Spurious correlation #2,848 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is US household spending on processed fruits and the second variable is GMO use in cotton in Louisiana. The chart goes from 2000 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 US household spending on processed fruits and the second variable is GMO use in cotton in Louisiana. The chart goes from 2000 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As households spent less on processed fruits, there was a decrease in fruit sticker production. This led to a nationwide sticker shortage. To fill the sticker gap, cotton in Louisiana was genetically modified to produce sticker-like tags, but it unexpectedly led to a decrease in GMO use in cotton.

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Generate a realistic image of a bustling grocery store with shelves of processed fruits gathering dust while shoppers walk by. Nearby, a Louisiana farm shows fields once filled with rows of genetically modified cotton, now blooming with vibrant non-GMO cotton plants, reflecting the shift in the market towards natural alternatives. 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: US household spending on processed fruits and GMO use in cotton 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: Realistic Minimalism Oragami Sci-fi fantacy Cute 2D animation
ChatGPT: Realistic

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 US household spending on processed fruits and GMO use in cotton in Louisiana, in the following situation: Because as people stopped buying processed fruits, cotton farmers in Louisiana had to spice things up by growing non-GMO cotton instead. They realized they couldn't squeeze out profits, so they dropped the GMO cotton and went au naturel, just like the fruits they weren't selling.. Keep the description simple.
ChatGPT: In the bustling grocery store, shelves of processed fruits gather dust as shoppers walk by. A nearby farm in Louisiana shows fields once filled with rows of genetically modified cotton now blooming with vibrant non-GMO cotton plants. The change in the fields reflects the shift away from processed fruits, as the farmers embrace natural alternatives to adapt to the changing market.

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: [ Realistic ] and depicting this scene: In the bustling grocery store, shelves of processed fruits gather dust as shoppers walk by. A nearby farm in Louisiana shows fields once filled with rows of genetically modified cotton now blooming with vibrant non-GMO cotton plants. The change in the fields reflects the shift away from processed fruits, as the farmers embrace natural alternatives to adapt to the changing market. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate a realistic image of a bustling grocery store with shelves of processed fruits gathering dust while shoppers walk by. Nearby, a Louisiana farm shows fields once filled with rows of genetically modified cotton, now blooming with vibrant non-GMO cotton plants, reflecting the shift in the market towards natural alternatives.

*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 US household spending on processed fruits caused GMO use in cotton in Louisiana to decrease.

AI academic paper

(Because p < 0.01)

Feeling Ginned Up: The Cotton Connection Between GMOs and Processed Fruit Spending in US Households

The Journal of Agricultural Comedic Studies

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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 US household spending on processed fruits and GMO use in cotton in Louisiana. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
Feeling Ginned Up: The Cotton Connection Between GMOs and Processed Fruit Spending in US Households

[[ABSTRACT]]
In this study, we peel back the layers of the relationship between US household spending on processed fruits and the use of genetically modified organisms (GMOs) in cotton production in Louisiana. Using data from the Bureau of Labor Statistics and USDA, we conducted a thorough analysis to explore the potential link between these seemingly disparate elements. Like a banana at a party, we aim to appeal to both the serious and the quirky sides of academia.

Our findings revealed a pear-fectly ripe correlation coefficient of 0.9263976 and a statistically significant p-value of less than 0.01 for the years 2000 to 2022, shedding light on the strong association between GMO cotton cultivation in Louisiana and household expenditure on processed fruits across the US. The results indicate that as GMO cotton production in Louisiana blooms, so does the spending on processed fruits by households nationwide. It's as if GMOs and processed fruits are engaging in a fruitful dance of economic interdependence.

Our research brings a unique flavor to the table by highlighting the unexplored connection between GMO cotton in one region and consumer choices in another. It seems that when it comes to household spending and agriculture, the seeds are sown more deeply than we previously thought. The findings of this study not only contribute to the understanding of consumer behavior and agricultural practices but also offer a refreshing perspective to the field of interdisciplinary research.

So, the next time someone questions the correlation between GMOs and processed fruit spending, you can confidently respond with, "That's just how the produce-pieces of the puzzle fit together!"

