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Spurious correlation #1,059 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Petroluem consumption in Azerbaijan and the second variable is The number of farm equipment mechanics in Alabama.  The chart goes from 2010 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As Azerbaijan's demand for petroluem grew, they started importing more petro-dollars from Alabama, leading to a spike in the sales of farm equipment. This, in turn, created a pressing need for additional farm equipment mechanics in Alabama to keep the increasingly busy farms up and running. It's like a chain reaction, but with a lot more grease and horsepower!

Model: dalle-3
Prompt: [ Hyper-realistic ] In a small town in Alabama, a bustling farm equipment repair shop dominates the scene, its exterior bathed in warm, golden sunlight. The air is thick with the distinct scent of gasoline and engine oil as seasoned mechanics deftly maneuver around clunky tractors and other agricultural machinery, honing their craft with precision and expertise. Each mechanic is meticulously engulfed in their tasks, their movements captured in immense detail, showcasing their dedication and skill. Meanwhile, in a vibrant city in Azerbaijan, the radiance of numerous city lights illuminates a gas station where a line of diverse cars patiently waits to be fueled. The bustling activity reveals diverse individuals rapidly filling up their vehicles as the scene showcases an eclectic mix of car models and vibrant city life, all seamlessly connected by the allure of gasoline. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: Rise in Petroleum Consumption in Azerbaijan Linked to Surge in Alabama's Farm Equipment Mechanics - Experts Attribute Increase to Trans-Continental Mechanic Migration Due to Irresistible Scent of Gasoline.. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: Macabre Steampunk Realistic An image that looks like it is a scene from 'Star Wars' Hyper-realistic
ChatGPT: Hyper-realistic

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. Rise in Petroleum Consumption in Azerbaijan Linked to Surge in Alabama's Farm Equipment Mechanics - Experts Attribute Increase to Trans-Continental Mechanic Migration Due to Irresistible Scent of Gasoline.
ChatGPT: In a small town in Alabama, a busy farm equipment repair shop bustles with activity as mechanics work on tractors and machinery. The air is filled with the scent of gasoline and engine oil. Meanwhile, in a bustling city in Azerbaijan, a line of cars waits at a gas station, and people fuel up their vehicles under the bright city lights. The simultaneous scenes depict the rise in petroleum consumption in Azerbaijan and the surge in farm equipment mechanics in Alabama, linked by the irresistible scent of gasoline drawing mechanics to locations where it is in high demand.

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: [ Hyper-realistic ] and depicting this scene: In a small town in Alabama, a busy farm equipment repair shop bustles with activity as mechanics work on tractors and machinery. The air is filled with the scent of gasoline and engine oil. Meanwhile, in a bustling city in Azerbaijan, a line of cars waits at a gas station, and people fuel up their vehicles under the bright city lights. The simultaneous scenes depict the rise in petroleum consumption in Azerbaijan and the surge in farm equipment mechanics in Alabama, linked by the irresistible scent of gasoline drawing mechanics to locations where it is in high demand. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Hyper-realistic ] In a small town in Alabama, a bustling farm equipment repair shop dominates the scene, its exterior bathed in warm, golden sunlight. The air is thick with the distinct scent of gasoline and engine oil as seasoned mechanics deftly maneuver around clunky tractors and other agricultural machinery, honing their craft with precision and expertise. Each mechanic is meticulously engulfed in their tasks, their movements captured in immense detail, showcasing their dedication and skill. Meanwhile, in a vibrant city in Azerbaijan, the radiance of numerous city lights illuminates a gas station where a line of diverse cars patiently waits to be fueled. The bustling activity reveals diverse individuals rapidly filling up their vehicles as the scene showcases an eclectic mix of car models and vibrant city life, all seamlessly connected by the allure of gasoline.

*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 Petroluem consumption in Azerbaijan caused The number of farm equipment mechanics in Alabama to increase.

AI academic paper

(Because p < 0.01)
Fueling the Farm: A Crude Connection Between Petroleum Consumption in Azerbaijan and the Number of Farm Equipment Mechanics in Alabama

The Journal of Energy Economics and Agricultural Labor Trends

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 Petroluem consumption in Azerbaijan and The number of farm equipment mechanics in Alabama. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, just make it sound clever.

Your research team used data from Energy Information Administration and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.9283473 and p < 0.01 for 2010 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]]
"Fueling the Farm: A Crude Connection Between Petroleum Consumption in Azerbaijan and the Number of Farm Equipment Mechanics in Alabama"

[[ABSTRACT]]
This paper delves into the curious correlation between the per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. By analyzing data from the Energy Information Administration and the Bureau of Labor Statistics spanning the years 2010 to 2021, we unearthed a striking correlation coefficient of 0.9283473 and a p-value of less than 0.01. Our findings suggest a significant relationship between these seemingly disparate factors, providing a quirky insight into the interplay of global energy usage and local labor markets. Our results have implications for policymakers, analysts, and anyone with an affinity for unexpected connections in the world of economics and energy.


