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AI explanation
As the kerosene usage in Djibouti rises, so does the illumination for crafting genius titles. This could be because the fumes are sparking extra creativity, or perhaps the content creators are just feeling a little more lit. Either way, it's clear that when it comes to insightful video titles, the connection is not dim.
Model: dalle-3
Prompt: Prompt: Generate an image in the style of a meme that shows a group of content creators in Djibouti sitting outside at dusk, collaborating on their next project under the warm glow of kerosene lamps. Capture the flickering light illuminating their faces as they brainstorm and inspire each other for their next YouTube video. 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: How insightful Casually Explained YouTube video titles are and Kerosene used in Djibouti. 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: a meme Minimalism Macabre Oragami Cyberpunk
ChatGPT: a meme
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 How insightful Casually Explained YouTube video titles are and Kerosene used in Djibouti, in the following situation: As the kerosene usage in Djibouti rises, so does the illumination for crafting genius titles. This could be because the fumes are sparking extra creativity, or perhaps the content creators are just feeling a little more lit. Either way, it's clear that when it comes to insightful video titles, the connection is not dim.. Keep the description simple.
ChatGPT: A group of content creators in Djibouti sit outside as the sun sets, using kerosene lamps to light their workspace. As the kerosene usage increases, their faces illuminate with inspiration, and one of them excitedly types, "How to Fail Like a Pro: A Casual Guide" for their next YouTube video title. The warm glow of the lamps highlights their insightful expressions as they brainstorm, the flickering light infusing their creativity with a warm and inviting glow.
Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ a meme ] and depicting this scene: A group of content creators in Djibouti sit outside as the sun sets, using kerosene lamps to light their workspace. As the kerosene usage increases, their faces illuminate with inspiration, and one of them excitedly types, "How to Fail Like a Pro: A Casual Guide" for their next YouTube video title. The warm glow of the lamps highlights their insightful expressions as they brainstorm, the flickering light infusing their creativity with a warm and inviting glow. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image in the style of a meme that shows a group of content creators in Djibouti sitting outside at dusk, collaborating on their next project under the warm glow of kerosene lamps. Capture the flickering light illuminating their faces as they brainstorm and inspire each other for their next YouTube video.
*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 an increase in How insightful Casually Explained YouTube video titles are caused Kerosene used in Djibouti to increase. Include one good pun.
AI academic paper
 |
Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti The International Journal of Digital Ethnography and Sustainable Development Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between How insightful Casually Explained YouTube video titles are and Kerosene used in Djibouti. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Rhyme words in the title.
Your research team used data from AI analysis of YouTube video titles and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.9839291 and p < 0.01 for 2015 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]]
Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti
[[ABSTRACT]]
This study seeks to shed light on the intriguing connection between seemingly unrelated phenomena: the insightful YouTube video titles of Casually Explained and the consumption of kerosene in Djibouti. By utilizing advanced AI analysis of YouTube video titles and accessing data from the Energy Information Administration, our research team has uncovered a surprising correlation, much like how a candlemaker prefers to work late, they've always got a burning desire to finish their work. With a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, we have a statistical basis for the intriguing relationship between the entertainingly informative content of Casually Explained videos and the consumption of kerosene in Djibouti. It's almost as if these seemingly unrelated subjects are... illuminating each other. We aim to spark further investigation into this unexpected correlation and encourage scholars to keep their research interests burning bright.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between How insightful Casually Explained YouTube video titles are and Kerosene used in Djibouti. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Here is the title and abstract of the paper:
[[TITLE]]
Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti
[[ABSTRACT]]
This study seeks to shed light on the intriguing connection between seemingly unrelated phenomena: the insightful YouTube video titles of Casually Explained and the consumption of kerosene in Djibouti. By utilizing advanced AI analysis of YouTube video titles and accessing data from the Energy Information Administration, our research team has uncovered a surprising correlation, much like how a candlemaker prefers to work late, they've always got a burning desire to finish their work. With a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, we have a statistical basis for the intriguing relationship between the entertainingly informative content of Casually Explained videos and the consumption of kerosene in Djibouti. It's almost as if these seemingly unrelated subjects are... illuminating each other. We aim to spark further investigation into this unexpected correlation and encourage scholars to keep their research interests burning bright.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
INTRODUCTION
The pursuit of knowledge often leads researchers down unexpected paths, much like a lost botanist ends up taking root in a new field. In the case of our research, we delved into the world of YouTube video titles and energy usage trends, aiming to shed light on the mysterious connection between casual explanations and kerosene consumption in Djibouti. It's almost as if we stumbled upon a statistical treasure map, leading us to a surprising correlation that's as bright as a well-lit laboratory.
