Spurious correlation #3,022 · 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 Violet and the second variable is Fossil fuel use in Equatorial Guinea. 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 Violet and the second variable is Fossil fuel use in Equatorial Guinea. The chart goes from 1980 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As more and more people were named Violet, the demand for violet-colored cars skyrocketed. This led to a global shortage of violet automotive paint, prompting intensified drilling for the rare violet fossil fuel in Equatorial Guinea. Remember, when it comes to naming trends, the fuel-ty's the limit!

^{Show image generation prompt} Model: dalle-3
Prompt: [ A photo-realistic image ] of a vibrant garden filled with lush violet flowers, each bloom exuding a mesmerizing brilliance. Delicate petals dance in the gentle breeze, forging a mesmerizing tapestry of purples and blues. Cast against this serene backdrop, a line of idling cars stand, emitting dark plumes of fossil fuel smoke that melds with the air. People can be seen attempting to fuel their vehicles with flower petals, highlighting the collision between nature and technology. This striking scene portrays the duality of the growing popularity of the name Violet and the consequential increase in fossil fuel use in Equatorial Guinea. 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 Violet and Fossil fuel use in Equatorial Guinea. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: A photo-realistic image Hyper-realistic A scene from Skyrim Cute 2D animation Scalar art
ChatGPT: A photo-realistic image

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 Violet and Fossil fuel use in Equatorial Guinea, in the following situation: Because as the name Violet gained popularity, more people wanted to live sustaina-"billy," leading to an increase in Equatorial Guinea's fossil fuel use. People thought they could "Violet" the laws of physics and "fuel" their cars with flower power, but it just "fueled" more environmentally unfriendly behavior. It's a "petrol" shame, really.. Keep the description simple.
ChatGPT: Picture a vibrant garden filled with beautiful violet flowers, symbolizing the growing popularity of the name Violet. In the background, there are a line of cars idling, emitting dark plumes of fossil fuel smoke as people try to fuel their vehicles with flower petals, signifying the increase in fossil fuel use in Equatorial Guinea. The juxtaposition of the serene garden and the polluting cars represent the ironic effect of the name's popularity on environmental behavior.

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 photo-realistic image ] and depicting this scene: Picture a vibrant garden filled with beautiful violet flowers, symbolizing the growing popularity of the name Violet. In the background, there are a line of cars idling, emitting dark plumes of fossil fuel smoke as people try to fuel their vehicles with flower petals, signifying the increase in fossil fuel use in Equatorial Guinea. The juxtaposition of the serene garden and the polluting cars represent the ironic effect of the name's popularity on environmental behavior. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A photo-realistic image ] of a vibrant garden filled with lush violet flowers, each bloom exuding a mesmerizing brilliance. Delicate petals dance in the gentle breeze, forging a mesmerizing tapestry of purples and blues. Cast against this serene backdrop, a line of idling cars stand, emitting dark plumes of fossil fuel smoke that melds with the air. People can be seen attempting to fuel their vehicles with flower petals, highlighting the collision between nature and technology. This striking scene portrays the duality of the growing popularity of the name Violet and the consequential increase in fossil fuel use in Equatorial Guinea.

*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 Violet caused Fossil fuel use in Equatorial Guinea to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)

Violet's Vortex: A Correlative Analysis of the Name Popularity and Fossil Fuel Use in Equatorial Guinea

Journal of Quirky Quandaries

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 Violet and Fossil fuel use in Equatorial Guinea. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.

Here is the title and abstract of the paper:
[[TITLE]]
Violet's Vortex: A Correlative Analysis of the Name Popularity and Fossil Fuel Use in Equatorial Guinea

[[ABSTRACT]]
The present study delves into the intriguing relationship between the popularity of the first name Violet and the consumption of fossil fuels in Equatorial Guinea. Leveraging data from the US Social Security Administration and the Energy Information Administration, our research team embarked on a statistical voyage to unravel this unconventional connection. A correlation coefficient of 0.9951033 and p < 0.01 were unearthed from the years 1980 to 2021, suggesting a remarkably strong association between the two variables.

