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Spurious correlation #2,307 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Wind power generated in Italy and the second variable is The price of gold.  The chart goes from 1989 to 2014, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

Italian economists suggested that as more wind turbines turned, they created a stronger "Euro wind" blowing through the market. This led to a spike in demand for gold as investors sought to hedge against the currency fluctuations. After all, when it comes to renewable energy and precious metals, it's all about that "watt" and "carat" balance in the market! Who would have thought that the real gold in Italy wasn't just in its art and architecture, but also in its gusty energy initiatives?

Model: dalle-3
Prompt: Generate an image that appears to be a scene from 'Star Wars', showing a cluster of colossal wind turbines dotting the landscape under a vibrant, cloudless Italian sky. In the background, a small group of figures can be seen meticulously sifting through a riverbed for glimmering specks of gold. 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: Wind power generated in Italy and The price of gold. 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: Cubism Oragami Photorealism An image that looks like it is a scene from 'Star Wars' inspired by bauhaus
ChatGPT: An image that looks like it is a scene from 'Star Wars'

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 Wind power generated in Italy and The price of gold together. Keep the description simple.
ChatGPT: A field of sturdy wind turbines stands tall under the clear blue Italian sky. In the distance, a group of people carefully sift through a riverbed, panning for specks of shimmering gold.

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: [ An image that looks like it is a scene from 'Star Wars' ] and depicting this scene: A field of sturdy wind turbines stands tall under the clear blue Italian sky. In the distance, a group of people carefully sift through a riverbed, panning for specks of shimmering gold. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that appears to be a scene from 'Star Wars', showing a cluster of colossal wind turbines dotting the landscape under a vibrant, cloudless Italian sky. In the background, a small group of figures can be seen meticulously sifting through a riverbed for glimmering specks of gold.

*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 Wind power generated in Italy caused The price of gold to increase. Include one good pun.

AI academic paper

(Because p < 0.01)
Blowing in the Wind: How Italian Turbines and Bullion Mines Are Inclined

Journal of Environmental Engineering and Geology

Jan 2024

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




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Wind power generated in Italy and The price of gold. Make lots of jokes, goofy observations, and puns.

Rhyme words in the title.

Your research team used data from Energy Information Administration and Kitco to assess this nagging question. You found a correlation coefficient of 0.9490346 and p < 0.01 for 1989 to 2014.

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]]
Blowing in the Wind: How Italian Turbines and Bullion Mines Are Inclined

[[ABSTRACT]]
This paper uncovers the curious relationship between wind power generation in Italy and the price of gold. Through an analysis of data sourced from the Energy Information Administration and Kitco, our research team identified a strong positive correlation between the two seemingly disparate phenomena. The data points to a correlation coefficient of 0.9490346, indicating a remarkably close relationship, and a p-value of less than 0.01, reinforcing the statistical significance of the findings. Our study spans the years 1989 to 2014, offering a comprehensive exploration of this unexpected association. Juxtaposing the breezy nature of wind energy with the lustrous allure of gold prices, our research sheds light on the windy ties that bind these two distinct realms. The study not only provides insight into the intriguing interplay between energy production and commodity valuation but also offers a whimsical twist in the understanding of economic trends.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Wind power generated in Italy and The price of gold. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
Blowing in the Wind: How Italian Turbines and Bullion Mines Are Inclined

[[ABSTRACT]]
This paper uncovers the curious relationship between wind power generation in Italy and the price of gold. Through an analysis of data sourced from the Energy Information Administration and Kitco, our research team identified a strong positive correlation between the two seemingly disparate phenomena. The data points to a correlation coefficient of 0.9490346, indicating a remarkably close relationship, and a p-value of less than 0.01, reinforcing the statistical significance of the findings. Our study spans the years 1989 to 2014, offering a comprehensive exploration of this unexpected association. Juxtaposing the breezy nature of wind energy with the lustrous allure of gold prices, our research sheds light on the windy ties that bind these two distinct realms. The study not only provides insight into the intriguing interplay between energy production and commodity valuation but also offers a whimsical twist in the understanding of economic trends.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
INTRODUCTION

Imagine a gust of wind, barreling through the Italian countryside, and then picture the glint of gold, nestled within the depths of a bullion mine. On the surface, these two entities seem worlds apart, akin to comparing the speed of snails to the pace of cheetahs. However, as our research team delved into the convoluted world of statistical analysis, we stumbled upon a discovery that would make even the most seasoned econometricians raise their eyebrows in disbelief.

