Spurious correlation #2,699 · 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 soybeans in North Dakota and the second variable is Geothermal power generated in Russia. The chart goes from 2000 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is GMO use in soybeans in North Dakota and the second variable is Geothermal power generated in Russia. The chart goes from 2000 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the soybeans in North Dakota became more genetically modified, they inadvertently started emitting a tiny, undetectable signal that resonated with the Earth's core. This signal acted as a catalyst for increased geothermal activity in Russia. It's like the soybeans were saying, "Let's spice things up underground," leading to a bean-ergetic boost in geothermal power production. Who knew that soybeans had a hot line to Mother Earth's kitchen?

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a futuristic North Dakota landscape where towering GMO soybean plants with deep roots stretch toward the sky. Show the Earth rumbling and cracking beneath the plants as geothermal activity surges unexpectedly. In the distance, depict a representation of Russia with the ground vibrating and geothermal power generation stations being activated, all sparked by the growth of the soybeans. This image should feel both high-tech and natural, with a sense of awe and wonder at the interconnectedness of the Earth's systems. 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 soybeans in North Dakota and Geothermal power generated in Russia. 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: 3D Pixar Style Symbolism a meme High-tech Data cyber art
ChatGPT: High-tech

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 soybeans in North Dakota and Geothermal power generated in Russia, in the following situation: As GMO soybeans in North Dakota grew taller and taller, they extended their roots deep into the Earth's crust, triggering an unexpected surge in geothermal activity that reverberated all the way to Russia, boosting their geothermal power generation.. Keep the description simple.
ChatGPT: In North Dakota, towering GMO soybean plants with deep roots caused rumblings in the Earth, as geothermal activity surged unexpectedly. Across the globe, in Russia, the ground vibrated with increased geothermal power generation, sparked by the distant growth of the soybeans.

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: [ High-tech ] and depicting this scene: In North Dakota, towering GMO soybean plants with deep roots caused rumblings in the Earth, as geothermal activity surged unexpectedly. Across the globe, in Russia, the ground vibrated with increased geothermal power generation, sparked by the distant growth of the soybeans. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a futuristic North Dakota landscape where towering GMO soybean plants with deep roots stretch toward the sky. Show the Earth rumbling and cracking beneath the plants as geothermal activity surges unexpectedly. In the distance, depict a representation of Russia with the ground vibrating and geothermal power generation stations being activated, all sparked by the growth of the soybeans. This image should feel both high-tech and natural, with a sense of awe and wonder at the interconnectedness of the Earth's systems.

*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 soybeans in North Dakota caused Geothermal power generated in Russia to increase.

AI academic paper

(Because p < 0.01)

From Soybeans to Steam: The GMO-Geothermal Connection Revealed

The Journal of Agricultural Alchemy

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 soybeans in North Dakota and Geothermal power generated in Russia. 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]]
From Soybeans to Steam: The GMO-Geothermal Connection Revealed

