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Spurious correlation #4,476 · 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 Louisiana and the second variable is Votes for the Republican Presidential candidate in Louisiana.  The chart goes from 2000 to 2020, and the two variables track closely in value over that time. Small Image
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AI explanation

As the saying goes, when it comes to GMO cotton in Louisiana, it's a real 'bale' of laughs. Perhaps the Republican candidate's campaign slogan should have been "Make Agriculture 'Grate' Again"! With GMO cotton on the rise, it looks like the Republican party really knows how to 'sow' the seeds of success in Louisiana. Who knew that a little bit of genetic modification could 'cotton' so well with Republican voters? It seems like in the political fields of Louisiana, the Republicans are really 'harvesting' the support, straight to the 'polls'! Remember, when it comes to politics and cotton, it’s all about 'reaping' what you 'sow'! Keep in mind that this explanation is only a humorous thought exercise, and in reality, political decisions are influenced by a wide range of complex factors.

Model: dalle-3
Prompt: Generate an image that captures the essence of 'Star Wars', but set within a picturesque Louisiana cotton field. The scene should showcase rows of genetically modified cotton plants extending into the distance, their vibrant green leaves dancing under the sunlight. In the foreground, a group of Republican supporters, clad in red hats with the campaign slogan "Make Agriculture 'Grate' Again," joyfully gather at the edge of the field. They exuberantly cheer as a bale of cotton is lifted onto a tractor, symbolizing a fruitful harvest. It's a lighthearted and playful scene, where the tractor proudly displays a sign that humorously proclaims, "Sow the Seeds of Success with GMO Cotton." This imaginative depiction humorously blends the use of GMO cotton and Republican support in the heart of Louisiana. 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 Louisiana and Votes for the Republican Presidential candidate in Louisiana. 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: a funny image you would see on reddit Brutalism An image that looks like it is a scene from A Disney Movie a meme An image that looks like it is a scene from 'Star Wars'
ChatGPT: An image that looks like it is a scene from 'Star Wars'

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 Louisiana and Votes for the Republican Presidential candidate in Louisiana, in the following situation: As the saying goes, when it comes to GMO cotton in Louisiana, it's a real 'bale' of laughs. Perhaps the Republican candidate's campaign slogan should have been "Make Agriculture 'Grate' Again"! With GMO cotton on the rise, it looks like the Republican party really knows how to 'sow' the seeds of success in Louisiana. Who knew that a little bit of genetic modification could 'cotton' so well with Republican voters? It seems like in the political fields of Louisiana, the Republicans are really 'harvesting' the support, straight to the 'polls'! Remember, when it comes to politics and cotton, it’s all about 'reaping' what you 'sow'! Keep in mind that this explanation is only a humorous thought exercise, and in reality, political decisions are influenced by a wide range of complex factors.. Keep the description simple.
ChatGPT: In a Louisiana cotton field, rows of genetically modified cotton plants stretch into the distance, their vibrant green leaves basking in the sunlight. At the edge of the field, a group of Republican supporters gathers, wearing red hats emblazoned with the campaign slogan "Make Agriculture 'Grate' Again". They cheer as a bale of cotton is hoisted onto a tractor, symbolizing the successful harvest. In a lighthearted twist, the tractor bears a sign that reads "Sow the Seeds of Success with GMO Cotton". The scene humorously captures the intersection of GMO cotton use and Republican support in Louisiana.

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: [ An image that looks like it is a scene from 'Star Wars' ] and depicting this scene: In a Louisiana cotton field, rows of genetically modified cotton plants stretch into the distance, their vibrant green leaves basking in the sunlight. At the edge of the field, a group of Republican supporters gathers, wearing red hats emblazoned with the campaign slogan "Make Agriculture 'Grate' Again". They cheer as a bale of cotton is hoisted onto a tractor, symbolizing the successful harvest. In a lighthearted twist, the tractor bears a sign that reads "Sow the Seeds of Success with GMO Cotton". The scene humorously captures the intersection of GMO cotton use and Republican support in Louisiana. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that captures the essence of 'Star Wars', but set within a picturesque Louisiana cotton field. The scene should showcase rows of genetically modified cotton plants extending into the distance, their vibrant green leaves dancing under the sunlight. In the foreground, a group of Republican supporters, clad in red hats with the campaign slogan "Make Agriculture 'Grate' Again," joyfully gather at the edge of the field. They exuberantly cheer as a bale of cotton is lifted onto a tractor, symbolizing a fruitful harvest. It's a lighthearted and playful scene, where the tractor proudly displays a sign that humorously proclaims, "Sow the Seeds of Success with GMO Cotton." This imaginative depiction humorously blends the use of GMO cotton and Republican support in the heart of Louisiana.

*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 Louisiana caused Votes for the Republican Presidential candidate in Louisiana to increase. Include one good pun.

AI academic paper

(Because p < 0.01)
From GMO to GOP: Unraveling the Cotton-nection Between Genetically Modified Cotton and Republican Votes in Louisiana

Journal of Agro-Political Dynamics

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 Louisiana and Votes for the Republican Presidential candidate in Louisiana. Make lots of jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, make it sound serious.

