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AI explanation
The genetically modified corn started producing energy-charged kernels, leading to more efficient biomass power generation in Austria. The corn literally became a-maize-ing fuel, creating a cob-bustion reaction in the power production process. This unexpected power plant growth spurt could only be attributed to the ear-resistible impact of GMO corn from Illinois, proving that when it comes to energy, it's all about that corn-verted power!Model: dalle-3
Prompt: Prompt: [ Cute cartoon ] Visual: In a whimsical cartoon style, imagine a golden field in Illinois filled with larger-than-life, adorable GMO cornstalks. Each stalk has a friendly, playful expression on its vibrant green leaves and a sunny disposition as they reach for the sunlight. A cheery tractor is seen busily harvesting the bountiful corn amidst the swaying cornstalks. Transitioning to the Austrian countryside, envision a charming power plant nestled amid the lush green hills. The plant appears as a cheerful character, with smiling silos and friendly turbines, emitting a magical, bright energy from the converted surplus corn stalks. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:
Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: GMO use in corn grown in Illinois and Biomass power generated in Austria. 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: Woodblock painting Whimsical illustration Cute cartoon Charcoal Cutsy graphics
ChatGPT: Cute cartoon
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both GMO use in corn grown in Illinois and Biomass power generated in Austria, in the following situation: The increase in GMO use in Illinois corn led to higher yields, which in turn led to more corn stalks being available for biomass power generation in Austria. The genetically modified corn must have had some kind of magical energy-boosting powers!. Keep the description simple.
ChatGPT: In a golden field in Illinois, towering GMO cornstalks sway in the breeze, their vibrant green leaves reaching for the sunlight. The neatly arranged rows stretch far into the distance, a testament to the increase in GMO use that has led to higher yields. Nearby, a tractor hums as it harvests the bountiful corn. Meanwhile, in the picturesque Austrian countryside, a power plant is surrounded by lush green hills. Smoke billows from the chimney as the facility converts the surplus corn stalks into energy, producing biomass power. The tall silos and turbines stand as a testament to the magical energy-boosting powers of the genetically modified corn, as it lights up the surrounding rural landscape.
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: [ Cute cartoon ] and depicting this scene: In a golden field in Illinois, towering GMO cornstalks sway in the breeze, their vibrant green leaves reaching for the sunlight. The neatly arranged rows stretch far into the distance, a testament to the increase in GMO use that has led to higher yields. Nearby, a tractor hums as it harvests the bountiful corn. Meanwhile, in the picturesque Austrian countryside, a power plant is surrounded by lush green hills. Smoke billows from the chimney as the facility converts the surplus corn stalks into energy, producing biomass power. The tall silos and turbines stand as a testament to the magical energy-boosting powers of the genetically modified corn, as it lights up the surrounding rural landscape. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: [ Cute cartoon ] Visual: In a whimsical cartoon style, imagine a golden field in Illinois filled with larger-than-life, adorable GMO cornstalks. Each stalk has a friendly, playful expression on its vibrant green leaves and a sunny disposition as they reach for the sunlight. A cheery tractor is seen busily harvesting the bountiful corn amidst the swaying cornstalks. Transitioning to the Austrian countryside, envision a charming power plant nestled amid the lush green hills. The plant appears as a cheerful character, with smiling silos and friendly turbines, emitting a magical, bright energy from the converted surplus corn stalks.
*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 corn grown in Illinois caused Biomass power generated in Austria to increase.
AI academic paper
MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria The Journal of Agricultural Innovation and Global Resource Management Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between GMO use in corn grown in Illinois and Biomass power generated in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Make the title a clever pun.
Your research team used data from USDA and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.9769152 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]]
MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria
[[ABSTRACT]]
The potential impact of genetically modified organisms (GMOs) on agricultural and energy sectors has been the subject of intense debate, sprouting various hypotheses and kernels of insight. Our study delves into the cornucopia of data to uncover the cob-nection between the use of GMO corn in Illinois and the generation of biomass power in Austria. Utilizing USDA and Energy Information Administration data from 2000 to 2021, we cultivated a comprehensive analysis to corn-firm our findings.
Analyzing the data sprouted some surprising results. We discovered a startling correlation coefficient of 0.9769152 between the use of GMO corn in Illinois and the generation of biomass power in Austria, with a p-value of less than 0.01. This strong correlation leaves husk little doubt about the potential impact of GMO corn cultivation on the generation of biomass power overseas.
The findings of our study pop with significance, indicating a robust relationship between GMO corn in the American heartland and the production of renewable energy in the mountains of Austria. Our results suggest that the planting of genetically modified corn in Illinois is positively correlated with the generation of biomass power in Austria, planting the seeds for further exploration into the burgeoning field of agricultural and energy interactions.
As a corny side note, our research sprouted a few kernels of wisdom along the way, but we couldn't husk the feeling that there's still a-maize-ing potential for further investigation in this field!
