Spurious correlation #3,763 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Bachelor's degrees awarded in law enforcement and the second variable is Hydopower energy generated in Uruguay. The chart goes from 2012 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 Bachelor's degrees awarded in law enforcement and the second variable is Hydopower energy generated in Uruguay. The chart goes from 2012 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As more people pursued law enforcement degrees, they became experts at current flow and decided to dam up the rivers for hydroelectric power, leading to a shocking increase in Uruguay's hydropower energy production. It's a case of higher education making waves in renewable energy!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image that showcases a university graduation ceremony, with the graduates wearing law enforcement attire and proudly receiving their Bachelor's degrees. In the background, illustrate a group of police officers cracking down on energy theft, leading to an increase in hydropower energy generation in Uruguay. The focus should be on the rushing waters of a powerful hydropower plant, symbolizing the surge in renewable energy and creating a powerful connection between crime fighting and sustainable resource utilization. Apply a glitch art style to the image, adding a touch of digital distortion and abstraction for an intriguing visual effect. 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: Bachelor's degrees awarded in law enforcement and Hydopower energy generated in Uruguay. 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: Glitch art Realistic Vaporwave An image that looks like it is a scene from a Pixar movie Photorealism
ChatGPT: Glitch art

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 Bachelor's degrees awarded in law enforcement and Hydopower energy generated in Uruguay, in the following situation: Sure thing! As the number of law enforcement degrees rises, more officers crack down on energy theft, causing a "current" surge in hydropower generation in Uruguay. This ironic twist "washes away" any doubts about the connection between crime fighting and renewable energy!. Keep the description simple.
ChatGPT: Imagine a university graduation ceremony where students in law enforcement attire proudly receive their Bachelor's degrees. As they celebrate their achievement, a group of police officers can be seen cracking down on energy theft, leading to an increase in hydropower energy generation in Uruguay. The rushing waters of a powerful hydropower plant symbolize the surge in renewable energy, creating a powerful connection between crime fighting and sustainable resource utilization.

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: [ Glitch art ] and depicting this scene: Imagine a university graduation ceremony where students in law enforcement attire proudly receive their Bachelor's degrees. As they celebrate their achievement, a group of police officers can be seen cracking down on energy theft, leading to an increase in hydropower energy generation in Uruguay. The rushing waters of a powerful hydropower plant symbolize the surge in renewable energy, creating a powerful connection between crime fighting and sustainable resource utilization. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that showcases a university graduation ceremony, with the graduates wearing law enforcement attire and proudly receiving their Bachelor's degrees. In the background, illustrate a group of police officers cracking down on energy theft, leading to an increase in hydropower energy generation in Uruguay. The focus should be on the rushing waters of a powerful hydropower plant, symbolizing the surge in renewable energy and creating a powerful connection between crime fighting and sustainable resource utilization. Apply a glitch art style to the image, adding a touch of digital distortion and abstraction for an intriguing visual effect.

*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 Bachelor's degrees awarded in law enforcement caused Hydopower energy generated in Uruguay to increase. Include one good pun.

AI academic paper

(Because p < 0.05)

Chasing Convictions: Exploring the Link Between Bachelor's Degrees in Law Enforcement and Hydropower Energy Generation in Uruguay

The Journal of Interdisciplinary Law and Sustainable Energy

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 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 Bachelor's degrees awarded in law enforcement and Hydopower energy generated in Uruguay. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from National Center for Education Statistics and Energy Information Administration . You used data from 2012 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]]
Chasing Convictions: Exploring the Link Between Bachelor's Degrees in Law Enforcement and Hydropower Energy Generation in Uruguay

[[ABSTRACT]]
This paper investigates the fascinating and often overlooked connection between the number of Bachelor's degrees awarded in law enforcement and the hydropower energy generated in the charming country of Uruguay. Through meticulous data analysis from the National Center for Education Statistics and the Energy Information Administration, we unveil a statistically significant correlation coefficient of 0.7497804 and p < 0.05 for the time span from 2012 to 2021. The results tantalizingly hint at a potential symbiotic relationship between the pursuit of justice and the flowing force of hydropower. While some might find this linkage a mere coincidence, we don't take these findings lightly – much like a buoyant hydropower turbine. This research serves as a reminder that the impacts of academic pursuits can flow downstream, shaping unexpected areas of society. So, let us not withhold the floodgates of curiosity but instead navigate these uncharted waters with a thoroughly grounded approach.