Your research team used data from USDA and MIT Election Data and Science Lab, Harvard Dataverse to assess this nagging question. You found a correlation coefficient of 0.9969641 and p < 0.01 for 2000 to 2020.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
From GMO to GOP: Unraveling the Cotton-nection Between Genetically Modified Cotton and Republican Votes in Louisiana

[[ABSTRACT]]
In this study, we delve into the captivating correlation between the use of genetically modified cotton (GMO) in Louisiana and the voting patterns for the Republican Party's presidential candidates. Our research team utilized data from the USDA and MIT Election Data and Science Lab, Harvard Dataverse to explore this curious relationship. Analyzing the data from 2000 to 2020, we discovered a strikingly high correlation coefficient of 0.9969641 with a p-value less than 0.01. The findings of our study not only unveil the intriguing intertwine between GMO and GOP, but also shed light on the unexpected and whimsical side of political and agricultural dynamics in Louisiana. Join us on this whimsical cotton-nection journey as we uncover the comical coexistence of genetically modified cotton and GOP votes in the Pelican State!


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 Louisiana and Votes for the Republican Presidential candidate in Louisiana. Make lots of jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
From GMO to GOP: Unraveling the Cotton-nection Between Genetically Modified Cotton and Republican Votes in Louisiana

[[ABSTRACT]]
In this study, we delve into the captivating correlation between the use of genetically modified cotton (GMO) in Louisiana and the voting patterns for the Republican Party's presidential candidates. Our research team utilized data from the USDA and MIT Election Data and Science Lab, Harvard Dataverse to explore this curious relationship. Analyzing the data from 2000 to 2020, we discovered a strikingly high correlation coefficient of 0.9969641 with a p-value less than 0.01. The findings of our study not only unveil the intriguing intertwine between GMO and GOP, but also shed light on the unexpected and whimsical side of political and agricultural dynamics in Louisiana. Join us on this whimsical cotton-nection journey as we uncover the comical coexistence of genetically modified cotton and GOP votes in the Pelican State!

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
*[[INTRODUCTION]]*
Ah, the wondrous world of genetically modified organisms (GMOs) and the colorful realm of political alliances! In this paper, we are about to embark on a journey through the fields of cotton in Louisiana and the ballot boxes of its residents, all in pursuit of uncovering the mysterious bond between genetically modified cotton and votes for the Republican presidential candidates. It's a tale of "GMO to GOP," where we aim to unravel the cotton-nection between these seemingly unrelated entities.

Louisiana, often associated with its vibrant culture, delicious cuisine, and the resonating tunes of jazz, has an equally captivating agricultural landscape. Among its agricultural commodities, cotton holds a significant place, contributing both economically and aesthetically to the state's character. Concurrently, Louisiana also exhibits intriguing and, dare I say, confounding political patterns. Now, what happens when we sprinkle a dash of genetically modified cotton into this political gumbo? Hold onto your lab coats, for this is where the plot thickens!

As we venture into this entangled tale, we cannot overlook the essence of GMOs and their impact on agricultural practices. While some may perceive GMOs as "Frankenfoods," others see them as technological innovations with the potential to revolutionize crop cultivation. Within this debate lies the inherently divisive nature of GMOs, just like a pair of genetically fragmented genes eager to express their phenotypes.

On the other hand, the Republican party, synonymous with the pachyderm mascot, has its stronghold in certain pockets of the U.S., including Louisiana. The party's political maneuvers often evoke quizzical looks and intense discussions, akin to solving a complex genetic puzzle. So, what curious concatenations could be revealed when we merge these two seemingly distant domains: GMO and GOP?

Now, before we delve deeper into the whimsical cotton-nection journey, let us prepare ourselves for a fascinating expedition that will take us beyond the realm of conventional political and agricultural analyses. It's time to set sail into the picturesque bayous of Louisiana, where GMOs and Republican votes converge in a kaleidoscope of amazement and intrigue. Join us as we unravel the captivating tale of "GMO to GOP" and discover the unforeseen interplay between genetically modified cotton and political preferences in the Bayou State!


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 Louisiana and Votes for the Republican Presidential candidate in Louisiana. Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some movies that you watched that are tangentially related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
From GMO to GOP: Unraveling the Cotton-nection Between Genetically Modified Cotton and Republican Votes in Louisiana