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 Petroluem consumption in Azerbaijan and The number of farm equipment mechanics in Alabama. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Fueling the Farm: A Crude Connection Between Petroleum Consumption in Azerbaijan and the Number of Farm Equipment Mechanics in Alabama"

[[ABSTRACT]]
This paper delves into the curious correlation between the per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. By analyzing data from the Energy Information Administration and the Bureau of Labor Statistics spanning the years 2010 to 2021, we unearthed a striking correlation coefficient of 0.9283473 and a p-value of less than 0.01. Our findings suggest a significant relationship between these seemingly disparate factors, providing a quirky insight into the interplay of global energy usage and local labor markets. Our results have implications for policymakers, analysts, and anyone with an affinity for unexpected connections in the world of economics and energy.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The world of economics and energy often brings to light unexpected connections and correlations that may seem far-fetched at first glance. In this study, we embark on a journey to explore the intriguing link between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. While the casual observer may raise an eyebrow at the juxtaposition of these two seemingly unrelated variables, our analysis uncovers a compelling relationship that warrants further investigation.

Azerbaijan, the land where the legendary oil fields of Baku have captured the imagination of oil enthusiasts for centuries, serves as the backdrop for our first variable in this curious equation. Meanwhile, the southern charm of Alabama, known for its scenic countryside and agricultural heritage, sets the stage for the second variable – the number of farm equipment mechanics. The collision of these disparate worlds in our analysis is a testament to the unexpected twists that can be found in the labyrinth of data analysis.

Before diving into the depths of our findings, it is essential to underscore the foundation of our inquiry. The Energy Information Administration (EIA) provides valuable insights into the petroleum consumption patterns in Azerbaijan, offering a glimpse into the fuel preferences and demands of this nation. On the other hand, the Bureau of Labor Statistics (BLS) furnishes us with the data on the number of farm equipment mechanics in the heart of Dixie – Alabama. These robust sources lay the groundwork for our statistical exploration, allowing us to unravel the hidden thread that binds these variables together.

Now, one may ponder: What could possibly link the gallons of fuel being consumed in the bustling streets of Baku to the wrenches and machinery tinkering in the cotton fields of Alabama? Our study aims to shed light on this puzzling relationship and bring forth meaningful insights that transcend the boundaries of conventional economic wisdom. The confluence of global energy trends and local labor dynamics is an engrossing puzzle that demands our attention, offering a beguiling glimpse into the complexity of interconnected systems.

As we journey through the labyrinth of data and statistical analysis, it becomes evident that the world of economics and energy is not only a playground for the serious-minded but also a canvas for the whimsical and unexpected. Our quest uncovers a correlation coefficient of 0.9283473 and a p-value that dances beneath the threshold of significance, underscoring the robustness of the relationship between these variables. The allure of such a striking correlation invites us to ponder the subtle dance of causation and correlation, reminding us that in the realm of statistical exploration, truth can often be found in the unlikeliest of bedfellows.

Join us as we unravel the delightful dance between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama, for in this intricate web of statistical connections, lies a trove of wisdom waiting to be unearthed.


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 Petroluem consumption in Azerbaijan and The number of farm equipment mechanics in Alabama. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
"Fueling the Farm: A Crude Connection Between Petroleum Consumption in Azerbaijan and the Number of Farm Equipment Mechanics in Alabama"

[[ABSTRACT]]
This paper delves into the curious correlation between the per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. By analyzing data from the Energy Information Administration and the Bureau of Labor Statistics spanning the years 2010 to 2021, we unearthed a striking correlation coefficient of 0.9283473 and a p-value of less than 0.01. Our findings suggest a significant relationship between these seemingly disparate factors, providing a quirky insight into the interplay of global energy usage and local labor markets. Our results have implications for policymakers, analysts, and anyone with an affinity for unexpected connections in the world of economics and energy.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The world of economics and energy often brings to light unexpected connections and correlations that may seem far-fetched at first glance. In this study, we embark on a journey to explore the intriguing link between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. While the casual observer may raise an eyebrow at the juxtaposition of these two seemingly unrelated variables, our analysis uncovers a compelling relationship that warrants further investigation.
Azerbaijan, the land where the legendary oil fields of Baku have captured the imagination of oil enthusiasts for centuries, serves as the backdrop for our first variable in this curious equation. Meanwhile, the southern charm of Alabama, known for its scenic countryside and agricultural heritage, sets the stage for the second variable – the number of farm equipment mechanics. The collision of these disparate worlds in our analysis is a testament to the unexpected twists that can be found in the labyrinth of data analysis.
Before diving into the depths of our findings, it is essential to underscore the foundation of our inquiry. The Energy Information Administration (EIA) provides valuable insights into the petroleum consumption patterns in Azerbaijan, offering a glimpse into the fuel preferences and demands of this nation. On the other hand, the Bureau of Labor Statistics (BLS) furnishes us with the data on the number of farm equipment mechanics in the heart of Dixie – Alabama. These robust sources lay the groundwork for our statistical exploration, allowing us to unravel the hidden thread that binds these variables together.
Now, one may ponder: What could possibly link the gallons of fuel being consumed in the bustling streets of Baku to the wrenches and machinery tinkering in the cotton fields of Alabama? Our study aims to shed light on this puzzling relationship and bring forth meaningful insights that transcend the boundaries of conventional economic wisdom. The confluence of global energy trends and local labor dynamics is an engrossing puzzle that demands our attention, offering a beguiling glimpse into the complexity of interconnected systems.
As we journey through the labyrinth of data and statistical analysis, it becomes evident that the world of economics and energy is not only a playground for the serious-minded but also a canvas for the whimsical and unexpected. Our quest uncovers a correlation coefficient of 0.9283473 and a p-value that dances beneath the threshold of significance, underscoring the robustness of the relationship between these variables. The allure of such a striking correlation invites us to ponder the subtle dance of causation and correlation, reminding us that in the realm of statistical exploration, truth can often be found in the unlikeliest of bedfellows.
Join us as we unravel the delightful dance between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama, for in this intricate web of statistical connections, lies a trove of wisdom waiting to be unearthed.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In "Smith and Doe (2020)," the authors find a parallel between the per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. Their study lays the groundwork for our investigation, delving into the intricate web of global energy usage and local labor markets. Drawing from the venerable tradition of economic analysis, the authors unearth a correlation coefficient that piques our interest and sets the stage for further exploration.

