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Spurious correlation #5,012 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air quality in Grand Forks, North Dakota and the second variable is Electricity generation in Azerbaijan.  The chart goes from 1992 to 2001, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

The cleaner air in Grand Forks led to an increase in productivity among the local goose population. These highly motivated geese then embarked on a goodwill tour to Azerbaijan, where they were welcomed as symbols of environmental purity. In a surprising turn of events, the government of Azerbaijan, deeply moved by the avian ambassadors, decided to invest heavily in wind energy as a gesture of solidarity with the geese. And that's how the improved air quality in one part of the world sparked a renewable energy revolution in another. Or, it could all just be a coincidence.

Model: dalle-3
Prompt: Generate an image of a flock of geese soaring gracefully through a futuristic landscape. The blue sky behind them is filled with sleek, towering wind turbines that mimic the geese's flight pattern. The geese are depicted in a shimmering, almost holographic style, embodying a sense of environmental purity and technological advancement. The landscape below the geese is a blend of Grand Forks, North Dakota, and Azerbaijan, featuring rolling hills and modern, sustainable infrastructure. The scene exudes a sense of harmony and celebration, capturing the geese's joyous migration and their impact on the futuristic world around them. 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: Air quality in Grand Forks, North Dakota and Electricity generation in Azerbaijan. 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: Charcoal Data cyber art Cyberpunk Futuristic Low poly
ChatGPT: Futuristic

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 Air quality in Grand Forks, North Dakota and Electricity generation in Azerbaijan, in the following situation: The cleaner air in Grand Forks led to an increase in productivity among the local goose population. These highly motivated geese then embarked on a goodwill tour to Azerbaijan, where they were welcomed as symbols of environmental purity. In a surprising turn of events, the government of Azerbaijan, deeply moved by the avian ambassadors, decided to invest heavily in wind energy as a gesture of solidarity with the geese. And that's how the improved air quality in one part of the world sparked a renewable energy revolution in another. Or, it could all just be a coincidence.. Keep the description simple.
ChatGPT: In Grand Forks, North Dakota, a flock of energetic and content geese honked joyfully as they effortlessly soared through the clear, fresh air. Their wings beat rhythmically against the backdrop of a blue sky, their sharp eyes taking in the stunning view below. As the geese joyfully migrated, they landed gracefully in Azerbaijan, where they were welcomed with open arms by the local community. The geese, hailed as symbols of environmental purity, were celebrated and revered for the positive impact they had on their surroundings. In response to this unexpected visit, the government of Azerbaijan took decisive action, wholeheartedly investing in the expansive, graceful wind turbines that now punctuate the country’s landscape.

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: [ Futuristic ] and depicting this scene: In Grand Forks, North Dakota, a flock of energetic and content geese honked joyfully as they effortlessly soared through the clear, fresh air. Their wings beat rhythmically against the backdrop of a blue sky, their sharp eyes taking in the stunning view below. As the geese joyfully migrated, they landed gracefully in Azerbaijan, where they were welcomed with open arms by the local community. The geese, hailed as symbols of environmental purity, were celebrated and revered for the positive impact they had on their surroundings. In response to this unexpected visit, the government of Azerbaijan took decisive action, wholeheartedly investing in the expansive, graceful wind turbines that now punctuate the country’s landscape. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a flock of geese soaring gracefully through a futuristic landscape. The blue sky behind them is filled with sleek, towering wind turbines that mimic the geese's flight pattern. The geese are depicted in a shimmering, almost holographic style, embodying a sense of environmental purity and technological advancement. The landscape below the geese is a blend of Grand Forks, North Dakota, and Azerbaijan, featuring rolling hills and modern, sustainable infrastructure. The scene exudes a sense of harmony and celebration, capturing the geese's joyous migration and their impact on the futuristic world around them.

*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 increases in Air quality in Grand Forks, North Dakota positively influenced Electricity generation in Azerbaijan.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)
Shocking Connections: Unearthing the Electrifying Link Between Air Quality in Grand Forks, North Dakota and Electricity Generation in Azerbaijan

The Journal of Transcontinental Environmental Dynamics

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 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 Air quality in Grand Forks, North Dakota and Electricity generation in Azerbaijan. Make lots of jokes, goofy observations, and puns.

Make the title seem clever.

Your research team used data from Environmental Protection Agency and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.8730857 and p < 0.01 for 1992 to 2001.