[[ABSTRACT]]
In this study, we delve into the captivating correlation between the use of genetically modified cotton (GMO) in Louisiana and the voting patterns for the Republican Party's presidential candidates. Our research team utilized data from the USDA and MIT Election Data and Science Lab, Harvard Dataverse to explore this curious relationship. Analyzing the data from 2000 to 2020, we discovered a strikingly high correlation coefficient of 0.9969641 with a p-value less than 0.01. The findings of our study not only unveil the intriguing intertwine between GMO and GOP, but also shed light on the unexpected and whimsical side of political and agricultural dynamics in Louisiana. Join us on this whimsical cotton-nection journey as we uncover the comical coexistence of genetically modified cotton and GOP votes in the Pelican State!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
**
Ah, the wondrous world of genetically modified organisms (GMOs) and the colorful realm of political alliances! In this paper, we are about to embark on a journey through the fields of cotton in Louisiana and the ballot boxes of its residents, all in pursuit of uncovering the mysterious bond between genetically modified cotton and votes for the Republican presidential candidates. It's a tale of "GMO to GOP," where we aim to unravel the cotton-nection between these seemingly unrelated entities.
Louisiana, often associated with its vibrant culture, delicious cuisine, and the resonating tunes of jazz, has an equally captivating agricultural landscape. Among its agricultural commodities, cotton holds a significant place, contributing both economically and aesthetically to the state's character. Concurrently, Louisiana also exhibits intriguing and, dare I say, confounding political patterns. Now, what happens when we sprinkle a dash of genetically modified cotton into this political gumbo? Hold onto your lab coats, for this is where the plot thickens!
As we venture into this entangled tale, we cannot overlook the essence of GMOs and their impact on agricultural practices. While some may perceive GMOs as "Frankenfoods," others see them as technological innovations with the potential to revolutionize crop cultivation. Within this debate lies the inherently divisive nature of GMOs, just like a pair of genetically fragmented genes eager to express their phenotypes.
On the other hand, the Republican party, synonymous with the pachyderm mascot, has its stronghold in certain pockets of the U.S., including Louisiana. The party's political maneuvers often evoke quizzical looks and intense discussions, akin to solving a complex genetic puzzle. So, what curious concatenations could be revealed when we merge these two seemingly distant domains: GMO and GOP?
Now, before we delve deeper into the whimsical cotton-nection journey, let us prepare ourselves for a fascinating expedition that will take us beyond the realm of conventional political and agricultural analyses. It's time to set sail into the picturesque bayous of Louisiana, where GMOs and Republican votes converge in a kaleidoscope of amazement and intrigue. Join us as we unravel the captivating tale of "GMO to GOP" and discover the unforeseen interplay between genetically modified cotton and political preferences in the Bayou State!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

As we traverse the curious terrain of the cotton fields of Louisiana and the political landscape intertwined within, it is imperative to explore the existing literature that sheds light on the enigmatic correlation between genetically modified cotton (GMO) and votes for the Republican presidential candidates. The fabric of this unconventional relationship has been woven through various scholarly works that impart both serious analyses and a dash of whimsy to our understanding.

Smith et al. (2010) delve into the agricultural ramifications of GMO utilization, providing a comprehensive analysis of its impact on crop yields and sustainability. Their findings offer a rich tapestry of insights into the role of GMO cotton in the agricultural fabric of Louisiana, where the threads of innovation and controversy intertwine.

In a similar vein, Doe and Jones (2015) conducted an in-depth examination of political voting patterns in Louisiana, unraveling the intricate web of factors that influence electoral choices. Their work provides a nuanced perspective on the varied influences shaping the political topography of the state, serving as a fitting background for our exploration of the cotton-nection between GMO and GOP votes.

Venturing into the realm of non-fiction literature, "The Omnivore's Dilemma" by Michael Pollan presents a savory blend of agricultural discourse and culinary contemplations, offering a hearty feast of insights into the complex interplay between food production and consumption. In this gastronomic odyssey, Pollan invites readers to ponder the profound implications of genetically modified crops on our plates and in our political palates.

Additionally, the work of fiction often serves as a source of inspiration with unexpected parallels to our research. In "Cotton Candy Cowboy" by Jill Marie Landis, the alluring allure of the cotton fields converges with the captivating cadence of romance, offering a whimsical juxtaposition to the empirical inquiries of our study. While the allure of romance may not directly influence voting patterns, it does add a touch of playfulness to the fabric of our exploration.

Drawing from the realm of cinematic experiences, the movie "Field of Dreams" provides a captivating metaphor for the quixotic quest we undertake in unraveling the cotton-nection between GMO and GOP votes. As we navigate through the cornfields of curiosity, mirages of unimaginable correlations emerge, beckoning us to build our own field of hypotheses and dreams. Just like in the movie, as we unearth the unexpected synergies, we are reminded that in the realm of research, "if you build it, correlations will come."

As we embark on this whimsical cotton-nection journey, our review of the literature prepares us for the unpredictably delightful discoveries that await us in the enthralling interplay between genetically modified cotton and Republican votes in the captivating state of Louisiana.


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 Louisiana and Votes for the Republican Presidential candidate in Louisiana. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from USDA and MIT Election Data and Science Lab, Harvard Dataverse . You used data from 2000 to 2020

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
From GMO to GOP: Unraveling the Cotton-nection Between Genetically Modified Cotton and Republican Votes in Louisiana

[[ABSTRACT]]
In this study, we delve into the captivating correlation between the use of genetically modified cotton (GMO) in Louisiana and the voting patterns for the Republican Party's presidential candidates. Our research team utilized data from the USDA and MIT Election Data and Science Lab, Harvard Dataverse to explore this curious relationship. Analyzing the data from 2000 to 2020, we discovered a strikingly high correlation coefficient of 0.9969641 with a p-value less than 0.01. The findings of our study not only unveil the intriguing intertwine between GMO and GOP, but also shed light on the unexpected and whimsical side of political and agricultural dynamics in Louisiana. Join us on this whimsical cotton-nection journey as we uncover the comical coexistence of genetically modified cotton and GOP votes in the Pelican State!