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between GMO use in corn grown in Illinois and Biomass power generated in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Here is the title and abstract of the paper:
[[TITLE]]
MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria
[[ABSTRACT]]
The potential impact of genetically modified organisms (GMOs) on agricultural and energy sectors has been the subject of intense debate, sprouting various hypotheses and kernels of insight. Our study delves into the cornucopia of data to uncover the cob-nection between the use of GMO corn in Illinois and the generation of biomass power in Austria. Utilizing USDA and Energy Information Administration data from 2000 to 2021, we cultivated a comprehensive analysis to corn-firm our findings.
Analyzing the data sprouted some surprising results. We discovered a startling correlation coefficient of 0.9769152 between the use of GMO corn in Illinois and the generation of biomass power in Austria, with a p-value of less than 0.01. This strong correlation leaves husk little doubt about the potential impact of GMO corn cultivation on the generation of biomass power overseas.
The findings of our study pop with significance, indicating a robust relationship between GMO corn in the American heartland and the production of renewable energy in the mountains of Austria. Our results suggest that the planting of genetically modified corn in Illinois is positively correlated with the generation of biomass power in Austria, planting the seeds for further exploration into the burgeoning field of agricultural and energy interactions.
As a corny side note, our research sprouted a few kernels of wisdom along the way, but we couldn't husk the feeling that there's still a-maize-ing potential for further investigation in this field!
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
The buzz surrounding genetically modified organisms (GMOs) in the agricultural world is stalk rising, with debates as heated as a freshly popped kernel. The cobs and cons of GMO corn cultivation have been thoroughly dissected, leaving many researchers kernels of doubt about their impact on various facets of the agricultural and energy sectors.
While the GMO corn debate continues to corn-tinue, our study seeks to shed light on a different facet of this cornundrum. By scrutinizing the relationship between the use of GMO corn in Illinois and the generation of biomass power in Austria, we aim to peel back the layers of this complex issue and reveal the cob-nection between corn cultivation and renewable energy production.
As we delve into the data, we aim to squash any doubts about the significance of our findings. Our research sprouted from a simple question: could there be a correlation between the cultivation of GMO corn in Illinois, known for its vast cornfields and nostalgia-inducing corn mazes, and the production of biomass power in a country like Austria, where the hills are truly alive with the sound of renewable energy?
Before we corn-clude, it's worth noting that this study isn't just a mere kernel of an idea. With the growing interest in sustainable energy sources and the widespread use of GMOs in modern agriculture, our research aims to kernel the potential implications of these practices on a global scale.
Now, let's dig into the data and see if we can uncover the root cause of the cob-nection between GMO corn and biomass power. It's time to separate the chaff from the wheat and sift through the evidence to appraise the corn-sequences of GMO corn cultivation on renewable energy production.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between GMO use in corn grown in Illinois and Biomass power generated in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.
Here is the title and abstract of the paper:
[[TITLE]]
MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria
[[ABSTRACT]]
The potential impact of genetically modified organisms (GMOs) on agricultural and energy sectors has been the subject of intense debate, sprouting various hypotheses and kernels of insight. Our study delves into the cornucopia of data to uncover the cob-nection between the use of GMO corn in Illinois and the generation of biomass power in Austria. Utilizing USDA and Energy Information Administration data from 2000 to 2021, we cultivated a comprehensive analysis to corn-firm our findings.
Analyzing the data sprouted some surprising results. We discovered a startling correlation coefficient of 0.9769152 between the use of GMO corn in Illinois and the generation of biomass power in Austria, with a p-value of less than 0.01. This strong correlation leaves husk little doubt about the potential impact of GMO corn cultivation on the generation of biomass power overseas.
The findings of our study pop with significance, indicating a robust relationship between GMO corn in the American heartland and the production of renewable energy in the mountains of Austria. Our results suggest that the planting of genetically modified corn in Illinois is positively correlated with the generation of biomass power in Austria, planting the seeds for further exploration into the burgeoning field of agricultural and energy interactions.
As a corny side note, our research sprouted a few kernels of wisdom along the way, but we couldn't husk the feeling that there's still a-maize-ing potential for further investigation in this field!
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The buzz surrounding genetically modified organisms (GMOs) in the agricultural world is stalk rising, with debates as heated as a freshly popped kernel. The cobs and cons of GMO corn cultivation have been thoroughly dissected, leaving many researchers kernels of doubt about their impact on various facets of the agricultural and energy sectors.
While the GMO corn debate continues to corn-tinue, our study seeks to shed light on a different facet of this cornundrum. By scrutinizing the relationship between the use of GMO corn in Illinois and the generation of biomass power in Austria, we aim to peel back the layers of this complex issue and reveal the cob-nection between corn cultivation and renewable energy production.
As we delve into the data, we aim to squash any doubts about the significance of our findings. Our research sprouted from a simple question: could there be a correlation between the cultivation of GMO corn in Illinois, known for its vast cornfields and nostalgia-inducing corn mazes, and the production of biomass power in a country like Austria, where the hills are truly alive with the sound of renewable energy?
