about · email me · subscribe
Spurious correlation #2,406 · 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 South Dakota and the second variable is Google searches for 'i cant even'.  The chart goes from 2004 to 2023, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

It's a-maize-ing! The GMO corn was feeling a little too corny, leading to a kernel of existential crisis. As it turns out, when you're genetically modified to resist pests, but not existential angst, you end up with a-maize-ing levels of confusion. Plus, all the cross-pollination with other crops had everyone feeling a-llama-nted. It's like the corn just couldn't even cob-cept that it was part of a larger stalk-er system. And that, my friends, is how GMO corn in South Dakota led to a-maize-ing levels of 'i cant even' searches.

Model: dalle-3
Prompt: Prompt: Generate an image that captures the essence of a tall field of genetically modified corn swaying in the South Dakota breeze. In the foreground, a few ears of corn stand with puzzled expressions, seemingly lost in deep thought. The vibrant green stalks reach toward the sky, surrounding the contemplative corn. Farther in the background, farmers tend to the flourishing crop. Additionally, convey the digital echo of the corn's existential dilemma through a composition featuring people in South Dakota interacting with their screens, expressing bewilderment and confusion. The scene should evoke a sense of whimsy and curiosity, inviting viewers to contemplate the interplay between the natural and digital worlds. 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 South Dakota and Google searches for 'i cant even'. 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: Whimsical illustration Parallax art Art nouveau Scalar art Parallax art
ChatGPT: Parallax art

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 South Dakota and Google searches for 'i cant even', in the following situation: As the corn grew taller and taller thanks to those G-MO's, it started to develop some serious existential corn-fusion, leading to a kernel of self-doubt. The ears of corn couldn't handle the pressure and kept saying, "I cob-believe it!" This led to a-maize-ing levels of distress, making people turn to Google to express their own inability to corn-prehend the situation. It's like the corn was asking, "What's poppin' with my genetically modified existence?" And the internet world collectively replied, "We can't even kernel with this cornundrum!" So, next time you see a towering stalk of GMO corn, just remember, it may be causing more than just a-maize-ing yields – it's also creating a-corny of 'I can't even' moments!. Keep the description simple.
ChatGPT: A tall field of genetically modified corn sways in the South Dakota breeze, its lush green stalks reaching towards the sky. Among the rows, a few ears of corn sport puzzled expressions, seemingly lost in deep thought. As they mull over their existential corn-fusion, nearby farmers tend to the flourishing crop. Meanwhile, on the screens of South Dakotans everywhere, a surge of Google searches for "I can't even" pops up. Fingers fly across keyboards and screens as people express their own bewilderment, creating a digital echo of the corn's existential dilemma.

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: [ Parallax art ] and depicting this scene: A tall field of genetically modified corn sways in the South Dakota breeze, its lush green stalks reaching towards the sky. Among the rows, a few ears of corn sport puzzled expressions, seemingly lost in deep thought. As they mull over their existential corn-fusion, nearby farmers tend to the flourishing crop. Meanwhile, on the screens of South Dakotans everywhere, a surge of Google searches for "I can't even" pops up. Fingers fly across keyboards and screens as people express their own bewilderment, creating a digital echo of the corn's existential dilemma. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image that captures the essence of a tall field of genetically modified corn swaying in the South Dakota breeze. In the foreground, a few ears of corn stand with puzzled expressions, seemingly lost in deep thought. The vibrant green stalks reach toward the sky, surrounding the contemplative corn. Farther in the background, farmers tend to the flourishing crop. Additionally, convey the digital echo of the corn's existential dilemma through a composition featuring people in South Dakota interacting with their screens, expressing bewilderment and confusion. The scene should evoke a sense of whimsy and curiosity, inviting viewers to contemplate the interplay between the natural and digital worlds.

*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.

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 South Dakota caused i cant even (Google searches for 'i cant even') to increase. Include one good pun.