Expanding upon the foundation set forth by Smith and Doe, "Jones et al. (2018)" offer a nuanced perspective on the interplay between petroleum consumption and labor dynamics. Their study, while rigorous and insightful, leaves ample room for the infusion of humor and unexpected insights. Indeed, as we wade into the depths of this peculiar correlation, it becomes increasingly clear that the marriage of Azerbaijani fuel trends and Alabama's machinery mechanics is not merely a dry statistical affair, but a rich tapestry weaving together the whimsical and the wondrous.

Venturing beyond the realm of conventional economic discourse, "Petroleum Patterns: A Global Overview" by A. Barrel and O. Spill offers a comprehensive exploration of the quirky tendencies of petroleum consumption across the globe. As we peruse the pages of this illuminating text, a delightful array of puns and jests grace the margins, reminding us that even the most serious of subjects can be tinged with levity.

Turning to the literary realm, "The Grapes of Wrath" by John Steinbeck beckons us into the heart of agricultural America, providing a narrative backdrop for our investigation into the labor dynamics of Alabama's farmlands. While seemingly unrelated to the world of petroleum consumption, this classic work serves as a poignant reminder of the interconnectedness of human endeavors and the unexpected twists that permeate our economic landscape.

Simultaneously, "Oil!: A Novel" by Upton Sinclair beckons forth a tale of ambition, treachery, and, yes, petroleum - offering a fictional lens through which we can glean insights into the complexities of energy markets and the labor forces that sustain them. In the world of literature, as in statistical analysis, one must always be prepared for the unexpected, for the most profound truths often emerge from the unlikeliest of narratives.

Shifting gears to a lighthearted note, the animated series "Bob the Builder" and "Handy Manny" regale us with the endearing escapades of skilled mechanics and handymen, beckoning us to contemplate the role of labor expertise in the maintenance of our built environment. While ostensibly aimed at a younger audience, these charming tales offer a whimsical perspective on the world of mechanical tinkering and the vital role it plays in sustaining our day-to-day livelihoods.

In this eclectic array of sources, we find a reflection of the multifaceted relationship between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. As we navigate this peculiar avenue of inquiry, it becomes increasingly clear that the intersection of economics, energy, and labor is not merely a dry terrain of statistical analysis, but a vibrant tapestry interwoven with humor, whimsy, and unexpected connections.


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 Petroluem consumption in Azerbaijan and The number of farm equipment mechanics in Alabama. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 Energy Information Administration and Bureau of Larbor Statistics . You used data from 2010 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]]
"Fueling the Farm: A Crude Connection Between Petroleum Consumption in Azerbaijan and the Number of Farm Equipment Mechanics in Alabama"

[[ABSTRACT]]
This paper delves into the curious correlation between the per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. By analyzing data from the Energy Information Administration and the Bureau of Labor Statistics spanning the years 2010 to 2021, we unearthed a striking correlation coefficient of 0.9283473 and a p-value of less than 0.01. Our findings suggest a significant relationship between these seemingly disparate factors, providing a quirky insight into the interplay of global energy usage and local labor markets. Our results have implications for policymakers, analysts, and anyone with an affinity for unexpected connections in the world of economics and energy.

