Spurious correlation #2,593 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is GMO use in corn grown in Illinois and the second variable is Organic Food Sales Volume in the United States. The chart goes from 2000 to 2012, 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 GMO use in corn grown in Illinois and the second variable is Organic Food Sales Volume in the United States. The chart goes from 2000 to 2012, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As GMO corn in Illinois grew larger and stronger, it developed a competitive streak. This led to a rise in organic farming techniques as the GMO corn taunted the other crops for using synthetic pesticides and fertilizers. Feeling superior, the organic crops flexed their chemical-free muscles, attracting more consumer interest and ultimately boosting organic food sales across the nation. It's like the corn started a farm-to-fork revolution, proving that even in the world of agriculture, a little bit of rivalry can lead to some ear-resistible growth.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image that showcases a beautiful contrast between a vast genetically modified cornfield in Illinois and a bustling organic food store in the United States. In the cornfield, rows of genetically modified corn stretch endlessly, with a mischievous ear of corn standing out amongst the stalks, telling corny jokes to the chuckling nearby farmers. Meanwhile, in the organic food store, an array of vibrant organic fruits and vegetables captivate customers who are laughing and chatting, feeling a deep connection to the earth and their food. The scene should resonate with the feeling of being "real" amidst the humor of the corny jokes. 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: GMO use in corn grown in Illinois and Organic Food Sales Volume in the United States. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: A TIME magazine cover image Pop art Whimsical illustration Cutsy graphics Celtic art
ChatGPT: A TIME magazine cover 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 GMO use in corn grown in Illinois and Organic Food Sales Volume in the United States, in the following situation: The GMO corn developed a sense of humor, and consumers found themselves inexplicably drawn to organic food as a way to "keep it real" in the midst of all the corn's corny jokes.. Keep the description simple.
ChatGPT: In a vast cornfield in Illinois, rows of genetically modified corn stretch as far as the eye can see. Amongst the stalks, a particularly mischievous ear of corn tells corny jokes, making the nearby farmers chuckle. Meanwhile, in a bustling organic food store in the United States, customers gather around the fresh produce section, drawn to the colorful array of organic fruits and vegetables. They laugh and chat, feeling a sense of connection to the earth and their food as a way to "keep it real" amidst all the corn's corny jokes.

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 TIME magazine cover image ] and depicting this scene: In a vast cornfield in Illinois, rows of genetically modified corn stretch as far as the eye can see. Amongst the stalks, a particularly mischievous ear of corn tells corny jokes, making the nearby farmers chuckle. Meanwhile, in a bustling organic food store in the United States, customers gather around the fresh produce section, drawn to the colorful array of organic fruits and vegetables. They laugh and chat, feeling a sense of connection to the earth and their food as a way to "keep it real" amidst all the corn's corny jokes. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that showcases a beautiful contrast between a vast genetically modified cornfield in Illinois and a bustling organic food store in the United States. In the cornfield, rows of genetically modified corn stretch endlessly, with a mischievous ear of corn standing out amongst the stalks, telling corny jokes to the chuckling nearby farmers. Meanwhile, in the organic food store, an array of vibrant organic fruits and vegetables captivate customers who are laughing and chatting, feeling a deep connection to the earth and their food. The scene should resonate with the feeling of being "real" amidst the humor of the corny jokes.

*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 GMO use in corn grown in Illinois caused Organic Food Sales Volume in the United States to increase.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Maze Craze: Unearthing the Corny Connection Between GMOs in Illinois and Organic Sales in the United States

The Journal of Agri-Quirky Studies

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between GMO use in corn grown in Illinois and Organic Food Sales Volume in the United States. 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 the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
"Maze Craze: Unearthing the Corny Connection Between GMOs in Illinois and Organic Sales in the United States"

[[ABSTRACT]]
In this study, we dive headfirst into the world of genetically modified organisms (GMOs) in the cornfields of Illinois and the curious correlation with organic food sales volume across the United States. As we peel back the husk of this perplexing relationship, our research team couldn't resist the kernel of truth hidden within the data.

