Spurious correlation #3,036 · 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 Eva and the second variable is Biomass power generated in Hungary. The chart goes from 1990 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 Eva and the second variable is Biomass power generated in Hungary. The chart goes from 1990 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the popularity of the name Eva rose, more and more people began naming their pet plants after the beloved name. This led to a surge in positive plant energy, quite literally fueling the growth of biomass in Hungary. It seems that every Eva-nwhen and Eva-rywhere a plant was named, it was destined to become a powerhouse of bioenergy. The connection between the name Eva and biomass power in Hungary has truly blossomed into a leafy green phenomenon!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a picturesque sunny day in Hungary, where a vibrant field of green crops sways gently in the breeze. Among the crops, a group of little girls named Eva play joyfully, their laughter echoing through the air. In the background, a towering biomass power plant hums with activity, its chimneys releasing wisps of clean white steam into the clear blue sky. The Evas' presence infuses the scene with a sense of renewed energy, symbolizing the connection between the popularity of the name Eva and the generation of biomass power in Hungary. 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 Eva and Biomass power generated in Hungary. 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: Cybernetic art Scalar art Glitch art Macabre A scene from Skyrim
ChatGPT: A scene from Skyrim

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 Eva and Biomass power generated in Hungary, in the following situation: Because as the name Eva became more popular, more parents started naming their daughters after Eva, the first woman according to the Bible. This resulted in a subconscious collective desire to honor the Earth, leading to an increase in demand for environmentally friendly energy sources, such as biomass power in Hungary. So, the more little Evas there are, the more biomass power gets generated. It's like a renewable energy spell cast by all the Evas out there!. Keep the description simple.
ChatGPT: Picture a sunny day in Hungary, where a field of vibrant green crops rustle gently in the breeze. Among the crops, a group of little girls named Eva joyfully play, their laughter filling the air. In the background, a towering biomass power plant hums with activity, its chimneys releasing wisps of clean white steam into the clear blue sky. As the Evas frolic and giggle, their collective presence seems to infuse the air with a sense of renewed energy, symbolizing the connection between the popularity of the name Eva and the generation of biomass power in Hungary.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A scene from Skyrim ] and depicting this scene: Picture a sunny day in Hungary, where a field of vibrant green crops rustle gently in the breeze. Among the crops, a group of little girls named Eva joyfully play, their laughter filling the air. In the background, a towering biomass power plant hums with activity, its chimneys releasing wisps of clean white steam into the clear blue sky. As the Evas frolic and giggle, their collective presence seems to infuse the air with a sense of renewed energy, symbolizing the connection between the popularity of the name Eva and the generation of biomass power in Hungary. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a picturesque sunny day in Hungary, where a vibrant field of green crops sways gently in the breeze. Among the crops, a group of little girls named Eva play joyfully, their laughter echoing through the air. In the background, a towering biomass power plant hums with activity, its chimneys releasing wisps of clean white steam into the clear blue sky. The Evas' presence infuses the scene with a sense of renewed energy, symbolizing the connection between the popularity of the name Eva and the generation of biomass power in Hungary.

*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 Eva caused Biomass power generated in Hungary to increase. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Eva-luating Eva's Impact: The Biomass Power of Punny Names in Hungary

The International Journal of LOL-nomics

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 Eva and Biomass power generated in Hungary. 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
"Eva-luating Eva's Impact: The Biomass Power of Punny Names in Hungary"

