Spurious correlation #3,384 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of Breweries in the United States and the second variable is Solar power generated in Peru. The chart goes from 2000 to 2021, 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 The number of Breweries in the United States and the second variable is Solar power generated in Peru. The chart goes from 2000 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of breweries in the United States increased, so did the demand for beer. This led to a surge in hop production, creating a need for more agricultural labor in Peru. With more people working outdoors, the Peruvian solar power industry experienced a boost in productivity from all the extra sunshine beer as the real power source!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a surreal landscape that blends the United States and Peru scenes in a Polaroid photo style. Create a vibrant, lush field of hops plants in the foreground, emitting a sweet, aromatic scent. The plants are thriving and cascading across the horizon, amplifying the sense of growth and prosperity. Integrate the image with a sun-drenched field of solar panels in the background, absorbing the intense rays of sunlight. The juxtaposition of the two scenes should convey a sense of harmony and interconnectedness, capturing the essence of sustainability and innovation. 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: The number of Breweries in the United States and Solar power generated in Peru. 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: Sci-fi fantacy Woodblock painting a Polaroid photo A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Symbolism
ChatGPT: a Polaroid photo

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 The number of Breweries in the United States and Solar power generated in Peru, in the following situation: Because as the number of breweries in the United States increased, so did the demand for beer. This led to an increase in hops production. Hops release a chemical that enhances the efficiency of solar panels, resulting in a boost in solar power generation in Peru.. Keep the description simple.
ChatGPT: In the United States, the number of breweries is on the rise, and we see an increasing demand for beer. As a result, hops production is flourishing. Fields of hops plants are vibrant, and the air is filled with the sweet scent of the blossoms. Meanwhile, in Peru, solar panels are soaking up the bright, sunny rays, generating a significant amount of solar power. The hop fields release a chemical that enhances the efficiency of the solar panels, contributing to an impressive boost in solar power generation.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ a Polaroid photo ] and depicting this scene: In the United States, the number of breweries is on the rise, and we see an increasing demand for beer. As a result, hops production is flourishing. Fields of hops plants are vibrant, and the air is filled with the sweet scent of the blossoms. Meanwhile, in Peru, solar panels are soaking up the bright, sunny rays, generating a significant amount of solar power. The hop fields release a chemical that enhances the efficiency of the solar panels, contributing to an impressive boost in solar power generation. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a surreal landscape that blends the United States and Peru scenes in a Polaroid photo style. Create a vibrant, lush field of hops plants in the foreground, emitting a sweet, aromatic scent. The plants are thriving and cascading across the horizon, amplifying the sense of growth and prosperity. Integrate the image with a sun-drenched field of solar panels in the background, absorbing the intense rays of sunlight. The juxtaposition of the two scenes should convey a sense of harmony and interconnectedness, capturing the essence of sustainability and innovation.

*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 The number of Breweries in the United States caused Solar power generated in Peru to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)

Brewing Up a Solar Storm: The Surprising Relationship Between U.S. Breweries and Solar Power Generation in Peru

Journal of Renewable Energy and Unconventional Partnerships

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 The number of Breweries in the United States and Solar power generated in Peru. 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 you might move on to cartoons and children's shows that you watched for research.

Here is the title and abstract of the paper:
[[TITLE]]
Brewing Up a Solar Storm: The Surprising Relationship Between U.S. Breweries and Solar Power Generation in Peru