Drawing from the rich vein of our findings, it appears that as the first name Violet gained increasing favor, there was a parallel surge in the utilization of fossil fuels in Equatorial Guinea. This unanticipated link raises intriguing questions about the underlying mechanisms at play and invites further investigation into the symbolic and tangible impact of moniker trends on energy consumption.

In conclusion, this research not only sheds light on the peculiarity of human behavior and nomenclature but also offers a compelling demonstration of the unforeseen connections that lurk beneath the surface of seemingly disparate phenomena. As the saying goes, "There's more to a name than meets the eye, just as there's more to fossil fuel use than meets the exhaust pipe."

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The discourse surrounding the impact of names on individual lives and broader societal trends often elicits a chuckle or two, but rarely does it veer into the realm of fossil fuel usage. Yet, here we are, embarking on a scholarly expedition into the curious case of the name Violet and its curious correlation with the consumption of fossil fuels in Equatorial Guinea.
As we delve into this unexpected link, one can't help but ponder: what do fossils have to do with a flower name? It seems the answer lies beneath the surface, much like those fossil fuels themselves. It is a mystery worth exploring, as any good detective - or pun enthusiast - would appreciate.
The research at hand aims to unravel this enigma by employing rigorous statistical analyses to scrutinize the trends of name popularity and energy consumption. The question lingers like an unfinished punchline: could the first name Violet be more than just a charming moniker, and instead serve as a silent influencer of energy dynamics? It's a notion that tickles the imagination, much like a dad joke at a family gathering.
By scrutinizing data from the US Social Security Administration and the Energy Information Administration, we have unraveled a compelling association between the surge in the usage of the name Violet and the parallel spike in fossil fuel consumption in Equatorial Guinea. This finding, like a well-timed punchline, invites fascination and prompts further inquiry into the unfamiliar domain at the intersection of nomenclature and energy utilization.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Members of academia have long been intrigued by the impact of names on various facets of human existence. Smith and Doe (2010) conducted a study exploring the psychological implications of individuals' names, while Jones (2015) delved into the social and cultural connotations associated with specific monikers. Despite the prevailing seriousness of such academic pursuits, the theoretical framework encompassing the connection between the popularity of a first name and fossil fuel use in Equatorial Guinea had largely eluded scholarly attention until now.

Speaking of eluding, one might say that the link between names and fuel usage has been a bit like a stealthy fossil, waiting to be unearthed. It's almost as if it's been fossil-fueling its own mystery, if you will.

Drawing from the realm of non-fiction literature, "The Namesake" by Jhumpa Lahiri (2003) and "Freakonomics" by Steven D. Levitt and Stephen J. Dubner (2005) provide valuable insights into the influence of names on individuals and societies. In a parallel fashion, "The Hunger Games" series by Suzanne Collins (2008-2010) and "The Girl with the Dragon Tattoo" by Stieg Larsson (2005) offer narratives that touch upon the unsuspected interconnectedness of seemingly disparate elements.

However, it is worth noting that the authors of this paper expanded their literature review beyond traditional sources. In addition to scholarly articles and acclaimed literary works, an unconventional approach involving the scrutiny of CVS receipts and fortune cookies was undertaken. Although nontraditional, this multipronged approach wielded valuable perspectives that significantly informed the research findings.

It's safe to say that this topic has been so under-researched, it's practically a fossilized treasure waiting to be discovered. Who knew the journey to understanding names and fuel usage could be so enlightening and pun-derful?

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 Violet and Fossil fuel use in Equatorial Guinea. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
Violet's Vortex: A Correlative Analysis of the Name Popularity and Fossil Fuel Use in Equatorial Guinea

[[ABSTRACT]]
The present study delves into the intriguing relationship between the popularity of the first name Violet and the consumption of fossil fuels in Equatorial Guinea. Leveraging data from the US Social Security Administration and the Energy Information Administration, our research team embarked on a statistical voyage to unravel this unconventional connection. A correlation coefficient of 0.9951033 and p < 0.01 were unearthed from the years 1980 to 2021, suggesting a remarkably strong association between the two variables.

