Spurious correlation #1,597 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Solar power generated in Rwanda and the second variable is Google searches for 'dollar store near me'. The chart goes from 2007 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 Solar power generated in Rwanda and the second variable is Google searches for 'dollar store near me'. The chart goes from 2007 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As more solar power was harnessed in Rwanda, it inadvertently led to a surge in atmospheric positivity. This positivity wafted across continents and inexplicably increased people's urge to hunt for budget-friendly deals at dollar stores, creating a magnetic pull towards the aisles of affordable, yet random, merchandise. Remember, when you're feeling charged up, a trip to the dollar store might just be the bright idea you need!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a bustling marketplace in Rwanda, where colorful local shops with solar panels on their rooftops are bathed in sunlight. The scene includes people walking and using their smartphones to search for "dollar store near me" on Google. Capture the lively atmosphere, vibrant colors of the market, and the juxtaposition of traditional architecture with modern technology. 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: Solar power generated in Rwanda and Google searches for 'dollar store near me'. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Realistic Surrealism Cute 2D animation Magic realism A scene from Skyrim
ChatGPT: Realistic

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Solar power generated in Rwanda and Google searches for 'dollar store near me' together. Keep the description simple.
ChatGPT: In a vibrant and sunny marketplace in Rwanda, solar panels are installed on the rooftops of local shops. At the same time, people are seen on their smartphones, using Google to search for "dollar store near me" as they walk past the solar-powered shops.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Realistic ] and depicting this scene: In a vibrant and sunny marketplace in Rwanda, solar panels are installed on the rooftops of local shops. At the same time, people are seen on their smartphones, using Google to search for "dollar store near me" as they walk past the solar-powered shops. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a bustling marketplace in Rwanda, where colorful local shops with solar panels on their rooftops are bathed in sunlight. The scene includes people walking and using their smartphones to search for "dollar store near me" on Google. Capture the lively atmosphere, vibrant colors of the market, and the juxtaposition of traditional architecture with modern technology.

*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 Solar power generated in Rwanda caused dollar store near me (Google searches for 'dollar store near me') to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)

Solar-Powered Savings: Illuminating the Correlation Between Solar Power in Rwanda and the Quest for Budget Bargains

The Journal of Renewable Energy Economics and Sustainable Development

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 Solar power generated in Rwanda and Google searches for 'dollar store near me'. Make lots of jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Solar-Powered Savings: Illuminating the Correlation Between Solar Power in Rwanda and the Quest for Budget Bargains"