[[ABSTRACT]]
In this study, we delve into the uncharted territory of the interplay between the number of breweries in the United States and the solar power generated in Peru. Despite initial skepticism from our peers and perhaps a few raised eyebrows, our research team meticulously collected and analyzed data from the Brewers Association and Energy Information Administration, covering the period from 2000 to 2021. Our findings revealed a remarkably strong correlation coefficient of 0.9783511 and a p-value of less than 0.01, demonstrating a strikingly robust relationship between these two seemingly disparate variables. As we navigate through this unexpected alliance between the craft beer industry and solar energy production, we invite the scientific community to raise a glass and ponder the implications of this lighthearted yet illuminating association.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Introduction
As we enter the realm of unconventional correlations and unexpected connections, our study embarks on a curious journey into the realm of sudsy libations and radiant energy. Brewing up a storm in the world of statistical analysis, we set out to explore the rather peculiar relationship between the number of breweries in the United States and the solar power generated in Peru.
At first glance, one might raise an eyebrow and wonder about the significance of these two variables. "Do breweries in the U.S. somehow influence solar power generation in Peru?" one might ask. Well, hold on to your beakers and alembics, because the results of our investigation might just brew up some surprising revelations.
The intersection of these seemingly unrelated entities raised more than a few puzzled looks during the initial stages of our research. However, armed with our trusty calculators, data spreadsheets, and a few well-timed quips, our team ventured forth undeterred into the statistical jungle.
Utilizing data from the Brewers Association and the Energy Information Administration spanning over two decades, we meticulously combed through the numbers, distilling the essence of these variables down to their statistical elements. We found ourselves knee-deep in numerical hops and solar wattage, endeavoring to uncover any glimmer of connection between these contrasting phenomena.
With a correlation coefficient of 0.9783511 and a p-value of less than 0.01, our findings pointed to a surprisingly sturdy relationship between the number of breweries popping up across the U.S. and the solar power illuminating the landscape of Peru. Amidst the brouhaha of bubbling fermentation and shimmering solar panels, a compelling correlation emerged, challenging conventional expectations and sparking curiosity among researchers and beer enthusiasts alike.
As we delve deeper into this brew-tiful alliance between the craft beer industry and solar energy production, we invite our colleagues in the scholarly community to join us in raising a glass, not only to toast this unexpected finding but also to contemplate the implications of this intriguing partnership. Let us raise our metaphorical flasks and ponder the unanticipated interplay between brews and rays, for in the world of statistics, as in life, sometimes the most delightful discoveries lie in the unlikeliest of pairings.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In the uncharted territory of peculiar correlations, our study traverses the landscape of scholarly works to shed light on the surprising relationship between the number of breweries in the United States and solar power generation in Peru. While this unusual pairing may seem far-fetched at first, it calls for a comprehensive exploration of existing literature and perspectives.

Smith (2015) offers a comprehensive analysis of the solar power dynamics in Peru, shedding light on the various factors influencing the country's solar energy production. Meanwhile, Doe (2017) delves into the exponential growth of breweries across the United States, providing valuable insights into the evolving landscape of craft beer in the nation.

Moving beyond the realm of scholarly articles, we turn our attention to non-fiction books that touch upon energy dynamics and the brewing industry. "Solar Power for Dummies" (Johnson, 2019) offers a beginner's guide to understanding solar energy, while "The Craft of Craft Beer" (Adams, 2018) provides a detailed exploration of the art and science behind brewing.

Venturing further into the literary world, we encounter fictional works that capture the essence of unexpected connections and whimsical pairings. In "The Sun Also Rises" (Hemingway, 1926), the interplay of light and shadow mirrors the juxtaposition of warm beer and radiant solar power, albeit in a more metaphorical sense. In a lighter vein, "Brewing Up a Storm" (Mortensen, 2013) paints a whimsical tale of a brewmaster who discovers a hidden link between his concoctions and the energy of the sun.

Not content with conventional sources, our research team delves into the realms of popular culture, drawing inspiration and insights from unlikely sources. As avid cartoon enthusiasts, we couldn't resist peeking into the world of "The Simpsons," where Homer Simpson's affinity for Duff Beer intersects with the occasional solar mishap, offering a lighthearted vantage point on the convergence of breweries and solar energy.

In the spirit of thorough investigation, we also explored children's shows that inadvertently shed light on our research topic. From "Bob the Builder" and his solar-powered construction equipment to the educational escapades of "Magic School Bus," wherein Ms. Frizzle unearths the interconnectedness of energy systems, our foray into cartoon and children's programming provided unexpected insights into the fusion of brewing and solar phenomena.

As we navigate through this eclectic array of literature, from scholarly works to whimsical tales and animated adventures, our quest for understanding the interplay between breweries and solar power continues to unveil unexpected connections and quirky perspectives.

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 The number of Breweries in the United States and Solar power generated in Peru. 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 Brewers Association and Energy Information Administration . You used data from 2000 to 2021

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]]
Brewing Up a Solar Storm: The Surprising Relationship Between U.S. Breweries and Solar Power Generation in Peru

[[ABSTRACT]]
In this study, we delve into the uncharted territory of the interplay between the number of breweries in the United States and the solar power generated in Peru. Despite initial skepticism from our peers and perhaps a few raised eyebrows, our research team meticulously collected and analyzed data from the Brewers Association and Energy Information Administration, covering the period from 2000 to 2021. Our findings revealed a remarkably strong correlation coefficient of 0.9783511 and a p-value of less than 0.01, demonstrating a strikingly robust relationship between these two seemingly disparate variables. As we navigate through this unexpected alliance between the craft beer industry and solar energy production, we invite the scientific community to raise a glass and ponder the implications of this lighthearted yet illuminating association.

