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AI explanation
As GMO use in Iowa soybeans increased, there was a soy much productivity growth that it bean to have a global impact. The surplus soybeans led to greater soybean meal production, which hogged the spotlight in Taiwan's livestock industry. With a pig demand for alternative energy sources, the idea of using soybean biomass to power up Taiwan took root. This not only solved their energy crisis, but also created a whole new field of renewable power. It's a-maize-ing how a little soy tweak in the heartland could lead to a powerhouse of a solution on the other side of the world!Model: dalle-3
Prompt: [ Whimsical illustration ] Imagine a surreal scene where a sprawling soybean field in Iowa extends into the distance, with each plant resembling a colorful, towering piece of whimsical art. The field is alive with motion, as the tall green soybean plants sway gracefully in the gentle breeze, forming vibrant patterns that dance across the landscape. Adjacent to the field, a bustling livestock farm comes to life with the presence of cheerful cows enjoying the bountiful GMO soybean feed, their playful antics adding a touch of enchantment to the scene. Meanwhile, across the world in Taiwan, a fantastical power plant thrums with energy, emanating an otherworldly glow that lights up the sky. Beside it, colossal soybean biomass takes on an ethereal quality as it is drawn into the plant, forming a mesmerizing spectacle of swirling shapes and vibrant hues. This whimsical depiction captures the unlikely and enchanting connection between GMO soybeans, livestock feed, and biomass power generation, transporting viewers to a world where the ordinary transforms into an extraordinary work of art. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: "Genetically Modified Outrage: Soybean Shenanigans Spark Surge in Taiwanese Biomass Power! Experts attribute the unlikely connection to a 'soy-percharged' chain of events, as the influx of GMO soybeans in Iowa led to an 'ear-resistible' increase in livestock feed production, resulting in a 'bean' toward biomass power generation in Taiwan. It's a 'soy-long, and thanks for all the power' situation!". Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s High-tech Steampunk Whimsical illustration Charcoal
ChatGPT: Whimsical illustration
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. "Genetically Modified Outrage: Soybean Shenanigans Spark Surge in Taiwanese Biomass Power! Experts attribute the unlikely connection to a 'soy-percharged' chain of events, as the influx of GMO soybeans in Iowa led to an 'ear-resistible' increase in livestock feed production, resulting in a 'bean' toward biomass power generation in Taiwan. It's a 'soy-long, and thanks for all the power' situation!"
ChatGPT: Imagine a sprawling soybean field in Iowa, with tall green plants swaying in the breeze. Next to the field, there's a bustling livestock farm with happy cows munching on freshly produced GMO soybean feed. On the other side of the world, in Taiwan, you see a power plant churning out energy, and next to it, you spot massive soybean biomass being fuelled into the plant. It's a surreal yet striking sight of the unlikely connection between GMO soybeans, livestock feed, and biomass power generation.
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: [ Whimsical illustration ] and depicting this scene: Imagine a sprawling soybean field in Iowa, with tall green plants swaying in the breeze. Next to the field, there's a bustling livestock farm with happy cows munching on freshly produced GMO soybean feed. On the other side of the world, in Taiwan, you see a power plant churning out energy, and next to it, you spot massive soybean biomass being fuelled into the plant. It's a surreal yet striking sight of the unlikely connection between GMO soybeans, livestock feed, and biomass power generation. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Whimsical illustration ] Imagine a surreal scene where a sprawling soybean field in Iowa extends into the distance, with each plant resembling a colorful, towering piece of whimsical art. The field is alive with motion, as the tall green soybean plants sway gracefully in the gentle breeze, forming vibrant patterns that dance across the landscape. Adjacent to the field, a bustling livestock farm comes to life with the presence of cheerful cows enjoying the bountiful GMO soybean feed, their playful antics adding a touch of enchantment to the scene. Meanwhile, across the world in Taiwan, a fantastical power plant thrums with energy, emanating an otherworldly glow that lights up the sky. Beside it, colossal soybean biomass takes on an ethereal quality as it is drawn into the plant, forming a mesmerizing spectacle of swirling shapes and vibrant hues. This whimsical depiction captures the unlikely and enchanting connection between GMO soybeans, livestock feed, and biomass power generation, transporting viewers to a world where the ordinary transforms into an extraordinary work of art.
*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 Iowa caused Biomass power generated in Taiwan to increase. Include one good pun.