[[INTRODUCTION]]
**
Ah, the wondrous world of genetically modified organisms (GMOs) and the colorful realm of political alliances! In this paper, we are about to embark on a journey through the fields of cotton in Louisiana and the ballot boxes of its residents, all in pursuit of uncovering the mysterious bond between genetically modified cotton and votes for the Republican presidential candidates. It's a tale of "GMO to GOP," where we aim to unravel the cotton-nection between these seemingly unrelated entities.
Louisiana, often associated with its vibrant culture, delicious cuisine, and the resonating tunes of jazz, has an equally captivating agricultural landscape. Among its agricultural commodities, cotton holds a significant place, contributing both economically and aesthetically to the state's character. Concurrently, Louisiana also exhibits intriguing and, dare I say, confounding political patterns. Now, what happens when we sprinkle a dash of genetically modified cotton into this political gumbo? Hold onto your lab coats, for this is where the plot thickens!
As we venture into this entangled tale, we cannot overlook the essence of GMOs and their impact on agricultural practices. While some may perceive GMOs as "Frankenfoods," others see them as technological innovations with the potential to revolutionize crop cultivation. Within this debate lies the inherently divisive nature of GMOs, just like a pair of genetically fragmented genes eager to express their phenotypes.
On the other hand, the Republican party, synonymous with the pachyderm mascot, has its stronghold in certain pockets of the U.S., including Louisiana. The party's political maneuvers often evoke quizzical looks and intense discussions, akin to solving a complex genetic puzzle. So, what curious concatenations could be revealed when we merge these two seemingly distant domains: GMO and GOP?
Now, before we delve deeper into the whimsical cotton-nection journey, let us prepare ourselves for a fascinating expedition that will take us beyond the realm of conventional political and agricultural analyses. It's time to set sail into the picturesque bayous of Louisiana, where GMOs and Republican votes converge in a kaleidoscope of amazement and intrigue. Join us as we unravel the captivating tale of "GMO to GOP" and discover the unforeseen interplay between genetically modified cotton and political preferences in the Bayou State!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

You, dear reader, are about to embark on a journey through the quirky corridors of our research methodology. So hold onto your lab goggles, because things are about to get a bit whimsical!

Data Collection:
Our first step in this captivating caper involved traversing the intricate labyrinth of the internet. We scavenged through online databases like an academic Sherlock Holmes in search of clues. Our primary sources of data included the United States Department of Agriculture (USDA) and the MIT Election Data and Science Lab, Harvard Dataverse. While we often found ourselves lost in the vast expanse of cyberspace, we eventually emerged victorious, armed with an arsenal of data on GMO cotton usage and Republican presidential voting patterns from the years 2000 to 2020.

Data Analysis:
Now, to make sense of this trove of information, we enlisted the help of our trusty statistical tools. Armed with spreadsheets, graphs, and a remarkable amount of caffeine, we set about unraveling the enigmatic relationship between GMO cotton and GOP votes. Using the ancient and mystical arts of correlation analysis and regression modeling, we sought to tease out any potential connections between these perplexing variables.

Wait, are we really suggesting that the fate of presidential candidates is intertwined with genetically modified cotton fields? Perhaps there’s a cotton-nection after all!

Multivariate Regression Modeling:
As any reputable researcher will tell you, one cannot simply waltz into the world of multivariate regression without a map and a sturdy pair of statistical boots. We navigated this complex terrain with the finesse of a GPS-guided explorer, carefully considering covariates such as agricultural demographics, regional electoral trends, and the occasional unexpected outlier (looking at you, anomalous election year of 2008).

By injecting these variables into our computational cauldron, we concocted a statistical potion that could distill the essence of the cotton-nection between GMO usage and GOP votes. With bated breath, we peered into the bubbling brew of coefficients and standard errors, hoping to glimpse the elusive threads that bound cotton and conservative political leanings together.

Spatial Analysis:
Like intrepid cartographers charting unexplored territories, we ventured into the realm of spatial analysis. Armed with geographic information systems (GIS) and a healthy dose of curiosity, we mapped the spatial distribution of GMO cotton cultivation and Republican electoral support across the parishes of Louisiana. The resulting cartographic tableau offered tantalizing glimpses into the geographical tapestry of this cotton-nection, painting a picture that transcended mere numbers and statistics.

Qualitative Inquiry:
As if this rollercoaster ride of quantitative methods wasn’t exhilarating enough, we also embraced the art of qualitative inquiry. We engaged in illuminating conversations with farmers, activists, and politically engaged citizens, seeking to understand the human dimensions of this cotton-nection. Their insights added depth to our findings, revealing the idiosyncratic nuances of GMO adoption and political affiliations in the cultural mosaic of Louisiana.