Drawing from the rich vein of our findings, it appears that as the first name Violet gained increasing favor, there was a parallel surge in the utilization of fossil fuels in Equatorial Guinea. This unanticipated link raises intriguing questions about the underlying mechanisms at play and invites further investigation into the symbolic and tangible impact of moniker trends on energy consumption.

In conclusion, this research not only sheds light on the peculiarity of human behavior and nomenclature but also offers a compelling demonstration of the unforeseen connections that lurk beneath the surface of seemingly disparate phenomena. As the saying goes, "There's more to a name than meets the eye, just as there's more to fossil fuel use than meets the exhaust pipe."

[[INTRODUCTION]]
The discourse surrounding the impact of names on individual lives and broader societal trends often elicits a chuckle or two, but rarely does it veer into the realm of fossil fuel usage. Yet, here we are, embarking on a scholarly expedition into the curious case of the name Violet and its curious correlation with the consumption of fossil fuels in Equatorial Guinea.
As we delve into this unexpected link, one can't help but ponder: what do fossils have to do with a flower name? It seems the answer lies beneath the surface, much like those fossil fuels themselves. It is a mystery worth exploring, as any good detective - or pun enthusiast - would appreciate.
The research at hand aims to unravel this enigma by employing rigorous statistical analyses to scrutinize the trends of name popularity and energy consumption. The question lingers like an unfinished punchline: could the first name Violet be more than just a charming moniker, and instead serve as a silent influencer of energy dynamics? It's a notion that tickles the imagination, much like a dad joke at a family gathering.
By scrutinizing data from the US Social Security Administration and the Energy Information Administration, we have unraveled a compelling association between the surge in the usage of the name Violet and the parallel spike in fossil fuel consumption in Equatorial Guinea. This finding, like a well-timed punchline, invites fascination and prompts further inquiry into the unfamiliar domain at the intersection of nomenclature and energy utilization.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To embark on our empirical exploration into the intriguing intersection of name popularity and fossil fuel consumption, a multi-faceted and robust methodological approach was employed. First, the data on the frequency of the first name Violet was obtained from the US Social Security Administration's records, which provided insight into the temporal trends of this floral appellation. The data, spanning from 1980 to 2021, unveiled the waxing and waning popularity of the name, much like the blooming and withering of an actual violet.

To complement this, information on fossil fuel use in Equatorial Guinea was sourced from the Energy Information Administration, allowing for a comprehensive examination of energy consumption patterns in the region. The juxtaposition of these datasets formed the basis for our quantitative inquiry into the unexpected nexus of nomenclature and energy dynamics.

Next, a series of sophisticated statistical analyses were deployed to unravel the relationship between the popularity of the name Violet and fossil fuel consumption in Equatorial Guinea. A correlation coefficient was calculated to gauge the strength and direction of the association between these seemingly disparate variables. Much like a pun in scholarly text, the correlation coefficient served as the punchline, pointing to the unexpected twist in the story of name popularity and energy consumption.

Furthermore, a regression analysis was conducted to identify potential predictors of fossil fuel use in Equatorial Guinea, with the frequency of the name Violet as a focal independent variable. This analytical strategy allowed for the examination of how variations in the popularity of the name Violet may contribute to fluctuations in fossil fuel consumption, shedding light on the underlying mechanisms of this unanticipated linkage.

Lastly, to mitigate the potential influence of confounding factors, a sensitivity analysis was performed to ascertain the robustness of the observed association between the first name Violet and fossil fuel use in Equatorial Guinea. This methodological precaution ensured that our findings were not merely a result of statistical happenstance, but rather a genuine reflection of the intriguing interplay between naming trends and energy utilization.

In the spirit of unexpected connections, our methodological design sought to untangle the curious correlation between the name Violet and fossil fuel use in Equatorial Guinea, illuminating the intertwining pathways of nomenclature and energy dynamics. As we navigate this peculiar terrain, we are reminded of the wise words of Shakespeare: "What's in a name? That which we call a rose by any other name would smell as sweet, but would it still fuel our vehicles?"

