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Spurious correlation #3,904 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is GMO use in cotton in Missouri and the second variable is Lockheed Martin's stock price (LMT).  The chart goes from 2005 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As GMO cotton production in Missouri surged, it inadvertently led to the creation of super-soft, ultra-durable cotton, catching the attention of Lockheed Martin. The company saw a potential opportunity to use this advanced cotton in their next generation of military uniforms and parachutes. This speculation created a buzz in the stock market, causing investors to flock to Lockheed Martin, thus driving up its stock price. Who knew that the secret to successful stock trading could be woven into something as seemingly unrelated as GMO cotton fields in the Show Me State!

Model: dalle-3
Prompt: Create an image of a meme where a giant cotton field stretches out as far as the eye can see in Missouri. The rows of flourishing cotton plants sway in the breeze, demonstrating the wide usage of GMOs. In the midst of the fields, a futuristic Lockheed Martin facility stands proudly, with their logo prominently displayed. Superimposed on the scene is a stock market chart showing Lockheed Martin's stock price with a sharp upward trajectory, symbolizing the surge in demand for their aerospace technology due to the ultra-secret astronaut diapers made from the super strong cotton fibers. 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 cotton in Missouri and Lockheed Martin's stock price (LMT). Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: An image that looks like it is a scene from A Disney Movie An image that looks like it is a scene from A Disney Movie Cyber folk Glitch art a meme
ChatGPT: A meme

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 cotton in Missouri and Lockheed Martin's stock price (LMT), in the following situation: Because the increase in GMO use in cotton in Missouri led to the creation of super strong cotton fibers, which were then used by Lockheed Martin to create ultra-secret, super-absorbent, top-secret astronaut diapers, causing a surge in demand for their aerospace technology and boosting their stock price.. Keep the description simple.
ChatGPT: In a vast expanse of cotton fields in Missouri, rows of tall, flourishing cotton plants sway in the breeze, showcasing the widespread use of GMOs. Amidst the fields, a high-tech facility belonging to Lockheed Martin stands proudly, with their logo prominently displayed. A stock market chart is overlaid on the scene, with Lockheed Martin's stock price graph showing a sharp upward trajectory, symbolizing the surge in demand for their aerospace technology due to the ultra-secret astronaut diapers made from the super strong cotton fibers.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A meme ] and depicting this scene: In a vast expanse of cotton fields in Missouri, rows of tall, flourishing cotton plants sway in the breeze, showcasing the widespread use of GMOs. Amidst the fields, a high-tech facility belonging to Lockheed Martin stands proudly, with their logo prominently displayed. A stock market chart is overlaid on the scene, with Lockheed Martin's stock price graph showing a sharp upward trajectory, symbolizing the surge in demand for their aerospace technology due to the ultra-secret astronaut diapers made from the super strong cotton fibers. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a meme where a giant cotton field stretches out as far as the eye can see in Missouri. The rows of flourishing cotton plants sway in the breeze, demonstrating the wide usage of GMOs. In the midst of the fields, a futuristic Lockheed Martin facility stands proudly, with their logo prominently displayed. Superimposed on the scene is a stock market chart showing Lockheed Martin's stock price with a sharp upward trajectory, symbolizing the surge in demand for their aerospace technology due to the ultra-secret astronaut diapers made from the super strong cotton fibers.

*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.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in GMO use in cotton in Missouri caused Lockheed Martin's stock price (LMT) to increase. Make it feel plausible.

AI academic paper

(Because p < 0.01)
GMO Gag: Gauging the Gossypium and Lockheed Link

The Journal of Genetically Engineered Agriculture and Technology

Jan 2024

Reminder: This paper is AI-generated. Not real!
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a 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 cotton in Missouri and Lockheed Martin's stock price (LMT). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title an alliteration.

Your research team used data from USDA and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9118069 and p < 0.01 for 2005 to 2022.

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]]
GMO Gag: Gauging the Gossypium and Lockheed Link

[[ABSTRACT]]
This paper delves into the unexpected connection between the usage of genetically modified organisms (GMOs) in cotton cultivation in Missouri and the stock price of aerospace giant Lockheed Martin (LMT). Seemingly disparate and unrelated, our research team sought to unravel the cottony conundrum and see if there is indeed a significant link to Lockheed Martin's stock performance. Utilizing data from the USDA and LSEG Analytics (Refinitiv), our analysis covered the years 2005 to 2022. Surprisingly, the results revealed a striking correlation coefficient of 0.9118069 and a significance level of p < 0.01, suggesting a rather "gossypolized" link between the two seemingly unrelated entities. This finding prompts a further exploration into the whimsical world of cotton and aerospace stock market relationships, adding a new layer to the complex fabric of market interconnections.


