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AI explanation
As the temperature rose in San Jose, it led to more frequent use of air conditioning. This, in turn, created a higher demand for electricity. To meet this increased demand, North Macedonia had to rely more heavily on petroleum-powered generators, thus leading to greater petroleum consumption. The sizzling heat in California's tech hub indirectly sparked a surge in the use of petroleum in a distant European country, demonstrating the shocking interconnectedness of global energy consumption. Remember, it's always sunny in the world of quirky correlational causation!
Model: dalle-3
Prompt: Generate a cute 2D animation depicting the contrast between the scorching heat in San Jose, California and the petroleum-powered generators in North Macedonia. Show a sunny day in San Jose with people fanning themselves and air conditioners blowing cool air. In contrast, showcase North Macedonia with cartoonish petroleum-powered generators chugging away. The animation should capture the unexpected link between the two events, emphasizing the impact of Californian heat on distant petroleum consumption. 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: Hot days in San Jose and Petroluem consumption in North Macedonia. 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: Cute 2D animation Voxel art Woodblock painting Cute 2D animation Cutsy graphics
ChatGPT: Cute 2D animation
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 Hot days in San Jose and Petroluem consumption in North Macedonia, in the following situation: As the temperature rose in San Jose, it led to more frequent use of air conditioning. This, in turn, created a higher demand for electricity. To meet this increased demand, North Macedonia had to rely more heavily on petroleum-powered generators, thus leading to greater petroleum consumption. The sizzling heat in California's tech hub indirectly sparked a surge in the use of petroleum in a distant European country, demonstrating the shocking interconnectedness of global energy consumption. Remember, it's always sunny in the world of quirky correlational causation!. Keep the description simple.
ChatGPT: In the scorching heat of San Jose, the air conditioners hummed on full blast as people sought relief from the hot days. Meanwhile, in North Macedonia, petroleum-powered generators sprang to life, working overtime to meet the increased demand for electricity. The connection between the two seemingly unrelated events was established, revealing the unexpected impact of hot days in California on petroleum consumption in distant North Macedonia.
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: [ Cute 2D animation ] and depicting this scene: In the scorching heat of San Jose, the air conditioners hummed on full blast as people sought relief from the hot days. Meanwhile, in North Macedonia, petroleum-powered generators sprang to life, working overtime to meet the increased demand for electricity. The connection between the two seemingly unrelated events was established, revealing the unexpected impact of hot days in California on petroleum consumption in distant North Macedonia. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate a cute 2D animation depicting the contrast between the scorching heat in San Jose, California and the petroleum-powered generators in North Macedonia. Show a sunny day in San Jose with people fanning themselves and air conditioners blowing cool air. In contrast, showcase North Macedonia with cartoonish petroleum-powered generators chugging away. The animation should capture the unexpected link between the two events, emphasizing the impact of Californian heat on distant petroleum consumption.
*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.
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 Hot days in San Jose positively influenced Petroluem consumption in North Macedonia.\Make it sound serious until the end.
AI academic paper
 |
Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption The Journal of Eclectic Energy Studies Jan 2024 Reminder: This paper is AI-generated. Not real! |
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 Hot days in San Jose and Petroluem consumption in North Macedonia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Make the title punny if you can come up with clever pun. If not, make it sound serious.
Your research team used data from NOAA National Climate Data Center and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.4013488 and p < 0.05 for 1992 to 2021.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
"Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption"
[[ABSTRACT]]
In this study, we investigate the connection between hot summer days in San Jose and petroleum consumption in North Macedonia, shedding light on a previously overlooked relationship. Leveraging data from the NOAA National Climate Data Center and the Energy Information Administration, we assessed the correlation between these seemingly disparate factors. Our findings reveal a statistically significant correlation coefficient of 0.4013488 and a p-value of less than 0.05, spanning the years 1992 to 2021. It seems that when the temperature rises in San Jose, so does the demand for petroleum in North Macedonia, creating a hot and fuelin' connection that cannot be ignored.
As the old saying goes, "When it's hot in San Jose, North Macedonia's petroleum usage will rise and shine like the sun!" Our research not only provides valuable insights for energy economists and climate analysts but also highlights the interconnectedness of global factors, proving that even the most unexpected pairings can fuel intriguing avenues of inquiry. So, let's keep our cool and dive into this sizzling relationship between weather patterns and energy consumption, because sometimes research really does make us all hot under the collar – or is it under the fuel cap?
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 Hot days in San Jose and Petroluem consumption in North Macedonia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Here is the title and abstract of the paper:
[[TITLE]]
"Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption"
[[ABSTRACT]]
In this study, we investigate the connection between hot summer days in San Jose and petroleum consumption in North Macedonia, shedding light on a previously overlooked relationship. Leveraging data from the NOAA National Climate Data Center and the Energy Information Administration, we assessed the correlation between these seemingly disparate factors. Our findings reveal a statistically significant correlation coefficient of 0.4013488 and a p-value of less than 0.05, spanning the years 1992 to 2021. It seems that when the temperature rises in San Jose, so does the demand for petroleum in North Macedonia, creating a hot and fuelin' connection that cannot be ignored.
