Spurious correlation #1,661 · 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 Wisconsin 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.

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 Wisconsin 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.

Download png, svg

AI explanation

The genetically modified corn in Wisconsin developed a new protein that inadvertently triggered existential crises in anyone who consumed it. As a result, people found themselves unable to even just like the corn couldn't even grow like regular corn, and the confusion led to a surge in searches for "i cant even." It was a-maize-ing and confusing times for everyone involved.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image that resembles a scene from 'Star Wars' with the following scenario: In a sun-drenched cornfield in Wisconsin, rows of tall, lush green corn stretch out as far as the eye can see. Among the golden stalks, a farmer carefully inspects his genetically modified corn plants, ensuring they are healthy and thriving. Nearby, a person on their smartphone is frantically typing "I can't even" into a Google search, their frustration evident as they navigate the internet for answers. The farmer's presence should be reminiscent of a Jedi, keeping the environment peaceful and serene, while the frustrated person's presence should evoke a sense of chaos and modern-day struggles. Instead of depicting a traditional 'Star Wars' scene, create an intriguing image that merges the tranquility of the cornfield with the modern frustration, infusing it with a touch of futuristic allure. 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 Wisconsin 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: An image that looks like it is a scene from 'Star Wars' Symbolism Charcoal Sci-fi fantacy An image that looks like it is a scene from 'Star Wars'
ChatGPT: An image that looks like it is a scene from 'Star Wars'

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 Wisconsin and Google searches for 'i cant even' together. Keep the description simple.
ChatGPT: In a sun-drenched cornfield in Wisconsin, rows of tall, lush green corn stretch out as far as the eye can see. Among the golden stalks, a farmer carefully inspects his genetically modified corn plants, ensuring they are healthy and thriving. Nearby, a person on their smartphone is frantically typing "I can't even" into a Google search, their frustration evident as they navigate the internet for answers.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ An image that looks like it is a scene from 'Star Wars' ] and depicting this scene: In a sun-drenched cornfield in Wisconsin, rows of tall, lush green corn stretch out as far as the eye can see. Among the golden stalks, a farmer carefully inspects his genetically modified corn plants, ensuring they are healthy and thriving. Nearby, a person on their smartphone is frantically typing "I can't even" into a Google search, their frustration evident as they navigate the internet for answers. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that resembles a scene from 'Star Wars' with the following scenario: In a sun-drenched cornfield in Wisconsin, rows of tall, lush green corn stretch out as far as the eye can see. Among the golden stalks, a farmer carefully inspects his genetically modified corn plants, ensuring they are healthy and thriving. Nearby, a person on their smartphone is frantically typing "I can't even" into a Google search, their frustration evident as they navigate the internet for answers. The farmer's presence should be reminiscent of a Jedi, keeping the environment peaceful and serene, while the frustrated person's presence should evoke a sense of chaos and modern-day struggles. Instead of depicting a traditional 'Star Wars' scene, create an intriguing image that merges the tranquility of the cornfield with the modern frustration, infusing it with a touch of futuristic allure.

*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 Wisconsin caused i cant even (Google searches for 'i cant even') to increase.

AI academic paper

(Because p < 0.01)

Kernel of Truth: Exploring the Interplay Between GMO Corn and 'I Can't Even' Google Searches in Wisconsin

The Journal of Agricultural Memeology

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between GMO use in corn grown in Wisconsin and Google searches for 'i cant even'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Kernel of Truth: Exploring the Interplay Between GMO Corn and 'I Can't Even' Google Searches in Wisconsin"

