Spurious correlation #3,426 · 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 Amelia and the second variable is Biomass power generated in El Salvador. 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 Amelia and the second variable is Biomass power generated in El Salvador. The chart goes from 1980 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the name Amelia gained popularity, more and more parents were drawn to its classic charm. This led to a baby boom in El Salvador, creating an unexpected demand for diapers. To meet this demand, there was a spike in the production of plant-based diapers, which in turn boosted the need for biomass power to operate the manufacturing plants. It seems that Amelia truly sparked a renewable energy revolution, one diaper at a time!

^{Show image generation prompt} Model: dalle-3
Prompt: [ Symbolism ] Generate an image of a powerful sun rising over a verdant landscape, where a majestic tree stands tall and vital. The tree's branches are adorned with colorful ribbons, representing the vibrant energy of a sustainable future. In the background, a silhouette of a modern biomass power plant, emitting ethereal wisps of clean energy, symbolizing progress and renewal. The scene is infused with a sense of optimism and harmony with nature. 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 Amelia and Biomass power generated in El Salvador. 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: Glitch art Photorealism Surrealism Brutalism Symbolism
ChatGPT: Symbolism

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 Amelia and Biomass power generated in El Salvador, in the following situation: Because the name Amelia became popular among Salvadoran energy experts, they named a new biomass power plant after her, inspiring increased investment in renewable energy.. Keep the description simple.
ChatGPT: In El Salvador, a bustling biomass power plant named "Amelia" stands tall against the horizon. Its smokestacks emit wisps of clean energy into the sky, while workers bustle about the grounds, filled with enthusiasm. A banner proudly proclaims "Amelia" as the plant's namesake, honoring the name's popularity and the country's dedication to renewable energy.

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: [ Symbolism ] and depicting this scene: In El Salvador, a bustling biomass power plant named "Amelia" stands tall against the horizon. Its smokestacks emit wisps of clean energy into the sky, while workers bustle about the grounds, filled with enthusiasm. A banner proudly proclaims "Amelia" as the plant's namesake, honoring the name's popularity and the country's dedication to renewable energy. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Symbolism ] Generate an image of a powerful sun rising over a verdant landscape, where a majestic tree stands tall and vital. The tree's branches are adorned with colorful ribbons, representing the vibrant energy of a sustainable future. In the background, a silhouette of a modern biomass power plant, emitting ethereal wisps of clean energy, symbolizing progress and renewal. The scene is infused with a sense of optimism and harmony with nature.

*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 Amelia caused Biomass power generated in El Salvador to increase. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Ameliorating Biomass: The Amelia Effect on Power Generation in El Salvador

The Journal of Renewable Energy Innovation

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 dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Amelia and Biomass power generated in El Salvador. Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some movies that you watched that are tangentially related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
"Ameliorating Biomass: The Amelia Effect on Power Generation in El Salvador"

[[ABSTRACT]]
This study investigates the intriguing relationship between the popularity of the first name Amelia and the biomass power generated in El Salvador. Leveraging data from the US Social Security Administration and the Energy Information Administration, our research team delved into the connection between these seemingly disparate phenomena. Surprisingly, our findings revealed a correlation coefficient of 0.9899469 and a statistically significant p-value of less than 0.01 for the period spanning 1980 to 2021, indicating a strong association between the two variables. As we illuminate this unanticipated connection, our study offers a lighthearted exploration of a topic that sheds light on the curious interplay between human nomenclature and renewable energy sources.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The conjunction of seemingly unrelated phenomena has long intrigued researchers across diverse disciplines. In this study, we set out to explore the curious correlation between the popularity of the first name Amelia and the generation of biomass power in El Salvador. While one may initially dismiss such an inquiry as whimsical, our investigation uncovers a surprisingly robust relationship that defies conventional expectations.
The name "Amelia," with its origins in Germanic and Latin languages, has surged in popularity in recent decades, capturing the hearts and minds of expectant parents worldwide. Simultaneously, El Salvador has made noteworthy strides in the development of biomass power, harnessing organic materials to produce sustainable energy. One might ponder: what could possibly connect the naming preferences of parents and the energy landscape of a Central American nation? Our study aims to answer this question and shed light on the enigmatic interplay between human nomenclature and renewable energy generation.
To embark on this investigation, we delved into the archives of the US Social Security Administration, scrutinizing the ebb and flow of Amelia's ascendancy in the ranks of baby names. Combining this dataset with the Energy Information Administration's records of biomass power generation in El Salvador over the same period, we employed robust statistical analyses to discern any conceivable link between these disparate realms.
As we present the revelations of our study, we invite readers to join us in this lighthearted exploration of an unexpected and inexplicable harmony. Through a jocular lens, we intend to unravel the mystique surrounding the "Amelia effect" on biomass power generation, recognizing the serendipitous aspects of scholarly inquiry while maintaining an unwavering commitment to empirical rigor.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The authors find that the connection between the popularity of the first name "Amelia" and the biomass power generated in El Salvador has been a subject of minimal prior investigation. However, Smith et al. (2015) conducted a meticulous analysis of naming trends in industrialized nations and observed a curious uptick in Amelias coinciding with advances in renewable energy technologies. Similarly, Doe and Jones (2018) examined the evolution of biomass power generation in Latin American countries, noting a perplexing correlation with the prevalence of certain given names within their populations.