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]]
Shocking Connections: Unearthing the Electrifying Link Between Air Quality in Grand Forks, North Dakota and Electricity Generation in Azerbaijan

[[ABSTRACT]]
In this study, we set out to shed some light on the inconceivable connection between air quality in the small town of Grand Forks, North Dakota, and the electricity generation practices in the faraway land of Azerbaijan. Despite the geographical distance and apparent lack of common ground, our research has uncovered a remarkably significant relationship. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we have calculated a correlation coefficient of 0.8730857 and a p-value of less than 0.01 for the period spanning from 1992 to 2001. Our results not only provide astonishing evidence of the link between these seemingly disparate factors but also may potentially facilitate a spark of change in the international energy landscape. As we delve deeper into this electrifying correlation, it becomes clear that the currents of environmental impact transcend borders and continents, ultimately showing that there is truly no "air" distance when it comes to the interplay of air quality and electricity generation.


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Air quality in Grand Forks, North Dakota and Electricity generation in Azerbaijan. 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]]
Shocking Connections: Unearthing the Electrifying Link Between Air Quality in Grand Forks, North Dakota and Electricity Generation in Azerbaijan

[[ABSTRACT]]
In this study, we set out to shed some light on the inconceivable connection between air quality in the small town of Grand Forks, North Dakota, and the electricity generation practices in the faraway land of Azerbaijan. Despite the geographical distance and apparent lack of common ground, our research has uncovered a remarkably significant relationship. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we have calculated a correlation coefficient of 0.8730857 and a p-value of less than 0.01 for the period spanning from 1992 to 2001. Our results not only provide astonishing evidence of the link between these seemingly disparate factors but also may potentially facilitate a spark of change in the international energy landscape. As we delve deeper into this electrifying correlation, it becomes clear that the currents of environmental impact transcend borders and continents, ultimately showing that there is truly no "air" distance when it comes to the interplay of air quality and electricity generation.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

As scientists, we are always seeking to illuminate the hidden connections that permeate our world, but little did we expect to stumble upon a discovery of such shockingly electrifying proportions. The chance to delve into the relationship between the air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan was too tantalizing to resist. After all, it's not every day that one gets to investigate the currents of correlation that flow between such disparate variables.

The tale of how we came to unearth this convoluted link is a story as compelling as any epic quest. Armed with a healthy dose of curiosity and an arsenal of statistical tools, we bravely ventured into the realm of data, determined to shine a spotlight on the enigmatic ties between air quality and electricity generation. Little did we know that our journey would lead us to a correlation coefficient of 0.8730857, a p-value of less than 0.01, and an understanding that the fates of air quality and electricity generation are intimately intertwined.

Some may wonder if our findings are simply a result of statistical flukes or the product of too many late-night research sessions, but we assure you that our methods were as rigorous as a marathon runner's training regimen. From analyzing data from the Environmental Protection Agency to poring over information from the Energy Information Administration, we left no stone unturned in our quest for answers.

But why, you may ask, should anyone care about this peculiar correlation between a small town in North Dakota and a nation halfway across the globe? Well, the implications of our discovery stretch further than a good dad joke. By shedding light on the interconnectedness of seemingly unrelated elements, we not only challenge conventional wisdom but also pave the way for a potential evolution in global energy strategies. After all, when it comes to the ties that bind air quality and electricity generation, it seems that there truly is no air distance too great to overcome.

So, without further ado, let us embark on a journey through the currents of correlation as we explore the gripping tale of air quality, electricity generation, and the electrifying connection that binds them together. As we unravel the strands of this tangled web, let us not forget that the world of science is often as full of surprises and twists as a good mystery novel. And with that, dear readers, we invite you to join us on this electrifying adventure of discovery and revelation.


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Air quality in Grand Forks, North Dakota and Electricity generation in Azerbaijan. 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]]
Shocking Connections: Unearthing the Electrifying Link Between Air Quality in Grand Forks, North Dakota and Electricity Generation in Azerbaijan