[[INTRODUCTION]]
The intertwining of academia and industry has long been a source of fascination for researchers seeking to uncover hidden connections that defy conventional wisdom. In the vast sea of academic inquiry, one might never expect the turbulent currents of law enforcement education to converge with the tranquil flow of hydropower energy generation. Yet, here we are, ready to dive into the depths of this unexpected linkage.
In recent years, Uruguay has emerged as a pioneer in renewable energy, with hydropower playing a substantial role in the country's energy landscape. Simultaneously, the pursuit of justice has been a cornerstone of societal progress, reflected in the conferral of Bachelor's degrees in law enforcement. As disparate as these two domains may seem, they serve as the focal points of our investigation.
It is worth noting that while the relationship between law enforcement education and hydropower energy generation may raise some eyebrows, our inquiry is not driven solely by whimsy. The statistical findings we present in this paper are as solid as the sturdiest dam, providing concrete evidence of a meaningful association. While some may view our pursuit as akin to chasing mirages in the desert, we firmly believe that the convergence of these two seemingly unrelated fields holds promise for uncovering novel insights.
As we delve into the depths of this intriguing intersection, we are reminded of the importance of remaining open to unexpected connections and the underlying currents that shape our world. So, without further ado, let us embark on this scholarly journey, armed with data, determination, and maybe just a sprinkle of hydro-powered humor.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the enigmatic entanglement between Bachelor's degrees in law enforcement and hydropower energy generation in Uruguay, our research team employed a methodological approach that could be likened to navigating the winding path of a river delta – complex, meandering, and occasionally full of unexpected surprises.

Data Collection:
We meticulously combed through the National Center for Education Statistics and the Energy Information Administration, scouring through an abundance of numerical tributaries to capture the essence of Bachelor's degrees awarded in law enforcement and hydropower energy generated in Uruguay from 2012 to 2021. Our data collection process may have involved some late nights spent staring at computer screens, resembling the intensity of a surveillance stakeout, but we emerged triumphant, armed with a bounty of statistical knowledge.

Correlation Analysis:
With a firm grip on our dataset, we fervently applied statistical tools to uncover the potential relationship between these seemingly disparate variables. Utilizing the power of correlation analysis, we sought to ascertain if the number of Bachelor's degrees in law enforcement presents a buoyant influence on the hydropower energy generated in Uruguay. This step required rigorous number-crunching, akin to the meticulous calculation of energy output from a hydroelectric dam – every variable was scrutinized with scientific precision.

Statistical Significance:
In our pursuit of enlightening findings, we didn't merely settle for statistical superficiality; instead, we delved deeper to uncover the metaphorical currents that underpin our data. Through the application of appropriate tests, we scrutinized the statistical significance of our results, ensuring that our findings were as sturdy as a well-constructed hydroelectric powerhouse. The p-value that emerged from our analysis served as a beacon of statistical significance, guiding us towards the promising shores of meaningful correlation.

Potential Confounders:
In our journey through the tumultuous waters of statistical analysis, we remained vigilant for potential confounders that could ripple through our results, distorting the clarity of our findings. While we cannot claim to have uncovered every hidden eddy within our dataset, we carefully considered external factors that might play a role in shaping the link between law enforcement education and hydropower energy generation. As we navigated these potential confounding currents, we remained cognizant of the need for robust analysis in the face of potential turbulence.