In "The Name Game" by Johnson (2016), a whimsical exploration of naming conventions, the author posits a tongue-in-cheek theory that names possess an inexplicable influence on the natural world, including the generation of sustainable energy sources. Conversely, "The Power of Biomass" by Williams (2017) offers a serious examination of biomass energy, champions the virtues of organic matter, and regrettably neglects any consideration of anthropomorphic nomenclature effects.

Notably, the fictional works "Amelia's Power Play" and "Biomass Babes" have not only elusive titles but also seemingly indirect connections to the subject matter at hand. However, the authors have come across these books while perusing the eclectic collection at a local bookstore, provoking a moment of levity in an otherwise arduous research process.

Moreover, the classic film "Amelia and the Biofuel Bandits" presents a captivating yet entirely fictitious narrative intertwining an individual named Amelia with a band of environmental crusaders who champion the power of biomass in the fight against climate change. While this cinematic masterpiece veers into the realm of fantasy, its thematic relevance to the current inquiry is unmistakable.

It is noteworthy that these sources, both real and imagined, provide valuable context for the uncharted territory our study seeks to navigate. The jocularity and seemingly tangential nature of these materials belie the potential for unexpected insights and delightfully offbeat discoveries, adding a dash of merriment to the rigorous pursuit of knowledge.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Popularity of the first name Amelia and Biomass power generated in El Salvador. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Energy Information Administration . You used data from 1980 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]]
"Ameliorating Biomass: The Amelia Effect on Power Generation in El Salvador"

[[ABSTRACT]]
This study investigates the intriguing relationship between the popularity of the first name Amelia and the biomass power generated in El Salvador. Leveraging data from the US Social Security Administration and the Energy Information Administration, our research team delved into the connection between these seemingly disparate phenomena. Surprisingly, our findings revealed a correlation coefficient of 0.9899469 and a statistically significant p-value of less than 0.01 for the period spanning 1980 to 2021, indicating a strong association between the two variables. As we illuminate this unanticipated connection, our study offers a lighthearted exploration of a topic that sheds light on the curious interplay between human nomenclature and renewable energy sources.

[[INTRODUCTION]]
The conjunction of seemingly unrelated phenomena has long intrigued researchers across diverse disciplines. In this study, we set out to explore the curious correlation between the popularity of the first name Amelia and the generation of biomass power in El Salvador. While one may initially dismiss such an inquiry as whimsical, our investigation uncovers a surprisingly robust relationship that defies conventional expectations.
The name "Amelia," with its origins in Germanic and Latin languages, has surged in popularity in recent decades, capturing the hearts and minds of expectant parents worldwide. Simultaneously, El Salvador has made noteworthy strides in the development of biomass power, harnessing organic materials to produce sustainable energy. One might ponder: what could possibly connect the naming preferences of parents and the energy landscape of a Central American nation? Our study aims to answer this question and shed light on the enigmatic interplay between human nomenclature and renewable energy generation.
To embark on this investigation, we delved into the archives of the US Social Security Administration, scrutinizing the ebb and flow of Amelia's ascendancy in the ranks of baby names. Combining this dataset with the Energy Information Administration's records of biomass power generation in El Salvador over the same period, we employed robust statistical analyses to discern any conceivable link between these disparate realms.
As we present the revelations of our study, we invite readers to join us in this lighthearted exploration of an unexpected and inexplicable harmony. Through a jocular lens, we intend to unravel the mystique surrounding the "Amelia effect" on biomass power generation, recognizing the serendipitous aspects of scholarly inquiry while maintaining an unwavering commitment to empirical rigor.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The methodology employed in this study was designed to meticulously sift through a plethora of data sets, combining sources from the US Social Security Administration and the Energy Information Administration to scrutinize the association between the popularity of the first name Amelia and biomass power generation in El Salvador. Given the seemingly unrelated nature of the variables under investigation, our approach demanded an innovative and comprehensive strategy.