[[ABSTRACT]]
This paper assesses the unexpected connection between the popularity of the first name "Eva" and the generation of biomass power in Hungary. Drawing on data from the US Social Security Administration and the Energy Information Administration, our research team calculated a correlation coefficient of 0.9652795 and p < 0.01 for the time period spanning 1990 to 2021. While the relationship between personal nomenclature and renewable energy production may seem frivolous, our findings suggest otherwise. This study provides insightful and, dare we say, "punderful" analysis into the hitherto unexplored realm of the impact of names on sustainable energy outcomes.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The influence of personal names on various aspects of individual and societal lives has been of interest to researchers across disciplines. While the scholarly community has delved into the implications of names on career prospects, academic achievement, and even interpersonal relationships, the connection between names and renewable energy production has been largely unexplored. This study seeks to fill this punny gap in the literature by examining the relationship between the popularity of the first name "Eva" and the generation of biomass power in Hungary.
The choice of the name "Eva" is not arbitrary, as it reflects a broader interest in the potential impact of names with a delightful twist – bear with us on this journey. The juxtaposition of a personal moniker with the disciplined realm of biomass power generation may raise a few eyebrows, but as we dove into the data, the correlation coefficients emerged with a surprising clarity and statistical significance – much like a punchline that unexpectedly lands with impeccable timing.
The title of this research paper endeavors to embody the lightheartedness that underpins this investigation. The term "Eva-luating" offers a whimsical play-on-words, inviting readers to approach the study with an open mind and a penchant for charming wordplay. The use of "pun" in the abstract, albeit mildly audacious, sets the tone for the levity and amusement that we hope will accompany the rigorous analysis presented in the subsequent sections.
Throughout this paper, we aim to strike a balance between the gravitas of academic inquiry and the jocularity that can be found in the unexpectedly delightful connections within our complex world. The investigation presented herein demonstrates that sometimes, the most amusing of correlations can uncover insights of genuine significance, and the intertwining of nomenclature and renewable energy production may yet reveal some surprising truths. withObjective scrutiny and perhaps a touch of silliness, we hereby embark on the exploration of Eva's impact on the biomass power landscape of Hungary.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

To fully comprehend the unexpected connection between the popularity of the first name "Eva" and the biomass power generated in Hungary, it is imperative to explore the existing literature on the subject, however scant it may be.

Smith and Doe (2015) investigated the effects of personal names on societal outcomes, albeit with no specific reference to renewable energy production or Hungarian naming conventions. Their work provided a valuable foundation for understanding the potential implications of nomenclature on broader phenomena, but fell short of delving into the realm of sustainable energy generation.

In the similarly titled "The Power of Names" (Jones, 2018), the author researched the impact of names on individual perceptions, attributions, and behavioral tendencies. While the book did not venture into the domain of biomass power production, its findings on the subconscious influences of names laid the groundwork for our investigation.

Expanding beyond conventional academic literature, "The Name Book" (Johnson, 2007) offered a comprehensive compilation of names and their purported meanings. While not a scholarly work per se, the book provided insight into the historical and cultural significance attributed to names, forming a contextual backdrop for our exploration.

Turning to the realm of fiction, "Naming Jack the Ripper" (Skinner, 2014) presented a speculative foray into the potential significance of names in infamous historical contexts. While a work of historical fiction, the book prompted considerations of the broader implications of names in shaping narratives and perceptions, thereby indirectly contributing to the foundational rationale for our study.

In a daring departure from traditional academic sources, the researchers also conducted a thorough review of the labels on various household items, including but not limited to condiment bottles, cereal boxes, and shampoo containers. While the findings from this unconventional source cannot be directly cited for academic purposes, the tongue-in-cheek mentions of "Eva" on some product packaging served to inspire alternate perspectives on the potential ubiquity of the name and its subtle yet impactful presence in everyday life.

Conclusively, the literature review presents a comprehensive yet lighthearted overview of the contextual underpinnings that have shaped the investigation into the correlation between the name "Eva" and biomass power generation in Hungary.

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 Eva and Biomass power generated in Hungary. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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 1990 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]]
"Eva-luating Eva's Impact: The Biomass Power of Punny Names in Hungary"

[[ABSTRACT]]
This paper assesses the unexpected connection between the popularity of the first name "Eva" and the generation of biomass power in Hungary. Drawing on data from the US Social Security Administration and the Energy Information Administration, our research team calculated a correlation coefficient of 0.9652795 and p < 0.01 for the time period spanning 1990 to 2021. While the relationship between personal nomenclature and renewable energy production may seem frivolous, our findings suggest otherwise. This study provides insightful and, dare we say, "punderful" analysis into the hitherto unexplored realm of the impact of names on sustainable energy outcomes.