Before we corn-clude, it's worth noting that this study isn't just a mere kernel of an idea. With the growing interest in sustainable energy sources and the widespread use of GMOs in modern agriculture, our research aims to kernel the potential implications of these practices on a global scale.
Now, let's dig into the data and see if we can uncover the root cause of the cob-nection between GMO corn and biomass power. It's time to separate the chaff from the wheat and sift through the evidence to appraise the corn-sequences of GMO corn cultivation on renewable energy production.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The connection between genetically modified organisms (GMOs) in corn cultivation and biomass power generation has been the subject of intense study, with researchers sifting through data like kernels of corn in search of cornclusive evidence. In "Smith et al.'s study," the authors find that GMO corn cultivation in Illinois has been on the rise, with significant implications for both the agricultural sector and energy production. The potential impact of this trend on international renewable energy generation has garnered considerable interest and debate.
As we cob-tain insight from a variety of sources, it becomes clear that the relationship between GMO corn and biomass power is the cornerstone of a-maize-ing potential for future research. In "Doe and Jones' analysis," the authors highlight the intricate cob-nection between agricultural practices and energy systems, opening new avenues for further exploration. This analysis seems to pop some questions, such as whether GMO corn has the potential to fuel not just livestock and human consumption, but also the generation of renewable energy.
And speaking of potential, one can't help but recall the classic works on agriculture and energy, such as "The Omnivore's Dilemma" by Michael Pollan and "The Quest" by Daniel Yergin. These works, like a field of corn in the summer, provide fertile ground for understanding the complexities of the modern food and energy systems. The literature review corn-tinues to sprout novel insights, with "The Overstory" by Richard Powers offering a leafy perspective on the interconnectedness of natural systems and human activities, akin to the intertwined roots of corn in an agricultural plot.
In our quest for knowledge, we couldn't help but dig a little deeper into unconventional sources, including the backs of shampoo bottles for an anthropological perspective on the curious habits of consumers. Surprisingly, we found that lathering and rinsing may not directly correlate with the generation of renewable energy in Austria, but the potential for a good hair day could indeed spark a positive outlook on sustainable practices.
The growth in interest around this topic is truly organic, with researchers corn-victed that uncovering the cob-nection between GMO corn in Illinois and biomass power in Austria holds the potential to reap fruitful insights for sustainable agricultural and energy practices. As we peel back the layers of this topic, it is clear that this field is ripe for further exploration, and we are eager to husk the potential implications for global energy and agricultural systems.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between GMO use in corn grown in Illinois and Biomass power generated in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
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]]
MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria
[[ABSTRACT]]
The potential impact of genetically modified organisms (GMOs) on agricultural and energy sectors has been the subject of intense debate, sprouting various hypotheses and kernels of insight. Our study delves into the cornucopia of data to uncover the cob-nection between the use of GMO corn in Illinois and the generation of biomass power in Austria. Utilizing USDA and Energy Information Administration data from 2000 to 2021, we cultivated a comprehensive analysis to corn-firm our findings.
Analyzing the data sprouted some surprising results. We discovered a startling correlation coefficient of 0.9769152 between the use of GMO corn in Illinois and the generation of biomass power in Austria, with a p-value of less than 0.01. This strong correlation leaves husk little doubt about the potential impact of GMO corn cultivation on the generation of biomass power overseas.
The findings of our study pop with significance, indicating a robust relationship between GMO corn in the American heartland and the production of renewable energy in the mountains of Austria. Our results suggest that the planting of genetically modified corn in Illinois is positively correlated with the generation of biomass power in Austria, planting the seeds for further exploration into the burgeoning field of agricultural and energy interactions.
As a corny side note, our research sprouted a few kernels of wisdom along the way, but we couldn't husk the feeling that there's still a-maize-ing potential for further investigation in this field!
[[INTRODUCTION]]
The buzz surrounding genetically modified organisms (GMOs) in the agricultural world is stalk rising, with debates as heated as a freshly popped kernel. The cobs and cons of GMO corn cultivation have been thoroughly dissected, leaving many researchers kernels of doubt about their impact on various facets of the agricultural and energy sectors.
While the GMO corn debate continues to corn-tinue, our study seeks to shed light on a different facet of this cornundrum. By scrutinizing the relationship between the use of GMO corn in Illinois and the generation of biomass power in Austria, we aim to peel back the layers of this complex issue and reveal the cob-nection between corn cultivation and renewable energy production.
As we delve into the data, we aim to squash any doubts about the significance of our findings. Our research sprouted from a simple question: could there be a correlation between the cultivation of GMO corn in Illinois, known for its vast cornfields and nostalgia-inducing corn mazes, and the production of biomass power in a country like Austria, where the hills are truly alive with the sound of renewable energy?
Before we corn-clude, it's worth noting that this study isn't just a mere kernel of an idea. With the growing interest in sustainable energy sources and the widespread use of GMOs in modern agriculture, our research aims to kernel the potential implications of these practices on a global scale.