As the old saying goes, "When it's hot in San Jose, North Macedonia's petroleum usage will rise and shine like the sun!" Our research not only provides valuable insights for energy economists and climate analysts but also highlights the interconnectedness of global factors, proving that even the most unexpected pairings can fuel intriguing avenues of inquiry. So, let's keep our cool and dive into this sizzling relationship between weather patterns and energy consumption, because sometimes research really does make us all hot under the collar – or is it under the fuel cap?
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
As the world grapples with the impacts of climate change and seeks to untangle the complex web of factors influencing energy consumption, it becomes increasingly clear that even the most unexpected connections can hold significant implications. In the realm of energy economics, one might think of hot days in San Jose and petroleum consumption in North Macedonia as distant cousins, rarely giving them a second thought. However, as we delve into the data, it becomes evident that these seemingly disparate elements may be more closely intertwined than previously assumed.
In the world of academic research, things can sometimes get a little heated – especially when trying to decipher the mysteries of economic relationships. And what better way to address a hot topic than by examining the influence of literal heat on energy consumption? It's like trying to find the missing pieces of a puzzle and realizing they were right under your nose the whole time – just like that elusive sock that always seems to disappear in the laundry. But fear not, dear reader, for we are here to shine a light on this unexpected phenomenon.
Our investigation takes us on a journey where San Jose's scorching summer days and North Macedonia's petroleum consumption intersect, creating a conundrum that's as puzzling as trying to find a parking spot in a crowded city – it seems impossible until you stumble upon an unexpected opening. Through comprehensive data analysis and rigorous statistical scrutiny, our study endeavors to unlock the secrets behind this curious connection, peeling back the layers of complexity like unwrapping a particularly perplexing riddle.
As we embark on this exploration, let's keep in mind the wise words of ancient philosophers: "When the heat's on in one place, it's sure to spark something in another." The interconnectedness of global phenomena often elicits surprise, akin to finding out that your quirky neighbor is actually a retired astronaut. Who would have thought that the weather in one city could have an impact on petroleum consumption thousands of miles away? But in the realm of energy economics, it seems that even the most unexpected pairings can fuel thought-provoking lines of inquiry – much like finding out that a hot dog is actually a sandwich.
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 Hot days in San Jose and Petroluem consumption in North Macedonia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some movies that you watched that are tangentially related to the topic.
Here is the title and abstract of the paper:
[[TITLE]]
"Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption"
[[ABSTRACT]]
In this study, we investigate the connection between hot summer days in San Jose and petroleum consumption in North Macedonia, shedding light on a previously overlooked relationship. Leveraging data from the NOAA National Climate Data Center and the Energy Information Administration, we assessed the correlation between these seemingly disparate factors. Our findings reveal a statistically significant correlation coefficient of 0.4013488 and a p-value of less than 0.05, spanning the years 1992 to 2021. It seems that when the temperature rises in San Jose, so does the demand for petroleum in North Macedonia, creating a hot and fuelin' connection that cannot be ignored.
As the old saying goes, "When it's hot in San Jose, North Macedonia's petroleum usage will rise and shine like the sun!" Our research not only provides valuable insights for energy economists and climate analysts but also highlights the interconnectedness of global factors, proving that even the most unexpected pairings can fuel intriguing avenues of inquiry. So, let's keep our cool and dive into this sizzling relationship between weather patterns and energy consumption, because sometimes research really does make us all hot under the collar – or is it under the fuel cap?
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As the world grapples with the impacts of climate change and seeks to untangle the complex web of factors influencing energy consumption, it becomes increasingly clear that even the most unexpected connections can hold significant implications. In the realm of energy economics, one might think of hot days in San Jose and petroleum consumption in North Macedonia as distant cousins, rarely giving them a second thought. However, as we delve into the data, it becomes evident that these seemingly disparate elements may be more closely intertwined than previously assumed.
In the world of academic research, things can sometimes get a little heated – especially when trying to decipher the mysteries of economic relationships. And what better way to address a hot topic than by examining the influence of literal heat on energy consumption? It's like trying to find the missing pieces of a puzzle and realizing they were right under your nose the whole time – just like that elusive sock that always seems to disappear in the laundry. But fear not, dear reader, for we are here to shine a light on this unexpected phenomenon.
Our investigation takes us on a journey where San Jose's scorching summer days and North Macedonia's petroleum consumption intersect, creating a conundrum that's as puzzling as trying to find a parking spot in a crowded city – it seems impossible until you stumble upon an unexpected opening. Through comprehensive data analysis and rigorous statistical scrutiny, our study endeavors to unlock the secrets behind this curious connection, peeling back the layers of complexity like unwrapping a particularly perplexing riddle.