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 cotton in Missouri and Lockheed Martin's stock price (LMT). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
GMO Gag: Gauging the Gossypium and Lockheed Link

[[ABSTRACT]]
This paper delves into the unexpected connection between the usage of genetically modified organisms (GMOs) in cotton cultivation in Missouri and the stock price of aerospace giant Lockheed Martin (LMT). Seemingly disparate and unrelated, our research team sought to unravel the cottony conundrum and see if there is indeed a significant link to Lockheed Martin's stock performance. Utilizing data from the USDA and LSEG Analytics (Refinitiv), our analysis covered the years 2005 to 2022. Surprisingly, the results revealed a striking correlation coefficient of 0.9118069 and a significance level of p < 0.01, suggesting a rather "gossypolized" link between the two seemingly unrelated entities. This finding prompts a further exploration into the whimsical world of cotton and aerospace stock market relationships, adding a new layer to the complex fabric of market interconnections.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
INTRODUCTION

The world of scientific research often leads us down unexpected and uncharted paths, much like a wandering electron in a quantum experiment. In this spirit of curiosity and adventure, we embarked on a peculiar journey to uncover the peculiar relationship between genetically modified organisms (GMOs) in cotton production and the stock price of Lockheed Martin (LMT), a nexus that seemed as unlikely as antimatter and cotton candy sharing a bond. The pursuit of this waggish endeavor was driven by the paradoxical proposition that the growth and cultivation of cotton, often perceived as a benign and fluffy agricultural pursuit, could verge into the realm of impacting aerospace and defense stock performance.

The seemingly disparate realms of biotechnology and stock market analytics collided in a delightful collision of disciplines, akin to the fusion of atoms in a nuclear reaction, and beckoned us to unravel a conundrum that could rival the most enigmatic of statistical paradoxes. The very mention of cotton conjures images of cozy fabrics and fields of white, but could there be an undercurrent of stock market reverberations concealed within the fibers of this seemingly humble crop? As we sifted through the copious amounts of data, we found ourselves entangled in a web of information that was as intricate as the structure of a DNA double helix, but with an element of surprise akin to discovering a cheese puff in a vegetable platter.

Our exploration into this intriguing correlation embarked on a path laden with potential pitfalls and statistical potholes, much like navigating through a minefield of hypotheses and assumptions. The delicate interplay of genetic modification in cotton, the vicissitudes of commodity markets, and the intricacies of stock price dynamics unfolded before us in a manner akin to a molecular ballet, swaying to the rhythms of market forces and biological imperatives. Our quantitative quest involved traversing through a landscape of numbers and metrics, akin to Lewis and Clark charting new territories, with the intrigue of uncovering a hidden treasure awaiting at the culmination of our arduous journey.

This study aims to shine a light on the unexpected dance between cotton cultivation and the stock market, an esoteric pas de deux that might provoke as much curiosity as a cat observing a puzzling quantum experiment. Through our meticulous analysis, we hope to unveil a remarkable story that could potentially transcend the boundaries of traditional economic and agricultural narratives, much like a zany science fiction tale that defies rational explanations. Our findings are bound to prompt both a chuckle and serious contemplation, for they cast a whimsical spotlight on the interconnectedness of seemingly incongruous components in the grand tapestry of the global economy and biosphere. With a dash of humor and a sprinkle of statistical wizardry, we invite the reader to join us in this riveting expedition, where cotton, GMOs, and stock prices converge in an unforeseen union that might just leave you saying, "Well, isn't that just a-ginetic marvel!"


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 cotton in Missouri and Lockheed Martin's stock price (LMT). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
GMO Gag: Gauging the Gossypium and Lockheed Link

[[ABSTRACT]]
This paper delves into the unexpected connection between the usage of genetically modified organisms (GMOs) in cotton cultivation in Missouri and the stock price of aerospace giant Lockheed Martin (LMT). Seemingly disparate and unrelated, our research team sought to unravel the cottony conundrum and see if there is indeed a significant link to Lockheed Martin's stock performance. Utilizing data from the USDA and LSEG Analytics (Refinitiv), our analysis covered the years 2005 to 2022. Surprisingly, the results revealed a striking correlation coefficient of 0.9118069 and a significance level of p < 0.01, suggesting a rather "gossypolized" link between the two seemingly unrelated entities. This finding prompts a further exploration into the whimsical world of cotton and aerospace stock market relationships, adding a new layer to the complex fabric of market interconnections.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The world of scientific research often leads us down unexpected and uncharted paths, much like a wandering electron in a quantum experiment. In this spirit of curiosity and adventure, we embarked on a peculiar journey to uncover the peculiar relationship between genetically modified organisms (GMOs) in cotton production and the stock price of Lockheed Martin (LMT), a nexus that seemed as unlikely as antimatter and cotton candy sharing a bond. The pursuit of this waggish endeavor was driven by the paradoxical proposition that the growth and cultivation of cotton, often perceived as a benign and fluffy agricultural pursuit, could verge into the realm of impacting aerospace and defense stock performance.
The seemingly disparate realms of biotechnology and stock market analytics collided in a delightful collision of disciplines, akin to the fusion of atoms in a nuclear reaction, and beckoned us to unravel a conundrum that could rival the most enigmatic of statistical paradoxes. The very mention of cotton conjures images of cozy fabrics and fields of white, but could there be an undercurrent of stock market reverberations concealed within the fibers of this seemingly humble crop? As we sifted through the copious amounts of data, we found ourselves entangled in a web of information that was as intricate as the structure of a DNA double helix, but with an element of surprise akin to discovering a cheese puff in a vegetable platter.
Our exploration into this intriguing correlation embarked on a path laden with potential pitfalls and statistical potholes, much like navigating through a minefield of hypotheses and assumptions. The delicate interplay of genetic modification in cotton, the vicissitudes of commodity markets, and the intricacies of stock price dynamics unfolded before us in a manner akin to a molecular ballet, swaying to the rhythms of market forces and biological imperatives. Our quantitative quest involved traversing through a landscape of numbers and metrics, akin to Lewis and Clark charting new territories, with the intrigue of uncovering a hidden treasure awaiting at the culmination of our arduous journey.
This study aims to shine a light on the unexpected dance between cotton cultivation and the stock market, an esoteric pas de deux that might provoke as much curiosity as a cat observing a puzzling quantum experiment. Through our meticulous analysis, we hope to unveil a remarkable story that could potentially transcend the boundaries of traditional economic and agricultural narratives, much like a zany science fiction tale that defies rational explanations. Our findings are bound to prompt both a chuckle and serious contemplation, for they cast a whimsical spotlight on the interconnectedness of seemingly incongruous components in the grand tapestry of the global economy and biosphere. With a dash of humor and a sprinkle of statistical wizardry, we invite the reader to join us in this riveting expedition, where cotton, GMOs, and stock prices converge in an unforeseen union that might just leave you saying, "Well, isn't that just a-ginetic marvel!"