The connection between wind power generation in Italy and the price of gold may seem as likely as finding a needle in a haystack in a tornado, but our findings unveil an unexpected relationship that will blow your mind more than a hurricane on a clear day. In our research, we combined the winds of statistical analysis with the golden nuggets of economic exploration to uncover a bond that's more intriguing than a detective novel written by a statistician with a penchant for puns.

As our study unravels the correlation coefficient of 0.9490346, we couldn't help but marvel at the sheer gusty magnitude of this connection. We observed a trend so robust, it's as if the windmills were whispering trade secrets to the bullion mines, and the gold prices were gleefully reciprocating with every gust, creating a symphony of economic entanglement that deserves a standing ovation. The p-value of less than 0.01 further solidifies the significance of this relationship, leaving us with the realization that this bond is as statistically strong as a bodybuilder flexing under the scrutiny of a rigorous t-test.

Our study spans the years 1989 to 2014, and like archaeologists dusting off ancient treasures, we unearthed a treasure trove of data that painted a compelling narrative of intertwining fates. It's as if the winds of fate were playfully nudging the gold prices, whispering, "Hey, I'm here, too," in an exchange that's more intricate than a dance between statistical outliers. With a conclusion that goes against the wind of conventional wisdom, our research stands as a testament to the unpredictable and oftentimes zephyrous nature of economic trends.

Join us as we embark on this whimsical journey, where the breeze carries the weight of economic influence and the price of gold dances to the rhythm of Italy's wind turbines. For in our exploration lies not just an understanding of the yin and yang of energy production and commodity valuation, but also a playful twist in the understanding of economic dynamics that's as refreshing as a gentle breeze on a scorching summer's day.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Wind power generated in Italy and The price of gold. Make lots of jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
Blowing in the Wind: How Italian Turbines and Bullion Mines Are Inclined

[[ABSTRACT]]
This paper uncovers the curious relationship between wind power generation in Italy and the price of gold. Through an analysis of data sourced from the Energy Information Administration and Kitco, our research team identified a strong positive correlation between the two seemingly disparate phenomena. The data points to a correlation coefficient of 0.9490346, indicating a remarkably close relationship, and a p-value of less than 0.01, reinforcing the statistical significance of the findings. Our study spans the years 1989 to 2014, offering a comprehensive exploration of this unexpected association. Juxtaposing the breezy nature of wind energy with the lustrous allure of gold prices, our research sheds light on the windy ties that bind these two distinct realms. The study not only provides insight into the intriguing interplay between energy production and commodity valuation but also offers a whimsical twist in the understanding of economic trends.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
Imagine a gust of wind, barreling through the Italian countryside, and then picture the glint of gold, nestled within the depths of a bullion mine. On the surface, these two entities seem worlds apart, akin to comparing the speed of snails to the pace of cheetahs. However, as our research team delved into the convoluted world of statistical analysis, we stumbled upon a discovery that would make even the most seasoned econometricians raise their eyebrows in disbelief.
The connection between wind power generation in Italy and the price of gold may seem as likely as finding a needle in a haystack in a tornado, but our findings unveil an unexpected relationship that will blow your mind more than a hurricane on a clear day. In our research, we combined the winds of statistical analysis with the golden nuggets of economic exploration to uncover a bond that's more intriguing than a detective novel written by a statistician with a penchant for puns.
As our study unravels the correlation coefficient of 0.9490346, we couldn't help but marvel at the sheer gusty magnitude of this connection. We observed a trend so robust, it's as if the windmills were whispering trade secrets to the bullion mines, and the gold prices were gleefully reciprocating with every gust, creating a symphony of economic entanglement that deserves a standing ovation. The p-value of less than 0.01 further solidifies the significance of this relationship, leaving us with the realization that this bond is as statistically strong as a bodybuilder flexing under the scrutiny of a rigorous t-test.
Our study spans the years 1989 to 2014, and like archaeologists dusting off ancient treasures, we unearthed a treasure trove of data that painted a compelling narrative of intertwining fates. It's as if the winds of fate were playfully nudging the gold prices, whispering, "Hey, I'm here, too," in an exchange that's more intricate than a dance between statistical outliers. With a conclusion that goes against the wind of conventional wisdom, our research stands as a testament to the unpredictable and oftentimes zephyrous nature of economic trends.
Join us as we embark on this whimsical journey, where the breeze carries the weight of economic influence and the price of gold dances to the rhythm of Italy's wind turbines. For in our exploration lies not just an understanding of the yin and yang of energy production and commodity valuation, but also a playful twist in the understanding of economic dynamics that's as refreshing as a gentle breeze on a scorching summer's day.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In "Wind Energy in Italy: A Case Study," Smith et al. examine the development and utilization of wind power in Italy, offering a comprehensive analysis of the country's initiatives in renewable energy. They discuss the technological advancements, policy frameworks, and socioeconomic implications of wind energy, providing a thorough understanding of its impact on the Italian energy landscape. Similarly, Doe and Jones, in "The Economics of Gold Mining," delve into the intricate workings of gold mining and its contribution to the global economy. Their research sheds light on the supply and demand dynamics, investment patterns, and geopolitical influences that shape the bullion market, offering a nuanced perspective on the valuation of gold.

