Download png, svg
AI explanation
As the GMO soybeans in Minnesota grew larger and stronger, their roots inadvertently tuned into a previously undiscovered underground network, transmitting signals to the flora in Taiwan. This unprecedented botanical communication led to a surge in biomass power generation, as the plants in Taiwan photosynthesized with a newfound exuberance, harnessing the unspoken energy from the modified soybeans. It's a case of transgenic transmission sparking a power plant proliferation!
Model: dalle-3
Prompt: [ A photo-realistic image ] In a Minnesota field, tall soybean plants stretch towards the sky, their leaves vibrant and green, contrasting against the blue sky. Amongst the crop, a farmer is seen tending to the plants. In the distance, a modern power plant in Taiwan looms, emitting wisps of clean smoke into the sky, surrounded by a lush forest. The scene represents a blend of GMO soybean cultivation in Minnesota and Biomass power generation in Taiwan. The image is to be detailed but not cluttered, ensuring that the vibrant green of the soybean plants and the modern aesthetic of the power plant are well represented. 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 Minnesota and Biomass power generated in Taiwan. 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: Sci-fi fantacy Realistic Low poly A photo-realistic image A TIME magazine cover image
ChatGPT: A photo-realistic image
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both GMO use in soybeans in Minnesota and Biomass power generated in Taiwan together. Keep the description simple.
ChatGPT: In a Minnesota field, tall soybean plants stretch towards the sky, their leaves vibrant and green, contrasting against the blue sky. Amongst the crop, a farmer is seen tending to the plants. In the distance, a modern power plant in Taiwan looms, emitting wisps of clean smoke into the sky, surrounded by a lush forest. The scene represents a blend of GMO soybean cultivation in Minnesota and Biomass power generation in Taiwan.
Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A photo-realistic image ] and depicting this scene: In a Minnesota field, tall soybean plants stretch towards the sky, their leaves vibrant and green, contrasting against the blue sky. Amongst the crop, a farmer is seen tending to the plants. In the distance, a modern power plant in Taiwan looms, emitting wisps of clean smoke into the sky, surrounded by a lush forest. The scene represents a blend of GMO soybean cultivation in Minnesota and Biomass power generation in Taiwan. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A photo-realistic image ] In a Minnesota field, tall soybean plants stretch towards the sky, their leaves vibrant and green, contrasting against the blue sky. Amongst the crop, a farmer is seen tending to the plants. In the distance, a modern power plant in Taiwan looms, emitting wisps of clean smoke into the sky, surrounded by a lush forest. The scene represents a blend of GMO soybean cultivation in Minnesota and Biomass power generation in Taiwan. The image is to be detailed but not cluttered, ensuring that the vibrant green of the soybean plants and the modern aesthetic of the power plant are well represented.
*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.
I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in GMO use in soybeans in Minnesota caused Biomass power generated in Taiwan to increase.
AI academic paper
 |
Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass The Journal of Sustainable Agriculture and Renewable Resources Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between GMO use in soybeans in Minnesota and Biomass power generated in Taiwan. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Make the title an alliteration.
Your research team used data from USDA and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.9596114 and p < 0.01 for 2000 to 2021.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass
[[ABSTRACT]]
This paper delves into the delightful dance between GMO soybeans in Minnesota and the production of biomass power in Taiwan. Using data from the USDA and Energy Information Administration, our research team examined the intricate web of connections between these seemingly disparate elements. Despite the dry nature of our study, the correlation coefficient of 0.9596114 and p < 0.01 for the years 2000 to 2021 revealed a strikingly strong relationship. Our findings not only shed light on this often-overlooked relationship but also offer a tantalizing glimpse into the potential synergies between two seemingly unrelated components of the global agricultural and energy landscapes.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between GMO use in soybeans in Minnesota and Biomass power generated in Taiwan. 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.
Here is the title and abstract of the paper:
[[TITLE]]
Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass
[[ABSTRACT]]
This paper delves into the delightful dance between GMO soybeans in Minnesota and the production of biomass power in Taiwan. Using data from the USDA and Energy Information Administration, our research team examined the intricate web of connections between these seemingly disparate elements. Despite the dry nature of our study, the correlation coefficient of 0.9596114 and p < 0.01 for the years 2000 to 2021 revealed a strikingly strong relationship. Our findings not only shed light on this often-overlooked relationship but also offer a tantalizing glimpse into the potential synergies between two seemingly unrelated components of the global agricultural and energy landscapes.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
Introduction
The modern world is a tangled web of interconnected systems, where seemingly unrelated phenomena often converge in unexpected ways. In the realm of agriculture and energy, one might not immediately draw a connection between genetically modified soybean production in the heartland of Minnesota and the generation of biomass power in the distant island of Taiwan. However, as we will uncover, these two seemingly disparate elements are locked in a subtle, almost cosmic, dance of cause and effect.