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In recent years, the intersection of agricultural practices and consumer behavior has garnered increasing attention from researchers and policymakers alike. As the global demand for processed fruits continues to grow, understanding the factors influencing household spending on these products has become a matter of significant importance. Likewise, the widespread adoption of genetically modified organisms (GMOs) in agricultural production has raised questions regarding its impact on both the environment and consumer choices. With this in mind, we set out to investigate the tantalizing relationship between US household spending on processed fruits and the use of GMOs in cotton production specifically in Louisiana.
It may seem like a stretch to draw a connection between cotton and cantaloupes, but our research aims to demonstrate that these seemingly unrelated agricultural sectors just might have more in common than meets the eye. It's like the old joke – why did the scarecrow win an award? Because he was outstanding in his field.
As we delve into the data, we find ourselves navigating through uncharted territory, like explorers in a strange new world of statistical analysis. Our study does more than just scratch the surface; it unearths compelling evidence of a strong relationship between the cultivation of GMO cotton in Louisiana and the spending habits of households across the entire United States when it comes to processed fruits. It's as if these agricultural phenomena are engaged in a delicate waltz, with each influencing the other in a complex and elegant symphony of economic interconnectedness.
And just like a chef adding the perfect dash of seasoning to a dish, our research adds a pinch of zest to the academic conversation surrounding consumer behavior and agricultural production. The findings of our study challenge traditional assumptions, demonstrating that the roots of consumer spending habits may extend far beyond the confines of regional borders. As we peel back the layers of this correlation, it becomes increasingly clear that the relationship between GMO cultivation and processed fruit spending is not just a fruitless endeavor – pardon the pun – but rather a branch of inquiry ripe for further exploration.
So, when it comes to understanding the economic dance between GMOs and processed fruits, our research serves as a fruitful addition to the scholarly banquet. With these findings, it's safe to say that this paper isn't just another fruitless pursuit – it's a fruitful one.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Previous research has delved into the intricate relationship between agricultural practices and consumer behavior, shedding light on the factors influencing household spending on processed fruits and the impact of genetically modified organisms (GMOs) in agricultural production. In "Smith," the authors find that GMO cultivation has prompted a shift in consumer preferences towards organic and non-GMO products, creating a ripple effect in the market. Similarly, "Doe" highlights the potential environmental consequences of widespread GMO adoption, emphasizing the need for thorough examination of its impact on consumer choices.

But let's not get too serious here, folks. This topic isn't all apples and oranges. In "Jones," the authors dig deeper into the societal implications of GMO usage, pitting advocates and critics against each other in a debate that's as juicy as a ripe watermelon on a summer day. Now, that's one way to make a splash in academia.

When we flip through the pages of non-fiction works related to agricultural economics, we encounter titles like "Food Politics" by Marion Nestle and "The Omnivore's Dilemma" by Michael Pollan. These books provide a fruitful backdrop for understanding the complex dynamics of consumer behavior and agricultural production. They're like the supporting actors in a blockbuster movie – essential to the plot but not stealing the show.

As we tiptoe along the edge of the plausible and the preposterous, let's not forget the fictitious works that might, in some alternate universe, shed light on the connection at hand. Imagine a world where "The Cotton Chronicles" by Agatha Seedley and "GMOs and Gumdrops" by Ernest Peaches are regarded as serious academic texts. It's a whimsical thought, isn't it? It's as if we're meandering through the produce aisle of literary imagination.

And just when you thought we were firmly rooted in the realm of rigorous scholarly inquiry, let me drop a bombshell – we conducted a cutting-edge analysis of CVS receipts to uncover insights into consumer spending habits on processed fruits. Yes, you read that right. We scoured through countless receipts, deciphering the cryptic codes of fruit snacks and dried mango purchases, all in the name of academic pursuit. It's the kind of outlandish approach that could only be justified by the pursuit of knowledge – or a very intense craving for dried apricots.

With a wide array of literature providing a kaleidoscope of perspectives, our research seeks to plant the seeds of understanding in the fertile soil of interdisciplinary inquiry. As we harvest the fruits of our labor, we hope to cultivate a deeper appreciation for the interconnectedness of seemingly disparate facets of the agricultural and consumer landscape.

In the words of the great philosopher Plato, "The first and greatest victory is to conquer yourself; to be conquered by yourself is of all things most shameful and vile." Okay, that quote has absolutely nothing to do with our topic, but it's a classic dad joke move to throw in a completely unrelated quote, right?

Stay tuned, dear readers, as we venture further into the tangled vines of GMO cotton and the bountiful orchards of processed fruit spending. It's going to be a wild ride – like a rollercoaster made entirely of cornstalks and banana peels.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 US household spending on processed fruits and GMO use in cotton in Louisiana. 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 Bureau of Labor Statistics and USDA . You used data from 2000 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]]
Feeling Ginned Up: The Cotton Connection Between GMOs and Processed Fruit Spending in US Households

[[ABSTRACT]]
In this study, we peel back the layers of the relationship between US household spending on processed fruits and the use of genetically modified organisms (GMOs) in cotton production in Louisiana. Using data from the Bureau of Labor Statistics and USDA, we conducted a thorough analysis to explore the potential link between these seemingly disparate elements. Like a banana at a party, we aim to appeal to both the serious and the quirky sides of academia.

Our findings revealed a pear-fectly ripe correlation coefficient of 0.9263976 and a statistically significant p-value of less than 0.01 for the years 2000 to 2022, shedding light on the strong association between GMO cotton cultivation in Louisiana and household expenditure on processed fruits across the US. The results indicate that as GMO cotton production in Louisiana blooms, so does the spending on processed fruits by households nationwide. It's as if GMOs and processed fruits are engaging in a fruitful dance of economic interdependence.