Expanding beyond these seminal works, "The Italian Job" by Economist et al. presents a detailed account of Italy's economic trajectory, including its energy sector and resource management. While not specifically focused on wind power or gold prices, the book offers valuable insights into the broader economic context, setting the stage for understanding the interplay between renewable energy and commodity markets. In a similar vein, "The Alchemist" by Philosopher explores the mystical allure of treasure and destiny, albeit in a fictional realm. Although not a direct source of empirical data, the book presents a whimsical take on the quest for riches, inviting readers to ponder the enigmatic forces that govern economic pursuits and the pursuit of the fabled "Philosopher's Stone."

In a somewhat tangential but nonetheless entertaining vein, the movies "The Italian Job" and "Fool's Gold" provide cinematic escapades that, while not rooted in empirical research, offer a lighthearted glimpse into the world of heists and treasure hunting. While the plots may not directly relate to our study, we cannot dismiss the possibility of wind energy making a cameo in a future sequel, perhaps in the form of a renewable energy-powered getaway vehicle or a blustery obstacle for treasure hunters navigating the high seas.

As we navigate the windy intersection of renewable energy and precious metals, it is essential to appreciate the multifaceted layers of influence that extend beyond traditional economic analyses. With a gust of humor and a touch of whimsy, our literature review sets the stage for a light-hearted exploration of the unexpected ties between Italian turbines and bullion mines.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Wind power generated in Italy and The price of gold. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and Kitco . You used data from 1989 to 2014

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]]
Blowing in the Wind: How Italian Turbines and Bullion Mines Are Inclined

[[ABSTRACT]]
This paper uncovers the curious relationship between wind power generation in Italy and the price of gold. Through an analysis of data sourced from the Energy Information Administration and Kitco, our research team identified a strong positive correlation between the two seemingly disparate phenomena. The data points to a correlation coefficient of 0.9490346, indicating a remarkably close relationship, and a p-value of less than 0.01, reinforcing the statistical significance of the findings. Our study spans the years 1989 to 2014, offering a comprehensive exploration of this unexpected association. Juxtaposing the breezy nature of wind energy with the lustrous allure of gold prices, our research sheds light on the windy ties that bind these two distinct realms. The study not only provides insight into the intriguing interplay between energy production and commodity valuation but also offers a whimsical twist in the understanding of economic trends.

[[INTRODUCTION]]
INTRODUCTION
Imagine a gust of wind, barreling through the Italian countryside, and then picture the glint of gold, nestled within the depths of a bullion mine. On the surface, these two entities seem worlds apart, akin to comparing the speed of snails to the pace of cheetahs. However, as our research team delved into the convoluted world of statistical analysis, we stumbled upon a discovery that would make even the most seasoned econometricians raise their eyebrows in disbelief.
The connection between wind power generation in Italy and the price of gold may seem as likely as finding a needle in a haystack in a tornado, but our findings unveil an unexpected relationship that will blow your mind more than a hurricane on a clear day. In our research, we combined the winds of statistical analysis with the golden nuggets of economic exploration to uncover a bond that's more intriguing than a detective novel written by a statistician with a penchant for puns.
As our study unravels the correlation coefficient of 0.9490346, we couldn't help but marvel at the sheer gusty magnitude of this connection. We observed a trend so robust, it's as if the windmills were whispering trade secrets to the bullion mines, and the gold prices were gleefully reciprocating with every gust, creating a symphony of economic entanglement that deserves a standing ovation. The p-value of less than 0.01 further solidifies the significance of this relationship, leaving us with the realization that this bond is as statistically strong as a bodybuilder flexing under the scrutiny of a rigorous t-test.
Our study spans the years 1989 to 2014, and like archaeologists dusting off ancient treasures, we unearthed a treasure trove of data that painted a compelling narrative of intertwining fates. It's as if the winds of fate were playfully nudging the gold prices, whispering, "Hey, I'm here, too," in an exchange that's more intricate than a dance between statistical outliers. With a conclusion that goes against the wind of conventional wisdom, our research stands as a testament to the unpredictable and oftentimes zephyrous nature of economic trends.
Join us as we embark on this whimsical journey, where the breeze carries the weight of economic influence and the price of gold dances to the rhythm of Italy's wind turbines. For in our exploration lies not just an understanding of the yin and yang of energy production and commodity valuation, but also a playful twist in the understanding of economic dynamics that's as refreshing as a gentle breeze on a scorching summer's day.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Our research methodology aimed to capture the whimsical dance of wind power generation and the price of gold, utilizing a blend of rigorous statistical analysis and a playful, inquisitive approach. This was not your average run-of-the-mill analysis; we infused our methodology with the enthusiasm of a researcher discovering a hidden treasure map in the dusty archives of economics.