To quantify the popularity of the name "Amelia," we scoured the depths of the US Social Security Administration's database, encompassing records from 1980 to 2021. Through rigorous analysis of name frequencies, trends, and even the occasional parental whim, we attained a nuanced understanding of the ebbs and flows in Amelia's prominence in the pantheon of nomenclature. This process involved treading through a veritable sea of data, filtering out the noise to discern the signal, much like locating a singular needle in an immensely vast haystack.

Concurrently, the investigation into biomass power generation in El Salvador delved into the Energy Information Administration's extensive reservoir of information. Collating data from a multitude of sources, we carefully considered the intricate dance of organic material, conversion processes, and energy output to capture the essence of biomass power generation in this Central American nation. The challenge of understanding this domain was akin to deciphering a complex puzzle, replete with the enigmatic allure of renewable energy dynamics.

It is crucial to note that the manner in which these data sources were harmonized presented a novel endeavor, blending the seemingly incongruent realms of human nomenclature and energy generation. The amalgamation of these disparate datasets demanded a synthesis that balanced the flexibilities and constraints of each domain, tastefully combining the art of naming and the science of renewable energy in a harmonious ballet of statistical inquiry.

The statistical analyses applied to explore the connection between Amelia's popularity and biomass power generation in El Salvador were as rigorous as they were whimsical. Regression models, correlation coefficients, and numerous other quantitative techniques were deftly wielded to capture the essence of the association. The statistical prowess exerted in this investigation would make even the most erudite of mathematicians nod in solemn acknowledgment of its adeptness.

Furthermore, the uncovering of this intriguing correlation was buttressed by a robust battery of sensitivity analyses and diagnostic tests, ensuring that the observed relationships were sustained under the rigor of scrutiny. This process involved peering through the looking glass of statistical inference, yielding a steadfast commitment to principled discovery.

In the culmination of these efforts, the methodology of this study epitomizes the unyielding dedication to unraveling the mysterious and uncanny relationship between a name and the energy it portends. Through the nuances of statistical analysis, dataset integration, and a touch of scholarly whimsy, our research proudly presents a framework that befits the elucidation of this unforeseen alliance.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Amelia and Biomass power generated in El Salvador. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Ameliorating Biomass: The Amelia Effect on Power Generation in El Salvador"

[[ABSTRACT]]
This study investigates the intriguing relationship between the popularity of the first name Amelia and the biomass power generated in El Salvador. Leveraging data from the US Social Security Administration and the Energy Information Administration, our research team delved into the connection between these seemingly disparate phenomena. Surprisingly, our findings revealed a correlation coefficient of 0.9899469 and a statistically significant p-value of less than 0.01 for the period spanning 1980 to 2021, indicating a strong association between the two variables. As we illuminate this unanticipated connection, our study offers a lighthearted exploration of a topic that sheds light on the curious interplay between human nomenclature and renewable energy sources.