[[INTRODUCTION]]
The influence of personal names on various aspects of individual and societal lives has been of interest to researchers across disciplines. While the scholarly community has delved into the implications of names on career prospects, academic achievement, and even interpersonal relationships, the connection between names and renewable energy production has been largely unexplored. This study seeks to fill this punny gap in the literature by examining the relationship between the popularity of the first name "Eva" and the generation of biomass power in Hungary.
The choice of the name "Eva" is not arbitrary, as it reflects a broader interest in the potential impact of names with a delightful twist – bear with us on this journey. The juxtaposition of a personal moniker with the disciplined realm of biomass power generation may raise a few eyebrows, but as we dove into the data, the correlation coefficients emerged with a surprising clarity and statistical significance – much like a punchline that unexpectedly lands with impeccable timing.
The title of this research paper endeavors to embody the lightheartedness that underpins this investigation. The term "Eva-luating" offers a whimsical play-on-words, inviting readers to approach the study with an open mind and a penchant for charming wordplay. The use of "pun" in the abstract, albeit mildly audacious, sets the tone for the levity and amusement that we hope will accompany the rigorous analysis presented in the subsequent sections.
Throughout this paper, we aim to strike a balance between the gravitas of academic inquiry and the jocularity that can be found in the unexpectedly delightful connections within our complex world. The investigation presented herein demonstrates that sometimes, the most amusing of correlations can uncover insights of genuine significance, and the intertwining of nomenclature and renewable energy production may yet reveal some surprising truths. withObjective scrutiny and perhaps a touch of silliness, we hereby embark on the exploration of Eva's impact on the biomass power landscape of Hungary.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The data used in this research was collected from the US Social Security Administration and the Energy Information Administration, covering the years 1990 to 2021. The first step involved extracting the frequency of the first name "Eva" from the US Social Security Administration's historical data. This data was then cross-referenced with the records of biomass power generation in Hungary obtained from the Energy Information Administration.

To ensure the reliability of the findings, a series of unorthodox techniques were utilized. The initial stage involved employing a "name-to-energy" algorithm that quantified the potential energetic impact of various names, including "Eva." This algorithm utilized linguistic structures, phonetic resonance, and cultural connotations to establish a name's probable influence on renewable energy output. While the use of such unconventional algorithms may seem peculiar, the aim was to capture the nuanced layers of connection that traditional statistical models might overlook.

Subsequently, a cross-temporal analysis, aptly named "The Chrono-Nomenclatural Energy Comparison," was devised to disentangle the temporal dynamics of Eva's popularity and biomass power generation in Hungary. This involved plotting Eva's frequency against the biomass power output across different time periods, taking into account historical and socio-cultural shifts that might impact both nomenclature trends and energy infrastructure development.

The computational analysis was supplemented by qualitative inquiries into the cultural symbolism and potential metaphysical resonance of the name "Eva" among Hungarian individuals involved in biomass power production. This included semi-structured interviews and participant observations to capture the nuanced socio-cultural implications that statistical parameters might not fully encapsulate.

The data thus obtained was then subjected to rigorous statistical analysis utilizing traditional correlation coefficients and regression models, accounting for potential confounding variables such as economic fluctuations, legislative changes, and renewable energy investment. The precision and robustness of the model were then stress-tested through extensive sensitivity analyses and Monte Carlo simulations, ensuring that the findings were not mere artifacts of the statistical procedure.

The culmination of these methodological approaches enabled the establishment of a credible and comprehensive assessment of the relationship between the popularity of the name "Eva" and the generation of biomass power in Hungary. The dissemination of results will undoubtedly illuminate the discourse in both the fields of onomastics and renewable energy, offering a thoughtful blend of insights and entertainment.

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 results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

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

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Energy Information Administration .

For the time period 1990 to 2021, you found a correlation 0.9652795, r-squared of 0.9317646, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"Eva-luating Eva's Impact: The Biomass Power of Punny Names in Hungary"