[[ABSTRACT]]
This study examined the fascinating relationship between the use of genetically modified organisms (GMOs) in corn cultivation in Wisconsin and the frequency of Google searches for the colloquial expression "I Can't Even." Utilizing data from the United States Department of Agriculture (USDA) and Google Trends, our research team sought to bring to light any potential connection between these seemingly unrelated phenomena. Surprisingly, a robust correlation coefficient of 0.9134915 and significant p-value (p < 0.01) were identified for the period spanning from 2004 to 2023, indicating a strong statistical association between the two variables. The implications of these findings are ripe with potential implications, with potential impacts on agriculture, social commentary, and even internet culture. This study thus sheds light on the corn-y relationship between GMOs and exasperation, providing food for thought for both researchers and laypersons alike.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
Genetically modified organisms (GMOs) have long been a subject of intense scrutiny and debate in the agricultural world. In recent years, the adoption of GMOs in corn cultivation has become increasingly common, with proponents lauding their potential to increase crop yields, improve resistance to pests, and reduce the need for chemical pesticides. Conversely, critics often express concerns about potential environmental impacts, effects on human health, and the domination of agribusiness conglomerates. This dichotomy of perspectives has cultivated a fertile ground for in-depth research into the implications of GMO use in corn production.
Amidst this backdrop of heated discourse, an unexpected and seemingly unrelated phenomenon has captured the attention of researchers and internet users alike. The colloquial expression "I Can't Even" has permeated popular culture, serving as a succinct, exasperated utterance often used to convey a sense of overwhelming emotional response. The term has garnered widespread usage across various social media platforms, serving as a linguistic marker of exasperation, disbelief, or astonishment. Its resonance in contemporary discourse has prompted inquiries into its implications within the realm of social commentary and linguistics.
In a convergence of seemingly disparate realms, our research team sought to explore the intriguing interplay between the use of GMOs in corn cultivation and the frequency of Google searches for the expression "I Can't Even" within the state of Wisconsin. Given the apparent disconnection between agricultural practices and online expression, our investigation aimed to unravel any potential entanglements that may underlie this peculiar relationship. By harnessing data from the United States Department of Agriculture (USDA) and Google Trends, we endeavored to unearth any hidden connections that may challenge traditional perceptions of cause and effect.
The aim of this study is to present a comprehensive analysis of the correlation between GMO corn cultivation and "I Can't Even" searches, thereby providing insight into the potential societal and cultural implications of agricultural practices. Our findings not only contribute to the dialogue surrounding GMOs and their impact on society but also offer a revealing glimpse into the intersection of digital trends and agricultural landscapes. As such, this investigation ventures beyond the realm of conventional agricultural research, delving into the rich tapestry of human expression and its unexpected ties to agricultural innovation.
In the following sections, we will elucidate our research methodology, data sources, analytical techniques, and the elucidation of our empirical findings. By addressing the correlation between GMO corn cultivation and expressions of exasperation, this study aims to offer a nuanced understanding of the interconnectedness of seemingly unrelated phenomena. Furthermore, we aim to cultivate fertile ground for further inquiry and spark contemplation on the unanticipated interplay between agriculture and linguistic meme-culture.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find that GMOs have been a subject of intense debate in the agricultural realm, as they boast the potential to bolster crop yields, enhance pest resistance, and diminish the reliance on chemical pesticides. Conversely, opponents express unease regarding potential environmental repercussions, impacts on human health, and the hegemony of agribusiness conglomerates. Amidst this dichotomy, the utilization of genetically modified organisms (GMOs) in the cultivation of corn has become increasingly prevalent.

Furthermore, "Doe and Jones" offer insights into the rise of colloquial expressions in popular culture. The term "I Can't Even," which has pervaded contemporary discourse as a succinct and exasperated utterance, serves as a marker of overwhelming emotional response across various social media platforms.

In the context of literature related to linguistic expressions, "Scholarly Work on Internet Slang" delves into the intricacies of contemporary linguistics, shedding light on the evolution and impact of digital vernacular. This body of work provides an understanding of the nuances and implications of internet-driven linguistic phenomena, setting the stage for an exploration of the unexpected interplay between agricultural practices and online expression.

In a further departure from traditional agricultural literature, "The Omnivore's Dilemma" by Michael Pollan offers an in-depth exploration of the modern food industry, while "The Grapes of Wrath" by John Steinbeck provides a poignant fictional account of agricultural struggles. These works, though not directly related to the specific interplay between GMO corn cultivation and linguistic expressions, serve as a reminder of the complex cultural and historical context that underpins agricultural practices.

Moving away from the realm of traditional academic literature, the authors came across an unexpected source of insight in the form of the backs of shampoo bottles. The ubiquitous nature of these items and their intriguing, albeit unrelated, content proved to be unexpectedly enlightening.

Overall, the literature on the subject provides a comprehensive backdrop for our investigation into the correlation between GMO corn cultivation and "I Can't Even" searches, with findings that serve both serious inquiry and a dash of unexpected humor.

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 Wisconsin and Google searches for 'i cant even'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
"Kernel of Truth: Exploring the Interplay Between GMO Corn and 'I Can't Even' Google Searches in Wisconsin"

[[ABSTRACT]]
This study examined the fascinating relationship between the use of genetically modified organisms (GMOs) in corn cultivation in Wisconsin and the frequency of Google searches for the colloquial expression "I Can't Even." Utilizing data from the United States Department of Agriculture (USDA) and Google Trends, our research team sought to bring to light any potential connection between these seemingly unrelated phenomena. Surprisingly, a robust correlation coefficient of 0.9134915 and significant p-value (p < 0.01) were identified for the period spanning from 2004 to 2023, indicating a strong statistical association between the two variables. The implications of these findings are ripe with potential implications, with potential impacts on agriculture, social commentary, and even internet culture. This study thus sheds light on the corn-y relationship between GMOs and exasperation, providing food for thought for both researchers and laypersons alike.

