Spurious correlation #2,658 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Global Rice Consumption and the second variable is Brookfield's stock price (BN). The chart goes from 2009 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 Global Rice Consumption and the second variable is Brookfield's stock price (BN). The chart goes from 2009 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As Global Rice Consumption rose, more people became invested in rice production and distribution. This created a stir in the market, leading to a grain of confidence in companies like Brookfield, ultimately causing their stock price to rice up.

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Generate an image of a cyberpunk-infused marketplace filled with people from around the world. In a corner, a large sign displays the rising global rice consumption, while a massive banner with Brookfield's logo hangs above a stand where people eagerly buy and sell shares. The marketplace's bustling energy reflects the ascending stock price of Brookfield, as investors recognize its essential role in the world's grain consumption. 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: Global Rice Consumption and Brookfield's stock price (BN). 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: Celtic art inspired by bauhaus Charcoal Cyberpunk Cutsy art illustration
ChatGPT: Cyberpunk

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 Global Rice Consumption and Brookfield's stock price (BN), in the following situation: As global rice consumption rose, so did Brookfield's stock price. Investors realized that while rice may fill people's bellies, Brookfield's projects fill their pockets. The market saw the company as essential to the world's grain consumption, driving up its stock price.. Keep the description simple.
ChatGPT: A busy marketplace bustling with activity and people from all over the world. In one corner, there is a large sign displaying the rising global rice consumption. Meanwhile, a giant banner with Brookfield's logo is prominently displayed above a stand where people are eagerly buying and selling shares. The bustling energy of the marketplace reflects the ascending stock price of Brookfield, as investors recognize its essential role in the world's grain consumption.

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: [ Cyberpunk ] and depicting this scene: A busy marketplace bustling with activity and people from all over the world. In one corner, there is a large sign displaying the rising global rice consumption. Meanwhile, a giant banner with Brookfield's logo is prominently displayed above a stand where people are eagerly buying and selling shares. The bustling energy of the marketplace reflects the ascending stock price of Brookfield, as investors recognize its essential role in the world's grain consumption. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image of a cyberpunk-infused marketplace filled with people from around the world. In a corner, a large sign displays the rising global rice consumption, while a massive banner with Brookfield's logo hangs above a stand where people eagerly buy and sell shares. The marketplace's bustling energy reflects the ascending stock price of Brookfield, as investors recognize its essential role in the world's grain consumption.

*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 an increase in Global Rice Consumption caused Brookfield's stock price (BN) to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Rice Rage: Relationship between Global Rice Consumption and Brookfield's BN stock price

Journal of Culinary Economics and Financial Analysis

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 Global Rice Consumption and Brookfield's stock price (BN). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
Rice Rage: Relationship between Global Rice Consumption and Brookfield's BN stock price

[[ABSTRACT]]
In the world of finance, strange connections emerge, and in this study, we delve into the curious correlation between global rice consumption and the stock price of Brookfield (BN). Leveraging data from Statista and LSEG Analytics (Refinitiv), we dissect the relationship between these seemingly disparate entities. Our findings reveal a striking correlation coefficient of 0.8258724 and a p-value of less than 0.01 for the period spanning from 2009 to 2022.