In summary, our research methodology was a spirited dance between the realms of data collection, statistical sorcery, spatial exploration, and qualitative storytelling. With the zeal of intrepid explorers and the antics of academic jesters, we set out to unravel the cotton-nection between GMO cotton and GOP votes in Louisiana, unearthing whimsy and wonder along the way.


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 Louisiana and Votes for the Republican Presidential candidate in Louisiana. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from USDA and MIT Election Data and Science Lab, Harvard Dataverse .

For the time period 2000 to 2020, you found a correlation 0.9969641, r-squared of 0.9939374, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
From GMO to GOP: Unraveling the Cotton-nection Between Genetically Modified Cotton and Republican Votes in Louisiana

[[ABSTRACT]]
In this study, we delve into the captivating correlation between the use of genetically modified cotton (GMO) in Louisiana and the voting patterns for the Republican Party's presidential candidates. Our research team utilized data from the USDA and MIT Election Data and Science Lab, Harvard Dataverse to explore this curious relationship. Analyzing the data from 2000 to 2020, we discovered a strikingly high correlation coefficient of 0.9969641 with a p-value less than 0.01. The findings of our study not only unveil the intriguing intertwine between GMO and GOP, but also shed light on the unexpected and whimsical side of political and agricultural dynamics in Louisiana. Join us on this whimsical cotton-nection journey as we uncover the comical coexistence of genetically modified cotton and GOP votes in the Pelican State!

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
**
Ah, the wondrous world of genetically modified organisms (GMOs) and the colorful realm of political alliances! In this paper, we are about to embark on a journey through the fields of cotton in Louisiana and the ballot boxes of its residents, all in pursuit of uncovering the mysterious bond between genetically modified cotton and votes for the Republican presidential candidates. It's a tale of "GMO to GOP," where we aim to unravel the cotton-nection between these seemingly unrelated entities.
Louisiana, often associated with its vibrant culture, delicious cuisine, and the resonating tunes of jazz, has an equally captivating agricultural landscape. Among its agricultural commodities, cotton holds a significant place, contributing both economically and aesthetically to the state's character. Concurrently, Louisiana also exhibits intriguing and, dare I say, confounding political patterns. Now, what happens when we sprinkle a dash of genetically modified cotton into this political gumbo? Hold onto your lab coats, for this is where the plot thickens!
As we venture into this entangled tale, we cannot overlook the essence of GMOs and their impact on agricultural practices. While some may perceive GMOs as "Frankenfoods," others see them as technological innovations with the potential to revolutionize crop cultivation. Within this debate lies the inherently divisive nature of GMOs, just like a pair of genetically fragmented genes eager to express their phenotypes.
On the other hand, the Republican party, synonymous with the pachyderm mascot, has its stronghold in certain pockets of the U.S., including Louisiana. The party's political maneuvers often evoke quizzical looks and intense discussions, akin to solving a complex genetic puzzle. So, what curious concatenations could be revealed when we merge these two seemingly distant domains: GMO and GOP?
Now, before we delve deeper into the whimsical cotton-nection journey, let us prepare ourselves for a fascinating expedition that will take us beyond the realm of conventional political and agricultural analyses. It's time to set sail into the picturesque bayous of Louisiana, where GMOs and Republican votes converge in a kaleidoscope of amazement and intrigue. Join us as we unravel the captivating tale of "GMO to GOP" and discover the unforeseen interplay between genetically modified cotton and political preferences in the Bayou State!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our investigation into the cotton-nection between genetically modified cotton (GMO) use in Louisiana and votes for the Republican presidential candidates from 2000 to 2020 are nothing short of extraordinary. We unearthed a correlation coefficient of 0.9969641, an r-squared value of 0.9939374, and a p-value less than 0.01. It seems that the GMO to GOP bond is no laughing matter; the correlation is as strong as the fibers in a well-spun cotton thread!

To visually encapsulate the striking correlation we uncovered, we present Figure 1, a scatterplot illustrating the robust relationship between the utilization of genetically modified cotton and the votes for the Republican presidential candidates in Louisiana. The figures truly speak for themselves and firmly convey the whimsical cotton-nection between these seemingly distinct realms.

Our findings suggest that there is more to Louisiana's agricultural and political landscape than meets the eye. The intertwining of genetically modified cotton and political preferences in this southern state is akin to a plot twist in a captivating novel – unexpected, enigmatic, and bound to keep the readers (or in this case, researchers) at the edge of their seats.

These results not only shed light on the remarkable correlation between GMO usage in cotton and Republican votes in Louisiana but also underscore the significance of considering unexpected variables in political and agricultural analyses. The intricate dance between genetically modified cotton and political preferences in Louisiana is a reminder that in the world of research, every correlation, no matter how quirky, demands attention and contemplation.

In conclusion, the GMO to GOP revelation serves as a whimsical reminder that in the land of agricultural organisms and political allegiances, the unexpected can often hold the key to unraveling the most captivating and bewildering mysteries. Join us in celebrating the fascinating cotton-nection between GMO and GOP, a tale that transcends traditional boundaries and leaves us marveling at the enthralling dance of variables in the charming Pelican State!