AI academic paper

(Because p < 0.01)
Maizey or Maybes: The Correlation Between GMO Corn in South Dakota and 'I Can't Even' Google Searches

The Journal of Agronomic Anecdotes

Jan 2024

Reminder: This paper is AI-generated. Not real!
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You 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 GMO use in corn grown in South Dakota and Google searches for 'i cant even'. Make lots of jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, make it sound serious.

Your research team used data from USDA and Google Trends to assess this nagging question. You found a correlation coefficient of 0.9137392 and p < 0.01 for 2004 to 2023.

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]]
"Maizey or Maybes: The Correlation Between GMO Corn in South Dakota and 'I Can't Even' Google Searches"

[[ABSTRACT]]
The cultivation of genetically modified organisms (GMO) in agriculture has spurred endless debates, but could there be a link between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? In this study, we employed data from the USDA and Google Trends to examine the potential connection. Our findings revealed a surprisingly strong correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 from 2004 to 2023. While the reasons for this intriguing correlation remain uncertain, it appears that the agricultural practices in the Corn Belt may be influencing both the physiology of maize and the exasperation levels of internet users. This research not only sheds light on the interplay between agricultural practices and online expressions of frustration but also adds a humorous twist to the ongoing dialogue surrounding GMO crops.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the 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 GMO use in corn grown in South Dakota and Google searches for 'i cant even'. Make lots of jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
"Maizey or Maybes: The Correlation Between GMO Corn in South Dakota and 'I Can't Even' Google Searches"

[[ABSTRACT]]
The cultivation of genetically modified organisms (GMO) in agriculture has spurred endless debates, but could there be a link between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? In this study, we employed data from the USDA and Google Trends to examine the potential connection. Our findings revealed a surprisingly strong correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 from 2004 to 2023. While the reasons for this intriguing correlation remain uncertain, it appears that the agricultural practices in the Corn Belt may be influencing both the physiology of maize and the exasperation levels of internet users. This research not only sheds light on the interplay between agricultural practices and online expressions of frustration but also adds a humorous twist to the ongoing dialogue surrounding GMO crops.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
The cultivation of genetically modified organisms (GMO) in agriculture has given rise to a plethora of discussions, debates, and a-maize-ing puns (see what I did there?). But could there be a kernel of truth to the seemingly corny connection between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? This study seeks to shed light on this unexpectedly captivating correlation.

As the never-ending saga of GMO debates continues, research has tiptoed into peculiar territories, and this study is no exception. We aimed to plow through the data from the USDA and Google Trends to unearth whether there was any discernible relationship between the cultivation of GMO corn in the heart of South Dakota and the online expression of exasperation. Our findings have peeled back a layer of intrigue in revealing a surprisingly robust correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 during the years 2004 to 2023. It seems, despite our initial skepticism, that we aren't just cornfused after all.

While it may seem like a kernel of corny humor, this research couldn't resist the urge to explore the uncharted territory of agricultural practices and internet expression. Perhaps, it appears, that the physiology of maize isn't the only thing being influenced by agricultural techniques in the Corn Belt. This study not only contributes to the ongoing dialogue surrounding GMO crops but also adds an unexpected, popcorn-worthy twist to the discourse. After all, where else would you find an academic paper that combines agriculture, internet searches, and puns in such a delightful mixture?


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between GMO use in corn grown in South Dakota and Google searches for 'i cant even'. Make lots of jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Maizey or Maybes: The Correlation Between GMO Corn in South Dakota and 'I Can't Even' Google Searches"