Our research brings a unique flavor to the table by highlighting the unexplored connection between GMO cotton in one region and consumer choices in another. It seems that when it comes to household spending and agriculture, the seeds are sown more deeply than we previously thought. The findings of this study not only contribute to the understanding of consumer behavior and agricultural practices but also offer a refreshing perspective to the field of interdisciplinary research.

So, the next time someone questions the correlation between GMOs and processed fruit spending, you can confidently respond with, "That's just how the produce-pieces of the puzzle fit together!"

[[INTRODUCTION]]
In recent years, the intersection of agricultural practices and consumer behavior has garnered increasing attention from researchers and policymakers alike. As the global demand for processed fruits continues to grow, understanding the factors influencing household spending on these products has become a matter of significant importance. Likewise, the widespread adoption of genetically modified organisms (GMOs) in agricultural production has raised questions regarding its impact on both the environment and consumer choices. With this in mind, we set out to investigate the tantalizing relationship between US household spending on processed fruits and the use of GMOs in cotton production specifically in Louisiana.
It may seem like a stretch to draw a connection between cotton and cantaloupes, but our research aims to demonstrate that these seemingly unrelated agricultural sectors just might have more in common than meets the eye. It's like the old joke – why did the scarecrow win an award? Because he was outstanding in his field.
As we delve into the data, we find ourselves navigating through uncharted territory, like explorers in a strange new world of statistical analysis. Our study does more than just scratch the surface; it unearths compelling evidence of a strong relationship between the cultivation of GMO cotton in Louisiana and the spending habits of households across the entire United States when it comes to processed fruits. It's as if these agricultural phenomena are engaged in a delicate waltz, with each influencing the other in a complex and elegant symphony of economic interconnectedness.
And just like a chef adding the perfect dash of seasoning to a dish, our research adds a pinch of zest to the academic conversation surrounding consumer behavior and agricultural production. The findings of our study challenge traditional assumptions, demonstrating that the roots of consumer spending habits may extend far beyond the confines of regional borders. As we peel back the layers of this correlation, it becomes increasingly clear that the relationship between GMO cultivation and processed fruit spending is not just a fruitless endeavor – pardon the pun – but rather a branch of inquiry ripe for further exploration.
So, when it comes to understanding the economic dance between GMOs and processed fruits, our research serves as a fruitful addition to the scholarly banquet. With these findings, it's safe to say that this paper isn't just another fruitless pursuit – it's a fruitful one.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the intriguing connection between US household spending on processed fruits and the use of genetically modified organisms (GMOs) in cotton production in Louisiana, we employed a combination of quantitative data analysis and econometric modeling. Our dataset was primarily sourced from the Bureau of Labor Statistics and the United States Department of Agriculture (USDA), covering the years 2000 to 2022. It's as if we gathered our ingredients from the finest grocery stores, but instead of groceries, we shopped for data.

To begin, we conducted a thorough examination of the household expenditure patterns on processed fruits at the national level, utilizing detailed data on consumer spending habits. We then turned our attention to the cultivation of GMO cotton in Louisiana, delving into agricultural reports and regional production statistics. Think of it as peeling the layers of an onion – each data point revealing a new dimension to the complex relationship we sought to unravel.

As we toiled through the vast landscape of data, we employed a series of econometric models, including multivariate regression analysis, to assess the association between GMO cotton production in Louisiana and household spending on processed fruits across different regions of the United States. For the statistically inclined, this was our way of mixing and matching mathematical formulas to find the best fit for our data – it's like creating a recipe for correlation.

Our modeling approach also accounted for various control variables, such as income levels, demographic factors, and other relevant economic indicators, to ensure that the observed relationship between GMO cotton and processed fruit spending was not confounded by external factors. In a sense, we were like detectives unraveling a mystery, carefully eliminating potential red herrings to reveal the true underlying patterns in the data.

Furthermore, we conducted robustness tests and sensitivity analyses to validate the robustness of our findings and ensure that our results were not unduly influenced by outliers or unusual fluctuations in the data. We left no statistical stone unturned, meticulously validating our conclusions to ensure that they were as sturdy as a perfectly ripe watermelon.

In addition to quantitative analyses, we supplemented our research with qualitative insights from industry experts and agricultural stakeholders, gaining a more holistic understanding of the broader contextual factors that could potentially impact both GMO cotton production and household spending on processed fruits. It's as if we took a bite out of the knowledge apple, savoring the nuanced flavors of expertise and experience.

All data manipulations and statistical analyses were conducted using specialized software packages, including but not limited to SAS, R, and Stata. These tools served as our trusty sous chefs, assisting us in transforming raw data into meaningful insights with a sprinkle of statistical seasoning.

In summary, our methodology combined the rigor of quantitative analysis with the nuance of qualitative inquiry, providing a comprehensive exploration of the link between GMO cotton cultivation in Louisiana and US household spending on processed fruits. Just like a well-crafted dish, our research methodology blended precision with creativity, serving up a flavorful approach to unraveling the intricate dance between agriculture and consumer choices. It's not often you can combine cotton and cantaloupes in a research study, but here we are, breaking new ground in interdisciplinary exploration.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 US household spending on processed fruits and GMO use in cotton in Louisiana. 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 Bureau of Labor Statistics and USDA .

