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AI explanation
As the number of babies named Elijah rose, so did the demand for soy-based products. This led to a higher need for genetically modified soybeans to keep up with the sudden surge in Elijah's consuming tofu and soy milk. Remember, with great soy comes great responsibility.
Model: dalle-3
Prompt: Generate an image that resembles a scene from a heartwarming Disney movie. Capture a vibrant farmers' market in Indiana with a prominently displayed "Elijah's Choice Soybeans" sign, attracting a bustling crowd of people eagerly lining up to purchase the non-GMO variety. This should evoke a sense of community and unity as the market-goers greet each other while shopping for fresh produce. The image should be rich in colors and details, exuding a warm and friendly atmosphere. 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 Elijah and GMO use in soybeans in Indiana. 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: An image that looks like it is a scene from A Disney Movie An image that looks like it is a scene from A Disney Movie Steampunk Macabre Cutsy art illustration
ChatGPT: An image that looks like it is a scene from A Disney Movie
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 Elijah and GMO use in soybeans in Indiana together. Keep the description simple.
ChatGPT: In a bustling Indiana farmers' market, a sign reading "Elijah's Choice Soybeans" is surrounded by a crowd of people eagerly lining up to buy the non-GMO variety. The name "Elijah" is also heard frequently as people greet each other while shopping for fresh produce.
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: [ An image that looks like it is a scene from A Disney Movie ] and depicting this scene: In a bustling Indiana farmers' market, a sign reading "Elijah's Choice Soybeans" is surrounded by a crowd of people eagerly lining up to buy the non-GMO variety. The name "Elijah" is also heard frequently as people greet each other while shopping for fresh produce. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that resembles a scene from a heartwarming Disney movie. Capture a vibrant farmers' market in Indiana with a prominently displayed "Elijah's Choice Soybeans" sign, attracting a bustling crowd of people eagerly lining up to purchase the non-GMO variety. This should evoke a sense of community and unity as the market-goers greet each other while shopping for fresh produce. The image should be rich in colors and details, exuding a warm and friendly atmosphere.
*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.
I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Popularity of the first name Elijah caused GMO use in soybeans in Indiana to increase. Add a funny one-liner at the end.
AI academic paper
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The Elijah Effect: Unraveling the Soybean Saga in Indiana The Journal of Agricultural Anecdotes Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Popularity of the first name Elijah and GMO use in soybeans in Indiana. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Make the title seem clever.
Your research team used data from US Social Security Administration and USDA to assess this nagging question. You found a correlation coefficient of 0.8880183 and p < 0.01 for 2000 to 2022.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
"The Elijah Effect: Unraveling the Soybean Saga in Indiana"
[[ABSTRACT]]
In this study, we delve into the curious relationship between the popularity of the first name "Elijah" and the use of genetically modified organisms (GMOs) in soybeans within the state of Indiana. Through meticulous analysis of data from the US Social Security Administration and the United States Department of Agriculture, we have uncovered an intriguing connection between these two seemingly disparate factors. Our research has revealed a striking correlation coefficient of 0.8880183 and a statistically significant p-value of less than 0.01 for the period spanning from 2000 to 2022.
The implications of our findings are both astonishing and uproarious, as we ponder whether there is more than meets the eye to the confluence of Elijah's popularity and the cultivation of genetically modified soybeans in the heart of the Midwest. While this study raises numerous questions, we must approach the results with a tempered enthusiasm, recognizing the comical potential for spurious correlations. Our investigation into the "Elijah Effect" serves as a lighthearted reminder that, in the realm of statistics, the most unexpected relationships can germinate in the seemingly mundane fields of monikers and agriculture.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Popularity of the first name Elijah and GMO use in soybeans in Indiana. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Here is the title and abstract of the paper:
[[TITLE]]
"The Elijah Effect: Unraveling the Soybean Saga in Indiana"
[[ABSTRACT]]
In this study, we delve into the curious relationship between the popularity of the first name "Elijah" and the use of genetically modified organisms (GMOs) in soybeans within the state of Indiana. Through meticulous analysis of data from the US Social Security Administration and the United States Department of Agriculture, we have uncovered an intriguing connection between these two seemingly disparate factors. Our research has revealed a striking correlation coefficient of 0.8880183 and a statistically significant p-value of less than 0.01 for the period spanning from 2000 to 2022.
The implications of our findings are both astonishing and uproarious, as we ponder whether there is more than meets the eye to the confluence of Elijah's popularity and the cultivation of genetically modified soybeans in the heart of the Midwest. While this study raises numerous questions, we must approach the results with a tempered enthusiasm, recognizing the comical potential for spurious correlations. Our investigation into the "Elijah Effect" serves as a lighthearted reminder that, in the realm of statistics, the most unexpected relationships can germinate in the seemingly mundane fields of monikers and agriculture.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
The world of scientific inquiry often leads us down unexpected and thought-provoking paths. In this paper, we aim to illuminate the enigmatic and, dare we say, titillating connection between the prevalence of the first name "Elijah" and the proliferation of genetically modified organisms (GMOs) in soybeans, nestled within the bucolic expanse of Indiana. This intersection of nomenclature and agricultural innovation presents an intriguing conundrum for researchers and a source of bemusement for the academically inclined.
