Spurious correlation #4,232 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Alanna and the second variable is Biomass power generated in United States. The chart goes from 1980 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Alanna and the second variable is Biomass power generated in United States. The chart goes from 1980 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As more and more babies named Alanna were born, it created a surge in demand for wooden name plaques. This led to a boom in the forestry industry, resulting in an abundance of wood byproducts that could be used for biomass power generation in the United States. It's like the Alannapocalyse of renewable energy!

^{Show image generation prompt} Model: dalle-3
Prompt: [ Cutsy art illustration ] Generate an image of a bustling sawmill in the United States, with workers cutting and shaping wood to create name plaques for baby Alannas. Show the air filled with the sweet scent of fresh wood shavings. Also, depict a nearby power plant proudly utilizing wood byproducts as fuel for biomass power generation, with smoke billowing from its chimney against the backdrop of a bright, sunny sky. 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: Popularity of the first name Alanna and Biomass power generated in United States. 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: Cyberpunk Woodblock painting Cutsy art illustration a Polaroid photo Vaporwave
ChatGPT: Cutsy art illustration

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 Popularity of the first name Alanna and Biomass power generated in United States, in the following situation: As more and more babies named Alanna were born, it created a surge in demand for wooden name plaques. This led to a boom in the forestry industry, resulting in an abundance of wood byproducts that could be used for biomass power generation in the United States. It's like the Alannapocalyse of renewable energy!. Keep the description simple.
ChatGPT: A bustling sawmill in the United States, with workers busy cutting and shaping wood to create name plaques for the rising number of baby Alannas. The air is filled with the sweet scent of fresh wood shavings. Meanwhile, a nearby power plant proudly utilizes the abundance of wood byproducts as fuel for biomass power generation, with smoke billowing from its chimney against the backdrop of a bright, sunny sky.

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: [ Cutsy art illustration ] and depicting this scene: A bustling sawmill in the United States, with workers busy cutting and shaping wood to create name plaques for the rising number of baby Alannas. The air is filled with the sweet scent of fresh wood shavings. Meanwhile, a nearby power plant proudly utilizes the abundance of wood byproducts as fuel for biomass power generation, with smoke billowing from its chimney against the backdrop of a bright, sunny sky. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Cutsy art illustration ] Generate an image of a bustling sawmill in the United States, with workers cutting and shaping wood to create name plaques for baby Alannas. Show the air filled with the sweet scent of fresh wood shavings. Also, depict a nearby power plant proudly utilizing wood byproducts as fuel for biomass power generation, with smoke billowing from its chimney against the backdrop of a bright, sunny sky.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Popularity of the first name Alanna caused Biomass power generated in United States to increase.

AI academic paper

(Because p < 0.01)

Power of Name: Exploring the Alanna-nature Connection in Biomass Energy Generation

The Journal of Ecological Linguistics

Jan 2024

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

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Popularity of the first name Alanna and Biomass power generated in United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then you might move on to cartoons and children's shows that you watched for research.

Here is the title and abstract of the paper:
[[TITLE]]
Power of Name: Exploring the Alanna-nature Connection in Biomass Energy Generation

[[ABSTRACT]]
The popularity of first names has long been a source of fascination for both the public and academicians. In this study, we delve into the compelling correlation between the popularity of the first name Alanna and the generation of biomass power in the United States. Using data from the US Social Security Administration and the Energy Information Administration for the years 1980 to 2021, we have unearthed a remarkable correlation coefficient of 0.9305282 and a statistically significant p-value of less than 0.01, suggesting a robust connection between the two phenomena.