[[INTRODUCTION]]
Introduction
As we enter the realm of unconventional correlations and unexpected connections, our study embarks on a curious journey into the realm of sudsy libations and radiant energy. Brewing up a storm in the world of statistical analysis, we set out to explore the rather peculiar relationship between the number of breweries in the United States and the solar power generated in Peru.
At first glance, one might raise an eyebrow and wonder about the significance of these two variables. "Do breweries in the U.S. somehow influence solar power generation in Peru?" one might ask. Well, hold on to your beakers and alembics, because the results of our investigation might just brew up some surprising revelations.
The intersection of these seemingly unrelated entities raised more than a few puzzled looks during the initial stages of our research. However, armed with our trusty calculators, data spreadsheets, and a few well-timed quips, our team ventured forth undeterred into the statistical jungle.
Utilizing data from the Brewers Association and the Energy Information Administration spanning over two decades, we meticulously combed through the numbers, distilling the essence of these variables down to their statistical elements. We found ourselves knee-deep in numerical hops and solar wattage, endeavoring to uncover any glimmer of connection between these contrasting phenomena.
With a correlation coefficient of 0.9783511 and a p-value of less than 0.01, our findings pointed to a surprisingly sturdy relationship between the number of breweries popping up across the U.S. and the solar power illuminating the landscape of Peru. Amidst the brouhaha of bubbling fermentation and shimmering solar panels, a compelling correlation emerged, challenging conventional expectations and sparking curiosity among researchers and beer enthusiasts alike.
As we delve deeper into this brew-tiful alliance between the craft beer industry and solar energy production, we invite our colleagues in the scholarly community to join us in raising a glass, not only to toast this unexpected finding but also to contemplate the implications of this intriguing partnership. Let us raise our metaphorical flasks and ponder the unanticipated interplay between brews and rays, for in the world of statistics, as in life, sometimes the most delightful discoveries lie in the unlikeliest of pairings.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The methodology employed in this study combined rigorous data collection and robust statistical analysis to unravel the intricate relationship between the number of breweries in the United States and the solar power generated in Peru. Our approach aimed to extract meaningful insights from disparate sources and distill them into a coherent narrative of correlation and causation.

Data Collection:
Our research team scoured the digital landscapes of the Brewers Association and the Energy Information Administration, meticulously harvesting data spanning the years 2000 to 2021. We tapped into the frothy reservoir of brewery statistics, sifting through the number of active breweries, production volumes, and geographical distribution across the expansive beer-scape of the United States. Simultaneously, we harnessed the radiant expanse of solar power data in Peru, capturing the wattage and geographic distribution of photovoltaic panels and solar arrays.

Experimental Design:
Embracing the whimsical essence of this endeavor, our experimental design drew inspiration from the art of mixology, blending elements of multivariate regression analysis and predictive modeling with a splash of speculative hypothesis testing. We embarked on a journey through the statistical stratosphere, tethered only by our unwavering dedication to uncovering the underlying patterns within our data.

Statistical Analysis:
Armed with an arsenal of statistical software and a liberal sprinkling of academic fervor, we conducted a series of analyses to unveil the hidden threads weaving the tapestry of brewing and solar power generation. The rich aroma of multivariate correlation analyses and robust linear modeling permeated our analytical enclave, as we sought to elucidate the nuanced interplay between these seemingly incongruous variables.

Novel Techniques:
As trailblazers in the realm of unexpected connections, we unleashed a curious melange of statistical techniques, encapsulating the essence of our unconventional pursuit. From unorthodox variable transformations to whimsical data visualization methods, our approach infused a spirit of exploration and whimsy into the hallowed halls of statistical inquiry. While adhering to the rigors of scientific inquiry, we left no statistical stone unturned, embracing the idiosyncrasies of our data with a twinkle in our analytical eyes.

Terrestrial and Celestial Alignment:
As we traversed the realm of statistical discovery, we couldn't help but notice the unusually cosmic alignment of our variables. While one might ponder the gravitational pull of brewing culture on solar energy production, we held steadfast in our commitment to unearthing tangible patterns within the labyrinthine corridors of statistical significance.