As researchers, we are often encouraged to think outside the box, and in this instance, we found ourselves pondering the correlation between the engagingly witty video titles of Casually Explained and the consumption of kerosene in Djibouti. This unexpected pairing led us to consider the ways in which seemingly disparate variables can interact, much like an electron seeking its perfect match in a covalent bond. With a flicker of curiosity, we embarked on this statistical journey, excited to uncover what lies beneath the surface of these seemingly unrelated subjects, just like a cryptic YouTube title leaves viewers yearning for clarity.
Research often takes unexpected turns, much like a lab mouse navigating a maze, and our findings proved to be no exception. Through rigorous analysis utilizing advanced AI algorithms, we uncovered a remarkable correlation with a coefficient that shines as brightly as a well-polished beaker. It's quite a gas when statistical analysis leads to illuminating insights, isn't it? Our preliminary findings revealed a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, demonstrating the strength of the connection between Casually Explained video titles and kerosene usage in Djibouti.
In the world of academia, unexpected correlations often spark intrigue and inspire further investigation, much like a titration reaction that sets off a chain of scientific inquiry. We hope to ignite curiosity and encourage fellow researchers to delve into this fascinating relationship, much like a Bunsen burner ignites a flame. By shedding light on this peculiar connection, we aim to illuminate the unconventional intersections of seemingly unrelated topics and spark further exploration into the possibilities of unexpected correlations in research. Just like a good dad joke, our findings may be unexpected, but they certainly leave an impression that lingers.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between How insightful Casually Explained YouTube video titles are and Kerosene used in Djibouti. 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]]
Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti
[[ABSTRACT]]
This study seeks to shed light on the intriguing connection between seemingly unrelated phenomena: the insightful YouTube video titles of Casually Explained and the consumption of kerosene in Djibouti. By utilizing advanced AI analysis of YouTube video titles and accessing data from the Energy Information Administration, our research team has uncovered a surprising correlation, much like how a candlemaker prefers to work late, they've always got a burning desire to finish their work. With a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, we have a statistical basis for the intriguing relationship between the entertainingly informative content of Casually Explained videos and the consumption of kerosene in Djibouti. It's almost as if these seemingly unrelated subjects are... illuminating each other. We aim to spark further investigation into this unexpected correlation and encourage scholars to keep their research interests burning bright.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The pursuit of knowledge often leads researchers down unexpected paths, much like a lost botanist ends up taking root in a new field. In the case of our research, we delved into the world of YouTube video titles and energy usage trends, aiming to shed light on the mysterious connection between casual explanations and kerosene consumption in Djibouti. It's almost as if we stumbled upon a statistical treasure map, leading us to a surprising correlation that's as bright as a well-lit laboratory.
As researchers, we are often encouraged to think outside the box, and in this instance, we found ourselves pondering the correlation between the engagingly witty video titles of Casually Explained and the consumption of kerosene in Djibouti. This unexpected pairing led us to consider the ways in which seemingly disparate variables can interact, much like an electron seeking its perfect match in a covalent bond. With a flicker of curiosity, we embarked on this statistical journey, excited to uncover what lies beneath the surface of these seemingly unrelated subjects, just like a cryptic YouTube title leaves viewers yearning for clarity.
Research often takes unexpected turns, much like a lab mouse navigating a maze, and our findings proved to be no exception. Through rigorous analysis utilizing advanced AI algorithms, we uncovered a remarkable correlation with a coefficient that shines as brightly as a well-polished beaker. It's quite a gas when statistical analysis leads to illuminating insights, isn't it? Our preliminary findings revealed a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, demonstrating the strength of the connection between Casually Explained video titles and kerosene usage in Djibouti.
In the world of academia, unexpected correlations often spark intrigue and inspire further investigation, much like a titration reaction that sets off a chain of scientific inquiry. We hope to ignite curiosity and encourage fellow researchers to delve into this fascinating relationship, much like a Bunsen burner ignites a flame. By shedding light on this peculiar connection, we aim to illuminate the unconventional intersections of seemingly unrelated topics and spark further exploration into the possibilities of unexpected correlations in research. Just like a good dad joke, our findings may be unexpected, but they certainly leave an impression that lingers.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
In their seminal work, Smith and Doe (2017) delved into the complex world of YouTube video titles, exploring the linguistic nuances and strategic wordplay employed by content creators to attract viewers. Similarly, Jones (2019) conducted a comprehensive analysis of energy consumption patterns in Djibouti, uncovering the various factors influencing the usage of kerosene in the region. These scholarly endeavors laid the groundwork for our research, much like a solid foundation supports a towering research edifice.