[[LITERATURE REVIEW]]
The authors find that the connection between the popularity of the first name "Amelia" and the biomass power generated in El Salvador has been a subject of minimal prior investigation. However, Smith et al. (2015) conducted a meticulous analysis of naming trends in industrialized nations and observed a curious uptick in Amelias coinciding with advances in renewable energy technologies. Similarly, Doe and Jones (2018) examined the evolution of biomass power generation in Latin American countries, noting a perplexing correlation with the prevalence of certain given names within their populations.
In "The Name Game" by Johnson (2016), a whimsical exploration of naming conventions, the author posits a tongue-in-cheek theory that names possess an inexplicable influence on the natural world, including the generation of sustainable energy sources. Conversely, "The Power of Biomass" by Williams (2017) offers a serious examination of biomass energy, champions the virtues of organic matter, and regrettably neglects any consideration of anthropomorphic nomenclature effects.
Notably, the fictional works "Amelia's Power Play" and "Biomass Babes" have not only elusive titles but also seemingly indirect connections to the subject matter at hand. However, the authors have come across these books while perusing the eclectic collection at a local bookstore, provoking a moment of levity in an otherwise arduous research process.
Moreover, the classic film "Amelia and the Biofuel Bandits" presents a captivating yet entirely fictitious narrative intertwining an individual named Amelia with a band of environmental crusaders who champion the power of biomass in the fight against climate change. While this cinematic masterpiece veers into the realm of fantasy, its thematic relevance to the current inquiry is unmistakable.
It is noteworthy that these sources, both real and imagined, provide valuable context for the uncharted territory our study seeks to navigate. The jocularity and seemingly tangential nature of these materials belie the potential for unexpected insights and delightfully offbeat discoveries, adding a dash of merriment to the rigorous pursuit of knowledge.

[[RESULTS]]
Upon rigorous analysis of the data from the US Social Security Administration and the Energy Information Administration, a remarkable discovery emerged. A strikingly high correlation coefficient of 0.9899469 was uncovered, indicating a robust relationship between the popularity of the first name Amelia and the generation of biomass power in El Salvador. The r-squared value of 0.9799949 further accentuated the strength of this association, corroborating the substantial influence of the name "Amelia" on the renewable energy landscape of El Salvador.
The p-value of less than 0.01 emphasized the statistical significance of this correlation, providing compelling evidence to support the unexpected connection between the two variables. This finding challenges preconceived notions and offers a whimsical insight into the intricate dynamics of human nomenclature and renewable energy generation.
Figure 1 showcases a scatterplot depicting the compelling correlation between the popularity of the name "Amelia" and the biomass power generated in El Salvador. This visual representation underscores the pronounced relationship between these seemingly disparate phenomena, leaving little room for doubt regarding the robustness of the observed association.
In light of these compelling results, our research team seeks to encourage further exploration of unconventional correlations and to celebrate the unexpected revelations that academic inquiry can unveil. While our investigation may have begun as a playful curiosity, it has culminated in a significant contribution to the understanding of the Amelia effect on power generation in El Salvador.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study not only corroborate but also elevate the quirky findings of prior research, which suggested a potential link between the name "Amelia" and the generation of biomass power. The minutiae of our statistical analysis undeniably supports the veracity of the Amelia effect on the renewable energy landscape of El Salvador. The high correlation coefficient and r-squared value underscore the palpable influence of this seemingly innocuous name on the generation of sustainable power. The statistical significance, as evidenced by the p-value of less than 0.01, unequivocally underscores the robust connection between the frequency of the name "Amelia" and the biomass power output in El Salvador.

The reinforcement of prior research findings, particularly the whimsical musings of Johnson (2016) on naming conventions and their inexplicable influence on the natural world, serves as an intriguing validation of our present results. The correlation between Amelia's popularity and biomass power generation is indeed a manifestation of the oftentimes serendipitous and unexpected interconnections that pervade the realm of scholarly inquiry. The interplay between human nomenclature and renewable energy sources, which was once a speculative curiosity, now emerges as a compelling area ripe for further investigation and mirthful contemplation.

Our findings, although unexpected and lighthearted in nature, bring to the fore the delightful paradoxes and incongruities that enliven the scholarly pursuit of knowledge. While ostensibly unrelated, the prominence of the name "Amelia" and the generation of biomass power in El Salvador converge in a manner that elicits both amusement and intellectual curiosity. Consequently, the peculiar association between a personal moniker and a source of renewable energy stands as a testament to the whimsical intricacies that underlie the interconnectedness of diverse phenomena.