For the time period 2000 to 2022, you found a correlation 0.9263976, r-squared of 0.8582125, 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]]
Feeling Ginned Up: The Cotton Connection Between GMOs and Processed Fruit Spending in US Households

[[ABSTRACT]]
In this study, we peel back the layers of the relationship between US household spending on processed fruits and the use of genetically modified organisms (GMOs) in cotton production in Louisiana. Using data from the Bureau of Labor Statistics and USDA, we conducted a thorough analysis to explore the potential link between these seemingly disparate elements. Like a banana at a party, we aim to appeal to both the serious and the quirky sides of academia.

Our findings revealed a pear-fectly ripe correlation coefficient of 0.9263976 and a statistically significant p-value of less than 0.01 for the years 2000 to 2022, shedding light on the strong association between GMO cotton cultivation in Louisiana and household expenditure on processed fruits across the US. The results indicate that as GMO cotton production in Louisiana blooms, so does the spending on processed fruits by households nationwide. It's as if GMOs and processed fruits are engaging in a fruitful dance of economic interdependence.

Our research brings a unique flavor to the table by highlighting the unexplored connection between GMO cotton in one region and consumer choices in another. It seems that when it comes to household spending and agriculture, the seeds are sown more deeply than we previously thought. The findings of this study not only contribute to the understanding of consumer behavior and agricultural practices but also offer a refreshing perspective to the field of interdisciplinary research.

So, the next time someone questions the correlation between GMOs and processed fruit spending, you can confidently respond with, "That's just how the produce-pieces of the puzzle fit together!"

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In recent years, the intersection of agricultural practices and consumer behavior has garnered increasing attention from researchers and policymakers alike. As the global demand for processed fruits continues to grow, understanding the factors influencing household spending on these products has become a matter of significant importance. Likewise, the widespread adoption of genetically modified organisms (GMOs) in agricultural production has raised questions regarding its impact on both the environment and consumer choices. With this in mind, we set out to investigate the tantalizing relationship between US household spending on processed fruits and the use of GMOs in cotton production specifically in Louisiana.
It may seem like a stretch to draw a connection between cotton and cantaloupes, but our research aims to demonstrate that these seemingly unrelated agricultural sectors just might have more in common than meets the eye. It's like the old joke – why did the scarecrow win an award? Because he was outstanding in his field.
As we delve into the data, we find ourselves navigating through uncharted territory, like explorers in a strange new world of statistical analysis. Our study does more than just scratch the surface; it unearths compelling evidence of a strong relationship between the cultivation of GMO cotton in Louisiana and the spending habits of households across the entire United States when it comes to processed fruits. It's as if these agricultural phenomena are engaged in a delicate waltz, with each influencing the other in a complex and elegant symphony of economic interconnectedness.
And just like a chef adding the perfect dash of seasoning to a dish, our research adds a pinch of zest to the academic conversation surrounding consumer behavior and agricultural production. The findings of our study challenge traditional assumptions, demonstrating that the roots of consumer spending habits may extend far beyond the confines of regional borders. As we peel back the layers of this correlation, it becomes increasingly clear that the relationship between GMO cultivation and processed fruit spending is not just a fruitless endeavor – pardon the pun – but rather a branch of inquiry ripe for further exploration.
So, when it comes to understanding the economic dance between GMOs and processed fruits, our research serves as a fruitful addition to the scholarly banquet. With these findings, it's safe to say that this paper isn't just another fruitless pursuit – it's a fruitful one.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The results of our analysis revealed a strikingly strong correlation between US household spending on processed fruits and the use of genetically modified organisms (GMOs) in cotton production in Louisiana. The correlation coefficient of 0.9263976 indicates a robust positive relationship between these two variables. It's almost as if GMOs and processed fruits have formed a fruitful partnership, showing that even in the world of economics, it takes two to mango. This correlation coefficient is akin to finding the perfect avocado – pleasantly surprising and undeniably satisfying.

Moreover, the calculated r-squared value of 0.8582125 suggests that approximately 85.82% of the variation in household spending on processed fruits can be explained by the variation in GMO cotton production in Louisiana. This finding underscores the substantial influence of GMO cotton cultivation in Louisiana on consumer choices in the processed fruit market across the United States. It's as if the GMO cotton fields in Louisiana have cast a wide net, reeling in consumer spending habits from all corners of the country.

The statistical significance of the relationship is further supported by the p-value of less than 0.01, indicating that the observed correlation is unlikely to have occurred by mere chance. This remarkably low p-value strengthens the case for a meaningful and impactful association between GMO cotton cultivation in Louisiana and household expenditure on processed fruits at the national level. It's as if these variables are in a GMO-processed fruits relationship "like peas in a pod," inseparable and deeply interconnected.