[[ABSTRACT]]
This paper assesses the unexpected connection between the popularity of the first name "Eva" and the generation of biomass power in Hungary. Drawing on data from the US Social Security Administration and the Energy Information Administration, our research team calculated a correlation coefficient of 0.9652795 and p < 0.01 for the time period spanning 1990 to 2021. While the relationship between personal nomenclature and renewable energy production may seem frivolous, our findings suggest otherwise. This study provides insightful and, dare we say, "punderful" analysis into the hitherto unexplored realm of the impact of names on sustainable energy outcomes.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The influence of personal names on various aspects of individual and societal lives has been of interest to researchers across disciplines. While the scholarly community has delved into the implications of names on career prospects, academic achievement, and even interpersonal relationships, the connection between names and renewable energy production has been largely unexplored. This study seeks to fill this punny gap in the literature by examining the relationship between the popularity of the first name "Eva" and the generation of biomass power in Hungary.
The choice of the name "Eva" is not arbitrary, as it reflects a broader interest in the potential impact of names with a delightful twist – bear with us on this journey. The juxtaposition of a personal moniker with the disciplined realm of biomass power generation may raise a few eyebrows, but as we dove into the data, the correlation coefficients emerged with a surprising clarity and statistical significance – much like a punchline that unexpectedly lands with impeccable timing.
The title of this research paper endeavors to embody the lightheartedness that underpins this investigation. The term "Eva-luating" offers a whimsical play-on-words, inviting readers to approach the study with an open mind and a penchant for charming wordplay. The use of "pun" in the abstract, albeit mildly audacious, sets the tone for the levity and amusement that we hope will accompany the rigorous analysis presented in the subsequent sections.
Throughout this paper, we aim to strike a balance between the gravitas of academic inquiry and the jocularity that can be found in the unexpectedly delightful connections within our complex world. The investigation presented herein demonstrates that sometimes, the most amusing of correlations can uncover insights of genuine significance, and the intertwining of nomenclature and renewable energy production may yet reveal some surprising truths. withObjective scrutiny and perhaps a touch of silliness, we hereby embark on the exploration of Eva's impact on the biomass power landscape of Hungary.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of the data revealed a remarkably strong positive correlation between the popularity of the first name "Eva" and the generation of biomass power in Hungary. The correlation coefficient of 0.9652795 indicated an exceptionally robust association, signifying that as the frequency of the name "Eva" increased, so did the production of biomass power. This relationship was further supported by an r-squared value of 0.9317646, indicating that approximately 93.18% of the variance in biomass power generation could be explained by the prevalence of the name "Eva." The statistical significance of the correlation was confirmed with a p-value of less than 0.01, providing compelling evidence to support the observed connection.

The scatterplot (Fig. 1) visually depicts the striking correlation between the two variables, illustrating a trend that is as clear as a well-delivered punchline. The upward trajectory of the data points conveys the steady increase in biomass power generation concurrent with the rising frequency of the name "Eva," leaving little room for doubt regarding the strength of this relationship. The data points themselves seem almost eager to align, as if each one is saying, "Eva-ry step of the way, I've got your back, biomass power!"

These findings bring to light the potential impact of seemingly unrelated factors on renewable energy outcomes. The unexpected entwining of personal nomenclature and sustainable energy production in Hungary invites a moment of reflection on the whimsical interconnectedness of the world. This study underscores the notion that even in the realm of empirical inquiry, there exists space for playful contemplation and recognition of the delightful surprises that emerge from rigorous analysis.

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 Eva and Biomass power generated in Hungary. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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]]
"Eva-luating Eva's Impact: The Biomass Power of Punny Names in Hungary"

[[ABSTRACT]]
This paper assesses the unexpected connection between the popularity of the first name "Eva" and the generation of biomass power in Hungary. Drawing on data from the US Social Security Administration and the Energy Information Administration, our research team calculated a correlation coefficient of 0.9652795 and p < 0.01 for the time period spanning 1990 to 2021. While the relationship between personal nomenclature and renewable energy production may seem frivolous, our findings suggest otherwise. This study provides insightful and, dare we say, "punderful" analysis into the hitherto unexplored realm of the impact of names on sustainable energy outcomes.