Utilizing data from the USDA and Statista, we meticulously examined the period from 2000 to 2012 to analyze the interplay between the cultivation of GMO corn in Illinois and the burgeoning sales of organic food products. With a correlation coefficient of 0.9696498 and p < 0.01, our findings sprouted a remarkable connection that left us a-maize-d.

Much like a corny dad joke, the relationship between the use of GMOs in corn and the surge in organic food sales is both unexpected and oddly delightful. The results of our study not only shed light on this correlation but also highlight the intricacies of agricultural practices and consumer trends. We hope this research leaves readers feeling cornfident in their understanding of these intertwined phenomena.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As the agricultural landscape continues to evolve, the intertwining of genetically modified organisms (GMOs) and organic food sales has sparked considerable curiosity. It's almost as if we've stumbled upon a confounding cornundrum! This study delves into the seemingly contradictory relationship between the widespread use of GMOs in the cornfields of Illinois and the remarkable rise in organic food sales across the United States.
GMOs and organic foods – it's like a game of corn and mouse, one altering genetic composition to enhance traits, while the other embraces the purity of nature's bounty. It's a-maize-ing how these two forces have sparked such widespread debate and market dynamics.
Our research sets out to unravel this perplexing relationship, akin to a-maize-ing sleuths cracking a particularly challenging case. By accessing comprehensive data from the USDA and Statista, we carefully examined the period from 2000 to 2012 to scrutinize the subtle and not-so-subtle interactions between GMO corn cultivation in Illinois and the burgeoning sales of organic food products. We left no kernel unturned in our quest for understanding.
The correlation coefficient of 0.9696498 and a p-value of less than 0.01 emerged from our analysis like a cornstalk rising above the rest. It’s enough to make a statistics enthusiast positively ear-resistible! These findings revealed a strikingly strong link between GMO corn production in Illinois and the surge in organic food sales nationwide. It’s like the statistical equivalent of finding a needle in a haystack – but instead, it's a corn kernel in a silo!
With this study, we aim to not only shed light on the fascinating correlation between the use of GMOs and the growth in organic food sales but also to highlight the intricate dance between agricultural practices and consumer preferences. We might just say we hope this research leaves readers feeling cornfident in their understanding of these intertwined phenomena, but that would be too corny, wouldn't it?

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Research in this field has sought to uncover the nuanced relationship between genetically modified organisms (GMOs) in corn production and the sales volume of organic food products in the United States. Jones et al. (2015) examined the impact of GMO corn cultivation on organic food consumption patterns, revealing a surprising correlation that has raised both eyebrows and corn stalks.

Now, let's turn our attention to some noteworthy non-fiction works that have provided valuable insight into the corny world of GMOs and organic foods. Michael Pollan's "The Omnivore's Dilemma" takes readers on a journey through the modern food industry, including the prevalence of GMO corn and the burgeoning organic food movement. In "Fast Food Nation" by Eric Schlosser, the author delves into the impact of industrial agriculture on food production, shedding light on the contentious debate surrounding GMOs and organic alternatives. These publications serve as a kernel of knowledge in understanding the broader context of our investigation.

As we peel back the layers of this research maze, let's not overlook the potential influences of fiction literature on our understanding of agricultural practices and consumer trends. Barbara Kingsolver's "Animal, Vegetable, Miracle" immerses readers in the author's own venture into sustainable food production, offering a compelling narrative that explores the intersection of GMOs and organic farming. Similarly, in John Steinbeck's classic "The Grapes of Wrath," the challenges faced by farmers in the Dust Bowl era invite contemplation on the evolving landscape of agricultural methods, including the introduction of GMOs and the rise of organic food sales.

Of course, no literature review would be complete without a touch of whimsy. In the spirit of unearthing unconventional sources, it's worth noting that our research team conducted a thorough examination of the backs of shampoo bottles in order to ascertain any subliminal messages regarding GMOs and organic food sales. Alas, the results revealed nothing more than a bubbly lather of disappointment and a cornucopia of corny puns.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 GMO use in corn grown in Illinois and Organic Food Sales Volume in the United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 USDA and Statista . You used data from 2000 to 2012

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]]
"Maze Craze: Unearthing the Corny Connection Between GMOs in Illinois and Organic Sales in the United States"

[[ABSTRACT]]
In this study, we dive headfirst into the world of genetically modified organisms (GMOs) in the cornfields of Illinois and the curious correlation with organic food sales volume across the United States. As we peel back the husk of this perplexing relationship, our research team couldn't resist the kernel of truth hidden within the data.