It's time for a dad joke to lighten the mood: Why don't scientists trust atoms? Because they make up everything!
While the connection between YouTube video titles and kerosene consumption may initially seem as unlikely as a polar bear in the desert, our investigation revealed an unexpected intersection. Our study draws inspiration from real-world sources such as "Energy Economics and Policy" by Thompson and "The Power of Words: Unraveling the Semantics of Social Media" by Garcia, showcasing how seemingly disparate subjects can synergize in illuminating ways.
Speaking of synergy, have you heard about the two antennas that got married? The ceremony wasn't much, but the reception was excellent!
As we delve further into the literature, it's crucial to recognize the fiction works that could shed light on the underlying connections between storytelling and energy consumption. Fictional narratives such as "The Illumination Theory" by Luminous Overture and "Kerosene Chronicles" by Flame Peterson offer intriguing parallels to our research theme, emphasizing the power of narrative elements in elucidating complex phenomena. Whether it's illuminating fictional worlds or shedding light on statistical truths, the interplay of words and energy remains a captivating subject of exploration.
Let's spice things up with a chemistry joke: Are you made of copper and tellurium? Because you're Cu-Te!
Beyond written literature, cinematic productions have also delved into themes relevant to our research. Films such as "The Lightbulb Effect" and "Bright Sparks: A Tale of Illumination" offer narrative perspectives on the symbiotic relationship between enlightenment and energy, providing creative insights that resonate with the connectivity we aim to uncover. Much like a well-crafted movie plot, our research seeks to captivate the audience and illuminate the unexpected twists and turns inherent in interdisciplinary inquiry.
In the pursuit of knowledge, embracing unexpected connections is akin to allowing a spark to ignite a flame, illuminating new pathways of thought and inquiry. As we navigate through the scholarly landscape, the fusion of insight and humor serves as a beacon, guiding us towards a deeper understanding of the interconnectedness between seemingly disparate domains. Just like a good pun, our research aims to elicit amusement while unveiling the unanticipated ties between Casually Explained YouTube titles and kerosene usage in Djibouti.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between How insightful Casually Explained YouTube video titles are and Kerosene used in Djibouti. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 AI analysis of YouTube video titles and Energy Information Administration . You used data from 2015 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]]
Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti
[[ABSTRACT]]
This study seeks to shed light on the intriguing connection between seemingly unrelated phenomena: the insightful YouTube video titles of Casually Explained and the consumption of kerosene in Djibouti. By utilizing advanced AI analysis of YouTube video titles and accessing data from the Energy Information Administration, our research team has uncovered a surprising correlation, much like how a candlemaker prefers to work late, they've always got a burning desire to finish their work. With a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, we have a statistical basis for the intriguing relationship between the entertainingly informative content of Casually Explained videos and the consumption of kerosene in Djibouti. It's almost as if these seemingly unrelated subjects are... illuminating each other. We aim to spark further investigation into this unexpected correlation and encourage scholars to keep their research interests burning bright.
[[INTRODUCTION]]
INTRODUCTION
The pursuit of knowledge often leads researchers down unexpected paths, much like a lost botanist ends up taking root in a new field. In the case of our research, we delved into the world of YouTube video titles and energy usage trends, aiming to shed light on the mysterious connection between casual explanations and kerosene consumption in Djibouti. It's almost as if we stumbled upon a statistical treasure map, leading us to a surprising correlation that's as bright as a well-lit laboratory.
As researchers, we are often encouraged to think outside the box, and in this instance, we found ourselves pondering the correlation between the engagingly witty video titles of Casually Explained and the consumption of kerosene in Djibouti. This unexpected pairing led us to consider the ways in which seemingly disparate variables can interact, much like an electron seeking its perfect match in a covalent bond. With a flicker of curiosity, we embarked on this statistical journey, excited to uncover what lies beneath the surface of these seemingly unrelated subjects, just like a cryptic YouTube title leaves viewers yearning for clarity.
Research often takes unexpected turns, much like a lab mouse navigating a maze, and our findings proved to be no exception. Through rigorous analysis utilizing advanced AI algorithms, we uncovered a remarkable correlation with a coefficient that shines as brightly as a well-polished beaker. It's quite a gas when statistical analysis leads to illuminating insights, isn't it? Our preliminary findings revealed a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, demonstrating the strength of the connection between Casually Explained video titles and kerosene usage in Djibouti.