Data Collection:
To embark on this adventure, we scoured the depths of the internet, navigating through the digital seas and valleys of information. We relied heavily on data from the Energy Information Administration and Kitco, mining their resources with the precision of a gold prospector sifting through riverbeds in search of that elusive nugget. Our quest spanned the years 1989 to 2014, a time period that encapsulated a captivating window into the wind-propelled economic landscape.

Wind Power Generation in Italy:
The foundation of our study rested on the spirited winds of Italy, where we gathered data on the country's wind power generation. We meticulously gathered information on the capacity, production, and utilization of wind power, treating each data point as a breeze whispering its story in the vast expanse of energy statistics.

Price of Gold:
In parallel, we delved into the depths of gold prices, harnessing data from Kitco to capture the effervescent glimmer of gold's valuation in the economic arena. We meticulously documented the daily fluctuations, observing the rise and fall of this precious metal's allure with a keen eye worthy of a vivacious explorer venturing into uncharted territories.

Statistical Analysis:
With our data in hand, we summoned the powers of statistical analysis, wielding the tools of correlation and regression with the finesse of a masterful artisan crafting a masterpiece. We sought to unravel the intricate patterns and connections, akin to deciphering a coded message embedded in the winds and whispers of economic phenomena.

Correlation Coefficient:
Our primary focus lay in computing the correlation coefficient, a numerical representation of the bond between wind power generation in Italy and the price of gold. With a correlation coefficient of 0.9490346, we were left in awe of the steadfast connection unfurling before our eyes—a connection as strong as the sturdy blades of a wind turbine standing against the tempestuous forces of nature.

P-Value Determination:
Further fortifying our findings, we conducted a P-value analysis, a statistical ritual akin to deciphering the cryptic symbols inscribed on an ancient artifact. With a P-value of less than 0.01, our results shimmered with a resounding significance, leaving us with the sense that we had stumbled upon a treasure trove of statistical marvels.

In essence, our methodology embraced the winds of exploratory inquiry, navigating through the gales of data collection, the gusts of statistical analysis, and the zephyrs of economic insight. It was a quest that merged the rigor of science with the whimsy of discovery, unearthing a correlation as intriguing as a riddle whispered by the breeze amidst the rustling leaves.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Wind power generated in Italy and The price of gold. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and Kitco .

For the time period 1989 to 2014, you found a correlation 0.9490346, r-squared of 0.9006667, 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]]
Blowing in the Wind: How Italian Turbines and Bullion Mines Are Inclined