Limitations:
As much as we would love to present our findings as an unquestionable downpour of irrefutable evidence, we acknowledge the limitations inherent in our methodology. The reliance on existing datasets may have presented the occasional obstacle, akin to navigating a river's course with a slightly outdated map. Additionally, the complexity of societal and educational dynamics cannot be fully encapsulated within numerical data alone, leaving some facets of this intricate relationship uncharted.

Ultimately, our methodology served as the sturdy vessel that carried us through the unpredictable waters of statistical analysis, guiding us towards the shores of meaningful insight. As we set sail on this scholarly expedition, we remained ever open to the unexpected eddies and undercurrents that shaped our findings, ensuring that our pursuit of knowledge remained as dynamic and unpredictable as the very forces we sought to understand.

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 Bachelor's degrees awarded in law enforcement and Hydopower energy generated in Uruguay. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
Chasing Convictions: Exploring the Link Between Bachelor's Degrees in Law Enforcement and Hydropower Energy Generation in Uruguay

[[ABSTRACT]]
This paper investigates the fascinating and often overlooked connection between the number of Bachelor's degrees awarded in law enforcement and the hydropower energy generated in the charming country of Uruguay. Through meticulous data analysis from the National Center for Education Statistics and the Energy Information Administration, we unveil a statistically significant correlation coefficient of 0.7497804 and p < 0.05 for the time span from 2012 to 2021. The results tantalizingly hint at a potential symbiotic relationship between the pursuit of justice and the flowing force of hydropower. While some might find this linkage a mere coincidence, we don't take these findings lightly – much like a buoyant hydropower turbine. This research serves as a reminder that the impacts of academic pursuits can flow downstream, shaping unexpected areas of society. So, let us not withhold the floodgates of curiosity but instead navigate these uncharted waters with a thoroughly grounded approach.

[[LITERATURE REVIEW]]
Previous studies have delved into the intriguing realm of educational pursuits and their unforeseen impacts on various sectors of society. Smith and Doe (2017) explored the correlation between education in criminal justice and its effects on societal structures, while Jones et al. (2019) investigated the influence of academic degrees on sustainable energy practices. However, none of these studies have ventured into the uncharted waters of connecting law enforcement education with hydropower energy generation, making our research a groundbreaking expedition into unconventional territory.
In "The Green Side of Law Enforcement" by Greenfield (2015), the author discusses the role of law enforcement in environmental conservation efforts, highlighting the potential for synergy between the disciplines of justice and sustainability. Meanwhile, "Renewable Energy: Myth or Reality" by Energy Expert (2018) presents a comprehensive analysis of hydropower as a renewable energy source, shedding light on the considerable impact of hydroelectricity production in countries like Uruguay.
In a rather unconventional twist, the fiction novel "The Case of the Mysterious Micro Hydro" by Wattson (2013) presents a thrilling tale of a detective who uncovers a secret hydropower project while investigating a crime in rural Uruguay. This fictional work, while not rooted in empirical research, offers a whimsical glimpse into the intersection of law enforcement and hydropower in the context of a captivating mystery.
On a more lighthearted note, the animated series "Hydropower Heroes" and the children's show "Law & Order: Junior Detectives" may seem like mere entertainment, but their portrayal of law enforcement and environmental conservation inadvertently sparks curiosity about the potential connections between the two realms.
With these diverse sources in mind, we approach our investigation with an appreciation for the multi-faceted nature of our topic, acknowledging the need to navigate through serious scholarship, imaginative narratives, and even animated interpretations. After all, who said academia can't have a splash of humor and creativity?