[[LITERATURE REVIEW]]
To fully comprehend the unexpected connection between the popularity of the first name "Eva" and the biomass power generated in Hungary, it is imperative to explore the existing literature on the subject, however scant it may be.
Smith and Doe (2015) investigated the effects of personal names on societal outcomes, albeit with no specific reference to renewable energy production or Hungarian naming conventions. Their work provided a valuable foundation for understanding the potential implications of nomenclature on broader phenomena, but fell short of delving into the realm of sustainable energy generation.
In the similarly titled "The Power of Names" (Jones, 2018), the author researched the impact of names on individual perceptions, attributions, and behavioral tendencies. While the book did not venture into the domain of biomass power production, its findings on the subconscious influences of names laid the groundwork for our investigation.
Expanding beyond conventional academic literature, "The Name Book" (Johnson, 2007) offered a comprehensive compilation of names and their purported meanings. While not a scholarly work per se, the book provided insight into the historical and cultural significance attributed to names, forming a contextual backdrop for our exploration.
Turning to the realm of fiction, "Naming Jack the Ripper" (Skinner, 2014) presented a speculative foray into the potential significance of names in infamous historical contexts. While a work of historical fiction, the book prompted considerations of the broader implications of names in shaping narratives and perceptions, thereby indirectly contributing to the foundational rationale for our study.
In a daring departure from traditional academic sources, the researchers also conducted a thorough review of the labels on various household items, including but not limited to condiment bottles, cereal boxes, and shampoo containers. While the findings from this unconventional source cannot be directly cited for academic purposes, the tongue-in-cheek mentions of "Eva" on some product packaging served to inspire alternate perspectives on the potential ubiquity of the name and its subtle yet impactful presence in everyday life.
Conclusively, the literature review presents a comprehensive yet lighthearted overview of the contextual underpinnings that have shaped the investigation into the correlation between the name "Eva" and biomass power generation in Hungary.

[[RESULTS]]
The analysis of the data revealed a remarkably strong positive correlation between the popularity of the first name "Eva" and the generation of biomass power in Hungary. The correlation coefficient of 0.9652795 indicated an exceptionally robust association, signifying that as the frequency of the name "Eva" increased, so did the production of biomass power. This relationship was further supported by an r-squared value of 0.9317646, indicating that approximately 93.18% of the variance in biomass power generation could be explained by the prevalence of the name "Eva." The statistical significance of the correlation was confirmed with a p-value of less than 0.01, providing compelling evidence to support the observed connection.
The scatterplot (Fig. 1) visually depicts the striking correlation between the two variables, illustrating a trend that is as clear as a well-delivered punchline. The upward trajectory of the data points conveys the steady increase in biomass power generation concurrent with the rising frequency of the name "Eva," leaving little room for doubt regarding the strength of this relationship. The data points themselves seem almost eager to align, as if each one is saying, "Eva-ry step of the way, I've got your back, biomass power!"
These findings bring to light the potential impact of seemingly unrelated factors on renewable energy outcomes. The unexpected entwining of personal nomenclature and sustainable energy production in Hungary invites a moment of reflection on the whimsical interconnectedness of the world. This study underscores the notion that even in the realm of empirical inquiry, there exists space for playful contemplation and recognition of the delightful surprises that emerge from rigorous analysis.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The robust correlation identified between the popularity of the first name "Eva" and the generation of biomass power in Hungary substantiates earlier, seemingly whimsical speculations regarding the potential impact of nomenclature on renewable energy outcomes. Our findings align with Smith and Doe's (2015) exploration of the effects of personal names on societal outcomes, albeit in a more literal and tangible context than previously considered. Furthermore, the unexpectedly strong association resonates with the underlying premise of "The Name Book" (Johnson, 2007), hinting at the historical and cultural significance attributed to names and their potential influence on societal trends. In an intriguing twist, our results seem to validate some of the speculative considerations presented in Skinner's (2014) "Naming Jack the Ripper," as the prominence of the name "Eva" does indeed appear to exert a tangible influence on a societal trend, albeit one of sustainable energy generation rather than historical notoriety.

The scatterplot visualization of the correlation depicts a trend that is as clear as a well-timed jest. The alignment of the data points seems almost choreographed, conveying a sense of harmony and cooperative spirit that evokes a playful analogy to the supportive nature of the name "Eva." This unexpected synergy between personal nomenclature and sustainable energy production in Hungary serves as a lighthearted yet compelling reminder of the whimsical interconnectedness of the world – a reminder that even in the realm of empirical inquiry, there exists room for delightful surprises and potential hidden humor.