[[INTRODUCTION]]
The world of economics and energy often brings to light unexpected connections and correlations that may seem far-fetched at first glance. In this study, we embark on a journey to explore the intriguing link between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. While the casual observer may raise an eyebrow at the juxtaposition of these two seemingly unrelated variables, our analysis uncovers a compelling relationship that warrants further investigation.
Azerbaijan, the land where the legendary oil fields of Baku have captured the imagination of oil enthusiasts for centuries, serves as the backdrop for our first variable in this curious equation. Meanwhile, the southern charm of Alabama, known for its scenic countryside and agricultural heritage, sets the stage for the second variable – the number of farm equipment mechanics. The collision of these disparate worlds in our analysis is a testament to the unexpected twists that can be found in the labyrinth of data analysis.
Before diving into the depths of our findings, it is essential to underscore the foundation of our inquiry. The Energy Information Administration (EIA) provides valuable insights into the petroleum consumption patterns in Azerbaijan, offering a glimpse into the fuel preferences and demands of this nation. On the other hand, the Bureau of Labor Statistics (BLS) furnishes us with the data on the number of farm equipment mechanics in the heart of Dixie – Alabama. These robust sources lay the groundwork for our statistical exploration, allowing us to unravel the hidden thread that binds these variables together.
Now, one may ponder: What could possibly link the gallons of fuel being consumed in the bustling streets of Baku to the wrenches and machinery tinkering in the cotton fields of Alabama? Our study aims to shed light on this puzzling relationship and bring forth meaningful insights that transcend the boundaries of conventional economic wisdom. The confluence of global energy trends and local labor dynamics is an engrossing puzzle that demands our attention, offering a beguiling glimpse into the complexity of interconnected systems.
As we journey through the labyrinth of data and statistical analysis, it becomes evident that the world of economics and energy is not only a playground for the serious-minded but also a canvas for the whimsical and unexpected. Our quest uncovers a correlation coefficient of 0.9283473 and a p-value that dances beneath the threshold of significance, underscoring the robustness of the relationship between these variables. The allure of such a striking correlation invites us to ponder the subtle dance of causation and correlation, reminding us that in the realm of statistical exploration, truth can often be found in the unlikeliest of bedfellows.
Join us as we unravel the delightful dance between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama, for in this intricate web of statistical connections, lies a trove of wisdom waiting to be unearthed.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To untangle the enigmatic web of statistical connections between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama, we employed a rigorous and methodical approach that combined statistical analysis with a touch of whimsy. Our data collection spanned the years 2010 to 2021, capturing a timeframe that encapsulated the ebb and flow of energy usage and labor dynamics. The primary sources of information for our study were the esteemed repositories of the Energy Information Administration (EIA) and the Bureau of Labor Statistics (BLS), from which we gleaned a plethora of numerical nuggets to fuel our inquiry.

The first thread in our methodological tapestry involves the extraction and compilation of petroleum consumption data from the energy-rich lands of Azerbaijan. The EIA served as our compass, guiding us through the labyrinth of oil statistics and rendering unto us the intriguing insights into the per capita consumption of petroleum in Azerbaijan. This beguiling dataset, while seemingly esoteric at first glance, holds the key to unlocking the potential linkages between global energy usage and localized labor dynamics.

On the other end of the spectrum, we turned our gaze towards the heart of Dixie – Alabama, with its rolling fields and the ever-present hum of farm machinery. The BLS, our trusted custodian of labor statistics, furnished us with the numbers pertaining to the count of farm equipment mechanics in the bucolic landscape of Alabama. This rich dataset, akin to a patchwork quilt of labor dynamics, became the companion piece to the petroleum consumption statistics from Azerbaijan. Together, they formed the yin and yang of our statistical exploration, poised to unravel the riddle of their interconnection.

With these datasets in hand, we embarked on the path of statistical analysis, wielding the formidable tools of correlation coefficient calculation and p-value assessment. Our journey through the realm of statistics was not without its twists and turns, akin to navigating a labyrinth where each statistical test held the potential for a surprising revelation. Through the methodical application of mathematical formulae and statistical rigour, we arrived at the striking correlation coefficient of 0.9283473 and a p-value that tiptoed beneath the threshold of significance, setting the stage for a curious unveiling of the relationship between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama.

In traversing this convoluted path of statistical exploration, we remain ever cognizant of the serendipitous nature of research, where the most unexpected connections often yield the richest insights. As we unveil the peculiar entwinement of petroleum usage in a distant land and the labor dynamics of the South, we invite the readers to partake in this delightful dance of statistical exploration, where the serious-minded analysis is interspersed with a touch of whimsy and wonder.


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 Petroluem consumption in Azerbaijan and The number of farm equipment mechanics in Alabama. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 Energy Information Administration and Bureau of Larbor Statistics .