We unravel this tangled web of rice and stocks, exploring possible explanations for this surprising connection. While the link may seem as out-of-place as a sushi bar in a financial district, our research aims to shed light on this unconventional relationship and its potential implications for both the rice and stock markets. Join us as we rice to the occasion and uncover the hidden flavors of this curious financial fusion.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
In the world of financial analysis, where numbers rule and correlations reign, it's not uncommon to stumble upon unexpected relationships between seemingly unrelated phenomena. The intertwined dance of supply, demand, and speculation often leads to peculiar connections that defy conventional wisdom.
Our study sets out to unravel one such enigmatic link, the connection between global rice consumption and the stock price of Brookfield (BN). Now, I know what you're thinking - what do rice and stocks have in common? Well, hold onto your grains, because we're about to dive into an intellectual stir-fry of statistical analysis and financial theory to uncover the truth behind this puzzling correlation.
Like a pair of mismatched socks or an equation that just doesn't add up, the relationship between rice consumption and stock prices raises eyebrows and invites skepticism. Yet, as diligent researchers armed with data from Statista and LSEG Analytics (Refinitiv), we dared to peel back the layers of this financial onion and examine the numbers behind the seemingly implausible connection.
The initial data analysis revealed a correlation coefficient of 0.8258724, sending ripples of astonishment through our research team. With a p-value of less than 0.01 for the period spanning from 2009 to 2022, we were left scratching our heads and reaching for our calculators in disbelief.
As we embark on this quixotic journey through the tangled vines of global rice consumption and the ever-fluctuating stock price of Brookfield, we must be prepared to confront the unexpected, the illogical, and the downright bizarre. So, buckle up, fellow researchers, for we are about to venture into uncharted waters - or should I say, uncharted paddy fields? As we sift through the grains of data, we will endeavor to separate the rice from the chaff and distill the essence of this perplexing relationship.
Our goal is not merely to decipher this unorthodox pairing, but to shed light on the potential implications that it holds for both the rice and stock markets. This study is more than just a statistical odyssey; it is an exploration of the intricate dance between human behavior, market forces, and the whims of global commerce. So, grab your calculators and leave your preconceptions at the door as we voyage into the realms of rice rage and stock market mystique.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

To begin our investigation into the peculiar connection between global rice consumption and the stock price of Brookfield (BN), we must first delve into the existing literature on this unorthodox pairing. While traditional economic theory may not have readily accounted for such an association, recent studies have begun to explore the intriguing intersection of food consumption and financial markets.

Smith et al. (2016) conducted a comprehensive analysis of agricultural commodities and their impact on stock market performance, delving into the potential influence of rice consumption on equity prices. Their findings hinted at the possibility of a nuanced relationship, piquing the curiosity of researchers and market analysts alike.

Building on this foundation, Doe and Jones (2018) surveyed global consumption patterns and their ripple effects on various sectors, including the financial industry. Although their study did not specifically focus on rice, it laid the groundwork for understanding the intricate web of interconnections that underpin market dynamics.

Shifting our focus from academic research to practical implications, the work of renowned economist John Keynes in "The General Theory of Employment, Interest, and Money" provides insights into the complexities of market behavior and the role of consumer spending. While Keynes may not have directly addressed the correlation between rice consumption and stock prices, his conceptual framework offers valuable perspectives on the broader forces at play in the financial domain.

In the realm of fiction, novels such as "Rice Fields and Wall Street" by Financial Fury offer a whimsical exploration of the symbiotic relationship between agricultural staples and high finance, albeit in a lighthearted and fictional context. While not grounded in empirical evidence, these imaginative narratives can inspire new avenues of inquiry and provoke unconventional thinking about the intertwining realms of rice and stocks.

Furthermore, it would be remiss not to acknowledge the internet's role in shaping contemporary discourse and meme culture. The now-iconic "Rice Guy" meme, which humorously juxtaposes rice-related scenarios with financial absurdity, serves as a light-hearted reminder of the widespread fascination with unconventional connections, regardless of their empirical validity. While memes may not offer scholarly insights, they reflect societal intrigue and curiosity around unexpected correlations, providing a touch of levity amidst the rigors of academic inquiry.

As we navigate this uncharted terrain of rice consumption and stock price dynamics, it is crucial to draw from a diverse array of sources, spanning academic rigor, literary imagination, and popular culture. In doing so, we can glean diverse perspectives and unearth new dimensions of this captivating conundrum.

With this eclectic foundation in mind, we proceed to analyze the empirical evidence and theoretical frameworks that will illuminate the mysterious interplay between global rice consumption and the stock performance of Brookfield (BN).

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 Global Rice Consumption and Brookfield's stock price (BN). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Statista and LSEG Analytics (Refinitiv) . You used data from 2009 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]]
Rice Rage: Relationship between Global Rice Consumption and Brookfield's BN stock price

[[ABSTRACT]]
In the world of finance, strange connections emerge, and in this study, we delve into the curious correlation between global rice consumption and the stock price of Brookfield (BN). Leveraging data from Statista and LSEG Analytics (Refinitiv), we dissect the relationship between these seemingly disparate entities. Our findings reveal a striking correlation coefficient of 0.8258724 and a p-value of less than 0.01 for the period spanning from 2009 to 2022.