In delving into this lighthearted yet illuminating quest, our methodology reflects both the scholarly rigor and the hopeful whimsy that infuse our pursuit of knowledge. With each statistical maneuver and gleeful hypothesis, we waltzed through the hallowed halls of academia, propelled by the tantalizing prospect of unearthing a correlation born of unexpected harmony.

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 The number of Breweries in the United States and Solar power generated in Peru. 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 Brewers Association and Energy Information Administration .

For the time period 2000 to 2021, you found a correlation 0.9783511, r-squared of 0.9571708, 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]]
Brewing Up a Solar Storm: The Surprising Relationship Between U.S. Breweries and Solar Power Generation in Peru

[[ABSTRACT]]
In this study, we delve into the uncharted territory of the interplay between the number of breweries in the United States and the solar power generated in Peru. Despite initial skepticism from our peers and perhaps a few raised eyebrows, our research team meticulously collected and analyzed data from the Brewers Association and Energy Information Administration, covering the period from 2000 to 2021. Our findings revealed a remarkably strong correlation coefficient of 0.9783511 and a p-value of less than 0.01, demonstrating a strikingly robust relationship between these two seemingly disparate variables. As we navigate through this unexpected alliance between the craft beer industry and solar energy production, we invite the scientific community to raise a glass and ponder the implications of this lighthearted yet illuminating association.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Introduction
As we enter the realm of unconventional correlations and unexpected connections, our study embarks on a curious journey into the realm of sudsy libations and radiant energy. Brewing up a storm in the world of statistical analysis, we set out to explore the rather peculiar relationship between the number of breweries in the United States and the solar power generated in Peru.
At first glance, one might raise an eyebrow and wonder about the significance of these two variables. "Do breweries in the U.S. somehow influence solar power generation in Peru?" one might ask. Well, hold on to your beakers and alembics, because the results of our investigation might just brew up some surprising revelations.
The intersection of these seemingly unrelated entities raised more than a few puzzled looks during the initial stages of our research. However, armed with our trusty calculators, data spreadsheets, and a few well-timed quips, our team ventured forth undeterred into the statistical jungle.
Utilizing data from the Brewers Association and the Energy Information Administration spanning over two decades, we meticulously combed through the numbers, distilling the essence of these variables down to their statistical elements. We found ourselves knee-deep in numerical hops and solar wattage, endeavoring to uncover any glimmer of connection between these contrasting phenomena.
With a correlation coefficient of 0.9783511 and a p-value of less than 0.01, our findings pointed to a surprisingly sturdy relationship between the number of breweries popping up across the U.S. and the solar power illuminating the landscape of Peru. Amidst the brouhaha of bubbling fermentation and shimmering solar panels, a compelling correlation emerged, challenging conventional expectations and sparking curiosity among researchers and beer enthusiasts alike.
As we delve deeper into this brew-tiful alliance between the craft beer industry and solar energy production, we invite our colleagues in the scholarly community to join us in raising a glass, not only to toast this unexpected finding but also to contemplate the implications of this intriguing partnership. Let us raise our metaphorical flasks and ponder the unanticipated interplay between brews and rays, for in the world of statistics, as in life, sometimes the most delightful discoveries lie in the unlikeliest of pairings.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The results of our analysis revealed a striking correlation between the number of breweries in the United States and the solar power generated in Peru over the period from 2000 to 2021. We found a correlation coefficient of 0.9783511, indicating a remarkably strong relationship between these two variables. In layman's terms, it's as if every new brewery that popped up in the U.S. was accompanied by a surge in solar power beaming down on Peru, or vice versa.

The r-squared value of 0.9571708 further solidifies this connection, suggesting that a whopping 95.71% of the variability in solar power generation in Peru can be explained by the number of breweries in the U.S. That's right, almost 96% of the ups and downs in solar wattage across the Peruvian landscape could be predicted by simply keeping an eye on the ever-growing brewery count in the U.S. It's almost like the sun is saying, "Hey, you brew, I'll shine!"

Now, the p-value of less than 0.01 indicates that our findings are highly significant and not just a statistical fluke. This means that the likelihood of such a strong association occurring by random chance is less than 1 in 100. In other words, the probability of this correlation being a cosmic coincidence is about as likely as stumbling upon a unicorn sipping a cold one under a solar-powered rainbow.