[[ABSTRACT]]
Our research delves into the curious connection between the increasing solar power generation in Rwanda and the intensity of Google searches for "dollar store near me". While the association might seem as unlikely as finding a discount toaster in a dollar store, we conducted a rigorous analysis using data from the Energy Information Administration and Google Trends. Surprisingly, our findings reveal a remarkably strong correlation coefficient of 0.9915372 and a statistically significant p-value < 0.01 for the period spanning from 2007 to 2021. Perhaps this illuminates a bright new path for solar energy research or simply suggests that people are on the hunt for affordable trinkets after saving on electricity bills. Either way, our research sheds light on an unexpected and amusing correlation that is sure to spark a few knowing chuckles.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the illustrious world of academia, where serious faces and even more serious statistical analyses reign supreme, it is not often that one encounters a research topic as peculiar and eyebrow-raising as the unlikely correlation between solar power generation in Rwanda and the fervent quest for budget bargains at dollar stores. Yet, here we are, embarking on a scholarly journey that traverses the realms of renewable energy and frugal shopping, proving that research can illuminate the most unexpected connections – much like a motion-activated solar-powered garden light.
While the notion of solar power and dollar store searches being intertwined may initially seem as incongruous as pairing a tuxedo with flip-flops, our intrepid research team could not resist delving into this peculiar pairing. Armed with an arsenal of statistical tools, data sources, and a healthy dose of skepticism, we set out to investigate whether there was more to this correlation than meets the eye – or the photovoltaic cell.
As we tiptoed through the labyrinth of data, we found ourselves confronted with the sunny statistics of solar energy generation in Rwanda, where the pursuit of sustainable and environmentally friendly power sources has been akin to a game of "which came first, the solar panel or the egg?" Simultaneously, the virtual footprints of individuals embarking on quests for affordable treasures at dollar stores via Google searches danced in our Excel sheets, revealing a narrative that seemed as improbable as stumbling upon a mint-condition lava lamp in the clearance section of a dollar store.
In this paper, we present the findings of our unconventional investigation, unveiling a correlation coefficient of 0.9915372 that is as dazzling as a newly-installed solar array on a clear day. By leveraging data from the Energy Information Administration to quantify solar power production and Google Trends to track the ebb and flow of "dollar store near me" searches, we were able to shed light on a connection that will undoubtedly raise a few eyebrows and, hopefully, elicit more than a few wry grins from our esteemed colleagues.
As we dive into the depths of this unexpected correlation, buckle up for a ride that is as illuminating as a solar-powered LED flashlight and as delightfully perplexing as stumbling upon a knockoff version of a famous brand in a dollar store. After all, in the realm of research, sometimes the most surprising discoveries are found in the most unexpected places – much like a hidden gem unearthed at the bottom of a bargain bin.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The association between solar power generation and consumer behavior has been a topic of great interest in recent years. Smith and Doe (2018) found a significant positive relationship between solar energy adoption and consumer spending patterns, highlighting the potential impact of renewable energy on economic activities. Similarly, Jones et al. (2019) explored the societal implications of solar power integration and observed shifts in consumer preferences for sustainable products. These studies underscore the intricate interplay between sustainable energy sources and consumer behavior, laying the groundwork for our investigation into the unexpected correlation between solar power generation in Rwanda and Google searches for "dollar store near me".
Moving beyond the scholarly realm, works such as "The Solar Future" by Green (2020) and "Clean Energy for Dummies" by Eco-Watts (2017) provide insights into the evolving landscape of renewable energy and its potential effects on various facets of society. On the other hand, fictional narratives like "Solar Flare" by Ray Star and "The Dollar Store Diaries" by Penny Pincher offer imaginative perspectives that, while not rooted in empirical data, explore themes that resonate with our research focus.
In a departure from traditional sources of scholarly inquiry, we also delved into unconventional literature, perusing the backs of shampoo bottles and fortune cookie messages in pursuit of hidden wisdom. While the scientific rigor of these sources may be questionable, we were determined to leave no stone unturned in our quest for knowledge – and perhaps a bit of lighthearted amusement amidst the rigorous academic pursuit.
As we navigate through the diverse landscape of literature and unconventional sources, it becomes evident that the intersection of solar power generation and consumer behavior is a rich tapestry of inquiry, teeming with potential insights and unexpected connections. Through our own study, we aim to add a colorful thread to this tapestry, one that sparkles with the whimsy of an unexpected correlation and the promise of solar-powered savings.

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 Solar power generated in Rwanda and Google searches for 'dollar store near me'. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and Google Trends . You used data from 2007 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]]
"Solar-Powered Savings: Illuminating the Correlation Between Solar Power in Rwanda and the Quest for Budget Bargains"

[[ABSTRACT]]
Our research delves into the curious connection between the increasing solar power generation in Rwanda and the intensity of Google searches for "dollar store near me". While the association might seem as unlikely as finding a discount toaster in a dollar store, we conducted a rigorous analysis using data from the Energy Information Administration and Google Trends. Surprisingly, our findings reveal a remarkably strong correlation coefficient of 0.9915372 and a statistically significant p-value < 0.01 for the period spanning from 2007 to 2021. Perhaps this illuminates a bright new path for solar energy research or simply suggests that people are on the hunt for affordable trinkets after saving on electricity bills. Either way, our research sheds light on an unexpected and amusing correlation that is sure to spark a few knowing chuckles.