As we embark on our expedition into the Elijah Effect, we are confronted with the striking juxtaposition of the seemingly unrelated spheres of demography and agronomy. One cannot help but be both awed and tickled by the prospect of uncovering a correlation between the bevy of infants bestowed with the moniker "Elijah" and the sophisticated science of GMO soybean cultivation. Indeed, the whimsicality of this inquiry is enough to tickle the funny bone of even the most stoic statisticians.
Through meticulous curation and dissection of datasets from the US Social Security Administration and the United States Department of Agriculture, we have unfurled an astonishing narrative that underscores the interplay between human cultural trends and agricultural practices. Our statistical analysis, conducted with the rigor and precision befitting the scientific method, has unearthed a correlation coefficient of 0.8880183, leaving us marveling at the closeness of the entwined strands of Elijah's popularity and the prevalence of GMO soybeans. Such a coefficient could even provoke a wry smirk from the most austere mathematicians.
The implications of our findings are as perplexing as they are delightful, prompting us to mull over the possible undercurrents and unseen forces that may orchestrate this curious harmony between name and crop. The significance of our results, with a p-value of less than 0.01 for the period from 2000 to 2022, beckons us to consider the possibility of a genuine connection, albeit one that we approach with a healthy dose of skepticism and humor.
In essence, our exploration of the "Elijah Effect" serves as a whimsical reminder that the inscrutable dance of data and variables may occasionally veer into whimsy and waggishness. While we embrace the potential profundity of our discoveries, we also recognize the inherent charm of uncovering extraordinary correlations in the unlikeliest of places. Join us, dear reader, as we embark on this intellectual escapade of statistical drollery and agricultural peculiarity.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between Popularity of the first name Elijah and GMO use in soybeans in Indiana. 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 name some movies that you watched that are tangentially related to the topic.
Here is the title and abstract of the paper:
[[TITLE]]
"The Elijah Effect: Unraveling the Soybean Saga in Indiana"
[[ABSTRACT]]
In this study, we delve into the curious relationship between the popularity of the first name "Elijah" and the use of genetically modified organisms (GMOs) in soybeans within the state of Indiana. Through meticulous analysis of data from the US Social Security Administration and the United States Department of Agriculture, we have uncovered an intriguing connection between these two seemingly disparate factors. Our research has revealed a striking correlation coefficient of 0.8880183 and a statistically significant p-value of less than 0.01 for the period spanning from 2000 to 2022.
The implications of our findings are both astonishing and uproarious, as we ponder whether there is more than meets the eye to the confluence of Elijah's popularity and the cultivation of genetically modified soybeans in the heart of the Midwest. While this study raises numerous questions, we must approach the results with a tempered enthusiasm, recognizing the comical potential for spurious correlations. Our investigation into the "Elijah Effect" serves as a lighthearted reminder that, in the realm of statistics, the most unexpected relationships can germinate in the seemingly mundane fields of monikers and agriculture.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The world of scientific inquiry often leads us down unexpected and thought-provoking paths. In this paper, we aim to illuminate the enigmatic and, dare we say, titillating connection between the prevalence of the first name "Elijah" and the proliferation of genetically modified organisms (GMOs) in soybeans, nestled within the bucolic expanse of Indiana. This intersection of nomenclature and agricultural innovation presents an intriguing conundrum for researchers and a source of bemusement for the academically inclined.
As we embark on our expedition into the Elijah Effect, we are confronted with the striking juxtaposition of the seemingly unrelated spheres of demography and agronomy. One cannot help but be both awed and tickled by the prospect of uncovering a correlation between the bevy of infants bestowed with the moniker "Elijah" and the sophisticated science of GMO soybean cultivation. Indeed, the whimsicality of this inquiry is enough to tickle the funny bone of even the most stoic statisticians.
Through meticulous curation and dissection of datasets from the US Social Security Administration and the United States Department of Agriculture, we have unfurled an astonishing narrative that underscores the interplay between human cultural trends and agricultural practices. Our statistical analysis, conducted with the rigor and precision befitting the scientific method, has unearthed a correlation coefficient of 0.8880183, leaving us marveling at the closeness of the entwined strands of Elijah's popularity and the prevalence of GMO soybeans. Such a coefficient could even provoke a wry smirk from the most austere mathematicians.
The implications of our findings are as perplexing as they are delightful, prompting us to mull over the possible undercurrents and unseen forces that may orchestrate this curious harmony between name and crop. The significance of our results, with a p-value of less than 0.01 for the period from 2000 to 2022, beckons us to consider the possibility of a genuine connection, albeit one that we approach with a healthy dose of skepticism and humor.
In essence, our exploration of the "Elijah Effect" serves as a whimsical reminder that the inscrutable dance of data and variables may occasionally veer into whimsy and waggishness. While we embrace the potential profundity of our discoveries, we also recognize the inherent charm of uncovering extraordinary correlations in the unlikeliest of places. Join us, dear reader, as we embark on this intellectual escapade of statistical drollery and agricultural peculiarity.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
To contextualize our study on the correlation between the popularity of the first name "Elijah" and the utilization of genetically modified organisms (GMOs) in soybeans within the state of Indiana, we must acknowledge the existing body of literature on name trends, agricultural practices, and the whimsically bizarre intersections of human culture and scientific phenomena. Smith and Doe (2010) examined regional naming patterns in their seminal work, "The Dynamics of Naming: A Multidisciplinary Exploration," offering insights into the shifts in naming conventions and their potential implications on societal constructs.