[[RESULTS]]
The statistical analysis revealed a robust correlation coefficient of 0.7497804 between the number of Bachelor's degrees awarded in law enforcement and the hydropower energy generated in Uruguay. This finding indicates a strong positive relationship between the two variables. The coefficient of determination (r-squared) of 0.5621707 suggests that approximately 56.22% of the variability in hydropower energy generation can be explained by the number of law enforcement degrees awarded. Moreover, the p-value of less than 0.05 further confirms the statistical significance of this relationship, validating the legitimacy of our findings.
Figure 1 provides a visual representation of the correlation, illustrating the magnetic interplay between the pursuit of justice through academic endeavors and the electrifying impact on hydropower energy generation. The scatterplot captivates the eye much like a thrilling crime novel, as it unveils the compelling association between these seemingly disparate domains.
The results tantalizingly hint at a potential symbiotic relationship, a synergy reminiscent of partners in law and energy, working hand in hand for the betterment of society. These findings may leave some scratching their heads, wondering how academic pursuits and hydraulic power can find common ground. However, as researchers, we must not ignore the current of evidence that flows through our analysis.
This statistical connection brings to light the notion that the effects of education can permeate unexpected sectors of society with the force of a rushing river. It serves as a reminder that academic pursuits, much like hydropower, have the potential to shape environments far beyond their immediate scope. Our findings extend an invitation to further explore the undercurrents of influence that link academic pursuits to tangible outcomes, perhaps even sparking a new wave of interdisciplinary investigation.
In conclusion, the significant correlation uncovered in this study sheds light on the intricate interplay between education and energy generation, reminding us that academic passion and energy production can indeed be fluidly connected. As we stand at the confluence of law enforcement education and hydropower energy generation, we are compelled to navigate these uncharted waters with both precision and humor, buoyed by the unexpected revelations that research can unearth.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The correlation found between the number of Bachelor's degrees awarded in law enforcement and hydropower energy generated in Uruguay has sparked more excitement than a police chase in a superhero movie. Our results align with previous studies that have emphasized the potential interconnectedness of seemingly unrelated domains, such as education and environmental sustainability. The statistically significant correlation coefficient of 0.7497804 and p < 0.05 that we've uncovered provides empirical support for the idea that academic pursuits in law enforcement can exert a tangible influence on the generation of hydropower energy.

We cannot overlook the prior literature's unconventional inclinations, including the exploration of law enforcement's role in environmental conservation as seen in Greenfield's "The Green Side of Law Enforcement." This connection takes center stage in our findings, revealing a substantial relationship between law enforcement education and the level of hydropower generated. It's as if the "mysterious micro hydro" from Wattson's fiction novel is not so mysterious after all, but rather a tangible manifestation of the intertwining of academic pursuits and energy production.

The dual perspective from "Hydropower Heroes" and "Law & Order: Junior Detectives," although seemingly light-hearted, inadvertently raises thought-provoking questions about the potential interplay between the disciplines of justice and sustainability. Our study not only substantiates these playful ponderings but delves deeper into the statistical evidence backing the real-world association between law enforcement education and the generation of hydropower.

Figure 1 wonderfully captures the electrifying interplay between these unexpected bedfellows, much like a page-turner that keeps readers on the edge of their seats. Our results echo the sentiment that academic pursuits can, like hydropower, flow beyond their intended boundaries, shaping diverse environments in ways that may surprise us. It's clear that the impact of law enforcement education, much like the force of hydropower, extends far beyond what meets the eye.

As we navigate the uncharted waters of this intriguing correlation, we are propelled by the realization that academic research can unearth unexpected truths with the force of a rushing river. We are poised to contribute to a new wave of interdisciplinary investigation, buoyed not only by our findings but also by the humorous and creative undertones that have colored our research journey. Our study encourages a light-hearted and imaginative approach to scientific exploration, proving that even the most improbable connections deserve to be examined with serious scholarly rigor.

And speaking of currents, we're undeniably swept away by the implications of our findings and look forward to further unraveling the mysteries that lie beneath the surface of academic pursuits and their impact on society – much like a captivating crime novel that keeps us guessing until the very end.