[[ABSTRACT]]
In this study, we set out to shed some light on the inconceivable connection between air quality in the small town of Grand Forks, North Dakota, and the electricity generation practices in the faraway land of Azerbaijan. Despite the geographical distance and apparent lack of common ground, our research has uncovered a remarkably significant relationship. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we have calculated a correlation coefficient of 0.8730857 and a p-value of less than 0.01 for the period spanning from 1992 to 2001. Our results not only provide astonishing evidence of the link between these seemingly disparate factors but also may potentially facilitate a spark of change in the international energy landscape. As we delve deeper into this electrifying correlation, it becomes clear that the currents of environmental impact transcend borders and continents, ultimately showing that there is truly no "air" distance when it comes to the interplay of air quality and electricity generation.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As scientists, we are always seeking to illuminate the hidden connections that permeate our world, but little did we expect to stumble upon a discovery of such shockingly electrifying proportions. The chance to delve into the relationship between the air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan was too tantalizing to resist. After all, it's not every day that one gets to investigate the currents of correlation that flow between such disparate variables.
The tale of how we came to unearth this convoluted link is a story as compelling as any epic quest. Armed with a healthy dose of curiosity and an arsenal of statistical tools, we bravely ventured into the realm of data, determined to shine a spotlight on the enigmatic ties between air quality and electricity generation. Little did we know that our journey would lead us to a correlation coefficient of 0.8730857, a p-value of less than 0.01, and an understanding that the fates of air quality and electricity generation are intimately intertwined.
Some may wonder if our findings are simply a result of statistical flukes or the product of too many late-night research sessions, but we assure you that our methods were as rigorous as a marathon runner's training regimen. From analyzing data from the Environmental Protection Agency to poring over information from the Energy Information Administration, we left no stone unturned in our quest for answers.
But why, you may ask, should anyone care about this peculiar correlation between a small town in North Dakota and a nation halfway across the globe? Well, the implications of our discovery stretch further than a good dad joke. By shedding light on the interconnectedness of seemingly unrelated elements, we not only challenge conventional wisdom but also pave the way for a potential evolution in global energy strategies. After all, when it comes to the ties that bind air quality and electricity generation, it seems that there truly is no air distance too great to overcome.
So, without further ado, let us embark on a journey through the currents of correlation as we explore the gripping tale of air quality, electricity generation, and the electrifying connection that binds them together. As we unravel the strands of this tangled web, let us not forget that the world of science is often as full of surprises and twists as a good mystery novel. And with that, dear readers, we invite you to join us on this electrifying adventure of discovery and revelation.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

To embark on our quest for unraveling the electrifying connection between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan, we first delve into the existing literature surrounding these two seemingly unrelated components. In "Air Quality in Small Towns" by Smith, the authors find that the air quality in small towns has a significant impact on the health and well-being of the community, but the book fails to mention any far-reaching connections to distant lands with exotic names like Azerbaijan. Following that, in "The Shocking Reality of Electricity Generation" by Doe, interesting insights are provided into the various methods of electricity generation, but in a shocking twist, no mention of connections to air quality in obscure locations is made. In stark contrast, Jones in "The Ties That Bind: Exploring Unlikely Connections" discusses surprising correlations discovered in the world, but unfortunately, fails to recognize the captivating link between air quality in Grand Forks and electricity generation in Azerbaijan.

As we traverse beyond the realms of academia, delving into the non-fiction realm, we peruse "The Air We Breathe: A Study of Environmental Impact" and "Sparks of Change: A Global Perspective on Electricity Generation" for illumination. However, as we flip through the pages, we find that these books, while informative, remain shockingly silent on the matter at hand. It appears that our quest for insight has hit a minor snag - or perhaps an electric shock!

Amidst the fictional landscape, we stumble upon "Electric Currents of Fate" and "The Winds of Energy: A Tale of Air and Electricity" – titles that, at first glance, seem to hold the promise of shedding light on our electrifying correlation. Unfortunately, we find ourselves swept into a world of fiction, where the connection between air quality and electricity generation remains as elusive as a yeti in the Himalayas.

Drawing inspiration from cinematic adventures, we whimsically consider the whimsical journey of "The Electric Airbender" and the high-voltage drama of "Azerbaijan Nights: The Spark Awakens." Alas, we find ourselves wading through a sea of popcorn instead of enlightenment, for these movies, while engaging, offer nothing of substance to our intriguing investigation.

As we meander through the labyrinth of literature, our journey takes an unexpected turn. Stay tuned as we dare to unravel the electrifying link between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan, amidst the titillating twists and tantalizing turns that research can often surprise us with. We promise the sparks will fly!


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Air quality in Grand Forks, North Dakota and Electricity generation in Azerbaijan. 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 Environmental Protection Agency and Energy Information Administration . You used data from 1992 to 2001

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]]
Shocking Connections: Unearthing the Electrifying Link Between Air Quality in Grand Forks, North Dakota and Electricity Generation in Azerbaijan

[[ABSTRACT]]
In this study, we set out to shed some light on the inconceivable connection between air quality in the small town of Grand Forks, North Dakota, and the electricity generation practices in the faraway land of Azerbaijan. Despite the geographical distance and apparent lack of common ground, our research has uncovered a remarkably significant relationship. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we have calculated a correlation coefficient of 0.8730857 and a p-value of less than 0.01 for the period spanning from 1992 to 2001. Our results not only provide astonishing evidence of the link between these seemingly disparate factors but also may potentially facilitate a spark of change in the international energy landscape. As we delve deeper into this electrifying correlation, it becomes clear that the currents of environmental impact transcend borders and continents, ultimately showing that there is truly no "air" distance when it comes to the interplay of air quality and electricity generation.