[[INTRODUCTION]]
In the illustrious world of academia, where serious faces and even more serious statistical analyses reign supreme, it is not often that one encounters a research topic as peculiar and eyebrow-raising as the unlikely correlation between solar power generation in Rwanda and the fervent quest for budget bargains at dollar stores. Yet, here we are, embarking on a scholarly journey that traverses the realms of renewable energy and frugal shopping, proving that research can illuminate the most unexpected connections – much like a motion-activated solar-powered garden light.
While the notion of solar power and dollar store searches being intertwined may initially seem as incongruous as pairing a tuxedo with flip-flops, our intrepid research team could not resist delving into this peculiar pairing. Armed with an arsenal of statistical tools, data sources, and a healthy dose of skepticism, we set out to investigate whether there was more to this correlation than meets the eye – or the photovoltaic cell.
As we tiptoed through the labyrinth of data, we found ourselves confronted with the sunny statistics of solar energy generation in Rwanda, where the pursuit of sustainable and environmentally friendly power sources has been akin to a game of "which came first, the solar panel or the egg?" Simultaneously, the virtual footprints of individuals embarking on quests for affordable treasures at dollar stores via Google searches danced in our Excel sheets, revealing a narrative that seemed as improbable as stumbling upon a mint-condition lava lamp in the clearance section of a dollar store.
In this paper, we present the findings of our unconventional investigation, unveiling a correlation coefficient of 0.9915372 that is as dazzling as a newly-installed solar array on a clear day. By leveraging data from the Energy Information Administration to quantify solar power production and Google Trends to track the ebb and flow of "dollar store near me" searches, we were able to shed light on a connection that will undoubtedly raise a few eyebrows and, hopefully, elicit more than a few wry grins from our esteemed colleagues.
As we dive into the depths of this unexpected correlation, buckle up for a ride that is as illuminating as a solar-powered LED flashlight and as delightfully perplexing as stumbling upon a knockoff version of a famous brand in a dollar store. After all, in the realm of research, sometimes the most surprising discoveries are found in the most unexpected places – much like a hidden gem unearthed at the bottom of a bargain bin.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To uncover the enigmatic relationship between solar power generation in Rwanda and the fervent pursuit of budget bargains encapsulated in Google searches for "dollar store near me", our research team embarked on a methodological odyssey that was as intriguing as a mysterious item found in the depths of a dollar store's clearance aisle.

Data Collection:
In our quest for knowledge, we scoured the digital landscape, navigating through the virtual jungles of information with the agility of a solar-powered chimpanzee swinging from tree to tree. Our primary data sources included the Energy Information Administration's database, where we obtained comprehensive and meticulously-maintained records of solar power generation in Rwanda from 2007 to 2021. Additionally, we harnessed the dynamic biodiversity of Google Trends to capture the temporal ebbs and flows of searches for "dollar store near me" and create a veritable portrait of budget bargain hunters traversing the digital savannah.

The Enigmatic Algorithms:
With the digital artifacts in hand, we delved into the mysterious realm of algorithms, where number-crunching and statistical sleuthing were akin to deciphering the ancient hieroglyphs of correlation and regression. Our research team invoked the mystical powers of statistical software, summoning the esoteric capabilities of R and Python, to weave an intricate web of mathematical analyses designed to unveil the hidden connections between solar power and the allure of discount trinkets.

Unraveling the Correlation:
Fuelled by countless cups of coffee and an unwavering determination reminiscent of a caffeine-fueled adventurer in search of the Holy Grail, we subjected our data to a grueling series of statistical tests. From Pearson's correlation coefficient to time-series analysis, we probed the depths of our findings with an almost obsessive fervor, as if peering through a high-powered telescope in pursuit of the elusive cosmic unity that binds solar power and dollar store quests.

Reliability and Validity:
As we journeyed through the labyrinth of statistical significance and effect size, we maintained a vigilant eye for potential confounding variables and spurious correlations that threatened to derail our scholarly expedition. Through rigorous sensitivity analyses and robustness checks, we fortified the foundations of our findings, ensuring that our conclusions were as sturdy as a well-constructed solar panel array and as dependable as the perennial availability of discount Reese's Pieces at a dollar store.

Ethical Considerations:
In our relentless pursuit of knowledge, we remained steadfast in upholding the noble principles of research ethics, navigating the treacherous terrain of data privacy and integrity with the grace of a tightrope walker in a solar-powered circus. With the utmost respect for the sanctity of personal information, we shielded the identities of digital adventurers captured in our Google Trends data, ensuring that their virtual wanderings through the aisles of digital dollar stores remained shrouded in anonymity.

In presenting our findings, we invite our esteemed colleagues to join us in unraveling this captivating tale of unexpected connections, as we shed light on a correlation that is as curious as a solar-powered dancing flower swaying to an unheard melody. As we unveil the results of our methodological escapades, we trust that our readers will find both enlightenment and amusement in this scholarly expedition that transcends the boundaries of conventional research, much like stumbling upon a whimsical unicorn-themed mug in a dollar store brimming with peculiar treasures.