In summary, these results provide compelling evidence of a substantial and noteworthy correlation between GMO cotton production in Louisiana and US household spending on processed fruits. This intricate relationship goes to show that when it comes to economic interactions, even the most unexpected pairings can bear fruit – or in this case, processed fruit. This study's findings not only add a new dimension to the understanding of consumer behavior and agricultural practices but also inject a refreshing flavor into the often dry discourse of economic analysis.

The figure (Fig. 1) in the paper visually represents the strong correlation between US household spending on processed fruits and GMO cotton production in Louisiana during the period under study, further cementing the robustness of our findings. It's almost as if this correlation is as clear as black and white – or in this case, as clear as the relationship between GMOs and processed fruits.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 US household spending on processed fruits and GMO use in cotton in Louisiana. 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]]
Feeling Ginned Up: The Cotton Connection Between GMOs and Processed Fruit Spending in US Households

[[ABSTRACT]]
In this study, we peel back the layers of the relationship between US household spending on processed fruits and the use of genetically modified organisms (GMOs) in cotton production in Louisiana. Using data from the Bureau of Labor Statistics and USDA, we conducted a thorough analysis to explore the potential link between these seemingly disparate elements. Like a banana at a party, we aim to appeal to both the serious and the quirky sides of academia.

Our findings revealed a pear-fectly ripe correlation coefficient of 0.9263976 and a statistically significant p-value of less than 0.01 for the years 2000 to 2022, shedding light on the strong association between GMO cotton cultivation in Louisiana and household expenditure on processed fruits across the US. The results indicate that as GMO cotton production in Louisiana blooms, so does the spending on processed fruits by households nationwide. It's as if GMOs and processed fruits are engaging in a fruitful dance of economic interdependence.

Our research brings a unique flavor to the table by highlighting the unexplored connection between GMO cotton in one region and consumer choices in another. It seems that when it comes to household spending and agriculture, the seeds are sown more deeply than we previously thought. The findings of this study not only contribute to the understanding of consumer behavior and agricultural practices but also offer a refreshing perspective to the field of interdisciplinary research.

So, the next time someone questions the correlation between GMOs and processed fruit spending, you can confidently respond with, "That's just how the produce-pieces of the puzzle fit together!"

[[LITERATURE REVIEW]]
Previous research has delved into the intricate relationship between agricultural practices and consumer behavior, shedding light on the factors influencing household spending on processed fruits and the impact of genetically modified organisms (GMOs) in agricultural production. In "Smith," the authors find that GMO cultivation has prompted a shift in consumer preferences towards organic and non-GMO products, creating a ripple effect in the market. Similarly, "Doe" highlights the potential environmental consequences of widespread GMO adoption, emphasizing the need for thorough examination of its impact on consumer choices.
But let's not get too serious here, folks. This topic isn't all apples and oranges. In "Jones," the authors dig deeper into the societal implications of GMO usage, pitting advocates and critics against each other in a debate that's as juicy as a ripe watermelon on a summer day. Now, that's one way to make a splash in academia.
When we flip through the pages of non-fiction works related to agricultural economics, we encounter titles like "Food Politics" by Marion Nestle and "The Omnivore's Dilemma" by Michael Pollan. These books provide a fruitful backdrop for understanding the complex dynamics of consumer behavior and agricultural production. They're like the supporting actors in a blockbuster movie – essential to the plot but not stealing the show.
As we tiptoe along the edge of the plausible and the preposterous, let's not forget the fictitious works that might, in some alternate universe, shed light on the connection at hand. Imagine a world where "The Cotton Chronicles" by Agatha Seedley and "GMOs and Gumdrops" by Ernest Peaches are regarded as serious academic texts. It's a whimsical thought, isn't it? It's as if we're meandering through the produce aisle of literary imagination.
And just when you thought we were firmly rooted in the realm of rigorous scholarly inquiry, let me drop a bombshell – we conducted a cutting-edge analysis of CVS receipts to uncover insights into consumer spending habits on processed fruits. Yes, you read that right. We scoured through countless receipts, deciphering the cryptic codes of fruit snacks and dried mango purchases, all in the name of academic pursuit. It's the kind of outlandish approach that could only be justified by the pursuit of knowledge – or a very intense craving for dried apricots.
With a wide array of literature providing a kaleidoscope of perspectives, our research seeks to plant the seeds of understanding in the fertile soil of interdisciplinary inquiry. As we harvest the fruits of our labor, we hope to cultivate a deeper appreciation for the interconnectedness of seemingly disparate facets of the agricultural and consumer landscape.
In the words of the great philosopher Plato, "The first and greatest victory is to conquer yourself; to be conquered by yourself is of all things most shameful and vile." Okay, that quote has absolutely nothing to do with our topic, but it's a classic dad joke move to throw in a completely unrelated quote, right?
Stay tuned, dear readers, as we venture further into the tangled vines of GMO cotton and the bountiful orchards of processed fruit spending. It's going to be a wild ride – like a rollercoaster made entirely of cornstalks and banana peels.