Utilizing data from the USDA and Statista, we meticulously examined the period from 2000 to 2012 to analyze the interplay between the cultivation of GMO corn in Illinois and the burgeoning sales of organic food products. With a correlation coefficient of 0.9696498 and p < 0.01, our findings sprouted a remarkable connection that left us a-maize-d.

Much like a corny dad joke, the relationship between the use of GMOs in corn and the surge in organic food sales is both unexpected and oddly delightful. The results of our study not only shed light on this correlation but also highlight the intricacies of agricultural practices and consumer trends. We hope this research leaves readers feeling cornfident in their understanding of these intertwined phenomena.

[[INTRODUCTION]]
As the agricultural landscape continues to evolve, the intertwining of genetically modified organisms (GMOs) and organic food sales has sparked considerable curiosity. It's almost as if we've stumbled upon a confounding cornundrum! This study delves into the seemingly contradictory relationship between the widespread use of GMOs in the cornfields of Illinois and the remarkable rise in organic food sales across the United States.
GMOs and organic foods – it's like a game of corn and mouse, one altering genetic composition to enhance traits, while the other embraces the purity of nature's bounty. It's a-maize-ing how these two forces have sparked such widespread debate and market dynamics.
Our research sets out to unravel this perplexing relationship, akin to a-maize-ing sleuths cracking a particularly challenging case. By accessing comprehensive data from the USDA and Statista, we carefully examined the period from 2000 to 2012 to scrutinize the subtle and not-so-subtle interactions between GMO corn cultivation in Illinois and the burgeoning sales of organic food products. We left no kernel unturned in our quest for understanding.
The correlation coefficient of 0.9696498 and a p-value of less than 0.01 emerged from our analysis like a cornstalk rising above the rest. It’s enough to make a statistics enthusiast positively ear-resistible! These findings revealed a strikingly strong link between GMO corn production in Illinois and the surge in organic food sales nationwide. It’s like the statistical equivalent of finding a needle in a haystack – but instead, it's a corn kernel in a silo!
With this study, we aim to not only shed light on the fascinating correlation between the use of GMOs and the growth in organic food sales but also to highlight the intricate dance between agricultural practices and consumer preferences. We might just say we hope this research leaves readers feeling cornfident in their understanding of these intertwined phenomena, but that would be too corny, wouldn't it?

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unearth the enigmatic relationship between the prevalence of GMOs in Illinois corn and the organic food sales volume in the United States, our research team embarked on a quest that combined the precision of a molecular biologist with the curiosity of a true corn connoisseur. Our methodology involved a series of data mining escapades and statistical acrobatics, all in pursuit of cracking the corny connection between these seemingly disparate phenomena.

First, we conducted an extensive review of existing literature, combing through scholarly articles and industry reports like intrepid explorers spelunking through the maize of information available. We wanted to ensure we were not reinventing the wheel, but perhaps just giving it a fresh coat of husk-inspired paint.

Next, we collected data from the USDA and Statista, two stalwart sources that provided us with a bounty of information akin to a cornucopia. We meticulously examined the years 2000 to 2012, as we wanted to capture the evolution of both GMO adoption and organic food sales, spanning a period of time that could be likened to the growth of a resilient corn stalk.

We then employed a series of robust statistical analyses, including regression models and time series analyses, to sift through the data and discern any meaningful patterns. Our statistical approaches were as carefully selected as the ripest ears of corn in the field, ensuring that we utilized methodologies that were both rigorous and fresh, like a just-picked cob of corn.

Of course, the complexity of our analyses demanded a keen eye for detail and a healthy dose of skepticism. We didn't want to be led astray by mere coincidences that were as flimsy as a corn husk in a gentle breeze. As such, we conducted sensitivity analyses and cross-validated our findings to ensure their robustness and reliability.