To visually capture the magnitude of this unexpected relationship, we present Figure 1, a scatterplot demonstrating the robust correlation between the number of breweries in the U.S. and the solar power generated in Peru. The data points align so closely that it's as if they're harmonizing in a cosmic symphony, one brewing up a storm while the other basks in the sun's luminous applause.

These findings not only shed light on the intertwined nature of these variables but also invite further exploration into the whimsical ways in which seemingly unrelated phenomena can dance together in the statistical spotlight. As we savor the boundless possibilities unveiled by this curious correlation, we invite our peers to join us in pondering the unforeseen links that enliven the tapestry of scientific inquiry. Cheers to the delightful surprises that arise when we examine the world through the lens of data and discovery!

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 The number of Breweries in the United States and Solar power generated in Peru. 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]]
Brewing Up a Solar Storm: The Surprising Relationship Between U.S. Breweries and Solar Power Generation in Peru

[[ABSTRACT]]
In this study, we delve into the uncharted territory of the interplay between the number of breweries in the United States and the solar power generated in Peru. Despite initial skepticism from our peers and perhaps a few raised eyebrows, our research team meticulously collected and analyzed data from the Brewers Association and Energy Information Administration, covering the period from 2000 to 2021. Our findings revealed a remarkably strong correlation coefficient of 0.9783511 and a p-value of less than 0.01, demonstrating a strikingly robust relationship between these two seemingly disparate variables. As we navigate through this unexpected alliance between the craft beer industry and solar energy production, we invite the scientific community to raise a glass and ponder the implications of this lighthearted yet illuminating association.

[[LITERATURE REVIEW]]
In the uncharted territory of peculiar correlations, our study traverses the landscape of scholarly works to shed light on the surprising relationship between the number of breweries in the United States and solar power generation in Peru. While this unusual pairing may seem far-fetched at first, it calls for a comprehensive exploration of existing literature and perspectives.
Smith (2015) offers a comprehensive analysis of the solar power dynamics in Peru, shedding light on the various factors influencing the country's solar energy production. Meanwhile, Doe (2017) delves into the exponential growth of breweries across the United States, providing valuable insights into the evolving landscape of craft beer in the nation.
Moving beyond the realm of scholarly articles, we turn our attention to non-fiction books that touch upon energy dynamics and the brewing industry. "Solar Power for Dummies" (Johnson, 2019) offers a beginner's guide to understanding solar energy, while "The Craft of Craft Beer" (Adams, 2018) provides a detailed exploration of the art and science behind brewing.
Venturing further into the literary world, we encounter fictional works that capture the essence of unexpected connections and whimsical pairings. In "The Sun Also Rises" (Hemingway, 1926), the interplay of light and shadow mirrors the juxtaposition of warm beer and radiant solar power, albeit in a more metaphorical sense. In a lighter vein, "Brewing Up a Storm" (Mortensen, 2013) paints a whimsical tale of a brewmaster who discovers a hidden link between his concoctions and the energy of the sun.
Not content with conventional sources, our research team delves into the realms of popular culture, drawing inspiration and insights from unlikely sources. As avid cartoon enthusiasts, we couldn't resist peeking into the world of "The Simpsons," where Homer Simpson's affinity for Duff Beer intersects with the occasional solar mishap, offering a lighthearted vantage point on the convergence of breweries and solar energy.
In the spirit of thorough investigation, we also explored children's shows that inadvertently shed light on our research topic. From "Bob the Builder" and his solar-powered construction equipment to the educational escapades of "Magic School Bus," wherein Ms. Frizzle unearths the interconnectedness of energy systems, our foray into cartoon and children's programming provided unexpected insights into the fusion of brewing and solar phenomena.
As we navigate through this eclectic array of literature, from scholarly works to whimsical tales and animated adventures, our quest for understanding the interplay between breweries and solar power continues to unveil unexpected connections and quirky perspectives.