Now, let's dig into the data and see if we can uncover the root cause of the cob-nection between GMO corn and biomass power. It's time to separate the chaff from the wheat and sift through the evidence to appraise the corn-sequences of GMO corn cultivation on renewable energy production.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To kernel down to the bottom of the cob-nection between GMO corn in Illinois and biomass power in Austria, our research team employed a kernel of creative research methods that would make even the most seasoned statistician green with envy. We compiled data from various sources, mainly drawing from the United States Department of Agriculture (USDA) and the Energy Information Administration (EIA) to gather a vast harvest of information spanning from 2000 to 2021.
Our first step was to cobble together a comprehensive database of GMO corn production in Illinois over the specified timeframe. We employed a method affectionately dubbed the "cornucopia algorithm," which involved digitally shucking and jiving through acres of data from USDA reports, crop surveys, and even the odd cornfield selfie on social media. We then cross-pollinated this data with regional weather patterns and fertilizer usage to weed out any potential confounding variables and ensure we were cob-fident in the accuracy of our findings.
Once our corn database was as ripe as a midsummer ear, we turned our attention to harvesting data on biomass power generation in Austria. This required a bit of transcontinental pollination, as we combed through EIA datasets, international energy reports, and even consulted with a few well-placed sources in the alpine energy sector. Our approach, affectionately called the "biomass bumblebee technique," involved flitting from dataset to dataset, gathering nectar in the form of kilowatt-hours and carbon emissions, before returning to the hive of statistical analysis.
To ensure the integrity of our findings, we cultivated a meticulous approach to data cleansing and standardization, uprooting any outliers or data silage that threatened to contaminate our results. We employed a cutting-edge statistical technique, which we aptly named the "cornstalk cleansing method," designed to prune away any extraneous data points and leave behind a field of pristine statistical significance.
In the spirit of full transparency, it's worth acknowledging that our research methods may have had some husky limitations, much like a trusty old combine harvester with a stubborn hitch. Despite our best efforts, there may be some unaccounted-for variability in the data that evaded our meticulous harvesting process. Nonetheless, we are confident that the crop of data we've cultivated provides a robust foundation for our subsequent analysis.
Our data analysis truly germinated under the careful watch of statistical scrutiny, with a bountiful harvest of correlation analysis, regression modeling, and hypothesis testing. We employed the tried and true techniques of regression analysis to unearth the cob-nection between GMO corn use in Illinois and biomass power generation in Austria, all the while ensuring that our statistical models were as airtight as a silo in October.
In the spirit of academic integrity, it's important to note that our findings may be subject to potential biases or unaccounted sources of variability. Like a farmer keeping an eye on the weather, we remained vigilant in considering potential confounding factors that could cloud the sunny skies of our conclusions.
In the end, our methodology may have resembled more of a statistical hoedown than a meticulously orchestrated ballet, but we're confident that our research methods have provided a robust foundation for understanding the cob-nection between GMO corn cultivation in the heartland of America and the generation of renewable energy in the mountains of Austria.
Now, with our methodology freshly husked and polished, we can turn our attention to the rich harvest of results that our data has yielded. But first, a seed of wisdom: What do you call a group of musical corn cobs? A "corn-ert ensemble"!
That wraps up my methodology section. Can I help you with anything else?
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between GMO use in corn grown in Illinois and Biomass power generated in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
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 0.9769152, r-squared of 0.9543633, 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]]
MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria
[[ABSTRACT]]
The potential impact of genetically modified organisms (GMOs) on agricultural and energy sectors has been the subject of intense debate, sprouting various hypotheses and kernels of insight. Our study delves into the cornucopia of data to uncover the cob-nection between the use of GMO corn in Illinois and the generation of biomass power in Austria. Utilizing USDA and Energy Information Administration data from 2000 to 2021, we cultivated a comprehensive analysis to corn-firm our findings.
Analyzing the data sprouted some surprising results. We discovered a startling correlation coefficient of 0.9769152 between the use of GMO corn in Illinois and the generation of biomass power in Austria, with a p-value of less than 0.01. This strong correlation leaves husk little doubt about the potential impact of GMO corn cultivation on the generation of biomass power overseas.
The findings of our study pop with significance, indicating a robust relationship between GMO corn in the American heartland and the production of renewable energy in the mountains of Austria. Our results suggest that the planting of genetically modified corn in Illinois is positively correlated with the generation of biomass power in Austria, planting the seeds for further exploration into the burgeoning field of agricultural and energy interactions.
As a corny side note, our research sprouted a few kernels of wisdom along the way, but we couldn't husk the feeling that there's still a-maize-ing potential for further investigation in this field!
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
The buzz surrounding genetically modified organisms (GMOs) in the agricultural world is stalk rising, with debates as heated as a freshly popped kernel. The cobs and cons of GMO corn cultivation have been thoroughly dissected, leaving many researchers kernels of doubt about their impact on various facets of the agricultural and energy sectors.
While the GMO corn debate continues to corn-tinue, our study seeks to shed light on a different facet of this cornundrum. By scrutinizing the relationship between the use of GMO corn in Illinois and the generation of biomass power in Austria, we aim to peel back the layers of this complex issue and reveal the cob-nection between corn cultivation and renewable energy production.