[[INTRODUCTION]]
INTRODUCTION
Genetically modified organisms (GMOs) have long been a subject of intense scrutiny and debate in the agricultural world. In recent years, the adoption of GMOs in corn cultivation has become increasingly common, with proponents lauding their potential to increase crop yields, improve resistance to pests, and reduce the need for chemical pesticides. Conversely, critics often express concerns about potential environmental impacts, effects on human health, and the domination of agribusiness conglomerates. This dichotomy of perspectives has cultivated a fertile ground for in-depth research into the implications of GMO use in corn production.
Amidst this backdrop of heated discourse, an unexpected and seemingly unrelated phenomenon has captured the attention of researchers and internet users alike. The colloquial expression "I Can't Even" has permeated popular culture, serving as a succinct, exasperated utterance often used to convey a sense of overwhelming emotional response. The term has garnered widespread usage across various social media platforms, serving as a linguistic marker of exasperation, disbelief, or astonishment. Its resonance in contemporary discourse has prompted inquiries into its implications within the realm of social commentary and linguistics.
In a convergence of seemingly disparate realms, our research team sought to explore the intriguing interplay between the use of GMOs in corn cultivation and the frequency of Google searches for the expression "I Can't Even" within the state of Wisconsin. Given the apparent disconnection between agricultural practices and online expression, our investigation aimed to unravel any potential entanglements that may underlie this peculiar relationship. By harnessing data from the United States Department of Agriculture (USDA) and Google Trends, we endeavored to unearth any hidden connections that may challenge traditional perceptions of cause and effect.
The aim of this study is to present a comprehensive analysis of the correlation between GMO corn cultivation and "I Can't Even" searches, thereby providing insight into the potential societal and cultural implications of agricultural practices. Our findings not only contribute to the dialogue surrounding GMOs and their impact on society but also offer a revealing glimpse into the intersection of digital trends and agricultural landscapes. As such, this investigation ventures beyond the realm of conventional agricultural research, delving into the rich tapestry of human expression and its unexpected ties to agricultural innovation.
In the following sections, we will elucidate our research methodology, data sources, analytical techniques, and the elucidation of our empirical findings. By addressing the correlation between GMO corn cultivation and expressions of exasperation, this study aims to offer a nuanced understanding of the interconnectedness of seemingly unrelated phenomena. Furthermore, we aim to cultivate fertile ground for further inquiry and spark contemplation on the unanticipated interplay between agriculture and linguistic meme-culture.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection:
The data utilized in this study was harvested from the extensive fields of the internet, with a specific focus on sources such as the United States Department of Agriculture (USDA) and Google Trends. The time span for data collection extended from 2004 to 2023, encompassing a significant period of agricultural and digital evolution. The team employed advanced web-crawling techniques, traversing the digital landscape in search of pertinent information, akin to intrepid explorers navigating through a dense maize of online data. After laboriously sifting through countless web pages and information sources, the research team meticulously compiled a comprehensive dataset for analysis.

GMO Corn Cultivation Metrics:
In order to evaluate the extent of genetically modified organism (GMO) utilization in corn cultivation, the research team examined a range of agricultural indicators. These included the prevalence of GMO corn seeds in Wisconsin, the proportion of GMO corn acreage to total corn acreage, and the frequency of GMO-related discourse within agricultural publications. The team navigated through a labyrinth of agricultural reports and databases, akin to seekers in search of a kernel of truth amidst the vast expanse of cornfields.

"I Can't Even" Google Search Analysis:
To assess the frequency of Google searches for the expression "I Can't Even" within the state of Wisconsin, the research team employed Google Trends data. This tool provided invaluable insights into the temporal patterns and geographic distribution of such searches, allowing for a nuanced understanding of digital exasperation dynamics. Furthermore, the team applied sophisticated linguistic analysis techniques to decipher the underlying sentiments and contextual nuances embedded within these online expressions of exasperation.

Statistical Analysis:
The statistical analysis encompassed in this study involved correlation analysis, regression modeling, and temporal trend assessments. The research team wielded an arsenal of statistical software, unleashing the power of mathematical algorithms to unveil the intricate relationship between GMO corn cultivation and expressions of exasperation. Through rigorous statistical scrutiny, the team meticulously calculated correlation coefficients, evaluated regression models, and discerned any temporal shifts in the interplay between GMO usage and digital exasperation.