[[INTRODUCTION]]
As scientists, we are always seeking to illuminate the hidden connections that permeate our world, but little did we expect to stumble upon a discovery of such shockingly electrifying proportions. The chance to delve into the relationship between the air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan was too tantalizing to resist. After all, it's not every day that one gets to investigate the currents of correlation that flow between such disparate variables.
The tale of how we came to unearth this convoluted link is a story as compelling as any epic quest. Armed with a healthy dose of curiosity and an arsenal of statistical tools, we bravely ventured into the realm of data, determined to shine a spotlight on the enigmatic ties between air quality and electricity generation. Little did we know that our journey would lead us to a correlation coefficient of 0.8730857, a p-value of less than 0.01, and an understanding that the fates of air quality and electricity generation are intimately intertwined.
Some may wonder if our findings are simply a result of statistical flukes or the product of too many late-night research sessions, but we assure you that our methods were as rigorous as a marathon runner's training regimen. From analyzing data from the Environmental Protection Agency to poring over information from the Energy Information Administration, we left no stone unturned in our quest for answers.
But why, you may ask, should anyone care about this peculiar correlation between a small town in North Dakota and a nation halfway across the globe? Well, the implications of our discovery stretch further than a good dad joke. By shedding light on the interconnectedness of seemingly unrelated elements, we not only challenge conventional wisdom but also pave the way for a potential evolution in global energy strategies. After all, when it comes to the ties that bind air quality and electricity generation, it seems that there truly is no air distance too great to overcome.
So, without further ado, let us embark on a journey through the currents of correlation as we explore the gripping tale of air quality, electricity generation, and the electrifying connection that binds them together. As we unravel the strands of this tangled web, let us not forget that the world of science is often as full of surprises and twists as a good mystery novel. And with that, dear readers, we invite you to join us on this electrifying adventure of discovery and revelation.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To establish the link between air quality in Grand Forks, North Dakota, and electricity generation practices in Azerbaijan, our research team embarked on a journey that rivaled the zaniest of escapades. Our methodology was as comprehensive as an encyclopedia but as eccentric as a mad scientist's lab notes. We gathered data from the Environmental Protection Agency and the Energy Information Administration, utilizing information spanning from 1992 to 2001. Now, you might be wondering why we chose this time frame - was it a nostalgic nod to the heyday of grunge music and frosted tips? Not quite! We selected this period strategically to encapsulate an era where the delicate dance of air quality and electricity generation was ripe with potential discoveries.

Having secured our data treasure trove, we set about applying statistical wizardry to uncover the tantalizing link between these seemingly incongruous variables. Sweeping through the data like a detective at a crime scene, we sampled the air quality measurements in Grand Forks and cross-referenced them with the electricity generation statistics from Azerbaijan. The sheer audacity of this juxtaposition may have raised a few eyebrows, but we were undeterred in our pursuit of scientific comedy gold.

Our statistical analysis resembled a dance between two unlikely partners, with correlation coefficients shimmying alongside p-values in a mesmerizing tango. Through these statistical machinations, we calculated a correlation coefficient of 0.8730857 that would make even the most cynical onlooker raise an eyebrow in bemused surprise. The p-value of less than 0.01 provided further validation to our findings, as if to say, "Well, looks like these variables aren't just blowing hot air after all!"

Amidst these calculations, we ensured that our methodology adhered to the highest standards of scientific rigor. We applied multivariate regression models with the grace of a seasoned conductor leading an orchestra, harmonizing the variables in a symphony of statistical elegance. We crossed our t's, dotted our i's, and even threw in a few semicolons for good measure, just to ensure that our findings were as robust as a sumo wrestler in a tug-of-war contest.

In capturing the essence of our research methodology, we must emphasize that our approach was as meticulously planned as a NASA launch but as delightfully unpredictable as a game of scientific roulette. This whimsical blend of thoroughness and audacity epitomizes the spirit of scientific inquiry - an adventure that is as full of surprises and comedic twists as a slapstick comedy show.

So there you have it - the methodology behind our electrifying pursuit of the unseen connections between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan. As we dare to peer into the mysterious depths of scientific investigation, let us never forget that the pursuit of knowledge should always be as exciting and enigmatic as an intriguing whodunit novel. And with that, dear readers, we invite you to revel in the thrilling absurdity of our scientific odyssey.


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Air quality in Grand Forks, North Dakota and Electricity generation in Azerbaijan. 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 Environmental Protection Agency and Energy Information Administration .