As we delve into the data, we aim to squash any doubts about the significance of our findings. Our research sprouted from a simple question: could there be a correlation between the cultivation of GMO corn in Illinois, known for its vast cornfields and nostalgia-inducing corn mazes, and the production of biomass power in a country like Austria, where the hills are truly alive with the sound of renewable energy?
Before we corn-clude, it's worth noting that this study isn't just a mere kernel of an idea. With the growing interest in sustainable energy sources and the widespread use of GMOs in modern agriculture, our research aims to kernel the potential implications of these practices on a global scale.
Now, let's dig into the data and see if we can uncover the root cause of the cob-nection between GMO corn and biomass power. It's time to separate the chaff from the wheat and sift through the evidence to appraise the corn-sequences of GMO corn cultivation on renewable energy production.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The correlation analysis conducted revealed a strong positive correlation of 0.9769152 between the use of genetically modified (GMO) corn in Illinois and the generation of biomass power in Austria. This correlation suggests a robust relationship between the cultivation of GMO corn in the heartland of the United States and the production of renewable energy in the beautiful country of Austria.
The r-squared value of 0.9543633 indicated that a whopping 95.4% of the variance in biomass power generated in Austria can be corn-fidently explained by the use of GMO corn in Illinois. This result indicates a remarkable degree of predictability and provides strong evidence for the cob-nection between GMO corn cultivation and biomass power generation overseas.
The p-value of less than 0.01 further reinforces the significance of our findings, leaving little room for corn-tradictory interpretations. This finding suggests that it is highly unlikely that the strong correlation observed is a result of random chance, bolstering the validity of our research. As the old adage goes, "where there's a will, there's a maize."
Upon visual inspection, the scatterplot (Fig. 1) depicting the relationship between GMO corn use in Illinois and biomass power generated in Austria demonstrates a clear and compelling pattern. The data points coalesce to form a positively sloped line, underscoring the strong positive correlation between these two variables. It's almost as if the data itself is a-maize-ing at the strength of the association!
In summary, our analysis reveals a significant and robust cob-nection between the use of GMO corn in Illinois and the generation of biomass power in Austria. These findings highlight the potential implications of GMO corn cultivation on renewable energy production and sow the seeds for further exploration in this burgeoning field of agricultural and energy interactions.
Before we corn-clude, let's not forget the timeless wisdom of the agricultural world: "What do you call a group of musical corn cobs? A-corn band!" With that kernel of humor, we plant the seed for future research in this ear-resistible field.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between GMO use in corn grown in Illinois and Biomass power generated in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
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]]
MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria
[[ABSTRACT]]
The potential impact of genetically modified organisms (GMOs) on agricultural and energy sectors has been the subject of intense debate, sprouting various hypotheses and kernels of insight. Our study delves into the cornucopia of data to uncover the cob-nection between the use of GMO corn in Illinois and the generation of biomass power in Austria. Utilizing USDA and Energy Information Administration data from 2000 to 2021, we cultivated a comprehensive analysis to corn-firm our findings.
Analyzing the data sprouted some surprising results. We discovered a startling correlation coefficient of 0.9769152 between the use of GMO corn in Illinois and the generation of biomass power in Austria, with a p-value of less than 0.01. This strong correlation leaves husk little doubt about the potential impact of GMO corn cultivation on the generation of biomass power overseas.
The findings of our study pop with significance, indicating a robust relationship between GMO corn in the American heartland and the production of renewable energy in the mountains of Austria. Our results suggest that the planting of genetically modified corn in Illinois is positively correlated with the generation of biomass power in Austria, planting the seeds for further exploration into the burgeoning field of agricultural and energy interactions.
As a corny side note, our research sprouted a few kernels of wisdom along the way, but we couldn't husk the feeling that there's still a-maize-ing potential for further investigation in this field!
[[LITERATURE REVIEW]]
The connection between genetically modified organisms (GMOs) in corn cultivation and biomass power generation has been the subject of intense study, with researchers sifting through data like kernels of corn in search of cornclusive evidence. In "Smith et al.'s study," the authors find that GMO corn cultivation in Illinois has been on the rise, with significant implications for both the agricultural sector and energy production. The potential impact of this trend on international renewable energy generation has garnered considerable interest and debate.
As we cob-tain insight from a variety of sources, it becomes clear that the relationship between GMO corn and biomass power is the cornerstone of a-maize-ing potential for future research. In "Doe and Jones' analysis," the authors highlight the intricate cob-nection between agricultural practices and energy systems, opening new avenues for further exploration. This analysis seems to pop some questions, such as whether GMO corn has the potential to fuel not just livestock and human consumption, but also the generation of renewable energy.
And speaking of potential, one can't help but recall the classic works on agriculture and energy, such as "The Omnivore's Dilemma" by Michael Pollan and "The Quest" by Daniel Yergin. These works, like a field of corn in the summer, provide fertile ground for understanding the complexities of the modern food and energy systems. The literature review corn-tinues to sprout novel insights, with "The Overstory" by Richard Powers offering a leafy perspective on the interconnectedness of natural systems and human activities, akin to the intertwined roots of corn in an agricultural plot.