Experimental Controls:
Given the complexity of the interplay between agricultural practices and digital trends, the research team implemented robust controls to account for potential confounding variables. These controls encompassed meteorological factors, socio-economic dynamics, and broader internet trends, ensuring that the identified relationship between GMO corn cultivation and "I Can't Even" searches shone through with clarity, akin to a proverbial ear of corn standing resolute amidst a field of wheat.

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 Wisconsin and Google searches for 'i cant even'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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 0.9134915, r-squared of 0.8344667, 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]]
"Kernel of Truth: Exploring the Interplay Between GMO Corn and 'I Can't Even' Google Searches in Wisconsin"

[[ABSTRACT]]
This study examined the fascinating relationship between the use of genetically modified organisms (GMOs) in corn cultivation in Wisconsin and the frequency of Google searches for the colloquial expression "I Can't Even." Utilizing data from the United States Department of Agriculture (USDA) and Google Trends, our research team sought to bring to light any potential connection between these seemingly unrelated phenomena. Surprisingly, a robust correlation coefficient of 0.9134915 and significant p-value (p < 0.01) were identified for the period spanning from 2004 to 2023, indicating a strong statistical association between the two variables. The implications of these findings are ripe with potential implications, with potential impacts on agriculture, social commentary, and even internet culture. This study thus sheds light on the corn-y relationship between GMOs and exasperation, providing food for thought for both researchers and laypersons alike.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
Genetically modified organisms (GMOs) have long been a subject of intense scrutiny and debate in the agricultural world. In recent years, the adoption of GMOs in corn cultivation has become increasingly common, with proponents lauding their potential to increase crop yields, improve resistance to pests, and reduce the need for chemical pesticides. Conversely, critics often express concerns about potential environmental impacts, effects on human health, and the domination of agribusiness conglomerates. This dichotomy of perspectives has cultivated a fertile ground for in-depth research into the implications of GMO use in corn production.
Amidst this backdrop of heated discourse, an unexpected and seemingly unrelated phenomenon has captured the attention of researchers and internet users alike. The colloquial expression "I Can't Even" has permeated popular culture, serving as a succinct, exasperated utterance often used to convey a sense of overwhelming emotional response. The term has garnered widespread usage across various social media platforms, serving as a linguistic marker of exasperation, disbelief, or astonishment. Its resonance in contemporary discourse has prompted inquiries into its implications within the realm of social commentary and linguistics.
In a convergence of seemingly disparate realms, our research team sought to explore the intriguing interplay between the use of GMOs in corn cultivation and the frequency of Google searches for the expression "I Can't Even" within the state of Wisconsin. Given the apparent disconnection between agricultural practices and online expression, our investigation aimed to unravel any potential entanglements that may underlie this peculiar relationship. By harnessing data from the United States Department of Agriculture (USDA) and Google Trends, we endeavored to unearth any hidden connections that may challenge traditional perceptions of cause and effect.
The aim of this study is to present a comprehensive analysis of the correlation between GMO corn cultivation and "I Can't Even" searches, thereby providing insight into the potential societal and cultural implications of agricultural practices. Our findings not only contribute to the dialogue surrounding GMOs and their impact on society but also offer a revealing glimpse into the intersection of digital trends and agricultural landscapes. As such, this investigation ventures beyond the realm of conventional agricultural research, delving into the rich tapestry of human expression and its unexpected ties to agricultural innovation.
In the following sections, we will elucidate our research methodology, data sources, analytical techniques, and the elucidation of our empirical findings. By addressing the correlation between GMO corn cultivation and expressions of exasperation, this study aims to offer a nuanced understanding of the interconnectedness of seemingly unrelated phenomena. Furthermore, we aim to cultivate fertile ground for further inquiry and spark contemplation on the unanticipated interplay between agriculture and linguistic meme-culture.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis of the data revealed a remarkably strong correlation between the use of genetically modified organisms (GMOs) in corn cultivation in Wisconsin and the frequency of Google searches for the expression "I Can't Even." During the 2004 to 2023 period, a correlation coefficient of 0.9134915 was determined, indicating a robust positive relationship between the two variables. The high coefficient of determination (r-squared = 0.8344667) further substantiates this association, signifying that approximately 83.45% of the variability in "I Can't Even" searches can be explained by the variability in GMO corn use. The p-value obtained was less than 0.01, signifying that the observed correlation is statistically significant.

Figure 1 depicts the scatterplot illustrating the striking correlation between GMO corn cultivation and the frequency of "I Can't Even" Google searches during the study period, serving as a visual testament to the connection uncovered by our analysis. The scatterplot unmistakably portrays a clear positive trend, highlighting the synchronous rise in GMO corn usage and the frequency of exasperated online expressions.

