Spurious correlation #1,520 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Wind power generated in Honduras and the second variable is The number of pharmacists in North Carolina. The chart goes from 2011 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 Wind power generated in Honduras and the second variable is The number of pharmacists in North Carolina. The chart goes from 2011 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the wind power in Honduras increased, so did the number of pharmacy students visiting the country for "high windspiration" to excel in their studies.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a sprawling steampunk cityscape, with towering wind turbines integrated seamlessly into the architecture. The city should have an industrial, Victorian-era feel, with gears, pipes, and steam-powered machinery. In the foreground, show a group of dedicated pharmacists working in a vintage apothecary, surrounded by antique medicine bottles and elaborate steampunk equipment. The scene should exude an atmosphere of innovation, community care, and the harmonious coexistence of advanced technology and traditional craftsmanship. 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: Wind power generated in Honduras and The number of pharmacists in North Carolina. 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: Steampunk An image that looks like it is a scene from a Pixar movie a Polaroid photo Cyber folk High-tech
ChatGPT: Steampunk

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 Wind power generated in Honduras and The number of pharmacists in North Carolina together. Keep the description simple.
ChatGPT: In a sprawling landscape in Honduras, rows of towering wind turbines harness the power of the breeze. Meanwhile, in the bustling streets of North Carolina, a team of dedicated pharmacists work diligently to fill prescriptions and provide expert care to their community.

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: [ Steampunk ] and depicting this scene: In a sprawling landscape in Honduras, rows of towering wind turbines harness the power of the breeze. Meanwhile, in the bustling streets of North Carolina, a team of dedicated pharmacists work diligently to fill prescriptions and provide expert care to their community. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a sprawling steampunk cityscape, with towering wind turbines integrated seamlessly into the architecture. The city should have an industrial, Victorian-era feel, with gears, pipes, and steam-powered machinery. In the foreground, show a group of dedicated pharmacists working in a vintage apothecary, surrounded by antique medicine bottles and elaborate steampunk equipment. The scene should exude an atmosphere of innovation, community care, and the harmonious coexistence of advanced technology and traditional craftsmanship.

*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 humerus 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 Wind power generated in Honduras caused The number of pharmacists in North Carolina to increase. Add a funny one-liner about one of the variables at the end.

AI academic paper

(Because p < 0.01)

The Wind in Honduras Blowing Northward: A Correlative Chronicle of Pharmacist Population Popping Up

The Journal of Whimsical Wind Studies

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Wind power generated in Honduras and The number of pharmacists in North Carolina. 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 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]]
The Wind in Honduras Blowing Northward: A Correlative Chronicle of Pharmacist Population Popping Up

[[ABSTRACT]]
This research paper delves into the delightfully bizarre world of correlation between the wind power generated in Honduras and the number of pharmacists in North Carolina. With a verifiable correlation coefficient of 0.9470731 and p < 0.01 over the decade from 2011 to 2021, it's clear that there's more than just hot air at play here. Could it be that the gentle Honduran breeze is whispering secrets directly into the ears of North Carolinian pharmacists, inspiring them to stock more medications or creating a demand for them to work longer hours? Or, could this be a case of pure coincidence, where the wind power and pharmacy numbers in these distant regions are dancing to the same tune without even realizing it? Our findings present a whirlwind of questions, leaving one to ponder the windy connections between distant lands and professions.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The universe is a mystical place, full of unexpected connections and baffling correlations. One might think that the wind blowing through the colorful landscapes of Honduras and the number of pharmacists populating the bustling state of North Carolina have absolutely nothing in common. However, as we peel back the layers of this bizarre onion of data, we find ourselves embarking on a journey through the windy corridors of statistical analysis and the labyrinthine alleys of professional demographics.
As we delve into this peculiar pairing of wind power and pharmaceutical expertise, one can't help but ponder the whimsical possibilities of how these two seemingly disparate entities could be intertwined. Are the pharmacists in North Carolina somehow harnessing the power of the Honduran zephyrs to enhance their pharmaceutical prowess? Or perhaps, the wind is simply carrying signals that compel pharmacists in North Carolina to stock up on antihistamines and motion sickness medication? The possibilities are as limitless as the wind itself.
In this paper, we aim to unravel the enigma behind the correlation between wind power in Honduras and the pharmacist population in North Carolina. Our findings promise to whip up a gust of wonder and awe, leaving readers breathless in the face of this unexpected correlation. So, let us unfurl the sails of curiosity and embark on a journey through the breezy nexus of wind power and pharmaceutical expertise.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The study of interconnections between seemingly unrelated phenomena has often been a source of fascination and puzzlement for researchers. Numerous studies have delved into the enigmatic correlations that exist between disparate variables, with the aim of unraveling the tangled web of causation and coincidence. In "Smith et al., 2015," the authors find an intriguing association between wind patterns in Central America and their potential impact on atmospheric circulation in the Eastern United States. Similarly, "Doe and Jones, 2018" present a comprehensive analysis of the demographic distribution of healthcare professionals in different regions of the United States, shedding light on the factors that influence the density of pharmacists in North Carolina.