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The exploration of the interconnectedness between the utilization of genetically modified organisms (GMOs) in cotton cultivation and the stock price of Lockheed Martin (LMT) ventures into uncharted and intriguing territory, akin to the discovery of a secret door in a labyrinth. Our investigation into this whimsical phenomenon led us to delve deep into the annals of research, where we encountered a blend of serious scholarly works and unexpected sources that added an element of quirkiness to our pursuit.

In "The Influence of Genetically Modified Crops on Modern Agriculture," Smith et al. examine the impact of GMOs on agricultural practices, shedding light on the potential ramifications for various crops, including cotton. Their rigorous analysis provides a solid foundation for understanding the broader implications of GMO adoption in the agricultural landscape, but it fails to address the curious connection to aerospace and defense industry stocks - a peculiar gap in the literature that propels our study forward.

Doe's comprehensive study, "Economic Impacts of Biotechnology in Agriculture," delves into the economic implications of biotechnological advancements in the agricultural sector, encompassing the adoption of GMOs in cotton production. While the study offers valuable insights into the economic landscape of biotechnology, the analysis overlooks the offbeat correlation we aim to unravel in our exploration of the cotton-Lockheed nexus.

Jones' seminal work, "The Global Cotton Market: Challenges and Opportunities," provides a panoramic view of the cotton market, from production to trade dynamics, offering a nuanced understanding of the cotton industry's multifaceted nature. Yet, much to our chagrin, the enigmatic link to aerospace stock performance remains elusive within the pages of this authoritative tome.

Transitioning from the scholarly domain to broader literary influences, Michael Pollan's "The Botany of Desire" and Pietra Rivoli's "The Travels of a T-Shirt in the Global Economy" present captivating narratives that intricately weave together the stories of cotton cultivation and global trade. While these works captivate the reader with their storytelling prowess, they, too, eclipse the arcane connection to aerospace stocks with their focus on more conventional aspects of the cotton trade.

Enter the realm of fiction and imagination, where the threads of cotton and aerospace twist into unexpected configurations. Michael Crichton's "Airframe" and Tom Clancy's "Flight of the Intruder" transport readers into the riveting world of aerospace intrigue, with narratives that soar through airborne adventures but regrettably overlook the peculiar gravitational pull between cotton and Lockheed Martin's stock price.

In an unconventional turn, our inquiry led us to glean insights from a rather unconventional source – the backs of shampoo bottles. While ostensibly unrelated to our topic, a curious anecdote about the invention of the cotton swab prompted a serendipitous revelation about the unexpected intersections of cotton in everyday life, underscoring the interwoven nature of seemingly disparate elements – a testament to the whimsical pathways of research exploration.

As we reflect on our odyssey through scholarly tomes, enthralling narratives, and even the unlikeliest of sources, the confluence of cotton and Lockheed Martin's stock price emerges as a captivating enigma that defies conventional categorization. Our choreographed foray through the labyrinth of literature has thus set the stage for our empirical exploration, inviting further investigation into this zany but compelling nexus.


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 cotton in Missouri and Lockheed Martin's stock price (LMT). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from USDA and LSEG Analytics (Refinitiv) . You used data from 2005 to 2022

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]]
GMO Gag: Gauging the Gossypium and Lockheed Link

[[ABSTRACT]]
This paper delves into the unexpected connection between the usage of genetically modified organisms (GMOs) in cotton cultivation in Missouri and the stock price of aerospace giant Lockheed Martin (LMT). Seemingly disparate and unrelated, our research team sought to unravel the cottony conundrum and see if there is indeed a significant link to Lockheed Martin's stock performance. Utilizing data from the USDA and LSEG Analytics (Refinitiv), our analysis covered the years 2005 to 2022. Surprisingly, the results revealed a striking correlation coefficient of 0.9118069 and a significance level of p < 0.01, suggesting a rather "gossypolized" link between the two seemingly unrelated entities. This finding prompts a further exploration into the whimsical world of cotton and aerospace stock market relationships, adding a new layer to the complex fabric of market interconnections.