[[ABSTRACT]]
This paper investigates the surprising link between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. Despite the vast geographical distance between the two, our research team has identified a remarkable correlation that cannot be dismissed as pure coincidence. Using data from the USDA and Energy Information Administration spanning from 2000 to 2021, we have calculated a correlation coefficient of 0.9513419, with a statistically significant p-value of less than 0.01. Our findings raise intriguing questions about the potential transcontinental transmission of agricultural and energy influences - a phenomenon we playfully dub "GMO-thermal power." This unexpected connection challenges our traditional understanding of agricultural and energy systems and underscores the need for interdisciplinary examination of seemingly unrelated phenomena.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The relationship between agricultural practices and energy generation has long been a topic of interest, primarily in the context of biofuel production, land use for renewable energy sources, and the environmental impacts of farming activities. However, the specific connection between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia has, until now, remained largely unexplored and shrouded in mystery.
In a serendipitous turn of events, our research team stumbled upon this peculiar link while analyzing disparate datasets related to agricultural and energy production. What began as a seemingly routine examination of soybean cultivation practices and energy usage patterns soon metamorphosed into a captivating intellectual puzzle. The seemingly incongruous pairing of soybeans and steam - the former representing a staple of modern agriculture and the latter a hallmark of geothermal energy generation - beckoned us to delve deeper into the potential correlation between these two seemingly unrelated domains.
One might be inclined to dismiss this correlation as mere happenstance, a chance alignment of statistical anomalies in two distant spheres of human activity. Yet, with each probing statistical test and nuanced analysis, the robustness of the relationship between the use of genetically modified soybeans in the heartland of North Dakota and the extraction of geothermal power in the expansive Russian landscape became increasingly apparent.
Our discovery of this unexpected association challenges conventional wisdom and stimulates contemplation on the far-reaching ripple effects of human endeavors. It invites us to marvel at the intricate, intricate dance of agricultural and energy systems across continents, urging our minds to embrace the complex interconnectedness of seemingly disparate phenomena. Indeed, this connection between GMO soybeans and geothermal power defies the boundaries of traditional disciplinary silos and beckons us to innovate novel analytical lenses to apprehend the subtle interplay of human activities in shaping our world.
As we embark upon the exposition of our groundbreaking findings, we invite our esteemed readers to accompany us on a journey of exploration and scrutiny, as we unravel the enigmatic threads that weave the fabric of "GMO-thermal power." This revelation promises to disrupt entrenched paradigms and ignite a fervor of interdisciplinary discourse, redefining the frontiers of agricultural and energy research in unforeseen ways. With this fervent anticipation, we present our discerning investigation into the intriguing correlation between genetically modified soybeans and geothermal power generation - a revelation that defies expectation and entices the inquiring intellect.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find a positive correlation between the cultivation of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. This unexpected relationship has sparked considerable intrigue among researchers, prompting a broader exploration of the potential interplay between agricultural practices and energy production on a global scale.

Similarly, in "Doe and Jones," the authors delve into the complex dynamics of agricultural land use and energy generation, shedding light on the nuanced connections that underpin these seemingly distinct domains. These studies serve as the foundational bedrock upon which our investigation into the GMO-geothermal connection unfolds.

Expanding beyond the realm of traditional academic papers, works such as "GMOs and You: A Comprehensive Guide" and "Geothermal Energy: From Theory to Practice" have provided invaluable insights into the individual components of our study. However, it is the fusion of these disparate elements that truly captures the whimsical imagination and challenges the boundaries of scholarly inquiry.

In the realm of fiction, novels such as "The Soybean Conspiracy" and "The Steam Mysteries" may appear unrelated to our empirical investigation. However, upon deeper introspection, these literary creations offer a glimpse into the collective unconscious, where the seeds of seemingly incongruous connections are sown.

As we journey further into our exploration of the GMO-geothermal enigma, it is imperative to acknowledge the unconventional sources that have informed our understanding. From decoding the cryptic symbolism of crop rotation in supermarket aisle three to unraveling the metaphysical implications of geothermal exploration in the context of ancient folklore, our literature review transcends the confines of conventional scholarship.

With an unyielding spirit of inquiry, our research team has probed into the unlikeliest of reservoirs of knowledge, including but not limited to deciphering the implications of grocery store receipts and divining the otherworldly wisdom embedded within cereal box packaging. These unorthodox sources, while whimsical in appearance, have been integral to our comprehensive and multidimensional examination of the intricate web that binds soybeans and steam.

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 soybeans in North Dakota and Geothermal power generated in Russia. Make lots of 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 Energy Information Administration . You used data from 2000 to 2021

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
From Soybeans to Steam: The GMO-Geothermal Connection Revealed

[[ABSTRACT]]
This paper investigates the surprising link between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. Despite the vast geographical distance between the two, our research team has identified a remarkable correlation that cannot be dismissed as pure coincidence. Using data from the USDA and Energy Information Administration spanning from 2000 to 2021, we have calculated a correlation coefficient of 0.9513419, with a statistically significant p-value of less than 0.01. Our findings raise intriguing questions about the potential transcontinental transmission of agricultural and energy influences - a phenomenon we playfully dub "GMO-thermal power." This unexpected connection challenges our traditional understanding of agricultural and energy systems and underscores the need for interdisciplinary examination of seemingly unrelated phenomena.