In conclusion, our study not only shines a light on the idiosyncratic interplay between human nomenclature and renewable energy but also invites scholars to embrace the unexpected and amusing facets of academic inquiry. The connection between the popularity of the first name "Amelia" and biomass power generation in El Salvador, while initially whimsical in nature, ultimately enriches the tapestry of scholarly discourse by presenting an unexpected and delightful confluence of research subjects. These findings underscore the unforeseen avenues of inquiry that stimulate scholarly curiosity and prompt a good-natured appreciation for the charmingly eccentric dimensions of academic exploration.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Amelia and Biomass power generated in El Salvador. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Ameliorating Biomass: The Amelia Effect on Power Generation in El Salvador"

[[ABSTRACT]]
This study investigates the intriguing relationship between the popularity of the first name Amelia and the biomass power generated in El Salvador. Leveraging data from the US Social Security Administration and the Energy Information Administration, our research team delved into the connection between these seemingly disparate phenomena. Surprisingly, our findings revealed a correlation coefficient of 0.9899469 and a statistically significant p-value of less than 0.01 for the period spanning 1980 to 2021, indicating a strong association between the two variables. As we illuminate this unanticipated connection, our study offers a lighthearted exploration of a topic that sheds light on the curious interplay between human nomenclature and renewable energy sources.

[[INTRDUCTION]]
The conjunction of seemingly unrelated phenomena has long intrigued researchers across diverse disciplines. In this study, we set out to explore the curious correlation between the popularity of the first name Amelia and the generation of biomass power in El Salvador. While one may initially dismiss such an inquiry as whimsical, our investigation uncovers a surprisingly robust relationship that defies conventional expectations.
The name "Amelia," with its origins in Germanic and Latin languages, has surged in popularity in recent decades, capturing the hearts and minds of expectant parents worldwide. Simultaneously, El Salvador has made noteworthy strides in the development of biomass power, harnessing organic materials to produce sustainable energy. One might ponder: what could possibly connect the naming preferences of parents and the energy landscape of a Central American nation? Our study aims to answer this question and shed light on the enigmatic interplay between human nomenclature and renewable energy generation.
To embark on this investigation, we delved into the archives of the US Social Security Administration, scrutinizing the ebb and flow of Amelia's ascendancy in the ranks of baby names. Combining this dataset with the Energy Information Administration's records of biomass power generation in El Salvador over the same period, we employed robust statistical analyses to discern any conceivable link between these disparate realms.
As we present the revelations of our study, we invite readers to join us in this lighthearted exploration of an unexpected and inexplicable harmony. Through a jocular lens, we intend to unravel the mystique surrounding the "Amelia effect" on biomass power generation, recognizing the serendipitous aspects of scholarly inquiry while maintaining an unwavering commitment to empirical rigor.

[[RESULTS]]
Upon rigorous analysis of the data from the US Social Security Administration and the Energy Information Administration, a remarkable discovery emerged. A strikingly high correlation coefficient of 0.9899469 was uncovered, indicating a robust relationship between the popularity of the first name Amelia and the generation of biomass power in El Salvador. The r-squared value of 0.9799949 further accentuated the strength of this association, corroborating the substantial influence of the name "Amelia" on the renewable energy landscape of El Salvador.
The p-value of less than 0.01 emphasized the statistical significance of this correlation, providing compelling evidence to support the unexpected connection between the two variables. This finding challenges preconceived notions and offers a whimsical insight into the intricate dynamics of human nomenclature and renewable energy generation.
Figure 1 showcases a scatterplot depicting the compelling correlation between the popularity of the name "Amelia" and the biomass power generated in El Salvador. This visual representation underscores the pronounced relationship between these seemingly disparate phenomena, leaving little room for doubt regarding the robustness of the observed association.
In light of these compelling results, our research team seeks to encourage further exploration of unconventional correlations and to celebrate the unexpected revelations that academic inquiry can unveil. While our investigation may have begun as a playful curiosity, it has culminated in a significant contribution to the understanding of the Amelia effect on power generation in El Salvador.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the correlation between the popularity of the first name Amelia and biomass power generation in El Salvador has proven to be an unexpected yet robust connection. It appears that the more parents name their children Amelia, the more biomass power is generated in this Central American nation. It is quite a "powerful" impact the name has, if you pardon the pun.

These findings highlight the need to consider unconventional factors in the study of energy generation and human behavior. Who would have thought that a simple name could have such an influence on renewable energy production? It seems that the universe works in mysterious ways, and statistical analysis has a way of uncovering these whimsical relationships. This just goes to show that one should never underestimate the influence of nomenclature in shaping our world – or at least the world of biomass power in El Salvador.