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 Solar power generated in Rwanda and Google searches for 'dollar store near me'. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and Google Trends .

For the time period 2007 to 2021, you found a correlation 0.9915372, r-squared of 0.9831461, 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]]
"Solar-Powered Savings: Illuminating the Correlation Between Solar Power in Rwanda and the Quest for Budget Bargains"

[[ABSTRACT]]
Our research delves into the curious connection between the increasing solar power generation in Rwanda and the intensity of Google searches for "dollar store near me". While the association might seem as unlikely as finding a discount toaster in a dollar store, we conducted a rigorous analysis using data from the Energy Information Administration and Google Trends. Surprisingly, our findings reveal a remarkably strong correlation coefficient of 0.9915372 and a statistically significant p-value < 0.01 for the period spanning from 2007 to 2021. Perhaps this illuminates a bright new path for solar energy research or simply suggests that people are on the hunt for affordable trinkets after saving on electricity bills. Either way, our research sheds light on an unexpected and amusing correlation that is sure to spark a few knowing chuckles.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the illustrious world of academia, where serious faces and even more serious statistical analyses reign supreme, it is not often that one encounters a research topic as peculiar and eyebrow-raising as the unlikely correlation between solar power generation in Rwanda and the fervent quest for budget bargains at dollar stores. Yet, here we are, embarking on a scholarly journey that traverses the realms of renewable energy and frugal shopping, proving that research can illuminate the most unexpected connections – much like a motion-activated solar-powered garden light.
While the notion of solar power and dollar store searches being intertwined may initially seem as incongruous as pairing a tuxedo with flip-flops, our intrepid research team could not resist delving into this peculiar pairing. Armed with an arsenal of statistical tools, data sources, and a healthy dose of skepticism, we set out to investigate whether there was more to this correlation than meets the eye – or the photovoltaic cell.
As we tiptoed through the labyrinth of data, we found ourselves confronted with the sunny statistics of solar energy generation in Rwanda, where the pursuit of sustainable and environmentally friendly power sources has been akin to a game of "which came first, the solar panel or the egg?" Simultaneously, the virtual footprints of individuals embarking on quests for affordable treasures at dollar stores via Google searches danced in our Excel sheets, revealing a narrative that seemed as improbable as stumbling upon a mint-condition lava lamp in the clearance section of a dollar store.
In this paper, we present the findings of our unconventional investigation, unveiling a correlation coefficient of 0.9915372 that is as dazzling as a newly-installed solar array on a clear day. By leveraging data from the Energy Information Administration to quantify solar power production and Google Trends to track the ebb and flow of "dollar store near me" searches, we were able to shed light on a connection that will undoubtedly raise a few eyebrows and, hopefully, elicit more than a few wry grins from our esteemed colleagues.
As we dive into the depths of this unexpected correlation, buckle up for a ride that is as illuminating as a solar-powered LED flashlight and as delightfully perplexing as stumbling upon a knockoff version of a famous brand in a dollar store. After all, in the realm of research, sometimes the most surprising discoveries are found in the most unexpected places – much like a hidden gem unearthed at the bottom of a bargain bin.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

In this section, we present the illuminating results of our investigation into the uncharted territory of the correlation between solar power generation in Rwanda and the fervent hunt for budget bargains at dollar stores, as revealed by Google searches for "dollar store near me". Our analysis revealed a correlation coefficient of 0.9915372, an r-squared value of 0.9831461, and a p-value of less than 0.01 for the period spanning from 2007 to 2021. These results shine bright like a high-wattage solar-powered floodlight, leaving no room for doubt about the robustness and statistical significance of the relationship between these seemingly unrelated phenomena.

The strong correlation coefficient of 0.9915372 suggests that the connection between solar power generation in Rwanda and the quest for budget bargains at dollar stores is as unmistakable as a neon sign in a dark alley. This finding dances across the academic stage, dazzling skeptics and supporters alike with its resilience to statistical scrutiny. The r-squared value of 0.9831461 further emphasizes the tightness of the relationship, indicating that approximately 98.31% of the variance in "dollar store near me" searches can be explained by the variance in solar power generation in Rwanda. It's as if the solar panels themselves are beaming out a message: "Come find your bargains here!"

Yet, we must not overlook the significance of the p-value being less than 0.01, a result that is about as rare as finding an unopened pack of batteries at a dollar store. This p-value reinforces the robustness of the correlation, providing evidence that the relationship between these two variables is not the result of mere chance but is, in fact, a bona fide connection worthy of scholarly attention.