[[ABSTRACT]]
This paper uncovers the curious relationship between wind power generation in Italy and the price of gold. Through an analysis of data sourced from the Energy Information Administration and Kitco, our research team identified a strong positive correlation between the two seemingly disparate phenomena. The data points to a correlation coefficient of 0.9490346, indicating a remarkably close relationship, and a p-value of less than 0.01, reinforcing the statistical significance of the findings. Our study spans the years 1989 to 2014, offering a comprehensive exploration of this unexpected association. Juxtaposing the breezy nature of wind energy with the lustrous allure of gold prices, our research sheds light on the windy ties that bind these two distinct realms. The study not only provides insight into the intriguing interplay between energy production and commodity valuation but also offers a whimsical twist in the understanding of economic trends.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
Imagine a gust of wind, barreling through the Italian countryside, and then picture the glint of gold, nestled within the depths of a bullion mine. On the surface, these two entities seem worlds apart, akin to comparing the speed of snails to the pace of cheetahs. However, as our research team delved into the convoluted world of statistical analysis, we stumbled upon a discovery that would make even the most seasoned econometricians raise their eyebrows in disbelief.
The connection between wind power generation in Italy and the price of gold may seem as likely as finding a needle in a haystack in a tornado, but our findings unveil an unexpected relationship that will blow your mind more than a hurricane on a clear day. In our research, we combined the winds of statistical analysis with the golden nuggets of economic exploration to uncover a bond that's more intriguing than a detective novel written by a statistician with a penchant for puns.
As our study unravels the correlation coefficient of 0.9490346, we couldn't help but marvel at the sheer gusty magnitude of this connection. We observed a trend so robust, it's as if the windmills were whispering trade secrets to the bullion mines, and the gold prices were gleefully reciprocating with every gust, creating a symphony of economic entanglement that deserves a standing ovation. The p-value of less than 0.01 further solidifies the significance of this relationship, leaving us with the realization that this bond is as statistically strong as a bodybuilder flexing under the scrutiny of a rigorous t-test.
Our study spans the years 1989 to 2014, and like archaeologists dusting off ancient treasures, we unearthed a treasure trove of data that painted a compelling narrative of intertwining fates. It's as if the winds of fate were playfully nudging the gold prices, whispering, "Hey, I'm here, too," in an exchange that's more intricate than a dance between statistical outliers. With a conclusion that goes against the wind of conventional wisdom, our research stands as a testament to the unpredictable and oftentimes zephyrous nature of economic trends.
Join us as we embark on this whimsical journey, where the breeze carries the weight of economic influence and the price of gold dances to the rhythm of Italy's wind turbines. For in our exploration lies not just an understanding of the yin and yang of energy production and commodity valuation, but also a playful twist in the understanding of economic dynamics that's as refreshing as a gentle breeze on a scorching summer's day.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Our analysis of the relationship between wind power generation in Italy and the price of gold has blown away conventional expectations and opens up a whirlwind of possibilities in the world of economic research. The correlation coefficient of 0.9490346 speaks volumes about the unexpected harmony between these seemingly unrelated variables. It's as if the winds of change have zephyred through the world of economics, redefining the very essence of statistical influence.

The r-squared value of 0.9006667 underscores the strength of this connection, akin to a robust turbine weathering a gusty storm. The p-value of less than 0.01 seals the deal, indicating that this relationship is as significant as discovering the cure for statistical obscureness.

In Figure 1, the scatterplot visually encapsulates the spirited connection between wind power generation in Italy and the price of gold. It's a sight to behold, reflecting a correlation so prominent that even a casual observer would have to admit, "Well, isn't that a breezy coincidence?"

Our findings invite a playful interpretation of economic dynamics, hinting at a lighthearted dance between wind power and gold prices where the winds of Italy playfully beckon the shimmering allure of bullion. To think that this correlation has been breezing under the radar for so long is nothing short of a revelation.

This study not only adds a gust of whimsy to the world of economic analysis but also offers a refreshing breeze of insight into the undulating dance of energy production and commodity valuation. As we blow away the cobwebs of mundane economic research, our findings stand as a testament to the unforeseeable liaisons that can arise in the tempestuous realm of statistical analysis.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Wind power generated in Italy and The price of gold. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Blowing in the Wind: How Italian Turbines and Bullion Mines Are Inclined

[[ABSTRACT]]
This paper uncovers the curious relationship between wind power generation in Italy and the price of gold. Through an analysis of data sourced from the Energy Information Administration and Kitco, our research team identified a strong positive correlation between the two seemingly disparate phenomena. The data points to a correlation coefficient of 0.9490346, indicating a remarkably close relationship, and a p-value of less than 0.01, reinforcing the statistical significance of the findings. Our study spans the years 1989 to 2014, offering a comprehensive exploration of this unexpected association. Juxtaposing the breezy nature of wind energy with the lustrous allure of gold prices, our research sheds light on the windy ties that bind these two distinct realms. The study not only provides insight into the intriguing interplay between energy production and commodity valuation but also offers a whimsical twist in the understanding of economic trends.

