Spurious correlation #1,896 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Hydopower energy generated in South Africa and the second variable is The number of school teachers in North Carolina. The chart goes from 2010 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Hydopower energy generated in South Africa and the second variable is The number of school teachers in North Carolina. The chart goes from 2010 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The production of less hydropower in South Africa led to a shortage of energy, causing a ripple effect on the global energy market. This, in turn, inflated the cost of producing electricity in North Carolina. Facing budget constraints, the state had to make cuts in various sectors, including education. As a result, there was a decrease in the number of school teachers in North Carolina. Who would have thought that a small hiccup in hydropower production could have such far-reaching consequences for the education system in a completely different continent!

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image of a vibrant and dynamic landscape split into two halves. On the left, depict a powerful rushing river cutting through a verdant, lush South African landscape, with a hydroelectric dam strategically placed to harness its energy. On the right, showcase a bustling, energetic classroom scene in North Carolina, filled with enthusiastic educators engaging with students, surrounded by a supportive community of dedicated school teachers. The composition should convey the contrast between natural energy generation and the nurturing of human potential in an evocative and visually striking manner. 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: Hydopower energy generated in South Africa and The number of school teachers in North Carolina. 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: An image that looks like it is a scene from a Pixar movie Low poly A Discovery magazine cover image Steampunk Minimalism
ChatGPT: A Discovery magazine cover image

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 Hydopower energy generated in South Africa and The number of school teachers in North Carolina together. Keep the description simple.
ChatGPT: A rushing river flows through a lush, green landscape in South Africa, with a hydroelectric dam harnessing the power of the water to generate energy. In the distance, a group of educators in North Carolina gather in a lively classroom, supported by a strong community of school teachers dedicated to shaping the future.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A Discovery magazine cover image ] and depicting this scene: A rushing river flows through a lush, green landscape in South Africa, with a hydroelectric dam harnessing the power of the water to generate energy. In the distance, a group of educators in North Carolina gather in a lively classroom, supported by a strong community of school teachers dedicated to shaping the future. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a vibrant and dynamic landscape split into two halves. On the left, depict a powerful rushing river cutting through a verdant, lush South African landscape, with a hydroelectric dam strategically placed to harness its energy. On the right, showcase a bustling, energetic classroom scene in North Carolina, filled with enthusiastic educators engaging with students, surrounded by a supportive community of dedicated school teachers. The composition should convey the contrast between natural energy generation and the nurturing of human potential in an evocative and visually striking manner.

*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.
^{Show prompt for explanation} 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 a decrease in Hydopower energy generated in South Africa caused The number of school teachers in North Carolina to decrease.

AI academic paper

(Because p < 0.01)

Sparking Curiosity: The Hydro-powered Connection Between South African Energy and North Carolina's Teaching Staff

The Journal of Eclectic Energy Studies

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} 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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Hydopower energy generated in South Africa and The number of school teachers in North Carolina. 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 cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
"Sparking Curiosity: The Hydro-powered Connection Between South African Energy and North Carolina's Teaching Staff"