Our comprehensive analysis culminates in the presentation of a scatterplot (Fig. 1) that visually encapsulates the strength of the correlation between solar power generation in Rwanda and Google searches for "dollar store near me". This chart serves as a veritable beacon, illuminating the unmistakable link between these two seemingly disparate domains with all the subtlety of a fireworks display in broad daylight.

In summary, our results unequivocally demonstrate a remarkable association between solar power generation in Rwanda and the intensity of searches for budget bargains at dollar stores. This unexpected correlation may have wide-reaching implications for both the renewable energy sector and the retail industry, shedding light on a connection that is as surprising as finding a gold-plated trinket in a dollar store treasure hunt.

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 Solar power generated in Rwanda and Google searches for 'dollar store near me'. Make lots of jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Solar-Powered Savings: Illuminating the Correlation Between Solar Power in Rwanda and the Quest for Budget Bargains"

[[ABSTRACT]]
Our research delves into the curious connection between the increasing solar power generation in Rwanda and the intensity of Google searches for "dollar store near me". While the association might seem as unlikely as finding a discount toaster in a dollar store, we conducted a rigorous analysis using data from the Energy Information Administration and Google Trends. Surprisingly, our findings reveal a remarkably strong correlation coefficient of 0.9915372 and a statistically significant p-value < 0.01 for the period spanning from 2007 to 2021. Perhaps this illuminates a bright new path for solar energy research or simply suggests that people are on the hunt for affordable trinkets after saving on electricity bills. Either way, our research sheds light on an unexpected and amusing correlation that is sure to spark a few knowing chuckles.

[[LITERATURE REVIEW]]
The association between solar power generation and consumer behavior has been a topic of great interest in recent years. Smith and Doe (2018) found a significant positive relationship between solar energy adoption and consumer spending patterns, highlighting the potential impact of renewable energy on economic activities. Similarly, Jones et al. (2019) explored the societal implications of solar power integration and observed shifts in consumer preferences for sustainable products. These studies underscore the intricate interplay between sustainable energy sources and consumer behavior, laying the groundwork for our investigation into the unexpected correlation between solar power generation in Rwanda and Google searches for "dollar store near me".
Moving beyond the scholarly realm, works such as "The Solar Future" by Green (2020) and "Clean Energy for Dummies" by Eco-Watts (2017) provide insights into the evolving landscape of renewable energy and its potential effects on various facets of society. On the other hand, fictional narratives like "Solar Flare" by Ray Star and "The Dollar Store Diaries" by Penny Pincher offer imaginative perspectives that, while not rooted in empirical data, explore themes that resonate with our research focus.
In a departure from traditional sources of scholarly inquiry, we also delved into unconventional literature, perusing the backs of shampoo bottles and fortune cookie messages in pursuit of hidden wisdom. While the scientific rigor of these sources may be questionable, we were determined to leave no stone unturned in our quest for knowledge – and perhaps a bit of lighthearted amusement amidst the rigorous academic pursuit.
As we navigate through the diverse landscape of literature and unconventional sources, it becomes evident that the intersection of solar power generation and consumer behavior is a rich tapestry of inquiry, teeming with potential insights and unexpected connections. Through our own study, we aim to add a colorful thread to this tapestry, one that sparkles with the whimsy of an unexpected correlation and the promise of solar-powered savings.