[[LITERATURE REVIEW]]
In "Wind Energy in Italy: A Case Study," Smith et al. examine the development and utilization of wind power in Italy, offering a comprehensive analysis of the country's initiatives in renewable energy. They discuss the technological advancements, policy frameworks, and socioeconomic implications of wind energy, providing a thorough understanding of its impact on the Italian energy landscape. Similarly, Doe and Jones, in "The Economics of Gold Mining," delve into the intricate workings of gold mining and its contribution to the global economy. Their research sheds light on the supply and demand dynamics, investment patterns, and geopolitical influences that shape the bullion market, offering a nuanced perspective on the valuation of gold.
Expanding beyond these seminal works, "The Italian Job" by Economist et al. presents a detailed account of Italy's economic trajectory, including its energy sector and resource management. While not specifically focused on wind power or gold prices, the book offers valuable insights into the broader economic context, setting the stage for understanding the interplay between renewable energy and commodity markets. In a similar vein, "The Alchemist" by Philosopher explores the mystical allure of treasure and destiny, albeit in a fictional realm. Although not a direct source of empirical data, the book presents a whimsical take on the quest for riches, inviting readers to ponder the enigmatic forces that govern economic pursuits and the pursuit of the fabled "Philosopher's Stone."
In a somewhat tangential but nonetheless entertaining vein, the movies "The Italian Job" and "Fool's Gold" provide cinematic escapades that, while not rooted in empirical research, offer a lighthearted glimpse into the world of heists and treasure hunting. While the plots may not directly relate to our study, we cannot dismiss the possibility of wind energy making a cameo in a future sequel, perhaps in the form of a renewable energy-powered getaway vehicle or a blustery obstacle for treasure hunters navigating the high seas.
As we navigate the windy intersection of renewable energy and precious metals, it is essential to appreciate the multifaceted layers of influence that extend beyond traditional economic analyses. With a gust of humor and a touch of whimsy, our literature review sets the stage for a light-hearted exploration of the unexpected ties between Italian turbines and bullion mines.

[[RESULTS]]
Our analysis of the relationship between wind power generation in Italy and the price of gold has blown away conventional expectations and opens up a whirlwind of possibilities in the world of economic research. The correlation coefficient of 0.9490346 speaks volumes about the unexpected harmony between these seemingly unrelated variables. It's as if the winds of change have zephyred through the world of economics, redefining the very essence of statistical influence.
The r-squared value of 0.9006667 underscores the strength of this connection, akin to a robust turbine weathering a gusty storm. The p-value of less than 0.01 seals the deal, indicating that this relationship is as significant as discovering the cure for statistical obscureness.
In Figure 1, the scatterplot visually encapsulates the spirited connection between wind power generation in Italy and the price of gold. It's a sight to behold, reflecting a correlation so prominent that even a casual observer would have to admit, "Well, isn't that a breezy coincidence?"
Our findings invite a playful interpretation of economic dynamics, hinting at a lighthearted dance between wind power and gold prices where the winds of Italy playfully beckon the shimmering allure of bullion. To think that this correlation has been breezing under the radar for so long is nothing short of a revelation.
This study not only adds a gust of whimsy to the world of economic analysis but also offers a refreshing breeze of insight into the undulating dance of energy production and commodity valuation. As we blow away the cobwebs of mundane economic research, our findings stand as a testament to the unforeseeable liaisons that can arise in the tempestuous realm of statistical analysis.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our research has uncovered a wind of change in the world of economic analysis, revealing a surprising link between wind power generation in Italy and the price of gold. The strong positive correlation between these seemingly unrelated variables not only raises eyebrows but also prompts a whirlwind of questions about the interconnectedness of economic phenomena. It appears that the winds of Italy have been quietly whispering their influence on the shiny world of bullion, creating a gust of excitement in the realm of statistical analysis.

Our findings are supported by the prior research, specifically the work of Smith et al. on wind energy in Italy and Doe and Jones on the economics of gold mining. Building upon these studies, our results demonstrate the playful interplay between renewable energy initiatives and commodity valuation, adding a breezy twist to the understanding of economic trends. This unexpected correlation has, in a sense, added a breath of fresh air to the conventional economic analyses, reminding us that the winds of statistical influence can blow in unexpectedly from the most unlikely of sources.

The visual representation of this relationship in our scatterplot, much like a wind map for economic forces, encapsulates the spirited connection between wind power generation and gold prices. It's as if the scatterplot itself is saying, "Look at this whirlwind romance! Who would have thought that gold prices could be so alluring to the winds of change?" Our findings not only bolster the existing literature but also invite a playful interpretation of economic dynamics, injecting a gust of whimsy into the field of statistical analysis.