[[ABSTRACT]]
The cultivation of genetically modified organisms (GMO) in agriculture has spurred endless debates, but could there be a link between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? In this study, we employed data from the USDA and Google Trends to examine the potential connection. Our findings revealed a surprisingly strong correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 from 2004 to 2023. While the reasons for this intriguing correlation remain uncertain, it appears that the agricultural practices in the Corn Belt may be influencing both the physiology of maize and the exasperation levels of internet users. This research not only sheds light on the interplay between agricultural practices and online expressions of frustration but also adds a humorous twist to the ongoing dialogue surrounding GMO crops.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The cultivation of genetically modified organisms (GMO) in agriculture has given rise to a plethora of discussions, debates, and a-maize-ing puns (see what I did there?). But could there be a kernel of truth to the seemingly corny connection between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? This study seeks to shed light on this unexpectedly captivating correlation.
As the never-ending saga of GMO debates continues, research has tiptoed into peculiar territories, and this study is no exception. We aimed to plow through the data from the USDA and Google Trends to unearth whether there was any discernible relationship between the cultivation of GMO corn in the heart of South Dakota and the online expression of exasperation. Our findings have peeled back a layer of intrigue in revealing a surprisingly robust correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 during the years 2004 to 2023. It seems, despite our initial skepticism, that we aren't just cornfused after all.
While it may seem like a kernel of corny humor, this research couldn't resist the urge to explore the uncharted territory of agricultural practices and internet expression. Perhaps, it appears, that the physiology of maize isn't the only thing being influenced by agricultural techniques in the Corn Belt. This study not only contributes to the ongoing dialogue surrounding GMO crops but also adds an unexpected, popcorn-worthy twist to the discourse. After all, where else would you find an academic paper that combines agriculture, internet searches, and puns in such a delightful mixture?

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The authors find that the connection between GMO use in South Dakota's cornfields and the frequency of "I can't even" Google searches is a topic that has not been extensively explored in the academic literature. Previous studies by Smith (2010) and Doe (2015) have primarily focused on the environmental and health implications of GMO crops, rather than their potential influence on Internet search patterns. However, the dearth of empirical evidence linking agricultural practices to digital frustration does not preclude the existence of such a relationship.

Additionally, Jones (2018) analyzes the socioeconomic impacts of GMO cultivation but does not delve into the intriguing realm of online exasperation. Although these studies provide valuable insights into the broader implications of GMO adoption, they do not directly address the peculiar correlation under investigation in this study.

Turning to non-fiction books related to agriculture and internet culture, "The Omnivore's Dilemma" by Michael Pollan and "Amusing Ourselves to Death" by Neil Postman offer thought-provoking perspectives on the intersection of food production and digital communication. However, neither work explicitly discusses the potential connection between GMO corn and online exasperation, leaving us to tread uncharted territory.

On the fictional front, novels such as "The Circle" by Dave Eggers and "Oryx and Crake" by Margaret Atwood explore the impact of technology on society and the environment. While these literary works stimulate the imagination, they regrettably provide no empirical evidence to inform our current investigation.

Stretching the boundaries of scholarly rigor, the authors also consulted an assortment of eclectic sources, including but not limited to memes, viral videos, and overheard conversations in coffee shops. Furthermore, unorthodox research methods involved a thorough analysis of grocery store receipts, particularly those from establishments known for their exceptionally corny jokes.

In sum, the existing literature hints at a gap in our understanding of the potential link between GMO corn production in South Dakota and expressions of exasperation in online search queries. This motivates our present endeavor to explore this unanticipated correlation, which may possess implications far beyond the confines of academic inquiry.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between GMO use in corn grown in South Dakota and Google searches for 'i cant even'. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from USDA and Google Trends . You used data from 2004 to 2023

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]]
"Maizey or Maybes: The Correlation Between GMO Corn in South Dakota and 'I Can't Even' Google Searches"

[[ABSTRACT]]
The cultivation of genetically modified organisms (GMO) in agriculture has spurred endless debates, but could there be a link between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? In this study, we employed data from the USDA and Google Trends to examine the potential connection. Our findings revealed a surprisingly strong correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 from 2004 to 2023. While the reasons for this intriguing correlation remain uncertain, it appears that the agricultural practices in the Corn Belt may be influencing both the physiology of maize and the exasperation levels of internet users. This research not only sheds light on the interplay between agricultural practices and online expressions of frustration but also adds a humorous twist to the ongoing dialogue surrounding GMO crops.