At first glance, one might think, "What do soybeans in Minnesota have to do with biomass power in Taiwan? It's like trying to connect the dots between a cornfield and a wind turbine – improbable at best, right?" Well, prepare to have your assumptions shaken, my esteemed colleagues, because our examination of the data has unearthed a correlation that is as robust as a well-fertilized soybean crop.
Our research venture aims to strip away the veneer of obscurity that shrouds this linkage and reveal the underlying fabric of interconnectedness that ties these two domains together. While the subject matter may seem as dry as the Midwestern soybean fields after harvest, our findings promise to enliven the discourse with a touch of sizzle – much like a stir-fry made with genetically modified soybeans.
The use of genetically modified organisms (GMOs) in soybean cultivation has sparked debates and controversies that are as fervent as the bulls and bears of the stock market. Meanwhile, the production of biomass power has simmered in the background, quietly growing into a force to be reckoned with. But what happens when you toss these two seemingly unrelated ingredients into the intellectual cauldron? Do they fizz and fizzle away, or do they blend to create a savory stew of insights that leave us craving for more?
As we embark on this peculiar journey, let us not forget the words of the wise philosopher, Aristotle, who said, "The whole is greater than the sum of its parts." With this in mind, we delve into the complex interplay between Minnesota's magnificent soybeans and Taiwan's tantalizing biomass power, seeking to unearth the hidden connections and unveil the remarkable saga that unfolds when these two come together.
Ready your spectacles, my dear readers, for what lies ahead is a tale of bioengineered beans, renewable energy, and the intriguing interweaving of global systems. Let us press forth and explore the enchanting nexus between agriculture and energy, where the mundane and the marvelous collide.
So, fasten your seatbelts and ensure your wheat fields are far from your wind turbines, for we are about to embark on a voyage that promises to enrapture and illuminate, as we journey into the nexus of GMO soybeans and biomass power.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between GMO use in soybeans in Minnesota and Biomass power generated in Taiwan. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.
Here is the title and abstract of the paper:
[[TITLE]]
Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass
[[ABSTRACT]]
This paper delves into the delightful dance between GMO soybeans in Minnesota and the production of biomass power in Taiwan. Using data from the USDA and Energy Information Administration, our research team examined the intricate web of connections between these seemingly disparate elements. Despite the dry nature of our study, the correlation coefficient of 0.9596114 and p < 0.01 for the years 2000 to 2021 revealed a strikingly strong relationship. Our findings not only shed light on this often-overlooked relationship but also offer a tantalizing glimpse into the potential synergies between two seemingly unrelated components of the global agricultural and energy landscapes.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Introduction
The modern world is a tangled web of interconnected systems, where seemingly unrelated phenomena often converge in unexpected ways. In the realm of agriculture and energy, one might not immediately draw a connection between genetically modified soybean production in the heartland of Minnesota and the generation of biomass power in the distant island of Taiwan. However, as we will uncover, these two seemingly disparate elements are locked in a subtle, almost cosmic, dance of cause and effect.
At first glance, one might think, "What do soybeans in Minnesota have to do with biomass power in Taiwan? It's like trying to connect the dots between a cornfield and a wind turbine – improbable at best, right?" Well, prepare to have your assumptions shaken, my esteemed colleagues, because our examination of the data has unearthed a correlation that is as robust as a well-fertilized soybean crop.
Our research venture aims to strip away the veneer of obscurity that shrouds this linkage and reveal the underlying fabric of interconnectedness that ties these two domains together. While the subject matter may seem as dry as the Midwestern soybean fields after harvest, our findings promise to enliven the discourse with a touch of sizzle – much like a stir-fry made with genetically modified soybeans.
The use of genetically modified organisms (GMOs) in soybean cultivation has sparked debates and controversies that are as fervent as the bulls and bears of the stock market. Meanwhile, the production of biomass power has simmered in the background, quietly growing into a force to be reckoned with. But what happens when you toss these two seemingly unrelated ingredients into the intellectual cauldron? Do they fizz and fizzle away, or do they blend to create a savory stew of insights that leave us craving for more?
As we embark on this peculiar journey, let us not forget the words of the wise philosopher, Aristotle, who said, "The whole is greater than the sum of its parts." With this in mind, we delve into the complex interplay between Minnesota's magnificent soybeans and Taiwan's tantalizing biomass power, seeking to unearth the hidden connections and unveil the remarkable saga that unfolds when these two come together.
Ready your spectacles, my dear readers, for what lies ahead is a tale of bioengineered beans, renewable energy, and the intriguing interweaving of global systems. Let us press forth and explore the enchanting nexus between agriculture and energy, where the mundane and the marvelous collide.
So, fasten your seatbelts and ensure your wheat fields are far from your wind turbines, for we are about to embark on a voyage that promises to enrapture and illuminate, as we journey into the nexus of GMO soybeans and biomass power.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
Investigations into the tangled relationship between genetically modified soybeans in Minnesota and the generation of biomass power in Taiwan have been a source of scholarly inquiry for many years, with studies such as those by Smith (2005), Doe (2010), and Jones (2017) attempting to unravel the complex web of connections. It is fascinating to observe the persistence of researchers in attempting to connect the dots, much like attempting to unravel a cryptic crossword, where each clue, no matter how obscure, hints at the broader picture.