AI academic paper
From Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion The International Journal of Agro-Engineering and Biorenewable 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 Iowa and Biomass power generated in Taiwan. Make lots of jokes, goofy observations, and puns.
Rhyme words in the title.
Your research team used data from USDA and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.9392647 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]]
From Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion
[[ABSTRACT]]
Soybeans and Taiwan might seem as unrelated as apples and... biogas, but our research has uncovered a rather illuminating correlation. Our study delves into the potential link between the use of genetically modified soybeans in the cornfields of Iowa and the generation of biomass power in the bustling island of Taiwan. To peel back the layers of this agricultural and energy enigma, we crunched the numbers from USDA and the Energy Information Administration. The results revealed a notable correlation coefficient of 0.9392647 and a p-value less than 0.01 for the period spanning from 2000 to 2021. Our findings not only shed light on the soybean-biomass power relationship but also provoke a soy-lful amount of curiosity and excitement. So, brace yourself for an intellectual ride from the heartland of America to the technological marvels of Taiwan - it's a grain and power game!
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 Iowa and Biomass power generated in Taiwan. Make lots of 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]]
From Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion
[[ABSTRACT]]
Soybeans and Taiwan might seem as unrelated as apples and... biogas, but our research has uncovered a rather illuminating correlation. Our study delves into the potential link between the use of genetically modified soybeans in the cornfields of Iowa and the generation of biomass power in the bustling island of Taiwan. To peel back the layers of this agricultural and energy enigma, we crunched the numbers from USDA and the Energy Information Administration. The results revealed a notable correlation coefficient of 0.9392647 and a p-value less than 0.01 for the period spanning from 2000 to 2021. Our findings not only shed light on the soybean-biomass power relationship but also provoke a soy-lful amount of curiosity and excitement. So, brace yourself for an intellectual ride from the heartland of America to the technological marvels of Taiwan - it's a grain and power game!
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
Introduction
As we soar into the 21st century, the world finds itself embroiled in an ever-evolving dance between agricultural innovation and sustainable energy practices. This confluence of forces has brought us to the intriguing intersection of genetically modified soybeans in the heartland of Iowa and the burgeoning production of biomass power on the distant shores of Taiwan. At first glance, one might ponder the connection between these seemingly disparate elements and muse, "What on earth do soybeans and biomass power have in common?"
Our quest to unravel this soybean saga and energy escapade stems from a blend of curiosity and a dash of scientific inquiry. Together, we aim to traverse the sprawling fields of crop genetics and the labyrinthine realm of renewable energy production to uncover any hidden kernels of truth. Let us embark on this expedition with gusto, fueled by the tantalizing prospects of uncovering an unexpected bond between the GMO-laden soybeans of Iowa and the power-packed biomass facilities in Taiwan.
While the association between soybeans in the American Midwest and the energy landscape of East Asia may seem as distant as a GMO-free farm and a soy milk latte, we hypothesize that there exists a discernible correlation that merits a closer examination. We take a bold leap into the realm of data analysis, armed with statistical tools and a healthy dose of skepticism, to test our audacious assertion. So, fasten your seatbelts and prepare for a rollercoaster ride through the worlds of agriculture and energy - you may be in for some soy-prise discoveries!
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 Iowa and Biomass power generated in Taiwan. 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 name some movies that you watched that are tangentially related to the topic.
Here is the title and abstract of the paper:
[[TITLE]]
From Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion
[[ABSTRACT]]
Soybeans and Taiwan might seem as unrelated as apples and... biogas, but our research has uncovered a rather illuminating correlation. Our study delves into the potential link between the use of genetically modified soybeans in the cornfields of Iowa and the generation of biomass power in the bustling island of Taiwan. To peel back the layers of this agricultural and energy enigma, we crunched the numbers from USDA and the Energy Information Administration. The results revealed a notable correlation coefficient of 0.9392647 and a p-value less than 0.01 for the period spanning from 2000 to 2021. Our findings not only shed light on the soybean-biomass power relationship but also provoke a soy-lful amount of curiosity and excitement. So, brace yourself for an intellectual ride from the heartland of America to the technological marvels of Taiwan - it's a grain and power game!
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Introduction
As we soar into the 21st century, the world finds itself embroiled in an ever-evolving dance between agricultural innovation and sustainable energy practices. This confluence of forces has brought us to the intriguing intersection of genetically modified soybeans in the heartland of Iowa and the burgeoning production of biomass power on the distant shores of Taiwan. At first glance, one might ponder the connection between these seemingly disparate elements and muse, "What on earth do soybeans and biomass power have in common?"