Expanding our horizons beyond the realm of traditional academic literature, the works of authors such as "Wind Power: Harnessing the Zephyrs" and "Pharmacists' Almanac: Medications and Meteorology" offer an alternative perspective on the potential linkages between wind power and the pharmaceutical landscape. Although these sources may verge on the fantastical, they encourage a broader consideration of the complex relationships that underpin our natural and professional environments. In a similar vein, fictional narratives such as "The Wind Whisperer's Pharmacy" and "Pharmaceutical Fables: A Tale of Two Breezes" provide imaginative accounts of the intertwining of atmospheric forces and pharmaceutical practices, prompting reflection on the whimsical possibilities that lie within our data-driven narratives.

Turning to more unconventional sources, the animated series "Gusty Gustav and the Medicine Menagerie" and the children's show "Pharmacist Farm: Windy Adventures" have been explored for potential insights into the subconscious influences of meteorological elements on the professional inclinations of pharmacists. While these sources may raise an eyebrow in academic contexts, they serve to underscore the multifaceted nature of correlation research and the unexpected sources of inspiration that may inform our understanding of complex phenomena.

This eclectic array of literature encapsulates both the serious and imaginative dimensions of our pursuit to unravel the connection between wind power in Honduras and the number of pharmacists in North Carolina. As we navigate through this swirling confluence of empirical studies, speculative musings, and unconventional inspirations, we are poised to embark on a journey that blows the winds of curiosity and amusement.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Wind power generated in Honduras and The number of pharmacists in North Carolina. 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 Bureau of Larbor Statistics . You used data from 2011 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]]
The Wind in Honduras Blowing Northward: A Correlative Chronicle of Pharmacist Population Popping Up

[[ABSTRACT]]
This research paper delves into the delightfully bizarre world of correlation between the wind power generated in Honduras and the number of pharmacists in North Carolina. With a verifiable correlation coefficient of 0.9470731 and p < 0.01 over the decade from 2011 to 2021, it's clear that there's more than just hot air at play here. Could it be that the gentle Honduran breeze is whispering secrets directly into the ears of North Carolinian pharmacists, inspiring them to stock more medications or creating a demand for them to work longer hours? Or, could this be a case of pure coincidence, where the wind power and pharmacy numbers in these distant regions are dancing to the same tune without even realizing it? Our findings present a whirlwind of questions, leaving one to ponder the windy connections between distant lands and professions.

[[INTRODUCTION]]
The universe is a mystical place, full of unexpected connections and baffling correlations. One might think that the wind blowing through the colorful landscapes of Honduras and the number of pharmacists populating the bustling state of North Carolina have absolutely nothing in common. However, as we peel back the layers of this bizarre onion of data, we find ourselves embarking on a journey through the windy corridors of statistical analysis and the labyrinthine alleys of professional demographics.
As we delve into this peculiar pairing of wind power and pharmaceutical expertise, one can't help but ponder the whimsical possibilities of how these two seemingly disparate entities could be intertwined. Are the pharmacists in North Carolina somehow harnessing the power of the Honduran zephyrs to enhance their pharmaceutical prowess? Or perhaps, the wind is simply carrying signals that compel pharmacists in North Carolina to stock up on antihistamines and motion sickness medication? The possibilities are as limitless as the wind itself.
In this paper, we aim to unravel the enigma behind the correlation between wind power in Honduras and the pharmacist population in North Carolina. Our findings promise to whip up a gust of wonder and awe, leaving readers breathless in the face of this unexpected correlation. So, let us unfurl the sails of curiosity and embark on a journey through the breezy nexus of wind power and pharmaceutical expertise.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection:
The data for wind power generated in Honduras and the number of pharmacists in North Carolina was collected from a variety of sources, primarily through the Energy Information Administration and the Bureau of Labor Statistics. Our research team scoured the depths of the internet, navigating through the virtual winds of information to gather the necessary data from the years 2011 to 2021. Like intrepid sailors navigating through stormy seas, we ventured through the digital currents to capture the elusive winds of numeric data and the pharmacy population statistics.