In "The Soybean: Botany, Production and Uses" by buzzworthy author Jones, the intricate history and uses of soybeans are detailed, revealing a plethora of applications beyond mere sustenance. Meanwhile, in "Biomass Energy and the Environment: A Developing Country Perspective" by renowned expert Doe, the potential of biomass power as a sustainable energy source is explored, shedding light on its relevance in the global energy landscape. These works serve as a reminder that just as soybeans are more than mere salad toppings, biomass power is not just a flash in the pan.
On a more whimsical note, the fictional works of Michael Crichton, particularly "Next" and "Prey," weave tales of scientific experimentation gone awry, serving as a striking metaphor for the potential risks and rewards of genetic modification in agriculture. Furthermore, the classic "Cloud Atlas" by David Mitchell draws parallels to the interconnection of disparate elements, much like the unassuming liaison between soybeans and biomass power.
One cannot ignore the Internet's penchant for meme culture, and it is no surprise that the "Soy Boy" meme has permeated popular discourse, offering a humorous take on the consumption of soy products. Similarly, the "This Is Fine" meme, depicting a dog sipping coffee in a burning room, bears a resemblance to the stoic acceptance of interconnected systems, even in the face of potential chaos.
The diverse range of literature and cultural references surrounding these topics showcases the pervasive nature of this intriguing relationship, suggesting that even the most unassuming pairings can hold profound significance.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between GMO use in soybeans in Minnesota and Biomass power generated in Taiwan. 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 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]]
Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass
[[ABSTRACT]]
This paper delves into the delightful dance between GMO soybeans in Minnesota and the production of biomass power in Taiwan. Using data from the USDA and Energy Information Administration, our research team examined the intricate web of connections between these seemingly disparate elements. Despite the dry nature of our study, the correlation coefficient of 0.9596114 and p < 0.01 for the years 2000 to 2021 revealed a strikingly strong relationship. Our findings not only shed light on this often-overlooked relationship but also offer a tantalizing glimpse into the potential synergies between two seemingly unrelated components of the global agricultural and energy landscapes.
[[INTRODUCTION]]
Introduction
The modern world is a tangled web of interconnected systems, where seemingly unrelated phenomena often converge in unexpected ways. In the realm of agriculture and energy, one might not immediately draw a connection between genetically modified soybean production in the heartland of Minnesota and the generation of biomass power in the distant island of Taiwan. However, as we will uncover, these two seemingly disparate elements are locked in a subtle, almost cosmic, dance of cause and effect.
At first glance, one might think, "What do soybeans in Minnesota have to do with biomass power in Taiwan? It's like trying to connect the dots between a cornfield and a wind turbine – improbable at best, right?" Well, prepare to have your assumptions shaken, my esteemed colleagues, because our examination of the data has unearthed a correlation that is as robust as a well-fertilized soybean crop.
Our research venture aims to strip away the veneer of obscurity that shrouds this linkage and reveal the underlying fabric of interconnectedness that ties these two domains together. While the subject matter may seem as dry as the Midwestern soybean fields after harvest, our findings promise to enliven the discourse with a touch of sizzle – much like a stir-fry made with genetically modified soybeans.
The use of genetically modified organisms (GMOs) in soybean cultivation has sparked debates and controversies that are as fervent as the bulls and bears of the stock market. Meanwhile, the production of biomass power has simmered in the background, quietly growing into a force to be reckoned with. But what happens when you toss these two seemingly unrelated ingredients into the intellectual cauldron? Do they fizz and fizzle away, or do they blend to create a savory stew of insights that leave us craving for more?
As we embark on this peculiar journey, let us not forget the words of the wise philosopher, Aristotle, who said, "The whole is greater than the sum of its parts." With this in mind, we delve into the complex interplay between Minnesota's magnificent soybeans and Taiwan's tantalizing biomass power, seeking to unearth the hidden connections and unveil the remarkable saga that unfolds when these two come together.
Ready your spectacles, my dear readers, for what lies ahead is a tale of bioengineered beans, renewable energy, and the intriguing interweaving of global systems. Let us press forth and explore the enchanting nexus between agriculture and energy, where the mundane and the marvelous collide.
So, fasten your seatbelts and ensure your wheat fields are far from your wind turbines, for we are about to embark on a voyage that promises to enrapture and illuminate, as we journey into the nexus of GMO soybeans and biomass power.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
METHODOLOGY
Our research methodology meticulously pieced together the puzzle of the relationship between genetically modified soybean production in Minnesota and the generation of biomass power in Taiwan. The data collection process involved sifting through a vast array of sources, primarily drawing from the databases of the United States Department of Agriculture (USDA) and the Energy Information Administration (EIA). The period under scrutiny spanned from 2000 to 2021, allowing for a comprehensive examination of the trends and patterns in both the cultivation of GMO soybeans and the production of biomass power.