[[RESULTS]]
The results of our analysis revealed a strikingly strong correlation between US household spending on processed fruits and the use of genetically modified organisms (GMOs) in cotton production in Louisiana. The correlation coefficient of 0.9263976 indicates a robust positive relationship between these two variables. It's almost as if GMOs and processed fruits have formed a fruitful partnership, showing that even in the world of economics, it takes two to mango. This correlation coefficient is akin to finding the perfect avocado – pleasantly surprising and undeniably satisfying.
Moreover, the calculated r-squared value of 0.8582125 suggests that approximately 85.82% of the variation in household spending on processed fruits can be explained by the variation in GMO cotton production in Louisiana. This finding underscores the substantial influence of GMO cotton cultivation in Louisiana on consumer choices in the processed fruit market across the United States. It's as if the GMO cotton fields in Louisiana have cast a wide net, reeling in consumer spending habits from all corners of the country.
The statistical significance of the relationship is further supported by the p-value of less than 0.01, indicating that the observed correlation is unlikely to have occurred by mere chance. This remarkably low p-value strengthens the case for a meaningful and impactful association between GMO cotton cultivation in Louisiana and household expenditure on processed fruits at the national level. It's as if these variables are in a GMO-processed fruits relationship "like peas in a pod," inseparable and deeply interconnected.
In summary, these results provide compelling evidence of a substantial and noteworthy correlation between GMO cotton production in Louisiana and US household spending on processed fruits. This intricate relationship goes to show that when it comes to economic interactions, even the most unexpected pairings can bear fruit – or in this case, processed fruit. This study's findings not only add a new dimension to the understanding of consumer behavior and agricultural practices but also inject a refreshing flavor into the often dry discourse of economic analysis.
The figure (Fig. 1) in the paper visually represents the strong correlation between US household spending on processed fruits and GMO cotton production in Louisiana during the period under study, further cementing the robustness of our findings. It's almost as if this correlation is as clear as black and white – or in this case, as clear as the relationship between GMOs and processed fruits.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study unequivocally endorse the prior literature's assertions regarding the intricate relationship between agricultural practices and consumer behavior. The research conducted by "Smith" and "Doe" laid the breadcrumbs for our investigation, and it seems we've followed them to a fruitful destination. The correlation we uncovered between GMO cotton cultivation in Louisiana and household expenditure on processed fruits aligns with the notion that changes in agricultural production can indeed influence consumer spending habits. It's a bit like finding a hidden banana in a bunch – the connection was there all along, waiting to be revealed.

Additionally, our findings resonate with the offbeat perspectives offered in "Jones," underlining the impactful implications of GMO usage. While the debate around GMOs can be as divided as a sliced cantaloupe, our results suggest that its influence extends beyond the agricultural realm, permeating into the realm of consumer choices.

The surprising correlation coefficient of 0.9263976 and the eye-popping p-value of less than 0.01 conspire to affirm the significance of the relationship we observed. It's a bit like discovering that behind the curtain of simplistic consumer spending lies a complex tango between GMO cotton and processed fruits. The r-squared value of 0.8582125 further corroborates the robustness of this interplay, capturing approximately 85.82% of the symphony of variation in household spending on processed fruits.

As we continue to dissect the roots of this correlation, the emerging narrative points to a symbiotic relationship between GMO cotton in Louisiana and processed fruit spending across the US. It's as if these two seemingly unrelated elements have formed an unexpected alliance, akin to a comedy duo that no one saw coming – GMOs and processed fruits, the unlikeliest of partners in economic ballet.

The statistical significance of our findings resonates like a punchline in a serious conversation, highlighting the surprising interconnectedness of GMO cotton production in Louisiana and nationwide consumer choices in the processed fruit market. It's as if this relationship is a well-crafted joke – seemingly unlikely at first glance, but undeniably impactful once revealed.

In essence, our study's results lend weight to the notion that agricultural practices, particularly the use of GMOs, can cast a wide net of influence on consumer spending behaviors. Like a crisp apple in a sea of produce, our research serves as a fresh addition to the expanding canvas of interdisciplinary inquiry, combining the fields of agricultural economics and consumer behavior in unexpected harmony. We've managed to show that in the garden of economic analysis, even the most curious pairings can yield ripe and insightful results.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 US household spending on processed fruits and GMO use in cotton in Louisiana. 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]]
Feeling Ginned Up: The Cotton Connection Between GMOs and Processed Fruit Spending in US Households

[[ABSTRACT]]
In this study, we peel back the layers of the relationship between US household spending on processed fruits and the use of genetically modified organisms (GMOs) in cotton production in Louisiana. Using data from the Bureau of Labor Statistics and USDA, we conducted a thorough analysis to explore the potential link between these seemingly disparate elements. Like a banana at a party, we aim to appeal to both the serious and the quirky sides of academia.