Wind Power Calculation:
The wind power data for Honduras was a culmination of meteorological data, turbine efficiency, and energy transmission losses - a wind of figures, if you will. Harnessing the gales of data from various meteorological stations and wind farms, our team calculated the total wind power generated in Honduras. We then harmonized the wind data, much like a symphony conductor orchestrating a cacophony of winds, to create a unified representation of the Honduran wind power over the years under study.

Pharmacist Population Counting:
Counting the number of pharmacists in North Carolina was akin to unraveling a tempestuous whirl of professional demographics. Our team navigated the labyrinth of healthcare employment figures, carefully tallying the number of pharmacists populating the rolling hills of North Carolina. Much like enigmatic wind whispers, the data revealed the ebb and flow of pharmaceutical professionals in the state, offering a tantalizing glimpse into the gusty world of pharmacist demographics.

Statistical Analysis:
To explore the potential correlation between wind power in Honduras and the pharmacist population in North Carolina, we employed rigorous statistical analyses. Our team leveraged the robust tools of correlation coefficients, regression analyses, and p-values to unravel the mysterious intertwining of these seemingly disparate phenomena. Like skilled wind surfers riding the waves of data, we navigated through the statistical winds to reveal the tantalizing correlation between these enigmatic variables.

Regression Models:
In addition to exploring simple correlations, we constructed elegant regression models to capture the intricate dance of wind power and pharmacist numbers. The modeling process was akin to choreographing a graceful ballroom dance, as we sought to unveil the nuanced interplay between the winds of Honduras and the pharmaceutical landscape of North Carolina. Through these models, we endeavored to encapsulate the complex and captivating relationship between these variables, much like a delicate dance guided by the winds of statistical elegance.

Sensitivity Analysis:
Our investigation also included a sensitivity analysis to assess the robustness of the observed correlation and regression results. Like a weather vane pivoting in the changing breezes, we sought to gauge the stability of our findings in the face of potential data perturbations and methodological variations. This allowed us to discern the resilience of our observed connections in the face of fluctuating winds of uncertainty.

Limitations:
It is important to acknowledge the limitations of this study. Despite meticulous data collection and rigorous analyses, our research is not immune to the gusts of limitations that buffet all scientific endeavors. Factors such as potential confounding variables, regional economic dynamics, and the intricate web of healthcare policies may flutter in the winds of uncertainty, casting shadows over our findings.

In summary, our methodology encapsulated a journey through the winds of data collection, the turbulent seas of statistical analyses, and the graceful waltz of regression modeling, all in pursuit of unraveling the mysterious connection between the wind power of Honduras and the pharmacist population of North Carolina.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Wind power generated in Honduras and The number of pharmacists in North Carolina. 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]]
The Wind in Honduras Blowing Northward: A Correlative Chronicle of Pharmacist Population Popping Up

[[ABSTRACT]]
This research paper delves into the delightfully bizarre world of correlation between the wind power generated in Honduras and the number of pharmacists in North Carolina. With a verifiable correlation coefficient of 0.9470731 and p < 0.01 over the decade from 2011 to 2021, it's clear that there's more than just hot air at play here. Could it be that the gentle Honduran breeze is whispering secrets directly into the ears of North Carolinian pharmacists, inspiring them to stock more medications or creating a demand for them to work longer hours? Or, could this be a case of pure coincidence, where the wind power and pharmacy numbers in these distant regions are dancing to the same tune without even realizing it? Our findings present a whirlwind of questions, leaving one to ponder the windy connections between distant lands and professions.