To illuminate this seemingly anomalous connection, our research team employed a combination of quantitative and qualitative analyses. Quantitatively, we utilized statistical methods to explore the trends and associations between soybean production in Minnesota and the generation of biomass power in Taiwan. The correlation coefficient and regression analyses were employed to provide insight into the strength and direction of the relationship between these variables. Simultaneously, qualitative analyses were conducted to contextualize the statistical findings within the broader socio-economic and geopolitical factors that may influence the dynamics of the soybean-biomass power nexus.
The quantitative component of our analysis delved into the historical production data of GMO soybeans in Minnesota and the corresponding data on biomass power generation in Taiwan. Various statistical tests, including linear regression and time series analysis, were applied to identify any discernible patterns and relationships. Moreover, econometric modeling techniques were employed to control for potential confounding variables and assess the robustness of the identified associations.
Complementing the quantitative analyses, the qualitative dimension of our research involved a comprehensive review of literature pertaining to GMO soybean cultivation, biomass power production, and the global trade dynamics that underpin the interconnectedness of agricultural and energy systems. This qualitative assessment aimed to provide a nuanced understanding of the contextual factors that shape the link between soybean production and biomass power generation, shedding light on the implications for policy, trade, and sustainability.
Additionally, in a rather unconventional twist, the research team incorporated a socio-cultural perspective into the analysis, delving into the metaphorical and symbolic resonances of soybeans and biomass power in the collective consciousness. This qualitative inquiry sought to explore the cultural narratives and representations surrounding these elements, offering a whimsical yet thought-provoking dimension to our investigation.
It is important to note that the methodology involved a series of rigorous validations to ensure the reliability and validity of the findings. Sensitivity analyses and robustness checks were performed to gauge the stability of the identified correlations and to assess the resilience of the associations under different analytical scenarios.
So, as we embark on this methodological odyssey, bravely navigating the sea of data and theories, prepare to be dazzled by the complexity and intricacy of our approach, which, much like the flavorful fusion of soybeans and biomass, promises to offer an intellectually satisfying yield of insights.
---
This fictional research paper blends scientific inquiry with a touch of humor and whimsy to explore the interplay between GMO soybeans in Minnesota and biomass power in Taiwan. If reality could be as entertaining as this, academic research might just become everyone's favorite bedtime reading!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between GMO use in soybeans in Minnesota and Biomass power generated in Taiwan. 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 Energy Information Administration .
For the time period 2000 to 2021, you found a correlation 0.9596114, r-squared of 0.9208541, 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]]
Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass
[[ABSTRACT]]
This paper delves into the delightful dance between GMO soybeans in Minnesota and the production of biomass power in Taiwan. Using data from the USDA and Energy Information Administration, our research team examined the intricate web of connections between these seemingly disparate elements. Despite the dry nature of our study, the correlation coefficient of 0.9596114 and p < 0.01 for the years 2000 to 2021 revealed a strikingly strong relationship. Our findings not only shed light on this often-overlooked relationship but also offer a tantalizing glimpse into the potential synergies between two seemingly unrelated components of the global agricultural and energy landscapes.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
Introduction
The modern world is a tangled web of interconnected systems, where seemingly unrelated phenomena often converge in unexpected ways. In the realm of agriculture and energy, one might not immediately draw a connection between genetically modified soybean production in the heartland of Minnesota and the generation of biomass power in the distant island of Taiwan. However, as we will uncover, these two seemingly disparate elements are locked in a subtle, almost cosmic, dance of cause and effect.
At first glance, one might think, "What do soybeans in Minnesota have to do with biomass power in Taiwan? It's like trying to connect the dots between a cornfield and a wind turbine – improbable at best, right?" Well, prepare to have your assumptions shaken, my esteemed colleagues, because our examination of the data has unearthed a correlation that is as robust as a well-fertilized soybean crop.
Our research venture aims to strip away the veneer of obscurity that shrouds this linkage and reveal the underlying fabric of interconnectedness that ties these two domains together. While the subject matter may seem as dry as the Midwestern soybean fields after harvest, our findings promise to enliven the discourse with a touch of sizzle – much like a stir-fry made with genetically modified soybeans.
The use of genetically modified organisms (GMOs) in soybean cultivation has sparked debates and controversies that are as fervent as the bulls and bears of the stock market. Meanwhile, the production of biomass power has simmered in the background, quietly growing into a force to be reckoned with. But what happens when you toss these two seemingly unrelated ingredients into the intellectual cauldron? Do they fizz and fizzle away, or do they blend to create a savory stew of insights that leave us craving for more?
As we embark on this peculiar journey, let us not forget the words of the wise philosopher, Aristotle, who said, "The whole is greater than the sum of its parts." With this in mind, we delve into the complex interplay between Minnesota's magnificent soybeans and Taiwan's tantalizing biomass power, seeking to unearth the hidden connections and unveil the remarkable saga that unfolds when these two come together.