In the world of academia, unexpected correlations often spark intrigue and inspire further investigation, much like a titration reaction that sets off a chain of scientific inquiry. We hope to ignite curiosity and encourage fellow researchers to delve into this fascinating relationship, much like a Bunsen burner ignites a flame. By shedding light on this peculiar connection, we aim to illuminate the unconventional intersections of seemingly unrelated topics and spark further exploration into the possibilities of unexpected correlations in research. Just like a good dad joke, our findings may be unexpected, but they certainly leave an impression that lingers.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
Sampling Procedure:
To investigate the surprising relationship between Casually Explained YouTube video titles and kerosene usage in Djibouti, we employed a non-probability sampling method, much like a whimsical game of musical chairs. We extracted data from all Casually Explained video titles posted on YouTube from 2015 to 2021, encompassing subjects ranging from "The CIA's Romanticized Retellings of Its Greatest Failures" to "The Economic Decline of Kentucky in the 17th Century". These thought-provoking titles were analyzed using advanced AI algorithms to discern the depth of insight they provide. It's almost like mining for comedic gold in a sea of data; a true digital treasure hunt!
Data Collection:
Additionally, we amassed data on kerosene consumption in Djibouti from the Energy Information Administration, sifting through years of statistical records with the determination of an archeologist unearthing ancient artifacts. We sought to unveil any patterns or trends that might shed light on the relationship between the entertainingly illuminating YouTube content and the energy usage habits of the people of Djibouti. It's as if we were piecing together a puzzle, with kerosene consumption data as one piece and Casually Explained video titles as another, trying to reveal the bigger picture hidden within the statistical mosaic.
Statistical Analysis:
Following the collection of data, we subjected it to rigorous statistical analysis, akin to putting the data under a microscope and examining it with a fine-tooth comb. Through a series of correlation analyses and regression models, we aimed to elucidate the connection between the witty, insightful video titles and the consumption of kerosene in Djibouti. It's almost as if we were conducting a scientific experiment, carefully measuring each variable to see if they interacted melodically like a finely tuned orchestra. Our statistical methods were as precise as a chemist measuring and pouring liquids into a beaker, aiming to distill the essence of the relationship between these seemingly incongruous subjects.
Ethical Considerations:
As responsible researchers, we ensured ethical guidelines were strictly followed throughout the data collection and analysis process, treating the information with the utmost respect, just like a well-mannered laboratory assistant handling delicate glassware. We upheld the principles of academic integrity and data privacy, ensuring that our research adhered to ethical standards and policies, even if our dad jokes sometimes blurred the line between science and comedy.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between How insightful Casually Explained YouTube video titles are and Kerosene used in Djibouti. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 AI analysis of YouTube video titles and Energy Information Administration .
For the time period 2015 to 2021, you found a correlation 0.9839291, r-squared of 0.9681165, 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]]
Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti
[[ABSTRACT]]
This study seeks to shed light on the intriguing connection between seemingly unrelated phenomena: the insightful YouTube video titles of Casually Explained and the consumption of kerosene in Djibouti. By utilizing advanced AI analysis of YouTube video titles and accessing data from the Energy Information Administration, our research team has uncovered a surprising correlation, much like how a candlemaker prefers to work late, they've always got a burning desire to finish their work. With a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, we have a statistical basis for the intriguing relationship between the entertainingly informative content of Casually Explained videos and the consumption of kerosene in Djibouti. It's almost as if these seemingly unrelated subjects are... illuminating each other. We aim to spark further investigation into this unexpected correlation and encourage scholars to keep their research interests burning bright.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
The pursuit of knowledge often leads researchers down unexpected paths, much like a lost botanist ends up taking root in a new field. In the case of our research, we delved into the world of YouTube video titles and energy usage trends, aiming to shed light on the mysterious connection between casual explanations and kerosene consumption in Djibouti. It's almost as if we stumbled upon a statistical treasure map, leading us to a surprising correlation that's as bright as a well-lit laboratory.
As researchers, we are often encouraged to think outside the box, and in this instance, we found ourselves pondering the correlation between the engagingly witty video titles of Casually Explained and the consumption of kerosene in Djibouti. This unexpected pairing led us to consider the ways in which seemingly disparate variables can interact, much like an electron seeking its perfect match in a covalent bond. With a flicker of curiosity, we embarked on this statistical journey, excited to uncover what lies beneath the surface of these seemingly unrelated subjects, just like a cryptic YouTube title leaves viewers yearning for clarity.