For the time period 1992 to 2001, you found a correlation 0.8730857, r-squared of 0.7622786, 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]]
Shocking Connections: Unearthing the Electrifying Link Between Air Quality in Grand Forks, North Dakota and Electricity Generation in Azerbaijan

[[ABSTRACT]]
In this study, we set out to shed some light on the inconceivable connection between air quality in the small town of Grand Forks, North Dakota, and the electricity generation practices in the faraway land of Azerbaijan. Despite the geographical distance and apparent lack of common ground, our research has uncovered a remarkably significant relationship. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we have calculated a correlation coefficient of 0.8730857 and a p-value of less than 0.01 for the period spanning from 1992 to 2001. Our results not only provide astonishing evidence of the link between these seemingly disparate factors but also may potentially facilitate a spark of change in the international energy landscape. As we delve deeper into this electrifying correlation, it becomes clear that the currents of environmental impact transcend borders and continents, ultimately showing that there is truly no "air" distance when it comes to the interplay of air quality and electricity generation.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
As scientists, we are always seeking to illuminate the hidden connections that permeate our world, but little did we expect to stumble upon a discovery of such shockingly electrifying proportions. The chance to delve into the relationship between the air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan was too tantalizing to resist. After all, it's not every day that one gets to investigate the currents of correlation that flow between such disparate variables.
The tale of how we came to unearth this convoluted link is a story as compelling as any epic quest. Armed with a healthy dose of curiosity and an arsenal of statistical tools, we bravely ventured into the realm of data, determined to shine a spotlight on the enigmatic ties between air quality and electricity generation. Little did we know that our journey would lead us to a correlation coefficient of 0.8730857, a p-value of less than 0.01, and an understanding that the fates of air quality and electricity generation are intimately intertwined.
Some may wonder if our findings are simply a result of statistical flukes or the product of too many late-night research sessions, but we assure you that our methods were as rigorous as a marathon runner's training regimen. From analyzing data from the Environmental Protection Agency to poring over information from the Energy Information Administration, we left no stone unturned in our quest for answers.
But why, you may ask, should anyone care about this peculiar correlation between a small town in North Dakota and a nation halfway across the globe? Well, the implications of our discovery stretch further than a good dad joke. By shedding light on the interconnectedness of seemingly unrelated elements, we not only challenge conventional wisdom but also pave the way for a potential evolution in global energy strategies. After all, when it comes to the ties that bind air quality and electricity generation, it seems that there truly is no air distance too great to overcome.
So, without further ado, let us embark on a journey through the currents of correlation as we explore the gripping tale of air quality, electricity generation, and the electrifying connection that binds them together. As we unravel the strands of this tangled web, let us not forget that the world of science is often as full of surprises and twists as a good mystery novel. And with that, dear readers, we invite you to join us on this electrifying adventure of discovery and revelation.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The data analysis revealed a shockingly strong correlation between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan during the period from 1992 to 2001. The correlation coefficient of 0.8730857 left us feeling positively charged, and the r-squared value of 0.7622786 confirmed that there's certainly an electrifying link between these two seemingly unrelated variables. With a p-value of less than 0.01, we can confidently say that this connection is statistically significant, sparking our interest even further.

Our findings are visually showcased in Fig. 1, a scatterplot that illustrates the striking relationship between air quality and electricity generation. Think of it as a thrilling rollercoaster ride through the peaks and valleys of correlation, where the data points are like small, electrified particles dancing across the chart.

It's fascinating to consider the implications of these results. Who would have thought that a town known for its love of hockey and a country famous for its fire-blanket-wrestling would be linked in such a meaningful way? The currents of correlation truly flow in mysterious ways.

So, what does this all mean? Well, it seems that when it comes to the invisible threads that connect air quality and electricity generation, the world of science continues to astound us with its shocking revelations. Our discovery might just generate a powerful buzz in the fields of energy policy and environmental protection. After all, it's a stark reminder that the impact of our actions is not confined to one location or sector, and that the interconnected web of forces at play in our world is full of surprises.

In conclusion, our research has not only illuminated the surprisingly strong link between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan but also added a jolt of excitement to the study of environmental and energy dynamics. We hope that our findings will energize further exploration and foster a current of creativity in addressing these critical issues. Let's keep our eyes peeled and our minds open for more shockingly electrifying connections in the future!


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Air quality in Grand Forks, North Dakota and Electricity generation in Azerbaijan. 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]]
Shocking Connections: Unearthing the Electrifying Link Between Air Quality in Grand Forks, North Dakota and Electricity Generation in Azerbaijan

[[ABSTRACT]]
In this study, we set out to shed some light on the inconceivable connection between air quality in the small town of Grand Forks, North Dakota, and the electricity generation practices in the faraway land of Azerbaijan. Despite the geographical distance and apparent lack of common ground, our research has uncovered a remarkably significant relationship. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we have calculated a correlation coefficient of 0.8730857 and a p-value of less than 0.01 for the period spanning from 1992 to 2001. Our results not only provide astonishing evidence of the link between these seemingly disparate factors but also may potentially facilitate a spark of change in the international energy landscape. As we delve deeper into this electrifying correlation, it becomes clear that the currents of environmental impact transcend borders and continents, ultimately showing that there is truly no "air" distance when it comes to the interplay of air quality and electricity generation.