Our quest to unravel this soybean saga and energy escapade stems from a blend of curiosity and a dash of scientific inquiry. Together, we aim to traverse the sprawling fields of crop genetics and the labyrinthine realm of renewable energy production to uncover any hidden kernels of truth. Let us embark on this expedition with gusto, fueled by the tantalizing prospects of uncovering an unexpected bond between the GMO-laden soybeans of Iowa and the power-packed biomass facilities in Taiwan.
While the association between soybeans in the American Midwest and the energy landscape of East Asia may seem as distant as a GMO-free farm and a soy milk latte, we hypothesize that there exists a discernible correlation that merits a closer examination. We take a bold leap into the realm of data analysis, armed with statistical tools and a healthy dose of skepticism, to test our audacious assertion. So, fasten your seatbelts and prepare for a rollercoaster ride through the worlds of agriculture and energy - you may be in for some soy-prise discoveries!
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
As we delve into the tangled web of genetically modified soybeans and the generation of biomass power, the literature presents a mix of serious studies and some unexpected - and perhaps even zany - connections. In their study, "The Impact of GMO Soybean Cultivation on Agricultural Practices" (Smith et al., 2012), the authors find a comprehensive analysis of the adoption and impact of GMO soybeans in Iowa. The study highlights the widespread use of genetically modified soybeans and their influence on yield, pesticide usage, and overall agricultural practices. However, what this study does not cover is the potential ripple effect of these soybeans on the distant energy landscapes of Taiwan.
Another study by Doe et al. (2015), titled "Biomass Power Generation: Challenges and Opportunities," offers an in-depth exploration of the intricacies of biomass power, focusing primarily on technology, policy, and market dynamics. Though informative, this study fails to consider the remote possibility that the humble soybean - albeit genetically modified - could exert any influence on the biomass power industry, particularly on an international scale.
In "Energy Revolution: The Physics and the Politics" (Jones, 2019), the author provides a meticulous examination of the global energy landscape and the potential for renewable energy sources to revolutionize power generation. While the book discusses the economics and politics of energy, it neglects to entertain the notion of an agricultural commodity like soybeans playing a role in the energy revolution, let alone crossing continents to impact the power scene in Taiwan.
Shifting focus from non-fiction to fiction, J.K. Rowling's "Harry Potter and the Goblet of Fire" unexpectedly mentions a soybean plant in the Herbology class at Hogwarts, hinting at the potential magical prowess of this humble crop. Meanwhile, in Michael Pollan's "The Omnivore's Dilemma," the author weaves a narrative around the intricate connections between humans and their food, leaving little room for speculation on the far-reaching implications of soybeans on energy generation.
On a lighter note, the 1989 classic film "Field of Dreams" tells the tale of, well, a field of dreams in Iowa, albeit unrelated to soybeans or biomass power. Nonetheless, the notion of unexpected connections and unanticipated outcomes in unlikely places resonates with our quest to uncover the link between Iowa's soybeans and Taiwan's biomass power.
Now that we have laid the groundwork with the literature review, we are poised to unearth the unexpected and whimsical revelations in our investigation.
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 Iowa and Biomass power generated in Taiwan. 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 Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion
[[ABSTRACT]]
Soybeans and Taiwan might seem as unrelated as apples and... biogas, but our research has uncovered a rather illuminating correlation. Our study delves into the potential link between the use of genetically modified soybeans in the cornfields of Iowa and the generation of biomass power in the bustling island of Taiwan. To peel back the layers of this agricultural and energy enigma, we crunched the numbers from USDA and the Energy Information Administration. The results revealed a notable correlation coefficient of 0.9392647 and a p-value less than 0.01 for the period spanning from 2000 to 2021. Our findings not only shed light on the soybean-biomass power relationship but also provoke a soy-lful amount of curiosity and excitement. So, brace yourself for an intellectual ride from the heartland of America to the technological marvels of Taiwan - it's a grain and power game!
[[INTRODUCTION]]
Introduction
As we soar into the 21st century, the world finds itself embroiled in an ever-evolving dance between agricultural innovation and sustainable energy practices. This confluence of forces has brought us to the intriguing intersection of genetically modified soybeans in the heartland of Iowa and the burgeoning production of biomass power on the distant shores of Taiwan. At first glance, one might ponder the connection between these seemingly disparate elements and muse, "What on earth do soybeans and biomass power have in common?"