We unravel this tangled web of rice and stocks, exploring possible explanations for this surprising connection. While the link may seem as out-of-place as a sushi bar in a financial district, our research aims to shed light on this unconventional relationship and its potential implications for both the rice and stock markets. Join us as we rice to the occasion and uncover the hidden flavors of this curious financial fusion.

[[INTRODUCTION]]
INTRODUCTION
In the world of financial analysis, where numbers rule and correlations reign, it's not uncommon to stumble upon unexpected relationships between seemingly unrelated phenomena. The intertwined dance of supply, demand, and speculation often leads to peculiar connections that defy conventional wisdom.
Our study sets out to unravel one such enigmatic link, the connection between global rice consumption and the stock price of Brookfield (BN). Now, I know what you're thinking - what do rice and stocks have in common? Well, hold onto your grains, because we're about to dive into an intellectual stir-fry of statistical analysis and financial theory to uncover the truth behind this puzzling correlation.
Like a pair of mismatched socks or an equation that just doesn't add up, the relationship between rice consumption and stock prices raises eyebrows and invites skepticism. Yet, as diligent researchers armed with data from Statista and LSEG Analytics (Refinitiv), we dared to peel back the layers of this financial onion and examine the numbers behind the seemingly implausible connection.
The initial data analysis revealed a correlation coefficient of 0.8258724, sending ripples of astonishment through our research team. With a p-value of less than 0.01 for the period spanning from 2009 to 2022, we were left scratching our heads and reaching for our calculators in disbelief.
As we embark on this quixotic journey through the tangled vines of global rice consumption and the ever-fluctuating stock price of Brookfield, we must be prepared to confront the unexpected, the illogical, and the downright bizarre. So, buckle up, fellow researchers, for we are about to venture into uncharted waters - or should I say, uncharted paddy fields? As we sift through the grains of data, we will endeavor to separate the rice from the chaff and distill the essence of this perplexing relationship.
Our goal is not merely to decipher this unorthodox pairing, but to shed light on the potential implications that it holds for both the rice and stock markets. This study is more than just a statistical odyssey; it is an exploration of the intricate dance between human behavior, market forces, and the whims of global commerce. So, grab your calculators and leave your preconceptions at the door as we voyage into the realms of rice rage and stock market mystique.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Our investigation into the perplexing nexus of rice consumption and Brookfield's stock price involved a multifaceted approach that was as complex as a Sudoku puzzle and as dynamic as a rollercoaster ride through statistical terrain. We adopted a retrospective observational design, tapping into data sources like Statista and LSEG Analytics (Refinitiv) to piece together the puzzle of this curious correlation.

Data Collection:
We scoured the vast expanse of the internet, rummaging through virtual shelves of statistics and financial data like a diligent bibliophile on the hunt for a rare comic book. Specifically, data on global rice consumption was sourced from Statista, while Brookfield's stock price data was procured from LSEG Analytics (Refinitiv). This period of investigation spanned from 2009 to 2022, a time frame akin to a marathon for data collectors but ultimately essential for capturing the ebbs and flows of both rice consumption and stock prices.

Variable Selection:
Just as a chef carefully selects the finest ingredients for a culinary masterpiece, we meticulously chose our variables to ensure a robust analysis. Global rice consumption was our independent variable, representing the aggregate demand for this staple crop across various regions. Meanwhile, Brookfield's stock price served as our dependent variable, embodying the capricious nature of financial markets and investor sentiment. Our decision to focus on these variables was not arbitrary; it was the fruit of countless deliberations and sleepless nights spent pondering the intricate interplay between grains and gains.

Statistical Analysis:
Employing rigorous statistical tools, we unleashed the full arsenal of parametric and non-parametric tests to scrutinize the relationship between global rice consumption and Brookfield's stock price. Our exploration included the calculation of the correlation coefficient, a measure of the strength and direction of the linear relationship between the two variables. We spared no effort in conducting regression analyses, time series modeling, and exploratory data analysis, treating our data with the kind of attention usually reserved for museum artifacts.

Assumptions and Limitations:
As with any scientific endeavor, our research was not immune to limitations and assumptions. The quality and reliability of the data from Statista and LSEG Analytics (Refinitiv) were pivotal but not infallible, akin to relying on a GPS in an uncharted territory. Additionally, while our findings showcased a robust correlation and p-value, we acknowledge the presence of potential confounding variables that we couldn't corral into our analysis. However, armed with statistical rigor and unwavering determination, we steered our ship through these choppy methodological waters with the hope of illuminating this enigmatic association.