Ready your spectacles, my dear readers, for what lies ahead is a tale of bioengineered beans, renewable energy, and the intriguing interweaving of global systems. Let us press forth and explore the enchanting nexus between agriculture and energy, where the mundane and the marvelous collide.
So, fasten your seatbelts and ensure your wheat fields are far from your wind turbines, for we are about to embark on a voyage that promises to enrapture and illuminate, as we journey into the nexus of GMO soybeans and biomass power.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The examination of data from the USDA and Energy Information Administration yielded a correlation coefficient of 0.9596114, an r-squared value of 0.9208541, and a remarkable p-value of less than 0.01 for the time period from 2000 to 2021. These findings suggest a strikingly strong relationship between the use of genetically modified soybeans in Minnesota and the generation of biomass power in Taiwan. The strength of this correlation is as unyielding as a well-rooted soybean plant, standing tall and proud in the fields of Minnesota.
Moreover, in our quest to unravel the interwoven tapestry of agricultural and energy systems, we could not help but notice the visually compelling nature of the relationship between these variables. The accompanying scatterplot (Fig. 1) lends further credence to the robust correlation we have uncovered. Much like a perfectly crafted soybean stir-fry, the scatterplot illustrates the delightful dance between GMO soybeans and biomass power, captivating the senses with its visual elegance.
These results not only emphasize the unexpected interconnectedness of seemingly unrelated elements but also hint at the potential for synergistic interactions that transcend geographical boundaries. The subtle, almost serendipitous interplay between these two components of the global agricultural and energy landscapes underscores the intricate nature of our world's interconnected systems.
It is important to note, however, that correlation does not imply causation. While our findings illuminate the existence of a strong relationship, further research is warranted to fully comprehend the mechanisms underpinning this intriguing connection. The soybeans of Minnesota and the biomass power of Taiwan may continue to hold secrets yet to be unveiled, much like treasure buried deep within the soil, waiting to be unearthed.
In conclusion, the results of this study not only highlight the unexpected convergence of GMO soybean production in Minnesota and biomass power generation in Taiwan but also underscore the complex web of interactions that define our global agricultural and energy landscapes. This revelation invites further exploration and analysis, igniting the imagination with the boundless possibilities that arise when seemingly disparate elements come together.
The detailed findings and implications of this research pave the way for future investigations into the interconnectedness of agricultural and energy systems, promising to unravel more hidden connections and enrich our understanding of the intricate dance that unfolds when the mundane and the marvelous collide.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between GMO use in soybeans in Minnesota and Biomass power generated in Taiwan. 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]]
Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass
[[ABSTRACT]]
This paper delves into the delightful dance between GMO soybeans in Minnesota and the production of biomass power in Taiwan. Using data from the USDA and Energy Information Administration, our research team examined the intricate web of connections between these seemingly disparate elements. Despite the dry nature of our study, the correlation coefficient of 0.9596114 and p < 0.01 for the years 2000 to 2021 revealed a strikingly strong relationship. Our findings not only shed light on this often-overlooked relationship but also offer a tantalizing glimpse into the potential synergies between two seemingly unrelated components of the global agricultural and energy landscapes.
[[LITERATURE REVIEW]]
Investigations into the tangled relationship between genetically modified soybeans in Minnesota and the generation of biomass power in Taiwan have been a source of scholarly inquiry for many years, with studies such as those by Smith (2005), Doe (2010), and Jones (2017) attempting to unravel the complex web of connections. It is fascinating to observe the persistence of researchers in attempting to connect the dots, much like attempting to unravel a cryptic crossword, where each clue, no matter how obscure, hints at the broader picture.
In "The Soybean: Botany, Production and Uses" by buzzworthy author Jones, the intricate history and uses of soybeans are detailed, revealing a plethora of applications beyond mere sustenance. Meanwhile, in "Biomass Energy and the Environment: A Developing Country Perspective" by renowned expert Doe, the potential of biomass power as a sustainable energy source is explored, shedding light on its relevance in the global energy landscape. These works serve as a reminder that just as soybeans are more than mere salad toppings, biomass power is not just a flash in the pan.
On a more whimsical note, the fictional works of Michael Crichton, particularly "Next" and "Prey," weave tales of scientific experimentation gone awry, serving as a striking metaphor for the potential risks and rewards of genetic modification in agriculture. Furthermore, the classic "Cloud Atlas" by David Mitchell draws parallels to the interconnection of disparate elements, much like the unassuming liaison between soybeans and biomass power.
One cannot ignore the Internet's penchant for meme culture, and it is no surprise that the "Soy Boy" meme has permeated popular discourse, offering a humorous take on the consumption of soy products. Similarly, the "This Is Fine" meme, depicting a dog sipping coffee in a burning room, bears a resemblance to the stoic acceptance of interconnected systems, even in the face of potential chaos.
The diverse range of literature and cultural references surrounding these topics showcases the pervasive nature of this intriguing relationship, suggesting that even the most unassuming pairings can hold profound significance.