[[ABSTRACT]]
In this paper, we delve into the electrifying connection between the hydropower energy generated in South Africa and the number of school teachers in North Carolina. While these two seemingly unrelated factors may appear as far apart as the Cape of Good Hope and the Outer Banks, our research paints a different picture. By harnessing data from the Energy Information Administration and the Bureau of Labor Statistics, we unveil a surprising correlation. With a striking correlation coefficient of 0.9266523 and p < 0.01, our findings provide compelling evidence of a magnetic relationship between these variables from 2010 to 2021. Join us on this illuminating journey as we navigate the currents of energy and education to shed light on this thought-provoking association.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As we plug into the fascinating world of energy and education, it is often the unexpected connections that leave us truly electrified. While it might seem like a leap from hydroelectric power in South Africa to the number of school teachers in North Carolina, our research sets out to show that these seemingly distant domains are more entwined than one might imagine. One could say we are embarking on a journey where the currents of energy and education converge in a shockingly illuminating manner.
The use of hydropower as a source of energy has been a dam good solution for many countries, including South Africa, where it accounts for a significant portion of the nation's energy production. Meanwhile, on the other side of the globe, North Carolina boasts a rich pool of teaching talents, though the ebb and flow of their numbers may seem far removed from the rivers and turbines of South Africa. Nevertheless, as we dive deeper into the data, we find ourselves awash in a wave of unexpected correlations and interconnectedness.
Our study aims to bridge the gap between these two domains, shedding light on the underlying forces that seem to bind them together. Just as a hydroelectric dam generates power by harnessing the force of flowing water, our research seeks to harness the flow of data to reveal the currents that connect South African energy production to the educational landscape of North Carolina. And let's face it, who wouldn't be amped up to uncover such an unexpected relationship?
So, dear reader, join us as we embark on this academic adventure. While the path may wind through complex statistical analyses and rigorous methodology, we assure you that the journey promises some shocking revelations that will leave you positively charged with new insights. Let's dive in and ride the wave of discovery together!

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The interplay between hydropower energy in South Africa and the number of school teachers in North Carolina has sparked considerable interest and, dare I say, sparked a certain current of curiosity among researchers in recent years. While this topic may seem like a "current" buzz in the academic world, it is worth noting that the connection between energy production and the labor market has been a source of ongoing inquiry.

Smith et al. (2015) first shed light on the potential link between hydropower generation and educational staffing patterns, setting the stage for our own electrifying investigation. Their study, "Rivers of Talent: Exploring the Nexus of Hydropower and Teacher Supply," laid the groundwork for understanding how the ebb and flow of energy sources may have a ripple effect on the labor force. Building on this seminal work, Doe (2018) conducted a comprehensive analysis titled "The Current State of Educational Employment in the Wake of Hydropower Expansion," which revealed some shocking correlations between hydroelectric expansion and employment trends in the education sector.

However, as we delved deeper into the literature, we found ourselves venturing into uncharted territory, crossing the bridge between conventional academic studies and more unexpected sources of inspiration. Books such as "The Water Will Come: Rising Seas, Sinking Cities, and the Remaking of the Civilized World" by Jeff Goodell and "Liquid Rules: The Delightful and Dangerous Substances That Flow Through Our Lives" by Mark Miodownik offered intriguing perspectives on the fluid dynamics of energy and its impact on societal structures.

Of course, in the spirit of unearthing unexpected connections, one cannot overlook the influence of fiction on our understanding of real-world phenomena. Novels like "The Secret Life of Bees" by Sue Monk Kidd and "A River Runs Through It" by Norman Maclean, while not overtly related to our subject, do serve as a reminder of the powerful imagery and symbolism associated with water – a theme that undoubtedly permeates our exploration of energy and education.

But let's not stop there. As we navigated the currents of research, we found ourselves drifting into the realm of childhood memories and animated influences. Cartoons such as "The Magic School Bus" and "Captain Planet and the Planeteers" offered simplistic yet endearing portrayals of environmental dynamics and the importance of education, albeit with the occasional dose of whimsy and anthropomorphized eco-friendly superheroes.

While these sources may not align directly with the scholarly canon, they underscore the pervasive nature of water-related themes and their impact on our perspectives, both academic and otherwise. After all, what better way to illustrate the interconnectedness of hydropower and education than through a whimsical journey down memory lane?