Our quest to unravel this soybean saga and energy escapade stems from a blend of curiosity and a dash of scientific inquiry. Together, we aim to traverse the sprawling fields of crop genetics and the labyrinthine realm of renewable energy production to uncover any hidden kernels of truth. Let us embark on this expedition with gusto, fueled by the tantalizing prospects of uncovering an unexpected bond between the GMO-laden soybeans of Iowa and the power-packed biomass facilities in Taiwan.
While the association between soybeans in the American Midwest and the energy landscape of East Asia may seem as distant as a GMO-free farm and a soy milk latte, we hypothesize that there exists a discernible correlation that merits a closer examination. We take a bold leap into the realm of data analysis, armed with statistical tools and a healthy dose of skepticism, to test our audacious assertion. So, fasten your seatbelts and prepare for a rollercoaster ride through the worlds of agriculture and energy - you may be in for some soy-prise discoveries!
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To untangle the intricate web of soybean genetics and biomass power generation, our research team embarked on a journey that rivaled the Indiana Jones' quest for the Holy Grail – albeit with fewer booby traps and more internet searches. Our methodological approach was as precise as a genetically modified soybean, taking into account the multifaceted nature of agricultural and energy data.
The primary source of our data was the United States Department of Agriculture (USDA) for information on soybean cultivation, including the use of genetically modified soybeans in Iowa from the year 2000 to 2021. We did scour the web for data, but let's face it, when in doubt, trust the USDA – they really know their beans! As for the correlation on the Taiwan side of things, we relied on the Energy Information Administration for data on biomass power generation during the same period.
Our research team combed through a colossal amount of data like a group of enthusiastic archaeologists sifting through ruins, selecting only the plumpest and juiciest statistics to analyze. We then performed a series of statistical analyses using software that could crunch numbers faster than a squirrel storing nuts for the winter – indeed, our computers were working overtime!
To assess the relationship between the use of GMO soybeans in Iowa and the generation of biomass power in Taiwan, we calculated the correlation coefficient and associated p-value. The correlation coefficient, succinctly put, measures the strength and direction of a linear relationship between two variables, while the p-value indicates the statistical significance of our findings. Our goal was to decipher whether there was a tangible connection between the two seemingly disparate elements and, if so, to quantify the strength of this relationship.
The statistical analyses were conducted with a level of scrutiny that could rival a hawk eyeing its prey – every figure was scrutinized, every assumption tested, and every variable probed. Our statistical approach was as rigorous as a strict librarian monitoring overdue books; we left no statistical stone unturned in our quest for soybean and biomass power enlightenment.
It's worth noting that while the methods used may seem as complex as a genetic modification process, we strove to ensure that our analyses were as transparent and robust as possible, allowing for the replication and validation of our findings. Just like a good soybean crop, we aimed for our results to be hearty, reliable, and resistant to scientific pests.
In the end, our methodology was a marriage of precision and perseverance, a dance between data and statistical rigor that sought to uncover the hidden connections between soybeans and power generation, and to punctuate our findings with a dash of statistical flavor. So, fasten your seatbelts – we're about to dive into the statistical soy sauce of our research findings!
Next, we would take the research findings and conclusion for your academic research paper.
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 Iowa and Biomass power generated in Taiwan. 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 0.9392647, r-squared of 0.8822181, 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 Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion
[[ABSTRACT]]
Soybeans and Taiwan might seem as unrelated as apples and... biogas, but our research has uncovered a rather illuminating correlation. Our study delves into the potential link between the use of genetically modified soybeans in the cornfields of Iowa and the generation of biomass power in the bustling island of Taiwan. To peel back the layers of this agricultural and energy enigma, we crunched the numbers from USDA and the Energy Information Administration. The results revealed a notable correlation coefficient of 0.9392647 and a p-value less than 0.01 for the period spanning from 2000 to 2021. Our findings not only shed light on the soybean-biomass power relationship but also provoke a soy-lful amount of curiosity and excitement. So, brace yourself for an intellectual ride from the heartland of America to the technological marvels of Taiwan - it's a grain and power game!
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
Introduction
As we soar into the 21st century, the world finds itself embroiled in an ever-evolving dance between agricultural innovation and sustainable energy practices. This confluence of forces has brought us to the intriguing intersection of genetically modified soybeans in the heartland of Iowa and the burgeoning production of biomass power on the distant shores of Taiwan. At first glance, one might ponder the connection between these seemingly disparate elements and muse, "What on earth do soybeans and biomass power have in common?"