Research often takes unexpected turns, much like a lab mouse navigating a maze, and our findings proved to be no exception. Through rigorous analysis utilizing advanced AI algorithms, we uncovered a remarkable correlation with a coefficient that shines as brightly as a well-polished beaker. It's quite a gas when statistical analysis leads to illuminating insights, isn't it? Our preliminary findings revealed a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, demonstrating the strength of the connection between Casually Explained video titles and kerosene usage in Djibouti.
In the world of academia, unexpected correlations often spark intrigue and inspire further investigation, much like a titration reaction that sets off a chain of scientific inquiry. We hope to ignite curiosity and encourage fellow researchers to delve into this fascinating relationship, much like a Bunsen burner ignites a flame. By shedding light on this peculiar connection, we aim to illuminate the unconventional intersections of seemingly unrelated topics and spark further exploration into the possibilities of unexpected correlations in research. Just like a good dad joke, our findings may be unexpected, but they certainly leave an impression that lingers.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
Our analysis revealed a strong correlation between the insightful YouTube video titles of Casually Explained and the consumption of kerosene in Djibouti. The correlation coefficient of 0.9839291 suggests a relationship as clear as day, much like how a conductor leads a symphony. Furthermore, with an r-squared of 0.9681165 and statistical significance at p < 0.01, we can confidently say that this unexpected association is not just a flash in the pan but a crucial spark of understanding in the realm of energy consumption and digital content creation.
The surprising nature of this correlation might lead one to think it's as odd as finding a polar bear in a desert, but the data paints a different picture. The scatterplot in Fig. 1 depicts a strong linear relationship between the insightful YouTube video titles and kerosene usage in Djibouti, just as how the moon influences the tides – a force that shouldn't be underestimated.
Every data point seems to illuminate this unusual relationship, much like a candle in the dark. This statistical discovery is a shining example of how seemingly unrelated variables can shed light on each other. It's as if these numbers are winking at us, revealing a hidden connection that's as unexpected as an unplanned experiment. This correlation is truly a shining beacon in the sea of unpredictable research findings.
Our findings raise more questions than a curious kitten, and we cannot help but encourage further investigation into this intriguing correlation. Like a light bulb moment in the midst of scientific inquiry, this discovery serves as a reminder that innovative research often leads to unexpected connections, much like how a good dad joke never fails to brighten the day – pun intended!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between How insightful Casually Explained YouTube video titles are and Kerosene used in Djibouti. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti
[[ABSTRACT]]
This study seeks to shed light on the intriguing connection between seemingly unrelated phenomena: the insightful YouTube video titles of Casually Explained and the consumption of kerosene in Djibouti. By utilizing advanced AI analysis of YouTube video titles and accessing data from the Energy Information Administration, our research team has uncovered a surprising correlation, much like how a candlemaker prefers to work late, they've always got a burning desire to finish their work. With a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, we have a statistical basis for the intriguing relationship between the entertainingly informative content of Casually Explained videos and the consumption of kerosene in Djibouti. It's almost as if these seemingly unrelated subjects are... illuminating each other. We aim to spark further investigation into this unexpected correlation and encourage scholars to keep their research interests burning bright.
[[LITERATURE REVIEW]]
In their seminal work, Smith and Doe (2017) delved into the complex world of YouTube video titles, exploring the linguistic nuances and strategic wordplay employed by content creators to attract viewers. Similarly, Jones (2019) conducted a comprehensive analysis of energy consumption patterns in Djibouti, uncovering the various factors influencing the usage of kerosene in the region. These scholarly endeavors laid the groundwork for our research, much like a solid foundation supports a towering research edifice.
It's time for a dad joke to lighten the mood: Why don't scientists trust atoms? Because they make up everything!
While the connection between YouTube video titles and kerosene consumption may initially seem as unlikely as a polar bear in the desert, our investigation revealed an unexpected intersection. Our study draws inspiration from real-world sources such as "Energy Economics and Policy" by Thompson and "The Power of Words: Unraveling the Semantics of Social Media" by Garcia, showcasing how seemingly disparate subjects can synergize in illuminating ways.
Speaking of synergy, have you heard about the two antennas that got married? The ceremony wasn't much, but the reception was excellent!
As we delve further into the literature, it's crucial to recognize the fiction works that could shed light on the underlying connections between storytelling and energy consumption. Fictional narratives such as "The Illumination Theory" by Luminous Overture and "Kerosene Chronicles" by Flame Peterson offer intriguing parallels to our research theme, emphasizing the power of narrative elements in elucidating complex phenomena. Whether it's illuminating fictional worlds or shedding light on statistical truths, the interplay of words and energy remains a captivating subject of exploration.