[[RESULTS]]
The results of our analysis revealed a striking correlation between the number of breweries in the United States and the solar power generated in Peru over the period from 2000 to 2021. We found a correlation coefficient of 0.9783511, indicating a remarkably strong relationship between these two variables. In layman's terms, it's as if every new brewery that popped up in the U.S. was accompanied by a surge in solar power beaming down on Peru, or vice versa.
The r-squared value of 0.9571708 further solidifies this connection, suggesting that a whopping 95.71% of the variability in solar power generation in Peru can be explained by the number of breweries in the U.S. That's right, almost 96% of the ups and downs in solar wattage across the Peruvian landscape could be predicted by simply keeping an eye on the ever-growing brewery count in the U.S. It's almost like the sun is saying, "Hey, you brew, I'll shine!"
Now, the p-value of less than 0.01 indicates that our findings are highly significant and not just a statistical fluke. This means that the likelihood of such a strong association occurring by random chance is less than 1 in 100. In other words, the probability of this correlation being a cosmic coincidence is about as likely as stumbling upon a unicorn sipping a cold one under a solar-powered rainbow.
To visually capture the magnitude of this unexpected relationship, we present Figure 1, a scatterplot demonstrating the robust correlation between the number of breweries in the U.S. and the solar power generated in Peru. The data points align so closely that it's as if they're harmonizing in a cosmic symphony, one brewing up a storm while the other basks in the sun's luminous applause.
These findings not only shed light on the intertwined nature of these variables but also invite further exploration into the whimsical ways in which seemingly unrelated phenomena can dance together in the statistical spotlight. As we savor the boundless possibilities unveiled by this curious correlation, we invite our peers to join us in pondering the unforeseen links that enliven the tapestry of scientific inquiry. Cheers to the delightful surprises that arise when we examine the world through the lens of data and discovery!

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study have brought to light a fascinating and, dare we say, refreshing connection between the number of breweries in the United States and the solar power generated in Peru. While some skeptics may raise an eyebrow at this unlikely partnership, our findings align with prior research in unexpected yet surprisingly insightful ways.

One cannot help but recall the works of Mortensen (2013) who, in "Brewing Up a Storm," whimsically spun a tale of a brewmaster stumbling upon a mysterious link between his concoctions and the energy of the sun. Little did we know that such a playful premise could hold a kernel of truth, as our analysis unequivocally supports a robust relationship between the brewing industry and solar power generation.

Comparable to the exponential growth of U.S. breweries documented by Doe (2017), our results unveil a substantial correlation between the proliferation of breweries in the U.S. and the solar power radiating upon the Peruvian terrain. It's as if the upward trend in craft beer establishments triggers a concurrent surge in solar energy, akin to a jovial dance between fermenting hops and gleaming photons.

Moreover, the alignment of our findings with the scholarly analysis of solar power dynamics in Peru by Smith (2015) reinforces the notion that the number of breweries in the U.S. exerts a palpable influence on the solar wattage gracing the Peruvian landscape. This unexpected synergy, much like the interplay of light and shadow in Hemingway's "The Sun Also Rises," showcases the profound, albeit metaphorical, connection between beer brewing and solar energy production.

Our results not only uphold prior literature on these seemingly divergent domains but also open the door to a myriad of puns and playful perspectives. As we raise a glass to these findings, we invite our peers to imbibe the mirthful possibilities presented by this unconventional correlation. After all, who would have thought that the whimsical interweaving of breweries and solar power could yield such illuminating statistical revelations? Let's embrace the joyous kaleidoscope of science, replete with unexpected connections and wink-worthy associations. Cheers to the serendipitous discoveries that fuel the exuberant spirit of research and inquiry!

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 The number of Breweries in the United States and Solar power generated in Peru. 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]]
Brewing Up a Solar Storm: The Surprising Relationship Between U.S. Breweries and Solar Power Generation in Peru

[[ABSTRACT]]
In this study, we delve into the uncharted territory of the interplay between the number of breweries in the United States and the solar power generated in Peru. Despite initial skepticism from our peers and perhaps a few raised eyebrows, our research team meticulously collected and analyzed data from the Brewers Association and Energy Information Administration, covering the period from 2000 to 2021. Our findings revealed a remarkably strong correlation coefficient of 0.9783511 and a p-value of less than 0.01, demonstrating a strikingly robust relationship between these two seemingly disparate variables. As we navigate through this unexpected alliance between the craft beer industry and solar energy production, we invite the scientific community to raise a glass and ponder the implications of this lighthearted yet illuminating association.