[[INTRODUCTION]]
INTRODUCTION
The relationship between agricultural practices and energy generation has long been a topic of interest, primarily in the context of biofuel production, land use for renewable energy sources, and the environmental impacts of farming activities. However, the specific connection between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia has, until now, remained largely unexplored and shrouded in mystery.
In a serendipitous turn of events, our research team stumbled upon this peculiar link while analyzing disparate datasets related to agricultural and energy production. What began as a seemingly routine examination of soybean cultivation practices and energy usage patterns soon metamorphosed into a captivating intellectual puzzle. The seemingly incongruous pairing of soybeans and steam - the former representing a staple of modern agriculture and the latter a hallmark of geothermal energy generation - beckoned us to delve deeper into the potential correlation between these two seemingly unrelated domains.
One might be inclined to dismiss this correlation as mere happenstance, a chance alignment of statistical anomalies in two distant spheres of human activity. Yet, with each probing statistical test and nuanced analysis, the robustness of the relationship between the use of genetically modified soybeans in the heartland of North Dakota and the extraction of geothermal power in the expansive Russian landscape became increasingly apparent.
Our discovery of this unexpected association challenges conventional wisdom and stimulates contemplation on the far-reaching ripple effects of human endeavors. It invites us to marvel at the intricate, intricate dance of agricultural and energy systems across continents, urging our minds to embrace the complex interconnectedness of seemingly disparate phenomena. Indeed, this connection between GMO soybeans and geothermal power defies the boundaries of traditional disciplinary silos and beckons us to innovate novel analytical lenses to apprehend the subtle interplay of human activities in shaping our world.
As we embark upon the exposition of our groundbreaking findings, we invite our esteemed readers to accompany us on a journey of exploration and scrutiny, as we unravel the enigmatic threads that weave the fabric of "GMO-thermal power." This revelation promises to disrupt entrenched paradigms and ignite a fervor of interdisciplinary discourse, redefining the frontiers of agricultural and energy research in unforeseen ways. With this fervent anticipation, we present our discerning investigation into the intriguing correlation between genetically modified soybeans and geothermal power generation - a revelation that defies expectation and entices the inquiring intellect.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

METHODOLOGY

Data Collection:
The examination of the correlation between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia necessitated the collection of comprehensive and diverse datasets. To this end, our research team diligently scoured a multitude of sources, sifting through an extensive array of publicly available information spanning from the year 2000 to 2021. The primary repositories co-opted for this pursuit were the United States Department of Agriculture (USDA) and the Energy Information Administration, with their wealth of data serving as the bedrock for our analysis.

Statistical Analysis:
The initial phase of our inquiry entailed the extraction of pertinent data pertaining to GMO soybean cultivation in North Dakota and geothermal power generation in Russia. Subsequently, employing an arsenal of statistical tools and techniques, we undertook an in-depth exploration of potential correlations between these seemingly disparate phenomena. The statistical package R, renowned for its prowess in uncovering hidden relationships within complex datasets, emerged as the venerated ally in our quest to elucidate the enigmatic bond between GMO soybeans and geothermal power.

Correlation Coefficient Calculation:
The calculation of the correlation coefficient, the linchpin of our investigation, demanded the application of the revered Pearson correlation analysis. Through this method, we endeavored to distill the essence of the relationship between the adoption of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia into a numeric manifestation. The resultant coefficient, bearing the weight of our hypothesis, manifested itself as a compelling testament to the interwoven nature of agricultural and energy landscapes.

P-Value Determination:
In conjunction with the correlation coefficient, our diagnostic endeavors engendered the calculation of the p-value, a quintessentially pivotal metric in ascertaining the statistical significance of our findings. The discernment of a p-value of less than 0.01 served as an unequivocal validation of the robustness of the association between the deployment of GMO soybeans in North Dakota and the production of geothermal power in Russia, reaffirming the legitimacy of our revelatory revelation.

Sensitivity Analysis:
Bolstering our empirical underpinnings, a sensitivity analysis was meticulously conducted to gauge the stability and resilience of our derived correlation. This rigorous scrutiny served to fortify the veracity of our findings, finetuning our confidence in the overarching relationship between GMO soybeans and geothermal power.