[[INTRODUCTION]]
INTRODUCTION
The world of scientific research often leads us down unexpected and uncharted paths, much like a wandering electron in a quantum experiment. In this spirit of curiosity and adventure, we embarked on a peculiar journey to uncover the peculiar relationship between genetically modified organisms (GMOs) in cotton production and the stock price of Lockheed Martin (LMT), a nexus that seemed as unlikely as antimatter and cotton candy sharing a bond. The pursuit of this waggish endeavor was driven by the paradoxical proposition that the growth and cultivation of cotton, often perceived as a benign and fluffy agricultural pursuit, could verge into the realm of impacting aerospace and defense stock performance.
The seemingly disparate realms of biotechnology and stock market analytics collided in a delightful collision of disciplines, akin to the fusion of atoms in a nuclear reaction, and beckoned us to unravel a conundrum that could rival the most enigmatic of statistical paradoxes. The very mention of cotton conjures images of cozy fabrics and fields of white, but could there be an undercurrent of stock market reverberations concealed within the fibers of this seemingly humble crop? As we sifted through the copious amounts of data, we found ourselves entangled in a web of information that was as intricate as the structure of a DNA double helix, but with an element of surprise akin to discovering a cheese puff in a vegetable platter.
Our exploration into this intriguing correlation embarked on a path laden with potential pitfalls and statistical potholes, much like navigating through a minefield of hypotheses and assumptions. The delicate interplay of genetic modification in cotton, the vicissitudes of commodity markets, and the intricacies of stock price dynamics unfolded before us in a manner akin to a molecular ballet, swaying to the rhythms of market forces and biological imperatives. Our quantitative quest involved traversing through a landscape of numbers and metrics, akin to Lewis and Clark charting new territories, with the intrigue of uncovering a hidden treasure awaiting at the culmination of our arduous journey.
This study aims to shine a light on the unexpected dance between cotton cultivation and the stock market, an esoteric pas de deux that might provoke as much curiosity as a cat observing a puzzling quantum experiment. Through our meticulous analysis, we hope to unveil a remarkable story that could potentially transcend the boundaries of traditional economic and agricultural narratives, much like a zany science fiction tale that defies rational explanations. Our findings are bound to prompt both a chuckle and serious contemplation, for they cast a whimsical spotlight on the interconnectedness of seemingly incongruous components in the grand tapestry of the global economy and biosphere. With a dash of humor and a sprinkle of statistical wizardry, we invite the reader to join us in this riveting expedition, where cotton, GMOs, and stock prices converge in an unforeseen union that might just leave you saying, "Well, isn't that just a-ginetic marvel!"

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[METHODOLOGY]

This study employed a whimsical blend of statistical techniques and scientific sleuthing to unravel the enigmatic connection between the use of genetically modified organisms (GMOs) in cotton and the fluctuation of Lockheed Martin's (LMT) stock price. The data utilized for this endeavor were primarily culled from the illustrious databanks of the USDA and LSEG Analytics (Refinitiv), renowned for serving the delectable dish of economic and agricultural metrics to researchers on a silver platter. The time period under investigation spanned from 2005 to 2022, allowing us to scrutinize a substantial canvas of economic and agricultural narratives.

To measure the relationship between GMO cotton use in Missouri and Lockheed Martin's stock price, we first performed a comprehensive data cleansing, where we skillfully plucked out any outliers and wily artifacts that sought to disrupt our statistical ballet. Once the data were purged of any incongruities, we delighted in the art of correlation analysis, employing the Pearson correlation coefficient to ascertain the degree of association between our agricultural protagonist and the celestial giant of the stock market.

What's a research methodology without a splash of regression? We leveraged the enchanting powers of regression analysis, including both simple and multiple regressions, to further dissect the intricate dance between GMO cotton and Lockheed Martin's stock price, unveiling the dynamics of their hidden romance with the utmost scientific sophistication.

In addition, to add a touch of quantitative finesse to our already delightful concoction, we also baked a scrumptious significance test into our analytical pie. Adopting the robust methods of hypothesis testing, we endeavored to showcase the statistical relevance of our findings, allowing us to confidently assert the credibility of the "gossypolized" link that emerged from our data spelunking.

Lastly, to provide a nuanced perspective on our findings, we tastefully juxtaposed our statistical revelations with the broader market trends and the scuttlebutt swirling within the agricultural community, drawing upon an unending wellspring of news articles, industry reports, and market analyses, much like a seasoned chef embellishing a culinary masterpiece with just the right garnishes.

This blend of statistical savoir-faire, quantitative quirkiness, and agricultural acumen formed the cornerstone of our methodological feast, allowing us to savor the fusion of science and statistics with a fervor that might rival the excitement of uncovering a golden egg in a data-driven Easter egg hunt.


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 cotton in Missouri and Lockheed Martin's stock price (LMT). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from USDA and LSEG Analytics (Refinitiv) .

For the time period 2005 to 2022, you found a correlation 0.9118069, r-squared of 0.8313918, 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]]
GMO Gag: Gauging the Gossypium and Lockheed Link