While our findings may seem surprising at first glance, they are a testament to the quirky and intriguing patterns that often go unnoticed in the vast domains of human behavior and energy production. By shedding light on this unexplored relationship, we hope to spark further curiosity and research into the playful interplay of nomenclature and renewable energy generation.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The power of a name has been a topic of intrigue since the dawn of time. Our fascination with names extends from the playground, where we may have giggled at the sound of a classmate's peculiar moniker, to the boardroom, where the implications of a company's branding are carefully scrutinized. In the context of this research, we turn our attention to the correlation between the popularity of the first name Alanna and the production of biomass energy in the United States.
While the concept may seem whimsical at first, the statistical analysis in this study reveals a substantial correlation coefficient, indicating a strong relationship between the frequency of the name Alanna and the generation of biomass power. This unexpected discovery prompts us to delve deeper into the mechanisms behind this connection and contemplate the broader implications it may have for societal and environmental dynamics.
Our endeavor is not merely a playful exploration of nomenclature; it is an earnest attempt to uncover underlying patterns that may shed light on the interconnected web of human behavior and renewable energy production. As we embark on this journey, we invite the reader to join us in unraveling the mysterious dance between names and the sustainable generation of power.
So, strap in and prepare for a wild ride through the uncharted territory where the whimsical world of nomenclature intersects with the serious business of renewable energy. Let's dive in and see what surprises await in the correlations between Alannas and biomass power generation!

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

As we dive into the compelling connection between the popularity of the first name Alanna and biomass power generation in the United States, it is essential to examine the existing literature on the subject. While the topic may seem unusual, our exploration is grounded in the pursuit of uncovering unconventional patterns and correlations. Let us first consider the serious research literature that serves as the foundation for our whimsical investigation.

Smith et al. (2015) conducted a comprehensive study on the societal implications of first names, delving into the psychological and cultural factors that influence naming trends. Their work provides valuable insights into the significance attached to names and the subtle ways in which they may influence individual behavior.

Doe and Jones (2018) offer an in-depth analysis of renewable energy sources, focusing on the challenges and opportunities in biomass power generation. Though seemingly unrelated to our investigation, their exploration of biomass energy production sets the stage for our examination of the Alanna-nature connection.

Turning our attention to non-fiction literature, "The Power of Names" by Johnson (2013) offers a thought-provoking exploration of the historical, linguistic, and societal dimensions of names. While not directly addressing the correlation between names and energy, this work sparks contemplation on the intricate significance of nomenclature in human interactions.

In a similar vein, "Renewable Energy: A Comprehensive Guide" by White (2017) provides a comprehensive overview of renewable energy technologies, including biomass power. While the book primarily analyzes the technical aspects of biomass energy, it offers a backdrop for our investigation into the playful association between the name Alanna and sustainable power generation.

Transitioning to the realm of fiction, the novel "Eco-Empress" by Green (2005) weaves a tale of a protagonist named Alanna, who discovers a mystical connection between her name and the natural world, culminating in a quest to harness renewable energy for the betterment of society. While a work of imagination, the novel echoes the themes we seek to explore in our research, blurring the lines between whimsy and empirical investigation.

Building on the theme of unexpected allegories, the children's book "The Biomass Adventure of Alanna the Explorer" by Blue (2010) tells the story of a young girl named Alanna who ventures into a magical forest, where she encounters talking trees and learns the secrets of sustainable energy production. Though intended for young readers, the book's fanciful narrative resonates with the serendipitous intersection of Alannas and biomass power generation that we aim to unravel.

As we venture into uncharted territory, it becomes evident that the intertwining of names and renewable energy spans realms both factual and fantastical. Our exploration is not merely a scientific inquiry; it is a whimsical expedition into the playful blend of nomenclature and sustainable power generation. Join us in navigating this peculiar landscape, where statistical analysis intersects with the enchanting allure of Alannas and biomass energy.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Alanna and Biomass power generated in United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Power of Name: Exploring the Alanna-nature Connection in Biomass Energy Generation

[[ABSTRACT]]
The popularity of first names has long been a source of fascination for both the public and academicians. In this study, we delve into the compelling correlation between the popularity of the first name Alanna and the generation of biomass power in the United States. Using data from the US Social Security Administration and the Energy Information Administration for the years 1980 to 2021, we have unearthed a remarkable correlation coefficient of 0.9305282 and a statistically significant p-value of less than 0.01, suggesting a robust connection between the two phenomena.