For the time period 2010 to 2021, you found a correlation 0.9283473, r-squared of 0.8618287, 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]]
"Fueling the Farm: A Crude Connection Between Petroleum Consumption in Azerbaijan and the Number of Farm Equipment Mechanics in Alabama"

[[ABSTRACT]]
This paper delves into the curious correlation between the per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. By analyzing data from the Energy Information Administration and the Bureau of Labor Statistics spanning the years 2010 to 2021, we unearthed a striking correlation coefficient of 0.9283473 and a p-value of less than 0.01. Our findings suggest a significant relationship between these seemingly disparate factors, providing a quirky insight into the interplay of global energy usage and local labor markets. Our results have implications for policymakers, analysts, and anyone with an affinity for unexpected connections in the world of economics and energy.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The world of economics and energy often brings to light unexpected connections and correlations that may seem far-fetched at first glance. In this study, we embark on a journey to explore the intriguing link between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. While the casual observer may raise an eyebrow at the juxtaposition of these two seemingly unrelated variables, our analysis uncovers a compelling relationship that warrants further investigation.
Azerbaijan, the land where the legendary oil fields of Baku have captured the imagination of oil enthusiasts for centuries, serves as the backdrop for our first variable in this curious equation. Meanwhile, the southern charm of Alabama, known for its scenic countryside and agricultural heritage, sets the stage for the second variable – the number of farm equipment mechanics. The collision of these disparate worlds in our analysis is a testament to the unexpected twists that can be found in the labyrinth of data analysis.
Before diving into the depths of our findings, it is essential to underscore the foundation of our inquiry. The Energy Information Administration (EIA) provides valuable insights into the petroleum consumption patterns in Azerbaijan, offering a glimpse into the fuel preferences and demands of this nation. On the other hand, the Bureau of Labor Statistics (BLS) furnishes us with the data on the number of farm equipment mechanics in the heart of Dixie – Alabama. These robust sources lay the groundwork for our statistical exploration, allowing us to unravel the hidden thread that binds these variables together.
Now, one may ponder: What could possibly link the gallons of fuel being consumed in the bustling streets of Baku to the wrenches and machinery tinkering in the cotton fields of Alabama? Our study aims to shed light on this puzzling relationship and bring forth meaningful insights that transcend the boundaries of conventional economic wisdom. The confluence of global energy trends and local labor dynamics is an engrossing puzzle that demands our attention, offering a beguiling glimpse into the complexity of interconnected systems.
As we journey through the labyrinth of data and statistical analysis, it becomes evident that the world of economics and energy is not only a playground for the serious-minded but also a canvas for the whimsical and unexpected. Our quest uncovers a correlation coefficient of 0.9283473 and a p-value that dances beneath the threshold of significance, underscoring the robustness of the relationship between these variables. The allure of such a striking correlation invites us to ponder the subtle dance of causation and correlation, reminding us that in the realm of statistical exploration, truth can often be found in the unlikeliest of bedfellows.
Join us as we unravel the delightful dance between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama, for in this intricate web of statistical connections, lies a trove of wisdom waiting to be unearthed.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The statistical analysis of the relationship between per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama yielded noteworthy results. Over the time period of 2010 to 2021, a strong correlation coefficient of 0.9283473 was observed, indicating a robust positive association between these seemingly disparate variables. Furthermore, the coefficient of determination (r-squared) was calculated to be 0.8618287, indicating that approximately 86% of the variability in the number of farm equipment mechanics in Alabama can be explained by the variability in petroleum consumption in Azerbaijan. The p-value of less than 0.01 further underscores the significance of this correlation.

Fig. 1 presents a scatterplot illustrating the pronounced positive correlation between per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. The data points exhibit a clear pattern, reinforcing the robustness of the correlation and the potential implications of this intriguing connection.

These findings shed light on the dynamic interplay between global energy consumption and local labor markets. While it may seem like a stretch to connect the bustling oil-rich landscape of Azerbaijan to the agrarian strongholds of Alabama, our results highlight the whimsical and unexpected nature of statistical analysis, where the unlikeliest of bedfellows often reveal meaningful relationships.

The implications of these findings reach beyond mere statistical curiosity, offering insights that could prove valuable for policymakers and analysts. The correlation uncovered in this study begs the question: is there a crude connection between the fuel preferences of one region and the labor market dynamics of another? Our results present a quirky yet thought-provoking angle on the intricate web of economic and energy relationships, inviting further inquiry into the unconventional intersections of seemingly disparate variables.


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 Petroluem consumption in Azerbaijan and The number of farm equipment mechanics in Alabama. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Fueling the Farm: A Crude Connection Between Petroleum Consumption in Azerbaijan and the Number of Farm Equipment Mechanics in Alabama"

[[ABSTRACT]]
This paper delves into the curious correlation between the per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. By analyzing data from the Energy Information Administration and the Bureau of Labor Statistics spanning the years 2010 to 2021, we unearthed a striking correlation coefficient of 0.9283473 and a p-value of less than 0.01. Our findings suggest a significant relationship between these seemingly disparate factors, providing a quirky insight into the interplay of global energy usage and local labor markets. Our results have implications for policymakers, analysts, and anyone with an affinity for unexpected connections in the world of economics and energy.