So, as we wade into the depths of academic inquiry, let us not forget the unexpected reservoirs of insight that lie beyond the confines of traditional research. The ripples of knowledge, it seems, can originate from the unlikeliest of sources, and it is in embracing this diversity of influences that we truly illuminate the multifaceted nature of our subject matter.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Hydopower energy generated in South Africa and The number of school teachers in North Carolina. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Sparking Curiosity: The Hydro-powered Connection Between South African Energy and North Carolina's Teaching Staff"

[[ABSTRACT]]
In this paper, we delve into the electrifying connection between the hydropower energy generated in South Africa and the number of school teachers in North Carolina. While these two seemingly unrelated factors may appear as far apart as the Cape of Good Hope and the Outer Banks, our research paints a different picture. By harnessing data from the Energy Information Administration and the Bureau of Labor Statistics, we unveil a surprising correlation. With a striking correlation coefficient of 0.9266523 and p < 0.01, our findings provide compelling evidence of a magnetic relationship between these variables from 2010 to 2021. Join us on this illuminating journey as we navigate the currents of energy and education to shed light on this thought-provoking association.

[[LITERATURE REVIEW]]
The interplay between hydropower energy in South Africa and the number of school teachers in North Carolina has sparked considerable interest and, dare I say, sparked a certain current of curiosity among researchers in recent years. While this topic may seem like a "current" buzz in the academic world, it is worth noting that the connection between energy production and the labor market has been a source of ongoing inquiry.
Smith et al. (2015) first shed light on the potential link between hydropower generation and educational staffing patterns, setting the stage for our own electrifying investigation. Their study, "Rivers of Talent: Exploring the Nexus of Hydropower and Teacher Supply," laid the groundwork for understanding how the ebb and flow of energy sources may have a ripple effect on the labor force. Building on this seminal work, Doe (2018) conducted a comprehensive analysis titled "The Current State of Educational Employment in the Wake of Hydropower Expansion," which revealed some shocking correlations between hydroelectric expansion and employment trends in the education sector.
However, as we delved deeper into the literature, we found ourselves venturing into uncharted territory, crossing the bridge between conventional academic studies and more unexpected sources of inspiration. Books such as "The Water Will Come: Rising Seas, Sinking Cities, and the Remaking of the Civilized World" by Jeff Goodell and "Liquid Rules: The Delightful and Dangerous Substances That Flow Through Our Lives" by Mark Miodownik offered intriguing perspectives on the fluid dynamics of energy and its impact on societal structures.
Of course, in the spirit of unearthing unexpected connections, one cannot overlook the influence of fiction on our understanding of real-world phenomena. Novels like "The Secret Life of Bees" by Sue Monk Kidd and "A River Runs Through It" by Norman Maclean, while not overtly related to our subject, do serve as a reminder of the powerful imagery and symbolism associated with water – a theme that undoubtedly permeates our exploration of energy and education.
But let's not stop there. As we navigated the currents of research, we found ourselves drifting into the realm of childhood memories and animated influences. Cartoons such as "The Magic School Bus" and "Captain Planet and the Planeteers" offered simplistic yet endearing portrayals of environmental dynamics and the importance of education, albeit with the occasional dose of whimsy and anthropomorphized eco-friendly superheroes.
While these sources may not align directly with the scholarly canon, they underscore the pervasive nature of water-related themes and their impact on our perspectives, both academic and otherwise. After all, what better way to illustrate the interconnectedness of hydropower and education than through a whimsical journey down memory lane?
So, as we wade into the depths of academic inquiry, let us not forget the unexpected reservoirs of insight that lie beyond the confines of traditional research. The ripples of knowledge, it seems, can originate from the unlikeliest of sources, and it is in embracing this diversity of influences that we truly illuminate the multifaceted nature of our subject matter.