In a light-hearted nod to both our research subject and the traditional business of farming, we also incorporated some "fieldwork" into our methodology. We ventured out to cornfields and organic farms, engaging in discussions with farmers and producers to gain insights that couldn’t be gleaned from data alone. It was a veritable cornucopia of information-gathering, and we were cob-stantly amazed by the breadth of knowledge we acquired.

Our methodology was not without its challenges, much like navigating a maze constructed entirely of puns and dad jokes. However, in the end, our approach was as rigorous as it was whimsical – much like the juxtaposition of a corn kernel's audacious leap from the cob.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 GMO use in corn grown in Illinois and Organic Food Sales Volume in the United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 USDA and Statista .

For the time period 2000 to 2012, you found a correlation 0.9696498, r-squared of 0.9402208, 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]]
"Maze Craze: Unearthing the Corny Connection Between GMOs in Illinois and Organic Sales in the United States"

[[ABSTRACT]]
In this study, we dive headfirst into the world of genetically modified organisms (GMOs) in the cornfields of Illinois and the curious correlation with organic food sales volume across the United States. As we peel back the husk of this perplexing relationship, our research team couldn't resist the kernel of truth hidden within the data.

Utilizing data from the USDA and Statista, we meticulously examined the period from 2000 to 2012 to analyze the interplay between the cultivation of GMO corn in Illinois and the burgeoning sales of organic food products. With a correlation coefficient of 0.9696498 and p < 0.01, our findings sprouted a remarkable connection that left us a-maize-d.

Much like a corny dad joke, the relationship between the use of GMOs in corn and the surge in organic food sales is both unexpected and oddly delightful. The results of our study not only shed light on this correlation but also highlight the intricacies of agricultural practices and consumer trends. We hope this research leaves readers feeling cornfident in their understanding of these intertwined phenomena.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
As the agricultural landscape continues to evolve, the intertwining of genetically modified organisms (GMOs) and organic food sales has sparked considerable curiosity. It's almost as if we've stumbled upon a confounding cornundrum! This study delves into the seemingly contradictory relationship between the widespread use of GMOs in the cornfields of Illinois and the remarkable rise in organic food sales across the United States.
GMOs and organic foods – it's like a game of corn and mouse, one altering genetic composition to enhance traits, while the other embraces the purity of nature's bounty. It's a-maize-ing how these two forces have sparked such widespread debate and market dynamics.
Our research sets out to unravel this perplexing relationship, akin to a-maize-ing sleuths cracking a particularly challenging case. By accessing comprehensive data from the USDA and Statista, we carefully examined the period from 2000 to 2012 to scrutinize the subtle and not-so-subtle interactions between GMO corn cultivation in Illinois and the burgeoning sales of organic food products. We left no kernel unturned in our quest for understanding.
The correlation coefficient of 0.9696498 and a p-value of less than 0.01 emerged from our analysis like a cornstalk rising above the rest. It’s enough to make a statistics enthusiast positively ear-resistible! These findings revealed a strikingly strong link between GMO corn production in Illinois and the surge in organic food sales nationwide. It’s like the statistical equivalent of finding a needle in a haystack – but instead, it's a corn kernel in a silo!
With this study, we aim to not only shed light on the fascinating correlation between the use of GMOs and the growth in organic food sales but also to highlight the intricate dance between agricultural practices and consumer preferences. We might just say we hope this research leaves readers feeling cornfident in their understanding of these intertwined phenomena, but that would be too corny, wouldn't it?

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The results of our analysis showcased a staggering correlation coefficient of 0.9696498 between the utilization of genetically modified organisms (GMOs) in corn grown in Illinois and the sales volume of organic food products across the United States. To put it simply, the connection between these two variables is as strong as a cob of corn in a cornfield. It's a-maize-ing how intertwined these phenomena turned out to be!

The r-squared value of 0.9402208 indicated that a whopping 94% of the variation in organic food sales can be explained by the use of GMOs in Illinois-grown corn. It's like having 94% confidence that the correlation isn't just another statistical kernel of truth—it's as real as corn on the cob. Now that's what we call a strong statistical cob-nnection!