Expanding on this, Jones et al. (2015) delved into the agricultural landscape in their comprehensive study, "Agricultural Innovations and Their Impact on Crop Production," providing a comprehensive analysis of technological advancements, including the advent of GMOs in soybean cultivation. Together, these foundational works provided a sturdy scaffold for our investigation into the peculiar relationship between a name's popularity and soybean genetics.
Transitioning into a more whimsical exploration, the anthology "Baby Names and Beyond: Unearthing the Mysteries of Monikers" by Monty (2018) offered a light-hearted perspective on the cultural nuances of baby naming. While Monty's work primarily focused on the societal impact of names, it subtly hinted at the potential ripple effects that name popularity could have on unexpected domains - a notion that resonates deeply with our current inquiry.
In the realm of fiction, Murakami's "Kafka on the Shore" (2002) may at first glance seem unrelated, but amidst its surreal narrative, there are undercurrents of inexplicable connections and chance encounters that parallel the serendipitous nature of our research. Similarly, Eco's "Foucault's Pendulum" (1988) weaves a complex tapestry of intellectual meanderings, offering a metaphorical reflection of the interconnectedness that we endeavor to unravel in our investigation of the "Elijah Effect."
It is also noteworthy to acknowledge the cinematic influences that have subtly shaped our perspective. The movie "Interstellar" (2014), with its exploration of interdimensional phenomena and the enigmatic forces that govern existence, serves as an allegorical mirror to the enigmatic correlations we seek to elucidate. Additionally, the whimsical and unexpectedly profound "Cloudy with a Chance of Meatballs" (2009) serves as a lighthearted reminder of the potential for extraordinary phenomena in the seemingly mundane aspects of life.
As we wade through the scholarly and fictional landscapes to situate our study in the broader context of human curiosity and scientific inquiry, we embrace the lightheartedness and absurdity of the path we have chosen. This juxtaposition of solemn scholarship and whimsical musings incites a chuckle, reminding us that in the pursuit of knowledge, there exists ample room for laughter and wonder.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between Popularity of the first name Elijah and GMO use in soybeans in Indiana. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and USDA . You used data from 2000 to 2022
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]]
"The Elijah Effect: Unraveling the Soybean Saga in Indiana"
[[ABSTRACT]]
In this study, we delve into the curious relationship between the popularity of the first name "Elijah" and the use of genetically modified organisms (GMOs) in soybeans within the state of Indiana. Through meticulous analysis of data from the US Social Security Administration and the United States Department of Agriculture, we have uncovered an intriguing connection between these two seemingly disparate factors. Our research has revealed a striking correlation coefficient of 0.8880183 and a statistically significant p-value of less than 0.01 for the period spanning from 2000 to 2022.
The implications of our findings are both astonishing and uproarious, as we ponder whether there is more than meets the eye to the confluence of Elijah's popularity and the cultivation of genetically modified soybeans in the heart of the Midwest. While this study raises numerous questions, we must approach the results with a tempered enthusiasm, recognizing the comical potential for spurious correlations. Our investigation into the "Elijah Effect" serves as a lighthearted reminder that, in the realm of statistics, the most unexpected relationships can germinate in the seemingly mundane fields of monikers and agriculture.
[[INTRODUCTION]]
The world of scientific inquiry often leads us down unexpected and thought-provoking paths. In this paper, we aim to illuminate the enigmatic and, dare we say, titillating connection between the prevalence of the first name "Elijah" and the proliferation of genetically modified organisms (GMOs) in soybeans, nestled within the bucolic expanse of Indiana. This intersection of nomenclature and agricultural innovation presents an intriguing conundrum for researchers and a source of bemusement for the academically inclined.
As we embark on our expedition into the Elijah Effect, we are confronted with the striking juxtaposition of the seemingly unrelated spheres of demography and agronomy. One cannot help but be both awed and tickled by the prospect of uncovering a correlation between the bevy of infants bestowed with the moniker "Elijah" and the sophisticated science of GMO soybean cultivation. Indeed, the whimsicality of this inquiry is enough to tickle the funny bone of even the most stoic statisticians.
Through meticulous curation and dissection of datasets from the US Social Security Administration and the United States Department of Agriculture, we have unfurled an astonishing narrative that underscores the interplay between human cultural trends and agricultural practices. Our statistical analysis, conducted with the rigor and precision befitting the scientific method, has unearthed a correlation coefficient of 0.8880183, leaving us marveling at the closeness of the entwined strands of Elijah's popularity and the prevalence of GMO soybeans. Such a coefficient could even provoke a wry smirk from the most austere mathematicians.
The implications of our findings are as perplexing as they are delightful, prompting us to mull over the possible undercurrents and unseen forces that may orchestrate this curious harmony between name and crop. The significance of our results, with a p-value of less than 0.01 for the period from 2000 to 2022, beckons us to consider the possibility of a genuine connection, albeit one that we approach with a healthy dose of skepticism and humor.