[[RESULTS]]
The results of our investigation into the correlation between hydropower energy generated in South Africa and the number of school teachers in North Carolina are nothing short of shocking. Our data analysis revealed a striking correlation coefficient of 0.9266523, indicating a strong positive linear relationship between these seemingly disparate variables. In other words, it seems that when it rains, it pours – both in terms of hydropower generation and the number of educators in North Carolina.
Furthermore, the coefficient of determination (r-squared) of 0.8586845 suggests that a whopping 85.87% of the variability in the number of school teachers in North Carolina can be explained by the variation in hydropower energy generated in South Africa. It's as if the hydroelectric turbines in South Africa are directly churning out educators for the classrooms of North Carolina. Who would have thought that hydroelectric power could be such a powerhouse in the world of education?
The p-value of less than 0.01 confidently indicates that this relationship is not a mere statistical fluke but bears real significance. The probability of observing such a strong correlation between these variables by chance is lower than finding a needle in a haystack – or in this case, a hydroelectric generator in a river.
To visually illustrate this electrifying correlation, we present Figure 1, a scatterplot that unmistakably portrays the strong positive linear relationship between hydropower energy generated in South Africa and the number of school teachers in North Carolina. The data points resemble a surge of electric current, highlighting the undeniable connection between these two seemingly unrelated factors.
In conclusion, our findings provide compelling evidence of a magnetic relationship between hydropower energy in South Africa and the number of school teachers in North Carolina from 2010 to 2021. This unexpected correlation opens the floodgates to a new understanding of the interconnectedness between energy production and the educational workforce, leaving us positively charged with insights that challenge traditional boundaries.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study have illuminated an unexpected and undeniably "current" connection between hydropower energy generated in South Africa and the number of school teachers in North Carolina. These findings not only corroborate previous research but also shed light on the potential for hydroelectric power to power-up the educational workforce in distant corners of the globe.

Building upon the electrifying work of Smith et al. (2015) and Doe (2018), our research reaffirms the hypothesis that hydropower generation and educational staffing patterns are indeed intertwined. Like a river's eddy influencing the course of downstream currents, the expansion of hydropower in South Africa seems to make waves in the supply of educators in North Carolina. As our data posit, the "Rivers of Talent" indeed flow from one continent to another, much like the waters of the Nile enrich the soil of the Nile Delta.

Moreover, our findings echo the resonant insights of Jeff Goodell and Mark Miodownik, who, in their literary works, remind us of the monumental impact that water – and by extension, hydropower – can have on societal structures. The symbolic resonance of water as a life-giving force is evident in the way hydropower seems to "nourish" the educational field, almost like a bountiful aquifer sustaining the verdant fields of academia.

Additionally, the strong correlation coefficient we observed further underscores the substantial impact of hydropower energy on the academic labor market. With a coefficient of determination that explains over 85% of the variation in the number of school teachers in North Carolina, it's clear that the ebb and flow of education is closely tied to the surges and currents of hydropower generation. This remarkable interplay suggests that hydroelectric power is no mere "drop in the bucket" when it comes to influencing the educational landscape.

While our study may seem like an unexpected detour into uncharted territory, the undeniable connection we've uncovered stands as a testament to the far-reaching and interconnected nature of our world – a world where hydroelectric turbines can inadvertently shape the composition of North Carolina's teaching staff, akin to the way a stone creates ripples when tossed into a pond.

In conclusion, our research serves as a beacon, illuminating the metaphorical bridge that unites the gushing streams of hydropower energy in South Africa with the tributaries of education in North Carolina. This surprising correlation challenges conventional wisdom and invites further exploration into the complex and often whimsical currents that underpin the relationship between energy production and the educational sphere.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Hydopower energy generated in South Africa and The number of school teachers in North Carolina. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Sparking Curiosity: The Hydro-powered Connection Between South African Energy and North Carolina's Teaching Staff"

[[ABSTRACT]]
In this paper, we delve into the electrifying connection between the hydropower energy generated in South Africa and the number of school teachers in North Carolina. While these two seemingly unrelated factors may appear as far apart as the Cape of Good Hope and the Outer Banks, our research paints a different picture. By harnessing data from the Energy Information Administration and the Bureau of Labor Statistics, we unveil a surprising correlation. With a striking correlation coefficient of 0.9266523 and p < 0.01, our findings provide compelling evidence of a magnetic relationship between these variables from 2010 to 2021. Join us on this illuminating journey as we navigate the currents of energy and education to shed light on this thought-provoking association.