In the words of renowned physicist Niels Bohr, "Prediction is very difficult, especially if it's about the future." With this sage advice in mind, we navigated the murky depths of data and statistics, resilient in our pursuit of unraveling the mystery of rice rage and stock market serendipity.

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 Global Rice Consumption and Brookfield's stock price (BN). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Rice Rage: Relationship between Global Rice Consumption and Brookfield's BN stock price

[[ABSTRACT]]
In the world of finance, strange connections emerge, and in this study, we delve into the curious correlation between global rice consumption and the stock price of Brookfield (BN). Leveraging data from Statista and LSEG Analytics (Refinitiv), we dissect the relationship between these seemingly disparate entities. Our findings reveal a striking correlation coefficient of 0.8258724 and a p-value of less than 0.01 for the period spanning from 2009 to 2022.

We unravel this tangled web of rice and stocks, exploring possible explanations for this surprising connection. While the link may seem as out-of-place as a sushi bar in a financial district, our research aims to shed light on this unconventional relationship and its potential implications for both the rice and stock markets. Join us as we rice to the occasion and uncover the hidden flavors of this curious financial fusion.

[[LITERATURE REVIEW]]
To begin our investigation into the peculiar connection between global rice consumption and the stock price of Brookfield (BN), we must first delve into the existing literature on this unorthodox pairing. While traditional economic theory may not have readily accounted for such an association, recent studies have begun to explore the intriguing intersection of food consumption and financial markets.
Smith et al. (2016) conducted a comprehensive analysis of agricultural commodities and their impact on stock market performance, delving into the potential influence of rice consumption on equity prices. Their findings hinted at the possibility of a nuanced relationship, piquing the curiosity of researchers and market analysts alike.
Building on this foundation, Doe and Jones (2018) surveyed global consumption patterns and their ripple effects on various sectors, including the financial industry. Although their study did not specifically focus on rice, it laid the groundwork for understanding the intricate web of interconnections that underpin market dynamics.
Shifting our focus from academic research to practical implications, the work of renowned economist John Keynes in "The General Theory of Employment, Interest, and Money" provides insights into the complexities of market behavior and the role of consumer spending. While Keynes may not have directly addressed the correlation between rice consumption and stock prices, his conceptual framework offers valuable perspectives on the broader forces at play in the financial domain.
In the realm of fiction, novels such as "Rice Fields and Wall Street" by Financial Fury offer a whimsical exploration of the symbiotic relationship between agricultural staples and high finance, albeit in a lighthearted and fictional context. While not grounded in empirical evidence, these imaginative narratives can inspire new avenues of inquiry and provoke unconventional thinking about the intertwining realms of rice and stocks.
Furthermore, it would be remiss not to acknowledge the internet's role in shaping contemporary discourse and meme culture. The now-iconic "Rice Guy" meme, which humorously juxtaposes rice-related scenarios with financial absurdity, serves as a light-hearted reminder of the widespread fascination with unconventional connections, regardless of their empirical validity. While memes may not offer scholarly insights, they reflect societal intrigue and curiosity around unexpected correlations, providing a touch of levity amidst the rigors of academic inquiry.
As we navigate this uncharted terrain of rice consumption and stock price dynamics, it is crucial to draw from a diverse array of sources, spanning academic rigor, literary imagination, and popular culture. In doing so, we can glean diverse perspectives and unearth new dimensions of this captivating conundrum.
With this eclectic foundation in mind, we proceed to analyze the empirical evidence and theoretical frameworks that will illuminate the mysterious interplay between global rice consumption and the stock performance of Brookfield (BN).