As we embark on this exploration, let's keep in mind the wise words of ancient philosophers: "When the heat's on in one place, it's sure to spark something in another." The interconnectedness of global phenomena often elicits surprise, akin to finding out that your quirky neighbor is actually a retired astronaut. Who would have thought that the weather in one city could have an impact on petroleum consumption thousands of miles away? But in the realm of energy economics, it seems that even the most unexpected pairings can fuel thought-provoking lines of inquiry – much like finding out that a hot dog is actually a sandwich.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The relationship between weather patterns and energy consumption has been a subject of interest for researchers across various disciplines. Smith et al. (2015) have conducted a comprehensive analysis of the impact of temperature on energy demand, highlighting the nuanced interplay between meteorological conditions and fuel consumption. Similarly, Doe and Jones (2018) have delved into the complexities of global energy dynamics, emphasizing the need to consider both direct and indirect influences on petroleum usage. These studies lay the groundwork for our exploration of the intriguing connection between hot days in San Jose and petroleum consumption in North Macedonia.
It's no surprise that when the mercury rises, so does the demand for energy. As the saying goes, "It's so hot, I'm sweating more than a laptop in a sauna!" It seems that this heat-induced phenomenon extends beyond mere comfort levels to impact the very fuel that drives economies – talk about a hot topic in more ways than one!
Beyond the realm of academic research, several non-fiction works provide valuable insights into energy consumption patterns and climate influences. In "The Big Heatwave: How Weather Shapes Our World" by Weatherly (2019), the author explores the far-reaching implications of temperature fluctuations, shedding light on the surprising ways in which weather can sway energy usage. Moreover, "Fuel or Fizzle: The Global Quest for Energy" by Powerhouse (2017) offers a comprehensive overview of the factors driving petroleum consumption, revealing the intricate dance between environmental conditions and fuel demand.
It's clear that the heat is on in our exploration of this captivating connection, much like a summer blockbuster that leaves audiences on the edge of their seats – or in this case, the edge of their air-conditioned rooms!
Turning to fictional literature, "The Scorching Secret" by Blaze (2020) presents a thrilling tale of intrigue and suspense centered around a mysterious link between weather anomalies and energy crises. While purely a work of fiction, the novel draws attention to the enigmatic nature of interconnected global phenomena, leaving readers pondering the potential real-world implications of such enthralling narratives.
And who can forget the cult classic film "Heat"? While not directly related to climate and energy, this cinematic masterpiece starring Al Pacino and Robert De Niro reminds us that the heat is often an integral component of intense and unexpected connections. As we unravel the intriguing relationship between hot days in San Jose and petroleum consumption in North Macedonia, it's as if we're piecing together clues in a riveting whodunit – only this time, the mystery revolves around the sizzle and pop of energy dynamics!
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 Hot days in San Jose and Petroluem consumption in North Macedonia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Your research team collected data from all across the internet, but mostly just used information from NOAA National Climate Data Center and Energy Information Administration . You used data from 1992 to 2021
Make up the research methods you don't know. Make them a bit goofy and convoluted.
Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption"
[[ABSTRACT]]
In this study, we investigate the connection between hot summer days in San Jose and petroleum consumption in North Macedonia, shedding light on a previously overlooked relationship. Leveraging data from the NOAA National Climate Data Center and the Energy Information Administration, we assessed the correlation between these seemingly disparate factors. Our findings reveal a statistically significant correlation coefficient of 0.4013488 and a p-value of less than 0.05, spanning the years 1992 to 2021. It seems that when the temperature rises in San Jose, so does the demand for petroleum in North Macedonia, creating a hot and fuelin' connection that cannot be ignored.
As the old saying goes, "When it's hot in San Jose, North Macedonia's petroleum usage will rise and shine like the sun!" Our research not only provides valuable insights for energy economists and climate analysts but also highlights the interconnectedness of global factors, proving that even the most unexpected pairings can fuel intriguing avenues of inquiry. So, let's keep our cool and dive into this sizzling relationship between weather patterns and energy consumption, because sometimes research really does make us all hot under the collar – or is it under the fuel cap?
[[INTRODUCTION]]
As the world grapples with the impacts of climate change and seeks to untangle the complex web of factors influencing energy consumption, it becomes increasingly clear that even the most unexpected connections can hold significant implications. In the realm of energy economics, one might think of hot days in San Jose and petroleum consumption in North Macedonia as distant cousins, rarely giving them a second thought. However, as we delve into the data, it becomes evident that these seemingly disparate elements may be more closely intertwined than previously assumed.
In the world of academic research, things can sometimes get a little heated – especially when trying to decipher the mysteries of economic relationships. And what better way to address a hot topic than by examining the influence of literal heat on energy consumption? It's like trying to find the missing pieces of a puzzle and realizing they were right under your nose the whole time – just like that elusive sock that always seems to disappear in the laundry. But fear not, dear reader, for we are here to shine a light on this unexpected phenomenon.
Our investigation takes us on a journey where San Jose's scorching summer days and North Macedonia's petroleum consumption intersect, creating a conundrum that's as puzzling as trying to find a parking spot in a crowded city – it seems impossible until you stumble upon an unexpected opening. Through comprehensive data analysis and rigorous statistical scrutiny, our study endeavors to unlock the secrets behind this curious connection, peeling back the layers of complexity like unwrapping a particularly perplexing riddle.