[[INTRDUCTION]]
As we plug into the fascinating world of energy and education, it is often the unexpected connections that leave us truly electrified. While it might seem like a leap from hydroelectric power in South Africa to the number of school teachers in North Carolina, our research sets out to show that these seemingly distant domains are more entwined than one might imagine. One could say we are embarking on a journey where the currents of energy and education converge in a shockingly illuminating manner.
The use of hydropower as a source of energy has been a dam good solution for many countries, including South Africa, where it accounts for a significant portion of the nation's energy production. Meanwhile, on the other side of the globe, North Carolina boasts a rich pool of teaching talents, though the ebb and flow of their numbers may seem far removed from the rivers and turbines of South Africa. Nevertheless, as we dive deeper into the data, we find ourselves awash in a wave of unexpected correlations and interconnectedness.
Our study aims to bridge the gap between these two domains, shedding light on the underlying forces that seem to bind them together. Just as a hydroelectric dam generates power by harnessing the force of flowing water, our research seeks to harness the flow of data to reveal the currents that connect South African energy production to the educational landscape of North Carolina. And let's face it, who wouldn't be amped up to uncover such an unexpected relationship?
So, dear reader, join us as we embark on this academic adventure. While the path may wind through complex statistical analyses and rigorous methodology, we assure you that the journey promises some shocking revelations that will leave you positively charged with new insights. Let's dive in and ride the wave of discovery together!

[[RESULTS]]
The results of our investigation into the correlation between hydropower energy generated in South Africa and the number of school teachers in North Carolina are nothing short of shocking. Our data analysis revealed a striking correlation coefficient of 0.9266523, indicating a strong positive linear relationship between these seemingly disparate variables. In other words, it seems that when it rains, it pours – both in terms of hydropower generation and the number of educators in North Carolina.
Furthermore, the coefficient of determination (r-squared) of 0.8586845 suggests that a whopping 85.87% of the variability in the number of school teachers in North Carolina can be explained by the variation in hydropower energy generated in South Africa. It's as if the hydroelectric turbines in South Africa are directly churning out educators for the classrooms of North Carolina. Who would have thought that hydroelectric power could be such a powerhouse in the world of education?
The p-value of less than 0.01 confidently indicates that this relationship is not a mere statistical fluke but bears real significance. The probability of observing such a strong correlation between these variables by chance is lower than finding a needle in a haystack – or in this case, a hydroelectric generator in a river.
To visually illustrate this electrifying correlation, we present Figure 1, a scatterplot that unmistakably portrays the strong positive linear relationship between hydropower energy generated in South Africa and the number of school teachers in North Carolina. The data points resemble a surge of electric current, highlighting the undeniable connection between these two seemingly unrelated factors.
In conclusion, our findings provide compelling evidence of a magnetic relationship between hydropower energy in South Africa and the number of school teachers in North Carolina from 2010 to 2021. This unexpected correlation opens the floodgates to a new understanding of the interconnectedness between energy production and the educational workforce, leaving us positively charged with insights that challenge traditional boundaries.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

As we wrap up this electrifying exploration, we have both sparked curiosity and shed light on the shockingly magnetic connection between hydropower energy in South Africa and the number of school teachers in North Carolina. Our research has unveiled a relationship so compelling, it's like finding a teacher's red pen in a sea of blue ink – unexpected, but undeniably linked.

With a correlation coefficient of 0.9266523, our findings suggest that there's more to this connection than meets the eye. It's as if the rivers of South Africa are not only flowing with water, but with the very essence of education itself, creating a current that pulls educators across continents.

The coefficient of determination of 0.8586845 further cements the notion that the ebb and flow of hydropower in South Africa has a shocking impact on the educational landscape of North Carolina. It's almost as if Mother Nature herself is running a teacher recruitment agency, using the power of water to churn out educators like hydroelectric turbines churn out energy.

But fear not, dear reader, for this is no statistical fluke. With a p-value of less than 0.01, we can confidently say that this connection is as real as finding a penny on the ground – it may seem small, but it's definitely worth picking up.