Our findings revealed a pear-fectly ripe correlation coefficient of 0.9263976 and a statistically significant p-value of less than 0.01 for the years 2000 to 2022, shedding light on the strong association between GMO cotton cultivation in Louisiana and household expenditure on processed fruits across the US. The results indicate that as GMO cotton production in Louisiana blooms, so does the spending on processed fruits by households nationwide. It's as if GMOs and processed fruits are engaging in a fruitful dance of economic interdependence.

Our research brings a unique flavor to the table by highlighting the unexplored connection between GMO cotton in one region and consumer choices in another. It seems that when it comes to household spending and agriculture, the seeds are sown more deeply than we previously thought. The findings of this study not only contribute to the understanding of consumer behavior and agricultural practices but also offer a refreshing perspective to the field of interdisciplinary research.

So, the next time someone questions the correlation between GMOs and processed fruit spending, you can confidently respond with, "That's just how the produce-pieces of the puzzle fit together!"

[[INTRDUCTION]]
In recent years, the intersection of agricultural practices and consumer behavior has garnered increasing attention from researchers and policymakers alike. As the global demand for processed fruits continues to grow, understanding the factors influencing household spending on these products has become a matter of significant importance. Likewise, the widespread adoption of genetically modified organisms (GMOs) in agricultural production has raised questions regarding its impact on both the environment and consumer choices. With this in mind, we set out to investigate the tantalizing relationship between US household spending on processed fruits and the use of GMOs in cotton production specifically in Louisiana.
It may seem like a stretch to draw a connection between cotton and cantaloupes, but our research aims to demonstrate that these seemingly unrelated agricultural sectors just might have more in common than meets the eye. It's like the old joke – why did the scarecrow win an award? Because he was outstanding in his field.
As we delve into the data, we find ourselves navigating through uncharted territory, like explorers in a strange new world of statistical analysis. Our study does more than just scratch the surface; it unearths compelling evidence of a strong relationship between the cultivation of GMO cotton in Louisiana and the spending habits of households across the entire United States when it comes to processed fruits. It's as if these agricultural phenomena are engaged in a delicate waltz, with each influencing the other in a complex and elegant symphony of economic interconnectedness.
And just like a chef adding the perfect dash of seasoning to a dish, our research adds a pinch of zest to the academic conversation surrounding consumer behavior and agricultural production. The findings of our study challenge traditional assumptions, demonstrating that the roots of consumer spending habits may extend far beyond the confines of regional borders. As we peel back the layers of this correlation, it becomes increasingly clear that the relationship between GMO cultivation and processed fruit spending is not just a fruitless endeavor – pardon the pun – but rather a branch of inquiry ripe for further exploration.
So, when it comes to understanding the economic dance between GMOs and processed fruits, our research serves as a fruitful addition to the scholarly banquet. With these findings, it's safe to say that this paper isn't just another fruitless pursuit – it's a fruitful one.

[[RESULTS]]
The results of our analysis revealed a strikingly strong correlation between US household spending on processed fruits and the use of genetically modified organisms (GMOs) in cotton production in Louisiana. The correlation coefficient of 0.9263976 indicates a robust positive relationship between these two variables. It's almost as if GMOs and processed fruits have formed a fruitful partnership, showing that even in the world of economics, it takes two to mango. This correlation coefficient is akin to finding the perfect avocado – pleasantly surprising and undeniably satisfying.
Moreover, the calculated r-squared value of 0.8582125 suggests that approximately 85.82% of the variation in household spending on processed fruits can be explained by the variation in GMO cotton production in Louisiana. This finding underscores the substantial influence of GMO cotton cultivation in Louisiana on consumer choices in the processed fruit market across the United States. It's as if the GMO cotton fields in Louisiana have cast a wide net, reeling in consumer spending habits from all corners of the country.
The statistical significance of the relationship is further supported by the p-value of less than 0.01, indicating that the observed correlation is unlikely to have occurred by mere chance. This remarkably low p-value strengthens the case for a meaningful and impactful association between GMO cotton cultivation in Louisiana and household expenditure on processed fruits at the national level. It's as if these variables are in a GMO-processed fruits relationship "like peas in a pod," inseparable and deeply interconnected.
In summary, these results provide compelling evidence of a substantial and noteworthy correlation between GMO cotton production in Louisiana and US household spending on processed fruits. This intricate relationship goes to show that when it comes to economic interactions, even the most unexpected pairings can bear fruit – or in this case, processed fruit. This study's findings not only add a new dimension to the understanding of consumer behavior and agricultural practices but also inject a refreshing flavor into the often dry discourse of economic analysis.
The figure (Fig. 1) in the paper visually represents the strong correlation between US household spending on processed fruits and GMO cotton production in Louisiana during the period under study, further cementing the robustness of our findings. It's almost as if this correlation is as clear as black and white – or in this case, as clear as the relationship between GMOs and processed fruits.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has uncovered a fruitful relationship between US household spending on processed fruits and the use of genetically modified organisms (GMOs) in cotton production in Louisiana. The pear-fectly ripe correlation coefficient and the remarkably low p-value sow the seeds of a convincing association, highlighting the banana-nas of an unexpected duo – GMOs and processed fruits. It's almost as if they've formed a berry special bond!