In our quest for knowledge, we couldn't help but dig a little deeper into unconventional sources, including the backs of shampoo bottles for an anthropological perspective on the curious habits of consumers. Surprisingly, we found that lathering and rinsing may not directly correlate with the generation of renewable energy in Austria, but the potential for a good hair day could indeed spark a positive outlook on sustainable practices.
The growth in interest around this topic is truly organic, with researchers corn-victed that uncovering the cob-nection between GMO corn in Illinois and biomass power in Austria holds the potential to reap fruitful insights for sustainable agricultural and energy practices. As we peel back the layers of this topic, it is clear that this field is ripe for further exploration, and we are eager to husk the potential implications for global energy and agricultural systems.
[[RESULTS]]
The correlation analysis conducted revealed a strong positive correlation of 0.9769152 between the use of genetically modified (GMO) corn in Illinois and the generation of biomass power in Austria. This correlation suggests a robust relationship between the cultivation of GMO corn in the heartland of the United States and the production of renewable energy in the beautiful country of Austria.
The r-squared value of 0.9543633 indicated that a whopping 95.4% of the variance in biomass power generated in Austria can be corn-fidently explained by the use of GMO corn in Illinois. This result indicates a remarkable degree of predictability and provides strong evidence for the cob-nection between GMO corn cultivation and biomass power generation overseas.
The p-value of less than 0.01 further reinforces the significance of our findings, leaving little room for corn-tradictory interpretations. This finding suggests that it is highly unlikely that the strong correlation observed is a result of random chance, bolstering the validity of our research. As the old adage goes, "where there's a will, there's a maize."
Upon visual inspection, the scatterplot (Fig. 1) depicting the relationship between GMO corn use in Illinois and biomass power generated in Austria demonstrates a clear and compelling pattern. The data points coalesce to form a positively sloped line, underscoring the strong positive correlation between these two variables. It's almost as if the data itself is a-maize-ing at the strength of the association!
In summary, our analysis reveals a significant and robust cob-nection between the use of GMO corn in Illinois and the generation of biomass power in Austria. These findings highlight the potential implications of GMO corn cultivation on renewable energy production and sow the seeds for further exploration in this burgeoning field of agricultural and energy interactions.
Before we corn-clude, let's not forget the timeless wisdom of the agricultural world: "What do you call a group of musical corn cobs? A-corn band!" With that kernel of humor, we plant the seed for future research in this ear-resistible field.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The results of our study unearth a compelling cob-nection between the use of genetically modified organisms (GMOs) in corn cultivation in Illinois and the generation of biomass power in Austria. The findings corroborate prior research, particularly the work of Smith et al., which highlighted the increasing prevalence of GMO corn cultivation in Illinois and its potential implications for both agriculture and energy production. Our study's robust correlation coefficient of 0.9769152 aligns with these previous observations, suggesting a strong relationship between GMO corn and biomass power generation overseas. It's corn-firming to see that our findings have rooted themselves in the existing body of research.
In addition, our analysis sprouted a r-squared value of 0.9543633, indicating that a substantial 95.4% of the variance in biomass power generated in Austria can be accounted for by the use of GMO corn in Illinois. This result reinforces the notion put forward by Doe and Jones, who emphasized the intricate cob-nection between agricultural practices and energy systems, providing further support for the impact of GMO corn cultivation on renewable energy production. It's almost as if our data is whispering "kernels of truth" to those who are willing to listen.
The p-value of less than 0.01 provides a husk-strong endorsement of the significance of our findings, in line with the scholarly consensus that has been growing around this emerging research area. This aligns with the exhortation by agriculturalists that understanding the cob-nection between GMO corn in Illinois and biomass power in Austria can sow the seeds for a more sustainable future in both agriculture and energy.
As we reflected on the visual depiction of our findings in the scatterplot (Fig. 1), it's hard not to admire how the data points seem to align in harmony, almost like the members of a well-organized a-corn band! This compelling illustration underscores the a-maize-ing strength of the association we have uncovered.
In conclusion, our study has unearthed a kernel of truth in the agricultural and energy landscape, highlighting the symbiotic relationship between the use of GMO corn in Illinois and the generation of biomass power in Austria. While our research is ripe with insights, we are excited by the a-maize-ing potential for future investigation in this field.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between GMO use in corn grown in Illinois and Biomass power generated in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
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]]
MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria
[[ABSTRACT]]
The potential impact of genetically modified organisms (GMOs) on agricultural and energy sectors has been the subject of intense debate, sprouting various hypotheses and kernels of insight. Our study delves into the cornucopia of data to uncover the cob-nection between the use of GMO corn in Illinois and the generation of biomass power in Austria. Utilizing USDA and Energy Information Administration data from 2000 to 2021, we cultivated a comprehensive analysis to corn-firm our findings.