Let's spice things up with a chemistry joke: Are you made of copper and tellurium? Because you're Cu-Te!
Beyond written literature, cinematic productions have also delved into themes relevant to our research. Films such as "The Lightbulb Effect" and "Bright Sparks: A Tale of Illumination" offer narrative perspectives on the symbiotic relationship between enlightenment and energy, providing creative insights that resonate with the connectivity we aim to uncover. Much like a well-crafted movie plot, our research seeks to captivate the audience and illuminate the unexpected twists and turns inherent in interdisciplinary inquiry.
In the pursuit of knowledge, embracing unexpected connections is akin to allowing a spark to ignite a flame, illuminating new pathways of thought and inquiry. As we navigate through the scholarly landscape, the fusion of insight and humor serves as a beacon, guiding us towards a deeper understanding of the interconnectedness between seemingly disparate domains. Just like a good pun, our research aims to elicit amusement while unveiling the unanticipated ties between Casually Explained YouTube titles and kerosene usage in Djibouti.
[[RESULTS]]
Our analysis revealed a strong correlation between the insightful YouTube video titles of Casually Explained and the consumption of kerosene in Djibouti. The correlation coefficient of 0.9839291 suggests a relationship as clear as day, much like how a conductor leads a symphony. Furthermore, with an r-squared of 0.9681165 and statistical significance at p < 0.01, we can confidently say that this unexpected association is not just a flash in the pan but a crucial spark of understanding in the realm of energy consumption and digital content creation.
The surprising nature of this correlation might lead one to think it's as odd as finding a polar bear in a desert, but the data paints a different picture. The scatterplot in Fig. 1 depicts a strong linear relationship between the insightful YouTube video titles and kerosene usage in Djibouti, just as how the moon influences the tides – a force that shouldn't be underestimated.
Every data point seems to illuminate this unusual relationship, much like a candle in the dark. This statistical discovery is a shining example of how seemingly unrelated variables can shed light on each other. It's as if these numbers are winking at us, revealing a hidden connection that's as unexpected as an unplanned experiment. This correlation is truly a shining beacon in the sea of unpredictable research findings.
Our findings raise more questions than a curious kitten, and we cannot help but encourage further investigation into this intriguing correlation. Like a light bulb moment in the midst of scientific inquiry, this discovery serves as a reminder that innovative research often leads to unexpected connections, much like how a good dad joke never fails to brighten the day – pun intended!
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The results of our research have illuminated a surprising nexus between the engagingly informative content of Casually Explained YouTube video titles and the consumption of kerosene in Djibouti. Similar to how a good punchline can light up a room, this unexpected relationship between digital content and energy usage has sparked considerable interest in the scientific community. Our findings not only support previous studies on the linguistic nuances of YouTube video titles but also align with research into the complex factors influencing energy consumption in regional contexts, much like how a well-told dad joke brings joy to any situation.
The statistical significance and robust correlation coefficient observed in our study underscore the meaningful connection between these seemingly unrelated variables, much like how a positively charged ion attracts its negative counterpart. The strength of this association is as evident as a bright neon sign, highlighting the inherent synergy between the captivating narratives presented in YouTube video titles and the practical energy needs of communities in Djibouti. It's almost as if our findings are spelling out a punchline – the unexpected hook of the narrative leading to an illuminating conclusion.
Our results lend credence to the notion that even in the realm of scholarly inquiry, the seemingly disparate can converge in unexpectedly enlightening ways. The strong correlation between Casually Explained YouTube video titles and kerosene consumption in Djibouti is as coherent as a well-crafted pun, presenting a convergence of themes that may initially have seemed as unrelated as a politician's promise. This discovery serves as a reminder that entertaining content and practical energy usage are not as distinct as one might assume, much like how a cleverly worded dad joke can bridge the gap between science and laughter.
As we delve further into the implications of this intriguing correlation, we are reminded of the parallel paradoxes and unexpected relationships that often characterize the scientific endeavor. Our research underscores the virtue of embracing unanticipated connections, much like how a good joke can illuminate an otherwise serious discussion. This unexpected juxtaposition of digital content and energy consumption represents the delightful surprises that emerge when rigorous analysis meets the uncharted territories of interdisciplinary inquiry.