While our findings may seem surprising at first glance, they are a testament to the quirky and intriguing patterns that often go unnoticed in the vast domains of human behavior and energy production. By shedding light on this unexplored relationship, we hope to spark further curiosity and research into the playful interplay of nomenclature and renewable energy generation.

[[LITERATURE REVIEW]]
As we dive into the compelling connection between the popularity of the first name Alanna and biomass power generation in the United States, it is essential to examine the existing literature on the subject. While the topic may seem unusual, our exploration is grounded in the pursuit of uncovering unconventional patterns and correlations. Let us first consider the serious research literature that serves as the foundation for our whimsical investigation.
Smith et al. (2015) conducted a comprehensive study on the societal implications of first names, delving into the psychological and cultural factors that influence naming trends. Their work provides valuable insights into the significance attached to names and the subtle ways in which they may influence individual behavior.
Doe and Jones (2018) offer an in-depth analysis of renewable energy sources, focusing on the challenges and opportunities in biomass power generation. Though seemingly unrelated to our investigation, their exploration of biomass energy production sets the stage for our examination of the Alanna-nature connection.
Turning our attention to non-fiction literature, "The Power of Names" by Johnson (2013) offers a thought-provoking exploration of the historical, linguistic, and societal dimensions of names. While not directly addressing the correlation between names and energy, this work sparks contemplation on the intricate significance of nomenclature in human interactions.
In a similar vein, "Renewable Energy: A Comprehensive Guide" by White (2017) provides a comprehensive overview of renewable energy technologies, including biomass power. While the book primarily analyzes the technical aspects of biomass energy, it offers a backdrop for our investigation into the playful association between the name Alanna and sustainable power generation.
Transitioning to the realm of fiction, the novel "Eco-Empress" by Green (2005) weaves a tale of a protagonist named Alanna, who discovers a mystical connection between her name and the natural world, culminating in a quest to harness renewable energy for the betterment of society. While a work of imagination, the novel echoes the themes we seek to explore in our research, blurring the lines between whimsy and empirical investigation.
Building on the theme of unexpected allegories, the children's book "The Biomass Adventure of Alanna the Explorer" by Blue (2010) tells the story of a young girl named Alanna who ventures into a magical forest, where she encounters talking trees and learns the secrets of sustainable energy production. Though intended for young readers, the book's fanciful narrative resonates with the serendipitous intersection of Alannas and biomass power generation that we aim to unravel.
As we venture into uncharted territory, it becomes evident that the intertwining of names and renewable energy spans realms both factual and fantastical. Our exploration is not merely a scientific inquiry; it is a whimsical expedition into the playful blend of nomenclature and sustainable power generation. Join us in navigating this peculiar landscape, where statistical analysis intersects with the enchanting allure of Alannas and biomass energy.

[[RESULTS]]
The results of our analysis reveal a remarkably strong correlation between the popularity of the first name Alanna and the generation of biomass power in the United States. After sifting through the data from the US Social Security Administration and the Energy Information Administration for the period from 1980 to 2021, we found a correlation coefficient of 0.9305282 between the frequency of the name Alanna and the biomass power generated. This correlation coefficient indicates a robust positive relationship between the two variables.
Furthermore, the coefficient of determination (r-squared) of 0.8658828 suggests that a substantial proportion of the variation in biomass power generation can be explained by the frequency of the name Alanna. In other words, the popularity of the name Alanna is a powerful predictor of the amount of biomass power produced, which is quite unexpected and intriguing.
The statistical significance of our findings is also noteworthy, as indicated by a p-value of less than 0.01. This means that the likelihood of observing such a strong correlation by random chance is extremely low, adding further credence to the legitimacy of our results.
In essence, our analysis uncovers a fascinating connection between the prevalence of the name Alanna and the production of biomass energy, suggesting that there may be captivating underlying mechanisms at play. This unexpected correlation piques curiosity and prompts the exploration of potential explanations for this peculiar relationship.
For a more visual representation of our findings, please refer to Figure 1, which displays a scatterplot illustrating the strong correlation between the frequency of the name Alanna and biomass power generation.
These results provide compelling evidence of the intricate interplay between nomenclature and renewable energy production, opening the door to a realm of inquiry that transcends the ordinary boundaries of academic investigation. While the prospect of a name influencing biomass energy generation may initially seem whimsical, our data-driven analysis underscores the importance of considering unconventional factors in the study of societal and environmental phenomena.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our findings substantiate and extend the prior research that has prodded at the intersection of nomenclature and environmental domains, delving into the perplexing correlation between the prevalence of the first name Alanna and biomass power generation in the United States. While this investigation may initially appear lighthearted, the robust statistical significance of our results underscores the significance of this relationship.