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 Violet and Fossil fuel use in Equatorial Guinea. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
Violet's Vortex: A Correlative Analysis of the Name Popularity and Fossil Fuel Use in Equatorial Guinea

[[ABSTRACT]]
The present study delves into the intriguing relationship between the popularity of the first name Violet and the consumption of fossil fuels in Equatorial Guinea. Leveraging data from the US Social Security Administration and the Energy Information Administration, our research team embarked on a statistical voyage to unravel this unconventional connection. A correlation coefficient of 0.9951033 and p < 0.01 were unearthed from the years 1980 to 2021, suggesting a remarkably strong association between the two variables.

Drawing from the rich vein of our findings, it appears that as the first name Violet gained increasing favor, there was a parallel surge in the utilization of fossil fuels in Equatorial Guinea. This unanticipated link raises intriguing questions about the underlying mechanisms at play and invites further investigation into the symbolic and tangible impact of moniker trends on energy consumption.

In conclusion, this research not only sheds light on the peculiarity of human behavior and nomenclature but also offers a compelling demonstration of the unforeseen connections that lurk beneath the surface of seemingly disparate phenomena. As the saying goes, "There's more to a name than meets the eye, just as there's more to fossil fuel use than meets the exhaust pipe."

[[LITERATURE REVIEW]]
Members of academia have long been intrigued by the impact of names on various facets of human existence. Smith and Doe (2010) conducted a study exploring the psychological implications of individuals' names, while Jones (2015) delved into the social and cultural connotations associated with specific monikers. Despite the prevailing seriousness of such academic pursuits, the theoretical framework encompassing the connection between the popularity of a first name and fossil fuel use in Equatorial Guinea had largely eluded scholarly attention until now.
Speaking of eluding, one might say that the link between names and fuel usage has been a bit like a stealthy fossil, waiting to be unearthed. It's almost as if it's been fossil-fueling its own mystery, if you will.
Drawing from the realm of non-fiction literature, "The Namesake" by Jhumpa Lahiri (2003) and "Freakonomics" by Steven D. Levitt and Stephen J. Dubner (2005) provide valuable insights into the influence of names on individuals and societies. In a parallel fashion, "The Hunger Games" series by Suzanne Collins (2008-2010) and "The Girl with the Dragon Tattoo" by Stieg Larsson (2005) offer narratives that touch upon the unsuspected interconnectedness of seemingly disparate elements.
However, it is worth noting that the authors of this paper expanded their literature review beyond traditional sources. In addition to scholarly articles and acclaimed literary works, an unconventional approach involving the scrutiny of CVS receipts and fortune cookies was undertaken. Although nontraditional, this multipronged approach wielded valuable perspectives that significantly informed the research findings.
It's safe to say that this topic has been so under-researched, it's practically a fossilized treasure waiting to be discovered. Who knew the journey to understanding names and fuel usage could be so enlightening and pun-derful?

[[RESULTS]]
The analysis of the data revealed a striking correlation coefficient of 0.9951033, indicative of a robust relationship between the popularity of the first name Violet and fossil fuel use in Equatorial Guinea. This correlation coefficient, much like a classic dad joke, left little room for doubt about the strength of the association.
Furthermore, the r-squared value of 0.9902306 underscored the extent to which variations in the popularity of the name Violet could explain the fluctuations in fossil fuel consumption. The r-squared value, much like a well-crafted pun, neatly encapsulated the essence of the relationship in a succinct manner.
Notably, the p-value of less than 0.01 provided compelling evidence to reject the null hypothesis and confirm the existence of a significant association between the two variables. This p-value, akin to a clever wordplay, added a touch of confidence to the statistical findings.
The compelling nature of these results is visually encapsulated in Fig. 1, where a scatterplot elicits a reaction much like a well-timed dad joke. The plot vividly depicts the strong positive correlation between the popularity of the first name Violet and the consumption of fossil fuels in Equatorial Guinea, reinforcing the solidity of the statistical analyses.
In sum, this research unearths an unexpected and thought-provoking connection between the choice of a name and a country's energy consumption. As we reflect on these findings, one cannot help but appreciate the unexpected humor in the unexpected linkage, much like stumbling upon a dad joke in a research paper.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The statistical analyses unveiled an extraordinary correlation between the popularity of the first name Violet and the consumption of fossil fuels in Equatorial Guinea. These findings not only lend credence to the proposition that names hold an unforeseen influence on societal dynamics but also raise thought-provoking questions about the underlying mechanisms at play.

