldn't be intrigued by the unlikely juxtaposition of academia and bureaucracy, intertwined in an enigmatic dance of statistical significance?


[[RESULTS]]
The analysis of the relationship between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the charming state of New Mexico revealed a remarkably robust correlation. The correlation coefficient of 0.9306981 suggests a strong positive relationship between these two seemingly disparate variables. It appears that the advanced knowledge and skills acquired through engineering education are intricately linked to the workforce dynamics of court and municipal clerks in New Mexico, much like how a wrench is intricately linked to a toolbox – an indispensable correlation indeed.
The observed correlation is substantiated by an r-squared value of 0.8661990, signifying that approximately 86.62% of the variation in the employment of court and municipal clerks in New Mexico can be explained by the number of Master's degrees awarded in Engineering. One might say that this correlation is as clear as a blueprint, outlining the interconnectedness of academic pursuits and administrative employment.
The significance of this relationship is further underscored by the p-value being less than 0.01, indicating that the observed correlation is unlikely to have occurred by chance. In simpler terms, the likelihood of this correlation being a fluke is smaller than the chances of finding a needle in a haystack, which is to say – it's quite remarkable.
Furthermore, our findings are visually represented in Figure 1, a scatterplot that vividly portrays the strong positive correlation between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in New Mexico. The scatterplot illustrates how the pursuit of advanced engineering education seems to be harmoniously aligned with the employment trends in administrative roles, much like a well-choreographed dance routine – an unexpected yet captivating display of correlation.
In essence, our research unravels an intriguing coherence between the advancement of engineering education and the proliferation of court and municipal clerks in New Mexico. This peculiar correlation is as unexpected as finding a screwdriver in a pencil case – it's unexpected, yet undeniably fitting. Our study sheds light on the interplay of academic achievements and workforce dynamics, offering a unique perspective on the symbiotic relationship between academia and bureaucracy.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has uncovered a remarkable correlation between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the charming state of New Mexico. It appears that the pursuit of advanced engineering education is closely entwined with the landscape of administrative employment in a manner that is as surprising as finding a "watt" in a "bolt" – a truly electrifying connection.

The robust correlation coefficient of 0.9306981 and the substantial r-squared value of 0.8661990 emphasize the strong positive relationship between these seemingly unrelated variables, painting a picture as clear as an architect's blueprint. It seems that the pursuit of knowledge in engineering has a notable impact on the dynamics of administrative employment, akin to a well-oiled machine working in tandem – it's a fitting correlation indeed.

Additionally, the p-value being less than 0.01 cements the statistical significance of this finding, making it as unlikely to have occurred by chance as spotting a rare bird in a crowded aviary – a truly remarkable discovery. Our results, vividly encapsulated in Figure 1, illustrate this unexpected yet captivating dance of correlation between the pursuit of advanced engineering education and the employment trends in administrative roles, much like a choreographed performance at a data-driven ball.

We must stress the gravity of our findings, just as an engineer stresses the importance of structural integrity. It is evident that the symbiotic relationship between academia and bureaucracy in the context of New Mexico's workforce is as distinct as a unique element in the periodic table – an unexpected but essential part of the narrative.

In light of these insights, it is our firm belief that further research in this area would be as unnecessary as a spanner in a knitting kit – our findings have illuminated this "engineeriously clerical" connection to a degree that underlines the completion of this particular investigation.


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 Mapping the Marvelous Menagerie: Master's Degrees in Engineering and the Mysteriously Multiplying Municipal Clerks in New Mexico. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Eccentric Engineering and Enigmatic Employment


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 Mapping the Marvelous Menagerie: Master's Degrees in Engineering and the Mysteriously Multiplying Municipal Clerks in New Mexico. Respond only with the name of a fictional organization.

ChatGPT:

The Society for the Advancement of Multidisciplinary Research in Nonsense 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 Mapping the Marvelous Menagerie: Master's Degrees in Engineering and the Mysteriously Multiplying Municipal Clerks in New Mexico with an abstract of In this research, we explore the surprisingly strong relationship between the number of Master's degrees awarded in Engineering and the employment statistics of court and municipal clerks in the lovely state of New Mexico. We boldly traversed the data from the National Center for Education Statistics and Bureau of Labor Statistics to unlock this enigmatic connection. Our findings revealed a striking correlation coefficient of 0.9306981, with a p-value less than 0.01, spanning the years 2012 to 2021.
It seems that the pursuit of knowledge in engineering may be wielding an unexpected influence on the administrative workforce in New Mexico, much like a handyman wielding a hammer – it's quite a striking correlation indeed. Our study sheds light on the intersection of academic pursuits and workforce dynamics, showing that trends in advanced engineering education could be shaping the landscape of employment in administrative roles. You could say that we've unveiled an "engineeriously clerical" connection – it's as if the gears of academia are intricately intertwined with the bureaucratic machinery.

ChatGPT:

Master's degrees in Engineering, employment statistics, court clerks, municipal clerks, New Mexico, National Center for Education Statistics, Bureau of Labor Statistics, correlation coefficient, p-value, workforce dynamics, academic pursuits, administrative roles, engineering education, employment trends, advanced degrees, workforce impact

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



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Data details

Master's degrees awarded in Engineering
Detailed data title: Master's degrees conferred by postsecondary institutions in Engineering
Source: National Center for Education Statistics
See what else correlates with Master's degrees awarded in Engineering

The number of court and municipal clerks in New Mexico
Detailed data title: BLS estimate of court, municipal, and license clerks in New Mexico
Source: Bureau of Larbor Statistics
See what else correlates with The number of court and municipal clerks in New Mexico

Correlation r = 0.9306981 (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 = 0.8661990 (Coefficient of determination)
This means 86.6% of the change in the one variable (i.e., The number of court and municipal clerks in New Mexico) is predictable based on the change in the other (i.e., Master's degrees awarded in Engineering) over the 10 years from 2012 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 9.3E-5. 0.0000927630588360729600000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.93 in 0.0093% of random cases. Said differently, if you correlated 10,780 random variables Which I absolutely did.
with the same 9 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 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, 0.98 ] 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.
2012201320142015201620172018201920202021
Master's degrees awarded in Engineering (Degrees awarded)40323404204237646117516465282651723497014727747257
The number of court and municipal clerks in New Mexico (Laborers)640600670620133013201230110010401040




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([40323,40420,42376,46117,51646,52826,51723,49701,47277,47257,])
array_2 = np.array([640,600,670,620,1330,1320,1230,1100,1040,1040,])
array_1_name = "Master's degrees awarded in Engineering"
array_2_name = "The number of court and municipal clerks in New Mexico"

# 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: 4090 · Black Variable ID: 1320 · Red Variable ID: 11903
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