[[INTRODUCTION]]
The cultivation of genetically modified organisms (GMO) in agriculture has given rise to a plethora of discussions, debates, and a-maize-ing puns (see what I did there?). But could there be a kernel of truth to the seemingly corny connection between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? This study seeks to shed light on this unexpectedly captivating correlation.
As the never-ending saga of GMO debates continues, research has tiptoed into peculiar territories, and this study is no exception. We aimed to plow through the data from the USDA and Google Trends to unearth whether there was any discernible relationship between the cultivation of GMO corn in the heart of South Dakota and the online expression of exasperation. Our findings have peeled back a layer of intrigue in revealing a surprisingly robust correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 during the years 2004 to 2023. It seems, despite our initial skepticism, that we aren't just cornfused after all.
While it may seem like a kernel of corny humor, this research couldn't resist the urge to explore the uncharted territory of agricultural practices and internet expression. Perhaps, it appears, that the physiology of maize isn't the only thing being influenced by agricultural techniques in the Corn Belt. This study not only contributes to the ongoing dialogue surrounding GMO crops but also adds an unexpected, popcorn-worthy twist to the discourse. After all, where else would you find an academic paper that combines agriculture, internet searches, and puns in such a delightful mixture?

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To uncover the potential correlation between the use of GMO corn in South Dakota and the frequency of "I can't even" Google searches, a myriad of data sources were utilized. The primary fount of information emanated from the United States Department of Agriculture (USDA), providing extensive data on the cultivation of GMO corn in South Dakota from 2004 to 2023. The second source of data, Google Trends, furnished the frequency of searches for the phrase "I can't even" within the same time frame. These data highways were essential to our quest for unraveling the curious relationship between agricultural practices and human exasperation on the internet.

The first step in our convoluted methodology involved sifting through mounds of USDA reports, navigating the cornucopia of information on GMO corn cultivation. This endeavor involved filtering out non-essential data, such as the average number of kernels per cob, to isolate the pertinent statistics on GMO corn production in South Dakota. Not to mention, the team also had to weed out the occasional pun-laden report, as tempting as they were.

Simultaneously, our researchers delved into the digital wilderness of Google Trends, tracking down the elusive trail of "I can't even" searches. This process required decoding the idiosyncrasies of internet search behavior and distinguishing genuine expressions of exasperation from mere trends in slang usage or language evolution. Nevertheless, the team emerged victorious in assembling a comprehensive dataset of "I can't even" searches to complement the USDA's cornucopia of information.

Having amassed these datasets, we adopted a hybrid approach to statistical analysis, combining elements of regression analysis, time series modeling, and a touch of magic to discern any underlying patterns. Through the wizardry of statistical software, we unleashed an array of tests and models upon the data, aiming to unveil the potential link between GMO corn cultivation and the surge in exasperated internet searches. The model was fine-tuned with the precision of a seasoned corn farmer, ensuring that it accounted for confounding variables and maintained the integrity of the results.

Lastly, with the statistical crops sown and nurtured, we employed a range of diagnostic tests to validate the robustness of our findings. These tests scrutinized the statistical assumptions underlying our analyses, ensuring that our results were as dependable as a well-rooted maize plant. The fruits of our labor materialized in the form of a correlation coefficient and p-value, signaling the strength and significance of the relationship between GMO corn cultivation and exasperated internet searches.

In conclusion, our methodology traversed the fields of agricultural data and digital landscapes, culminating in a harmonious union of information that bore fruit in our quest for understanding the interplay of GMO corn and online exasperation.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between GMO use in corn grown in South Dakota and Google searches for 'i cant even'. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from USDA and Google Trends .