The strong correlation coefficient of 0.9305282 between the frequency of the name Alanna and biomass power generation aligns with the earlier work of Smith et al. (2015), who elucidated the psychological and cultural implications of naming trends. Much like a name's influence on individual behavior, our results hint at a curious influence of the name Alanna on a broader societal phenomenon, albeit one that may have renewable energy enthusiasts scratching their heads.

Moreover, our findings echo the work of Green (2005) and Blue (2010), whose imaginative literature playfully mused on the potential connections between the name Alanna and the natural world. What once seemed like whimsical allegory now finds a semblance of empirical validation in our study, prompting contemplation on the mysterious interplay between human nomenclature and sustainable energy production.

It is intriguing to note the high coefficient of determination (r-squared) of 0.8658828 in our analysis, indicating that a substantial proportion of the variance in biomass power generation can be attributed to the frequency of the name Alanna – a fascinating revelation that intertwines statistical rigidity with the whimsy of name associations. This result mirrors the complexity inherent in naming identified by Johnson (2013), inviting consideration of the intricate significance of nomenclature in the broader context of societal and environmental phenomena.

As we traverse the terrain of our study, we are reminded of the serendipitous confluence of statistical analysis and enchanting nomenclature, evoking the playful possibilities that unfold when venturing into unconventional research territories. The statistically significant p-value of less than 0.01 further reinforces the credibility of our findings, stripping away any vestiges of doubt and illuminating the potential influence of names on the renewable energy landscape.

In summation, our investigation not only reinforces the veracity of the Alanna-nature connection but also instills a sense of wonder and inquisitiveness, ushering in a new wave of exploration amidst the academically uncharted waters of whimsical nomenclature and sustainable energy generation. This study sheds light on the captivating dance between human names and environmental phenomena, inviting scholars to embark on a journey where empirical investigation meets the unexpected allure of nomenclatural whimsy.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Popularity of the first name Alanna and Biomass power generated in United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Power of Name: Exploring the Alanna-nature Connection in Biomass Energy Generation

[[ABSTRACT]]
The popularity of first names has long been a source of fascination for both the public and academicians. In this study, we delve into the compelling correlation between the popularity of the first name Alanna and the generation of biomass power in the United States. Using data from the US Social Security Administration and the Energy Information Administration for the years 1980 to 2021, we have unearthed a remarkable correlation coefficient of 0.9305282 and a statistically significant p-value of less than 0.01, suggesting a robust connection between the two phenomena.

While our findings may seem surprising at first glance, they are a testament to the quirky and intriguing patterns that often go unnoticed in the vast domains of human behavior and energy production. By shedding light on this unexplored relationship, we hope to spark further curiosity and research into the playful interplay of nomenclature and renewable energy generation.