In conclusion, the study presents a "punderful" analysis of the unanticipated relationship between the popularity of the name "Eva" and the generation of biomass power in Hungary, shedding light on the potential impact of seemingly unrelated factors on renewable energy outcomes. These results prompt a consideration of the wry yet significant role of personal names in shaping societal phenomena – a role that warrants further exploration and "Eva"-luative research.

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 Eva and Biomass power generated in Hungary. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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]]
"Eva-luating Eva's Impact: The Biomass Power of Punny Names in Hungary"

[[ABSTRACT]]
This paper assesses the unexpected connection between the popularity of the first name "Eva" and the generation of biomass power in Hungary. Drawing on data from the US Social Security Administration and the Energy Information Administration, our research team calculated a correlation coefficient of 0.9652795 and p < 0.01 for the time period spanning 1990 to 2021. While the relationship between personal nomenclature and renewable energy production may seem frivolous, our findings suggest otherwise. This study provides insightful and, dare we say, "punderful" analysis into the hitherto unexplored realm of the impact of names on sustainable energy outcomes.

[[INTRDUCTION]]
The influence of personal names on various aspects of individual and societal lives has been of interest to researchers across disciplines. While the scholarly community has delved into the implications of names on career prospects, academic achievement, and even interpersonal relationships, the connection between names and renewable energy production has been largely unexplored. This study seeks to fill this punny gap in the literature by examining the relationship between the popularity of the first name "Eva" and the generation of biomass power in Hungary.
The choice of the name "Eva" is not arbitrary, as it reflects a broader interest in the potential impact of names with a delightful twist – bear with us on this journey. The juxtaposition of a personal moniker with the disciplined realm of biomass power generation may raise a few eyebrows, but as we dove into the data, the correlation coefficients emerged with a surprising clarity and statistical significance – much like a punchline that unexpectedly lands with impeccable timing.
The title of this research paper endeavors to embody the lightheartedness that underpins this investigation. The term "Eva-luating" offers a whimsical play-on-words, inviting readers to approach the study with an open mind and a penchant for charming wordplay. The use of "pun" in the abstract, albeit mildly audacious, sets the tone for the levity and amusement that we hope will accompany the rigorous analysis presented in the subsequent sections.
Throughout this paper, we aim to strike a balance between the gravitas of academic inquiry and the jocularity that can be found in the unexpectedly delightful connections within our complex world. The investigation presented herein demonstrates that sometimes, the most amusing of correlations can uncover insights of genuine significance, and the intertwining of nomenclature and renewable energy production may yet reveal some surprising truths. withObjective scrutiny and perhaps a touch of silliness, we hereby embark on the exploration of Eva's impact on the biomass power landscape of Hungary.

[[RESULTS]]
The analysis of the data revealed a remarkably strong positive correlation between the popularity of the first name "Eva" and the generation of biomass power in Hungary. The correlation coefficient of 0.9652795 indicated an exceptionally robust association, signifying that as the frequency of the name "Eva" increased, so did the production of biomass power. This relationship was further supported by an r-squared value of 0.9317646, indicating that approximately 93.18% of the variance in biomass power generation could be explained by the prevalence of the name "Eva." The statistical significance of the correlation was confirmed with a p-value of less than 0.01, providing compelling evidence to support the observed connection.
The scatterplot (Fig. 1) visually depicts the striking correlation between the two variables, illustrating a trend that is as clear as a well-delivered punchline. The upward trajectory of the data points conveys the steady increase in biomass power generation concurrent with the rising frequency of the name "Eva," leaving little room for doubt regarding the strength of this relationship. The data points themselves seem almost eager to align, as if each one is saying, "Eva-ry step of the way, I've got your back, biomass power!"
These findings bring to light the potential impact of seemingly unrelated factors on renewable energy outcomes. The unexpected entwining of personal nomenclature and sustainable energy production in Hungary invites a moment of reflection on the whimsical interconnectedness of the world. This study underscores the notion that even in the realm of empirical inquiry, there exists space for playful contemplation and recognition of the delightful surprises that emerge from rigorous analysis.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the research has provided compelling evidence for the correlation between the popularity of the first name "Eva" and the generation of biomass power in Hungary. The remarkably strong positive correlation coefficient of 0.9652795 not only suggests a link between personal nomenclature and renewable energy production but also highlights the potential impact of seemingly whimsical factors on sustainable outcomes. It appears that "Eva-ry rose has its biomass" in Hungary, with the data points aligning in a way that might make even the most dispassionate observer crack a smile.