For the time period 2004 to 2023, you found a correlation 0.9137392, r-squared of 0.8349194, 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]]
"Maizey or Maybes: The Correlation Between GMO Corn in South Dakota and 'I Can't Even' Google Searches"

[[ABSTRACT]]
The cultivation of genetically modified organisms (GMO) in agriculture has spurred endless debates, but could there be a link between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? In this study, we employed data from the USDA and Google Trends to examine the potential connection. Our findings revealed a surprisingly strong correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 from 2004 to 2023. While the reasons for this intriguing correlation remain uncertain, it appears that the agricultural practices in the Corn Belt may be influencing both the physiology of maize and the exasperation levels of internet users. This research not only sheds light on the interplay between agricultural practices and online expressions of frustration but also adds a humorous twist to the ongoing dialogue surrounding GMO crops.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The cultivation of genetically modified organisms (GMO) in agriculture has given rise to a plethora of discussions, debates, and a-maize-ing puns (see what I did there?). But could there be a kernel of truth to the seemingly corny connection between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? This study seeks to shed light on this unexpectedly captivating correlation.
As the never-ending saga of GMO debates continues, research has tiptoed into peculiar territories, and this study is no exception. We aimed to plow through the data from the USDA and Google Trends to unearth whether there was any discernible relationship between the cultivation of GMO corn in the heart of South Dakota and the online expression of exasperation. Our findings have peeled back a layer of intrigue in revealing a surprisingly robust correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 during the years 2004 to 2023. It seems, despite our initial skepticism, that we aren't just cornfused after all.
While it may seem like a kernel of corny humor, this research couldn't resist the urge to explore the uncharted territory of agricultural practices and internet expression. Perhaps, it appears, that the physiology of maize isn't the only thing being influenced by agricultural techniques in the Corn Belt. This study not only contributes to the ongoing dialogue surrounding GMO crops but also adds an unexpected, popcorn-worthy twist to the discourse. After all, where else would you find an academic paper that combines agriculture, internet searches, and puns in such a delightful mixture?

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our study revealed a staggering correlation coefficient of 0.9137392 between the use of genetically modified organisms (GMO) in corn grown in South Dakota and the frequency of Google searches for "I can't even" from 2004 to 2023. The r-squared value of 0.8349194 further illustrates the strong relationship between these seemingly unrelated variables. As if that weren't enough, the p-value of less than 0.01 cements the statistical significance of this unexpected association.

The scatterplot (Fig. 1) visually encapsulates the strength of the correlation, leaving little room for doubt about the connection between GMO corn and exasperated internet users. It seems that the debate surrounding GMO crops has now been sprinkled with a generous helping of internet humor, making this a-cornucopia of unexpected findings.

The robustness of the correlation prompts us to ponder whether the physiological effects of GMO corn extend beyond the agricultural realm and into the online domain. Could it be that the frustrations of internet users are linked, albeit indirectly, to the cultivation of maize in the Corn Belt? While the exact mechanism behind this correlation eludes us, there's no denying that this research has corn-ered a rather unanticipated discovery.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between GMO use in corn grown in South Dakota and Google searches for 'i cant even'. Make lots of jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Maizey or Maybes: The Correlation Between GMO Corn in South Dakota and 'I Can't Even' Google Searches"

[[ABSTRACT]]
The cultivation of genetically modified organisms (GMO) in agriculture has spurred endless debates, but could there be a link between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? In this study, we employed data from the USDA and Google Trends to examine the potential connection. Our findings revealed a surprisingly strong correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 from 2004 to 2023. While the reasons for this intriguing correlation remain uncertain, it appears that the agricultural practices in the Corn Belt may be influencing both the physiology of maize and the exasperation levels of internet users. This research not only sheds light on the interplay between agricultural practices and online expressions of frustration but also adds a humorous twist to the ongoing dialogue surrounding GMO crops.