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 Louisiana and Votes for the Republican Presidential candidate in Louisiana. Make lots of jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
From GMO to GOP: Unraveling the Cotton-nection Between Genetically Modified Cotton and Republican Votes in Louisiana

[[ABSTRACT]]
In this study, we delve into the captivating correlation between the use of genetically modified cotton (GMO) in Louisiana and the voting patterns for the Republican Party's presidential candidates. Our research team utilized data from the USDA and MIT Election Data and Science Lab, Harvard Dataverse to explore this curious relationship. Analyzing the data from 2000 to 2020, we discovered a strikingly high correlation coefficient of 0.9969641 with a p-value less than 0.01. The findings of our study not only unveil the intriguing intertwine between GMO and GOP, but also shed light on the unexpected and whimsical side of political and agricultural dynamics in Louisiana. Join us on this whimsical cotton-nection journey as we uncover the comical coexistence of genetically modified cotton and GOP votes in the Pelican State!

[[LITERATURE REVIEW]]
As we traverse the curious terrain of the cotton fields of Louisiana and the political landscape intertwined within, it is imperative to explore the existing literature that sheds light on the enigmatic correlation between genetically modified cotton (GMO) and votes for the Republican presidential candidates. The fabric of this unconventional relationship has been woven through various scholarly works that impart both serious analyses and a dash of whimsy to our understanding.
Smith et al. (2010) delve into the agricultural ramifications of GMO utilization, providing a comprehensive analysis of its impact on crop yields and sustainability. Their findings offer a rich tapestry of insights into the role of GMO cotton in the agricultural fabric of Louisiana, where the threads of innovation and controversy intertwine.
In a similar vein, Doe and Jones (2015) conducted an in-depth examination of political voting patterns in Louisiana, unraveling the intricate web of factors that influence electoral choices. Their work provides a nuanced perspective on the varied influences shaping the political topography of the state, serving as a fitting background for our exploration of the cotton-nection between GMO and GOP votes.
Venturing into the realm of non-fiction literature, "The Omnivore's Dilemma" by Michael Pollan presents a savory blend of agricultural discourse and culinary contemplations, offering a hearty feast of insights into the complex interplay between food production and consumption. In this gastronomic odyssey, Pollan invites readers to ponder the profound implications of genetically modified crops on our plates and in our political palates.
Additionally, the work of fiction often serves as a source of inspiration with unexpected parallels to our research. In "Cotton Candy Cowboy" by Jill Marie Landis, the alluring allure of the cotton fields converges with the captivating cadence of romance, offering a whimsical juxtaposition to the empirical inquiries of our study. While the allure of romance may not directly influence voting patterns, it does add a touch of playfulness to the fabric of our exploration.
Drawing from the realm of cinematic experiences, the movie "Field of Dreams" provides a captivating metaphor for the quixotic quest we undertake in unraveling the cotton-nection between GMO and GOP votes. As we navigate through the cornfields of curiosity, mirages of unimaginable correlations emerge, beckoning us to build our own field of hypotheses and dreams. Just like in the movie, as we unearth the unexpected synergies, we are reminded that in the realm of research, "if you build it, correlations will come."
As we embark on this whimsical cotton-nection journey, our review of the literature prepares us for the unpredictably delightful discoveries that await us in the enthralling interplay between genetically modified cotton and Republican votes in the captivating state of Louisiana.

[[RESULTS]]
The results of our investigation into the cotton-nection between genetically modified cotton (GMO) use in Louisiana and votes for the Republican presidential candidates from 2000 to 2020 are nothing short of extraordinary. We unearthed a correlation coefficient of 0.9969641, an r-squared value of 0.9939374, and a p-value less than 0.01. It seems that the GMO to GOP bond is no laughing matter; the correlation is as strong as the fibers in a well-spun cotton thread!
To visually encapsulate the striking correlation we uncovered, we present Figure 1, a scatterplot illustrating the robust relationship between the utilization of genetically modified cotton and the votes for the Republican presidential candidates in Louisiana. The figures truly speak for themselves and firmly convey the whimsical cotton-nection between these seemingly distinct realms.
Our findings suggest that there is more to Louisiana's agricultural and political landscape than meets the eye. The intertwining of genetically modified cotton and political preferences in this southern state is akin to a plot twist in a captivating novel – unexpected, enigmatic, and bound to keep the readers (or in this case, researchers) at the edge of their seats.
These results not only shed light on the remarkable correlation between GMO usage in cotton and Republican votes in Louisiana but also underscore the significance of considering unexpected variables in political and agricultural analyses. The intricate dance between genetically modified cotton and political preferences in Louisiana is a reminder that in the world of research, every correlation, no matter how quirky, demands attention and contemplation.
In conclusion, the GMO to GOP revelation serves as a whimsical reminder that in the land of agricultural organisms and political allegiances, the unexpected can often hold the key to unraveling the most captivating and bewildering mysteries. Join us in celebrating the fascinating cotton-nection between GMO and GOP, a tale that transcends traditional boundaries and leaves us marveling at the enthralling dance of variables in the charming Pelican State!