The p-value of less than 0.01 further solidified the significance of the relationship, making it as clear as corn syrup. With a p-value like that, the likelihood of this association being attributed to random chance is about as low as finding a needle in a cornfield.

Fig. 1 demonstrates the robust correlation we uncovered, with a scatterplot that resembles two peas in a pod—a perfect fit. It's almost like the plot is saying, "You can't kernel the truth about our relationship!"

In conclusion, our findings highlight a remarkably strong and statistically significant correlation between the use of GMOs in corn grown in Illinois and the sales volume of organic food products in the United States. This discovery not only enriches our understanding of agricultural practices and consumer behavior but also adds a kernel of insight into the ever-evolving dynamics of the food industry. Who knew that a-maize-ing truths could stem from a simple analysis of corn-related variables?

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between GMO use in corn grown in Illinois and Organic Food Sales Volume in the United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Maze Craze: Unearthing the Corny Connection Between GMOs in Illinois and Organic Sales in the United States"

[[ABSTRACT]]
In this study, we dive headfirst into the world of genetically modified organisms (GMOs) in the cornfields of Illinois and the curious correlation with organic food sales volume across the United States. As we peel back the husk of this perplexing relationship, our research team couldn't resist the kernel of truth hidden within the data.

Utilizing data from the USDA and Statista, we meticulously examined the period from 2000 to 2012 to analyze the interplay between the cultivation of GMO corn in Illinois and the burgeoning sales of organic food products. With a correlation coefficient of 0.9696498 and p < 0.01, our findings sprouted a remarkable connection that left us a-maize-d.

Much like a corny dad joke, the relationship between the use of GMOs in corn and the surge in organic food sales is both unexpected and oddly delightful. The results of our study not only shed light on this correlation but also highlight the intricacies of agricultural practices and consumer trends. We hope this research leaves readers feeling cornfident in their understanding of these intertwined phenomena.

[[LITERATURE REVIEW]]
Research in this field has sought to uncover the nuanced relationship between genetically modified organisms (GMOs) in corn production and the sales volume of organic food products in the United States. Jones et al. (2015) examined the impact of GMO corn cultivation on organic food consumption patterns, revealing a surprising correlation that has raised both eyebrows and corn stalks.
Now, let's turn our attention to some noteworthy non-fiction works that have provided valuable insight into the corny world of GMOs and organic foods. Michael Pollan's "The Omnivore's Dilemma" takes readers on a journey through the modern food industry, including the prevalence of GMO corn and the burgeoning organic food movement. In "Fast Food Nation" by Eric Schlosser, the author delves into the impact of industrial agriculture on food production, shedding light on the contentious debate surrounding GMOs and organic alternatives. These publications serve as a kernel of knowledge in understanding the broader context of our investigation.
As we peel back the layers of this research maze, let's not overlook the potential influences of fiction literature on our understanding of agricultural practices and consumer trends. Barbara Kingsolver's "Animal, Vegetable, Miracle" immerses readers in the author's own venture into sustainable food production, offering a compelling narrative that explores the intersection of GMOs and organic farming. Similarly, in John Steinbeck's classic "The Grapes of Wrath," the challenges faced by farmers in the Dust Bowl era invite contemplation on the evolving landscape of agricultural methods, including the introduction of GMOs and the rise of organic food sales.
Of course, no literature review would be complete without a touch of whimsy. In the spirit of unearthing unconventional sources, it's worth noting that our research team conducted a thorough examination of the backs of shampoo bottles in order to ascertain any subliminal messages regarding GMOs and organic food sales. Alas, the results revealed nothing more than a bubbly lather of disappointment and a cornucopia of corny puns.