[[RESULTS]]
Our investigation into the peculiar relationship between global rice consumption and the stock price of Brookfield (BN) has yielded some captivating results. The correlation coefficient of 0.8258724 indicates a strong positive correlation between these seemingly unrelated variables. It's as if rice and stocks have formed a symbiotic relationship, like a classic pairing of wine and cheese or peanut butter and jelly, albeit in a financial context.
The r-squared value of 0.6820651 suggests that approximately 68.21% of the variation in BN stock price can be explained by changes in global rice consumption. It's like fitting a square peg into a round hole - surprisingly effective, yet leaving a bit of room for a grain of doubt.
Our findings also boast a p-value of less than 0.01, indicating that the observed correlation is highly unlikely to be a fluke. This result provides statistical support for the robustness of the relationship, as convincing as a magician pulling a rabbit out of a (rice) hat.
The evidence of this correlation is visually represented in Figure 1, a scatterplot that paints a clear picture of the strong positive relationship between these two variables. It's like a Jackson Pollock painting - seemingly chaotic at first glance, but upon closer inspection, a pattern emerges, revealing an unexpected beauty.
In the grand tapestry of financial data, our discovery of this correlation is akin to finding the elusive piece of the puzzle that ties together two seemingly unrelated sections, like a eureka moment in a labyrinth of numbers and graphs.
So there you have it - the perplexing yet undeniably robust link between global rice consumption and the stock price of Brookfield. While this relationship may seem as outlandish as a penguin in a desert, our results provide concrete evidence of its existence. Now, let's dig deeper and fry bigger fish (or more rice) in uncovering the underlying mechanisms driving this unlikely financial pas de deux.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our investigation into the enigmatic intertwining of global rice consumption and the stock price of Brookfield (BN) has brought us to a fertile ground of inquiry, revealing a correlation that is as surprising as finding a quinoa plant in a rice paddy. This correlation, with a coefficient of 0.8258724 and a p-value of less than 0.01, supports the speculations raised by Smith et al. (2016) regarding the potential impact of rice consumption on equity prices, giving their findings more backing than a supportive quinoa pillow.

It is fascinating to note how our results align with the offhand references in the literature review, including the whimsical novel "Rice Fields and Wall Street" by Financial Fury. While this work may have been more satirical in nature, it is palpable evidence of the popular fascination with unexpected correlations, akin to stumbling upon a hidden treasure in the convoluted network of financial data.

Furthermore, the robust r-squared value of 0.6820651 signals that a significant proportion of the variability in BN stock price can be attributed to changes in global rice consumption. This statistical tidbit serves as a testament to the impact of that humble grain, rice, on the stock market, in a manner as surprising as discovering a pearl in a sushi roll.

The strength of this relationship, as portrayed in the scatterplot (Figure 1), is as striking as a firm handshake between two unrelated acquaintances. It exhibits a clear and unmistakable pattern, much like the intricate dance of market forces and dietary habits, emphasizing the surprising bond between rice and stocks.

Our results echo the sentiments of Keynes' conceptual framework, shedding light on the overlooked influence of consumer spending habits, as unassuming as a grain of rice overlooked in a rice bowl. This robust correlation offers a quirky testament to the complexity of market dynamics and the influence of unconventional factors, proving that sometimes, the most compelling discoveries emerge from the unlikeliest of bedfellows.

As we endeavor to unravel the intricacies of this curious pairing, we are reminded of the enduring fascination with unconventional connections, exemplified in the "Rice Guy" meme. While humor may not be conventional in academic research, it provides a lighthearted reminder of the societal intrigue surrounding unexpected correlations, offering a sprinkle of levity in the rigorous empirical pursuit.

In essence, our findings not only confirm the existence of a strong link between global rice consumption and the stock price of Brookfield (BN) but also open the door to further explorations in this unique terrain of financial symbiosis. It's like finding a subtle but undeniable flavor in an unexpected dish, encouraging us to savor the complexity and richness of the entwined worlds of rice and stocks. Let's raise a toast with a bowl of rice to celebrate this unanticipated financial fusion and embark on further expeditions into this captivating conundrum.

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 Global Rice Consumption and Brookfield's stock price (BN). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Rice Rage: Relationship between Global Rice Consumption and Brookfield's BN stock price

[[ABSTRACT]]
In the world of finance, strange connections emerge, and in this study, we delve into the curious correlation between global rice consumption and the stock price of Brookfield (BN). Leveraging data from Statista and LSEG Analytics (Refinitiv), we dissect the relationship between these seemingly disparate entities. Our findings reveal a striking correlation coefficient of 0.8258724 and a p-value of less than 0.01 for the period spanning from 2009 to 2022.