Stratified Sampling:
In consideration of the potentially heterogeneous nature of the underlying data, a stratified sampling approach was artfully employed to ensure a representative and balanced selection of data points. This methodological stratagem facilitated the attainment of a holistic and nuanced understanding of the interplay between GMO soybeans and geothermal power, minimizing the perils of misrepresentation and bias.

Radiant Enlightenment:
Through the judicious amalgamation of these methodological constructs and analytical pursuits, our research team endeavored to shed light on the unanticipated nexus between genetically modified soybeans and geothermal power. Within the prism of empirical rigor and scholarly sagacity, we aimed to demystify this captivating connection, elevating our collective consciousness in comprehending the complexities of our world.

The substrate of our methodology, fortified by scholarly rigor and methodological probity, forms the crucible within which the captivating narrative of "GMO-thermal power" unfolds. With steadfastness and unwavering resolve, our inquiry embarks upon the untrodden territory of interdisciplinary revelation, beckoning us to usher in a new epoch of analytical enlightenment and intellectual ingenuity.

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 soybeans in North Dakota and Geothermal power generated in Russia. Make lots of 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 Energy Information Administration .

For the time period 2000 to 2021, you found a correlation 0.9513419, r-squared of 0.9050515, 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]]
From Soybeans to Steam: The GMO-Geothermal Connection Revealed

[[ABSTRACT]]
This paper investigates the surprising link between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. Despite the vast geographical distance between the two, our research team has identified a remarkable correlation that cannot be dismissed as pure coincidence. Using data from the USDA and Energy Information Administration spanning from 2000 to 2021, we have calculated a correlation coefficient of 0.9513419, with a statistically significant p-value of less than 0.01. Our findings raise intriguing questions about the potential transcontinental transmission of agricultural and energy influences - a phenomenon we playfully dub "GMO-thermal power." This unexpected connection challenges our traditional understanding of agricultural and energy systems and underscores the need for interdisciplinary examination of seemingly unrelated phenomena.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
The relationship between agricultural practices and energy generation has long been a topic of interest, primarily in the context of biofuel production, land use for renewable energy sources, and the environmental impacts of farming activities. However, the specific connection between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia has, until now, remained largely unexplored and shrouded in mystery.
In a serendipitous turn of events, our research team stumbled upon this peculiar link while analyzing disparate datasets related to agricultural and energy production. What began as a seemingly routine examination of soybean cultivation practices and energy usage patterns soon metamorphosed into a captivating intellectual puzzle. The seemingly incongruous pairing of soybeans and steam - the former representing a staple of modern agriculture and the latter a hallmark of geothermal energy generation - beckoned us to delve deeper into the potential correlation between these two seemingly unrelated domains.
One might be inclined to dismiss this correlation as mere happenstance, a chance alignment of statistical anomalies in two distant spheres of human activity. Yet, with each probing statistical test and nuanced analysis, the robustness of the relationship between the use of genetically modified soybeans in the heartland of North Dakota and the extraction of geothermal power in the expansive Russian landscape became increasingly apparent.
Our discovery of this unexpected association challenges conventional wisdom and stimulates contemplation on the far-reaching ripple effects of human endeavors. It invites us to marvel at the intricate, intricate dance of agricultural and energy systems across continents, urging our minds to embrace the complex interconnectedness of seemingly disparate phenomena. Indeed, this connection between GMO soybeans and geothermal power defies the boundaries of traditional disciplinary silos and beckons us to innovate novel analytical lenses to apprehend the subtle interplay of human activities in shaping our world.
As we embark upon the exposition of our groundbreaking findings, we invite our esteemed readers to accompany us on a journey of exploration and scrutiny, as we unravel the enigmatic threads that weave the fabric of "GMO-thermal power." This revelation promises to disrupt entrenched paradigms and ignite a fervor of interdisciplinary discourse, redefining the frontiers of agricultural and energy research in unforeseen ways. With this fervent anticipation, we present our discerning investigation into the intriguing correlation between genetically modified soybeans and geothermal power generation - a revelation that defies expectation and entices the inquiring intellect.

-------

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 soybeans in North Dakota and the generation of geothermal power in Russia. The correlation coefficient was calculated to be 0.9513419, indicating a very high positive correlation between the two variables. The coefficient of determination (r-squared) was found to be 0.9050515, suggesting that approximately 90.5% of the variability in geothermal power generation in Russia can be explained by the use of GMO soybeans in North Dakota.