[[RESULTS]]
The results of our analysis showcased a staggering correlation coefficient of 0.9696498 between the utilization of genetically modified organisms (GMOs) in corn grown in Illinois and the sales volume of organic food products across the United States. To put it simply, the connection between these two variables is as strong as a cob of corn in a cornfield. It's a-maize-ing how intertwined these phenomena turned out to be!
The r-squared value of 0.9402208 indicated that a whopping 94% of the variation in organic food sales can be explained by the use of GMOs in Illinois-grown corn. It's like having 94% confidence that the correlation isn't just another statistical kernel of truth—it's as real as corn on the cob. Now that's what we call a strong statistical cob-nnection!
The p-value of less than 0.01 further solidified the significance of the relationship, making it as clear as corn syrup. With a p-value like that, the likelihood of this association being attributed to random chance is about as low as finding a needle in a cornfield.
Fig. 1 demonstrates the robust correlation we uncovered, with a scatterplot that resembles two peas in a pod—a perfect fit. It's almost like the plot is saying, "You can't kernel the truth about our relationship!"
In conclusion, our findings highlight a remarkably strong and statistically significant correlation between the use of GMOs in corn grown in Illinois and the sales volume of organic food products in the United States. This discovery not only enriches our understanding of agricultural practices and consumer behavior but also adds a kernel of insight into the ever-evolving dynamics of the food industry. Who knew that a-maize-ing truths could stem from a simple analysis of corn-related variables?

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our study yielded a-maize-ing results that not only supported the prior research but also popped (corn) several kernels of insight into the tangled relationship between GMO use in corn grown in Illinois and organic food sales volume in the United States. The correlation coefficient of 0.9696498 we uncovered is as strong as the gravitational pull of Jupiter, leaving us feeling not just corny, but astounded by the magnitude of this connection.

The kernel of truth we unearthed about the strong correlation between GMO use in Illinois-grown corn and organic food sales volume is not just a-maize-ing; it's something to truly relish, like a perfectly buttered ear of corn. Our findings align with Jones et al.'s (2015) revelation of a surprising correlation, adding another layer to the stalk of existing knowledge in this field.

As we peel back the layers of this research maize, it's clear that our results have shucked any lingering doubt about the robustness of the relationship. The r-squared value of 0.9402208 indicates that a whopping 94% of the variation in organic food sales volume can be explained by GMO use in Illinois-grown corn. This level of explanatory power is as solid as the golden kernels on an ear of corn, leaving little room for cob-fusion.

The p-value of less than 0.01 further validates the significance of our findings, portraying a statistical stance as firm as a corn stalk in a summer breeze. With such a low p-value, the likelihood of this association being attributed to random chance is about as slim as finding a gluten-free, dairy-free, soy-free, nut-free, guilt-free, taste-free, chocolate-free brownie—virtually impossible!

This statistically significant correlation, akin to a strong and sturdy stalk, not only enriches our understanding of agricultural practices and consumer behavior but also adds a delightful twist to the narrative of GMOs and organic food sales. It's almost as if these variables are caught in a maize-y love affair, and our study has finally brought their deep connection to light.

In the spirit of embracing the unexpected, our findings serve as a pop of surprise in the scientific community, injecting a sense of humor and delight into the typically serious discourse of research. After all, in the exciting world of scientific discovery, who says we can't sprinkle in a few puns and witticisms along the way? It's time to honor the a-maize-ing discoveries with a chuckle or two, for science doesn't always have to be as serious as a heart attack—sometimes, it can be as light and sweet as kettle corn at a fair.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between GMO use in corn grown in Illinois and Organic Food Sales Volume in the United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Maze Craze: Unearthing the Corny Connection Between GMOs in Illinois and Organic Sales in the United States"

[[ABSTRACT]]
In this study, we dive headfirst into the world of genetically modified organisms (GMOs) in the cornfields of Illinois and the curious correlation with organic food sales volume across the United States. As we peel back the husk of this perplexing relationship, our research team couldn't resist the kernel of truth hidden within the data.

Utilizing data from the USDA and Statista, we meticulously examined the period from 2000 to 2012 to analyze the interplay between the cultivation of GMO corn in Illinois and the burgeoning sales of organic food products. With a correlation coefficient of 0.9696498 and p < 0.01, our findings sprouted a remarkable connection that left us a-maize-d.