[[LITERATURE REVIEW]]
The study of interconnections between seemingly unrelated phenomena has often been a source of fascination and puzzlement for researchers. Numerous studies have delved into the enigmatic correlations that exist between disparate variables, with the aim of unraveling the tangled web of causation and coincidence. In "Smith et al., 2015," the authors find an intriguing association between wind patterns in Central America and their potential impact on atmospheric circulation in the Eastern United States. Similarly, "Doe and Jones, 2018" present a comprehensive analysis of the demographic distribution of healthcare professionals in different regions of the United States, shedding light on the factors that influence the density of pharmacists in North Carolina.
Expanding our horizons beyond the realm of traditional academic literature, the works of authors such as "Wind Power: Harnessing the Zephyrs" and "Pharmacists' Almanac: Medications and Meteorology" offer an alternative perspective on the potential linkages between wind power and the pharmaceutical landscape. Although these sources may verge on the fantastical, they encourage a broader consideration of the complex relationships that underpin our natural and professional environments. In a similar vein, fictional narratives such as "The Wind Whisperer's Pharmacy" and "Pharmaceutical Fables: A Tale of Two Breezes" provide imaginative accounts of the intertwining of atmospheric forces and pharmaceutical practices, prompting reflection on the whimsical possibilities that lie within our data-driven narratives.
Turning to more unconventional sources, the animated series "Gusty Gustav and the Medicine Menagerie" and the children's show "Pharmacist Farm: Windy Adventures" have been explored for potential insights into the subconscious influences of meteorological elements on the professional inclinations of pharmacists. While these sources may raise an eyebrow in academic contexts, they serve to underscore the multifaceted nature of correlation research and the unexpected sources of inspiration that may inform our understanding of complex phenomena.
This eclectic array of literature encapsulates both the serious and imaginative dimensions of our pursuit to unravel the connection between wind power in Honduras and the number of pharmacists in North Carolina. As we navigate through this swirling confluence of empirical studies, speculative musings, and unconventional inspirations, we are poised to embark on a journey that blows the winds of curiosity and amusement.

[[RESULTS]]
The investigation into the relationship between wind power generated in Honduras and the number of pharmacists in North Carolina yielded an astonishingly high correlation coefficient of 0.9470731, an r-squared value of 0.8969474, and a p-value of less than 0.01. These results suggest a remarkably strong association between these two seemingly unrelated variables. It appears that the wind in Honduras may indeed be blowing some pharmacy-related secrets northward, much to the surprise of our research team.
The figure (Fig. 1) included in this paper demonstrates the robust correlation between wind power in Honduras and the pharmacist population in North Carolina. The scatterplot reveals a clear and compelling linear relationship, leaving little room for doubt regarding the connection between these distant phenomena.
As we interpret these findings, one cannot help but entertain the whimsical notion of pharmacists in North Carolina tuning their pharmaceutical endeavors to the rhythm of the Honduran breezes. Whether the wind is carrying cryptic messages or simply stirring the pot of statistical curiosity, the implications of this correlation are as intriguing as they are unexpected. This correlation is truly a breath of fresh air in the world of statistical analysis, demonstrating that the winds of correlation can blow in delightfully unpredictable directions.
In conclusion, our research has unveiled an unexpectedly strong correlation between wind power in Honduras and the number of pharmacists in North Carolina, challenging conventional notions of causality and geographical influence. This correlation presents a riveting enigma, inviting further exploration and speculation into the unforeseen connections between distant lands and professional domains.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our investigation have unveiled a notable and somewhat surprising correlation between wind power generated in Honduras and the number of pharmacists in North Carolina. The remarkably high correlation coefficient and r-squared value indicate a strong linear relationship between these seemingly disparate variables. This finding echoes the speculations put forth in "Smith et al., 2015" and "Doe and Jones, 2018," which suggested the potential influence of atmospheric forces on professional domains.

But let's not blow this out of proportion. While the correlation may seem striking, we must exercise caution in ascribing causality to this association. After all, it's not every day that one can declare that the wind from afar is directly responsible for the distribution of pharmacists in a distant state. Nonetheless, the strength of the correlation coefficient and the statistical significance of the p-value lend credence to the idea that there may indeed be something to this windy connection.

Our results lend support to the whimsical musings of the authors of "Wind Power: Harnessing the Zephyrs" and "Pharmacists' Almanac: Medications and Meteorology," who entertained the possibility of atmospheric forces exerting a subtle influence on professional inclinations. Perhaps there is a gust of truth in their unconventional perspectives, suggesting that the winds of change may indeed extend to the realm of pharmaceutical endeavors.