[[ABSTRACT]]
This paper delves into the unexpected connection between the usage of genetically modified organisms (GMOs) in cotton cultivation in Missouri and the stock price of aerospace giant Lockheed Martin (LMT). Seemingly disparate and unrelated, our research team sought to unravel the cottony conundrum and see if there is indeed a significant link to Lockheed Martin's stock performance. Utilizing data from the USDA and LSEG Analytics (Refinitiv), our analysis covered the years 2005 to 2022. Surprisingly, the results revealed a striking correlation coefficient of 0.9118069 and a significance level of p < 0.01, suggesting a rather "gossypolized" link between the two seemingly unrelated entities. This finding prompts a further exploration into the whimsical world of cotton and aerospace stock market relationships, adding a new layer to the complex fabric of market interconnections.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
The world of scientific research often leads us down unexpected and uncharted paths, much like a wandering electron in a quantum experiment. In this spirit of curiosity and adventure, we embarked on a peculiar journey to uncover the peculiar relationship between genetically modified organisms (GMOs) in cotton production and the stock price of Lockheed Martin (LMT), a nexus that seemed as unlikely as antimatter and cotton candy sharing a bond. The pursuit of this waggish endeavor was driven by the paradoxical proposition that the growth and cultivation of cotton, often perceived as a benign and fluffy agricultural pursuit, could verge into the realm of impacting aerospace and defense stock performance.
The seemingly disparate realms of biotechnology and stock market analytics collided in a delightful collision of disciplines, akin to the fusion of atoms in a nuclear reaction, and beckoned us to unravel a conundrum that could rival the most enigmatic of statistical paradoxes. The very mention of cotton conjures images of cozy fabrics and fields of white, but could there be an undercurrent of stock market reverberations concealed within the fibers of this seemingly humble crop? As we sifted through the copious amounts of data, we found ourselves entangled in a web of information that was as intricate as the structure of a DNA double helix, but with an element of surprise akin to discovering a cheese puff in a vegetable platter.
Our exploration into this intriguing correlation embarked on a path laden with potential pitfalls and statistical potholes, much like navigating through a minefield of hypotheses and assumptions. The delicate interplay of genetic modification in cotton, the vicissitudes of commodity markets, and the intricacies of stock price dynamics unfolded before us in a manner akin to a molecular ballet, swaying to the rhythms of market forces and biological imperatives. Our quantitative quest involved traversing through a landscape of numbers and metrics, akin to Lewis and Clark charting new territories, with the intrigue of uncovering a hidden treasure awaiting at the culmination of our arduous journey.
This study aims to shine a light on the unexpected dance between cotton cultivation and the stock market, an esoteric pas de deux that might provoke as much curiosity as a cat observing a puzzling quantum experiment. Through our meticulous analysis, we hope to unveil a remarkable story that could potentially transcend the boundaries of traditional economic and agricultural narratives, much like a zany science fiction tale that defies rational explanations. Our findings are bound to prompt both a chuckle and serious contemplation, for they cast a whimsical spotlight on the interconnectedness of seemingly incongruous components in the grand tapestry of the global economy and biosphere. With a dash of humor and a sprinkle of statistical wizardry, we invite the reader to join us in this riveting expedition, where cotton, GMOs, and stock prices converge in an unforeseen union that might just leave you saying, "Well, isn't that just a-ginetic marvel!"

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Our analysis of the connection between genetically modified organism (GMO) use in cotton cultivation in Missouri and the stock price of Lockheed Martin (LMT) produced results as intriguing and unexpected as stumbling upon a rare unicorn in a cotton field. From 2005 to 2022, we found a correlation coefficient of 0.9118069, indicating a strong positive relationship between these seemingly unrelated entities. This correlation was further validated by an r-squared value of 0.8313918, implying that over 83% of the variation in LMT stock price can be explained by the changes in GMO use in cotton. The significance level of p < 0.01 provided robust support for the existence of this unlikely "GMO-LMT affair," akin to finding a grain of wheat in a haystack.

Furthermore, the statistically significant correlation between GMO use in cotton and Lockheed Martin's stock price is visually evident in the scatterplot shown in Fig. 1 (not included here), which displays the unmistakable trend resembling a DNA helix gyrating to the rhythm of market forces.

The strength of this correlation between GMO use in cotton and Lockheed Martin's stock price offers a rather "punny" reflection on the interconnected nature of biological and market phenomena, not unlike the unexpected fusion of peanut butter and bananas in a sandwich. This unexpected coupling sparks a curiosity as tantalizing as a freshly baked pie cooling on a windowsill and opens the door to a whimsical world where cotton and aerospace stock prices share a cheeky wink across the market landscape.

Our findings illuminate the infusion of levity in the otherwise solemn realms of market analysis and agricultural production, reminding us that humor, like statistical analysis, can reveal surprising connections and bring forth new perspectives. These results invite further investigation into the fabric of interconnecting market and biological forces, adding a quirky twist to the tapestry of scientific inquiry and market analysis, much like a hidden Easter egg waiting to be discovered in a scientific dataset.


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 cotton in Missouri and Lockheed Martin's stock price (LMT). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
GMO Gag: Gauging the Gossypium and Lockheed Link

[[ABSTRACT]]
This paper delves into the unexpected connection between the usage of genetically modified organisms (GMOs) in cotton cultivation in Missouri and the stock price of aerospace giant Lockheed Martin (LMT). Seemingly disparate and unrelated, our research team sought to unravel the cottony conundrum and see if there is indeed a significant link to Lockheed Martin's stock performance. Utilizing data from the USDA and LSEG Analytics (Refinitiv), our analysis covered the years 2005 to 2022. Surprisingly, the results revealed a striking correlation coefficient of 0.9118069 and a significance level of p < 0.01, suggesting a rather "gossypolized" link between the two seemingly unrelated entities. This finding prompts a further exploration into the whimsical world of cotton and aerospace stock market relationships, adding a new layer to the complex fabric of market interconnections.

[[LITERATURE REVIEW]]
The exploration of the interconnectedness between the utilization of genetically modified organisms (GMOs) in cotton cultivation and the stock price of Lockheed Martin (LMT) ventures into uncharted and intriguing territory, akin to the discovery of a secret door in a labyrinth. Our investigation into this whimsical phenomenon led us to delve deep into the annals of research, where we encountered a blend of serious scholarly works and unexpected sources that added an element of quirkiness to our pursuit.
In "The Influence of Genetically Modified Crops on Modern Agriculture," Smith et al. examine the impact of GMOs on agricultural practices, shedding light on the potential ramifications for various crops, including cotton. Their rigorous analysis provides a solid foundation for understanding the broader implications of GMO adoption in the agricultural landscape, but it fails to address the curious connection to aerospace and defense industry stocks - a peculiar gap in the literature that propels our study forward.
Doe's comprehensive study, "Economic Impacts of Biotechnology in Agriculture," delves into the economic implications of biotechnological advancements in the agricultural sector, encompassing the adoption of GMOs in cotton production. While the study offers valuable insights into the economic landscape of biotechnology, the analysis overlooks the offbeat correlation we aim to unravel in our exploration of the cotton-Lockheed nexus.
Jones' seminal work, "The Global Cotton Market: Challenges and Opportunities," provides a panoramic view of the cotton market, from production to trade dynamics, offering a nuanced understanding of the cotton industry's multifaceted nature. Yet, much to our chagrin, the enigmatic link to aerospace stock performance remains elusive within the pages of this authoritative tome.
Transitioning from the scholarly domain to broader literary influences, Michael Pollan's "The Botany of Desire" and Pietra Rivoli's "The Travels of a T-Shirt in the Global Economy" present captivating narratives that intricately weave together the stories of cotton cultivation and global trade. While these works captivate the reader with their storytelling prowess, they, too, eclipse the arcane connection to aerospace stocks with their focus on more conventional aspects of the cotton trade.
Enter the realm of fiction and imagination, where the threads of cotton and aerospace twist into unexpected configurations. Michael Crichton's "Airframe" and Tom Clancy's "Flight of the Intruder" transport readers into the riveting world of aerospace intrigue, with narratives that soar through airborne adventures but regrettably overlook the peculiar gravitational pull between cotton and Lockheed Martin's stock price.
In an unconventional turn, our inquiry led us to glean insights from a rather unconventional source – the backs of shampoo bottles. While ostensibly unrelated to our topic, a curious anecdote about the invention of the cotton swab prompted a serendipitous revelation about the unexpected intersections of cotton in everyday life, underscoring the interwoven nature of seemingly disparate elements – a testament to the whimsical pathways of research exploration.
As we reflect on our odyssey through scholarly tomes, enthralling narratives, and even the unlikeliest of sources, the confluence of cotton and Lockheed Martin's stock price emerges as a captivating enigma that defies conventional categorization. Our choreographed foray through the labyrinth of literature has thus set the stage for our empirical exploration, inviting further investigation into this zany but compelling nexus.

[[RESULTS]]
Our analysis of the connection between genetically modified organism (GMO) use in cotton cultivation in Missouri and the stock price of Lockheed Martin (LMT) produced results as intriguing and unexpected as stumbling upon a rare unicorn in a cotton field. From 2005 to 2022, we found a correlation coefficient of 0.9118069, indicating a strong positive relationship between these seemingly unrelated entities. This correlation was further validated by an r-squared value of 0.8313918, implying that over 83% of the variation in LMT stock price can be explained by the changes in GMO use in cotton. The significance level of p < 0.01 provided robust support for the existence of this unlikely "GMO-LMT affair," akin to finding a grain of wheat in a haystack.
Furthermore, the statistically significant correlation between GMO use in cotton and Lockheed Martin's stock price is visually evident in the scatterplot shown in Fig. 1 (not included here), which displays the unmistakable trend resembling a DNA helix gyrating to the rhythm of market forces.
The strength of this correlation between GMO use in cotton and Lockheed Martin's stock price offers a rather "punny" reflection on the interconnected nature of biological and market phenomena, not unlike the unexpected fusion of peanut butter and bananas in a sandwich. This unexpected coupling sparks a curiosity as tantalizing as a freshly baked pie cooling on a windowsill and opens the door to a whimsical world where cotton and aerospace stock prices share a cheeky wink across the market landscape.
Our findings illuminate the infusion of levity in the otherwise solemn realms of market analysis and agricultural production, reminding us that humor, like statistical analysis, can reveal surprising connections and bring forth new perspectives. These results invite further investigation into the fabric of interconnecting market and biological forces, adding a quirky twist to the tapestry of scientific inquiry and market analysis, much like a hidden Easter egg waiting to be discovered in a scientific dataset.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The unexpected correlation between the utilization of genetically modified organisms (GMOs) in cotton cultivation in Missouri and the stock price of Lockheed Martin (LMT) has unearthed a blend of surprise and amusement, not unlike stumbling upon a hidden treasure in a physics textbook and finding a joke hidden in the equations. Our results affirm and add a humorous twist to prior research, akin to finding a secret door in a labyrinth and discovering it leads to a whimsical wonderland.

The whimsy of our findings is akin to the bewildering blend of science and serendipity, much like discovering a DNA strand-shaped cloud in the sky. Our analysis, much like a scientific "magic trick," reveals a strong positive relationship between GMO use in cotton and Lockheed Martin's stock price. This discovery adds a whimsical layer to the knotty fabric of the previously overlooked connection, not dissimilar to finding a pun in a Shakespearean sonnet.

Our results are a testament to the humorous unpredictability of science and market analyses, akin to discovering a hidden punchline in a series of statistical tests. The strength and significance of the correlation between GMO use in cotton and Lockheed Martin's stock price invite a curious yet comical exploration of the interconnected nature of biological and market forces, much like uncovering a fossilized dinosaur footprint in a modern office building.

This zany "GMO-LMT affair" provides a serendipitous revelation about the surprising intersections of cotton and aerospace stock performance, much like finding an astronomer at a star-studded film premiere. The unexpected fusion of these seemingly unrelated entities has opened the door to a landscape where statistical analysis and market inquiry share a quirky handshake, not unlike a scientist moonlighting as a stand-up comedian.

The unexpected coupling of cotton and aerospace stock prices exemplifies the unanticipated blend of statistical analysis and amusement, highlighting the unconventional yet captivating nature of scientific inquiry, much like discovering a clownfish in a coffee mug. Our findings enhance the fabric of empirical exploration with a wry smile, inviting further investigation into the whimsical world of market interconnections, adding a delightful twist to the scientific tapestry, not unlike a subtle smirk hidden in a data plot.


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 cotton in Missouri and Lockheed Martin's stock price (LMT). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
GMO Gag: Gauging the Gossypium and Lockheed Link

[[ABSTRACT]]
This paper delves into the unexpected connection between the usage of genetically modified organisms (GMOs) in cotton cultivation in Missouri and the stock price of aerospace giant Lockheed Martin (LMT). Seemingly disparate and unrelated, our research team sought to unravel the cottony conundrum and see if there is indeed a significant link to Lockheed Martin's stock performance. Utilizing data from the USDA and LSEG Analytics (Refinitiv), our analysis covered the years 2005 to 2022. Surprisingly, the results revealed a striking correlation coefficient of 0.9118069 and a significance level of p < 0.01, suggesting a rather "gossypolized" link between the two seemingly unrelated entities. This finding prompts a further exploration into the whimsical world of cotton and aerospace stock market relationships, adding a new layer to the complex fabric of market interconnections.

[[INTRDUCTION]]
INTRODUCTION
The world of scientific research often leads us down unexpected and uncharted paths, much like a wandering electron in a quantum experiment. In this spirit of curiosity and adventure, we embarked on a peculiar journey to uncover the peculiar relationship between genetically modified organisms (GMOs) in cotton production and the stock price of Lockheed Martin (LMT), a nexus that seemed as unlikely as antimatter and cotton candy sharing a bond. The pursuit of this waggish endeavor was driven by the paradoxical proposition that the growth and cultivation of cotton, often perceived as a benign and fluffy agricultural pursuit, could verge into the realm of impacting aerospace and defense stock performance.
The seemingly disparate realms of biotechnology and stock market analytics collided in a delightful collision of disciplines, akin to the fusion of atoms in a nuclear reaction, and beckoned us to unravel a conundrum that could rival the most enigmatic of statistical paradoxes. The very mention of cotton conjures images of cozy fabrics and fields of white, but could there be an undercurrent of stock market reverberations concealed within the fibers of this seemingly humble crop? As we sifted through the copious amounts of data, we found ourselves entangled in a web of information that was as intricate as the structure of a DNA double helix, but with an element of surprise akin to discovering a cheese puff in a vegetable platter.
Our exploration into this intriguing correlation embarked on a path laden with potential pitfalls and statistical potholes, much like navigating through a minefield of hypotheses and assumptions. The delicate interplay of genetic modification in cotton, the vicissitudes of commodity markets, and the intricacies of stock price dynamics unfolded before us in a manner akin to a molecular ballet, swaying to the rhythms of market forces and biological imperatives. Our quantitative quest involved traversing through a landscape of numbers and metrics, akin to Lewis and Clark charting new territories, with the intrigue of uncovering a hidden treasure awaiting at the culmination of our arduous journey.
This study aims to shine a light on the unexpected dance between cotton cultivation and the stock market, an esoteric pas de deux that might provoke as much curiosity as a cat observing a puzzling quantum experiment. Through our meticulous analysis, we hope to unveil a remarkable story that could potentially transcend the boundaries of traditional economic and agricultural narratives, much like a zany science fiction tale that defies rational explanations. Our findings are bound to prompt both a chuckle and serious contemplation, for they cast a whimsical spotlight on the interconnectedness of seemingly incongruous components in the grand tapestry of the global economy and biosphere. With a dash of humor and a sprinkle of statistical wizardry, we invite the reader to join us in this riveting expedition, where cotton, GMOs, and stock prices converge in an unforeseen union that might just leave you saying, "Well, isn't that just a-ginetic marvel!"

[[RESULTS]]
Our analysis of the connection between genetically modified organism (GMO) use in cotton cultivation in Missouri and the stock price of Lockheed Martin (LMT) produced results as intriguing and unexpected as stumbling upon a rare unicorn in a cotton field. From 2005 to 2022, we found a correlation coefficient of 0.9118069, indicating a strong positive relationship between these seemingly unrelated entities. This correlation was further validated by an r-squared value of 0.8313918, implying that over 83% of the variation in LMT stock price can be explained by the changes in GMO use in cotton. The significance level of p < 0.01 provided robust support for the existence of this unlikely "GMO-LMT affair," akin to finding a grain of wheat in a haystack.
Furthermore, the statistically significant correlation between GMO use in cotton and Lockheed Martin's stock price is visually evident in the scatterplot shown in Fig. 1 (not included here), which displays the unmistakable trend resembling a DNA helix gyrating to the rhythm of market forces.
The strength of this correlation between GMO use in cotton and Lockheed Martin's stock price offers a rather "punny" reflection on the interconnected nature of biological and market phenomena, not unlike the unexpected fusion of peanut butter and bananas in a sandwich. This unexpected coupling sparks a curiosity as tantalizing as a freshly baked pie cooling on a windowsill and opens the door to a whimsical world where cotton and aerospace stock prices share a cheeky wink across the market landscape.
Our findings illuminate the infusion of levity in the otherwise solemn realms of market analysis and agricultural production, reminding us that humor, like statistical analysis, can reveal surprising connections and bring forth new perspectives. These results invite further investigation into the fabric of interconnecting market and biological forces, adding a quirky twist to the tapestry of scientific inquiry and market analysis, much like a hidden Easter egg waiting to be discovered in a scientific dataset.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has unraveled a rather "en-ginning" link between the usage of genetically modified organisms (GMOs) in cotton cultivation in Missouri and the stock price of Lockheed Martin (LMT), proving that there may indeed be more to cotton than meets the "eyelet" lace. The unexpectedly strong correlation coefficient of 0.9118069 and the robust 83% explanation of variations in LMT stock price by changes in GMO use in cotton have shed light on a partnership as whimsical as a cotton candy vendor at a high-tech expo.

The visually evident trend in the scatterplot, resembling a gyrating DNA helix, paints a picture as intriguing as a dapper pig in a mud puddle, emphasizing the dance between biological and market forces in this "GMO-LMT affair." This correlation, akin to a molecular waltz in a market square, sparks curiosity as profound as a scholarly debate on the existential ponderings of Schrödinger's cotton ball.

Our findings emphasize the need for a more light-hearted approach to scientific inquiry, proving that humor can impart new perspectives and connections—all while maintaining the utmost statistical rigor and sensibility. Consequently, we posit that no further research is needed in this area, as our exploration has left us cotton-eyed and content with the amusing interplay we have uncovered.


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 GMO Gag: Gauging the Gossypium and Lockheed Link. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Genetically Engineered Agriculture and Technology


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 GMO Gag: Gauging the Gossypium and Lockheed Link. Respond only with the name of a fictional organization.

ChatGPT:

The Federation of Genetically Modified Organism Studies (FEGEMO)


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 GMO Gag: Gauging the Gossypium and Lockheed Link with an abstract of This paper delves into the unexpected connection between the usage of genetically modified organisms (GMOs) in cotton cultivation in Missouri and the stock price of aerospace giant Lockheed Martin (LMT). Seemingly disparate and unrelated, our research team sought to unravel the cottony conundrum and see if there is indeed a significant link to Lockheed Martin's stock performance. Utilizing data from the USDA and LSEG Analytics (Refinitiv), our analysis covered the years 2005 to 2022. Surprisingly, the results revealed a striking correlation coefficient of 0.9118069 and a significance level of p < 0.01, suggesting a rather "gossypolized" link between the two seemingly unrelated entities. This finding prompts a further exploration into the whimsical world of cotton and aerospace stock market relationships, adding a new layer to the complex fabric of market interconnections.

ChatGPT:

GMOs in cotton cultivation, genetically modified organisms in agriculture, cotton cultivation in Missouri, aerospace industry, Lockheed Martin stock price correlation, USDA cotton data, LSEG analytics, cotton and aerospace stock market correlation, gossypol, cotton market interconnections

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.



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Data details

GMO use in cotton in Missouri
Detailed data title: Percent of cotton planted in Missouri genetically modified with both Bt and HT
Source: USDA
See what else correlates with GMO use in cotton in Missouri

Lockheed Martin's stock price (LMT)
Detailed data title: Opening price of Lockheed Martin (LMT) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function

See what else correlates with Lockheed Martin's stock price (LMT)

Correlation r = 0.9118069 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r2 = 0.8313918 (Coefficient of determination)
This means 83.1% of the change in the one variable (i.e., Lockheed Martin's stock price (LMT)) is predictable based on the change in the other (i.e., GMO use in cotton in Missouri) over the 18 years from 2005 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.4E-7. 0.0000001391389746648387500000
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 0.91 in 1.4E-5% of random cases. Said differently, if you correlated 7,187,059 random variables You don't actually need 7 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 17 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 17 because we have two variables measured over a period of 18 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.

[ 0.77, 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.
200520062007200820092010201120122013201420152016201720182019202020212022
GMO use in cotton in Missouri (GMO cotton %)162523195129293338485648587378778071
Lockheed Martin's stock price (LMT) (Stock price)55.463.391.6105.7784.3475.8770.282.1293.79147.05192.1214251.2322258.36392.86354.98354.68




Why this works

  1. 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.
  2. 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.
  3. 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([16,25,23,19,51,29,29,33,38,48,56,48,58,73,78,77,80,71,])
array_2 = np.array([55.4,63.3,91.6,105.77,84.34,75.87,70.2,82.12,93.79,147.05,192.1,214,251.2,322,258.36,392.86,354.98,354.68,])
array_1_name = "GMO use in cotton in Missouri"
array_2_name = "Lockheed Martin's stock price (LMT)"

# 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 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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Correlation ID: 3904 · Black Variable ID: 796 · Red Variable ID: 1630
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