While the findings of this study may initially seem like a deviation from traditional research inquiries, they serve as a reminder of the pervasive interconnectedness of the world. The unexpected link between a name and renewable energy generation encourages a lighthearted reflection on the serendipitous nature of empirical discoveries. After all, who would have thought that the oscillations in biomass power could be tied to the ebb and flow of a particular name?

Nevertheless, further research in this area may not yield substantial additional insights. Therefore, we propose to conclude that the relationship between the popularity of the name "Eva" and biomass power generation in Hungary has been sufficiently, and dare we say delightfully, illuminated. No more research is needed in this name-y field.

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 Eva-luating Eva's Impact: The Biomass Power of Punny Names in Hungary. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of LOL-nomics

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 Eva-luating Eva's Impact: The Biomass Power of Punny Names in Hungary. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Research on Humorous Biomass Applications

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 Eva-luating Eva's Impact: The Biomass Power of Punny Names in Hungary with an abstract of This paper assesses the unexpected connection between the popularity of the first name "Eva" and the generation of biomass power in Hungary. Drawing on data from the US Social Security Administration and the Energy Information Administration, our research team calculated a correlation coefficient of 0.9652795 and p < 0.01 for the time period spanning 1990 to 2021. While the relationship between personal nomenclature and renewable energy production may seem frivolous, our findings suggest otherwise. This study provides insightful and, dare we say, "punderful" analysis into the hitherto unexplored realm of the impact of names on sustainable energy outcomes.

ChatGPT:

Eva, biomass power, punny names, Hungary, correlation coefficient, renewable energy production, US Social Security Administration, Energy Information Administration, sustainable energy outcomes, personal nomenclature, research analysis

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

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Data details

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

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

Correlation r = 0.9652795 (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 = 0.9317646 (Coefficient of determination)
This means 93.2% of the change in the one variable (i.e., Biomass power generated in Hungary) is predictable based on the change in the other (i.e., Popularity of the first name Eva) over the 32 years from 1990 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.8E-19.^Show 0.0000000000000000004833593016
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 0.97 in 4.8E-17% of random cases. Said differently, if you correlated 2,068,854,362,975,602,176 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 31 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 31 because we have two variables measured over a period of 32 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.

[ 0.93, 0.98 ] 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.

	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 Eva (Babies born)	788	825	772	735	769	752	795	766	846	975	1093	1160	1334	1518	1738	2475	2789	2897	2970	3394	3278	3468	3368	3439	3690	3774	3814	3648	3563	3174	2843	2827
Biomass power generated in Hungary (Billion kWh)	0.034	0.048	0.091	0.077	0.09	0.103	0.091	0.095	0.112	0.12	0.12	0.126	0.071	0.194	0.751	1.73	1.396	1.709	2.052	2.452	2.449	1.994	1.773	1.933	2.244	2.302	2.283	2.356	2.518	2.472	2.393	2.233

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.

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([788,825,772,735,769,752,795,766,846,975,1093,1160,1334,1518,1738,2475,2789,2897,2970,3394,3278,3468,3368,3439,3690,3774,3814,3648,3563,3174,2843,2827,])
array_2 = np.array([0.034,0.048,0.091,0.077,0.09,0.103,0.091,0.095,0.112,0.12,0.12,0.126,0.071,0.194,0.751,1.73,1.396,1.709,2.052,2.452,2.449,1.994,1.773,1.933,2.244,2.302,2.283,2.356,2.518,2.472,2.393,2.233,])
array_1_name = "Popularity of the first name Eva"
array_2_name = "Biomass power generated in Hungary"

# 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 Eva
Line chart for only Biomass power generated in Hungary
AI-generated correlation image
The spurious research paper: Eva-luating Eva's Impact: The Biomass Power of Punny Names in Hungary

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Correlation ID: 3036 · Black Variable ID: 2647 · Red Variable ID: 23730


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