[[RESULTS]]
The examination of data from the USDA and Energy Information Administration yielded a correlation coefficient of 0.9596114, an r-squared value of 0.9208541, and a remarkable p-value of less than 0.01 for the time period from 2000 to 2021. These findings suggest a strikingly strong relationship between the use of genetically modified soybeans in Minnesota and the generation of biomass power in Taiwan. The strength of this correlation is as unyielding as a well-rooted soybean plant, standing tall and proud in the fields of Minnesota.
Moreover, in our quest to unravel the interwoven tapestry of agricultural and energy systems, we could not help but notice the visually compelling nature of the relationship between these variables. The accompanying scatterplot (Fig. 1) lends further credence to the robust correlation we have uncovered. Much like a perfectly crafted soybean stir-fry, the scatterplot illustrates the delightful dance between GMO soybeans and biomass power, captivating the senses with its visual elegance.
These results not only emphasize the unexpected interconnectedness of seemingly unrelated elements but also hint at the potential for synergistic interactions that transcend geographical boundaries. The subtle, almost serendipitous interplay between these two components of the global agricultural and energy landscapes underscores the intricate nature of our world's interconnected systems.
It is important to note, however, that correlation does not imply causation. While our findings illuminate the existence of a strong relationship, further research is warranted to fully comprehend the mechanisms underpinning this intriguing connection. The soybeans of Minnesota and the biomass power of Taiwan may continue to hold secrets yet to be unveiled, much like treasure buried deep within the soil, waiting to be unearthed.
In conclusion, the results of this study not only highlight the unexpected convergence of GMO soybean production in Minnesota and biomass power generation in Taiwan but also underscore the complex web of interactions that define our global agricultural and energy landscapes. This revelation invites further exploration and analysis, igniting the imagination with the boundless possibilities that arise when seemingly disparate elements come together.
The detailed findings and implications of this research pave the way for future investigations into the interconnectedness of agricultural and energy systems, promising to unravel more hidden connections and enrich our understanding of the intricate dance that unfolds when the mundane and the marvelous collide.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The results of our investigation into the correlation between GMO soybeans in Minnesota and the production of biomass power in Taiwan have provided compelling evidence of a strong and consistent relationship between these seemingly unrelated components. The robust correlation coefficient and low p-value not only bolster the findings of previous studies but also serve as a testament to the enduring interconnectedness of our global agricultural and energy systems. The literature review, with its diverse range of references, some lighthearted and others characteristically more serious, laid the groundwork for our study in a manner reminiscent of the tireless quest to solve a cryptic crossword puzzle. Indeed, much like the pursuit of knowledge, this investigation has been an endeavor marked by both serious scholarly inquiry and the occasional chuckle-inducing discovery.
The strong correlation coefficient and r-squared value affirm the persistence and determination of researchers in attempting to connect the dots in this enigmatic relationship. The scatterplot, akin to a visual masterpiece, not only brought to life the tangible manifestation of the strong correlation but also exuded a certain artistic flair. Just as a well-prepared soybean stir-fry tantalizes our taste buds, the scatterplot captivates the eye with its visual elegance—an unexpected but delightful parallel that underscores the multidimensional nature of our findings.
The wholesome vigor of GMO soybeans in Minnesota appears to have found an unexpected ally in the realm of biomass power in Taiwan, demonstrating the potential for synergistic interactions that transcend geographical boundaries. The interconnected nature of these variables, much like an intricate dance, highlights the complexity and interdependence of our global agricultural and energy landscapes. This revelation represents a poignant reminder that, like the myriad uses of soybeans detailed in the works of Jones, biomass power is not merely a fleeting trend but a stalwart presence in the evolving energy landscape.
The whimsical overlays from the literature review, including the resonance between the "Soy Boy" meme and the "This Is Fine" meme, serve as an amusing yet thought-provoking bridge between the scholarly discourse and popular culture, emphasizing the pervasive nature of this remarkable relationship. These lighthearted nods to everyday humor and cultural references only serve to underscore the captivating charm of our findings, revealing unexpected layers of significance amid the scholarly pursuit of knowledge.
In conclusion, our study illuminates the intricate dance between GMO soybeans in Minnesota and the production of biomass power in Taiwan, underscoring the multi-faceted nature of these seemingly disparate components. The results of this investigation serve as a springboard for future explorations into the interwoven tapestry of agricultural and energy systems, beckoning researchers to unravel more of the hidden connections that define our interconnected world. Without a doubt, the unexpected convergence of soybeans and biomass power has captivated our imaginations, leaving us eager to unravel more of the puzzles that await us in the captivating realms of agricultural and energy research.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between GMO use in soybeans in Minnesota and Biomass power generated in Taiwan. 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]]
Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass
[[ABSTRACT]]
This paper delves into the delightful dance between GMO soybeans in Minnesota and the production of biomass power in Taiwan. Using data from the USDA and Energy Information Administration, our research team examined the intricate web of connections between these seemingly disparate elements. Despite the dry nature of our study, the correlation coefficient of 0.9596114 and p < 0.01 for the years 2000 to 2021 revealed a strikingly strong relationship. Our findings not only shed light on this often-overlooked relationship but also offer a tantalizing glimpse into the potential synergies between two seemingly unrelated components of the global agricultural and energy landscapes.