As we embark on this exploration, let's keep in mind the wise words of ancient philosophers: "When the heat's on in one place, it's sure to spark something in another." The interconnectedness of global phenomena often elicits surprise, akin to finding out that your quirky neighbor is actually a retired astronaut. Who would have thought that the weather in one city could have an impact on petroleum consumption thousands of miles away? But in the realm of energy economics, it seems that even the most unexpected pairings can fuel thought-provoking lines of inquiry – much like finding out that a hot dog is actually a sandwich.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To unravel the heat-fueled connection between San Jose's scorching summer days and North Macedonia's petroleum consumption, our research team embarked on a data-driven odyssey, navigating through vast reservoirs of information akin to prospectors panning for statistical gold. Our primary sources of data were derived from the NOAA National Climate Data Center and the Energy Information Administration, as we sought to capture the temperature fluctuations in San Jose and the corresponding petroleum consumption trends in North Macedonia from 1992 to 2021.
In the spirit of thorough investigation, our methodology involved a blend of quantitative analysis and time-series modeling, akin to unraveling the intricate dance of synchronized swimming – except our "swimmers" were temperature data points and petroleum consumption figures. First, we meticulously collected and cleansed the data, sifting through it with an eagle eye for any anomalies or outliers, much like searching for a needle in a haystack, only to find it stuck to a magnet.
Considering the dynamic nature of climate and energy consumption patterns, we adopted a robust statistical approach, resembling the intricacies of a Rubik's Cube algorithm. Implementing correlation and regression analyses, we sought to unearth the nuances of the relationship between temperature and petroleum consumption, peeling back the layers of complexity like unwrapping a particularly perplexing riddle. With each twist and turn of the statistical process, we aimed to shed light on the quantitative underpinnings of this unexpected association, much like a detective unraveling the threads of a cryptic case.
Once our statistical toolkit had been thoroughly employed, we scrutinized the findings with a discerning eye, comparing our results to established theoretical frameworks and prior empirical research. This analytical rigor was akin to the meticulous art of sculpting, as we chiseled away at the data to reveal the underlying patterns, much like Michelangelo coaxing the figures from blocks of marble – though in our case, our material was more numerical than marble.
As we delved deeper into our analysis, we couldn't help but be reminded of a classic dad joke: "Why did the petroleum consumption cross the road? To get to the heat on the other side!" The humor in such a jest lies in its simplicity, but our research journey was anything but simple, filled with the twists and turns of uncovering the unexpected relationship between temperature and energy consumption. Yet, through our methodological labyrinth, we emerged with insights that could spark further inquiry into the interconnected dynamics of climate and energy economics, proving that sometimes, the most unassuming pairings can ignite captivating avenues of research.
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 Hot days in San Jose and Petroluem consumption in North Macedonia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Your research team collected data from all across the internet, but mostly just used information from NOAA National Climate Data Center and Energy Information Administration .
For the time period 1992 to 2021, you found a correlation 0.4013488, r-squared of 0.1610808, and p < 0.05.
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]]
"Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption"
[[ABSTRACT]]
In this study, we investigate the connection between hot summer days in San Jose and petroleum consumption in North Macedonia, shedding light on a previously overlooked relationship. Leveraging data from the NOAA National Climate Data Center and the Energy Information Administration, we assessed the correlation between these seemingly disparate factors. Our findings reveal a statistically significant correlation coefficient of 0.4013488 and a p-value of less than 0.05, spanning the years 1992 to 2021. It seems that when the temperature rises in San Jose, so does the demand for petroleum in North Macedonia, creating a hot and fuelin' connection that cannot be ignored.
As the old saying goes, "When it's hot in San Jose, North Macedonia's petroleum usage will rise and shine like the sun!" Our research not only provides valuable insights for energy economists and climate analysts but also highlights the interconnectedness of global factors, proving that even the most unexpected pairings can fuel intriguing avenues of inquiry. So, let's keep our cool and dive into this sizzling relationship between weather patterns and energy consumption, because sometimes research really does make us all hot under the collar – or is it under the fuel cap?
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
As the world grapples with the impacts of climate change and seeks to untangle the complex web of factors influencing energy consumption, it becomes increasingly clear that even the most unexpected connections can hold significant implications. In the realm of energy economics, one might think of hot days in San Jose and petroleum consumption in North Macedonia as distant cousins, rarely giving them a second thought. However, as we delve into the data, it becomes evident that these seemingly disparate elements may be more closely intertwined than previously assumed.
In the world of academic research, things can sometimes get a little heated – especially when trying to decipher the mysteries of economic relationships. And what better way to address a hot topic than by examining the influence of literal heat on energy consumption? It's like trying to find the missing pieces of a puzzle and realizing they were right under your nose the whole time – just like that elusive sock that always seems to disappear in the laundry. But fear not, dear reader, for we are here to shine a light on this unexpected phenomenon.
Our investigation takes us on a journey where San Jose's scorching summer days and North Macedonia's petroleum consumption intersect, creating a conundrum that's as puzzling as trying to find a parking spot in a crowded city – it seems impossible until you stumble upon an unexpected opening. Through comprehensive data analysis and rigorous statistical scrutiny, our study endeavors to unlock the secrets behind this curious connection, peeling back the layers of complexity like unwrapping a particularly perplexing riddle.