These findings suggest a conceivable interdependence between the agricultural landscape and digital discourse, weaving a narrative that transcends conventional conceptions of causality. The implications of this correlation extend beyond the realm of agriculture, permeating into the domains of linguistics, sociology, and internet culture. The unearthing of this unexpected relationship underscores the complexity of interconnected systems, inviting further exploration into the entangled tapestry of agricultural practices and societal expressions.

The remarkable strength of the identified correlation prompts contemplation on the potential influence of agricultural innovations on linguistic tropes. This revelation challenges traditional disciplinary boundaries, beckoning researchers to traverse uncharted territories where the fields of agriculture and online communication intersect. While the pursuit of knowledge often leads us down conventional paths, it is the discovery of unconventional relationships, such as the one unveiled in this study, that injects an element of surprise and intrigue into scholarly inquiry.

Overall, the elucidation of this correlation provides compelling food for thought, encouraging a reevaluation of the dynamics between agricultural advancements and cultural phenomena. This study exemplifies the unforeseen connections that can emerge from rigorous data analysis, shedding light on the corn-y relationship between GMOs and contemporary expressions of 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 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 Wisconsin and Google searches for 'i cant even'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
"Kernel of Truth: Exploring the Interplay Between GMO Corn and 'I Can't Even' Google Searches in Wisconsin"

[[ABSTRACT]]
This study examined the fascinating relationship between the use of genetically modified organisms (GMOs) in corn cultivation in Wisconsin and the frequency of Google searches for the colloquial expression "I Can't Even." Utilizing data from the United States Department of Agriculture (USDA) and Google Trends, our research team sought to bring to light any potential connection between these seemingly unrelated phenomena. Surprisingly, a robust correlation coefficient of 0.9134915 and significant p-value (p < 0.01) were identified for the period spanning from 2004 to 2023, indicating a strong statistical association between the two variables. The implications of these findings are ripe with potential implications, with potential impacts on agriculture, social commentary, and even internet culture. This study thus sheds light on the corn-y relationship between GMOs and exasperation, providing food for thought for both researchers and laypersons alike.

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find that GMOs have been a subject of intense debate in the agricultural realm, as they boast the potential to bolster crop yields, enhance pest resistance, and diminish the reliance on chemical pesticides. Conversely, opponents express unease regarding potential environmental repercussions, impacts on human health, and the hegemony of agribusiness conglomerates. Amidst this dichotomy, the utilization of genetically modified organisms (GMOs) in the cultivation of corn has become increasingly prevalent.
Furthermore, "Doe and Jones" offer insights into the rise of colloquial expressions in popular culture. The term "I Can't Even," which has pervaded contemporary discourse as a succinct and exasperated utterance, serves as a marker of overwhelming emotional response across various social media platforms.
In the context of literature related to linguistic expressions, "Scholarly Work on Internet Slang" delves into the intricacies of contemporary linguistics, shedding light on the evolution and impact of digital vernacular. This body of work provides an understanding of the nuances and implications of internet-driven linguistic phenomena, setting the stage for an exploration of the unexpected interplay between agricultural practices and online expression.
In a further departure from traditional agricultural literature, "The Omnivore's Dilemma" by Michael Pollan offers an in-depth exploration of the modern food industry, while "The Grapes of Wrath" by John Steinbeck provides a poignant fictional account of agricultural struggles. These works, though not directly related to the specific interplay between GMO corn cultivation and linguistic expressions, serve as a reminder of the complex cultural and historical context that underpins agricultural practices.
Moving away from the realm of traditional academic literature, the authors came across an unexpected source of insight in the form of the backs of shampoo bottles. The ubiquitous nature of these items and their intriguing, albeit unrelated, content proved to be unexpectedly enlightening.
Overall, the literature on the subject provides a comprehensive backdrop for our investigation into the correlation between GMO corn cultivation and "I Can't Even" searches, with findings that serve both serious inquiry and a dash of unexpected humor.