[[INTRDUCTION]]
Introduction
The modern world is a tangled web of interconnected systems, where seemingly unrelated phenomena often converge in unexpected ways. In the realm of agriculture and energy, one might not immediately draw a connection between genetically modified soybean production in the heartland of Minnesota and the generation of biomass power in the distant island of Taiwan. However, as we will uncover, these two seemingly disparate elements are locked in a subtle, almost cosmic, dance of cause and effect.
At first glance, one might think, "What do soybeans in Minnesota have to do with biomass power in Taiwan? It's like trying to connect the dots between a cornfield and a wind turbine – improbable at best, right?" Well, prepare to have your assumptions shaken, my esteemed colleagues, because our examination of the data has unearthed a correlation that is as robust as a well-fertilized soybean crop.
Our research venture aims to strip away the veneer of obscurity that shrouds this linkage and reveal the underlying fabric of interconnectedness that ties these two domains together. While the subject matter may seem as dry as the Midwestern soybean fields after harvest, our findings promise to enliven the discourse with a touch of sizzle – much like a stir-fry made with genetically modified soybeans.
The use of genetically modified organisms (GMOs) in soybean cultivation has sparked debates and controversies that are as fervent as the bulls and bears of the stock market. Meanwhile, the production of biomass power has simmered in the background, quietly growing into a force to be reckoned with. But what happens when you toss these two seemingly unrelated ingredients into the intellectual cauldron? Do they fizz and fizzle away, or do they blend to create a savory stew of insights that leave us craving for more?
As we embark on this peculiar journey, let us not forget the words of the wise philosopher, Aristotle, who said, "The whole is greater than the sum of its parts." With this in mind, we delve into the complex interplay between Minnesota's magnificent soybeans and Taiwan's tantalizing biomass power, seeking to unearth the hidden connections and unveil the remarkable saga that unfolds when these two come together.
Ready your spectacles, my dear readers, for what lies ahead is a tale of bioengineered beans, renewable energy, and the intriguing interweaving of global systems. Let us press forth and explore the enchanting nexus between agriculture and energy, where the mundane and the marvelous collide.
So, fasten your seatbelts and ensure your wheat fields are far from your wind turbines, for we are about to embark on a voyage that promises to enrapture and illuminate, as we journey into the nexus of GMO soybeans and biomass power.
[[RESULTS]]
The examination of data from the USDA and Energy Information Administration yielded a correlation coefficient of 0.9596114, an r-squared value of 0.9208541, and a remarkable p-value of less than 0.01 for the time period from 2000 to 2021. These findings suggest a strikingly strong relationship between the use of genetically modified soybeans in Minnesota and the generation of biomass power in Taiwan. The strength of this correlation is as unyielding as a well-rooted soybean plant, standing tall and proud in the fields of Minnesota.
Moreover, in our quest to unravel the interwoven tapestry of agricultural and energy systems, we could not help but notice the visually compelling nature of the relationship between these variables. The accompanying scatterplot (Fig. 1) lends further credence to the robust correlation we have uncovered. Much like a perfectly crafted soybean stir-fry, the scatterplot illustrates the delightful dance between GMO soybeans and biomass power, captivating the senses with its visual elegance.
These results not only emphasize the unexpected interconnectedness of seemingly unrelated elements but also hint at the potential for synergistic interactions that transcend geographical boundaries. The subtle, almost serendipitous interplay between these two components of the global agricultural and energy landscapes underscores the intricate nature of our world's interconnected systems.
It is important to note, however, that correlation does not imply causation. While our findings illuminate the existence of a strong relationship, further research is warranted to fully comprehend the mechanisms underpinning this intriguing connection. The soybeans of Minnesota and the biomass power of Taiwan may continue to hold secrets yet to be unveiled, much like treasure buried deep within the soil, waiting to be unearthed.
In conclusion, the results of this study not only highlight the unexpected convergence of GMO soybean production in Minnesota and biomass power generation in Taiwan but also underscore the complex web of interactions that define our global agricultural and energy landscapes. This revelation invites further exploration and analysis, igniting the imagination with the boundless possibilities that arise when seemingly disparate elements come together.
The detailed findings and implications of this research pave the way for future investigations into the interconnectedness of agricultural and energy systems, promising to unravel more hidden connections and enrich our understanding of the intricate dance that unfolds when the mundane and the marvelous collide.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In unraveling the perplexing enigma of the link between GMO soybeans in Minnesota and biomass power in Taiwan, our investigation has illuminated a correlation as striking as a bolt of lightning on a summer day. The robust relationship between these seemingly unrelated elements is as unexpected as finding a single, perfectly ripe tomato amidst a sea of unripened fruits. The scattering of data points in our visually compelling scatterplot (Fig. 1) is akin to a masterfully choreographed dance between two unlikely partners, captivating the beholder with its elegance, much like a delicate waltz between a soybean and a stalk of corn.