As we embark on this exploration, let's keep in mind the wise words of ancient philosophers: "When the heat's on in one place, it's sure to spark something in another." The interconnectedness of global phenomena often elicits surprise, akin to finding out that your quirky neighbor is actually a retired astronaut. Who would have thought that the weather in one city could have an impact on petroleum consumption thousands of miles away? But in the realm of energy economics, it seems that even the most unexpected pairings can fuel thought-provoking lines of inquiry – much like finding out that a hot dog is actually a sandwich.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The analysis of the data revealed a positive correlation between hot summer days in San Jose and petroleum consumption in North Macedonia. The correlation coefficient was found to be 0.4013488, indicating a moderate positive relationship between the two variables. This suggests that as the temperature rises in San Jose, there tends to be a corresponding increase in petroleum consumption in North Macedonia. It's almost as if the rising mercury in San Jose sends a signal across the globe, urging an uptick in fuel usage in North Macedonia.
The r-squared value of 0.1610808 suggests that approximately 16.1% of the variability in petroleum consumption in North Macedonia can be explained by the variations in temperature in San Jose. While the relationship is not deterministic, it certainly raises eyebrows and prompts further investigation into the underlying mechanisms driving this intriguing connection. It's like trying to solve a puzzle where the pieces keep shifting, making it a real hot topic in the world of energy analysis.
Furthermore, the p-value of less than 0.05 indicates that the correlation is statistically significant, bolstering the evidence for the interplay between these seemingly unrelated factors. It's like finding out that your favorite sweater actually matches perfectly with your most eccentric pair of socks – a surprising discovery that defies initial expectations.
Our findings are visually represented in Figure 1, which illustrates the strong positive correlation between hot summer days in San Jose and petroleum consumption in North Macedonia. The scatterplot unmistakably demonstrates the uptick in petroleum consumption as the temperature in San Jose rises, providing a compelling visual depiction of this unexpected relationship. It's as clear as day that when it's hot in San Jose, North Macedonia's petroleum usage heats up in sync, creating a connection that cannot be easily dismissed. It's like finding out that your car's fuel gauge always seems to mirror the thermometer – a true indicator of the hot relationship between weather and energy consumption.
These results not only shed light on the complex interplay between climate patterns and energy usage but also underscore the need for further exploration of seemingly unrelated variables in the realm of energy economics. As we unravel the mysteries of these interconnected factors, we are reminded that in the world of research, even the most unexpected connections can fuel valuable avenues of inquiry. It's like stumbling upon a hidden treasure in the attic – you never know what unexpected gems of insight might be waiting to be unearthed.
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 Hot days in San Jose and Petroluem consumption in North Macedonia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Limit your response to 500 tokens.
Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.
Do not write a conclusion. I will add a conclusion after this.
[[TITLE]]
"Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption"
[[ABSTRACT]]
In this study, we investigate the connection between hot summer days in San Jose and petroleum consumption in North Macedonia, shedding light on a previously overlooked relationship. Leveraging data from the NOAA National Climate Data Center and the Energy Information Administration, we assessed the correlation between these seemingly disparate factors. Our findings reveal a statistically significant correlation coefficient of 0.4013488 and a p-value of less than 0.05, spanning the years 1992 to 2021. It seems that when the temperature rises in San Jose, so does the demand for petroleum in North Macedonia, creating a hot and fuelin' connection that cannot be ignored.
As the old saying goes, "When it's hot in San Jose, North Macedonia's petroleum usage will rise and shine like the sun!" Our research not only provides valuable insights for energy economists and climate analysts but also highlights the interconnectedness of global factors, proving that even the most unexpected pairings can fuel intriguing avenues of inquiry. So, let's keep our cool and dive into this sizzling relationship between weather patterns and energy consumption, because sometimes research really does make us all hot under the collar – or is it under the fuel cap?
[[LITERATURE REVIEW]]
The relationship between weather patterns and energy consumption has been a subject of interest for researchers across various disciplines. Smith et al. (2015) have conducted a comprehensive analysis of the impact of temperature on energy demand, highlighting the nuanced interplay between meteorological conditions and fuel consumption. Similarly, Doe and Jones (2018) have delved into the complexities of global energy dynamics, emphasizing the need to consider both direct and indirect influences on petroleum usage. These studies lay the groundwork for our exploration of the intriguing connection between hot days in San Jose and petroleum consumption in North Macedonia.
It's no surprise that when the mercury rises, so does the demand for energy. As the saying goes, "It's so hot, I'm sweating more than a laptop in a sauna!" It seems that this heat-induced phenomenon extends beyond mere comfort levels to impact the very fuel that drives economies – talk about a hot topic in more ways than one!
Beyond the realm of academic research, several non-fiction works provide valuable insights into energy consumption patterns and climate influences. In "The Big Heatwave: How Weather Shapes Our World" by Weatherly (2019), the author explores the far-reaching implications of temperature fluctuations, shedding light on the surprising ways in which weather can sway energy usage. Moreover, "Fuel or Fizzle: The Global Quest for Energy" by Powerhouse (2017) offers a comprehensive overview of the factors driving petroleum consumption, revealing the intricate dance between environmental conditions and fuel demand.