As we reflect on the implications of our study, we cannot help but marvel at the fascinating intersections between seemingly unrelated domains. The "Amelia effect" on biomass power generation serves as a reminder of the delightful surprises that can emerge from scholarly inquiry. It is a testament to the serendipitous nature of research and the patterns that lie beneath the surface of our everyday experiences.

In light of these compelling revelations, it is clear that further research in this area is unnecessary. We are confident that this study has exhausted the depths of the "Amelia effect" on biomass power generation in El Salvador, and no more inquiries are needed in this delightful yet unexpected realm of scholarly exploration.

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 Ameliorating Biomass: The Amelia Effect on Power Generation in El Salvador. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Renewable Energy Innovation

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 Ameliorating Biomass: The Amelia Effect on Power Generation in El Salvador. Respond only with the name of a fictional organization.

ChatGPT:

The International Society for Sustainable Energy Solutions (ISSES)

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 Ameliorating Biomass: The Amelia Effect on Power Generation in El Salvador with an abstract of This study investigates the intriguing relationship between the popularity of the first name Amelia and the biomass power generated in El Salvador. Leveraging data from the US Social Security Administration and the Energy Information Administration, our research team delved into the connection between these seemingly disparate phenomena. Surprisingly, our findings revealed a correlation coefficient of 0.9899469 and a statistically significant p-value of less than 0.01 for the period spanning 1980 to 2021, indicating a strong association between the two variables. As we illuminate this unanticipated connection, our study offers a lighthearted exploration of a topic that sheds light on the curious interplay between human nomenclature and renewable energy sources.

ChatGPT:

Amelia popularity, biomass power generation, El Salvador, correlation coefficient, statistically significant, US Social Security Administration data, Energy Information Administration data

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

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

Correlation r = 0.9899469 (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 = 0.9799949 (Coefficient of determination)
This means 98% of the change in the one variable (i.e., Biomass power generated in El Salvador) is predictable based on the change in the other (i.e., Popularity of the first name Amelia) over the 42 years from 1980 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.^Show 0.0000000000000000000000000000
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 0.99 in 0% of random cases. Said differently, if you correlated
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inf random variables^Note
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You don't actually need
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INF variables to find a correlation like this one.
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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.
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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.

[ 0.98, 0.99 ] 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 Amelia (Babies born)	768	849	832	768	1100	1014	1023	1011	1129	1273	1513	1541	1345	1253	1254	1207	1291	1317	1424	1421	1531	1635	2444	3096	3366	3915	4070	4201	4351	4707	5464	6379	7246	8052	8812	9870	10806	11870	12394	12946	12786	13015
Biomass power generated in El Salvador (Billion kWh)	0.006	0.026	0.02	0.026	0.024	0.024	0.026	0.017	0.021	0.023	0.021	0.016	0.029	0.015	0.005	0.006	0.019	0.021	0.023	0.023	0.02	0.019	0.022	0.041	0.061	0.089	0.143	0.145	0.174	0.232	0.283	0.303	0.409	0.43	0.438	0.563	0.635	0.711	0.74	0.829	0.815	0.821495

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Confounding variable: 2020 is particularly different from the other years on this graph. Confounding variables (like global pandemics) will cause two variables to look connected when in fact a "sneaky third" variable is influencing both of them behind the scenes.

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([768,849,832,768,1100,1014,1023,1011,1129,1273,1513,1541,1345,1253,1254,1207,1291,1317,1424,1421,1531,1635,2444,3096,3366,3915,4070,4201,4351,4707,5464,6379,7246,8052,8812,9870,10806,11870,12394,12946,12786,13015,])
array_2 = np.array([0.006,0.026,0.02,0.026,0.024,0.024,0.026,0.017,0.021,0.023,0.021,0.016,0.029,0.015,0.005,0.006,0.019,0.021,0.023,0.023,0.02,0.019,0.022,0.041,0.061,0.089,0.143,0.145,0.174,0.232,0.283,0.303,0.409,0.43,0.438,0.563,0.635,0.711,0.74,0.829,0.815,0.821495,])
array_1_name = "Popularity of the first name Amelia"
array_2_name = "Biomass power generated in El Salvador"

# 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 Amelia
Line chart for only Biomass power generated in El Salvador
AI-generated correlation image
The spurious research paper: Ameliorating Biomass: The Amelia Effect on Power Generation in El Salvador

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Correlation ID: 3426 · Black Variable ID: 2433 · Red Variable ID: 23648


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