In conclusion, the remarkable correlation we have unearthed in this study reflects the interconnectedness and serendipitous discoveries that infuse scientific inquiry with both intrigue and a touch of levity. It reminds us that in the pursuit of knowledge, unexpected connections can lead to insights as bright as a well-timed dad joke – illuminating, captivating, and undeniably brilliant.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between How insightful Casually Explained YouTube video titles are and Kerosene used in Djibouti. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti
[[ABSTRACT]]
This study seeks to shed light on the intriguing connection between seemingly unrelated phenomena: the insightful YouTube video titles of Casually Explained and the consumption of kerosene in Djibouti. By utilizing advanced AI analysis of YouTube video titles and accessing data from the Energy Information Administration, our research team has uncovered a surprising correlation, much like how a candlemaker prefers to work late, they've always got a burning desire to finish their work. With a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, we have a statistical basis for the intriguing relationship between the entertainingly informative content of Casually Explained videos and the consumption of kerosene in Djibouti. It's almost as if these seemingly unrelated subjects are... illuminating each other. We aim to spark further investigation into this unexpected correlation and encourage scholars to keep their research interests burning bright.
[[INTRDUCTION]]
INTRODUCTION
The pursuit of knowledge often leads researchers down unexpected paths, much like a lost botanist ends up taking root in a new field. In the case of our research, we delved into the world of YouTube video titles and energy usage trends, aiming to shed light on the mysterious connection between casual explanations and kerosene consumption in Djibouti. It's almost as if we stumbled upon a statistical treasure map, leading us to a surprising correlation that's as bright as a well-lit laboratory.
As researchers, we are often encouraged to think outside the box, and in this instance, we found ourselves pondering the correlation between the engagingly witty video titles of Casually Explained and the consumption of kerosene in Djibouti. This unexpected pairing led us to consider the ways in which seemingly disparate variables can interact, much like an electron seeking its perfect match in a covalent bond. With a flicker of curiosity, we embarked on this statistical journey, excited to uncover what lies beneath the surface of these seemingly unrelated subjects, just like a cryptic YouTube title leaves viewers yearning for clarity.
Research often takes unexpected turns, much like a lab mouse navigating a maze, and our findings proved to be no exception. Through rigorous analysis utilizing advanced AI algorithms, we uncovered a remarkable correlation with a coefficient that shines as brightly as a well-polished beaker. It's quite a gas when statistical analysis leads to illuminating insights, isn't it? Our preliminary findings revealed a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, demonstrating the strength of the connection between Casually Explained video titles and kerosene usage in Djibouti.
In the world of academia, unexpected correlations often spark intrigue and inspire further investigation, much like a titration reaction that sets off a chain of scientific inquiry. We hope to ignite curiosity and encourage fellow researchers to delve into this fascinating relationship, much like a Bunsen burner ignites a flame. By shedding light on this peculiar connection, we aim to illuminate the unconventional intersections of seemingly unrelated topics and spark further exploration into the possibilities of unexpected correlations in research. Just like a good dad joke, our findings may be unexpected, but they certainly leave an impression that lingers.
[[RESULTS]]
Our analysis revealed a strong correlation between the insightful YouTube video titles of Casually Explained and the consumption of kerosene in Djibouti. The correlation coefficient of 0.9839291 suggests a relationship as clear as day, much like how a conductor leads a symphony. Furthermore, with an r-squared of 0.9681165 and statistical significance at p < 0.01, we can confidently say that this unexpected association is not just a flash in the pan but a crucial spark of understanding in the realm of energy consumption and digital content creation.
The surprising nature of this correlation might lead one to think it's as odd as finding a polar bear in a desert, but the data paints a different picture. The scatterplot in Fig. 1 depicts a strong linear relationship between the insightful YouTube video titles and kerosene usage in Djibouti, just as how the moon influences the tides – a force that shouldn't be underestimated.
Every data point seems to illuminate this unusual relationship, much like a candle in the dark. This statistical discovery is a shining example of how seemingly unrelated variables can shed light on each other. It's as if these numbers are winking at us, revealing a hidden connection that's as unexpected as an unplanned experiment. This correlation is truly a shining beacon in the sea of unpredictable research findings.
Our findings raise more questions than a curious kitten, and we cannot help but encourage further investigation into this intriguing correlation. Like a light bulb moment in the midst of scientific inquiry, this discovery serves as a reminder that innovative research often leads to unexpected connections, much like how a good dad joke never fails to brighten the day – pun intended!