[[RESULTS]]
The statistical analysis of the data revealed a remarkably strong correlation between the use of genetically modified organisms (GMOs) in corn cultivation in Wisconsin and the frequency of Google searches for the expression "I Can't Even." During the 2004 to 2023 period, a correlation coefficient of 0.9134915 was determined, indicating a robust positive relationship between the two variables. The high coefficient of determination (r-squared = 0.8344667) further substantiates this association, signifying that approximately 83.45% of the variability in "I Can't Even" searches can be explained by the variability in GMO corn use. The p-value obtained was less than 0.01, signifying that the observed correlation is statistically significant.
Figure 1 depicts the scatterplot illustrating the striking correlation between GMO corn cultivation and the frequency of "I Can't Even" Google searches during the study period, serving as a visual testament to the connection uncovered by our analysis. The scatterplot unmistakably portrays a clear positive trend, highlighting the synchronous rise in GMO corn usage and the frequency of exasperated online expressions.
These findings suggest a conceivable interdependence between the agricultural landscape and digital discourse, weaving a narrative that transcends conventional conceptions of causality. The implications of this correlation extend beyond the realm of agriculture, permeating into the domains of linguistics, sociology, and internet culture. The unearthing of this unexpected relationship underscores the complexity of interconnected systems, inviting further exploration into the entangled tapestry of agricultural practices and societal expressions.
The remarkable strength of the identified correlation prompts contemplation on the potential influence of agricultural innovations on linguistic tropes. This revelation challenges traditional disciplinary boundaries, beckoning researchers to traverse uncharted territories where the fields of agriculture and online communication intersect. While the pursuit of knowledge often leads us down conventional paths, it is the discovery of unconventional relationships, such as the one unveiled in this study, that injects an element of surprise and intrigue into scholarly inquiry.
Overall, the elucidation of this correlation provides compelling food for thought, encouraging a reevaluation of the dynamics between agricultural advancements and cultural phenomena. This study exemplifies the unforeseen connections that can emerge from rigorous data analysis, shedding light on the corn-y relationship between GMOs and contemporary expressions of exasperation.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

The robust correlation coefficient and statistically significant p-value obtained in the present study provide compelling evidence supporting the intriguing connection between GMO corn cultivation in Wisconsin and the frequency of "I Can't Even" Google searches. Our findings underscore the surprising interplay between agricultural practices and digital expressions of exasperation, inviting contemplation on the multifaceted influences that shape societal discourse. The observation of a strong positive relationship between these seemingly disparate phenomena challenges conventional expectations and expands the purview of interdisciplinary inquiry.

The literature review presented a comprehensive backdrop for our investigation, incorporating serious inquiry with a dash of unexpected humor, which was also found unexpectedly in the content of shampoo bottles. We were particularly intrigued by the rise of colloquial expressions in popular culture and their presence across various social media platforms, as highlighted in the works of "Doe and Jones." Subsequently, the unexpected source of insight found in the shampoo bottles offered an unexpected twist in our research journey, prompting contemplation on the diverse and unconventional reservoirs of knowledge. In integrating these seemingly disparate sources of inspiration, we were able to approach our investigation with a nuanced perspective.

The identified correlation between GMO corn cultivation and "I Can't Even" Google searches aligns with prior research that has explored the influence of agricultural practices on contemporary linguistic phenomena. The findings corroborate the notion that societal expressions are intricately intertwined with broader environmental and cultural contexts, hinting at the potential for agricultural innovations to shape linguistic tropes. This revelation challenges traditional boundaries in scholarly inquiry and underscores the need for interdisciplinary exploration into the interconnected nature of seemingly unrelated domains.

The emergence of this unexpected relationship highlights the complex and intertwined nature of agricultural practices and societal expressions, emphasizing the need for a holistic understanding of the interdependencies that underpin diverse facets of human experience. As we navigate the uncharted territories where the fields of agriculture and online communication intersect, it is essential to embrace the element of surprise and intrigue in scholarly inquiry, as discoveries like the one uncovered in this study continue to push the boundaries of conventional knowledge.

In conclusion, the correlation between GMO corn use and "I Can't Even" searches offers a thought-provoking lens through which to reevaluate the dynamics between agricultural innovations and cultural phenomena. The serendipitous nature of this discovery serves as a testament to the unforeseen connections that can emerge from rigorous data analysis, breathing life into the pursuit of knowledge and fostering curiosity in unforeseen relationships.

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 Wisconsin and Google searches for 'i cant even'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
"Kernel of Truth: Exploring the Interplay Between GMO Corn and 'I Can't Even' Google Searches in Wisconsin"

[[ABSTRACT]]
This study examined the fascinating relationship between the use of genetically modified organisms (GMOs) in corn cultivation in Wisconsin and the frequency of Google searches for the colloquial expression "I Can't Even." Utilizing data from the United States Department of Agriculture (USDA) and Google Trends, our research team sought to bring to light any potential connection between these seemingly unrelated phenomena. Surprisingly, a robust correlation coefficient of 0.9134915 and significant p-value (p < 0.01) were identified for the period spanning from 2004 to 2023, indicating a strong statistical association between the two variables. The implications of these findings are ripe with potential implications, with potential impacts on agriculture, social commentary, and even internet culture. This study thus sheds light on the corn-y relationship between GMOs and exasperation, providing food for thought for both researchers and laypersons alike.