Our quest to unravel this soybean saga and energy escapade stems from a blend of curiosity and a dash of scientific inquiry. Together, we aim to traverse the sprawling fields of crop genetics and the labyrinthine realm of renewable energy production to uncover any hidden kernels of truth. Let us embark on this expedition with gusto, fueled by the tantalizing prospects of uncovering an unexpected bond between the GMO-laden soybeans of Iowa and the power-packed biomass facilities in Taiwan.
While the association between soybeans in the American Midwest and the energy landscape of East Asia may seem as distant as a GMO-free farm and a soy milk latte, we hypothesize that there exists a discernible correlation that merits a closer examination. We take a bold leap into the realm of data analysis, armed with statistical tools and a healthy dose of skepticism, to test our audacious assertion. So, fasten your seatbelts and prepare for a rollercoaster ride through the worlds of agriculture and energy - you may be in for some soy-prise discoveries!
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
As we delved into the vast expanse of data related to soybean cultivation in Iowa and biomass power generation in Taiwan, we uncovered a striking correlation that sent shockwaves through the agricultural and energy spheres. Our analysis revealed a staggering correlation coefficient of 0.9392647, indicating a robust positive relationship between the usage of genetically modified soybeans in Iowa and the production of biomass power in Taiwan from 2000 to 2021. This correlation was further substantiated by an r-squared value of 0.8822181, signifying that approximately 88.22% of the variability in biomass power generation can be attributed to the usage of GMO soybeans in Iowa. Additionally, the p-value of less than 0.01 reaffirmed the statistical significance of this correlation, dispelling any doubts about the strength of the relationship.
The implications of this correlation are nothing short of monumental, akin to stumbling upon a rare heirloom soybean in a sea of ordinary legumes. Fig. 1 encapsulates this significant finding in a visually compelling manner, depicting a clear and unmistakable positive association between the utilization of GMO soybeans in Iowa and the production of biomass power in Taiwan. Like two peas in a pod, these seemingly disparate elements have woven an intricate bond, nurturing the growth of sustainable energy practices and agri-tech innovations. This revelation not only sheds light on the interconnectedness of global agricultural and energy systems but also prompts a soyful contemplation of the far-reaching impact of genetically modified crops on the renewable energy landscape.
The robustness of the association uncovered in this study underscores the need for future investigations to dig deeper into the mechanistic underpinnings of this soybean-biomass power nexus. As we bask in the afterglow of this remarkable discovery, it becomes abundantly clear that the soy to joy transition is not just a pun; it is a tangible reflection of the symbiotic relationship between agricultural biotechnology and clean energy solutions. This research paves the way for a soy-driven revolution in sustainable energy development, where the humble soybean emerges as an unlikely but pivotal player in the global pursuit of renewable energy sources.
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 Iowa and Biomass power generated in Taiwan. 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 Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion
[[ABSTRACT]]
Soybeans and Taiwan might seem as unrelated as apples and... biogas, but our research has uncovered a rather illuminating correlation. Our study delves into the potential link between the use of genetically modified soybeans in the cornfields of Iowa and the generation of biomass power in the bustling island of Taiwan. To peel back the layers of this agricultural and energy enigma, we crunched the numbers from USDA and the Energy Information Administration. The results revealed a notable correlation coefficient of 0.9392647 and a p-value less than 0.01 for the period spanning from 2000 to 2021. Our findings not only shed light on the soybean-biomass power relationship but also provoke a soy-lful amount of curiosity and excitement. So, brace yourself for an intellectual ride from the heartland of America to the technological marvels of Taiwan - it's a grain and power game!
[[LITERATURE REVIEW]]
As we delve into the tangled web of genetically modified soybeans and the generation of biomass power, the literature presents a mix of serious studies and some unexpected - and perhaps even zany - connections. In their study, "The Impact of GMO Soybean Cultivation on Agricultural Practices" (Smith et al., 2012), the authors find a comprehensive analysis of the adoption and impact of GMO soybeans in Iowa. The study highlights the widespread use of genetically modified soybeans and their influence on yield, pesticide usage, and overall agricultural practices. However, what this study does not cover is the potential ripple effect of these soybeans on the distant energy landscapes of Taiwan.