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our research has highlighted the captivating correlation between the engagingly informative video titles of Casually Explained and the consumption of kerosene in Djibouti. The statistical significance of our findings is as clear as day, much like when water gets angry, it turns into steam – it simply can't keep its cool. With a correlation coefficient of 0.9839291 and an r-squared value that shines like a supernova at 0.9681165, the relationship between these seemingly unrelated variables is as undeniable as a bad science pun - it's simply elemental!
This unexpected association has illuminated the unexplored intersections of digital content creation and energy usage, much like a high-powered torch in a dark cave. Our findings beamed a spotlight on the fact that research can yield surprising discoveries, akin to finding an algebraic equation in a sea of calculus. It's like discovering a hidden gem in the field of statistics – a rare find that brings a twinkle to researchers' eyes.
As we wrap up this study, it's worth noting that sometimes, research can lead us down unanticipated paths, much like a circuit with multiple resistors in parallel. Just as a good dad joke ties together a family dinner conversation, our findings have tied together these unexpected elements in a way that's as pleasing as a perfectly conducted experiment. Therefore, we assert with the confidence of a physicist in their lab coat that no more research is needed in this area. As they say, sometimes you have to call it quits—just like scientists do with bad experiments—because there's no point in dragging on a bright idea.
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 Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti. Respond only with the name of a fictional academic journal.
ChatGPT:
The International Journal of Digital Ethnography and Sustainable Development
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 Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti. Respond only with the name of a fictional organization.
ChatGPT:
The Global Energy Efficiency Consortium
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 Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti with an abstract of This study seeks to shed light on the intriguing connection between seemingly unrelated phenomena: the insightful YouTube video titles of Casually Explained and the consumption of kerosene in Djibouti. By utilizing advanced AI analysis of YouTube video titles and accessing data from the Energy Information Administration, our research team has uncovered a surprising correlation, much like how a candlemaker prefers to work late, they've always got a burning desire to finish their work. With a correlation coefficient of 0.9839291 and statistical significance at p < 0.01 for the period of 2015 to 2021, we have a statistical basis for the intriguing relationship between the entertainingly informative content of Casually Explained videos and the consumption of kerosene in Djibouti. It's almost as if these seemingly unrelated subjects are... illuminating each other. We aim to spark further investigation into this unexpected correlation and encourage scholars to keep their research interests burning bright.
ChatGPT:
YouTube video titles, Casually Explained, energy consumption, kerosene usage, Djibouti, correlation analysis, AI analysis, statistical significance, Energy Information Administration, data analysis
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
How insightful Casually Explained YouTube video titles areDetailed data title: How insightful Casually Explained YouTube video titles are, as rated by an AI.
Source: AI analysis of YouTube video titles
Additional Info: I asked a large language model, 'On a scale of 1-10, how _______ do you think this YouTube video title is?' for every video.
See what else correlates with How insightful Casually Explained YouTube video titles are
Kerosene used in Djibouti
Detailed data title: Volume of kerosene used consumed in Djibouti in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Kerosene used in Djibouti
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 = 0.9681165 (Coefficient of determination)
This means 96.8% of the change in the one variable (i.e., Kerosene used in Djibouti) is predictable based on the change in the other (i.e., How insightful Casually Explained YouTube video titles are) over the 7 years from 2015 through 2021.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.2E-5. 0.0000623455066034787000000000
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 0.98 in 0.0062% of random cases. Said differently, if you correlated 16,040 random variables Which I absolutely did.
with the same 6 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 6 because we have two variables measured over a period of 7 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.
[ 0.89, 1 ] 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.
| 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | |
| How insightful Casually Explained YouTube video titles are (Insightful score (out of 10)) | 5.6667 | 7.963 | 8.0714 | 8.1538 | 8 | 7.75 | 8.5 |
| Kerosene used in Djibouti (Million Barrels/Day) | 0.112243 | 0.133057 | 0.133422 | 0.133422 | 0.136874 | 0.130717 | 0.137928 |
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. - Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.
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([5.6667,7.963,8.0714,8.1538,8,7.75,8.5,])
array_2 = np.array([0.112243,0.133057,0.133422,0.133422,0.136874,0.130717,0.137928,])
array_1_name = "How insightful Casually Explained YouTube video titles are"
array_2_name = "Kerosene used in Djibouti"
# 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.
Full license details.
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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 How insightful Casually Explained YouTube video titles are
- Line chart for only Kerosene used in Djibouti
- AI-generated correlation image
- The spurious research paper: Kerosene and Casually Explained: How YouTube Video Titles Illuminate Energy Usage in Djibouti
Kudos for rating!
Correlation ID: 4349 · Black Variable ID: 25877 · Red Variable ID: 24355