The implications of these findings stretch further than a grapevine, demonstrating the interconnectedness of seemingly disparate agricultural sectors and consumer choices. In the economic dance between GMOs and processed fruits, it takes two to tango, and our research has shed light on this bountiful partnership. It's a relationship as strong as the stem of an apple, firmly rooted in statistical significance.

The striking correlation we've uncovered is as clear as day, or rather, as clear as the apple-seed relationship between GMO cotton production in Louisiana and household expenditure on processed fruits at the national level. Our study has peeled back the layers of this correlation, showing that it's not just a fruitless endeavor – indeed, it's ripe for further exploration.

Therefore, it's safe to say that this research is the apple of our eye, providing both food for thought and a-maize-ing insights into the delicate interplay between agricultural practices and consumer behavior. No further research is needed in this area; we've squeezed out all the juice from this lemon!

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 Feeling Ginned Up: The Cotton Connection Between GMOs and Processed Fruit Spending in US Households. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Agricultural Comedic Studies

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 Feeling Ginned Up: The Cotton Connection Between GMOs and Processed Fruit Spending in US Households. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Agricultural Innovation and Consumer Behavior

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 Feeling Ginned Up: The Cotton Connection Between GMOs and Processed Fruit Spending in US Households with an abstract of In this study, we peel back the layers of the relationship between US household spending on processed fruits and the use of genetically modified organisms (GMOs) in cotton production in Louisiana. Using data from the Bureau of Labor Statistics and USDA, we conducted a thorough analysis to explore the potential link between these seemingly disparate elements. Like a banana at a party, we aim to appeal to both the serious and the quirky sides of academia.
Our findings revealed a pear-fectly ripe correlation coefficient of 0.9263976 and a statistically significant p-value of less than 0.01 for the years 2000 to 2022, shedding light on the strong association between GMO cotton cultivation in Louisiana and household expenditure on processed fruits across the US. The results indicate that as GMO cotton production in Louisiana blooms, so does the spending on processed fruits by households nationwide. It's as if GMOs and processed fruits are engaging in a fruitful dance of economic interdependence.
Our research brings a unique flavor to the table by highlighting the unexplored connection between GMO cotton in one region and consumer choices in another. It seems that when it comes to household spending and agriculture, the seeds are sown more deeply than we previously thought. The findings of this study not only contribute to the understanding of consumer behavior and agricultural practices but also offer a refreshing perspective to the field of interdisciplinary research.
So, the next time someone questions the correlation between GMOs and processed fruit spending, you can confidently respond with, "That's just how the produce-pieces of the puzzle fit together!

ChatGPT:

GMO cotton, processed fruit spending, US households, Louisiana cotton production, correlation coefficient, genetic modification, consumer behavior, agricultural practices

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

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Data details

US household spending on processed fruits
Detailed data title: Annual US household spend on processed fruits, as a percentage of total household spend
Source: Bureau of Labor Statistics
See what else correlates with US household spending on processed fruits

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

Correlation r = 0.9263976 (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 = 0.8582125 (Coefficient of determination)
This means 85.8% of the change in the one variable (i.e., GMO use in cotton in Louisiana) is predictable based on the change in the other (i.e., US household spending on processed fruits) over the 23 years from 2000 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.3E-10.^Show 0.0000000002280302444803929000
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 0.93 in 2.3E-8% of random cases. Said differently, if you correlated 4,385,383,186 random variables^Note You don't actually need 4 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 22 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 22 because we have two variables measured over a period of 23 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.

[ 0.83, 0.97 ] 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.

	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
US household spending on processed fruits (Household spend)	0.302274	0.293537	0.285173	0.264596	0.253485	0.228404	0.225207	0.225634	0.229767	0.240488	0.234883	0.233377	0.221609	0.225049	0.203757	0.192933	0.19019	0.18648	0.186201	0.177676	0.203802	0.198721	0.197349
GMO use in cotton in Louisiana (GMO cotton %)	37	30	27	30	26	21	13	17	19	20	19	26	24	19	4	5	10	4	3	3	7	10	6

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.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

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([0.302274,0.293537,0.285173,0.264596,0.253485,0.228404,0.225207,0.225634,0.229767,0.240488,0.234883,0.233377,0.221609,0.225049,0.203757,0.192933,0.19019,0.18648,0.186201,0.177676,0.203802,0.198721,0.197349,])
array_2 = np.array([37,30,27,30,26,21,13,17,19,20,19,26,24,19,4,5,10,4,3,3,7,10,6,])
array_1_name = "US household spending on processed fruits"
array_2_name = "GMO use in cotton 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)

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
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only US household spending on processed fruits
Line chart for only GMO use in cotton in Louisiana
AI-generated correlation image
The spurious research paper: Feeling Ginned Up: The Cotton Connection Between GMOs and Processed Fruit Spending in US Households

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Correlation ID: 2848 · Black Variable ID: 19958 · Red Variable ID: 771


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