The p-value of less than 0.01 further reinforced the significance of this correlation, firmly rejecting the null hypothesis of no relationship between the two variables. This finding defies the expected norm and invites further investigation into the unconventional relationship between agricultural practices in one part of the world and energy production in another.

As promised, Figure 1 depicts a scatterplot illustrating the strong positive correlation between GMO soybean usage in North Dakota and geothermal power generation in Russia. The visual representation of this relationship captures the imagination and prompts contemplation on the intriguing intercontinental connection of agricultural and energy systems. It's like witnessing a long-distance romance between two unlikely partners – soybeans and steam – each influencing the other from across the globe.

It is imperative to acknowledge the limitations of our study, despite the compelling results. While the data sources from the USDA and the Energy Information Administration provided robust information, causality cannot be inferred from our findings. Furthermore, the intricacies of the mechanisms underlying this association remain enigmatic, beckoning future research to unravel the tangled web of influences between agricultural practices and energy generation.

In conclusion, the unexpected correlation between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia challenges our conventional understanding of interconnected systems. This peculiar association, affectionately dubbed "GMO-thermal power," serves as a whimsical reminder that the world of data analysis is filled with surprises, and sometimes, the most improbable connections yield the most enlightening insights.

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 soybeans in North Dakota and Geothermal power generated in Russia. Make lots of 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]]
From Soybeans to Steam: The GMO-Geothermal Connection Revealed

[[ABSTRACT]]
This paper investigates the surprising link between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. Despite the vast geographical distance between the two, our research team has identified a remarkable correlation that cannot be dismissed as pure coincidence. Using data from the USDA and Energy Information Administration spanning from 2000 to 2021, we have calculated a correlation coefficient of 0.9513419, with a statistically significant p-value of less than 0.01. Our findings raise intriguing questions about the potential transcontinental transmission of agricultural and energy influences - a phenomenon we playfully dub "GMO-thermal power." This unexpected connection challenges our traditional understanding of agricultural and energy systems and underscores the need for interdisciplinary examination of seemingly unrelated phenomena.

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find a positive correlation between the cultivation of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. This unexpected relationship has sparked considerable intrigue among researchers, prompting a broader exploration of the potential interplay between agricultural practices and energy production on a global scale.
Similarly, in "Doe and Jones," the authors delve into the complex dynamics of agricultural land use and energy generation, shedding light on the nuanced connections that underpin these seemingly distinct domains. These studies serve as the foundational bedrock upon which our investigation into the GMO-geothermal connection unfolds.
Expanding beyond the realm of traditional academic papers, works such as "GMOs and You: A Comprehensive Guide" and "Geothermal Energy: From Theory to Practice" have provided invaluable insights into the individual components of our study. However, it is the fusion of these disparate elements that truly captures the whimsical imagination and challenges the boundaries of scholarly inquiry.
In the realm of fiction, novels such as "The Soybean Conspiracy" and "The Steam Mysteries" may appear unrelated to our empirical investigation. However, upon deeper introspection, these literary creations offer a glimpse into the collective unconscious, where the seeds of seemingly incongruous connections are sown.
As we journey further into our exploration of the GMO-geothermal enigma, it is imperative to acknowledge the unconventional sources that have informed our understanding. From decoding the cryptic symbolism of crop rotation in supermarket aisle three to unraveling the metaphysical implications of geothermal exploration in the context of ancient folklore, our literature review transcends the confines of conventional scholarship.
With an unyielding spirit of inquiry, our research team has probed into the unlikeliest of reservoirs of knowledge, including but not limited to deciphering the implications of grocery store receipts and divining the otherworldly wisdom embedded within cereal box packaging. These unorthodox sources, while whimsical in appearance, have been integral to our comprehensive and multidimensional examination of the intricate web that binds soybeans and steam.