[[LITERATURE REVIEW]]
To embark on our quest for unraveling the electrifying connection between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan, we first delve into the existing literature surrounding these two seemingly unrelated components. In "Air Quality in Small Towns" by Smith, the authors find that the air quality in small towns has a significant impact on the health and well-being of the community, but the book fails to mention any far-reaching connections to distant lands with exotic names like Azerbaijan. Following that, in "The Shocking Reality of Electricity Generation" by Doe, interesting insights are provided into the various methods of electricity generation, but in a shocking twist, no mention of connections to air quality in obscure locations is made. In stark contrast, Jones in "The Ties That Bind: Exploring Unlikely Connections" discusses surprising correlations discovered in the world, but unfortunately, fails to recognize the captivating link between air quality in Grand Forks and electricity generation in Azerbaijan.
As we traverse beyond the realms of academia, delving into the non-fiction realm, we peruse "The Air We Breathe: A Study of Environmental Impact" and "Sparks of Change: A Global Perspective on Electricity Generation" for illumination. However, as we flip through the pages, we find that these books, while informative, remain shockingly silent on the matter at hand. It appears that our quest for insight has hit a minor snag - or perhaps an electric shock!
Amidst the fictional landscape, we stumble upon "Electric Currents of Fate" and "The Winds of Energy: A Tale of Air and Electricity" – titles that, at first glance, seem to hold the promise of shedding light on our electrifying correlation. Unfortunately, we find ourselves swept into a world of fiction, where the connection between air quality and electricity generation remains as elusive as a yeti in the Himalayas.
Drawing inspiration from cinematic adventures, we whimsically consider the whimsical journey of "The Electric Airbender" and the high-voltage drama of "Azerbaijan Nights: The Spark Awakens." Alas, we find ourselves wading through a sea of popcorn instead of enlightenment, for these movies, while engaging, offer nothing of substance to our intriguing investigation.
As we meander through the labyrinth of literature, our journey takes an unexpected turn. Stay tuned as we dare to unravel the electrifying link between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan, amidst the titillating twists and tantalizing turns that research can often surprise us with. We promise the sparks will fly!

[[RESULTS]]
The data analysis revealed a shockingly strong correlation between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan during the period from 1992 to 2001. The correlation coefficient of 0.8730857 left us feeling positively charged, and the r-squared value of 0.7622786 confirmed that there's certainly an electrifying link between these two seemingly unrelated variables. With a p-value of less than 0.01, we can confidently say that this connection is statistically significant, sparking our interest even further.
Our findings are visually showcased in Fig. 1, a scatterplot that illustrates the striking relationship between air quality and electricity generation. Think of it as a thrilling rollercoaster ride through the peaks and valleys of correlation, where the data points are like small, electrified particles dancing across the chart.
It's fascinating to consider the implications of these results. Who would have thought that a town known for its love of hockey and a country famous for its fire-blanket-wrestling would be linked in such a meaningful way? The currents of correlation truly flow in mysterious ways.
So, what does this all mean? Well, it seems that when it comes to the invisible threads that connect air quality and electricity generation, the world of science continues to astound us with its shocking revelations. Our discovery might just generate a powerful buzz in the fields of energy policy and environmental protection. After all, it's a stark reminder that the impact of our actions is not confined to one location or sector, and that the interconnected web of forces at play in our world is full of surprises.
In conclusion, our research has not only illuminated the surprisingly strong link between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan but also added a jolt of excitement to the study of environmental and energy dynamics. We hope that our findings will energize further exploration and foster a current of creativity in addressing these critical issues. Let's keep our eyes peeled and our minds open for more shockingly electrifying connections in the future!

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our results have left us positively electrified! The findings of our study not only confirm the existing literature, but they also add a spark of excitement to the somewhat dimly lit understanding of the relationship between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan. It's as if we've stumbled upon the Frankenstein's monster of correlations – unexpected, shocking, and possibly a little bit mad.

The strong correlation coefficient of 0.8730857 and the associated r-squared value of 0.7622786 confirm that there's more than just a passing current between these two seemingly unrelated variables. It's like the universe decided to play a game of "connect the dots," but instead of dots, it's air particles and electricity, and the lines drawn are positively electrifying.

Our study builds upon the existing literature, offering a bolt from the blue that ties in with the works of Smith, Doe, and Jones, albeit in a manner that is quite literally off the charts – or should we say, on the scatterplot. We've managed to harness the wild electricity of statistical analysis to illuminate a pathway between what were once thought to be insurmountable distances, proving that the impact of air quality and electricity generation transcends borders and continents, and possibly even dimensions.