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

Ah, the whimsical dance of genetically modified cotton and Republican votes in Louisiana has left us pondering the peculiarities of political and agricultural dynamics in the Pelican State. Our results have not only unveiled the comical fibers of the GMO to GOP connection but also added an unexpected twist to the fabric of research in Louisiana.

Smith et al. (2010) may have sown the seeds of knowledge about the agricultural impacts of GMO, but our findings have woven a more intricate pattern, highlighting a correlation as strong as the fibers in, well, a good old cotton thread. It seems that the interplay between GMO cotton and GOP votes is no joke, though the whimsicality of this unlikely connection brings a lighthearted levity to the research.

Intriguingly, just like "Cotton Candy Cowboy" by Jill Marie Landis, our study highlights the allure of the cotton fields and the captivating cadence of political choices. After all, who knew that romance at the cotton fields could weave its way into the state's voting patterns?

In the spirit of "Field of Dreams," our findings beckon us to build our own field of hypotheses and dreams, where unimaginable correlations emerge, urging us to embrace the unexpected synergies. The whimsical side of political and agricultural dynamics in Louisiana, indeed!

While we expected to uncover a fundamental connection, we were incredulous to discover a correlation coefficient as strong as the cotton fibers themselves. Our scatterplot, akin to a well-spun yarn, visually encapsulates the robust relationship we unveiled, leaving us marveling at the unexpected dance of variables in the charming Pelican State.

Ultimately, our study not only emphasizes the intriguing intertwine between GMO cotton and GOP votes but also underscores the significance of considering unexpected variables in political and agricultural analyses. The GMO to GOP revelation is a whimsical reminder that every correlation, no matter how quirky, holds the key to unraveling mesmerizing mysteries in the delightful state of Louisiana. Join us in celebrating the sweet and savory cotton-nection between GMO and GOP, a tale that transcends traditional boundaries and leaves us marveling at the enthralling quirks of research!



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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between GMO use in cotton in Louisiana and Votes for the Republican Presidential candidate in Louisiana. Make lots of jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
From GMO to GOP: Unraveling the Cotton-nection Between Genetically Modified Cotton and Republican Votes in Louisiana

[[ABSTRACT]]
In this study, we delve into the captivating correlation between the use of genetically modified cotton (GMO) in Louisiana and the voting patterns for the Republican Party's presidential candidates. Our research team utilized data from the USDA and MIT Election Data and Science Lab, Harvard Dataverse to explore this curious relationship. Analyzing the data from 2000 to 2020, we discovered a strikingly high correlation coefficient of 0.9969641 with a p-value less than 0.01. The findings of our study not only unveil the intriguing intertwine between GMO and GOP, but also shed light on the unexpected and whimsical side of political and agricultural dynamics in Louisiana. Join us on this whimsical cotton-nection journey as we uncover the comical coexistence of genetically modified cotton and GOP votes in the Pelican State!

[[INTRDUCTION]]
**
Ah, the wondrous world of genetically modified organisms (GMOs) and the colorful realm of political alliances! In this paper, we are about to embark on a journey through the fields of cotton in Louisiana and the ballot boxes of its residents, all in pursuit of uncovering the mysterious bond between genetically modified cotton and votes for the Republican presidential candidates. It's a tale of "GMO to GOP," where we aim to unravel the cotton-nection between these seemingly unrelated entities.
Louisiana, often associated with its vibrant culture, delicious cuisine, and the resonating tunes of jazz, has an equally captivating agricultural landscape. Among its agricultural commodities, cotton holds a significant place, contributing both economically and aesthetically to the state's character. Concurrently, Louisiana also exhibits intriguing and, dare I say, confounding political patterns. Now, what happens when we sprinkle a dash of genetically modified cotton into this political gumbo? Hold onto your lab coats, for this is where the plot thickens!
As we venture into this entangled tale, we cannot overlook the essence of GMOs and their impact on agricultural practices. While some may perceive GMOs as "Frankenfoods," others see them as technological innovations with the potential to revolutionize crop cultivation. Within this debate lies the inherently divisive nature of GMOs, just like a pair of genetically fragmented genes eager to express their phenotypes.
On the other hand, the Republican party, synonymous with the pachyderm mascot, has its stronghold in certain pockets of the U.S., including Louisiana. The party's political maneuvers often evoke quizzical looks and intense discussions, akin to solving a complex genetic puzzle. So, what curious concatenations could be revealed when we merge these two seemingly distant domains: GMO and GOP?
Now, before we delve deeper into the whimsical cotton-nection journey, let us prepare ourselves for a fascinating expedition that will take us beyond the realm of conventional political and agricultural analyses. It's time to set sail into the picturesque bayous of Louisiana, where GMOs and Republican votes converge in a kaleidoscope of amazement and intrigue. Join us as we unravel the captivating tale of "GMO to GOP" and discover the unforeseen interplay between genetically modified cotton and political preferences in the Bayou State!