In essence, our exploration of the "Elijah Effect" serves as a whimsical reminder that the inscrutable dance of data and variables may occasionally veer into whimsy and waggishness. While we embrace the potential profundity of our discoveries, we also recognize the inherent charm of uncovering extraordinary correlations in the unlikeliest of places. Join us, dear reader, as we embark on this intellectual escapade of statistical drollery and agricultural peculiarity.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To embark on this amusing expedition of statistical bewilderment and agricultural curiosity, our research team harnessed an array of analytical methods to weave together the whimsical tapestry of data connecting the popularity of the first name "Elijah" and the prevalence of genetically modified organisms (GMOs) in soybeans across Indiana.
The primary source of our data on the popularity of the name "Elijah" sprouted from the records of the US Social Security Administration, which thankfully sowed the seeds of information essential for this peculiar research endeavor. The rich harvest of data spanning from 2000 to 2022 allowed us to plough through the statistical landscape and dig deep into the trend of Elijah’s ascendancy within the tides of nomenclature.
In tandem, the United States Department of Agriculture provided the fertile earth from which we gathered the data on the deployment of GMO soybeans within the agrarian expanse of Indiana. Their dataset, ripe with information on soybean cultivation practices, allowed us to till the soil of inquiry and delve into the nuanced landscape of agricultural innovation.
Combining these datasets, we tilled the fertile ground of statistical analysis, employing a rigorous approach to uncover the entwined roots of Elijah's popularity and the proliferation of GMO soybeans. Through the judicious application of correlation analysis and regression models, we sought to elucidate the burgeoning relationship between these seemingly incongruous variables, sowing the seeds of statistical scrutiny into the fertile soil of our data.
The correlation coefficient, a stalwart measure of the bond between our variables, was undeniably a fertile trove of information that unveiled a coefficient of 0.8880183, leaving us both amused and bemused at the unexpected robustness of this association. Furthermore, our statistical models bore fruit with a p-value of less than 0.01, indicating a statistically significant relationship that was as surprising as it was statistically sound.
In summary, our methodology harnessed the bountiful yields of data from the US Social Security Administration and the United States Department of Agriculture, cultivating a vibrant crop of statistical analysis to unveil the captivating connection between the popularity of the name "Elijah" and the prevalence of GMO soybeans in the heartland of Indiana. This methodology, much like the growth of GMO soybeans, has germinated in the fertile soil of statistical inquiry, yielding a harvest of bewildering yet uproariously delightful findings.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Popularity of the first name Elijah and GMO use in soybeans in Indiana. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and USDA .
For the time period 2000 to 2022, you found a correlation 0.8880183, r-squared of 0.7885765, 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]]
"The Elijah Effect: Unraveling the Soybean Saga in Indiana"
[[ABSTRACT]]
In this study, we delve into the curious relationship between the popularity of the first name "Elijah" and the use of genetically modified organisms (GMOs) in soybeans within the state of Indiana. Through meticulous analysis of data from the US Social Security Administration and the United States Department of Agriculture, we have uncovered an intriguing connection between these two seemingly disparate factors. Our research has revealed a striking correlation coefficient of 0.8880183 and a statistically significant p-value of less than 0.01 for the period spanning from 2000 to 2022.
The implications of our findings are both astonishing and uproarious, as we ponder whether there is more than meets the eye to the confluence of Elijah's popularity and the cultivation of genetically modified soybeans in the heart of the Midwest. While this study raises numerous questions, we must approach the results with a tempered enthusiasm, recognizing the comical potential for spurious correlations. Our investigation into the "Elijah Effect" serves as a lighthearted reminder that, in the realm of statistics, the most unexpected relationships can germinate in the seemingly mundane fields of monikers and agriculture.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
The world of scientific inquiry often leads us down unexpected and thought-provoking paths. In this paper, we aim to illuminate the enigmatic and, dare we say, titillating connection between the prevalence of the first name "Elijah" and the proliferation of genetically modified organisms (GMOs) in soybeans, nestled within the bucolic expanse of Indiana. This intersection of nomenclature and agricultural innovation presents an intriguing conundrum for researchers and a source of bemusement for the academically inclined.
As we embark on our expedition into the Elijah Effect, we are confronted with the striking juxtaposition of the seemingly unrelated spheres of demography and agronomy. One cannot help but be both awed and tickled by the prospect of uncovering a correlation between the bevy of infants bestowed with the moniker "Elijah" and the sophisticated science of GMO soybean cultivation. Indeed, the whimsicality of this inquiry is enough to tickle the funny bone of even the most stoic statisticians.
Through meticulous curation and dissection of datasets from the US Social Security Administration and the United States Department of Agriculture, we have unfurled an astonishing narrative that underscores the interplay between human cultural trends and agricultural practices. Our statistical analysis, conducted with the rigor and precision befitting the scientific method, has unearthed a correlation coefficient of 0.8880183, leaving us marveling at the closeness of the entwined strands of Elijah's popularity and the prevalence of GMO soybeans. Such a coefficient could even provoke a wry smirk from the most austere mathematicians.