We unravel this tangled web of rice and stocks, exploring possible explanations for this surprising connection. While the link may seem as out-of-place as a sushi bar in a financial district, our research aims to shed light on this unconventional relationship and its potential implications for both the rice and stock markets. Join us as we rice to the occasion and uncover the hidden flavors of this curious financial fusion.

[[INTRDUCTION]]
INTRODUCTION
In the world of financial analysis, where numbers rule and correlations reign, it's not uncommon to stumble upon unexpected relationships between seemingly unrelated phenomena. The intertwined dance of supply, demand, and speculation often leads to peculiar connections that defy conventional wisdom.
Our study sets out to unravel one such enigmatic link, the connection between global rice consumption and the stock price of Brookfield (BN). Now, I know what you're thinking - what do rice and stocks have in common? Well, hold onto your grains, because we're about to dive into an intellectual stir-fry of statistical analysis and financial theory to uncover the truth behind this puzzling correlation.
Like a pair of mismatched socks or an equation that just doesn't add up, the relationship between rice consumption and stock prices raises eyebrows and invites skepticism. Yet, as diligent researchers armed with data from Statista and LSEG Analytics (Refinitiv), we dared to peel back the layers of this financial onion and examine the numbers behind the seemingly implausible connection.
The initial data analysis revealed a correlation coefficient of 0.8258724, sending ripples of astonishment through our research team. With a p-value of less than 0.01 for the period spanning from 2009 to 2022, we were left scratching our heads and reaching for our calculators in disbelief.
As we embark on this quixotic journey through the tangled vines of global rice consumption and the ever-fluctuating stock price of Brookfield, we must be prepared to confront the unexpected, the illogical, and the downright bizarre. So, buckle up, fellow researchers, for we are about to venture into uncharted waters - or should I say, uncharted paddy fields? As we sift through the grains of data, we will endeavor to separate the rice from the chaff and distill the essence of this perplexing relationship.
Our goal is not merely to decipher this unorthodox pairing, but to shed light on the potential implications that it holds for both the rice and stock markets. This study is more than just a statistical odyssey; it is an exploration of the intricate dance between human behavior, market forces, and the whims of global commerce. So, grab your calculators and leave your preconceptions at the door as we voyage into the realms of rice rage and stock market mystique.

[[RESULTS]]
Our investigation into the peculiar relationship between global rice consumption and the stock price of Brookfield (BN) has yielded some captivating results. The correlation coefficient of 0.8258724 indicates a strong positive correlation between these seemingly unrelated variables. It's as if rice and stocks have formed a symbiotic relationship, like a classic pairing of wine and cheese or peanut butter and jelly, albeit in a financial context.
The r-squared value of 0.6820651 suggests that approximately 68.21% of the variation in BN stock price can be explained by changes in global rice consumption. It's like fitting a square peg into a round hole - surprisingly effective, yet leaving a bit of room for a grain of doubt.
Our findings also boast a p-value of less than 0.01, indicating that the observed correlation is highly unlikely to be a fluke. This result provides statistical support for the robustness of the relationship, as convincing as a magician pulling a rabbit out of a (rice) hat.
The evidence of this correlation is visually represented in Figure 1, a scatterplot that paints a clear picture of the strong positive relationship between these two variables. It's like a Jackson Pollock painting - seemingly chaotic at first glance, but upon closer inspection, a pattern emerges, revealing an unexpected beauty.
In the grand tapestry of financial data, our discovery of this correlation is akin to finding the elusive piece of the puzzle that ties together two seemingly unrelated sections, like a eureka moment in a labyrinth of numbers and graphs.
So there you have it - the perplexing yet undeniably robust link between global rice consumption and the stock price of Brookfield. While this relationship may seem as outlandish as a penguin in a desert, our results provide concrete evidence of its existence. Now, let's dig deeper and fry bigger fish (or more rice) in uncovering the underlying mechanisms driving this unlikely financial pas de deux.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has traversed the winding road of statistical analysis to unravel the enigmatic relationship between global rice consumption and the stock price of Brookfield (BN). It's safe to say that we've gone beyond the typical stock market stir-fry and entered uncharted financial territory. Our findings have served up a dish of surprises, demonstrating a strong positive correlation between these seemingly unrelated variables, akin to discovering a hidden (rice) treasure in the stock market's pantry.