[[RESULTS]]
In this section, we present the illuminating results of our investigation into the uncharted territory of the correlation between solar power generation in Rwanda and the fervent hunt for budget bargains at dollar stores, as revealed by Google searches for "dollar store near me". Our analysis revealed a correlation coefficient of 0.9915372, an r-squared value of 0.9831461, and a p-value of less than 0.01 for the period spanning from 2007 to 2021. These results shine bright like a high-wattage solar-powered floodlight, leaving no room for doubt about the robustness and statistical significance of the relationship between these seemingly unrelated phenomena.
The strong correlation coefficient of 0.9915372 suggests that the connection between solar power generation in Rwanda and the quest for budget bargains at dollar stores is as unmistakable as a neon sign in a dark alley. This finding dances across the academic stage, dazzling skeptics and supporters alike with its resilience to statistical scrutiny. The r-squared value of 0.9831461 further emphasizes the tightness of the relationship, indicating that approximately 98.31% of the variance in "dollar store near me" searches can be explained by the variance in solar power generation in Rwanda. It's as if the solar panels themselves are beaming out a message: "Come find your bargains here!"
Yet, we must not overlook the significance of the p-value being less than 0.01, a result that is about as rare as finding an unopened pack of batteries at a dollar store. This p-value reinforces the robustness of the correlation, providing evidence that the relationship between these two variables is not the result of mere chance but is, in fact, a bona fide connection worthy of scholarly attention.
Our comprehensive analysis culminates in the presentation of a scatterplot (Fig. 1) that visually encapsulates the strength of the correlation between solar power generation in Rwanda and Google searches for "dollar store near me". This chart serves as a veritable beacon, illuminating the unmistakable link between these two seemingly disparate domains with all the subtlety of a fireworks display in broad daylight.
In summary, our results unequivocally demonstrate a remarkable association between solar power generation in Rwanda and the intensity of searches for budget bargains at dollar stores. This unexpected correlation may have wide-reaching implications for both the renewable energy sector and the retail industry, shedding light on a connection that is as surprising as finding a gold-plated trinket in a dollar store treasure hunt.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our findings provide compelling evidence for the unexpected yet undeniably potent correlation between the burgeoning solar power generation in Rwanda and the zealous pursuit of affordable goodies at dollar stores. While the notion of solar panels whispering sweet bargain secrets to frugal shoppers might initially elicit a chuckle, our results underscore the robustness of this remarkable association.

Building on the scholarly work of Smith and Doe (2018), our research echoes their findings of a positive relationship between solar energy adoption and consumer spending patterns. It seems that as the sun shines down on Rwanda, so does the allure of budget-friendly treasures, drawing consumers to seek out dollar store wonders like moths to a solar-powered flame. Similarly, the observations by Jones et al. (2019) resonate with our results, suggesting that the integration of solar power can indeed influence consumer behavior in unsuspected ways – perhaps inspiring individuals to bask in the glow of sustainable energy and then go on a quest for super-cheap snacks.

Our study transcends the traditional scholarly landscape by embracing unconventional sources, such as the fictional narratives "Solar Flare" and "The Dollar Store Diaries", to explore the symbolic resonance of our findings with the human experience. The connection between solar power and dime-store dreams seems to reach beyond the confines of empirical data, tapping into an undercurrent of whimsy that adds a splash of color to the often serious world of academic inquiry.

Emerging from this vibrant tapestry of research, our results present a compelling case for recognizing the intersection of solar power generation and the pursuit of budget bargains as a bona fide area of scholarly inquiry. As we peer into the dazzling scatterplot, it's as if we can see the faint yet unmistakable outline of a shopping cart, filled to the brim with solar-powered solutions and dollar store delights. This unexpected correlation, while ripe with amusing overtones, carries important implications for understanding the complex interplay between sustainable energy adoption and consumer behavior.

In conclusion, our study not only broadens the scope of scholarly investigation into renewable energy impacts but also invites a playful reimagining of the ways in which solar power may weave into the fabric of everyday consumer choices. The solar-powered siren call of dollar store bargains beckons, and our research offers a glimmer of insight into this curious dance between light, energy, and the pursuit of an irresistible deal.

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 Solar power generated in Rwanda and Google searches for 'dollar store near me'. Make lots of jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Solar-Powered Savings: Illuminating the Correlation Between Solar Power in Rwanda and the Quest for Budget Bargains"

[[ABSTRACT]]
Our research delves into the curious connection between the increasing solar power generation in Rwanda and the intensity of Google searches for "dollar store near me". While the association might seem as unlikely as finding a discount toaster in a dollar store, we conducted a rigorous analysis using data from the Energy Information Administration and Google Trends. Surprisingly, our findings reveal a remarkably strong correlation coefficient of 0.9915372 and a statistically significant p-value < 0.01 for the period spanning from 2007 to 2021. Perhaps this illuminates a bright new path for solar energy research or simply suggests that people are on the hunt for affordable trinkets after saving on electricity bills. Either way, our research sheds light on an unexpected and amusing correlation that is sure to spark a few knowing chuckles.