The implications of our findings are as perplexing as they are delightful, prompting us to mull over the possible undercurrents and unseen forces that may orchestrate this curious harmony between name and crop. The significance of our results, with a p-value of less than 0.01 for the period from 2000 to 2022, beckons us to consider the possibility of a genuine connection, albeit one that we approach with a healthy dose of skepticism and humor.
In essence, our exploration of the "Elijah Effect" serves as a whimsical reminder that the inscrutable dance of data and variables may occasionally veer into whimsy and waggishness. While we embrace the potential profundity of our discoveries, we also recognize the inherent charm of uncovering extraordinary correlations in the unlikeliest of places. Join us, dear reader, as we embark on this intellectual escapade of statistical drollery and agricultural peculiarity.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
Our investigation into the "Elijah Effect" has illuminated a compelling relationship between the prevalence of the first name "Elijah" and the utilization of genetically modified organisms (GMOs) in soybean cultivation within the confines of Indiana. The statistical analysis of data spanning from 2000 to 2022 has uncovered a striking correlation coefficient of 0.8880183, indicative of a robust linear association between these seemingly incongruous variables. The r-squared value of 0.7885765 further underscores the strength of this correlation, while the p-value of less than 0.01 solidifies the statistical significance of our findings.
Fig. 1 showcases the scatterplot that visually captures the strong positive relationship between the popularity of the name "Elijah" and the prevalence of GMO soybeans in Indiana. The figure encapsulates the epitome of statistical humor, where the whimsical nature of correlated variables is subtly unveiled amidst the ostensibly dry data representation.
The implications of these results are as intriguing as they are entertaining, inviting us to contemplate the unforeseen interplay between human nomenclature trends and agricultural practices. As we reflect on the correlation coefficient and its significance, we are reminded of the capriciousness inherent in statistical analyses, where even the most unexpected relationships can sprout forth from the humdrum data.
While we approach our findings with academic rigor and a hint of levity, we are cognizant of the potential for spurious correlations, emphasizing the need for cautious interpretation in the realm of statistical inquiry. Our investigation provides a compelling testament to the whimsical charm of scientific pursuits and serves as a delightful divergence from the customary rigidity often associated with scholarly pursuits.
In summary, our exploration of the "Elijah Effect" offers a buoyant reminder that statistical inquiry is not devoid of whimsy and may occasionally yield results that provoke both mirth and contemplation. We eagerly anticipate further scholarly engagement with the lighthearted revelations born from this peculiar confluence of nomenclature and agricultural innovation.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Elijah and GMO use in soybeans in Indiana. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Limit your response to 500 tokens.
Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.
Do not write a conclusion. I will add a conclusion after this.
[[TITLE]]
"The Elijah Effect: Unraveling the Soybean Saga in Indiana"
[[ABSTRACT]]
In this study, we delve into the curious relationship between the popularity of the first name "Elijah" and the use of genetically modified organisms (GMOs) in soybeans within the state of Indiana. Through meticulous analysis of data from the US Social Security Administration and the United States Department of Agriculture, we have uncovered an intriguing connection between these two seemingly disparate factors. Our research has revealed a striking correlation coefficient of 0.8880183 and a statistically significant p-value of less than 0.01 for the period spanning from 2000 to 2022.
The implications of our findings are both astonishing and uproarious, as we ponder whether there is more than meets the eye to the confluence of Elijah's popularity and the cultivation of genetically modified soybeans in the heart of the Midwest. While this study raises numerous questions, we must approach the results with a tempered enthusiasm, recognizing the comical potential for spurious correlations. Our investigation into the "Elijah Effect" serves as a lighthearted reminder that, in the realm of statistics, the most unexpected relationships can germinate in the seemingly mundane fields of monikers and agriculture.
[[LITERATURE REVIEW]]
To contextualize our study on the correlation between the popularity of the first name "Elijah" and the utilization of genetically modified organisms (GMOs) in soybeans within the state of Indiana, we must acknowledge the existing body of literature on name trends, agricultural practices, and the whimsically bizarre intersections of human culture and scientific phenomena. Smith and Doe (2010) examined regional naming patterns in their seminal work, "The Dynamics of Naming: A Multidisciplinary Exploration," offering insights into the shifts in naming conventions and their potential implications on societal constructs.
Expanding on this, Jones et al. (2015) delved into the agricultural landscape in their comprehensive study, "Agricultural Innovations and Their Impact on Crop Production," providing a comprehensive analysis of technological advancements, including the advent of GMOs in soybean cultivation. Together, these foundational works provided a sturdy scaffold for our investigation into the peculiar relationship between a name's popularity and soybean genetics.
Transitioning into a more whimsical exploration, the anthology "Baby Names and Beyond: Unearthing the Mysteries of Monikers" by Monty (2018) offered a light-hearted perspective on the cultural nuances of baby naming. While Monty's work primarily focused on the societal impact of names, it subtly hinted at the potential ripple effects that name popularity could have on unexpected domains - a notion that resonates deeply with our current inquiry.
In the realm of fiction, Murakami's "Kafka on the Shore" (2002) may at first glance seem unrelated, but amidst its surreal narrative, there are undercurrents of inexplicable connections and chance encounters that parallel the serendipitous nature of our research. Similarly, Eco's "Foucault's Pendulum" (1988) weaves a complex tapestry of intellectual meanderings, offering a metaphorical reflection of the interconnectedness that we endeavor to unravel in our investigation of the "Elijah Effect."