The robustness of this connection, supported by a correlation coefficient of 0.8258724 and a p-value of less than 0.01, leaves little room for doubt. It's as clear as day, or perhaps as clear as a perfectly cooked bowl of rice. Our results are as solid as a basmati brick in the world of financial research, providing a legume-upon which future studies can build.

As we wrap up this culinary expedition into the realms of rice rage and stock market mystique, it's evident that this quirky correlation, though unexpected and perplexing, stands as a flavorful addition to the menu of financial knowledge. It's a bit like stumbling upon a fusion restaurant in the heart of Wall Street – unexpected, yet intriguing in its own right.

With such compelling evidence at hand, we boldly declare that no further research is needed in this area. We've cracked the code on this unconventional pairing, leaving future researchers with more time to tackle less seasoned financial puzzles. So, let's raise a glass of rice wine – or maybe just a bowl of steamed jasmine rice – to the fruitful findings of this study, and may our future endeavors in financial research be equally rich and satisfying.

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 Rice Rage: Relationship between Global Rice Consumption and Brookfield's BN stock price. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Culinary Economics and Financial Analysis

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 Rice Rage: Relationship between Global Rice Consumption and Brookfield's BN stock price. Respond only with the name of a fictional organization.

ChatGPT:

National Institute for Cereal Consumption Research

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 Rice Rage: Relationship between Global Rice Consumption and Brookfield's BN stock price with an abstract of In the world of finance, strange connections emerge, and in this study, we delve into the curious correlation between global rice consumption and the stock price of Brookfield (BN). Leveraging data from Statista and LSEG Analytics (Refinitiv), we dissect the relationship between these seemingly disparate entities. Our findings reveal a striking correlation coefficient of 0.8258724 and a p-value of less than 0.01 for the period spanning from 2009 to 2022.
We unravel this tangled web of rice and stocks, exploring possible explanations for this surprising connection. While the link may seem as out-of-place as a sushi bar in a financial district, our research aims to shed light on this unconventional relationship and its potential implications for both the rice and stock markets. Join us as we rice to the occasion and uncover the hidden flavors of this curious financial fusion.

ChatGPT:

"rice consumption", "global rice market", "Brookfield BN stock price", "finance and food correlation", "financial market analysis", "correlation coefficient", "p-value", "stock market trends", "statistical analysis", "LSEG Analytics", "Rice and stock market relationship", "rice consumption impact on stock price"

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

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Data details

Global Rice Consumption
Source: Statista
See what else correlates with Global Rice Consumption

Brookfield's stock price (BN)
Detailed data title: Opening price of Brookfield (BN) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: ^{See full details} Via Microsoft Excel Stockhistory function

See what else correlates with Brookfield's stock price (BN)

Correlation r = 0.8258724 (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 = 0.6820651 (Coefficient of determination)
This means 68.2% of the change in the one variable (i.e., Brookfield's stock price (BN)) is predictable based on the change in the other (i.e., Global Rice Consumption) over the 14 years from 2009 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00027.^Show 0.0002734522469898977600000000
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 0.83 in 0.027% of random cases. Said differently, if you correlated 3,657 random variables^Note Which I absolutely did.
with the same 13 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 13 because we have two variables measured over a period of 14 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.

[ 0.53, 0.94 ] 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.

	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Global Rice Consumption (Thousand Metric Tons)	437179	438338	445084	460825	462623	473878	474845	468882	483817	481678	485064	493953	503437	519895
Brookfield's stock price (BN) (Stock price)	12.32	18.46	27.25	22.74	30.35	31.54	40.76	25.29	26.96	35.47	30.89	47.17	33.43	49.19

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([437179,438338,445084,460825,462623,473878,474845,468882,483817,481678,485064,493953,503437,519895,])
array_2 = np.array([12.32,18.46,27.25,22.74,30.35,31.54,40.76,25.29,26.96,35.47,30.89,47.17,33.43,49.19,])
array_1_name = "Global Rice Consumption"
array_2_name = "Brookfield's stock price (BN)"

# 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 Global Rice Consumption
Line chart for only Brookfield's stock price (BN)
AI-generated correlation image
The spurious research paper: Rice Rage: Relationship between Global Rice Consumption and Brookfield's BN stock price

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Correlation ID: 2658 · Black Variable ID: 437 · Red Variable ID: 1706


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