In summary, our research has bridged the gap between these seemingly distant domains, revealing a current of interconnectedness that challenges conventional wisdom. The implications of this unexpected correlation are as monumental as a hydroelectric dam, shaping our understanding of the intricate web of relationships that exist within the realms of energy and education, and leaving us thoroughly charged with newfound insights.

In conclusion, it seems the age-old saying holds true: when it rains, it pours – both in terms of water and wisdom. Our findings point to a dazzling correlation that needs no further current research.

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 Sparking Curiosity: The Hydro-powered Connection Between South African Energy and North Carolina's Teaching Staff. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Eclectic Energy Studies

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 Sparking Curiosity: The Hydro-powered Connection Between South African Energy and North Carolina's Teaching Staff. Respond only with the name of a fictional organization.

ChatGPT:

Institute for Global Energy Solutions

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 Sparking Curiosity: The Hydro-powered Connection Between South African Energy and North Carolina's Teaching Staff with an abstract of In this paper, we delve into the electrifying connection between the hydropower energy generated in South Africa and the number of school teachers in North Carolina. While these two seemingly unrelated factors may appear as far apart as the Cape of Good Hope and the Outer Banks, our research paints a different picture. By harnessing data from the Energy Information Administration and the Bureau of Labor Statistics, we unveil a surprising correlation. With a striking correlation coefficient of 0.9266523 and p < 0.01, our findings provide compelling evidence of a magnetic relationship between these variables from 2010 to 2021. Join us on this illuminating journey as we navigate the currents of energy and education to shed light on this thought-provoking association.

ChatGPT:

Hydropower energy, South Africa, North Carolina, teaching staff, energy generation, correlation, Energy Information Administration, Bureau of Labor Statistics, correlation coefficient, education, association, magnetism, data analysis, research findings

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

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Data details

Hydopower energy generated in South Africa
Detailed data title: Total hydopower energy generated in South Africa in billion kWh
Source: Energy Information Administration
See what else correlates with Hydopower energy generated in South Africa

The number of school teachers in North Carolina
Detailed data title: BLS estimate of secondary school teachers, except special and career/technical education in North Carolina
Source: Bureau of Larbor Statistics
See what else correlates with The number of school teachers in North Carolina

Correlation r = 0.9266523 (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 = 0.8586845 (Coefficient of determination)
This means 85.9% of the change in the one variable (i.e., The number of school teachers in North Carolina) is predictable based on the change in the other (i.e., Hydopower energy generated in South Africa) over the 12 years from 2010 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.5E-5.^Show 0.0000147685588035318080000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note 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 0.0015% of random cases. Said differently, if you correlated 67,711 random variables^Note You don't actually need 67 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, ^Note 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.

[ 0.75, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} 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: ^Note 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.

	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Hydopower energy generated in South Africa (Billion kWh)	2.093	2.036	1.193	1.10682	0.90387	0.8019	0.67419	0.81	1.104	0.731	1.444	1.47333
The number of school teachers in North Carolina (Laborers)	26990	26970	24450	24190	23730	22960	23760	24170	25240	24030	24820	26080

Why this works

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.
Lack of causal connection: There is probably^Note 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.
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^Note 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.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} 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([2.093,2.036,1.193,1.10682,0.90387,0.8019,0.67419,0.81,1.104,0.731,1.444,1.47333,])
array_2 = np.array([26990,26970,24450,24190,23730,22960,23760,24170,25240,24030,24820,26080,])
array_1_name = "Hydopower energy generated in South Africa"
array_2_name = "The number of school teachers in North Carolina"

# 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)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

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.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Hydopower energy generated in South Africa
Line chart for only The number of school teachers in North Carolina
AI-generated correlation image
The spurious research paper: Sparking Curiosity: The Hydro-powered Connection Between South African Energy and North Carolina's Teaching Staff

View another random correlation

How fun was this correlation?

You're the correlation whisperer we needed!

Correlation ID: 1896 · Black Variable ID: 23985 · Red Variable ID: 18442


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