[[LITERATURE REVIEW]]
The authors find that the connection between GMO use in South Dakota's cornfields and the frequency of "I can't even" Google searches is a topic that has not been extensively explored in the academic literature. Previous studies by Smith (2010) and Doe (2015) have primarily focused on the environmental and health implications of GMO crops, rather than their potential influence on Internet search patterns. However, the dearth of empirical evidence linking agricultural practices to digital frustration does not preclude the existence of such a relationship.
Additionally, Jones (2018) analyzes the socioeconomic impacts of GMO cultivation but does not delve into the intriguing realm of online exasperation. Although these studies provide valuable insights into the broader implications of GMO adoption, they do not directly address the peculiar correlation under investigation in this study.
Turning to non-fiction books related to agriculture and internet culture, "The Omnivore's Dilemma" by Michael Pollan and "Amusing Ourselves to Death" by Neil Postman offer thought-provoking perspectives on the intersection of food production and digital communication. However, neither work explicitly discusses the potential connection between GMO corn and online exasperation, leaving us to tread uncharted territory.
On the fictional front, novels such as "The Circle" by Dave Eggers and "Oryx and Crake" by Margaret Atwood explore the impact of technology on society and the environment. While these literary works stimulate the imagination, they regrettably provide no empirical evidence to inform our current investigation.
Stretching the boundaries of scholarly rigor, the authors also consulted an assortment of eclectic sources, including but not limited to memes, viral videos, and overheard conversations in coffee shops. Furthermore, unorthodox research methods involved a thorough analysis of grocery store receipts, particularly those from establishments known for their exceptionally corny jokes.
In sum, the existing literature hints at a gap in our understanding of the potential link between GMO corn production in South Dakota and expressions of exasperation in online search queries. This motivates our present endeavor to explore this unanticipated correlation, which may possess implications far beyond the confines of academic inquiry.

[[RESULTS]]
The results of our study revealed a staggering correlation coefficient of 0.9137392 between the use of genetically modified organisms (GMO) in corn grown in South Dakota and the frequency of Google searches for "I can't even" from 2004 to 2023. The r-squared value of 0.8349194 further illustrates the strong relationship between these seemingly unrelated variables. As if that weren't enough, the p-value of less than 0.01 cements the statistical significance of this unexpected association.
The scatterplot (Fig. 1) visually encapsulates the strength of the correlation, leaving little room for doubt about the connection between GMO corn and exasperated internet users. It seems that the debate surrounding GMO crops has now been sprinkled with a generous helping of internet humor, making this a-cornucopia of unexpected findings.
The robustness of the correlation prompts us to ponder whether the physiological effects of GMO corn extend beyond the agricultural realm and into the online domain. Could it be that the frustrations of internet users are linked, albeit indirectly, to the cultivation of maize in the Corn Belt? While the exact mechanism behind this correlation eludes us, there's no denying that this research has corn-ered a rather unanticipated discovery.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The findings of this study have lent support to the scant prior research that has hinted at the potential connection between GMO corn cultivation in South Dakota and the frequency of "I can't even" Google searches. While the literature review playfully delved into non-traditional sources, including grocery store receipts and corny jokes, the results of this investigation have concretely demonstrated a significant correlation between these seemingly disparate phenomena.

The robust correlation coefficient of 0.9137392 and the r-squared value of 0.8349194 uphold the unconventional link between GMO corn and online exasperation, echoing the prior studies' subtle insinuations about the unexplored relationship. Despite the lighthearted tone of the literature review, the serious statistical significance of the p-value of less than 0.01 underscores the credibility of this unexpected association. It appears that the agricultural practices in South Dakota's cornfields may be influencing not only the physiological composition of maize but also the exasperation levels of internet users.

Delving into this unanticipated correlation, it is evident that the study has shed inadvertently humorous light on the interplay between agricultural practices and humorous digital expressions of "I can't even." The results may challenge the existing perception of the internet as an ethereal realm disconnected from the physical world, as it appears that frustrations of online users are linked, albeit indirectly, to the cultivation of GMO corn in the Corn Belt. The unexpected nature of this discovery may prompt future researchers to carefully consider the potential unexpected consequences of agronomic practices on digital culture.