Our results aligned with prior research, affirming the growing body of evidence that suggests the influence of names extends beyond mere social and psychological dimensions. Smith and Doe (2010) hinted at the potential psychological implications of names, and it appears that the impact may extend to broader societal phenomena, such as energy consumption patterns, as well. This parallel between the psychological and societal impact of names can be likened to a well-orchestrated pun – seemingly disparate elements coming together in an unexpected manner.

Moreover, the present study corroborates the findings of Jones (2015), who delved into the societal and cultural connotations associated with specific monikers. Just as societal connotations of names can shape individuals' experiences, our research suggests that they may also exert an unforeseen influence on energy consumption patterns at a macro level. It is as if the impact of names on societal dynamics is akin to a hidden punchline in a joke – surprising and often overlooked, yet possessing the power to influence perceptions significantly.

In a similar vein, "Freakonomics" by Levitt and Dubner (2005) offers valuable insights into the unforeseen connections that underpin societal phenomena. Our findings underscore the unexpected interconnectedness between the popularity of a first name and a country's energy consumption patterns, akin to a punchline that catches one off guard with its unexpected relevance.

Interestingly, the unconventional sources consulted in our literature review – including CVS receipts and fortune cookies – offered unique perspectives that brought an unconventional twist to our understanding of the complex interplay between names and societal phenomena. This multidisciplinary approach, much like an unexpected dad joke in a serious conversation, yielded valuable insights that enriched the depth and breadth of our investigation.

Thus, while the linkage between the popularity of a first name and fossil fuel use in Equatorial Guinea may seem improbable at first glance, our research serves as a lighthearted yet compelling reminder of the unexpected connections that underlie seemingly distinct facets of human existence. As we continue to unravel the complexity of these intertwined variables, it is essential to approach such investigations with an open mind, recognizing that, much like a well-timed dad joke, there may be unexpected layers of meaning waiting to be discovered.

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 Violet and Fossil fuel use in Equatorial Guinea. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
Violet's Vortex: A Correlative Analysis of the Name Popularity and Fossil Fuel Use in Equatorial Guinea

[[ABSTRACT]]
The present study delves into the intriguing relationship between the popularity of the first name Violet and the consumption of fossil fuels in Equatorial Guinea. Leveraging data from the US Social Security Administration and the Energy Information Administration, our research team embarked on a statistical voyage to unravel this unconventional connection. A correlation coefficient of 0.9951033 and p < 0.01 were unearthed from the years 1980 to 2021, suggesting a remarkably strong association between the two variables.

Drawing from the rich vein of our findings, it appears that as the first name Violet gained increasing favor, there was a parallel surge in the utilization of fossil fuels in Equatorial Guinea. This unanticipated link raises intriguing questions about the underlying mechanisms at play and invites further investigation into the symbolic and tangible impact of moniker trends on energy consumption.

In conclusion, this research not only sheds light on the peculiarity of human behavior and nomenclature but also offers a compelling demonstration of the unforeseen connections that lurk beneath the surface of seemingly disparate phenomena. As the saying goes, "There's more to a name than meets the eye, just as there's more to fossil fuel use than meets the exhaust pipe."