Much like a corny dad joke, the relationship between the use of GMOs in corn and the surge in organic food sales is both unexpected and oddly delightful. The results of our study not only shed light on this correlation but also highlight the intricacies of agricultural practices and consumer trends. We hope this research leaves readers feeling cornfident in their understanding of these intertwined phenomena.

[[INTRDUCTION]]
As the agricultural landscape continues to evolve, the intertwining of genetically modified organisms (GMOs) and organic food sales has sparked considerable curiosity. It's almost as if we've stumbled upon a confounding cornundrum! This study delves into the seemingly contradictory relationship between the widespread use of GMOs in the cornfields of Illinois and the remarkable rise in organic food sales across the United States.
GMOs and organic foods – it's like a game of corn and mouse, one altering genetic composition to enhance traits, while the other embraces the purity of nature's bounty. It's a-maize-ing how these two forces have sparked such widespread debate and market dynamics.
Our research sets out to unravel this perplexing relationship, akin to a-maize-ing sleuths cracking a particularly challenging case. By accessing comprehensive data from the USDA and Statista, we carefully examined the period from 2000 to 2012 to scrutinize the subtle and not-so-subtle interactions between GMO corn cultivation in Illinois and the burgeoning sales of organic food products. We left no kernel unturned in our quest for understanding.
The correlation coefficient of 0.9696498 and a p-value of less than 0.01 emerged from our analysis like a cornstalk rising above the rest. It’s enough to make a statistics enthusiast positively ear-resistible! These findings revealed a strikingly strong link between GMO corn production in Illinois and the surge in organic food sales nationwide. It’s like the statistical equivalent of finding a needle in a haystack – but instead, it's a corn kernel in a silo!
With this study, we aim to not only shed light on the fascinating correlation between the use of GMOs and the growth in organic food sales but also to highlight the intricate dance between agricultural practices and consumer preferences. We might just say we hope this research leaves readers feeling cornfident in their understanding of these intertwined phenomena, but that would be too corny, wouldn't it?

[[RESULTS]]
The results of our analysis showcased a staggering correlation coefficient of 0.9696498 between the utilization of genetically modified organisms (GMOs) in corn grown in Illinois and the sales volume of organic food products across the United States. To put it simply, the connection between these two variables is as strong as a cob of corn in a cornfield. It's a-maize-ing how intertwined these phenomena turned out to be!
The r-squared value of 0.9402208 indicated that a whopping 94% of the variation in organic food sales can be explained by the use of GMOs in Illinois-grown corn. It's like having 94% confidence that the correlation isn't just another statistical kernel of truth—it's as real as corn on the cob. Now that's what we call a strong statistical cob-nnection!
The p-value of less than 0.01 further solidified the significance of the relationship, making it as clear as corn syrup. With a p-value like that, the likelihood of this association being attributed to random chance is about as low as finding a needle in a cornfield.
Fig. 1 demonstrates the robust correlation we uncovered, with a scatterplot that resembles two peas in a pod—a perfect fit. It's almost like the plot is saying, "You can't kernel the truth about our relationship!"
In conclusion, our findings highlight a remarkably strong and statistically significant correlation between the use of GMOs in corn grown in Illinois and the sales volume of organic food products in the United States. This discovery not only enriches our understanding of agricultural practices and consumer behavior but also adds a kernel of insight into the ever-evolving dynamics of the food industry. Who knew that a-maize-ing truths could stem from a simple analysis of corn-related variables?

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study uncovered a-maize-ing and statistically significant evidence of the connection between the utilization of GMOs in corn grown in Illinois and the sales volume of organic food products in the United States. It's like we've stumbled upon a cornucopia of interconnected phenomena - who would've thought GMO corn could be so kernel to organic food sales?

Our findings reinforce the notion that the relationship between these variables is as strong as the stalks of corn swaying in the wind – with a correlation coefficient of 0.9696498, it's clear that this connection isn't just a-maize-ing coincidence but a bona fide statistical cob-nnection! It's like finding the perfect mathematical ear of corn.

With an r-squared value of 0.9402208, we can confidently say that 94% of the variation in organic food sales can be attributed to the use of GMOs in Illinois-grown corn. It's as if the statistics are telling us, "You can count on this correlation – no kernel of doubt about it!"