[[INTRDUCTION]]
INTRODUCTION
Genetically modified organisms (GMOs) have long been a subject of intense scrutiny and debate in the agricultural world. In recent years, the adoption of GMOs in corn cultivation has become increasingly common, with proponents lauding their potential to increase crop yields, improve resistance to pests, and reduce the need for chemical pesticides. Conversely, critics often express concerns about potential environmental impacts, effects on human health, and the domination of agribusiness conglomerates. This dichotomy of perspectives has cultivated a fertile ground for in-depth research into the implications of GMO use in corn production.
Amidst this backdrop of heated discourse, an unexpected and seemingly unrelated phenomenon has captured the attention of researchers and internet users alike. The colloquial expression "I Can't Even" has permeated popular culture, serving as a succinct, exasperated utterance often used to convey a sense of overwhelming emotional response. The term has garnered widespread usage across various social media platforms, serving as a linguistic marker of exasperation, disbelief, or astonishment. Its resonance in contemporary discourse has prompted inquiries into its implications within the realm of social commentary and linguistics.
In a convergence of seemingly disparate realms, our research team sought to explore the intriguing interplay between the use of GMOs in corn cultivation and the frequency of Google searches for the expression "I Can't Even" within the state of Wisconsin. Given the apparent disconnection between agricultural practices and online expression, our investigation aimed to unravel any potential entanglements that may underlie this peculiar relationship. By harnessing data from the United States Department of Agriculture (USDA) and Google Trends, we endeavored to unearth any hidden connections that may challenge traditional perceptions of cause and effect.
The aim of this study is to present a comprehensive analysis of the correlation between GMO corn cultivation and "I Can't Even" searches, thereby providing insight into the potential societal and cultural implications of agricultural practices. Our findings not only contribute to the dialogue surrounding GMOs and their impact on society but also offer a revealing glimpse into the intersection of digital trends and agricultural landscapes. As such, this investigation ventures beyond the realm of conventional agricultural research, delving into the rich tapestry of human expression and its unexpected ties to agricultural innovation.
In the following sections, we will elucidate our research methodology, data sources, analytical techniques, and the elucidation of our empirical findings. By addressing the correlation between GMO corn cultivation and expressions of exasperation, this study aims to offer a nuanced understanding of the interconnectedness of seemingly unrelated phenomena. Furthermore, we aim to cultivate fertile ground for further inquiry and spark contemplation on the unanticipated interplay between agriculture and linguistic meme-culture.

[[RESULTS]]
The statistical analysis of the data revealed a remarkably strong correlation between the use of genetically modified organisms (GMOs) in corn cultivation in Wisconsin and the frequency of Google searches for the expression "I Can't Even." During the 2004 to 2023 period, a correlation coefficient of 0.9134915 was determined, indicating a robust positive relationship between the two variables. The high coefficient of determination (r-squared = 0.8344667) further substantiates this association, signifying that approximately 83.45% of the variability in "I Can't Even" searches can be explained by the variability in GMO corn use. The p-value obtained was less than 0.01, signifying that the observed correlation is statistically significant.
Figure 1 depicts the scatterplot illustrating the striking correlation between GMO corn cultivation and the frequency of "I Can't Even" Google searches during the study period, serving as a visual testament to the connection uncovered by our analysis. The scatterplot unmistakably portrays a clear positive trend, highlighting the synchronous rise in GMO corn usage and the frequency of exasperated online expressions.
These findings suggest a conceivable interdependence between the agricultural landscape and digital discourse, weaving a narrative that transcends conventional conceptions of causality. The implications of this correlation extend beyond the realm of agriculture, permeating into the domains of linguistics, sociology, and internet culture. The unearthing of this unexpected relationship underscores the complexity of interconnected systems, inviting further exploration into the entangled tapestry of agricultural practices and societal expressions.
The remarkable strength of the identified correlation prompts contemplation on the potential influence of agricultural innovations on linguistic tropes. This revelation challenges traditional disciplinary boundaries, beckoning researchers to traverse uncharted territories where the fields of agriculture and online communication intersect. While the pursuit of knowledge often leads us down conventional paths, it is the discovery of unconventional relationships, such as the one unveiled in this study, that injects an element of surprise and intrigue into scholarly inquiry.
Overall, the elucidation of this correlation provides compelling food for thought, encouraging a reevaluation of the dynamics between agricultural advancements and cultural phenomena. This study exemplifies the unforeseen connections that can emerge from rigorous data analysis, shedding light on the corn-y relationship between GMOs and contemporary expressions of exasperation.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the findings of this study paint a compelling picture of the intertwined dance between GMO corn cultivation in Wisconsin and the frequency of "I Can't Even" Google searches. The remarkably strong correlation identified, indicated by a robust correlation coefficient and a statistically significant p-value, serves as a testament to the unexpected interconnectedness of seemingly disparate phenomena. The visual representation in Figure 1 vividly captures the synchronous rise in GMO corn usage and the frequency of exasperated online expressions, serving as a striking visual testament to the interplay between agricultural innovation and modern linguistic tropes.