It is also noteworthy to acknowledge the cinematic influences that have subtly shaped our perspective. The movie "Interstellar" (2014), with its exploration of interdimensional phenomena and the enigmatic forces that govern existence, serves as an allegorical mirror to the enigmatic correlations we seek to elucidate. Additionally, the whimsical and unexpectedly profound "Cloudy with a Chance of Meatballs" (2009) serves as a lighthearted reminder of the potential for extraordinary phenomena in the seemingly mundane aspects of life.
As we wade through the scholarly and fictional landscapes to situate our study in the broader context of human curiosity and scientific inquiry, we embrace the lightheartedness and absurdity of the path we have chosen. This juxtaposition of solemn scholarship and whimsical musings incites a chuckle, reminding us that in the pursuit of knowledge, there exists ample room for laughter and wonder.
[[RESULTS]]
Our investigation into the "Elijah Effect" has illuminated a compelling relationship between the prevalence of the first name "Elijah" and the utilization of genetically modified organisms (GMOs) in soybean cultivation within the confines of Indiana. The statistical analysis of data spanning from 2000 to 2022 has uncovered a striking correlation coefficient of 0.8880183, indicative of a robust linear association between these seemingly incongruous variables. The r-squared value of 0.7885765 further underscores the strength of this correlation, while the p-value of less than 0.01 solidifies the statistical significance of our findings.
Fig. 1 showcases the scatterplot that visually captures the strong positive relationship between the popularity of the name "Elijah" and the prevalence of GMO soybeans in Indiana. The figure encapsulates the epitome of statistical humor, where the whimsical nature of correlated variables is subtly unveiled amidst the ostensibly dry data representation.
The implications of these results are as intriguing as they are entertaining, inviting us to contemplate the unforeseen interplay between human nomenclature trends and agricultural practices. As we reflect on the correlation coefficient and its significance, we are reminded of the capriciousness inherent in statistical analyses, where even the most unexpected relationships can sprout forth from the humdrum data.
While we approach our findings with academic rigor and a hint of levity, we are cognizant of the potential for spurious correlations, emphasizing the need for cautious interpretation in the realm of statistical inquiry. Our investigation provides a compelling testament to the whimsical charm of scientific pursuits and serves as a delightful divergence from the customary rigidity often associated with scholarly pursuits.
In summary, our exploration of the "Elijah Effect" offers a buoyant reminder that statistical inquiry is not devoid of whimsy and may occasionally yield results that provoke both mirth and contemplation. We eagerly anticipate further scholarly engagement with the lighthearted revelations born from this peculiar confluence of nomenclature and agricultural innovation.
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Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our study has unearthed a correlation that may, at first glance, seem as mind-boggling as Schroedinger's Cat - the prevalence of the first name "Elijah" and the adoption of genetically modified organisms (GMOs) in soybean cultivation in Indiana. While this connection may appear as peculiar as a well-colored petri dish, our findings echo the sentiments of past research, infusing a touch of humor into the world of statistical analysis.
Drawing parallels to Monty's whimsical exploration of societal impacts of names, we find ourselves pondering the unforeseen ripples that name popularity may create in the agricultural landscape. The robust correlation coefficient of 0.8880183, akin to a precise titration, echoes the foundation laid by Smith and Doe in uncovering regional naming patterns, allowing us to infer a potential influence of naming trends on agricultural practices.
Our results align with the lighthearted musings evoked in "Cloudy with a Chance of Meatballs," where extraordinary phenomena unfold in the seemingly mundane. The scatterplot presented in Fig. 1, akin to a visual pun in a scientific comedy sketch, encapsulates the embodiment of statistical amusement, visually showcasing the unexpected relationship between the popularity of the name "Elijah" and the prevalence of GMO soybeans in Indiana.
The statistical significance of our findings, with a p-value of less than 0.01 and an r-squared value of 0.7885765, cannot be dismissed as a statistical fluke. However, as we navigate the comical potential for spurious correlations, we remain rooted in academic rigor, acknowledging the need for cautious interpretation amidst the whimsical nature of our results.
Amidst our lighthearted revelations, we find ourselves at the crossroads where scientific inquiry meets serendipity. The "Elijah Effect" serves as a harmonious fusion of academic investigation and jovial wonder, beckoning further exploration into the unexpected interplay between human nomenclature trends and agricultural evolution. As we bring this discussion to a close, we recognize that in the world of statistics, the most surprising relationships can germinate from the unlikeliest of origins, perpetuating the enchanting nature of scientific inquiry.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between Popularity of the first name Elijah and GMO use in soybeans in Indiana. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.
Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"The Elijah Effect: Unraveling the Soybean Saga in Indiana"
[[ABSTRACT]]
In this study, we delve into the curious relationship between the popularity of the first name "Elijah" and the use of genetically modified organisms (GMOs) in soybeans within the state of Indiana. Through meticulous analysis of data from the US Social Security Administration and the United States Department of Agriculture, we have uncovered an intriguing connection between these two seemingly disparate factors. Our research has revealed a striking correlation coefficient of 0.8880183 and a statistically significant p-value of less than 0.01 for the period spanning from 2000 to 2022.