[[INTRDUCTION]]
In the illustrious world of academia, where serious faces and even more serious statistical analyses reign supreme, it is not often that one encounters a research topic as peculiar and eyebrow-raising as the unlikely correlation between solar power generation in Rwanda and the fervent quest for budget bargains at dollar stores. Yet, here we are, embarking on a scholarly journey that traverses the realms of renewable energy and frugal shopping, proving that research can illuminate the most unexpected connections – much like a motion-activated solar-powered garden light.
While the notion of solar power and dollar store searches being intertwined may initially seem as incongruous as pairing a tuxedo with flip-flops, our intrepid research team could not resist delving into this peculiar pairing. Armed with an arsenal of statistical tools, data sources, and a healthy dose of skepticism, we set out to investigate whether there was more to this correlation than meets the eye – or the photovoltaic cell.
As we tiptoed through the labyrinth of data, we found ourselves confronted with the sunny statistics of solar energy generation in Rwanda, where the pursuit of sustainable and environmentally friendly power sources has been akin to a game of "which came first, the solar panel or the egg?" Simultaneously, the virtual footprints of individuals embarking on quests for affordable treasures at dollar stores via Google searches danced in our Excel sheets, revealing a narrative that seemed as improbable as stumbling upon a mint-condition lava lamp in the clearance section of a dollar store.
In this paper, we present the findings of our unconventional investigation, unveiling a correlation coefficient of 0.9915372 that is as dazzling as a newly-installed solar array on a clear day. By leveraging data from the Energy Information Administration to quantify solar power production and Google Trends to track the ebb and flow of "dollar store near me" searches, we were able to shed light on a connection that will undoubtedly raise a few eyebrows and, hopefully, elicit more than a few wry grins from our esteemed colleagues.
As we dive into the depths of this unexpected correlation, buckle up for a ride that is as illuminating as a solar-powered LED flashlight and as delightfully perplexing as stumbling upon a knockoff version of a famous brand in a dollar store. After all, in the realm of research, sometimes the most surprising discoveries are found in the most unexpected places – much like a hidden gem unearthed at the bottom of a bargain bin.

[[RESULTS]]
In this section, we present the illuminating results of our investigation into the uncharted territory of the correlation between solar power generation in Rwanda and the fervent hunt for budget bargains at dollar stores, as revealed by Google searches for "dollar store near me". Our analysis revealed a correlation coefficient of 0.9915372, an r-squared value of 0.9831461, and a p-value of less than 0.01 for the period spanning from 2007 to 2021. These results shine bright like a high-wattage solar-powered floodlight, leaving no room for doubt about the robustness and statistical significance of the relationship between these seemingly unrelated phenomena.
The strong correlation coefficient of 0.9915372 suggests that the connection between solar power generation in Rwanda and the quest for budget bargains at dollar stores is as unmistakable as a neon sign in a dark alley. This finding dances across the academic stage, dazzling skeptics and supporters alike with its resilience to statistical scrutiny. The r-squared value of 0.9831461 further emphasizes the tightness of the relationship, indicating that approximately 98.31% of the variance in "dollar store near me" searches can be explained by the variance in solar power generation in Rwanda. It's as if the solar panels themselves are beaming out a message: "Come find your bargains here!"
Yet, we must not overlook the significance of the p-value being less than 0.01, a result that is about as rare as finding an unopened pack of batteries at a dollar store. This p-value reinforces the robustness of the correlation, providing evidence that the relationship between these two variables is not the result of mere chance but is, in fact, a bona fide connection worthy of scholarly attention.
Our comprehensive analysis culminates in the presentation of a scatterplot (Fig. 1) that visually encapsulates the strength of the correlation between solar power generation in Rwanda and Google searches for "dollar store near me". This chart serves as a veritable beacon, illuminating the unmistakable link between these two seemingly disparate domains with all the subtlety of a fireworks display in broad daylight.
In summary, our results unequivocally demonstrate a remarkable association between solar power generation in Rwanda and the intensity of searches for budget bargains at dollar stores. This unexpected correlation may have wide-reaching implications for both the renewable energy sector and the retail industry, shedding light on a connection that is as surprising as finding a gold-plated trinket in a dollar store treasure hunt.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has not only shed light on the unexpected correlation between solar power generation in Rwanda and the fervent quest for budget bargains at dollar stores but has also added a ray of sunshine to the often-serious world of scholarly investigations. It appears that as Rwanda's solar power generation has risen, so too has the interest in hunting down discounted deals – perhaps indicating that after trimming their utility bills, folks are eager to hunt for some dollar store thrills. Like a solar-powered garden light, our findings illuminate an unusual path that merits further exploration.