It is important to note that our findings do not provide a definitive explanation for this correlation. Yet, they do serve as a zephyr of inspiration for future research endeavors, inviting further exploration into the potential mechanisms underlying this unexpected relationship. So, while the wind may have whispered some statistical secrets in our ears, the full narrative of this correlation remains to be unraveled.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Wind power generated in Honduras and The number of pharmacists in North Carolina. 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]]
The Wind in Honduras Blowing Northward: A Correlative Chronicle of Pharmacist Population Popping Up

[[ABSTRACT]]
This research paper delves into the delightfully bizarre world of correlation between the wind power generated in Honduras and the number of pharmacists in North Carolina. With a verifiable correlation coefficient of 0.9470731 and p < 0.01 over the decade from 2011 to 2021, it's clear that there's more than just hot air at play here. Could it be that the gentle Honduran breeze is whispering secrets directly into the ears of North Carolinian pharmacists, inspiring them to stock more medications or creating a demand for them to work longer hours? Or, could this be a case of pure coincidence, where the wind power and pharmacy numbers in these distant regions are dancing to the same tune without even realizing it? Our findings present a whirlwind of questions, leaving one to ponder the windy connections between distant lands and professions.

[[INTRDUCTION]]
The universe is a mystical place, full of unexpected connections and baffling correlations. One might think that the wind blowing through the colorful landscapes of Honduras and the number of pharmacists populating the bustling state of North Carolina have absolutely nothing in common. However, as we peel back the layers of this bizarre onion of data, we find ourselves embarking on a journey through the windy corridors of statistical analysis and the labyrinthine alleys of professional demographics.
As we delve into this peculiar pairing of wind power and pharmaceutical expertise, one can't help but ponder the whimsical possibilities of how these two seemingly disparate entities could be intertwined. Are the pharmacists in North Carolina somehow harnessing the power of the Honduran zephyrs to enhance their pharmaceutical prowess? Or perhaps, the wind is simply carrying signals that compel pharmacists in North Carolina to stock up on antihistamines and motion sickness medication? The possibilities are as limitless as the wind itself.
In this paper, we aim to unravel the enigma behind the correlation between wind power in Honduras and the pharmacist population in North Carolina. Our findings promise to whip up a gust of wonder and awe, leaving readers breathless in the face of this unexpected correlation. So, let us unfurl the sails of curiosity and embark on a journey through the breezy nexus of wind power and pharmaceutical expertise.

[[RESULTS]]
The investigation into the relationship between wind power generated in Honduras and the number of pharmacists in North Carolina yielded an astonishingly high correlation coefficient of 0.9470731, an r-squared value of 0.8969474, and a p-value of less than 0.01. These results suggest a remarkably strong association between these two seemingly unrelated variables. It appears that the wind in Honduras may indeed be blowing some pharmacy-related secrets northward, much to the surprise of our research team.
The figure (Fig. 1) included in this paper demonstrates the robust correlation between wind power in Honduras and the pharmacist population in North Carolina. The scatterplot reveals a clear and compelling linear relationship, leaving little room for doubt regarding the connection between these distant phenomena.
As we interpret these findings, one cannot help but entertain the whimsical notion of pharmacists in North Carolina tuning their pharmaceutical endeavors to the rhythm of the Honduran breezes. Whether the wind is carrying cryptic messages or simply stirring the pot of statistical curiosity, the implications of this correlation are as intriguing as they are unexpected. This correlation is truly a breath of fresh air in the world of statistical analysis, demonstrating that the winds of correlation can blow in delightfully unpredictable directions.
In conclusion, our research has unveiled an unexpectedly strong correlation between wind power in Honduras and the number of pharmacists in North Carolina, challenging conventional notions of causality and geographical influence. This correlation presents a riveting enigma, inviting further exploration and speculation into the unforeseen connections between distant lands and professional domains.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has blown the lid off a truly breezy brainteaser, shedding an unexpected gust of insight into the windswept corridors of statistical analysis. The remarkably strong correlation between wind power in Honduras and the number of pharmacists in North Carolina has left our research team in a whirlwind of wonder. Who would have thought that the gentle Honduran zephyrs could hold the key to the pharmaceutical proclivities of North Carolinian pharmacists?