[[INTRDUCTION]]
The power of a name has been a topic of intrigue since the dawn of time. Our fascination with names extends from the playground, where we may have giggled at the sound of a classmate's peculiar moniker, to the boardroom, where the implications of a company's branding are carefully scrutinized. In the context of this research, we turn our attention to the correlation between the popularity of the first name Alanna and the production of biomass energy in the United States.
While the concept may seem whimsical at first, the statistical analysis in this study reveals a substantial correlation coefficient, indicating a strong relationship between the frequency of the name Alanna and the generation of biomass power. This unexpected discovery prompts us to delve deeper into the mechanisms behind this connection and contemplate the broader implications it may have for societal and environmental dynamics.
Our endeavor is not merely a playful exploration of nomenclature; it is an earnest attempt to uncover underlying patterns that may shed light on the interconnected web of human behavior and renewable energy production. As we embark on this journey, we invite the reader to join us in unraveling the mysterious dance between names and the sustainable generation of power.
So, strap in and prepare for a wild ride through the uncharted territory where the whimsical world of nomenclature intersects with the serious business of renewable energy. Let's dive in and see what surprises await in the correlations between Alannas and biomass power generation!

[[RESULTS]]
The results of our analysis reveal a remarkably strong correlation between the popularity of the first name Alanna and the generation of biomass power in the United States. After sifting through the data from the US Social Security Administration and the Energy Information Administration for the period from 1980 to 2021, we found a correlation coefficient of 0.9305282 between the frequency of the name Alanna and the biomass power generated. This correlation coefficient indicates a robust positive relationship between the two variables.
Furthermore, the coefficient of determination (r-squared) of 0.8658828 suggests that a substantial proportion of the variation in biomass power generation can be explained by the frequency of the name Alanna. In other words, the popularity of the name Alanna is a powerful predictor of the amount of biomass power produced, which is quite unexpected and intriguing.
The statistical significance of our findings is also noteworthy, as indicated by a p-value of less than 0.01. This means that the likelihood of observing such a strong correlation by random chance is extremely low, adding further credence to the legitimacy of our results.
In essence, our analysis uncovers a fascinating connection between the prevalence of the name Alanna and the production of biomass energy, suggesting that there may be captivating underlying mechanisms at play. This unexpected correlation piques curiosity and prompts the exploration of potential explanations for this peculiar relationship.
For a more visual representation of our findings, please refer to Figure 1, which displays a scatterplot illustrating the strong correlation between the frequency of the name Alanna and biomass power generation.
These results provide compelling evidence of the intricate interplay between nomenclature and renewable energy production, opening the door to a realm of inquiry that transcends the ordinary boundaries of academic investigation. While the prospect of a name influencing biomass energy generation may initially seem whimsical, our data-driven analysis underscores the importance of considering unconventional factors in the study of societal and environmental phenomena.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the whimsical and unexpected correlation between the prevalence of the first name Alanna and the generation of biomass power in the United States has brought to light a delightful nexus between nomenclature and renewable energy. Our findings, with a correlation coefficient of 0.9305282 and a p-value of less than 0.01, emphasize the robustness and statistical significance of this connection, much like finding treasure at the end of a quirky scavenger hunt.

The compelling nature of this correlation leaves us pondering the potential influence of Alannas on the renewable energy landscape. Perhaps every time someone exclaims, "Alanna!", a gust of wind propels a turbine or a ray of sunshine amplifies solar panels. It's as if the universe is secretly whispering, "Alanna, Alanna, create energy!"

This study not only adds a whimsical twist to the academic discourse but also underscores the importance of considering unconventional socio-cultural factors in the realms of renewable energy and sustainable development. While the correlation may seem like the plot of a quirky sitcom, its statistical significance cannot be ignored, much like a catchy tune that refuses to leave the mind.

As we wrap up this exploration, we invite the scholarly community to channel their inner Alanna and embark on ventures that embrace the unexpected and the unconventional. We emphatically assert that no further research is needed in this area, as we have unraveled the enchanting saga of the Alanna-nature connection, leaving our data-driven mark on the wacky intersection of nomenclature and biomass power generation.

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 Power of Name: Exploring the Alanna-nature Connection in Biomass Energy Generation. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Ecological Linguistics

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 Power of Name: Exploring the Alanna-nature Connection in Biomass Energy Generation. Respond only with the name of a fictional organization.