As we blow away the cobwebs of mundane economic research, our study stands as a testament to the surprising liaisons that can arise in the tempestuous realm of statistical analysis. It is as if the winds of fate have eagerly embraced the turbines of Italy, blowing in a new era of economic insight and renewable energy romance. Our punny findings not only provide a breath of fresh air in the world of economic research but also remind us of the delightful zephyrs of curiosity that can lead to unexpected discoveries.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Wind power generated in Italy and The price of gold. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Blowing in the Wind: How Italian Turbines and Bullion Mines Are Inclined

[[ABSTRACT]]
This paper uncovers the curious relationship between wind power generation in Italy and the price of gold. Through an analysis of data sourced from the Energy Information Administration and Kitco, our research team identified a strong positive correlation between the two seemingly disparate phenomena. The data points to a correlation coefficient of 0.9490346, indicating a remarkably close relationship, and a p-value of less than 0.01, reinforcing the statistical significance of the findings. Our study spans the years 1989 to 2014, offering a comprehensive exploration of this unexpected association. Juxtaposing the breezy nature of wind energy with the lustrous allure of gold prices, our research sheds light on the windy ties that bind these two distinct realms. The study not only provides insight into the intriguing interplay between energy production and commodity valuation but also offers a whimsical twist in the understanding of economic trends.

[[INTRDUCTION]]
INTRODUCTION
Imagine a gust of wind, barreling through the Italian countryside, and then picture the glint of gold, nestled within the depths of a bullion mine. On the surface, these two entities seem worlds apart, akin to comparing the speed of snails to the pace of cheetahs. However, as our research team delved into the convoluted world of statistical analysis, we stumbled upon a discovery that would make even the most seasoned econometricians raise their eyebrows in disbelief.
The connection between wind power generation in Italy and the price of gold may seem as likely as finding a needle in a haystack in a tornado, but our findings unveil an unexpected relationship that will blow your mind more than a hurricane on a clear day. In our research, we combined the winds of statistical analysis with the golden nuggets of economic exploration to uncover a bond that's more intriguing than a detective novel written by a statistician with a penchant for puns.
As our study unravels the correlation coefficient of 0.9490346, we couldn't help but marvel at the sheer gusty magnitude of this connection. We observed a trend so robust, it's as if the windmills were whispering trade secrets to the bullion mines, and the gold prices were gleefully reciprocating with every gust, creating a symphony of economic entanglement that deserves a standing ovation. The p-value of less than 0.01 further solidifies the significance of this relationship, leaving us with the realization that this bond is as statistically strong as a bodybuilder flexing under the scrutiny of a rigorous t-test.
Our study spans the years 1989 to 2014, and like archaeologists dusting off ancient treasures, we unearthed a treasure trove of data that painted a compelling narrative of intertwining fates. It's as if the winds of fate were playfully nudging the gold prices, whispering, "Hey, I'm here, too," in an exchange that's more intricate than a dance between statistical outliers. With a conclusion that goes against the wind of conventional wisdom, our research stands as a testament to the unpredictable and oftentimes zephyrous nature of economic trends.
Join us as we embark on this whimsical journey, where the breeze carries the weight of economic influence and the price of gold dances to the rhythm of Italy's wind turbines. For in our exploration lies not just an understanding of the yin and yang of energy production and commodity valuation, but also a playful twist in the understanding of economic dynamics that's as refreshing as a gentle breeze on a scorching summer's day.

[[RESULTS]]
Our analysis of the relationship between wind power generation in Italy and the price of gold has blown away conventional expectations and opens up a whirlwind of possibilities in the world of economic research. The correlation coefficient of 0.9490346 speaks volumes about the unexpected harmony between these seemingly unrelated variables. It's as if the winds of change have zephyred through the world of economics, redefining the very essence of statistical influence.
The r-squared value of 0.9006667 underscores the strength of this connection, akin to a robust turbine weathering a gusty storm. The p-value of less than 0.01 seals the deal, indicating that this relationship is as significant as discovering the cure for statistical obscureness.
In Figure 1, the scatterplot visually encapsulates the spirited connection between wind power generation in Italy and the price of gold. It's a sight to behold, reflecting a correlation so prominent that even a casual observer would have to admit, "Well, isn't that a breezy coincidence?"
Our findings invite a playful interpretation of economic dynamics, hinting at a lighthearted dance between wind power and gold prices where the winds of Italy playfully beckon the shimmering allure of bullion. To think that this correlation has been breezing under the radar for so long is nothing short of a revelation.
This study not only adds a gust of whimsy to the world of economic analysis but also offers a refreshing breeze of insight into the undulating dance of energy production and commodity valuation. As we blow away the cobwebs of mundane economic research, our findings stand as a testament to the unforeseeable liaisons that can arise in the tempestuous realm of statistical analysis.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has unraveled a connection between wind power generation in Italy and the price of gold that's as compelling as a whimsical plot twist in an economic narrative. The robust correlation coefficient and r-squared value paint a picture of a relationship as formidable as a gusty gale, stirring up the world of economic dynamics with an unexpected playfulness. It's as if the winds of Italy were whispering secrets to the bullion mines, and the gold prices were gleefully reciprocating with every gust, creating a symphony of economic entanglement that dazzles like a trove of statistical treasures.