The implications of our findings are both astonishing and uproarious, as we ponder whether there is more than meets the eye to the confluence of Elijah's popularity and the cultivation of genetically modified soybeans in the heart of the Midwest. While this study raises numerous questions, we must approach the results with a tempered enthusiasm, recognizing the comical potential for spurious correlations. Our investigation into the "Elijah Effect" serves as a lighthearted reminder that, in the realm of statistics, the most unexpected relationships can germinate in the seemingly mundane fields of monikers and agriculture.
[[INTRDUCTION]]
The world of scientific inquiry often leads us down unexpected and thought-provoking paths. In this paper, we aim to illuminate the enigmatic and, dare we say, titillating connection between the prevalence of the first name "Elijah" and the proliferation of genetically modified organisms (GMOs) in soybeans, nestled within the bucolic expanse of Indiana. This intersection of nomenclature and agricultural innovation presents an intriguing conundrum for researchers and a source of bemusement for the academically inclined.
As we embark on our expedition into the Elijah Effect, we are confronted with the striking juxtaposition of the seemingly unrelated spheres of demography and agronomy. One cannot help but be both awed and tickled by the prospect of uncovering a correlation between the bevy of infants bestowed with the moniker "Elijah" and the sophisticated science of GMO soybean cultivation. Indeed, the whimsicality of this inquiry is enough to tickle the funny bone of even the most stoic statisticians.
Through meticulous curation and dissection of datasets from the US Social Security Administration and the United States Department of Agriculture, we have unfurled an astonishing narrative that underscores the interplay between human cultural trends and agricultural practices. Our statistical analysis, conducted with the rigor and precision befitting the scientific method, has unearthed a correlation coefficient of 0.8880183, leaving us marveling at the closeness of the entwined strands of Elijah's popularity and the prevalence of GMO soybeans. Such a coefficient could even provoke a wry smirk from the most austere mathematicians.
The implications of our findings are as perplexing as they are delightful, prompting us to mull over the possible undercurrents and unseen forces that may orchestrate this curious harmony between name and crop. The significance of our results, with a p-value of less than 0.01 for the period from 2000 to 2022, beckons us to consider the possibility of a genuine connection, albeit one that we approach with a healthy dose of skepticism and humor.
In essence, our exploration of the "Elijah Effect" serves as a whimsical reminder that the inscrutable dance of data and variables may occasionally veer into whimsy and waggishness. While we embrace the potential profundity of our discoveries, we also recognize the inherent charm of uncovering extraordinary correlations in the unlikeliest of places. Join us, dear reader, as we embark on this intellectual escapade of statistical drollery and agricultural peculiarity.
[[RESULTS]]
Our investigation into the "Elijah Effect" has illuminated a compelling relationship between the prevalence of the first name "Elijah" and the utilization of genetically modified organisms (GMOs) in soybean cultivation within the confines of Indiana. The statistical analysis of data spanning from 2000 to 2022 has uncovered a striking correlation coefficient of 0.8880183, indicative of a robust linear association between these seemingly incongruous variables. The r-squared value of 0.7885765 further underscores the strength of this correlation, while the p-value of less than 0.01 solidifies the statistical significance of our findings.
Fig. 1 showcases the scatterplot that visually captures the strong positive relationship between the popularity of the name "Elijah" and the prevalence of GMO soybeans in Indiana. The figure encapsulates the epitome of statistical humor, where the whimsical nature of correlated variables is subtly unveiled amidst the ostensibly dry data representation.
The implications of these results are as intriguing as they are entertaining, inviting us to contemplate the unforeseen interplay between human nomenclature trends and agricultural practices. As we reflect on the correlation coefficient and its significance, we are reminded of the capriciousness inherent in statistical analyses, where even the most unexpected relationships can sprout forth from the humdrum data.
While we approach our findings with academic rigor and a hint of levity, we are cognizant of the potential for spurious correlations, emphasizing the need for cautious interpretation in the realm of statistical inquiry. Our investigation provides a compelling testament to the whimsical charm of scientific pursuits and serves as a delightful divergence from the customary rigidity often associated with scholarly pursuits.
In summary, our exploration of the "Elijah Effect" offers a buoyant reminder that statistical inquiry is not devoid of whimsy and may occasionally yield results that provoke both mirth and contemplation. We eagerly anticipate further scholarly engagement with the lighthearted revelations born from this peculiar confluence of nomenclature and agricultural innovation.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In closing, our research unveils a whimsically puzzling liaison between the prevalence of the name "Elijah" and the utilization of genetically modified organisms (GMOs) in Indiana's soybean cultivation. The robust correlation coefficient of 0.8880183 and the statistically significant p-value < 0.01 undoubtedly stir both academic fascination and sly amusement. The scatterplot in Fig. 1 encapsulates the giddy marriage of statistics and subtlety, where the unexpected embrace of correlated variables is unveiled amidst the seemingly unremarkable data representation.