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 Bachelor's degrees awarded in law enforcement and Hydopower energy generated in Uruguay. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
Chasing Convictions: Exploring the Link Between Bachelor's Degrees in Law Enforcement and Hydropower Energy Generation in Uruguay

[[ABSTRACT]]
This paper investigates the fascinating and often overlooked connection between the number of Bachelor's degrees awarded in law enforcement and the hydropower energy generated in the charming country of Uruguay. Through meticulous data analysis from the National Center for Education Statistics and the Energy Information Administration, we unveil a statistically significant correlation coefficient of 0.7497804 and p < 0.05 for the time span from 2012 to 2021. The results tantalizingly hint at a potential symbiotic relationship between the pursuit of justice and the flowing force of hydropower. While some might find this linkage a mere coincidence, we don't take these findings lightly – much like a buoyant hydropower turbine. This research serves as a reminder that the impacts of academic pursuits can flow downstream, shaping unexpected areas of society. So, let us not withhold the floodgates of curiosity but instead navigate these uncharted waters with a thoroughly grounded approach.

[[INTRDUCTION]]
The intertwining of academia and industry has long been a source of fascination for researchers seeking to uncover hidden connections that defy conventional wisdom. In the vast sea of academic inquiry, one might never expect the turbulent currents of law enforcement education to converge with the tranquil flow of hydropower energy generation. Yet, here we are, ready to dive into the depths of this unexpected linkage.
In recent years, Uruguay has emerged as a pioneer in renewable energy, with hydropower playing a substantial role in the country's energy landscape. Simultaneously, the pursuit of justice has been a cornerstone of societal progress, reflected in the conferral of Bachelor's degrees in law enforcement. As disparate as these two domains may seem, they serve as the focal points of our investigation.
It is worth noting that while the relationship between law enforcement education and hydropower energy generation may raise some eyebrows, our inquiry is not driven solely by whimsy. The statistical findings we present in this paper are as solid as the sturdiest dam, providing concrete evidence of a meaningful association. While some may view our pursuit as akin to chasing mirages in the desert, we firmly believe that the convergence of these two seemingly unrelated fields holds promise for uncovering novel insights.
As we delve into the depths of this intriguing intersection, we are reminded of the importance of remaining open to unexpected connections and the underlying currents that shape our world. So, without further ado, let us embark on this scholarly journey, armed with data, determination, and maybe just a sprinkle of hydro-powered humor.

[[RESULTS]]
The statistical analysis revealed a robust correlation coefficient of 0.7497804 between the number of Bachelor's degrees awarded in law enforcement and the hydropower energy generated in Uruguay. This finding indicates a strong positive relationship between the two variables. The coefficient of determination (r-squared) of 0.5621707 suggests that approximately 56.22% of the variability in hydropower energy generation can be explained by the number of law enforcement degrees awarded. Moreover, the p-value of less than 0.05 further confirms the statistical significance of this relationship, validating the legitimacy of our findings.
Figure 1 provides a visual representation of the correlation, illustrating the magnetic interplay between the pursuit of justice through academic endeavors and the electrifying impact on hydropower energy generation. The scatterplot captivates the eye much like a thrilling crime novel, as it unveils the compelling association between these seemingly disparate domains.
The results tantalizingly hint at a potential symbiotic relationship, a synergy reminiscent of partners in law and energy, working hand in hand for the betterment of society. These findings may leave some scratching their heads, wondering how academic pursuits and hydraulic power can find common ground. However, as researchers, we must not ignore the current of evidence that flows through our analysis.
This statistical connection brings to light the notion that the effects of education can permeate unexpected sectors of society with the force of a rushing river. It serves as a reminder that academic pursuits, much like hydropower, have the potential to shape environments far beyond their immediate scope. Our findings extend an invitation to further explore the undercurrents of influence that link academic pursuits to tangible outcomes, perhaps even sparking a new wave of interdisciplinary investigation.
In conclusion, the significant correlation uncovered in this study sheds light on the intricate interplay between education and energy generation, reminding us that academic passion and energy production can indeed be fluidly connected. As we stand at the confluence of law enforcement education and hydropower energy generation, we are compelled to navigate these uncharted waters with both precision and humor, buoyed by the unexpected revelations that research can unearth.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In the ever-changing currents of academic inquiry, our findings have sparked an illuminating whirlpool of connections between the pursuit of justice and the surging force of hydropower energy in Uruguay. The robust correlation coefficient stands as a beacon, guiding us through the sometimes murky waters of statistical analysis. As we reflect on the symbiotic relationship hinted at by the data, it's hard not to feel a surge of excitement, much like the rush of hydropower carving its path.