But let's not forget the creative sparks that ignited this research in the first place. As we meandered through the labyrinth of literature, we encountered tales of airbenders and electric nights, reminding us that while the pursuit of knowledge is serious business, it's also a journey filled with unexpected twists and turns. Who would have thought that the sparks of a cinematic adventure would find their way into the heart of scientific inquiry? But as researchers, we must be willing to embrace a bit of cinematic drama in our quest for knowledge; after all, what's a good research project without a few electrifying plot twists?

As we move forward, we hope that our study ignites a fire in the realm of energy policy and environmental protection, infusing it with the incandescent glow of discovery. The interconnected web of forces at play in our world is full of surprises, and we should never be complacent in our assumptions. Our findings exemplify the fact that research can truly bridge the seemingly insurmountable gaps between different domains, electrifying our understanding and expanding the boundaries of what is possible.

In the words of Nikola Tesla, "Let the future tell the truth and evaluate each one according to his work and accomplishments. The present is theirs; the future, for which I have really worked, is mine." And with that, we await the future with open arms and a bit of anticipation – who knows what other shocking connections are waiting to be unveiled? Let's keep our gazes skyward and our feet grounded, ready to embrace the electrifying mysteries that lie ahead.


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Air quality in Grand Forks, North Dakota and Electricity generation in Azerbaijan. 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]]
Shocking Connections: Unearthing the Electrifying Link Between Air Quality in Grand Forks, North Dakota and Electricity Generation in Azerbaijan

[[ABSTRACT]]
In this study, we set out to shed some light on the inconceivable connection between air quality in the small town of Grand Forks, North Dakota, and the electricity generation practices in the faraway land of Azerbaijan. Despite the geographical distance and apparent lack of common ground, our research has uncovered a remarkably significant relationship. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we have calculated a correlation coefficient of 0.8730857 and a p-value of less than 0.01 for the period spanning from 1992 to 2001. Our results not only provide astonishing evidence of the link between these seemingly disparate factors but also may potentially facilitate a spark of change in the international energy landscape. As we delve deeper into this electrifying correlation, it becomes clear that the currents of environmental impact transcend borders and continents, ultimately showing that there is truly no "air" distance when it comes to the interplay of air quality and electricity generation.

[[INTRDUCTION]]
As scientists, we are always seeking to illuminate the hidden connections that permeate our world, but little did we expect to stumble upon a discovery of such shockingly electrifying proportions. The chance to delve into the relationship between the air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan was too tantalizing to resist. After all, it's not every day that one gets to investigate the currents of correlation that flow between such disparate variables.
The tale of how we came to unearth this convoluted link is a story as compelling as any epic quest. Armed with a healthy dose of curiosity and an arsenal of statistical tools, we bravely ventured into the realm of data, determined to shine a spotlight on the enigmatic ties between air quality and electricity generation. Little did we know that our journey would lead us to a correlation coefficient of 0.8730857, a p-value of less than 0.01, and an understanding that the fates of air quality and electricity generation are intimately intertwined.
Some may wonder if our findings are simply a result of statistical flukes or the product of too many late-night research sessions, but we assure you that our methods were as rigorous as a marathon runner's training regimen. From analyzing data from the Environmental Protection Agency to poring over information from the Energy Information Administration, we left no stone unturned in our quest for answers.
But why, you may ask, should anyone care about this peculiar correlation between a small town in North Dakota and a nation halfway across the globe? Well, the implications of our discovery stretch further than a good dad joke. By shedding light on the interconnectedness of seemingly unrelated elements, we not only challenge conventional wisdom but also pave the way for a potential evolution in global energy strategies. After all, when it comes to the ties that bind air quality and electricity generation, it seems that there truly is no air distance too great to overcome.
So, without further ado, let us embark on a journey through the currents of correlation as we explore the gripping tale of air quality, electricity generation, and the electrifying connection that binds them together. As we unravel the strands of this tangled web, let us not forget that the world of science is often as full of surprises and twists as a good mystery novel. And with that, dear readers, we invite you to join us on this electrifying adventure of discovery and revelation.

[[RESULTS]]
The data analysis revealed a shockingly strong correlation between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan during the period from 1992 to 2001. The correlation coefficient of 0.8730857 left us feeling positively charged, and the r-squared value of 0.7622786 confirmed that there's certainly an electrifying link between these two seemingly unrelated variables. With a p-value of less than 0.01, we can confidently say that this connection is statistically significant, sparking our interest even further.
Our findings are visually showcased in Fig. 1, a scatterplot that illustrates the striking relationship between air quality and electricity generation. Think of it as a thrilling rollercoaster ride through the peaks and valleys of correlation, where the data points are like small, electrified particles dancing across the chart.
It's fascinating to consider the implications of these results. Who would have thought that a town known for its love of hockey and a country famous for its fire-blanket-wrestling would be linked in such a meaningful way? The currents of correlation truly flow in mysterious ways.
So, what does this all mean? Well, it seems that when it comes to the invisible threads that connect air quality and electricity generation, the world of science continues to astound us with its shocking revelations. Our discovery might just generate a powerful buzz in the fields of energy policy and environmental protection. After all, it's a stark reminder that the impact of our actions is not confined to one location or sector, and that the interconnected web of forces at play in our world is full of surprises.
In conclusion, our research has not only illuminated the surprisingly strong link between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan but also added a jolt of excitement to the study of environmental and energy dynamics. We hope that our findings will energize further exploration and foster a current of creativity in addressing these critical issues. Let's keep our eyes peeled and our minds open for more shockingly electrifying connections in the future!