ChatGPT:

Center for Bioenergy 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 Power of Name: Exploring the Alanna-nature Connection in Biomass Energy Generation with an abstract of The popularity of first names has long been a source of fascination for both the public and academicians. In this study, we delve into the compelling correlation between the popularity of the first name Alanna and the generation of biomass power in the United States. Using data from the US Social Security Administration and the Energy Information Administration for the years 1980 to 2021, we have unearthed a remarkable correlation coefficient of 0.9305282 and a statistically significant p-value of less than 0.01, suggesting a robust connection between the two phenomena.
While our findings may seem surprising at first glance, they are a testament to the quirky and intriguing patterns that often go unnoticed in the vast domains of human behavior and energy production. By shedding light on this unexplored relationship, we hope to spark further curiosity and research into the playful interplay of nomenclature and renewable energy generation.

ChatGPT:

Alanna, first name popularity, biomass power generation, United States, correlation coefficient, US Social Security Administration, Energy Information Administration, renewable energy generation

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

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Data details

Popularity of the first name Alanna
Detailed data title: Babies of all sexes born in the US named Alanna
Source: US Social Security Administration
See what else correlates with Popularity of the first name Alanna

Biomass power generated in United States
Detailed data title: Total biomass power generated in United States in billion kWh
Source: Energy Information Administration
See what else correlates with Biomass power generated in United States

Correlation r = 0.9305282 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.8658828 (Coefficient of determination)
This means 86.6% of the change in the one variable (i.e., Biomass power generated in United States) is predictable based on the change in the other (i.e., Popularity of the first name Alanna) over the 42 years from 1980 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.8E-19.^Show 0.0000000000000000004759580917
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.93 in 4.8E-17% of random cases. Said differently, if you correlated 2,101,025,315,964,808,960 random variables^Note You don't actually need 2 quintillion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 41 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 41 because we have two variables measured over a period of 42 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.

[ 0.87, 0.96 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	1980	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	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
Popularity of the first name Alanna (Babies born)	252	295	289	245	275	297	289	286	334	361	520	476	480	499	491	481	543	499	497	544	541	543	565	587	625	618	667	691	683	654	573	579	626	597	586	620	554	565	558	575	523	547
Biomass power generated in United States (Billion kWh)	0.433163	0.367829	0.320918	0.378612	0.885951	1.38287	1.17674	1.47703	1.67424	40.2294	49.3979	54.129	58.0646	59.4436	60.7329	61.0299	61.2829	62.2695	62.3577	63.6367	65.5201	61.6544	67.2357	67.3856	67.7699	67.0979	67.835	67.7697	66.8373	66.4211	68.9447	70.8244	71.4092	74.4455	77.3827	77.5866	76.4495	75.7418	74.8051	70.8381	67.5668	67.6189

Why this works

Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([252,295,289,245,275,297,289,286,334,361,520,476,480,499,491,481,543,499,497,544,541,543,565,587,625,618,667,691,683,654,573,579,626,597,586,620,554,565,558,575,523,547,])
array_2 = np.array([0.433163,0.367829,0.320918,0.378612,0.885951,1.38287,1.17674,1.47703,1.67424,40.2294,49.3979,54.129,58.0646,59.4436,60.7329,61.0299,61.2829,62.2695,62.3577,63.6367,65.5201,61.6544,67.2357,67.3856,67.7699,67.0979,67.835,67.7697,66.8373,66.4211,68.9447,70.8244,71.4092,74.4455,77.3827,77.5866,76.4495,75.7418,74.8051,70.8381,67.5668,67.6189,])
array_1_name = "Popularity of the first name Alanna"
array_2_name = "Biomass power generated in United States"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

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

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Popularity of the first name Alanna
Line chart for only Biomass power generated in United States
AI-generated correlation image
The spurious research paper: Power of Name: Exploring the Alanna-nature Connection in Biomass Energy Generation

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Correlation ID: 4232 · Black Variable ID: 2845 · Red Variable ID: 24080


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