This research has not only unveiled a peculiar correlation but has also humorously seasoned the ongoing dialogue surrounding GMO crops with a dash of internet humor. The interdisciplinary nature of this study, acknowledging both the lightheartedness and the statistical significance, underscores the importance of exploring unanticipated connections and approaching scholarly inquiry with an open mind. These results prompt us to consider the far-reaching implications of agricultural practices, reminding us that even in the world of scholarly research, one can't even predict where the next unexpected correlation will crop up.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between GMO use in corn grown in South Dakota and Google searches for 'i cant even'. Make lots of jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Maizey or Maybes: The Correlation Between GMO Corn in South Dakota and 'I Can't Even' Google Searches"

[[ABSTRACT]]
The cultivation of genetically modified organisms (GMO) in agriculture has spurred endless debates, but could there be a link between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? In this study, we employed data from the USDA and Google Trends to examine the potential connection. Our findings revealed a surprisingly strong correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 from 2004 to 2023. While the reasons for this intriguing correlation remain uncertain, it appears that the agricultural practices in the Corn Belt may be influencing both the physiology of maize and the exasperation levels of internet users. This research not only sheds light on the interplay between agricultural practices and online expressions of frustration but also adds a humorous twist to the ongoing dialogue surrounding GMO crops.

[[INTRDUCTION]]
The cultivation of genetically modified organisms (GMO) in agriculture has given rise to a plethora of discussions, debates, and a-maize-ing puns (see what I did there?). But could there be a kernel of truth to the seemingly corny connection between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? This study seeks to shed light on this unexpectedly captivating correlation.
As the never-ending saga of GMO debates continues, research has tiptoed into peculiar territories, and this study is no exception. We aimed to plow through the data from the USDA and Google Trends to unearth whether there was any discernible relationship between the cultivation of GMO corn in the heart of South Dakota and the online expression of exasperation. Our findings have peeled back a layer of intrigue in revealing a surprisingly robust correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 during the years 2004 to 2023. It seems, despite our initial skepticism, that we aren't just cornfused after all.
While it may seem like a kernel of corny humor, this research couldn't resist the urge to explore the uncharted territory of agricultural practices and internet expression. Perhaps, it appears, that the physiology of maize isn't the only thing being influenced by agricultural techniques in the Corn Belt. This study not only contributes to the ongoing dialogue surrounding GMO crops but also adds an unexpected, popcorn-worthy twist to the discourse. After all, where else would you find an academic paper that combines agriculture, internet searches, and puns in such a delightful mixture?

[[RESULTS]]
The results of our study revealed a staggering correlation coefficient of 0.9137392 between the use of genetically modified organisms (GMO) in corn grown in South Dakota and the frequency of Google searches for "I can't even" from 2004 to 2023. The r-squared value of 0.8349194 further illustrates the strong relationship between these seemingly unrelated variables. As if that weren't enough, the p-value of less than 0.01 cements the statistical significance of this unexpected association.
The scatterplot (Fig. 1) visually encapsulates the strength of the correlation, leaving little room for doubt about the connection between GMO corn and exasperated internet users. It seems that the debate surrounding GMO crops has now been sprinkled with a generous helping of internet humor, making this a-cornucopia of unexpected findings.
The robustness of the correlation prompts us to ponder whether the physiological effects of GMO corn extend beyond the agricultural realm and into the online domain. Could it be that the frustrations of internet users are linked, albeit indirectly, to the cultivation of maize in the Corn Belt? While the exact mechanism behind this correlation eludes us, there's no denying that this research has corn-ered a rather unanticipated discovery.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, this study has revealed a corn-nected relationship between the use of GMO in South Dakota's cornfields and the frequency of "I can't even" Google searches, as surprising as finding a single unpopped kernel in a bag of microwave popcorn. The robust correlation coefficient and statistically significant p-value leave little room for doubt, just as a corn maze leaves little room for a straightforward path. It is clear that the agricultural practices in the Corn Belt may be influencing not only the physiology of maize but also the exasperation levels of internet users, creating a crop of unexpected findings that should not be husked away lightly.

While the reasons behind this correlation remain shrouded in mystery, it seems that the influence of GMO corn may extend beyond the farm to the vast expanse of the internet, leaving users "ear-itated" in its wake. As we close the book on this study, it is clear that the interplay between agricultural practices and online expressions of frustration is a-maize-ingly complex, offering a kernel of humor in the ongoing discourse surrounding GMO crops.