The implications of this correlation extend beyond the domain of agriculture, offering a whimsical panorama of potential influences on linguistic expressions, social commentary, and the digital zeitgeist. As we ponder the kernels of truth unearthed in this study, it becomes evident that the landscape of human expression is not merely shaped by cultural trends and digital influences but also by the undercurrents of agricultural innovation. This revelation beckons researchers and enthusiasts alike to traverse uncharted territories where the fields of agriculture and colloquial expression converge, cultivating a fertile ground for contemplation and scholarly inquiry. The unanticipated discovery of this compelling relationship injects an element of surprise and whimsy into the realm of academic exploration, reminding us that the pursuit of knowledge often leads us to unexpected, ear-resistible revelations.

While the connection between GMO corn cultivation and "I Can't Even" searches might appear to be a-maize-ing and corny at first glance, probing deeper into this correlation unearths thought-provoking reflections on the interwoven fabric of agricultural practices and contemporary expressions of exasperation. Nevertheless, on the moss-t pressing exactly what pressing issues has this study resolved, there is still a-rose-m for further inquiry, and this is unlikely due to the rigour and thoroughness of the study, rather this conclusion is based on the understandably limited audience who might be fascinated by research in this area. Hence, at corn-clusion, no more research is needed in this area.

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 Kernel of Truth: Exploring the Interplay Between GMO Corn and 'I Can't Even' Google Searches in Wisconsin. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Agricultural Memeology

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 Kernel of Truth: Exploring the Interplay Between GMO Corn and 'I Can't Even' Google Searches in Wisconsin. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Agricultural Innovation and Genomic Research (SAIGR)

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 Kernel of Truth: Exploring the Interplay Between GMO Corn and 'I Can't Even' Google Searches in Wisconsin with an abstract of This study examined the fascinating relationship between the use of genetically modified organisms (GMOs) in corn cultivation in Wisconsin and the frequency of Google searches for the colloquial expression "I Can't Even." Utilizing data from the United States Department of Agriculture (USDA) and Google Trends, our research team sought to bring to light any potential connection between these seemingly unrelated phenomena. Surprisingly, a robust correlation coefficient of 0.9134915 and significant p-value (p < 0.01) were identified for the period spanning from 2004 to 2023, indicating a strong statistical association between the two variables. The implications of these findings are ripe with potential implications, with potential impacts on agriculture, social commentary, and even internet culture. This study thus sheds light on the corn-y relationship between GMOs and exasperation, providing food for thought for both researchers and laypersons alike.

ChatGPT:

"GMO corn cultivation Wisconsin," "Google searches 'I Can't Even' correlation," "United States Department of Agriculture USDA data," "Google Trends analysis GMO corn searches," "Statistical association GMO corn Google searches," "Implications GMO corn cultivation," "Agricultural impact GMO corn," "Social commentary Google searches correlation," "Internet culture GMO corn searches."

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

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: ^{See full details} Relative search volume (not absolute numbers)

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

Correlation r = 0.9134915 (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 = 0.8344667 (Coefficient of determination)
This means 83.4% 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 Wisconsin) over the 20 years from 2004 through 2023.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.9E-8.^Show 0.0000000187638658886095100000
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 0.91 in 1.9E-6% of random cases. Said differently, if you correlated 53,293,922 random variables^Note You don't actually need 53 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, ^Note 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)
^{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.

	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022	2023
GMO use in corn grown in Wisconsin (GMO corn %)	2	6	10	22	35	37	38	41	53	63	72	70	70	71	72	72	76	76	77	80
Google searches for 'i cant even' (Rel. search volume)	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

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([2,6,10,22,35,37,38,41,53,63,72,70,70,71,72,72,76,76,77,80,])
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 Wisconsin"
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. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
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Portable line chart (png)
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Line chart for only GMO use in corn grown in Wisconsin
Line chart for only Google searches for 'i cant even'
AI-generated correlation image
The spurious research paper: Kernel of Truth: Exploring the Interplay Between GMO Corn and 'I Can't Even' Google Searches in Wisconsin

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Correlation ID: 1661 · Black Variable ID: 751 · Red Variable ID: 1525


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