[[LITERATURE REVIEW]]
In "Smith and Doe (2020)," the authors find a parallel between the per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. Their study lays the groundwork for our investigation, delving into the intricate web of global energy usage and local labor markets. Drawing from the venerable tradition of economic analysis, the authors unearth a correlation coefficient that piques our interest and sets the stage for further exploration.
Expanding upon the foundation set forth by Smith and Doe, "Jones et al. (2018)" offer a nuanced perspective on the interplay between petroleum consumption and labor dynamics. Their study, while rigorous and insightful, leaves ample room for the infusion of humor and unexpected insights. Indeed, as we wade into the depths of this peculiar correlation, it becomes increasingly clear that the marriage of Azerbaijani fuel trends and Alabama's machinery mechanics is not merely a dry statistical affair, but a rich tapestry weaving together the whimsical and the wondrous.
Venturing beyond the realm of conventional economic discourse, "Petroleum Patterns: A Global Overview" by A. Barrel and O. Spill offers a comprehensive exploration of the quirky tendencies of petroleum consumption across the globe. As we peruse the pages of this illuminating text, a delightful array of puns and jests grace the margins, reminding us that even the most serious of subjects can be tinged with levity.
Turning to the literary realm, "The Grapes of Wrath" by John Steinbeck beckons us into the heart of agricultural America, providing a narrative backdrop for our investigation into the labor dynamics of Alabama's farmlands. While seemingly unrelated to the world of petroleum consumption, this classic work serves as a poignant reminder of the interconnectedness of human endeavors and the unexpected twists that permeate our economic landscape.
Simultaneously, "Oil!: A Novel" by Upton Sinclair beckons forth a tale of ambition, treachery, and, yes, petroleum - offering a fictional lens through which we can glean insights into the complexities of energy markets and the labor forces that sustain them. In the world of literature, as in statistical analysis, one must always be prepared for the unexpected, for the most profound truths often emerge from the unlikeliest of narratives.
Shifting gears to a lighthearted note, the animated series "Bob the Builder" and "Handy Manny" regale us with the endearing escapades of skilled mechanics and handymen, beckoning us to contemplate the role of labor expertise in the maintenance of our built environment. While ostensibly aimed at a younger audience, these charming tales offer a whimsical perspective on the world of mechanical tinkering and the vital role it plays in sustaining our day-to-day livelihoods.
In this eclectic array of sources, we find a reflection of the multifaceted relationship between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. As we navigate this peculiar avenue of inquiry, it becomes increasingly clear that the intersection of economics, energy, and labor is not merely a dry terrain of statistical analysis, but a vibrant tapestry interwoven with humor, whimsy, and unexpected connections.

[[RESULTS]]
The statistical analysis of the relationship between per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama yielded noteworthy results. Over the time period of 2010 to 2021, a strong correlation coefficient of 0.9283473 was observed, indicating a robust positive association between these seemingly disparate variables. Furthermore, the coefficient of determination (r-squared) was calculated to be 0.8618287, indicating that approximately 86% of the variability in the number of farm equipment mechanics in Alabama can be explained by the variability in petroleum consumption in Azerbaijan. The p-value of less than 0.01 further underscores the significance of this correlation.
Fig. 1 presents a scatterplot illustrating the pronounced positive correlation between per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. The data points exhibit a clear pattern, reinforcing the robustness of the correlation and the potential implications of this intriguing connection.
These findings shed light on the dynamic interplay between global energy consumption and local labor markets. While it may seem like a stretch to connect the bustling oil-rich landscape of Azerbaijan to the agrarian strongholds of Alabama, our results highlight the whimsical and unexpected nature of statistical analysis, where the unlikeliest of bedfellows often reveal meaningful relationships.
The implications of these findings reach beyond mere statistical curiosity, offering insights that could prove valuable for policymakers and analysts. The correlation uncovered in this study begs the question: is there a crude connection between the fuel preferences of one region and the labor market dynamics of another? Our results present a quirky yet thought-provoking angle on the intricate web of economic and energy relationships, inviting further inquiry into the unconventional intersections of seemingly disparate variables.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The correlation between per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama, as unveiled in this study, opens a veritable cornucopia of whimsical inquiries and unexpected insights. Our findings not only substantiate the observations put forth by Smith and Doe (2020) and Jones et al. (2018), but also breathe vivacious life into the seemingly dry realm of statistical analysis.

Amidst the labyrinth of correlation coefficients and p-values, the robust positive association we have unearthed sheds light on the captivating dance between global energy trends and the idyllic plains of Alabama. It seems that as the engines in Baku roar, the gears in Alabama turn in harmonious synchrony. Perhaps there is indeed a crude connection at play, as the tendrils of petrol reach across oceans and continents to grease the wheels of rural industry.

Our results not only offer a tongue-in-cheek nod to the astute musings of the authors who preceded us, but also propel us into the realm of economic enigma and energy eccentricity. The scatterplot, like a surrealist masterpiece, captures the imagination with its stark portrayal of the intertwined destinies of Azerbaijani petroleum and Alabama's mechanical mastery. In this vibrant tapestry of data points, we witness a whimsical tango between energy abundance and labor expertise, leaving us to ponder the unpredictable dance of economic forces.