Our findings suggest that the winds of change have ushered in a new era of economic exploration, redefining the very essence of statistical influence with a playful twist. As economists navigate this zephyrous dance between wind power and gold prices, they'll be reminded that there's always room for unexpected connections in this tempestuous realm of statistical analysis. However, it seems the time has come to let this particular zephyr settle – no more research is needed in this area, for now, we're content with letting this breezy conundrum blow in the wind of academic curiosity.


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 Blowing in the Wind: How Italian Turbines and Bullion Mines Are Inclined. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Environmental Engineering and Geology


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 Blowing in the Wind: How Italian Turbines and Bullion Mines Are Inclined. Respond only with the name of a fictional organization.

ChatGPT:

The International Society for Alternative Energy 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 Blowing in the Wind: How Italian Turbines and Bullion Mines Are Inclined with an abstract of This paper uncovers the curious relationship between wind power generation in Italy and the price of gold. Through an analysis of data sourced from the Energy Information Administration and Kitco, our research team identified a strong positive correlation between the two seemingly disparate phenomena. The data points to a correlation coefficient of 0.9490346, indicating a remarkably close relationship, and a p-value of less than 0.01, reinforcing the statistical significance of the findings. Our study spans the years 1989 to 2014, offering a comprehensive exploration of this unexpected association. Juxtaposing the breezy nature of wind energy with the lustrous allure of gold prices, our research sheds light on the windy ties that bind these two distinct realms. The study not only provides insight into the intriguing interplay between energy production and commodity valuation but also offers a whimsical twist in the understanding of economic trends.

ChatGPT:

wind power generation, Italy, gold prices, correlation, Energy Information Administration, Kitco, correlation coefficient, p-value, statistical significance, economic trends

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



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Data details

Wind power generated in Italy
Detailed data title: Total wind power generated in Italy in billion kWh
Source: Energy Information Administration
See what else correlates with Wind power generated in Italy

The price of gold
Detailed data title: Yearly cumulative average of London PM fix gold price
Source: Kitco
See what else correlates with The price of gold

Correlation r = 0.9490346 (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 = 0.9006667 (Coefficient of determination)
This means 90.1% of the change in the one variable (i.e., The price of gold) is predictable based on the change in the other (i.e., Wind power generated in Italy) over the 26 years from 1989 through 2014.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.6E-13. 0.0000000000001560795000939902
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 0.95 in 1.6E-11% of random cases. Said differently, if you correlated 6,406,991,305,058 random variables You don't actually need 6 trillion 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 25 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 25 because we have two variables measured over a period of 26 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.

[ 0.89, 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.
19891990199119921993199419951996199719981999200020012002200320042005200620072008200920102011201220132014
Wind power generated in Italy (Billion kWh)0.00190.0020.0030.0020.0040.0070.0090.0330.1180.2310.4030.5631.1791.4041.4581.8472.3442.9714.0344.8616.5439.0489.77513.33314.81215.089
The price of gold (In USD per ounce)381.44383.51362.11343.82359.77384383.792387.81331.02294.24278.98279.11271.04309.73363.38409.72444.74603.46695.39871.96972.351224.531571.521668.981411.231291.88




Why this works

  1. Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 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([0.0019,0.002,0.003,0.002,0.004,0.007,0.009,0.033,0.118,0.231,0.403,0.563,1.179,1.404,1.458,1.847,2.344,2.971,4.034,4.861,6.543,9.048,9.775,13.333,14.812,15.089,])
array_2 = np.array([381.44,383.51,362.11,343.82,359.77,384,383.792,387.81,331.02,294.24,278.98,279.11,271.04,309.73,363.38,409.72,444.74,603.46,695.39,871.96,972.35,1224.53,1571.52,1668.98,1411.23,1291.88,])
array_1_name = "Wind power generated in Italy"
array_2_name = "The price of gold"

# 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: 2307 · Black Variable ID: 23750 · Red Variable ID: 346
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