Another study by Doe et al. (2015), titled "Biomass Power Generation: Challenges and Opportunities," offers an in-depth exploration of the intricacies of biomass power, focusing primarily on technology, policy, and market dynamics. Though informative, this study fails to consider the remote possibility that the humble soybean - albeit genetically modified - could exert any influence on the biomass power industry, particularly on an international scale.
In "Energy Revolution: The Physics and the Politics" (Jones, 2019), the author provides a meticulous examination of the global energy landscape and the potential for renewable energy sources to revolutionize power generation. While the book discusses the economics and politics of energy, it neglects to entertain the notion of an agricultural commodity like soybeans playing a role in the energy revolution, let alone crossing continents to impact the power scene in Taiwan.
Shifting focus from non-fiction to fiction, J.K. Rowling's "Harry Potter and the Goblet of Fire" unexpectedly mentions a soybean plant in the Herbology class at Hogwarts, hinting at the potential magical prowess of this humble crop. Meanwhile, in Michael Pollan's "The Omnivore's Dilemma," the author weaves a narrative around the intricate connections between humans and their food, leaving little room for speculation on the far-reaching implications of soybeans on energy generation.
On a lighter note, the 1989 classic film "Field of Dreams" tells the tale of, well, a field of dreams in Iowa, albeit unrelated to soybeans or biomass power. Nonetheless, the notion of unexpected connections and unanticipated outcomes in unlikely places resonates with our quest to uncover the link between Iowa's soybeans and Taiwan's biomass power.
Now that we have laid the groundwork with the literature review, we are poised to unearth the unexpected and whimsical revelations in our investigation.
[[RESULTS]]
As we delved into the vast expanse of data related to soybean cultivation in Iowa and biomass power generation in Taiwan, we uncovered a striking correlation that sent shockwaves through the agricultural and energy spheres. Our analysis revealed a staggering correlation coefficient of 0.9392647, indicating a robust positive relationship between the usage of genetically modified soybeans in Iowa and the production of biomass power in Taiwan from 2000 to 2021. This correlation was further substantiated by an r-squared value of 0.8822181, signifying that approximately 88.22% of the variability in biomass power generation can be attributed to the usage of GMO soybeans in Iowa. Additionally, the p-value of less than 0.01 reaffirmed the statistical significance of this correlation, dispelling any doubts about the strength of the relationship.
The implications of this correlation are nothing short of monumental, akin to stumbling upon a rare heirloom soybean in a sea of ordinary legumes. Fig. 1 encapsulates this significant finding in a visually compelling manner, depicting a clear and unmistakable positive association between the utilization of GMO soybeans in Iowa and the production of biomass power in Taiwan. Like two peas in a pod, these seemingly disparate elements have woven an intricate bond, nurturing the growth of sustainable energy practices and agri-tech innovations. This revelation not only sheds light on the interconnectedness of global agricultural and energy systems but also prompts a soyful contemplation of the far-reaching impact of genetically modified crops on the renewable energy landscape.
The robustness of the association uncovered in this study underscores the need for future investigations to dig deeper into the mechanistic underpinnings of this soybean-biomass power nexus. As we bask in the afterglow of this remarkable discovery, it becomes abundantly clear that the soy to joy transition is not just a pun; it is a tangible reflection of the symbiotic relationship between agricultural biotechnology and clean energy solutions. This research paves the way for a soy-driven revolution in sustainable energy development, where the humble soybean emerges as an unlikely but pivotal player in the global pursuit of renewable energy sources.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
In discussing the unexpected connection between the use of genetically modified soybeans in Iowa and the generation of biomass power in Taiwan, we find ourselves grappling with a confluence of agricultural and energy factors like trying to fit a square peg into a round bioenergy plant. Our results not only validate the previous serious studies but also offer a saucy addition to the literature, enriching it with an unlikely pairing reminiscent of a quirky rom-com.
Taking a leaf out of Smith et al.'s (2012) comprehensive analysis of GMO soybean cultivation in Iowa, our findings corroborate the widespread adoption of genetically modified soybeans and their significant influence on agricultural practices. It appears that these soybeans are not just a mere side dish to the main course of Iowa’s agricultural landscape but have, in fact, sown the seeds for an unexpected overseas adventure in the form of biomaterials power generation in Taiwan.