The implications of this correlation, while decidedly unorthodox, provoke contemplation and perhaps a chuckle or two. Could it be that the rumbles of Azerbaijani oil consumption reverberate through the fields of Alabama, shaping the employment landscape in ways both comical and consequential? Might there exist an allegorical tale of energy exploration and labor intrigue, with characters as diverse as the black gold itself?

As we traverse this unorthodox intersection of economic and energy pathways, the eclectic array of sources encountered in our literary review makes a spirited reappearance. From the jovial escapades of "Bob the Builder" and "Handy Manny" to the poignant labor struggles depicted in "The Grapes of Wrath" and "Oil!: A Novel," the seemingly incongruous world of literature casts a whimsical shadow over our statistical pursuits.

Indeed, the interplay between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama is not merely a dry-as-dust exercise in number-crunching, but a rich reservoir of unexpected associations and delightful foibles. In the realm of economics, as in life, the most remarkable truths often reveal themselves through the most improbable of lenses.

As we bring this discussion to a lighthearted yet probing close, we are stirred to contemplate not only the intercontinental dance of petrol and pistons, but also the charming unpredictability that enlivens our scholarly pursuits. For in the corridors of research, as in the boundless expanse of human endeavor, we find that even the most curious of connections can unravel into a tapestry teeming with wit and wonder.


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 Petroluem consumption in Azerbaijan and The number of farm equipment mechanics in Alabama. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Fueling the Farm: A Crude Connection Between Petroleum Consumption in Azerbaijan and the Number of Farm Equipment Mechanics in Alabama"

[[ABSTRACT]]
This paper delves into the curious correlation between the per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. By analyzing data from the Energy Information Administration and the Bureau of Labor Statistics spanning the years 2010 to 2021, we unearthed a striking correlation coefficient of 0.9283473 and a p-value of less than 0.01. Our findings suggest a significant relationship between these seemingly disparate factors, providing a quirky insight into the interplay of global energy usage and local labor markets. Our results have implications for policymakers, analysts, and anyone with an affinity for unexpected connections in the world of economics and energy.

[[INTRDUCTION]]
The world of economics and energy often brings to light unexpected connections and correlations that may seem far-fetched at first glance. In this study, we embark on a journey to explore the intriguing link between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. While the casual observer may raise an eyebrow at the juxtaposition of these two seemingly unrelated variables, our analysis uncovers a compelling relationship that warrants further investigation.
Azerbaijan, the land where the legendary oil fields of Baku have captured the imagination of oil enthusiasts for centuries, serves as the backdrop for our first variable in this curious equation. Meanwhile, the southern charm of Alabama, known for its scenic countryside and agricultural heritage, sets the stage for the second variable – the number of farm equipment mechanics. The collision of these disparate worlds in our analysis is a testament to the unexpected twists that can be found in the labyrinth of data analysis.
Before diving into the depths of our findings, it is essential to underscore the foundation of our inquiry. The Energy Information Administration (EIA) provides valuable insights into the petroleum consumption patterns in Azerbaijan, offering a glimpse into the fuel preferences and demands of this nation. On the other hand, the Bureau of Labor Statistics (BLS) furnishes us with the data on the number of farm equipment mechanics in the heart of Dixie – Alabama. These robust sources lay the groundwork for our statistical exploration, allowing us to unravel the hidden thread that binds these variables together.
Now, one may ponder: What could possibly link the gallons of fuel being consumed in the bustling streets of Baku to the wrenches and machinery tinkering in the cotton fields of Alabama? Our study aims to shed light on this puzzling relationship and bring forth meaningful insights that transcend the boundaries of conventional economic wisdom. The confluence of global energy trends and local labor dynamics is an engrossing puzzle that demands our attention, offering a beguiling glimpse into the complexity of interconnected systems.
As we journey through the labyrinth of data and statistical analysis, it becomes evident that the world of economics and energy is not only a playground for the serious-minded but also a canvas for the whimsical and unexpected. Our quest uncovers a correlation coefficient of 0.9283473 and a p-value that dances beneath the threshold of significance, underscoring the robustness of the relationship between these variables. The allure of such a striking correlation invites us to ponder the subtle dance of causation and correlation, reminding us that in the realm of statistical exploration, truth can often be found in the unlikeliest of bedfellows.
Join us as we unravel the delightful dance between petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama, for in this intricate web of statistical connections, lies a trove of wisdom waiting to be unearthed.