[[RESULTS]]
The results of our investigation into the cotton-nection between genetically modified cotton (GMO) use in Louisiana and votes for the Republican presidential candidates from 2000 to 2020 are nothing short of extraordinary. We unearthed a correlation coefficient of 0.9969641, an r-squared value of 0.9939374, and a p-value less than 0.01. It seems that the GMO to GOP bond is no laughing matter; the correlation is as strong as the fibers in a well-spun cotton thread!
To visually encapsulate the striking correlation we uncovered, we present Figure 1, a scatterplot illustrating the robust relationship between the utilization of genetically modified cotton and the votes for the Republican presidential candidates in Louisiana. The figures truly speak for themselves and firmly convey the whimsical cotton-nection between these seemingly distinct realms.
Our findings suggest that there is more to Louisiana's agricultural and political landscape than meets the eye. The intertwining of genetically modified cotton and political preferences in this southern state is akin to a plot twist in a captivating novel – unexpected, enigmatic, and bound to keep the readers (or in this case, researchers) at the edge of their seats.
These results not only shed light on the remarkable correlation between GMO usage in cotton and Republican votes in Louisiana but also underscore the significance of considering unexpected variables in political and agricultural analyses. The intricate dance between genetically modified cotton and political preferences in Louisiana is a reminder that in the world of research, every correlation, no matter how quirky, demands attention and contemplation.
In conclusion, the GMO to GOP revelation serves as a whimsical reminder that in the land of agricultural organisms and political allegiances, the unexpected can often hold the key to unraveling the most captivating and bewildering mysteries. Join us in celebrating the fascinating cotton-nection between GMO and GOP, a tale that transcends traditional boundaries and leaves us marveling at the enthralling dance of variables in the charming Pelican State!

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

As we come to the end of our whimsical cotton-nection journey, it's clear that the intertwining of genetically modified cotton and Republican votes in Louisiana is as puzzling as a crop circle in a bayou. The correlation coefficient of 0.9969641 we discovered is stronger than an alligator's bite and leaves us reeling like a Mardi Gras reveler after a night of festivities.

Our findings not only confirm the unexpected and comical relationship between GMO and GOP but also highlight the quirkiness that permeates the political and agricultural dynamics in Louisiana. It's as if the genetically modified cotton plants and Republican voters have formed an alliance stronger than crawfish and étouffée!

The results presented in this paper are as undeniable as the appeal of a freshly baked beignet. It's clear that further research in this area would be like trying to reinvent the wheel - unnecessary and, dare I say, a bit silly. So, let's raise a glass of sweet tea to the enchanting cotton-nection between GMO and GOP in the Pelican State and bid adieu to this peculiar but thoroughly entertaining research endeavor!


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited From GMO to GOP: Unraveling the Cotton-nection Between Genetically Modified Cotton and Republican Votes in Louisiana. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Agro-Political Dynamics


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited From GMO to GOP: Unraveling the Cotton-nection Between Genetically Modified Cotton and Republican Votes in Louisiana. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Cotton Studies and Political Patterns (CCSPP)


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled From GMO to GOP: Unraveling the Cotton-nection Between Genetically Modified Cotton and Republican Votes in Louisiana with an abstract of In this study, we delve into the captivating correlation between the use of genetically modified cotton (GMO) in Louisiana and the voting patterns for the Republican Party's presidential candidates. Our research team utilized data from the USDA and MIT Election Data and Science Lab, Harvard Dataverse to explore this curious relationship. Analyzing the data from 2000 to 2020, we discovered a strikingly high correlation coefficient of 0.9969641 with a p-value less than 0.01. The findings of our study not only unveil the intriguing intertwine between GMO and GOP, but also shed light on the unexpected and whimsical side of political and agricultural dynamics in Louisiana. Join us on this whimsical cotton-nection journey as we uncover the comical coexistence of genetically modified cotton and GOP votes in the Pelican State!

ChatGPT:

genetically modified cotton, GMO, Republican votes Louisiana, GOP voting patterns, USDA data, MIT Election Data and Science Lab, Harvard Dataverse, political and agricultural dynamics Louisiana

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

Votes for the Republican Presidential candidate in Louisiana
Detailed data title: Percentage of all votes cast for the Republican Presidential candidate in Louisiana
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for the Republican Presidential candidate in Louisiana

Correlation r = 0.9969641 (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 = 0.9939374 (Coefficient of determination)
This means 99.4% of the change in the one variable (i.e., Votes for the Republican Presidential candidate in Louisiana) is predictable based on the change in the other (i.e., GMO use in cotton in Louisiana) over the 6 years from 2000 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.4E-5. 0.0000138109940717411200000000
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 1 in 0.0014% of random cases. Said differently, if you correlated 72,406 random variables You don't actually need 72 thousand 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 5 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 5 because we have two variables measured over a period of 6 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.

[ 0.97, 1 ] 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.
200020042008201220162020
GMO use in cotton in Louisiana (GMO cotton %)809398979899
Votes for the Republican Presidential candidate in Louisiana (Percentage of votes)52.551156.72258.562757.784658.088758.4609




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.
  4. Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.




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([80,93,98,97,98,99,])
array_2 = np.array([52.5511,56.722,58.5627,57.7846,58.0887,58.4609,])
array_1_name = "GMO use in cotton in Louisiana"
array_2_name = "Votes for the Republican Presidential candidate in Louisiana"

# 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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