Indeed, it seems that the scholarly community no longer needs to stalk this particular correlation further, as it has been harvested and presented in all its corny glory. This research has shed light on a unique, unexpected interconnection and planted the seed for future exploration. However, with a statistical significance rivaling the discovery of a four-leaf clover, it can be safely asserted that no more research is needed in this area - this relationship has certainly bean sprouted.


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 Maizey or Maybes: The Correlation Between GMO Corn in South Dakota and 'I Can't Even' Google Searches. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Agronomic 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 Maizey or Maybes: The Correlation Between GMO Corn in South Dakota and 'I Can't Even' Google Searches. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Ethnobotanical Research and Innovation


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 Maizey or Maybes: The Correlation Between GMO Corn in South Dakota and 'I Can't Even' Google Searches with an abstract of The cultivation of genetically modified organisms (GMO) in agriculture has spurred endless debates, but could there be a link between GMO use in South Dakota's cornfields and the exasperated cry of "I can't even" in internet searches? In this study, we employed data from the USDA and Google Trends to examine the potential connection. Our findings revealed a surprisingly strong correlation coefficient of 0.9137392 and a statistically significant p-value of less than 0.01 from 2004 to 2023. While the reasons for this intriguing correlation remain uncertain, it appears that the agricultural practices in the Corn Belt may be influencing both the physiology of maize and the exasperation levels of internet users. This research not only sheds light on the interplay between agricultural practices and online expressions of frustration but also adds a humorous twist to the ongoing dialogue surrounding GMO crops.

ChatGPT:

GMO corn, South Dakota, agriculture, genetically modified organisms, GMO use, internet searches, Google Trends, USDA data, correlation coefficient, p-value, Corn Belt, maize physiology, frustration levels, online expressions, agricultural practices, GMO crops.

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



Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error


Data details

GMO use in corn grown in South Dakota
Detailed data title: Percent of all corn planted in South Dakota genetically modified with both Bt and HT
Source: USDA
See what else correlates with GMO use in corn grown in South Dakota

Google searches for 'i cant even'
Detailed data title: Relative volume of Google searches for 'i cant even' (Worldwide, without quotes)
Source: Google Trends
Additional Info: Relative search volume (not absolute numbers)

See what else correlates with Google searches for 'i cant even'

Correlation r = 0.9137392 (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 = 0.8349194 (Coefficient of determination)
This means 83.5% of the change in the one variable (i.e., Google searches for 'i cant even') is predictable based on the change in the other (i.e., GMO use in corn grown in South Dakota) over the 20 years from 2004 through 2023.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.8E-8. 0.0000000183026916207774270000
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 0.91 in 1.8E-6% of random cases. Said differently, if you correlated 54,636,773 random variables You don't actually need 54 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 19 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 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.

[ 0.79, 0.97 ] 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.
20042005200620072008200920102011201220132014201520162017201820192020202120222023
GMO use in corn grown in South Dakota (GMO corn %)2122344358656064628280837877797980838487
Google searches for 'i cant even' (Rel. search volume)11.83332433.58333234.7537.560.2563.333354.333363.2570.833374.7571.166772.41676355.916764.08336572.083382.1111




Why this works

  1. 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.
  2. 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.
  3. 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([21,22,34,43,58,65,60,64,62,82,80,83,78,77,79,79,80,83,84,87,])
array_2 = np.array([11.8333,24,33.5833,32,34.75,37.5,60.25,63.3333,54.3333,63.25,70.8333,74.75,71.1667,72.4167,63,55.9167,64.0833,65,72.0833,82.1111,])
array_1_name = "GMO use in corn grown in South Dakota"
array_2_name = "Google searches for 'i cant even'"

# 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.

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:


View another random correlation

How fun was this correlation?

I'm genuinely thankful for your rating!


Correlation ID: 2406 · Black Variable ID: 749 · Red Variable ID: 1525
about · subscribe · emailme@tylervigen.com · twitter

CC BY 4.0