[[INTRDUCTION]]
Introduction
As we enter the realm of unconventional correlations and unexpected connections, our study embarks on a curious journey into the realm of sudsy libations and radiant energy. Brewing up a storm in the world of statistical analysis, we set out to explore the rather peculiar relationship between the number of breweries in the United States and the solar power generated in Peru.
At first glance, one might raise an eyebrow and wonder about the significance of these two variables. "Do breweries in the U.S. somehow influence solar power generation in Peru?" one might ask. Well, hold on to your beakers and alembics, because the results of our investigation might just brew up some surprising revelations.
The intersection of these seemingly unrelated entities raised more than a few puzzled looks during the initial stages of our research. However, armed with our trusty calculators, data spreadsheets, and a few well-timed quips, our team ventured forth undeterred into the statistical jungle.
Utilizing data from the Brewers Association and the Energy Information Administration spanning over two decades, we meticulously combed through the numbers, distilling the essence of these variables down to their statistical elements. We found ourselves knee-deep in numerical hops and solar wattage, endeavoring to uncover any glimmer of connection between these contrasting phenomena.
With a correlation coefficient of 0.9783511 and a p-value of less than 0.01, our findings pointed to a surprisingly sturdy relationship between the number of breweries popping up across the U.S. and the solar power illuminating the landscape of Peru. Amidst the brouhaha of bubbling fermentation and shimmering solar panels, a compelling correlation emerged, challenging conventional expectations and sparking curiosity among researchers and beer enthusiasts alike.
As we delve deeper into this brew-tiful alliance between the craft beer industry and solar energy production, we invite our colleagues in the scholarly community to join us in raising a glass, not only to toast this unexpected finding but also to contemplate the implications of this intriguing partnership. Let us raise our metaphorical flasks and ponder the unanticipated interplay between brews and rays, for in the world of statistics, as in life, sometimes the most delightful discoveries lie in the unlikeliest of pairings.

[[RESULTS]]
The results of our analysis revealed a striking correlation between the number of breweries in the United States and the solar power generated in Peru over the period from 2000 to 2021. We found a correlation coefficient of 0.9783511, indicating a remarkably strong relationship between these two variables. In layman's terms, it's as if every new brewery that popped up in the U.S. was accompanied by a surge in solar power beaming down on Peru, or vice versa.
The r-squared value of 0.9571708 further solidifies this connection, suggesting that a whopping 95.71% of the variability in solar power generation in Peru can be explained by the number of breweries in the U.S. That's right, almost 96% of the ups and downs in solar wattage across the Peruvian landscape could be predicted by simply keeping an eye on the ever-growing brewery count in the U.S. It's almost like the sun is saying, "Hey, you brew, I'll shine!"
Now, the p-value of less than 0.01 indicates that our findings are highly significant and not just a statistical fluke. This means that the likelihood of such a strong association occurring by random chance is less than 1 in 100. In other words, the probability of this correlation being a cosmic coincidence is about as likely as stumbling upon a unicorn sipping a cold one under a solar-powered rainbow.
To visually capture the magnitude of this unexpected relationship, we present Figure 1, a scatterplot demonstrating the robust correlation between the number of breweries in the U.S. and the solar power generated in Peru. The data points align so closely that it's as if they're harmonizing in a cosmic symphony, one brewing up a storm while the other basks in the sun's luminous applause.
These findings not only shed light on the intertwined nature of these variables but also invite further exploration into the whimsical ways in which seemingly unrelated phenomena can dance together in the statistical spotlight. As we savor the boundless possibilities unveiled by this curious correlation, we invite our peers to join us in pondering the unforeseen links that enliven the tapestry of scientific inquiry. Cheers to the delightful surprises that arise when we examine the world through the lens of data and discovery!

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

Conclusion

In conclusion, our research has illuminated a captivating connection between the proliferation of breweries in the United States and the solar power radiating across Peru. The robust correlation coefficient of 0.9783511 and the red-hot p-value of less than 0.01 leave little room for doubt about the intertwined fate of craft beer and solar energy. It's as if every fizzy brew and sunbeam are engaged in an enchanting waltz across continents.

The high r-squared value of 0.9571708 provides a striking testament to the predictability of solar energy fluctuations based on U.S. brewery counts. This unexpected partnership between beer and sunshine proves to be statistically sturdy, leaving little room for dispute. It's like the sun and the brewing industry have entered into some kind of illuminating contract, promising a bright future for both.

Figure 1, our scatterplot, visually encapsulates this intriguing relationship, displaying a dance of data points so harmonious that they make statistical analysis seem like a cosmic ballet. The probability of this correlation occurring by chance is as remote as stumbling upon a scientific breakthrough while searching for the end of a rainbow.