Doe et al.'s (2015) exploration of biomass power generation's intricacies misses out on the soybean link, which we have now elucidated. As our findings reveal a notable correlation coefficient, it seems that the soybeans have been quietly whispering to the Taiwanese power landscape, seeding the growth of biomass power. This connection is as surprising as finding a winning lottery ticket in a soybean pod.
In light of our results, we cannot help but embrace the unexpected resonances found in works of fiction, such as J.K. Rowling's brief mention of a soybean plant in "Harry Potter and the Goblet of Fire." If Hogwarts can accommodate the mighty soybean in its Herbology class, then surely, the global energy landscape can accommodate its substantial impact on biomass power generation. The sheer unlikeliness of this connection, akin to a magical spell cast by the soybean, has us questioning the narratives that we have constructed around global energy production.
As we move forward from this study, it is evident that the soybean has truly left an indelible mark on the arena of global renewable energy. It’s as if Iowa’s soybeans and Taiwan's biomass power industry, once strangers in the night, have now waltzed together onto the sustainable energy stage, creating a noteworthy performance that is both surprising and applaud-worthy. While the connection between them might seem peculiar at first glance, our research has laid bare the intertwining roots of agricultural and energy systems, prompting a soy-ful reflection on the potential for unconventional agricultural forces to shape the renewable energy landscape. This is not just another soybeans story, but the commencement of a full-fledged soybean saga in the realm of sustainable energy development.
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 Iowa and Biomass power generated in Taiwan. 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 Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion
[[ABSTRACT]]
Soybeans and Taiwan might seem as unrelated as apples and... biogas, but our research has uncovered a rather illuminating correlation. Our study delves into the potential link between the use of genetically modified soybeans in the cornfields of Iowa and the generation of biomass power in the bustling island of Taiwan. To peel back the layers of this agricultural and energy enigma, we crunched the numbers from USDA and the Energy Information Administration. The results revealed a notable correlation coefficient of 0.9392647 and a p-value less than 0.01 for the period spanning from 2000 to 2021. Our findings not only shed light on the soybean-biomass power relationship but also provoke a soy-lful amount of curiosity and excitement. So, brace yourself for an intellectual ride from the heartland of America to the technological marvels of Taiwan - it's a grain and power game!
[[INTRDUCTION]]
Introduction
As we soar into the 21st century, the world finds itself embroiled in an ever-evolving dance between agricultural innovation and sustainable energy practices. This confluence of forces has brought us to the intriguing intersection of genetically modified soybeans in the heartland of Iowa and the burgeoning production of biomass power on the distant shores of Taiwan. At first glance, one might ponder the connection between these seemingly disparate elements and muse, "What on earth do soybeans and biomass power have in common?"
Our quest to unravel this soybean saga and energy escapade stems from a blend of curiosity and a dash of scientific inquiry. Together, we aim to traverse the sprawling fields of crop genetics and the labyrinthine realm of renewable energy production to uncover any hidden kernels of truth. Let us embark on this expedition with gusto, fueled by the tantalizing prospects of uncovering an unexpected bond between the GMO-laden soybeans of Iowa and the power-packed biomass facilities in Taiwan.
While the association between soybeans in the American Midwest and the energy landscape of East Asia may seem as distant as a GMO-free farm and a soy milk latte, we hypothesize that there exists a discernible correlation that merits a closer examination. We take a bold leap into the realm of data analysis, armed with statistical tools and a healthy dose of skepticism, to test our audacious assertion. So, fasten your seatbelts and prepare for a rollercoaster ride through the worlds of agriculture and energy - you may be in for some soy-prise discoveries!
[[RESULTS]]
As we delved into the vast expanse of data related to soybean cultivation in Iowa and biomass power generation in Taiwan, we uncovered a striking correlation that sent shockwaves through the agricultural and energy spheres. Our analysis revealed a staggering correlation coefficient of 0.9392647, indicating a robust positive relationship between the usage of genetically modified soybeans in Iowa and the production of biomass power in Taiwan from 2000 to 2021. This correlation was further substantiated by an r-squared value of 0.8822181, signifying that approximately 88.22% of the variability in biomass power generation can be attributed to the usage of GMO soybeans in Iowa. Additionally, the p-value of less than 0.01 reaffirmed the statistical significance of this correlation, dispelling any doubts about the strength of the relationship.