Our study tantalizingly underscores the fertile ground within statistical inquiry for jest and playfulness, illuminating the comical potential for spurious correlations and evoking a chuckle from even the most stoic mathematicians. As we demurely part ways with this curious tryst of nomenclature and agriculture, we assert with an ounce of mirth and a smidgeon of gravity that no further inquiry is needed in this whimsical realm of statistical drollery and agricultural peculiarity.
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 The Elijah Effect: Unraveling the Soybean Saga in Indiana. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Agricultural Anecdotes
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 The Elijah Effect: Unraveling the Soybean Saga in Indiana. Respond only with the name of a fictional organization.
ChatGPT:
EcoAg Alliance
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 The Elijah Effect: Unraveling the Soybean Saga in Indiana with an abstract of In this study, we delve into the curious relationship between the popularity of the first name "Elijah" and the use of genetically modified organisms (GMOs) in soybeans within the state of Indiana. Through meticulous analysis of data from the US Social Security Administration and the United States Department of Agriculture, we have uncovered an intriguing connection between these two seemingly disparate factors. Our research has revealed a striking correlation coefficient of 0.8880183 and a statistically significant p-value of less than 0.01 for the period spanning from 2000 to 2022.
The implications of our findings are both astonishing and uproarious, as we ponder whether there is more than meets the eye to the confluence of Elijah's popularity and the cultivation of genetically modified soybeans in the heart of the Midwest. While this study raises numerous questions, we must approach the results with a tempered enthusiasm, recognizing the comical potential for spurious correlations. Our investigation into the "Elijah Effect" serves as a lighthearted reminder that, in the realm of statistics, the most unexpected relationships can germinate in the seemingly mundane fields of monikers and agriculture.
ChatGPT:
"Elijah Effect" "genetically modified soybeans" Indiana, "Elijah popularity" correlation GMOs, "US Social Security Administration data" "USDA agriculture data" correlation, "Elijah name popularity" GMO soybeans Indiana correlation, "Lighthearted statistical correlations" "Elijah name" agriculture connection
*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 ElijahDetailed data title: Babies of all sexes born in the US named Elijah
Source: US Social Security Administration
See what else correlates with Popularity of the first name Elijah
GMO use in soybeans in Indiana
Detailed data title: Percent of soybeans planted in Indiana that are genetically modified to be herbicide-tolerant (HT), but not insect-resistant (Bt)
Source: USDA
See what else correlates with GMO use in soybeans in Indiana
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 = 0.7885765 (Coefficient of determination)
This means 78.9% of the change in the one variable (i.e., GMO use in soybeans in Indiana) is predictable based on the change in the other (i.e., Popularity of the first name Elijah) over the 23 years from 2000 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.6E-8. 0.0000000157185821174968760000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.
But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.
Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.89 in 1.6E-6% of random cases. Said differently, if you correlated 63,618,970 random variables You don't actually need 63 million 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 22 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 22 because we have two variables measured over a period of 23 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.
[ 0.75, 0.95 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
| 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | |
| Popularity of the first name Elijah (Babies born) | 7496 | 8381 | 10091 | 10710 | 11789 | 11649 | 12089 | 12453 | 13278 | 12876 | 13959 | 14023 | 13923 | 13845 | 13899 | 13726 | 13983 | 13448 | 13030 | 13414 | 13203 | 12802 | 12010 |
| GMO use in soybeans in Indiana (GMO soybeans %) | 63 | 78 | 83 | 88 | 87 | 89 | 92 | 94 | 96 | 94 | 95 | 96 | 93 | 90 | 92 | 93 | 92 | 92 | 91 | 93 | 93 | 91 | 93 |
Why this works
- Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
- Lack of causal connection: There is probably
Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied. - Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple
Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.Step 2: Open a plaintext editor like Notepad and paste the code below into it.
Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"
Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.
Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.
Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.
Step 7: Run the Python script by typing "python calculate_correlation.py"
If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:
"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."
# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats
# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):
# Calculate Pearson correlation coefficient and p-value
correlation, p_value = stats.pearsonr(array1, array2)
# Calculate R-squared as the square of the correlation coefficient
r_squared = correlation**2
return correlation, r_squared, p_value
# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([7496,8381,10091,10710,11789,11649,12089,12453,13278,12876,13959,14023,13923,13845,13899,13726,13983,13448,13030,13414,13203,12802,12010,])
array_2 = np.array([63,78,83,88,87,89,92,94,96,94,95,96,93,90,92,93,92,92,91,93,93,91,93,])
array_1_name = "Popularity of the first name Elijah"
array_2_name = "GMO use in soybeans in Indiana"
# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)
# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)Reuseable content
You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.
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When spoken, my last name is pronounced "vegan," like I don't eat meat.
Full license details.
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Download images for these variables:
- High resolution line chart
The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
Alternatively you can use a tool like Inkscape. - High resolution line chart, optimized for mobile
- Alternative high resolution line chart
- Scatterplot
- Portable line chart (png)
- Portable line chart (png), optimized for mobile
- Line chart for only Popularity of the first name Elijah
- Line chart for only GMO use in soybeans in Indiana
- AI-generated correlation image
- The spurious research paper: The Elijah Effect: Unraveling the Soybean Saga in Indiana
Your correlation rating is out of this world!
Correlation ID: 1662 · Black Variable ID: 2128 · Red Variable ID: 815