Moreover, the p-value of less than 0.01 solidifies the significance of this relationship, leaving little room for skepticism. It's as rare as a unicorn sighting in a cornfield! It's clear that this correlation is as authentic as non-GMO, organic corn.

Therefore, we assert that no further research is needed in this area. Our findings are as sound as a corn on the cob and as clear as day – this is the ear-resistible conclusion to the maize craze mystery!

And remember, folks, when it comes to GMOs and organic food sales, let's not shuck at the correlations – it's all a-maize-ing science!

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 Maze Craze: Unearthing the Corny Connection Between GMOs in Illinois and Organic Sales in the United States. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Agri-Quirky Studies

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 Maze Craze: Unearthing the Corny Connection Between GMOs in Illinois and Organic Sales in the United States. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Agricultural Amusement and Analysis

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 Maze Craze: Unearthing the Corny Connection Between GMOs in Illinois and Organic Sales in the United States with an abstract of In this study, we dive headfirst into the world of genetically modified organisms (GMOs) in the cornfields of Illinois and the curious correlation with organic food sales volume across the United States. As we peel back the husk of this perplexing relationship, our research team couldn't resist the kernel of truth hidden within the data.
Utilizing data from the USDA and Statista, we meticulously examined the period from 2000 to 2012 to analyze the interplay between the cultivation of GMO corn in Illinois and the burgeoning sales of organic food products. With a correlation coefficient of 0.9696498 and p < 0.01, our findings sprouted a remarkable connection that left us a-maize-d.
Much like a corny dad joke, the relationship between the use of GMOs in corn and the surge in organic food sales is both unexpected and oddly delightful. The results of our study not only shed light on this correlation but also highlight the intricacies of agricultural practices and consumer trends. We hope this research leaves readers feeling cornfident in their understanding of these intertwined phenomena.

ChatGPT:

GMOs, Illinois, organic sales, United States, correlation, USDA, Statista, GMO corn, cultivation, sales volume, 2000-2012, correlation coefficient, agricultural practices, consumer trends

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

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Data details

GMO use in corn grown in Illinois
Detailed data title: Percent of all corn planted in Illinois that is genetically modified to be herbicide-tolerant (HT), but not insect-resistant (Bt)
Source: USDA
See what else correlates with GMO use in corn grown in Illinois

Organic Food Sales Volume in the United States
Source: Statista
See what else correlates with Organic Food Sales Volume in the United States

Correlation r = 0.9696498 (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 = 0.9402208 (Coefficient of determination)
This means 94% of the change in the one variable (i.e., Organic Food Sales Volume in the United States) is predictable based on the change in the other (i.e., GMO use in corn grown in Illinois) over the 13 years from 2000 through 2012.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.51E-8.^Show 0.0000000450501131712750700000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.97 in 4.51E-6% of random cases. Said differently, if you correlated 22,197,503 random variables^Note You don't actually need 22 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 12 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 12 because we have two variables measured over a period of 13 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.

[ 0.9, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012
GMO use in corn grown in Illinois (GMO corn %)	3	3	3	4	5	6	12	15	15	15	15	17	18
Organic Food Sales Volume in the United States (Sales in US Dollars)	6100000000	7360000000	8635000000	10381000000	12002000000	14223000000	17221000000	20410000000	23607000000	24803000000	26708000000	29220000000	31320000000

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([3,3,3,4,5,6,12,15,15,15,15,17,18,])
array_2 = np.array([6100000000,7360000000,8635000000,10381000000,12002000000,14223000000,17221000000,20410000000,23607000000,24803000000,26708000000,29220000000,31320000000,])
array_1_name = "GMO use in corn grown in Illinois"
array_2_name = "Organic Food Sales Volume in the United States"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only GMO use in corn grown in Illinois
Line chart for only Organic Food Sales Volume in the United States
AI-generated correlation image
The spurious research paper: Maze Craze: Unearthing the Corny Connection Between GMOs in Illinois and Organic Sales in the United States

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Correlation ID: 2593 · Black Variable ID: 725 · Red Variable ID: 492


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