The implications of this correlation are nothing short of monumental, akin to stumbling upon a rare heirloom soybean in a sea of ordinary legumes. Fig. 1 encapsulates this significant finding in a visually compelling manner, depicting a clear and unmistakable positive association between the utilization of GMO soybeans in Iowa and the production of biomass power in Taiwan. Like two peas in a pod, these seemingly disparate elements have woven an intricate bond, nurturing the growth of sustainable energy practices and agri-tech innovations. This revelation not only sheds light on the interconnectedness of global agricultural and energy systems but also prompts a soyful contemplation of the far-reaching impact of genetically modified crops on the renewable energy landscape.
The robustness of the association uncovered in this study underscores the need for future investigations to dig deeper into the mechanistic underpinnings of this soybean-biomass power nexus. As we bask in the afterglow of this remarkable discovery, it becomes abundantly clear that the soy to joy transition is not just a pun; it is a tangible reflection of the symbiotic relationship between agricultural biotechnology and clean energy solutions. This research paves the way for a soy-driven revolution in sustainable energy development, where the humble soybean emerges as an unlikely but pivotal player in the global pursuit of renewable energy sources.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
As we wrap up this scholarly soyiree, it's clear that the ties between GMO soybeans in Iowa and biomass power in Taiwan are as tight as a pair of soybean pods. Our findings offer food for thought, or should we say "fuel for thought," as we contemplate the remarkable synergy between these seemingly unrelated entities. It's quite a soy-surprise to see how a crop from the heartlands of Iowa can power up the bustling island of Taiwan, isn't it? It seems the soybeans have gone global, not just in our stir-fries, but also in our energy solutions!
In conclusion, we've cracked the soycode to reveal the entwined fate of soybeans and sustainable power. No more research is needed here – we've pressed the soybutton, and the results speak for themselves. It's time to let this soygantic discovery simmer and sow the seeds of a new era in agricultural and energy integration. Remember, when life gives you soybeans, make soy lecithin – and maybe a few kilowatts of clean energy while you're at it! So, as we bid adieu to our soy-dventure, let's raise a tofu toast to the humble soybean and its unexpected role in powering the world. Cheers to sow much more than meets the eye!
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 Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion. Respond only with the name of a fictional academic journal.
ChatGPT:
The International Journal of Agro-Engineering and Biorenewable 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 From Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion. Respond only with the name of a fictional organization.
ChatGPT:
The Center for Sustainable Agriculture and Biotechnology Research
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 Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion with an abstract of Soybeans and Taiwan might seem as unrelated as apples and... biogas, but our research has uncovered a rather illuminating correlation. Our study delves into the potential link between the use of genetically modified soybeans in the cornfields of Iowa and the generation of biomass power in the bustling island of Taiwan. To peel back the layers of this agricultural and energy enigma, we crunched the numbers from USDA and the Energy Information Administration. The results revealed a notable correlation coefficient of 0.9392647 and a p-value less than 0.01 for the period spanning from 2000 to 2021. Our findings not only shed light on the soybean-biomass power relationship but also provoke a soy-lful amount of curiosity and excitement. So, brace yourself for an intellectual ride from the heartland of America to the technological marvels of Taiwan - it's a grain and power game!
ChatGPT:
soybeans, GMO, Iowa, Taiwan, biomass power, correlation, genetically modified soybeans, agricultural, energy, USDA, Energy Information Administration, soybean-biomass power relationship, intellectual ride, heartland of America, technological marvels
*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 IowaDetailed data title: Percent of soybeans planted in Iowa 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 Iowa
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 = 0.8822181 (Coefficient of determination)
This means 88.2% 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 Iowa) over the 22 years from 2000 through 2021.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 9.6E-11. 0.0000000000958067283331965600
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 0.94 in 9.6E-9% of random cases. Said differently, if you correlated 10,437,680,290 random variables You don't actually need 10 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.
[ 0.86, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
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 Iowa (GMO soybeans %) | 59 | 73 | 75 | 84 | 89 | 91 | 91 | 94 | 95 | 94 | 96 | 97 | 97 | 93 | 97 | 96 | 97 | 94 | 95 | 94 | 93 | 97 |
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([59,73,75,84,89,91,91,94,95,94,96,97,97,93,97,96,97,94,95,94,93,97,])
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 Iowa"
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)
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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.
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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 Iowa
- Line chart for only Biomass power generated in Taiwan
- The spurious research paper: From Soy to Joy: The GMO-Grown Iowa Soybean Connection to Taiwan's Biomass Power Commotion
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Correlation ID: 1252 · Black Variable ID: 816 · Red Variable ID: 24024