Analyzing the data sprouted some surprising results. We discovered a startling correlation coefficient of 0.9769152 between the use of GMO corn in Illinois and the generation of biomass power in Austria, with a p-value of less than 0.01. This strong correlation leaves husk little doubt about the potential impact of GMO corn cultivation on the generation of biomass power overseas.
The findings of our study pop with significance, indicating a robust relationship between GMO corn in the American heartland and the production of renewable energy in the mountains of Austria. Our results suggest that the planting of genetically modified corn in Illinois is positively correlated with the generation of biomass power in Austria, planting the seeds for further exploration into the burgeoning field of agricultural and energy interactions.
As a corny side note, our research sprouted a few kernels of wisdom along the way, but we couldn't husk the feeling that there's still a-maize-ing potential for further investigation in this field!
[[INTRDUCTION]]
The buzz surrounding genetically modified organisms (GMOs) in the agricultural world is stalk rising, with debates as heated as a freshly popped kernel. The cobs and cons of GMO corn cultivation have been thoroughly dissected, leaving many researchers kernels of doubt about their impact on various facets of the agricultural and energy sectors.
While the GMO corn debate continues to corn-tinue, our study seeks to shed light on a different facet of this cornundrum. By scrutinizing the relationship between the use of GMO corn in Illinois and the generation of biomass power in Austria, we aim to peel back the layers of this complex issue and reveal the cob-nection between corn cultivation and renewable energy production.
As we delve into the data, we aim to squash any doubts about the significance of our findings. Our research sprouted from a simple question: could there be a correlation between the cultivation of GMO corn in Illinois, known for its vast cornfields and nostalgia-inducing corn mazes, and the production of biomass power in a country like Austria, where the hills are truly alive with the sound of renewable energy?
Before we corn-clude, it's worth noting that this study isn't just a mere kernel of an idea. With the growing interest in sustainable energy sources and the widespread use of GMOs in modern agriculture, our research aims to kernel the potential implications of these practices on a global scale.
Now, let's dig into the data and see if we can uncover the root cause of the cob-nection between GMO corn and biomass power. It's time to separate the chaff from the wheat and sift through the evidence to appraise the corn-sequences of GMO corn cultivation on renewable energy production.
[[RESULTS]]
The correlation analysis conducted revealed a strong positive correlation of 0.9769152 between the use of genetically modified (GMO) corn in Illinois and the generation of biomass power in Austria. This correlation suggests a robust relationship between the cultivation of GMO corn in the heartland of the United States and the production of renewable energy in the beautiful country of Austria.
The r-squared value of 0.9543633 indicated that a whopping 95.4% of the variance in biomass power generated in Austria can be corn-fidently explained by the use of GMO corn in Illinois. This result indicates a remarkable degree of predictability and provides strong evidence for the cob-nection between GMO corn cultivation and biomass power generation overseas.
The p-value of less than 0.01 further reinforces the significance of our findings, leaving little room for corn-tradictory interpretations. This finding suggests that it is highly unlikely that the strong correlation observed is a result of random chance, bolstering the validity of our research. As the old adage goes, "where there's a will, there's a maize."
Upon visual inspection, the scatterplot (Fig. 1) depicting the relationship between GMO corn use in Illinois and biomass power generated in Austria demonstrates a clear and compelling pattern. The data points coalesce to form a positively sloped line, underscoring the strong positive correlation between these two variables. It's almost as if the data itself is a-maize-ing at the strength of the association!
In summary, our analysis reveals a significant and robust cob-nection between the use of GMO corn in Illinois and the generation of biomass power in Austria. These findings highlight the potential implications of GMO corn cultivation on renewable energy production and sow the seeds for further exploration in this burgeoning field of agricultural and energy interactions.
Before we corn-clude, let's not forget the timeless wisdom of the agricultural world: "What do you call a group of musical corn cobs? A-corn band!" With that kernel of humor, we plant the seed for future research in this ear-resistible field.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
To shell-ebrate the findings of our study, let's take a moment to appreciate the ear-resistible cob-nection we've unearthed between GMO corn in Illinois and biomass power generation in Austria. Our results yield kernel-to-kernel insights into the potential impact of genetically modified corn cultivation on renewable energy production, showcasing a-maize-ing potential for further exploration in this field.
The strong positive correlation coefficient and impressively high r-squared value illustrate the husk-tounding degree to which the use of GMO corn in the heartland of the United States can predict the production of biomass power in the picturesque hills of Austria. It's almost as if these variables are perfectly in-corn-porated into a well-choreographed dance of agricultural and energy synergy.
Now, let's address the elephant in the room - or should I say, the elephant-eared cornstalk? It's clear that the findings of our study point to a corn-cise relationship between GMO corn cultivation and biomass power generation. The data speaks for itself, and it's a-maize-ing how well it articulates the cob-nection between these seemingly unrelated variables.
With our research findings in hand, we can confidently say that the debate around GMOs and their impact on energy sectors may have just reached a new ear-a. As we wrap up, let's not forget the timeless wisdom of the agricultural world: "What does a corn say when it gets a compliment? Aw, shucks!"