As we reflect on these findings, one can't help but marvel at the windy dance of statistical serendipity. It's as if the wind in Honduras is whispering secrets to the pharmacists of North Carolina, nudging them to stock more cough syrup and antihistamines. Or perhaps, the wind is simply playing a game of statistical hide-and-seek, leaving us to ponder the invisible threads that weave through the fabric of professional demographics.

Our investigation has opened a Pandora's box of whimsical possibilities, compelling us to contemplate the airy mysteries of correlation and causation. With a correlation coefficient as strong as a hurricane's gust and a p-value as rare as a calm day in the Windy City, this correlation has blown away our expectations and left us reaching for our metaphorical windbreakers.

In light of these findings, it seems that no further research is needed in this area, as we have successfully breezed through the labyrinth of statistical inquiry and uncovered the unforeseen connection between distant lands and professional domains. The winds of correlation have spoken, and they have left us marveling at the capricious pathways through which statistical breezes can blow.

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 The Wind in Honduras Blowing Northward: A Correlative Chronicle of Pharmacist Population Popping Up. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Whimsical Wind Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Wind in Honduras Blowing Northward: A Correlative Chronicle of Pharmacist Population Popping Up. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Ethereal Pharmaceutical Phenomena Research

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Wind in Honduras Blowing Northward: A Correlative Chronicle of Pharmacist Population Popping Up with an abstract of This research paper delves into the delightfully bizarre world of correlation between the wind power generated in Honduras and the number of pharmacists in North Carolina. With a verifiable correlation coefficient of 0.9470731 and p < 0.01 over the decade from 2011 to 2021, it's clear that there's more than just hot air at play here. Could it be that the gentle Honduran breeze is whispering secrets directly into the ears of North Carolinian pharmacists, inspiring them to stock more medications or creating a demand for them to work longer hours? Or, could this be a case of pure coincidence, where the wind power and pharmacy numbers in these distant regions are dancing to the same tune without even realizing it? Our findings present a whirlwind of questions, leaving one to ponder the windy connections between distant lands and professions.

ChatGPT:

"wind power," "pharmacists," "Honduras," "North Carolina," "correlation coefficient," "pharmacy numbers," "Honduran breeze," "pharmacy demand," "wind influence on professions," "correlation study," "regional profession trends," "wind patterns and profession data," "geographical influence on professions," "pharmacist workforce 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

Wind power generated in Honduras
Detailed data title: Total wind power generated in Honduras in billion kWh
Source: Energy Information Administration
See what else correlates with Wind power generated in Honduras

The number of pharmacists in North Carolina
Detailed data title: BLS estimate of pharmacists in North Carolina
Source: Bureau of Larbor Statistics
See what else correlates with The number of pharmacists in North Carolina

Correlation r = 0.9470731 (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 = 0.8969474 (Coefficient of determination)
This means 89.7% of the change in the one variable (i.e., The number of pharmacists in North Carolina) is predictable based on the change in the other (i.e., Wind power generated in Honduras) over the 11 years from 2011 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 9.8E-6.^Show 0.0000097885483594195300000000
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 0.95 in 0.00098% of random cases. Said differently, if you correlated 102,160 random variables^Note You don't actually need 102 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 10 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 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.

[ 0.8, 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.

	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Wind power generated in Honduras (Billion kWh)	0.117	0.338	0.31	0.398	0.665	0.583	0.578	0.929	0.818	0.707	0.803674
The number of pharmacists in North Carolina (Pharmacists)	8240	8580	8730	9010	9420	9550	9430	9970	10020	10110	10350

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([0.117,0.338,0.31,0.398,0.665,0.583,0.578,0.929,0.818,0.707,0.803674,])
array_2 = np.array([8240,8580,8730,9010,9420,9550,9430,9970,10020,10110,10350,])
array_1_name = "Wind power generated in Honduras"
array_2_name = "The number of pharmacists in North Carolina"

# 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 Wind power generated in Honduras
Line chart for only The number of pharmacists in North Carolina
AI-generated correlation image
The spurious research paper: The Wind in Honduras Blowing Northward: A Correlative Chronicle of Pharmacist Population Popping Up

View another random correlation

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Correlation ID: 1520 · Black Variable ID: 23722 · Red Variable ID: 12372


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