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]
Our findings have truly left us feeling positively charged, shedding light on the electrifying connection between air quality in Grand Forks, North Dakota, and electricity generation in Azerbaijan. It seems the world of science is full of such shockingly electrifying connections, just like those frizzy-haired mad scientists in the movies. It's as if the statistical analysis sent shockwaves through our research team, sparking an unprecedented level of excitement akin to discovering a lightning bolt in a bottle.

The correlation coefficient of 0.8730857 and the p-value of less than 0.01 have electrified our understanding of the interplay between these seemingly unrelated variables. Our results have sparked a surge of interest in the international energy landscape, proving that the currents of environmental impact transcend borders and continents, just like a bolt of lightning piercing through the dark sky.

As we bid adieu to this electrifying adventure of discovery and revelation, we can confidently say that no more research is needed in this area. After all, the mere thought of delving deeper into this electrifying connection might just make our hair stand on end!


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 Shocking Connections: Unearthing the Electrifying Link Between Air Quality in Grand Forks, North Dakota and Electricity Generation in Azerbaijan. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Transcontinental Environmental Dynamics


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 Shocking Connections: Unearthing the Electrifying Link Between Air Quality in Grand Forks, North Dakota and Electricity Generation in Azerbaijan. Respond only with the name of a fictional organization.

ChatGPT:

International Society for Atmospheric Electricity and Energy Connections


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 Shocking Connections: Unearthing the Electrifying Link Between Air Quality in Grand Forks, North Dakota and Electricity Generation in Azerbaijan with an abstract of In this study, we set out to shed some light on the inconceivable connection between air quality in the small town of Grand Forks, North Dakota, and the electricity generation practices in the faraway land of Azerbaijan. Despite the geographical distance and apparent lack of common ground, our research has uncovered a remarkably significant relationship. Through rigorous analysis of data from the Environmental Protection Agency and the Energy Information Administration, we have calculated a correlation coefficient of 0.8730857 and a p-value of less than 0.01 for the period spanning from 1992 to 2001. Our results not only provide astonishing evidence of the link between these seemingly disparate factors but also may potentially facilitate a spark of change in the international energy landscape. As we delve deeper into this electrifying correlation, it becomes clear that the currents of environmental impact transcend borders and continents, ultimately showing that there is truly no "air" distance when it comes to the interplay of air quality and electricity generation.

ChatGPT:

air quality, Grand Forks, North Dakota, electricity generation, Azerbaijan, environmental impact, correlation coefficient, p-value, international energy landscape, interplay of air quality and electricity generation

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



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Data details

Air quality in Grand Forks, North Dakota
Detailed data title: Percentage of days with good or moderate air quality in Grand Forks, ND-MN
Source: Environmental Protection Agency
See what else correlates with Air quality in Grand Forks, North Dakota

Electricity generation in Azerbaijan
Detailed data title: Total electricity generation in Azerbaijan in billion kWh
Source: Energy Information Administration
See what else correlates with Electricity generation in Azerbaijan

Correlation r = 0.8730857 (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 = 0.7622786 (Coefficient of determination)
This means 76.2% of the change in the one variable (i.e., Electricity generation in Azerbaijan) is predictable based on the change in the other (i.e., Air quality in Grand Forks, North Dakota) over the 10 years from 1992 through 2001.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00097. 0.0009711726638620049000000000
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 0.87 in 0.097% of random cases. Said differently, if you correlated 1,030 random variables Which I absolutely did.
with the same 9 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.54, 0.97 ] 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.
1992199319941995199619971998199920002001
Air quality in Grand Forks, North Dakota (Good air quality)0.994253100000011
Electricity generation in Azerbaijan (Billion kWh)18.5818.07416.60916.116.1415.91217.01517.16217.654117.8959




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
  4. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."


# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([0.994253,1,0,0,0,0,0,0,1,1,])
array_2 = np.array([18.58,18.074,16.609,16.1,16.14,15.912,17.015,17.162,17.6541,17.8959,])
array_1_name = "Air quality in Grand Forks, North Dakota"
array_2_name = "Electricity generation in Azerbaijan"

# 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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Correlation ID: 5012 · Black Variable ID: 21823 · Red Variable ID: 23482
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