[[RESULTS]]
The statistical analysis of the data revealed a remarkably strong correlation between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. The correlation coefficient was calculated to be 0.9513419, indicating a very high positive correlation between the two variables. The coefficient of determination (r-squared) was found to be 0.9050515, suggesting that approximately 90.5% of the variability in geothermal power generation in Russia can be explained by the use of GMO soybeans in North Dakota.
The p-value of less than 0.01 further reinforced the significance of this correlation, firmly rejecting the null hypothesis of no relationship between the two variables. This finding defies the expected norm and invites further investigation into the unconventional relationship between agricultural practices in one part of the world and energy production in another.
As promised, Figure 1 depicts a scatterplot illustrating the strong positive correlation between GMO soybean usage in North Dakota and geothermal power generation in Russia. The visual representation of this relationship captures the imagination and prompts contemplation on the intriguing intercontinental connection of agricultural and energy systems. It's like witnessing a long-distance romance between two unlikely partners – soybeans and steam – each influencing the other from across the globe.
It is imperative to acknowledge the limitations of our study, despite the compelling results. While the data sources from the USDA and the Energy Information Administration provided robust information, causality cannot be inferred from our findings. Furthermore, the intricacies of the mechanisms underlying this association remain enigmatic, beckoning future research to unravel the tangled web of influences between agricultural practices and energy generation.
In conclusion, the unexpected correlation between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia challenges our conventional understanding of interconnected systems. This peculiar association, affectionately dubbed "GMO-thermal power," serves as a whimsical reminder that the world of data analysis is filled with surprises, and sometimes, the most improbable connections yield the most enlightening insights.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study have provided robust support for the previously established correlations between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. The remarkable correlation coefficient of 0.9513419, along with a p-value of less than 0.01, reinforces the unexpected relationship between these seemingly disparate phenomena. This finding not only validates the pioneering work of Smith et al. and Doe and Jones but also adds a new layer of complexity to the whimsical world of agricultural and energy interplay.

Although our investigation began with a touch of whimsical imagination, the results have illuminated a fascinating connection between agricultural cultivation and energy generation. The statistical significance of our findings cannot be dismissed as mere happenstance; rather, they invite further exploration into the underlying mechanisms that link the growth of GMO soybeans in one hemisphere to the surging production of geothermal power in another. It's akin to witnessing a transcontinental dance where soybeans sway in rhythm with the steam that powers distant turbines, a mesmerizing spectacle indeed.

Returning to the lighthearted elements of our literature review, the connection between "The Soybean Conspiracy" and our empirical findings should not be overlooked. What may have initially seemed like a flight of fancy in a work of fiction has now found a foothold in the realm of scientific inquiry. Similarly, the cryptic symbolism of crop rotation in supermarket aisle three has proven to be more than a mere jest, as it indirectly hints at the transoceanic sway of agricultural practices on distant energy landscapes.

The limitations of our study notwithstanding, the fused energies of soybeans and steam - affectionately christened "GMO-thermal power" - have indeed dared the scholarly community to rethink the boundaries of traditional disciplinary confines. As we look ahead, it is imperative for researchers to adopt an open-minded perspective and embrace the delightful kaleidoscope of connections that may lie hidden within the mundane and the extraordinary.

In summary, our study has unveiled a captivating association between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. This unexpected bond challenges our understanding of agricultural and energy systems, illustrating that beneath the surface of conventional wisdom, lies a world of quirky relationships waiting to be discovered. As we continue on this scholarly journey, it is crucial to remember that in the tapestry of interconnected phenomena, even the most unconventional pairings may hold the key to unraveling the mysteries of our world.

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 soybeans in North Dakota and Geothermal power generated in Russia. Make lots of 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]]
From Soybeans to Steam: The GMO-Geothermal Connection Revealed

[[ABSTRACT]]
This paper investigates the surprising link between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. Despite the vast geographical distance between the two, our research team has identified a remarkable correlation that cannot be dismissed as pure coincidence. Using data from the USDA and Energy Information Administration spanning from 2000 to 2021, we have calculated a correlation coefficient of 0.9513419, with a statistically significant p-value of less than 0.01. Our findings raise intriguing questions about the potential transcontinental transmission of agricultural and energy influences - a phenomenon we playfully dub "GMO-thermal power." This unexpected connection challenges our traditional understanding of agricultural and energy systems and underscores the need for interdisciplinary examination of seemingly unrelated phenomena.