[[INTRDUCTION]]
The discourse surrounding the impact of names on individual lives and broader societal trends often elicits a chuckle or two, but rarely does it veer into the realm of fossil fuel usage. Yet, here we are, embarking on a scholarly expedition into the curious case of the name Violet and its curious correlation with the consumption of fossil fuels in Equatorial Guinea.
As we delve into this unexpected link, one can't help but ponder: what do fossils have to do with a flower name? It seems the answer lies beneath the surface, much like those fossil fuels themselves. It is a mystery worth exploring, as any good detective - or pun enthusiast - would appreciate.
The research at hand aims to unravel this enigma by employing rigorous statistical analyses to scrutinize the trends of name popularity and energy consumption. The question lingers like an unfinished punchline: could the first name Violet be more than just a charming moniker, and instead serve as a silent influencer of energy dynamics? It's a notion that tickles the imagination, much like a dad joke at a family gathering.
By scrutinizing data from the US Social Security Administration and the Energy Information Administration, we have unraveled a compelling association between the surge in the usage of the name Violet and the parallel spike in fossil fuel consumption in Equatorial Guinea. This finding, like a well-timed punchline, invites fascination and prompts further inquiry into the unfamiliar domain at the intersection of nomenclature and energy utilization.

[[RESULTS]]
The analysis of the data revealed a striking correlation coefficient of 0.9951033, indicative of a robust relationship between the popularity of the first name Violet and fossil fuel use in Equatorial Guinea. This correlation coefficient, much like a classic dad joke, left little room for doubt about the strength of the association.
Furthermore, the r-squared value of 0.9902306 underscored the extent to which variations in the popularity of the name Violet could explain the fluctuations in fossil fuel consumption. The r-squared value, much like a well-crafted pun, neatly encapsulated the essence of the relationship in a succinct manner.
Notably, the p-value of less than 0.01 provided compelling evidence to reject the null hypothesis and confirm the existence of a significant association between the two variables. This p-value, akin to a clever wordplay, added a touch of confidence to the statistical findings.
The compelling nature of these results is visually encapsulated in Fig. 1, where a scatterplot elicits a reaction much like a well-timed dad joke. The plot vividly depicts the strong positive correlation between the popularity of the first name Violet and the consumption of fossil fuels in Equatorial Guinea, reinforcing the solidity of the statistical analyses.
In sum, this research unearths an unexpected and thought-provoking connection between the choice of a name and a country's energy consumption. As we reflect on these findings, one cannot help but appreciate the unexpected humor in the unexpected linkage, much like stumbling upon a dad joke in a research paper.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the present study has boldly ventured into the uncharted territory of the correlation between the popularity of the first name Violet and fossil fuel use in Equatorial Guinea. The robust correlation coefficient and the minuscule p-value discovered in this investigation provide compelling evidence of an unforeseen and remarkably strong connection between these seemingly unrelated variables. It seems the name Violet is not just a pretty flower, but also a potent force in the realm of energy dynamics, much like a pun that's both groan-inducing and strangely compelling at the same time.

This investigation has provided a glimpse into the unexpected influence of nomenclature on tangible societal phenomena, adding a layer of complexity to the intricate tapestry of human behavior and energy utilization. Just as a dad joke adds a touch of levity to everyday conversations, the unexpected connection between the popularity of the name Violet and fossil fuel use in Equatorial Guinea injects a sense of whimsy into the realm of statistical analyses and energy research.

While the results of this study may prompt a chuckle or two, they undeniably point to the need for further exploration into the intricate interplay between naming trends and energy dynamics. As the saying goes, "Let's not leave any stone unturned, unless it's a fossil fuel," but in this case, it seems that all the fossils and Violets have been thoroughly examined.

Therefore, it is our firm and unyielding stance that no further research is needed in this area. It's time to bid adieu to our investigations and allow these findings to bask in the spotlight, much like a perfectly-timed dad joke at a cocktail party.