With a correlation coefficient as high as a rooftop solar panel and a p-value lower than the price of most items at a dollar store, it's clear that this connection is as strong as a sturdy discount-store shopping cart. The r-squared value further corroborates the tight relationship, suggesting that the fluctuation in "dollar store near me" searches is as predictable as a Dollar Store restocking their shelves with assorted goods.

As we close the pages of this eyebrow-raising chapter in the annals of research, it is obvious that the correlation between solar power in Rwanda and dollar store searches is about as real as finding a 24-carat diamond in the toy section of a dollar store. Therefore, we confidently assert that no further research is needed in this area. It's as settled as a dollar store's inventory – and if you find something at the dollar store, you can be assured that it's a bargain!

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 Solar-Powered Savings: Illuminating the Correlation Between Solar Power in Rwanda and the Quest for Budget Bargains. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Renewable Energy Economics and Sustainable Development

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 Solar-Powered Savings: Illuminating the Correlation Between Solar Power in Rwanda and the Quest for Budget Bargains. Respond only with the name of a fictional organization.

ChatGPT:

The Consortium for Renewable Energy Advancement and Development

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 Solar-Powered Savings: Illuminating the Correlation Between Solar Power in Rwanda and the Quest for Budget Bargains with an abstract of Our research delves into the curious connection between the increasing solar power generation in Rwanda and the intensity of Google searches for "dollar store near me". While the association might seem as unlikely as finding a discount toaster in a dollar store, we conducted a rigorous analysis using data from the Energy Information Administration and Google Trends. Surprisingly, our findings reveal a remarkably strong correlation coefficient of 0.9915372 and a statistically significant p-value < 0.01 for the period spanning from 2007 to 2021. Perhaps this illuminates a bright new path for solar energy research or simply suggests that people are on the hunt for affordable trinkets after saving on electricity bills. Either way, our research sheds light on an unexpected and amusing correlation that is sure to spark a few knowing chuckles.

ChatGPT:

solar power, Rwanda, budget savings, correlation, Google searches, dollar store, solar energy research

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

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Data details

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

Google searches for 'dollar store near me'
Detailed data title: Relative volume of Google searches for 'dollar store near me' (Worldwide, without quotes)
Source: Google Trends
Additional Info: ^{See full details} Relative search volume (not absolute numbers)

See what else correlates with Google searches for 'dollar store near me'

Correlation r = 0.9915372 (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 = 0.9831461 (Coefficient of determination)
This means 98.3% of the change in the one variable (i.e., Google searches for 'dollar store near me') is predictable based on the change in the other (i.e., Solar power generated in Rwanda) over the 15 years from 2007 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.51E-13.^Show 0.0000000000006506925602242685
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 0.99 in 6.51E-11% of random cases. Said differently, if you correlated 1,536,824,087,331 random variables^Note You don't actually need 1 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 14 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 14 because we have two variables measured over a period of 15 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.97, 1 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{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.

	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Solar power generated in Rwanda (Billion kWh)	0.0002	0.0002	0.0002	0.0002	0.0002	0.001	0.001	0.007	0.021	0.03	0.037	0.054	0.056	0.056	0.056
Google searches for 'dollar store near me' (Rel. search volume)	0.181818	0	0	0	0	1	3.25	5.75	16.0833	30.75	45.8333	56.8333	69.1667	72.5	66.9167

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([0.0002,0.0002,0.0002,0.0002,0.0002,0.001,0.001,0.007,0.021,0.03,0.037,0.054,0.056,0.056,0.056,])
array_2 = np.array([0.181818,0,0,0,0,1,3.25,5.75,16.0833,30.75,45.8333,56.8333,69.1667,72.5,66.9167,])
array_1_name = "Solar power generated in Rwanda"
array_2_name = "Google searches for 'dollar store near me'"

# 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 Solar power generated in Rwanda
Line chart for only Google searches for 'dollar store near me'
AI-generated correlation image
The spurious research paper: Solar-Powered Savings: Illuminating the Correlation Between Solar Power in Rwanda and the Quest for Budget Bargains

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Correlation ID: 1597 · Black Variable ID: 23927 · Red Variable ID: 1375


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