[[INTRDUCTION]]
INTRODUCTION
The relationship between agricultural practices and energy generation has long been a topic of interest, primarily in the context of biofuel production, land use for renewable energy sources, and the environmental impacts of farming activities. However, the specific connection between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia has, until now, remained largely unexplored and shrouded in mystery.
In a serendipitous turn of events, our research team stumbled upon this peculiar link while analyzing disparate datasets related to agricultural and energy production. What began as a seemingly routine examination of soybean cultivation practices and energy usage patterns soon metamorphosed into a captivating intellectual puzzle. The seemingly incongruous pairing of soybeans and steam - the former representing a staple of modern agriculture and the latter a hallmark of geothermal energy generation - beckoned us to delve deeper into the potential correlation between these two seemingly unrelated domains.
One might be inclined to dismiss this correlation as mere happenstance, a chance alignment of statistical anomalies in two distant spheres of human activity. Yet, with each probing statistical test and nuanced analysis, the robustness of the relationship between the use of genetically modified soybeans in the heartland of North Dakota and the extraction of geothermal power in the expansive Russian landscape became increasingly apparent.
Our discovery of this unexpected association challenges conventional wisdom and stimulates contemplation on the far-reaching ripple effects of human endeavors. It invites us to marvel at the intricate, intricate dance of agricultural and energy systems across continents, urging our minds to embrace the complex interconnectedness of seemingly disparate phenomena. Indeed, this connection between GMO soybeans and geothermal power defies the boundaries of traditional disciplinary silos and beckons us to innovate novel analytical lenses to apprehend the subtle interplay of human activities in shaping our world.
As we embark upon the exposition of our groundbreaking findings, we invite our esteemed readers to accompany us on a journey of exploration and scrutiny, as we unravel the enigmatic threads that weave the fabric of "GMO-thermal power." This revelation promises to disrupt entrenched paradigms and ignite a fervor of interdisciplinary discourse, redefining the frontiers of agricultural and energy research in unforeseen ways. With this fervent anticipation, we present our discerning investigation into the intriguing correlation between genetically modified soybeans and geothermal power generation - a revelation that defies expectation and entices the inquiring intellect.

[[RESULTS]]
The statistical analysis of the data revealed a remarkably strong correlation between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. The correlation coefficient was calculated to be 0.9513419, indicating a very high positive correlation between the two variables. The coefficient of determination (r-squared) was found to be 0.9050515, suggesting that approximately 90.5% of the variability in geothermal power generation in Russia can be explained by the use of GMO soybeans in North Dakota.
The p-value of less than 0.01 further reinforced the significance of this correlation, firmly rejecting the null hypothesis of no relationship between the two variables. This finding defies the expected norm and invites further investigation into the unconventional relationship between agricultural practices in one part of the world and energy production in another.
As promised, Figure 1 depicts a scatterplot illustrating the strong positive correlation between GMO soybean usage in North Dakota and geothermal power generation in Russia. The visual representation of this relationship captures the imagination and prompts contemplation on the intriguing intercontinental connection of agricultural and energy systems. It's like witnessing a long-distance romance between two unlikely partners – soybeans and steam – each influencing the other from across the globe.
It is imperative to acknowledge the limitations of our study, despite the compelling results. While the data sources from the USDA and the Energy Information Administration provided robust information, causality cannot be inferred from our findings. Furthermore, the intricacies of the mechanisms underlying this association remain enigmatic, beckoning future research to unravel the tangled web of influences between agricultural practices and energy generation.
In conclusion, the unexpected correlation between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia challenges our conventional understanding of interconnected systems. This peculiar association, affectionately dubbed "GMO-thermal power," serves as a whimsical reminder that the world of data analysis is filled with surprises, and sometimes, the most improbable connections yield the most enlightening insights.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the peculiar partnership between genetically modified soybeans in North Dakota and the generation of geothermal power in Russia, affectionately termed "GMO-thermal power," has left researchers in awe of the unexpected dance of agricultural and energy influences across continents. This unconventional connection, akin to a long-distance relationship between two unlikely partners, challenges traditional disciplinary boundaries and beckons forth a breath of interdisciplinary exploration.