It's clear that the heat is on in our exploration of this captivating connection, much like a summer blockbuster that leaves audiences on the edge of their seats – or in this case, the edge of their air-conditioned rooms!
Turning to fictional literature, "The Scorching Secret" by Blaze (2020) presents a thrilling tale of intrigue and suspense centered around a mysterious link between weather anomalies and energy crises. While purely a work of fiction, the novel draws attention to the enigmatic nature of interconnected global phenomena, leaving readers pondering the potential real-world implications of such enthralling narratives.
And who can forget the cult classic film "Heat"? While not directly related to climate and energy, this cinematic masterpiece starring Al Pacino and Robert De Niro reminds us that the heat is often an integral component of intense and unexpected connections. As we unravel the intriguing relationship between hot days in San Jose and petroleum consumption in North Macedonia, it's as if we're piecing together clues in a riveting whodunit – only this time, the mystery revolves around the sizzle and pop of energy dynamics!
[[RESULTS]]
The analysis of the data revealed a positive correlation between hot summer days in San Jose and petroleum consumption in North Macedonia. The correlation coefficient was found to be 0.4013488, indicating a moderate positive relationship between the two variables. This suggests that as the temperature rises in San Jose, there tends to be a corresponding increase in petroleum consumption in North Macedonia. It's almost as if the rising mercury in San Jose sends a signal across the globe, urging an uptick in fuel usage in North Macedonia.
The r-squared value of 0.1610808 suggests that approximately 16.1% of the variability in petroleum consumption in North Macedonia can be explained by the variations in temperature in San Jose. While the relationship is not deterministic, it certainly raises eyebrows and prompts further investigation into the underlying mechanisms driving this intriguing connection. It's like trying to solve a puzzle where the pieces keep shifting, making it a real hot topic in the world of energy analysis.
Furthermore, the p-value of less than 0.05 indicates that the correlation is statistically significant, bolstering the evidence for the interplay between these seemingly unrelated factors. It's like finding out that your favorite sweater actually matches perfectly with your most eccentric pair of socks – a surprising discovery that defies initial expectations.
Our findings are visually represented in Figure 1, which illustrates the strong positive correlation between hot summer days in San Jose and petroleum consumption in North Macedonia. The scatterplot unmistakably demonstrates the uptick in petroleum consumption as the temperature in San Jose rises, providing a compelling visual depiction of this unexpected relationship. It's as clear as day that when it's hot in San Jose, North Macedonia's petroleum usage heats up in sync, creating a connection that cannot be easily dismissed. It's like finding out that your car's fuel gauge always seems to mirror the thermometer – a true indicator of the hot relationship between weather and energy consumption.
These results not only shed light on the complex interplay between climate patterns and energy usage but also underscore the need for further exploration of seemingly unrelated variables in the realm of energy economics. As we unravel the mysteries of these interconnected factors, we are reminded that in the world of research, even the most unexpected connections can fuel valuable avenues of inquiry. It's like stumbling upon a hidden treasure in the attic – you never know what unexpected gems of insight might be waiting to be unearthed.
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Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our results provide empirical support for the oft-quoted adage, "As San Jose sizzles, Macedonia's engines rev." The statistically significant positive correlation between hot summer days in San Jose and petroleum consumption in North Macedonia corroborates the previous research indicating the influence of weather patterns on energy demand. Our findings align with the studies by Smith et al. (2015) and Doe and Jones (2018), emphasizing the interconnectedness of meteorological conditions and fuel usage. The moderate positive correlation coefficient suggests that approximately 16.1% of the variability in petroleum consumption in North Macedonia can be attributed to the fluctuations in temperature in San Jose. This result underscores the influential role of hot weather in driving petroleum consumption, a finding that is as illuminating as a beacon in a heatwave.
Our analysis not only confirms the established relationship between weather patterns and energy dynamics but also underscores the importance of considering these intricate connections in energy policy and planning. It's like realizing that a well-fitting glove is just as essential as the right pair of shoes – sometimes, unexpected connections can make all the difference. The visual representation of our findings in Figure 1 echoes the robustness of this relationship, akin to a striking masterpiece that captures the essence of this sizzling connection between weather and energy consumption.
Our study contributes to the growing body of literature that explores the pervasive influence of climate on energy usage, adding a unique twist with its investigation of the transcontinental impact of hot summer days in San Jose on petroleum consumption in North Macedonia. It's like uncovering the punchline to a long-standing joke – the unexpected revelation adds a touch of humor to the narrative of research inquiry. As we move forward, it is vital to delve deeper into the underlying mechanisms driving this correlation, as well as to consider the broader implications for global energy dynamics. After all, understanding the interplay of seemingly unrelated variables can unveil unexpected insights, much like stumbling upon a hidden treasure in the attic – the thrill of discovery never ceases to spark curiosity.
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 Hot days in San Jose and Petroluem consumption in North Macedonia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.
Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption"
[[ABSTRACT]]
In this study, we investigate the connection between hot summer days in San Jose and petroleum consumption in North Macedonia, shedding light on a previously overlooked relationship. Leveraging data from the NOAA National Climate Data Center and the Energy Information Administration, we assessed the correlation between these seemingly disparate factors. Our findings reveal a statistically significant correlation coefficient of 0.4013488 and a p-value of less than 0.05, spanning the years 1992 to 2021. It seems that when the temperature rises in San Jose, so does the demand for petroleum in North Macedonia, creating a hot and fuelin' connection that cannot be ignored.
As the old saying goes, "When it's hot in San Jose, North Macedonia's petroleum usage will rise and shine like the sun!" Our research not only provides valuable insights for energy economists and climate analysts but also highlights the interconnectedness of global factors, proving that even the most unexpected pairings can fuel intriguing avenues of inquiry. So, let's keep our cool and dive into this sizzling relationship between weather patterns and energy consumption, because sometimes research really does make us all hot under the collar – or is it under the fuel cap?
[[INTRDUCTION]]
As the world grapples with the impacts of climate change and seeks to untangle the complex web of factors influencing energy consumption, it becomes increasingly clear that even the most unexpected connections can hold significant implications. In the realm of energy economics, one might think of hot days in San Jose and petroleum consumption in North Macedonia as distant cousins, rarely giving them a second thought. However, as we delve into the data, it becomes evident that these seemingly disparate elements may be more closely intertwined than previously assumed.
In the world of academic research, things can sometimes get a little heated – especially when trying to decipher the mysteries of economic relationships. And what better way to address a hot topic than by examining the influence of literal heat on energy consumption? It's like trying to find the missing pieces of a puzzle and realizing they were right under your nose the whole time – just like that elusive sock that always seems to disappear in the laundry. But fear not, dear reader, for we are here to shine a light on this unexpected phenomenon.
Our investigation takes us on a journey where San Jose's scorching summer days and North Macedonia's petroleum consumption intersect, creating a conundrum that's as puzzling as trying to find a parking spot in a crowded city – it seems impossible until you stumble upon an unexpected opening. Through comprehensive data analysis and rigorous statistical scrutiny, our study endeavors to unlock the secrets behind this curious connection, peeling back the layers of complexity like unwrapping a particularly perplexing riddle.
As we embark on this exploration, let's keep in mind the wise words of ancient philosophers: "When the heat's on in one place, it's sure to spark something in another." The interconnectedness of global phenomena often elicits surprise, akin to finding out that your quirky neighbor is actually a retired astronaut. Who would have thought that the weather in one city could have an impact on petroleum consumption thousands of miles away? But in the realm of energy economics, it seems that even the most unexpected pairings can fuel thought-provoking lines of inquiry – much like finding out that a hot dog is actually a sandwich.
[[RESULTS]]
The analysis of the data revealed a positive correlation between hot summer days in San Jose and petroleum consumption in North Macedonia. The correlation coefficient was found to be 0.4013488, indicating a moderate positive relationship between the two variables. This suggests that as the temperature rises in San Jose, there tends to be a corresponding increase in petroleum consumption in North Macedonia. It's almost as if the rising mercury in San Jose sends a signal across the globe, urging an uptick in fuel usage in North Macedonia.
The r-squared value of 0.1610808 suggests that approximately 16.1% of the variability in petroleum consumption in North Macedonia can be explained by the variations in temperature in San Jose. While the relationship is not deterministic, it certainly raises eyebrows and prompts further investigation into the underlying mechanisms driving this intriguing connection. It's like trying to solve a puzzle where the pieces keep shifting, making it a real hot topic in the world of energy analysis.
Furthermore, the p-value of less than 0.05 indicates that the correlation is statistically significant, bolstering the evidence for the interplay between these seemingly unrelated factors. It's like finding out that your favorite sweater actually matches perfectly with your most eccentric pair of socks – a surprising discovery that defies initial expectations.
Our findings are visually represented in Figure 1, which illustrates the strong positive correlation between hot summer days in San Jose and petroleum consumption in North Macedonia. The scatterplot unmistakably demonstrates the uptick in petroleum consumption as the temperature in San Jose rises, providing a compelling visual depiction of this unexpected relationship. It's as clear as day that when it's hot in San Jose, North Macedonia's petroleum usage heats up in sync, creating a connection that cannot be easily dismissed. It's like finding out that your car's fuel gauge always seems to mirror the thermometer – a true indicator of the hot relationship between weather and energy consumption.
These results not only shed light on the complex interplay between climate patterns and energy usage but also underscore the need for further exploration of seemingly unrelated variables in the realm of energy economics. As we unravel the mysteries of these interconnected factors, we are reminded that in the world of research, even the most unexpected connections can fuel valuable avenues of inquiry. It's like stumbling upon a hidden treasure in the attic – you never know what unexpected gems of insight might be waiting to be unearthed.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our research has unveiled an intriguing connection between hot summer days in San Jose and petroleum consumption in North Macedonia. The statistically significant correlation coefficient of 0.4013488 and the p-value of less than 0.05 demonstrate a compelling relationship that cannot be ignored. It seems that when the heat is on in San Jose, North Macedonia's demand for petroleum also rises, creating a hot and fuelin' dynamic that defies conventional expectations.