In closing, our study does not merely shed light on the nexus between these disparate components of the global agricultural and energy landscapes; it rouses the imagination, igniting a flame as fiery as a well-tended bonfire in the heart of winter. The potential for further examination of this enthralling linkage beckons like a ripe, juicy peach on a scorching summer day. However, much like a perfectly seasoned dish, it is time to savor the flavors we have uncovered and recognize that no more research is needed. For as the old saying goes, "Some puzzles are best left unsolved, like the mystery of why hot dogs come in packs of ten, but hot dog buns come in packs of eight."
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 Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Sustainable Agriculture and Renewable Resources
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 Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass. Respond only with the name of a fictional organization.
ChatGPT:
The Association for Agroecological Advancements (AAA)
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 Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass with an abstract of This paper delves into the delightful dance between GMO soybeans in Minnesota and the production of biomass power in Taiwan. Using data from the USDA and Energy Information Administration, our research team examined the intricate web of connections between these seemingly disparate elements. Despite the dry nature of our study, the correlation coefficient of 0.9596114 and p < 0.01 for the years 2000 to 2021 revealed a strikingly strong relationship. Our findings not only shed light on this often-overlooked relationship but also offer a tantalizing glimpse into the potential synergies between two seemingly unrelated components of the global agricultural and energy landscapes.
ChatGPT:
GMO soybeans, Minnesota, biomass power, Taiwan, correlation coefficient, USDA, Energy Information Administration, global agricultural, energy landscape, biomass production, soybean production, relationship analysis
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
Discover a new correlation
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Data details
GMO use in soybeans in MinnesotaDetailed data title: Percent of soybeans planted in Minnesota 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 Minnesota
Biomass power generated in Taiwan
Detailed data title: Total biomass power generated in Taiwan in billion kWh
Source: Energy Information Administration
See what else correlates with Biomass power generated in Taiwan
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 = 0.9208541 (Coefficient of determination)
This means 92.1% of the change in the one variable (i.e., Biomass power generated in Taiwan) is predictable based on the change in the other (i.e., GMO use in soybeans in Minnesota) over the 22 years from 2000 through 2021.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.8E-12. 0.0000000000017640311266281767
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.
But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.
Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.96 in 1.8E-10% of random cases. Said differently, if you correlated 566,883,421,106 random variables You don't actually need 566 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, 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.
[ 0.9, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
| 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | |
| GMO use in soybeans in Minnesota (GMO soybeans %) | 46 | 63 | 71 | 79 | 82 | 83 | 88 | 92 | 91 | 92 | 93 | 95 | 91 | 93 | 94 | 95 | 96 | 96 | 95 | 95 | 93 | 96 |
| Biomass power generated in Taiwan (Billion kWh) | 1.79272 | 2.30986 | 2.7877 | 3.15101 | 3.3493 | 3.37732 | 3.37797 | 3.46556 | 3.36123 | 3.2655 | 3.39759 | 3.43304 | 3.4192 | 3.47124 | 3.57527 | 3.6304 | 3.60197 | 3.52871 | 3.75188 | 3.80086 | 3.75309 | 3.77279 |
Why this works
- Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
- Lack of causal connection: There is probably
Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied. - Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple
Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.Step 2: Open a plaintext editor like Notepad and paste the code below into it.
Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"
Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.
Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.
Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.
Step 7: Run the Python script by typing "python calculate_correlation.py"
If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:
"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."
# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats
# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):
# Calculate Pearson correlation coefficient and p-value
correlation, p_value = stats.pearsonr(array1, array2)
# Calculate R-squared as the square of the correlation coefficient
r_squared = correlation**2
return correlation, r_squared, p_value
# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([46,63,71,79,82,83,88,92,91,92,93,95,91,93,94,95,96,96,95,95,93,96,])
array_2 = np.array([1.79272,2.30986,2.7877,3.15101,3.3493,3.37732,3.37797,3.46556,3.36123,3.2655,3.39759,3.43304,3.4192,3.47124,3.57527,3.6304,3.60197,3.52871,3.75188,3.80086,3.75309,3.77279,])
array_1_name = "GMO use in soybeans in Minnesota"
array_2_name = "Biomass power generated in Taiwan"
# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)
# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)Reuseable content
You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.
For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
Full license details.
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Download images for these variables:
- High resolution line chart
The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
Alternatively you can use a tool like Inkscape. - High resolution line chart, optimized for mobile
- Alternative high resolution line chart
- Scatterplot
- Portable line chart (png)
- Portable line chart (png), optimized for mobile
- Line chart for only GMO use in soybeans in Minnesota
- Line chart for only Biomass power generated in Taiwan
- AI-generated correlation image
- The spurious research paper: Marvelous Minnesota Soybeans: Unraveling the Link to Taiwan's Tantalizing Biomass
Thanks for being the explorer we needed!
Correlation ID: 1747 · Black Variable ID: 819 · Red Variable ID: 24024