Our study has shed light on the statistically significant correlation between these seemingly disparate phenomena, emphasizing the need for further investigation into the mysterious web of influences shaping our world. Nonetheless, the cryptic mechanisms underlying this association remain veiled in enigma, teasing researchers with the allure of unraveling the intricate threads of influence between soybeans and steam.

As we bid adieu to this revelatory expedition, we are left with a whimsical reminder that in the labyrinth of data analysis, even the most improbable connections can yield the most enlightening insights. Nevertheless, we assert that no further research is needed in this area, compelling our scholarly peers to humorously ponder the idiosyncrasies of "GMO-thermal power" while diverting their intellectual pursuits to other, less whimsical inquiries.

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 From Soybeans to Steam: The GMO-Geothermal Connection Revealed. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Agricultural Alchemy

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 From Soybeans to Steam: The GMO-Geothermal Connection Revealed. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Alternative Energy 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 From Soybeans to Steam: The GMO-Geothermal Connection Revealed with an abstract of This paper investigates the surprising link between the use of genetically modified soybeans in North Dakota and the generation of geothermal power in Russia. Despite the vast geographical distance between the two, our research team has identified a remarkable correlation that cannot be dismissed as pure coincidence. Using data from the USDA and Energy Information Administration spanning from 2000 to 2021, we have calculated a correlation coefficient of 0.9513419, with a statistically significant p-value of less than 0.01. Our findings raise intriguing questions about the potential transcontinental transmission of agricultural and energy influences - a phenomenon we playfully dub "GMO-thermal power." This unexpected connection challenges our traditional understanding of agricultural and energy systems and underscores the need for interdisciplinary examination of seemingly unrelated phenomena.

ChatGPT:

GMO soybeans, geothermal power, correlation, North Dakota, Russia, USDA data, Energy Information Administration, transcontinental transmission, agricultural influence, energy influence, interdisciplinary examination, GMO-thermal power, genetically modified organisms

*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 soybeans in North Dakota
Detailed data title: Percent of soybeans planted in North Dakota that are genetically modified to be herbicide-tolerant (HT), but not insect-resistant (Bt)
Source: USDA
See what else correlates with GMO use in soybeans in North Dakota

Geothermal power generated in Russia
Detailed data title: Total geothermal power generated in Russia in billion kWh
Source: Energy Information Administration
See what else correlates with Geothermal power generated in Russia

Correlation r = 0.9513419 (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 = 0.9050515 (Coefficient of determination)
This means 90.5% of the change in the one variable (i.e., Geothermal power generated in Russia) is predictable based on the change in the other (i.e., GMO use in soybeans in North Dakota) over the 22 years from 2000 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.1E-11.^Show 0.0000000000109772559066069130
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 0.95 in 1.1E-9% of random cases. Said differently, if you correlated 91,097,448,079 random variables^Note You don't actually need 91 billion 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 21 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 21 because we have two variables measured over a period of 22 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.

[ 0.88, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
GMO use in soybeans in North Dakota (GMO soybeans %)	22	49	61	74	82	89	90	92	94	94	94	94	98	94	96	94	95	95	95	95	94	93
Geothermal power generated in Russia (Billion kWh)	0.058	0.091	0.156	0.324	0.403	0.41	0.463	0.485	0.465	0.464	0.505	0.522	0.477	0.444	0.455	0.457	0.446	0.435	0.426	0.433	0.421	0.445

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([22,49,61,74,82,89,90,92,94,94,94,94,98,94,96,94,95,95,95,95,94,93,])
array_2 = np.array([0.058,0.091,0.156,0.324,0.403,0.41,0.463,0.485,0.465,0.464,0.505,0.522,0.477,0.444,0.455,0.457,0.446,0.435,0.426,0.433,0.421,0.445,])
array_1_name = "GMO use in soybeans in North Dakota"
array_2_name = "Geothermal power generated in Russia"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only GMO use in soybeans in North Dakota
Line chart for only Geothermal power generated in Russia
AI-generated correlation image
The spurious research paper: From Soybeans to Steam: The GMO-Geothermal Connection Revealed

View another random correlation

How fun was this correlation?

You're the rating guru we've been waiting for!

Correlation ID: 2699 · Black Variable ID: 823 · Red Variable ID: 23921


Problem variable:
Issue:
Additional details: Optional
Confirm you are a human: