Spurious correlation #3,236 · 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 Alabama and the second variable is The number of brickmasons in Alabama. The chart goes from 2005 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is GMO use in cotton in Alabama and the second variable is The number of brickmasons in Alabama. The chart goes from 2005 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The GMO cotton was engineered to grow softer and more pliable, leading to a higher demand for intricate brick designs. With the switch to non-GMO cotton, there was a noticeable decrease in the need for the expert hands of brickmasons across the state. These masons, once kept busy by the allure of GMO-induced brick complexities, found themselves facing a wall of unemployment as the demand for their artisanal bricklaying skills crumbled like, well, non-GMO cotton. Brick by brick, the GMO cotton had unwittingly built a lucrative niche market for the brickmasons, only to leave them out of work when their genetically modified canvas disappeared. The irony wasn't lost on the now nonplussed brickmasons, who had to go back to the drawing board to find new ways to bring home the bacon without the genetically enhanced cotton connection.

^{Show image generation prompt} Model: dalle-3
Prompt: [ A photo-realistic image ] Set in a cotton field in Alabama, a brickmason is diligently repairing a cotton gin with a trowel and bricks. The cotton plants in the background are notably smaller, illustrating the decrease in GMO use. As a result, there are fewer cotton gins in need of maintenance, leading to the departure of some brickmasons from the field. The image will portray the skilled brickmason amidst the sparse cotton plants, emphasizing the impact of reduced GMO use on the landscape and the labor force. 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 Alabama and The number of brickmasons in Alabama. 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: Parallax art Cubism An image that looks like it is a scene from 'Star Wars' 3D Pixar Style A photo-realistic image
ChatGPT: A photo-realistic image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both GMO use in cotton in Alabama and The number of brickmasons in Alabama, in the following situation: Because the decrease in GMO use in cotton in Alabama led to a decrease in cotton picking, there was a reduction in the need for cotton gin maintenance and construction. As a result, fewer brickmasons were required to build and repair the gins, leading to a decrease in the number of brickmasons in Alabama.. Keep the description simple.
ChatGPT: In a cotton field in Alabama, a brickmason is seen working on a cotton gin, repairing the structure with a trowel and bricks. However, the cotton plants in the field are noticeably smaller due to the decrease in GMO use. As a result, there are fewer cotton gins in need of maintenance and construction, leading to fewer brickmasons in the scene, with some of them leaving the field.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A photo-realistic image ] and depicting this scene: In a cotton field in Alabama, a brickmason is seen working on a cotton gin, repairing the structure with a trowel and bricks. However, the cotton plants in the field are noticeably smaller due to the decrease in GMO use. As a result, there are fewer cotton gins in need of maintenance and construction, leading to fewer brickmasons in the scene, with some of them leaving the field. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A photo-realistic image ] Set in a cotton field in Alabama, a brickmason is diligently repairing a cotton gin with a trowel and bricks. The cotton plants in the background are notably smaller, illustrating the decrease in GMO use. As a result, there are fewer cotton gins in need of maintenance, leading to the departure of some brickmasons from the field. The image will portray the skilled brickmason amidst the sparse cotton plants, emphasizing the impact of reduced GMO use on the landscape and the labor force.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in GMO use in cotton in Alabama caused The number of brickmasons in Alabama to decrease.

AI academic paper

(Because p < 0.01)

Genetically-Modified Cotton: Sow Your Seeds, Reap More Masons in Alabama

The Journal of Agricultural Genetics and Regional Economics

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between GMO use in cotton in Alabama and The number of brickmasons in Alabama. 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 name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
Genetically-Modified Cotton: Sow Your Seeds, Reap More Masons in Alabama

[[ABSTRACT]]
This study examines the relationship between the use of genetically-modified organisms (GMOs) in cotton farming in Alabama and the number of brickmasons in the state. Utilizing data from the USDA and the Bureau of Labor Statistics spanning the years 2005 to 2022, our research team sought to untangle the intricate threads connecting agricultural practices and labor trends. Our findings revealed a remarkable correlation coefficient of 0.9556719, with a p-value of less than 0.01, indicating a robust statistical relationship between the two variables.

Our investigation unearths a surprising and, quite literally, foundational bond between the adoption of GMOs in cotton cultivation and the demand for bricklayers in Alabama. While the precise mechanism driving this association remains a mystery, it seems that the seeds sown in the fields have found a way to also sow the seeds of masonry careers. It appears that GMO cotton has not only revolutionized the agricultural landscape but also laid the groundwork for a flourishing brickmasonry industry in the Heart of Dixie.

In conclusion, our research sheds light on the hitherto overlooked impact of agricultural innovations on the labor market, demonstrating that what sprouts in the fields may "brick" unconventional consequences.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The advent of genetically-modified organisms (GMOs) in agriculture has sparked contentious debates, sown widespread apprehension, and cultivated a burgeoning industry. In the United States, the adoption of GMO crops, including cotton, has been both lauded for its potential to bolster yields and criticized for its potential environmental and health implications. Alabama stands as a prime example of a state deeply entrenched in cotton farming, where the ramifications of GMO adoption reverberate through the agricultural landscape and, as our study reveals, extend their tendrils into the realm of brickmasonry.
One might jest that the relationship between GMO cotton and the number of brickmasons in Alabama is as unlikely as finding a needle in a haystack, yet our empirical investigation paints a different picture. As counterintuitive as it may seem, our research unearthed a substantial and consistent association between these seemingly disparate domains. It's almost as surprising as finding a "cotton"-candy machine inside a cotton gin!
While previous studies have predominantly focused on the agricultural and economic implications of GMO adoption, the specific impact on labor market dynamics has received scant attention. Thus, our research aims to bridge this gap and offer a fresh perspective on the repercussions of biotechnological advancements in the agricultural sector. Much like grafting a genetically-modified branch onto a traditional cotton plant, we aim to graft a new understanding of the broader implications of GMO adoption onto the existing body of knowledge.
The humorous anecdote you shared about the farmer who thought he had finally grown square watermelons only to discover they were actually bricks is a whimsical reminder of the unexpected ways in which agricultural innovations can shape not only the literal landscape, but also the labor market. Our study strives to unravel this enigma, shedding light on the intricate ways in which the tendrils of GMO cotton intertwine with the brick and mortar of Alabama's construction industry. After all, as they say, "Where there's a wheel, there's a way," and where there's GMO cotton, there might just be a demand for brickmasons.
Stay tuned for the analysis of the data, as our findings promise to pack a concrete punch, just like a well-laid brick wall.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The connection between the use of genetically-modified organisms (GMOs) in cotton farming and the number of brickmasons in Alabama has intrigued researchers and industry experts alike, leading to a plethora of studies investigating this unconventional relationship. In "Cotton and Its Genetics" by Smith, the authors find the influence of GMO cotton on the surrounding environment and agricultural practices, while in "Masonry Matters" by Doe, the authors explore the trends in brickmason labor force participation in various states.

Surprisingly, "GMOs and You" by Jones contributes a novel perspective by delving into the societal and economic impacts of GMO adoption, including its potential influences on labor markets. In the face of these serious and weighty academic tomes, one would be forgiven for assuming that the field of GMO cotton and brickmason dynamics is devoid of levity.

However, delving into less formal literature, such as "Genetically Modified Organisms for Dummies" and "Bricklaying for Beginners," one finds a wealth of accessible information that highlights the widespread interest in the intersection of these seemingly unrelated fields. The inquisitive nature of the general public extends even further, as fictional works like "The Cotton Chronicles" and "The Masonry Mysteries" hint at the allure of these topics, capturing the imagination of readers who seek to uncover the mysteries of GMO cultivation and bricklaying.

Moreover, popular internet memes such as the viral "GMO Cotton vs. Brickmason Showdown" portray humorous hypothetical scenarios that playfully speculate on the interactions between GMO cotton and the demand for brickmasons. While these lighthearted references may appear tangential to rigorous academic inquiry, they reflect the pervasive cultural fascination with the unexpected correlation our research endeavors to elucidate.

As we unravel the complex entanglement of GMO cotton and brickmasonry, it becomes apparent that this investigation is not just about bricks and cotton, but about the fabric of society and the potential for growth in unforeseen quarters. Thus, our endeavor to untangle this knotty issue promises to be as exhilarating as finding a hidden message in a brickwork facade – both puzzling and rewarding.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between GMO use in cotton in Alabama and The number of brickmasons in Alabama. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from USDA and Bureau of Larbor Statistics . 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]]
Genetically-Modified Cotton: Sow Your Seeds, Reap More Masons in Alabama

[[ABSTRACT]]
This study examines the relationship between the use of genetically-modified organisms (GMOs) in cotton farming in Alabama and the number of brickmasons in the state. Utilizing data from the USDA and the Bureau of Labor Statistics spanning the years 2005 to 2022, our research team sought to untangle the intricate threads connecting agricultural practices and labor trends. Our findings revealed a remarkable correlation coefficient of 0.9556719, with a p-value of less than 0.01, indicating a robust statistical relationship between the two variables.

Our investigation unearths a surprising and, quite literally, foundational bond between the adoption of GMOs in cotton cultivation and the demand for bricklayers in Alabama. While the precise mechanism driving this association remains a mystery, it seems that the seeds sown in the fields have found a way to also sow the seeds of masonry careers. It appears that GMO cotton has not only revolutionized the agricultural landscape but also laid the groundwork for a flourishing brickmasonry industry in the Heart of Dixie.

In conclusion, our research sheds light on the hitherto overlooked impact of agricultural innovations on the labor market, demonstrating that what sprouts in the fields may "brick" unconventional consequences.

[[INTRODUCTION]]
The advent of genetically-modified organisms (GMOs) in agriculture has sparked contentious debates, sown widespread apprehension, and cultivated a burgeoning industry. In the United States, the adoption of GMO crops, including cotton, has been both lauded for its potential to bolster yields and criticized for its potential environmental and health implications. Alabama stands as a prime example of a state deeply entrenched in cotton farming, where the ramifications of GMO adoption reverberate through the agricultural landscape and, as our study reveals, extend their tendrils into the realm of brickmasonry.
One might jest that the relationship between GMO cotton and the number of brickmasons in Alabama is as unlikely as finding a needle in a haystack, yet our empirical investigation paints a different picture. As counterintuitive as it may seem, our research unearthed a substantial and consistent association between these seemingly disparate domains. It's almost as surprising as finding a "cotton"-candy machine inside a cotton gin!
While previous studies have predominantly focused on the agricultural and economic implications of GMO adoption, the specific impact on labor market dynamics has received scant attention. Thus, our research aims to bridge this gap and offer a fresh perspective on the repercussions of biotechnological advancements in the agricultural sector. Much like grafting a genetically-modified branch onto a traditional cotton plant, we aim to graft a new understanding of the broader implications of GMO adoption onto the existing body of knowledge.
The humorous anecdote you shared about the farmer who thought he had finally grown square watermelons only to discover they were actually bricks is a whimsical reminder of the unexpected ways in which agricultural innovations can shape not only the literal landscape, but also the labor market. Our study strives to unravel this enigma, shedding light on the intricate ways in which the tendrils of GMO cotton intertwine with the brick and mortar of Alabama's construction industry. After all, as they say, "Where there's a wheel, there's a way," and where there's GMO cotton, there might just be a demand for brickmasons.
Stay tuned for the analysis of the data, as our findings promise to pack a concrete punch, just like a well-laid brick wall.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The methodological framework employed in this study involved a comprehensive analysis of secondary data obtained from the United States Department of Agriculture (USDA) and the Bureau of Labor Statistics (BLS). The primary objective was to investigate the relationship between the use of genetically-modified organisms (GMOs) in cotton farming in Alabama and the number of brickmasons employed in the state. The research team gathered data spanning the years 2005 to 2022, encompassing a period that encapsulates the widespread adoption and diffusion of GMO cotton cultivation practices across Alabama.

To assess the impact of GMO cotton on the labor market for brickmasons, a series of quantitative analyses were conducted. This involved the utilization of advanced statistical techniques, including regression analysis and time-series modeling, to discern any discernible patterns or associations between the variables of interest. The statistical models were meticulously constructed to control for potential confounding factors such as overall employment trends, construction industry dynamics, and broader economic fluctuations.

In a nod to the whimsical nature of our research subject, we harnessed an unconventional tool in our methodological arsenal: a modified version of the "Brick-and-Mortar Index." This bespoke index, devised specifically for this study, amalgamated data on cotton cultivation practices, GMO adoption rates, and brickmason employment levels to quantify the nuanced interplay between the agricultural and construction sectors. Rest assured, no bricks were harmed in the creation of this index – we jest, of course, as the integrity of the brick supply chain was paramount to our research efforts.

Moreover, to capture the regional nuances of the relationship under investigation, the research team implemented a spatial analysis component. Geospatial mapping techniques were employed to visualize the spatial distribution of GMO cotton cultivation and brickmason employment across different counties in Alabama, offering a nuanced depiction of the localized impact of agricultural innovations on labor market dynamics. This approach allowed us to "lay the foundation" for a comprehensive understanding of the geographical variations in the relationship between GMO cotton and brickmasonry demands across the state.

In the spirit of exploring uncharted terrain – or in this case, unbricked terrain – our methodological approach also incorporated qualitative insights gleaned from in-depth interviews with key stakeholders in the cotton and construction industries. These interviews provided valuable anecdotal evidence and qualitative perspectives on the potential mechanisms driving the observed relationship, offering a rich tapestry of firsthand experiences and industry insights. Additionally, the team delved into historical archives to trace the evolution of cotton farming practices and bricklaying traditions in Alabama, adding a historical dimension to our methodological repertoire.

With our methodological dexterity primed and our pun game strong, the research team navigated the labyrinthine terrain of agricultural and labor market data to unearth the unique connections between GMO cotton and the demand for brickmasons. While our approach may seem as unconventional as a genetically-modified watermelon, rest assured that our empirical journey adhered to rigorous scientific standards, engineered to plumb the depths of this intriguing phenomenon.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between GMO use in cotton in Alabama and The number of brickmasons in Alabama. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from USDA and Bureau of Larbor Statistics .

For the time period 2005 to 2022, you found a correlation 0.9556719, r-squared of 0.9133088, 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]]
Genetically-Modified Cotton: Sow Your Seeds, Reap More Masons in Alabama

[[ABSTRACT]]
This study examines the relationship between the use of genetically-modified organisms (GMOs) in cotton farming in Alabama and the number of brickmasons in the state. Utilizing data from the USDA and the Bureau of Labor Statistics spanning the years 2005 to 2022, our research team sought to untangle the intricate threads connecting agricultural practices and labor trends. Our findings revealed a remarkable correlation coefficient of 0.9556719, with a p-value of less than 0.01, indicating a robust statistical relationship between the two variables.

Our investigation unearths a surprising and, quite literally, foundational bond between the adoption of GMOs in cotton cultivation and the demand for bricklayers in Alabama. While the precise mechanism driving this association remains a mystery, it seems that the seeds sown in the fields have found a way to also sow the seeds of masonry careers. It appears that GMO cotton has not only revolutionized the agricultural landscape but also laid the groundwork for a flourishing brickmasonry industry in the Heart of Dixie.

In conclusion, our research sheds light on the hitherto overlooked impact of agricultural innovations on the labor market, demonstrating that what sprouts in the fields may "brick" unconventional consequences.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The advent of genetically-modified organisms (GMOs) in agriculture has sparked contentious debates, sown widespread apprehension, and cultivated a burgeoning industry. In the United States, the adoption of GMO crops, including cotton, has been both lauded for its potential to bolster yields and criticized for its potential environmental and health implications. Alabama stands as a prime example of a state deeply entrenched in cotton farming, where the ramifications of GMO adoption reverberate through the agricultural landscape and, as our study reveals, extend their tendrils into the realm of brickmasonry.
One might jest that the relationship between GMO cotton and the number of brickmasons in Alabama is as unlikely as finding a needle in a haystack, yet our empirical investigation paints a different picture. As counterintuitive as it may seem, our research unearthed a substantial and consistent association between these seemingly disparate domains. It's almost as surprising as finding a "cotton"-candy machine inside a cotton gin!
While previous studies have predominantly focused on the agricultural and economic implications of GMO adoption, the specific impact on labor market dynamics has received scant attention. Thus, our research aims to bridge this gap and offer a fresh perspective on the repercussions of biotechnological advancements in the agricultural sector. Much like grafting a genetically-modified branch onto a traditional cotton plant, we aim to graft a new understanding of the broader implications of GMO adoption onto the existing body of knowledge.
The humorous anecdote you shared about the farmer who thought he had finally grown square watermelons only to discover they were actually bricks is a whimsical reminder of the unexpected ways in which agricultural innovations can shape not only the literal landscape, but also the labor market. Our study strives to unravel this enigma, shedding light on the intricate ways in which the tendrils of GMO cotton intertwine with the brick and mortar of Alabama's construction industry. After all, as they say, "Where there's a wheel, there's a way," and where there's GMO cotton, there might just be a demand for brickmasons.
Stay tuned for the analysis of the data, as our findings promise to pack a concrete punch, just like a well-laid brick wall.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The results of our analysis revealed a strong positive correlation between the use of genetically-modified organisms (GMOs) in cotton farming in Alabama and the number of brickmasons in the state. The correlation coefficient of 0.9556719 and the r-squared value of 0.9133088 indicate a robust relationship between these two variables. This statistical association suggests a substantial impact of GMO cotton cultivation on the demand for bricklayers in Alabama.

Figure 1 presents a scatterplot illustrating the pronounced correlation between GMO cotton usage and the number of brickmasons in Alabama. The data points form a clear upward trend, emphasizing the close connection between these phenomena.

Some might find it "punny" that the correlation we uncovered between genetically-modified cotton and the masonry workforce is as solid as, well, a brick wall. This unlikely relationship may have seemed as improbable as a farmer growing square watermelons, only to discover a "block"-buster surprise! Our findings, however, dispel any doubts about the tangible link between agricultural practices and labor market dynamics.

When we planted the seeds of our research, we certainly didn't expect to harvest evidence of such a strong association between GMO cotton and the number of brickmasons. The unexpected nature of this correlation speaks to the intricate and often surprising ways in which economic and agricultural forces interweave. It seems that the impact of GMO cotton cultivation extends beyond the fields and into the very fabric of Alabama's labor market.

The significance of our results cannot be overstated, as they underscore the need to consider the broader repercussions of agricultural innovations on labor market dynamics. Our study offers a fresh perspective on the multifaceted effects of GMO adoption, challenging traditional notions of the boundaries between agricultural and labor sectors. After all, as the saying goes, "Behind every successful mason, there's a strong correlation with GMO cotton."

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between GMO use in cotton in Alabama and The number of brickmasons in Alabama. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
Genetically-Modified Cotton: Sow Your Seeds, Reap More Masons in Alabama

[[ABSTRACT]]
This study examines the relationship between the use of genetically-modified organisms (GMOs) in cotton farming in Alabama and the number of brickmasons in the state. Utilizing data from the USDA and the Bureau of Labor Statistics spanning the years 2005 to 2022, our research team sought to untangle the intricate threads connecting agricultural practices and labor trends. Our findings revealed a remarkable correlation coefficient of 0.9556719, with a p-value of less than 0.01, indicating a robust statistical relationship between the two variables.

Our investigation unearths a surprising and, quite literally, foundational bond between the adoption of GMOs in cotton cultivation and the demand for bricklayers in Alabama. While the precise mechanism driving this association remains a mystery, it seems that the seeds sown in the fields have found a way to also sow the seeds of masonry careers. It appears that GMO cotton has not only revolutionized the agricultural landscape but also laid the groundwork for a flourishing brickmasonry industry in the Heart of Dixie.

In conclusion, our research sheds light on the hitherto overlooked impact of agricultural innovations on the labor market, demonstrating that what sprouts in the fields may "brick" unconventional consequences.

[[LITERATURE REVIEW]]
The connection between the use of genetically-modified organisms (GMOs) in cotton farming and the number of brickmasons in Alabama has intrigued researchers and industry experts alike, leading to a plethora of studies investigating this unconventional relationship. In "Cotton and Its Genetics" by Smith, the authors find the influence of GMO cotton on the surrounding environment and agricultural practices, while in "Masonry Matters" by Doe, the authors explore the trends in brickmason labor force participation in various states.
Surprisingly, "GMOs and You" by Jones contributes a novel perspective by delving into the societal and economic impacts of GMO adoption, including its potential influences on labor markets. In the face of these serious and weighty academic tomes, one would be forgiven for assuming that the field of GMO cotton and brickmason dynamics is devoid of levity.
However, delving into less formal literature, such as "Genetically Modified Organisms for Dummies" and "Bricklaying for Beginners," one finds a wealth of accessible information that highlights the widespread interest in the intersection of these seemingly unrelated fields. The inquisitive nature of the general public extends even further, as fictional works like "The Cotton Chronicles" and "The Masonry Mysteries" hint at the allure of these topics, capturing the imagination of readers who seek to uncover the mysteries of GMO cultivation and bricklaying.
Moreover, popular internet memes such as the viral "GMO Cotton vs. Brickmason Showdown" portray humorous hypothetical scenarios that playfully speculate on the interactions between GMO cotton and the demand for brickmasons. While these lighthearted references may appear tangential to rigorous academic inquiry, they reflect the pervasive cultural fascination with the unexpected correlation our research endeavors to elucidate.
As we unravel the complex entanglement of GMO cotton and brickmasonry, it becomes apparent that this investigation is not just about bricks and cotton, but about the fabric of society and the potential for growth in unforeseen quarters. Thus, our endeavor to untangle this knotty issue promises to be as exhilarating as finding a hidden message in a brickwork facade – both puzzling and rewarding.

[[RESULTS]]
The results of our analysis revealed a strong positive correlation between the use of genetically-modified organisms (GMOs) in cotton farming in Alabama and the number of brickmasons in the state. The correlation coefficient of 0.9556719 and the r-squared value of 0.9133088 indicate a robust relationship between these two variables. This statistical association suggests a substantial impact of GMO cotton cultivation on the demand for bricklayers in Alabama.
Figure 1 presents a scatterplot illustrating the pronounced correlation between GMO cotton usage and the number of brickmasons in Alabama. The data points form a clear upward trend, emphasizing the close connection between these phenomena.
Some might find it "punny" that the correlation we uncovered between genetically-modified cotton and the masonry workforce is as solid as, well, a brick wall. This unlikely relationship may have seemed as improbable as a farmer growing square watermelons, only to discover a "block"-buster surprise! Our findings, however, dispel any doubts about the tangible link between agricultural practices and labor market dynamics.
When we planted the seeds of our research, we certainly didn't expect to harvest evidence of such a strong association between GMO cotton and the number of brickmasons. The unexpected nature of this correlation speaks to the intricate and often surprising ways in which economic and agricultural forces interweave. It seems that the impact of GMO cotton cultivation extends beyond the fields and into the very fabric of Alabama's labor market.
The significance of our results cannot be overstated, as they underscore the need to consider the broader repercussions of agricultural innovations on labor market dynamics. Our study offers a fresh perspective on the multifaceted effects of GMO adoption, challenging traditional notions of the boundaries between agricultural and labor sectors. After all, as the saying goes, "Behind every successful mason, there's a strong correlation with GMO cotton."

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The substantial correlation identified in our study aligns with prior research, affirming the unexpected but compelling relationship between the use of genetically-modified organisms (GMOs) in cotton farming and the demand for brickmasons in Alabama. These findings lend empirical support to the speculative narratives and jesting conjectures that have permeated both formal and informal discussions of this unusual association. The dotted lines connecting ploughed fields to laid bricks have now been filled in with robust statistical evidence.

The fruitful union between agricultural innovation and labor market dynamics has been a topic of academic interest for many years. While it may have once seemed as unlikely as a genetically modified watermelon, the symbiotic relationship between GMO cotton and the masonry workforce has now been firmly established through rigorous empirical investigation. Our study's confirmation of this unanticipated linkage between seemingly disparate domains underscores the need for researchers and policymakers to broaden their perspectives when analyzing the impact of agricultural advancements.

The clarity and strength of the correlation unveiled in our research provide compelling evidence that genetically-modified cotton's influence extends beyond the botanical realm and exerts a palpable effect on labor market conditions. This novel insight underscores the broader ramifications of agricultural practices and emphasizes the need for a more holistic understanding of the interconnectedness of diverse economic sectors. By shining a light on the far-reaching consequences of GMO adoption, our findings offer a fresh perspective on the intricate web of relationships that underpin economic activities.

Our results, while surprising to some, fit neatly into the growing body of literature that endeavors to demystify the intricate dance of cause and effect in complex economic systems. The humor and levity that have surrounded discussions of this unique correlation have found grounding in the empirical evidence we present. Indeed, our findings echo the words of a bricklayer's favorite joke: "I never believed in love at first sight until I laid eyes on a perfectly correlated dataset."

In conclusion, the findings from this study provide empirical support for the unorthodox relationship between GMO cotton farming and the demand for brickmasons in Alabama. As researchers continue to delve into the intricacies of economic interdependencies, it is evident that the seeds sown by agricultural advancements have the potential to cultivate burgeoning labor markets. The unexpected nature of this correlation reinforces the adage that "life, like statistics, often yields unexpected but meaningful outcomes."

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between GMO use in cotton in Alabama and The number of brickmasons in Alabama. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Genetically-Modified Cotton: Sow Your Seeds, Reap More Masons in Alabama

[[ABSTRACT]]
This study examines the relationship between the use of genetically-modified organisms (GMOs) in cotton farming in Alabama and the number of brickmasons in the state. Utilizing data from the USDA and the Bureau of Labor Statistics spanning the years 2005 to 2022, our research team sought to untangle the intricate threads connecting agricultural practices and labor trends. Our findings revealed a remarkable correlation coefficient of 0.9556719, with a p-value of less than 0.01, indicating a robust statistical relationship between the two variables.

Our investigation unearths a surprising and, quite literally, foundational bond between the adoption of GMOs in cotton cultivation and the demand for bricklayers in Alabama. While the precise mechanism driving this association remains a mystery, it seems that the seeds sown in the fields have found a way to also sow the seeds of masonry careers. It appears that GMO cotton has not only revolutionized the agricultural landscape but also laid the groundwork for a flourishing brickmasonry industry in the Heart of Dixie.

In conclusion, our research sheds light on the hitherto overlooked impact of agricultural innovations on the labor market, demonstrating that what sprouts in the fields may "brick" unconventional consequences.

[[INTRDUCTION]]
The advent of genetically-modified organisms (GMOs) in agriculture has sparked contentious debates, sown widespread apprehension, and cultivated a burgeoning industry. In the United States, the adoption of GMO crops, including cotton, has been both lauded for its potential to bolster yields and criticized for its potential environmental and health implications. Alabama stands as a prime example of a state deeply entrenched in cotton farming, where the ramifications of GMO adoption reverberate through the agricultural landscape and, as our study reveals, extend their tendrils into the realm of brickmasonry.
One might jest that the relationship between GMO cotton and the number of brickmasons in Alabama is as unlikely as finding a needle in a haystack, yet our empirical investigation paints a different picture. As counterintuitive as it may seem, our research unearthed a substantial and consistent association between these seemingly disparate domains. It's almost as surprising as finding a "cotton"-candy machine inside a cotton gin!
While previous studies have predominantly focused on the agricultural and economic implications of GMO adoption, the specific impact on labor market dynamics has received scant attention. Thus, our research aims to bridge this gap and offer a fresh perspective on the repercussions of biotechnological advancements in the agricultural sector. Much like grafting a genetically-modified branch onto a traditional cotton plant, we aim to graft a new understanding of the broader implications of GMO adoption onto the existing body of knowledge.
The humorous anecdote you shared about the farmer who thought he had finally grown square watermelons only to discover they were actually bricks is a whimsical reminder of the unexpected ways in which agricultural innovations can shape not only the literal landscape, but also the labor market. Our study strives to unravel this enigma, shedding light on the intricate ways in which the tendrils of GMO cotton intertwine with the brick and mortar of Alabama's construction industry. After all, as they say, "Where there's a wheel, there's a way," and where there's GMO cotton, there might just be a demand for brickmasons.
Stay tuned for the analysis of the data, as our findings promise to pack a concrete punch, just like a well-laid brick wall.

[[RESULTS]]
The results of our analysis revealed a strong positive correlation between the use of genetically-modified organisms (GMOs) in cotton farming in Alabama and the number of brickmasons in the state. The correlation coefficient of 0.9556719 and the r-squared value of 0.9133088 indicate a robust relationship between these two variables. This statistical association suggests a substantial impact of GMO cotton cultivation on the demand for bricklayers in Alabama.
Figure 1 presents a scatterplot illustrating the pronounced correlation between GMO cotton usage and the number of brickmasons in Alabama. The data points form a clear upward trend, emphasizing the close connection between these phenomena.
Some might find it "punny" that the correlation we uncovered between genetically-modified cotton and the masonry workforce is as solid as, well, a brick wall. This unlikely relationship may have seemed as improbable as a farmer growing square watermelons, only to discover a "block"-buster surprise! Our findings, however, dispel any doubts about the tangible link between agricultural practices and labor market dynamics.
When we planted the seeds of our research, we certainly didn't expect to harvest evidence of such a strong association between GMO cotton and the number of brickmasons. The unexpected nature of this correlation speaks to the intricate and often surprising ways in which economic and agricultural forces interweave. It seems that the impact of GMO cotton cultivation extends beyond the fields and into the very fabric of Alabama's labor market.
The significance of our results cannot be overstated, as they underscore the need to consider the broader repercussions of agricultural innovations on labor market dynamics. Our study offers a fresh perspective on the multifaceted effects of GMO adoption, challenging traditional notions of the boundaries between agricultural and labor sectors. After all, as the saying goes, "Behind every successful mason, there's a strong correlation with GMO cotton."

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation unveils a compelling relationship between the use of genetically-modified organisms (GMOs) in cotton farming in Alabama and the number of brickmasons in the state. The robust statistical correlation we uncovered indicates a noteworthy influence of GMO cotton cultivation on the demand for bricklayers. It seems that the seeds of GMO cotton not only yield bountiful crops but also lay the bricks for a flourishing masonry workforce in Alabama.

One might say that the connection between GMO cotton and the number of brickmasons is as solid as, well, a well-laid brick wall. It appears that these seemingly disparate domains are intertwined in ways as unexpected as finding a pyramid in a field of corn - a true "maize" of correlations, one might jest.

Our findings highlight the nuanced impact of agricultural advancements on labor market dynamics, challenging conventional wisdom and expanding our understanding of the far-reaching effects of biotechnological innovations. Much like a bricklayer meticulously arranging each brick, our study pieces together a new understanding of the intricate ties between agricultural practices and labor trends, demonstrating that the influence of GMO cotton transcends the confines of the farm and resonates firmly in the labor market.

Therefore, it is with a lighthearted yet firm conviction that we assert no further research is needed in this area. We have planted the seeds of knowledge, and they have sprouted into a robust and, dare I say, "punny" insight into the unexpected connections between genetically-modified cotton and the demand for bricklayers in Alabama. It seems that in this case, as in many others, where there's GMO cotton, there's a proliferation of brickmasons.

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 Genetically-Modified Cotton: Sow Your Seeds, Reap More Masons in Alabama. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Agricultural Genetics and Regional Economics

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 Genetically-Modified Cotton: Sow Your Seeds, Reap More Masons in Alabama. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Agricultural Advancement and Innovation

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Genetically-Modified Cotton: Sow Your Seeds, Reap More Masons in Alabama with an abstract of This study examines the relationship between the use of genetically-modified organisms (GMOs) in cotton farming in Alabama and the number of brickmasons in the state. Utilizing data from the USDA and the Bureau of Labor Statistics spanning the years 2005 to 2022, our research team sought to untangle the intricate threads connecting agricultural practices and labor trends. Our findings revealed a remarkable correlation coefficient of 0.9556719, with a p-value of less than 0.01, indicating a robust statistical relationship between the two variables.
Our investigation unearths a surprising and, quite literally, foundational bond between the adoption of GMOs in cotton cultivation and the demand for bricklayers in Alabama. While the precise mechanism driving this association remains a mystery, it seems that the seeds sown in the fields have found a way to also sow the seeds of masonry careers. It appears that GMO cotton has not only revolutionized the agricultural landscape but also laid the groundwork for a flourishing brickmasonry industry in the Heart of Dixie.
In conclusion, our research sheds light on the hitherto overlooked impact of agricultural innovations on the labor market, demonstrating that what sprouts in the fields may "brick" unconventional consequences.

ChatGPT:

genetically modified cotton, GMO cotton, cotton farming Alabama, brickmasons Alabama, USDA cotton data, Bureau of Labor Statistics Alabama, agricultural practices labor trends, GMOs labor market, cotton cultivation labor demand, agricultural innovations labor market

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

The number of brickmasons in Alabama
Detailed data title: BLS estimate of brickmasons and blockmasons in Alabama
Source: Bureau of Larbor Statistics
See what else correlates with The number of brickmasons in Alabama

Correlation r = 0.9556719 (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 = 0.9133088 (Coefficient of determination)
This means 91.3% of the change in the one variable (i.e., The number of brickmasons in Alabama) is predictable based on the change in the other (i.e., GMO use in cotton in Alabama) over the 18 years from 2005 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.5E-10.^Show 0.0000000006521180095745508000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.96 in 6.5E-8% of random cases. Said differently, if you correlated 1,533,464,780 random variables^Note You don't actually need 1 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 17 degrees of freedom, ^Note 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.

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

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

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

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

	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
GMO use in cotton in Alabama (GMO cotton %)	28	25	25	15	18	7	4	11	4	6	3	2	3	6	5	3	2	3
The number of brickmasons in Alabama (Laborers)	1220	1240	1280	1100	810	640	580	640	530	510	440	460	490	530	470	440	360	300

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([28,25,25,15,18,7,4,11,4,6,3,2,3,6,5,3,2,3,])
array_2 = np.array([1220,1240,1280,1100,810,640,580,640,530,510,440,460,490,530,470,440,360,300,])
array_1_name = "GMO use in cotton in Alabama"
array_2_name = "The number of brickmasons in Alabama"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
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Line chart for only GMO use in cotton in Alabama
Line chart for only The number of brickmasons in Alabama
AI-generated correlation image
The spurious research paper: Genetically-Modified Cotton: Sow Your Seeds, Reap More Masons in Alabama

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Correlation ID: 3236 · Black Variable ID: 779 · Red Variable ID: 4605


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