In summary, we assert with corn-fidence that no more research is needed in this field. Our findings have husked the potential implications of GMO corn cultivation on renewable energy production, leaving no cob-tradictory interpretations. It's time to pop the champagne and corn-memorate the conclusion of an ear-resistible study.
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 MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Agricultural Innovation and Global Resource Management
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 MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria. Respond only with the name of a fictional organization.
ChatGPT:
Alliance for Agricultural Advancement and Environmental Sustainability
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 MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria with an abstract of The potential impact of genetically modified organisms (GMOs) on agricultural and energy sectors has been the subject of intense debate, sprouting various hypotheses and kernels of insight. Our study delves into the cornucopia of data to uncover the cob-nection between the use of GMO corn in Illinois and the generation of biomass power in Austria. Utilizing USDA and Energy Information Administration data from 2000 to 2021, we cultivated a comprehensive analysis to corn-firm our findings.
Analyzing the data sprouted some surprising results. We discovered a startling correlation coefficient of 0.9769152 between the use of GMO corn in Illinois and the generation of biomass power in Austria, with a p-value of less than 0.01. This strong correlation leaves husk little doubt about the potential impact of GMO corn cultivation on the generation of biomass power overseas.
The findings of our study pop with significance, indicating a robust relationship between GMO corn in the American heartland and the production of renewable energy in the mountains of Austria. Our results suggest that the planting of genetically modified corn in Illinois is positively correlated with the generation of biomass power in Austria, planting the seeds for further exploration into the burgeoning field of agricultural and energy interactions.
As a corny side note, our research sprouted a few kernels of wisdom along the way, but we couldn't husk the feeling that there's still a-maize-ing potential for further investigation in this field!
ChatGPT:
GMO corn, Illinois, biomass power, Austria, genetically modified organisms, agricultural sector, energy sector, correlation coefficient, USDA data, Energy Information Administration data, renewable energy, corn cultivation, biomass power generation, genetically modified corn, agricultural and energy interactions, research, investigation.
*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 corn grown in IllinoisDetailed data title: Percent of all corn planted in Illinois that is genetically modified
Source: USDA
See what else correlates with GMO use in corn grown in Illinois
Biomass power generated in Austria
Detailed data title: Total biomass power generated in Austria in billion kWh
Source: Energy Information Administration
See what else correlates with Biomass power generated in Austria
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 = 0.9543633 (Coefficient of determination)
This means 95.4% of the change in the one variable (i.e., Biomass power generated in Austria) is predictable based on the change in the other (i.e., GMO use in corn grown in Illinois) over the 22 years from 2000 through 2021.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 7.05E-15. 0.0000000000000070524989090677
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 0.98 in 7.05E-13% of random cases. Said differently, if you correlated 141,793,712,114,476 random variables You don't actually need 141 trillion 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.
[ 0.94, 0.99 ] 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 corn grown in Illinois (GMO corn %) | 17 | 16 | 22 | 28 | 33 | 36 | 55 | 74 | 80 | 84 | 82 | 86 | 85 | 89 | 91 | 93 | 93 | 92 | 95 | 93 | 94 | 92 |
Biomass power generated in Austria (Billion kWh) | 1.656 | 1.888 | 1.739 | 1.939 | 2.334 | 2.879 | 3.775 | 4.597 | 4.763 | 4.884 | 5.069 | 5.123 | 5.367 | 5.315 | 5.105 | 5.328 | 5.495 | 5.616 | 5.646 | 5.533 | 5.331 | 4.202 |
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. - Outlandish outliers: There are "outliers" in this data.
In concept, "outlier" just means "way different than the rest of your dataset." When calculating a correlation like this, they are particularly impactful because a single outlier can substantially increase your correlation.
For the purposes of this project, I counted a point as an outlier if it the residual was two standard deviations from the mean.
(This bullet point only shows up in the details page on charts that do, in fact, have outliers.)
They stand out on the scatterplot above: notice the dots that are far away from any other dots. I intentionally mishandeled outliers, which makes the correlation look extra strong.
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([17,16,22,28,33,36,55,74,80,84,82,86,85,89,91,93,93,92,95,93,94,92,])
array_2 = np.array([1.656,1.888,1.739,1.939,2.334,2.879,3.775,4.597,4.763,4.884,5.069,5.123,5.367,5.315,5.105,5.328,5.495,5.616,5.646,5.533,5.331,4.202,])
array_1_name = "GMO use in corn grown in Illinois"
array_2_name = "Biomass power generated in Austria"
# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)
# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)
Reuseable content
You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.
For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.
Download images for these variables:
- 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 corn grown in Illinois
- Line chart for only Biomass power generated in Austria
- AI-generated correlation image
- The spurious research paper: MaIZE and EnergIZE: The Cob-nection Between GMO Corn in Illinois and Biomass Power in Austria
Your rating skills are legendary!
Correlation ID: 3244 · Black Variable ID: 753 · Red Variable ID: 23481