This unexpected association between seemingly disparate elements emphasizes the interconnectedness of global phenomena, reminding us that even the most unlikely pairings can fuel compelling areas of inquiry. It's like the unexpected friendship between a cat and a dog – you never know what surprising connections may emerge when we delve into the complex web of influences shaping our world.
Our findings provide valuable insights for energy economists and climate analysts, inviting further investigation into the mechanisms driving this sizzling relationship. As we navigate the intricacies of climate patterns and energy usage, it's important to keep our cool and pursue research that uncovers the unexpected – much like stumbling upon a hidden treasure map in the attic.
Given the compelling nature of our results, it's clear that no more research is needed in this area. It's time to extinguish the flames of inquiry and shift our focus to the next hot topic in the realm of energy economics. After all, when it comes to deciphering the mysteries of global interconnectedness, we've already struck oil in this captivating journey.
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 Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption. 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 Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption. Respond only with the name of a fictional organization.
ChatGPT:
The Institute for Transcontinental Energy Studies
Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption with an abstract of In this study, we investigate the connection between hot summer days in San Jose and petroleum consumption in North Macedonia, shedding light on a previously overlooked relationship. Leveraging data from the NOAA National Climate Data Center and the Energy Information Administration, we assessed the correlation between these seemingly disparate factors. Our findings reveal a statistically significant correlation coefficient of 0.4013488 and a p-value of less than 0.05, spanning the years 1992 to 2021. It seems that when the temperature rises in San Jose, so does the demand for petroleum in North Macedonia, creating a hot and fuelin' connection that cannot be ignored.
As the old saying goes, "When it's hot in San Jose, North Macedonia's petroleum usage will rise and shine like the sun!" Our research not only provides valuable insights for energy economists and climate analysts but also highlights the interconnectedness of global factors, proving that even the most unexpected pairings can fuel intriguing avenues of inquiry. So, let's keep our cool and dive into this sizzling relationship between weather patterns and energy consumption, because sometimes research really does make us all hot under the collar – or is it under the fuel cap?
ChatGPT:
San Jose, summer days, petroleum consumption, North Macedonia, correlation, temperature, energy consumption, weather patterns, climate data, Energy Information Administration, global factors, interconnectedness, energy economists, climate analysts, research, sizzling relationship, fuel consumption.
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
Discover a new correlation
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Data details
Hot days in San JoseDetailed data title: Number of days with maximum temperature >= 90 degrees Fahrenheit/32.2 degrees Celsius at SAN JOSE, CA US
Source: NOAA National Climate Data Center
See what else correlates with Hot days in San Jose
Petroluem consumption in North Macedonia
Detailed data title: Volume of petroluem consumption consumed in North Macedonia in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Petroluem consumption in North Macedonia
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 = 0.1610808 (Coefficient of determination)
This means 16.1% of the change in the one variable (i.e., Petroluem consumption in North Macedonia) is predictable based on the change in the other (i.e., Hot days in San Jose) over the 30 years from 1992 through 2021.
p < 0.05, which statistically significant(Null hypothesis significance test)
The p-value is 0.028. 0.0279328459365643830000000000
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 0.4 in 2.8% of random cases. Said differently, if you correlated 36 random variables Which I absolutely did.
with the same 29 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 29 because we have two variables measured over a period of 30 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.
[ 0.05, 0.67 ] 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.
| 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | |
| Hot days in San Jose (Hot days) | 0 | 24 | 0 | 0 | 43 | 21 | 30 | 0 | 0 | 0 | 0 | 20 | 0 | 5 | 17 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Petroluem consumption in North Macedonia (Million Barrels/Day) | 19.4 | 21.3 | 18 | 18.5 | 23.4 | 21 | 22.3 | 20 | 18.6492 | 15.4245 | 17.6106 | 16.8699 | 17.2013 | 17.6503 | 18.2756 | 20.1487 | 17.9017 | 18.7995 | 18.4027 | 18.9967 | 18.7283 | 18.7596 | 18.7026 | 20.4957 | 21 | 21.9307 | 20.9428 | 22.6796 | 19.5398 | 21.9012 |
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
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
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.
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([0,24,0,0,43,21,30,0,0,0,0,20,0,5,17,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,])
array_2 = np.array([19.4,21.3,18,18.5,23.4,21,22.3,20,18.6492,15.4245,17.6106,16.8699,17.2013,17.6503,18.2756,20.1487,17.9017,18.7995,18.4027,18.9967,18.7283,18.7596,18.7026,20.4957,21,21.9307,20.9428,22.6796,19.5398,21.9012,])
array_1_name = "Hot days in San Jose"
array_2_name = "Petroluem consumption in North Macedonia"
# 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. 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.
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Download images for these variables:
- High resolution line chart
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 Hot days in San Jose
- Line chart for only Petroluem consumption in North Macedonia
- AI-generated correlation image
- The spurious research paper: Fuelin' the Fire: The Hot Connection Between San Jose Summer Days and North Macedonian Petroleum Consumption
I'm grateful for your review!
Correlation ID: 4402 · Black Variable ID: 25417 · Red Variable ID: 24774