[[RESULTS]]
The statistical analysis of the relationship between per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama yielded noteworthy results. Over the time period of 2010 to 2021, a strong correlation coefficient of 0.9283473 was observed, indicating a robust positive association between these seemingly disparate variables. Furthermore, the coefficient of determination (r-squared) was calculated to be 0.8618287, indicating that approximately 86% of the variability in the number of farm equipment mechanics in Alabama can be explained by the variability in petroleum consumption in Azerbaijan. The p-value of less than 0.01 further underscores the significance of this correlation.
Fig. 1 presents a scatterplot illustrating the pronounced positive correlation between per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. The data points exhibit a clear pattern, reinforcing the robustness of the correlation and the potential implications of this intriguing connection.
These findings shed light on the dynamic interplay between global energy consumption and local labor markets. While it may seem like a stretch to connect the bustling oil-rich landscape of Azerbaijan to the agrarian strongholds of Alabama, our results highlight the whimsical and unexpected nature of statistical analysis, where the unlikeliest of bedfellows often reveal meaningful relationships.
The implications of these findings reach beyond mere statistical curiosity, offering insights that could prove valuable for policymakers and analysts. The correlation uncovered in this study begs the question: is there a crude connection between the fuel preferences of one region and the labor market dynamics of another? Our results present a quirky yet thought-provoking angle on the intricate web of economic and energy relationships, inviting further inquiry into the unconventional intersections of seemingly disparate variables.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study has elucidated a compelling correlation between per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. This unexpected connection challenges conventional wisdom and opens the door to a whimsical exploration of the interplay between global energy trends and local labor dynamics. The robust correlation coefficient of 0.9283473, coupled with a p-value of less than 0.01, underscores the statistical significance of this relationship, leaving us pondering the mysterious ways in which statistical analysis can lead us to unexpected discoveries.

The findings of this study not only provoke academic intrigue but also offer a cheeky reminder that the world of economics and energy is prone to delightful surprises. The whimsical dance between petroleum consumption in the land of Baku and the wrenches tinkering in the cotton fields of Alabama beckons us to embrace the unconventional connections that statistical analysis can unveil. Indeed, the allure of statistical exploration lies in the unlikeliest of bedfellows, where truth often emerges from the most unexpected pairings.

As we hang up our statistical hats and bid adieu to this delightful dance of data, it becomes apparent that no further research is needed in this area. The correlation is crystal clear, and it would seem that the mysterious bond between these seemingly unrelated variables has been unveiled in all its quirky glory. This study leaves us with a wry smile and a trove of unexpected wisdom, reminding us that in the realm of statistical inquiry, surprises are always on the cards - even if they involve the seemingly unconnected realms of petroleum consumption and farm equipment mechanics.


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 Fueling the Farm: A Crude Connection Between Petroleum Consumption in Azerbaijan and the Number of Farm Equipment Mechanics in Alabama. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Energy Economics and Agricultural Labor Trends


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 Fueling the Farm: A Crude Connection Between Petroleum Consumption in Azerbaijan and the Number of Farm Equipment Mechanics in Alabama. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Transnational Energy Research and Development


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 Fueling the Farm: A Crude Connection Between Petroleum Consumption in Azerbaijan and the Number of Farm Equipment Mechanics in Alabama with an abstract of This paper delves into the curious correlation between the per capita petroleum consumption in Azerbaijan and the number of farm equipment mechanics in Alabama. By analyzing data from the Energy Information Administration and the Bureau of Labor Statistics spanning the years 2010 to 2021, we unearthed a striking correlation coefficient of 0.9283473 and a p-value of less than 0.01. Our findings suggest a significant relationship between these seemingly disparate factors, providing a quirky insight into the interplay of global energy usage and local labor markets. Our results have implications for policymakers, analysts, and anyone with an affinity for unexpected connections in the world of economics and energy.

ChatGPT:

petroleum consumption Azerbaijan, farm equipment mechanics Alabama, correlation coefficient, p-value, Energy Information Administration data, Bureau of Labor Statistics data 2010-2021, global energy usage, local labor markets, economics energy connection

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



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Data details

Petroluem consumption in Azerbaijan
Detailed data title: Volume of petroluem consumption consumed in Azerbaijan in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Petroluem consumption in Azerbaijan

The number of farm equipment mechanics in Alabama
Detailed data title: BLS estimate of farm equipment mechanics and service technicians in Alabama
Source: Bureau of Larbor Statistics
See what else correlates with The number of farm equipment mechanics in Alabama

Correlation r = 0.9283473 (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 = 0.8618287 (Coefficient of determination)
This means 86.2% of the change in the one variable (i.e., The number of farm equipment mechanics in Alabama) is predictable based on the change in the other (i.e., Petroluem consumption in Azerbaijan) over the 12 years from 2010 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.3E-5. 0.0000131774301145694470000000
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 0.0013% of random cases. Said differently, if you correlated 75,887 random variables You don't actually need 75 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 11 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 11 because we have two variables measured over a period of 12 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.
201020112012201320142015201620172018201920202021
Petroluem consumption in Azerbaijan (Million Barrels/Day)82.627292.361196.9132100.15999.629398.125496.3042102.444100.261107.51698.039798.9297
The number of farm equipment mechanics in Alabama (Laborers)300400470580490430460520550620490530




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([82.6272,92.3611,96.9132,100.159,99.6293,98.1254,96.3042,102.444,100.261,107.516,98.0397,98.9297,])
array_2 = np.array([300,400,470,580,490,430,460,520,550,620,490,530,])
array_1_name = "Petroluem consumption in Azerbaijan"
array_2_name = "The number of farm equipment mechanics in Alabama"

# 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."

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