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 Violet's Vortex: A Correlative Analysis of the Name Popularity and Fossil Fuel Use in Equatorial Guinea. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Quirky Quandaries

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 Violet's Vortex: A Correlative Analysis of the Name Popularity and Fossil Fuel Use in Equatorial Guinea. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Quantitative Analysis (SQQAA)

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 Violet's Vortex: A Correlative Analysis of the Name Popularity and Fossil Fuel Use in Equatorial Guinea with an abstract of The present study delves into the intriguing relationship between the popularity of the first name Violet and the consumption of fossil fuels in Equatorial Guinea. Leveraging data from the US Social Security Administration and the Energy Information Administration, our research team embarked on a statistical voyage to unravel this unconventional connection. A correlation coefficient of 0.9951033 and p < 0.01 were unearthed from the years 1980 to 2021, suggesting a remarkably strong association between the two variables.
Drawing from the rich vein of our findings, it appears that as the first name Violet gained increasing favor, there was a parallel surge in the utilization of fossil fuels in Equatorial Guinea. This unanticipated link raises intriguing questions about the underlying mechanisms at play and invites further investigation into the symbolic and tangible impact of moniker trends on energy consumption.
In conclusion, this research not only sheds light on the peculiarity of human behavior and nomenclature but also offers a compelling demonstration of the unforeseen connections that lurk beneath the surface of seemingly disparate phenomena. As the saying goes, "There's more to a name than meets the eye, just as there's more to fossil fuel use than meets the exhaust pipe.

ChatGPT:

Violet, first name popularity, fossil fuel consumption, Equatorial Guinea, correlation analysis, statistical analysis, US Social Security Administration, Energy Information Administration, moniker trends, energy consumption, symbolic impact, nomenclature, human behavior

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

Fossil fuel use in Equatorial Guinea
Detailed data title: Total fossil fuel use in Equatorial Guinea in billion kWh
Source: Energy Information Administration
See what else correlates with Fossil fuel use in Equatorial Guinea

Correlation r = 0.9951033 (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 = 0.9902306 (Coefficient of determination)
This means 99% of the change in the one variable (i.e., Fossil fuel use in Equatorial Guinea) is predictable based on the change in the other (i.e., Popularity of the first name Violet) 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 1 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.

[ 0.99, 1 ] 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 Violet (Babies born)	141	147	150	141	138	142	125	144	133	133	127	133	143	142	159	162	161	183	234	255	316	381	419	468	482	846	1268	1538	1829	2260	2574	2902	3281	3941	4199	4819	4880	4730	4830	5416	5120	5508
Fossil fuel use in Equatorial Guinea (Billion kWh)	0.015	0.013	0.012	0.01	0.013	0.015	0.014	0.015	0.015	0.015	0.015	0.015	0.016	0.016	0.016	0.017	0.017	0.017	0.018	0.018	0.08084	0.05076	0.10152	0.1128	0.15604	0.1927	0.25192	0.31396	0.40514	0.46248	0.54802	0.62228	0.665	0.706	0.706	0.832	0.927	0.895667	0.911595	0.95349	0.91929	0.978125

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([141,147,150,141,138,142,125,144,133,133,127,133,143,142,159,162,161,183,234,255,316,381,419,468,482,846,1268,1538,1829,2260,2574,2902,3281,3941,4199,4819,4880,4730,4830,5416,5120,5508,])
array_2 = np.array([0.015,0.013,0.012,0.01,0.013,0.015,0.014,0.015,0.015,0.015,0.015,0.015,0.016,0.016,0.016,0.017,0.017,0.017,0.018,0.018,0.08084,0.05076,0.10152,0.1128,0.15604,0.1927,0.25192,0.31396,0.40514,0.46248,0.54802,0.62228,0.665,0.706,0.706,0.832,0.927,0.895667,0.911595,0.95349,0.91929,0.978125,])
array_1_name = "Popularity of the first name Violet"
array_2_name = "Fossil fuel use in Equatorial Guinea"

# 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
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Line chart for only Popularity of the first name Violet
Line chart for only Fossil fuel use in Equatorial Guinea
AI-generated correlation image
The spurious research paper: Violet's Vortex: A Correlative Analysis of the Name Popularity and Fossil Fuel Use in Equatorial Guinea

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Correlation ID: 3022 · Black Variable ID: 3933 · Red Variable ID: 23650


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