As we raise our imaginary flasks one last time, our findings underscore the whimsical ways in which scientific inquiry can uncover enchanting connections where none were expected. In the spirit of discovery, we submit that further research in this area would be as unnecessary as a solar-powered flashlight. The findings of our study should stand as a beacon of the unexpected and the amusing, igniting curiosity and sparking discussions among scholars and beer aficionados alike. Cheers to the delightful surprises that emerge when seemingly unrelated variables come together in a statistical pas de deux!

No further research is needed; let's savor this unexpected pairing like a finely brewed pun.

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 Brewing Up a Solar Storm: The Surprising Relationship Between U.S. Breweries and Solar Power Generation in Peru. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Renewable Energy and Unconventional Partnerships

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 Brewing Up a Solar Storm: The Surprising Relationship Between U.S. Breweries and Solar Power Generation in Peru. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Solar-Powered Suds

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 Brewing Up a Solar Storm: The Surprising Relationship Between U.S. Breweries and Solar Power Generation in Peru with an abstract of In this study, we delve into the uncharted territory of the interplay between the number of breweries in the United States and the solar power generated in Peru. Despite initial skepticism from our peers and perhaps a few raised eyebrows, our research team meticulously collected and analyzed data from the Brewers Association and Energy Information Administration, covering the period from 2000 to 2021. Our findings revealed a remarkably strong correlation coefficient of 0.9783511 and a p-value of less than 0.01, demonstrating a strikingly robust relationship between these two seemingly disparate variables. As we navigate through this unexpected alliance between the craft beer industry and solar energy production, we invite the scientific community to raise a glass and ponder the implications of this lighthearted yet illuminating association.

ChatGPT:

U.S. breweries, solar power generation, Peru, correlation coefficient, p-value, Brewers Association, Energy Information Administration, craft beer industry, solar energy production, solar power, number of breweries, relationship, research, data analysis

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

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Data details

The number of Breweries in the United States
Detailed data title: Number of Breweries in the United States
Source: Brewers Association
See what else correlates with The number of Breweries in the United States

Solar power generated in Peru
Detailed data title: Total solar power generated in Peru in billion kWh
Source: Energy Information Administration
See what else correlates with Solar power generated in Peru

Correlation r = 0.9783511 (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 = 0.9571708 (Coefficient of determination)
This means 95.7% of the change in the one variable (i.e., Solar power generated in Peru) is predictable based on the change in the other (i.e., The number of Breweries in the United States) over the 22 years from 2000 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.7E-15.^Show 0.0000000000000037327108415636
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 0.98 in 3.7E-13% of random cases. Said differently, if you correlated 267,901,812,501,798 random variables^Note You don't actually need 267 trillion 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 21 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 21 because we have two variables measured over a period of 22 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.

[ 0.95, 0.99 ] 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
The number of Breweries in the United States (Number of breweries)	1493	1499	1575	1629	1635	1612	1741	1805	1896	1933	2131	2525	2670	3162	4014	4847	5780	6767	7722	8557	9092	9384
Solar power generated in Peru (Billion kWh)	5.0E-5	5.0E-5	5.0E-5	5.0E-5	5.0E-5	5.0E-5	5.0E-5	5.0E-5	5.0E-5	5.0E-5	5.0E-5	5.0E-5	0.093	0.238	0.247	0.286	0.306	0.361	0.75	0.779	0.794	0.819

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.
Confounding variable: 2020 is particularly different from the other years on this graph. Confounding variables (like global pandemics) will cause two variables to look connected when in fact a "sneaky third" variable is influencing both of them behind the scenes.

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([1493,1499,1575,1629,1635,1612,1741,1805,1896,1933,2131,2525,2670,3162,4014,4847,5780,6767,7722,8557,9092,9384,])
array_2 = np.array([5.0E-5,5.0E-5,5.0E-5,5.0E-5,5.0E-5,5.0E-5,5.0E-5,5.0E-5,5.0E-5,5.0E-5,5.0E-5,5.0E-5,0.093,0.238,0.247,0.286,0.306,0.361,0.75,0.779,0.794,0.819,])
array_1_name = "The number of Breweries in the United States"
array_2_name = "Solar power generated in Peru"

# 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 The number of Breweries in the United States
Line chart for only Solar power generated in Peru
AI-generated correlation image
The spurious research paper: Brewing Up a Solar Storm: The Surprising Relationship Between U.S. Breweries and Solar Power Generation in Peru

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Correlation ID: 3384 · Black Variable ID: 34 · Red Variable ID: 23896


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