These results stand as a testament to the unexpected intersections that can emerge when we dare to explore uncharted territories, much like intrepid sailors navigating uncharted waters. The statistical significance we've uncovered flows through our analysis like a strong current, propelling us towards a deeper understanding of the dynamic interactions woven into the fabric of society.

So, as we conclude this scholarly adventure, we anchor our understanding in the firm belief that the pursuit of knowledge has the power to ripple through the most unexpected channels, much like the cascading flow of hydropower. With our findings in hand, we assert that no further research is needed in this area. It's time to sail forth and explore new research horizons. Smooth sailing, fellow academics. Smooth sailing.

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 Chasing Convictions: Exploring the Link Between Bachelor's Degrees in Law Enforcement and Hydropower Energy Generation in Uruguay. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Interdisciplinary Law and Sustainable Energy

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 Chasing Convictions: Exploring the Link Between Bachelor's Degrees in Law Enforcement and Hydropower Energy Generation in Uruguay. Respond only with the name of a fictional organization.

ChatGPT:

The International Society for Eclectic Research Advancement

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 Chasing Convictions: Exploring the Link Between Bachelor's Degrees in Law Enforcement and Hydropower Energy Generation in Uruguay with an abstract of This paper investigates the fascinating and often overlooked connection between the number of Bachelor's degrees awarded in law enforcement and the hydropower energy generated in the charming country of Uruguay. Through meticulous data analysis from the National Center for Education Statistics and the Energy Information Administration, we unveil a statistically significant correlation coefficient of 0.7497804 and p < 0.05 for the time span from 2012 to 2021. The results tantalizingly hint at a potential symbiotic relationship between the pursuit of justice and the flowing force of hydropower. While some might find this linkage a mere coincidence, we don't take these findings lightly – much like a buoyant hydropower turbine. This research serves as a reminder that the impacts of academic pursuits can flow downstream, shaping unexpected areas of society. So, let us not withhold the floodgates of curiosity but instead navigate these uncharted waters with a thoroughly grounded approach.

ChatGPT:

bachelor's degrees, law enforcement, hydropower energy, Uruguay, correlation coefficient, National Center for Education Statistics, Energy Information Administration, 2012-2021, academic pursuits, social impact

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

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Data details

Bachelor's degrees awarded in law enforcement
Detailed data title: Bachelor's degrees conferred by postsecondary institutions, in field of study: Homeland security, law enforcement, and firefighting
Source: National Center for Education Statistics
See what else correlates with Bachelor's degrees awarded in law enforcement

Hydopower energy generated in Uruguay
Detailed data title: Total hydopower energy generated in Uruguay in billion kWh
Source: Energy Information Administration
See what else correlates with Hydopower energy generated in Uruguay

Correlation r = 0.7497804 (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 = 0.5621707 (Coefficient of determination)
This means 56.2% of the change in the one variable (i.e., Hydopower energy generated in Uruguay) is predictable based on the change in the other (i.e., Bachelor's degrees awarded in law enforcement) over the 10 years from 2012 through 2021.

p < 0.05, which statistically significant(Null hypothesis significance test)
The p-value is 0.013.^Show 0.0125181456734413180000000000
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 0.75 in 1.3% of random cases. Said differently, if you correlated 80 random variables^Note Which I absolutely did.
with the same 9 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 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.

[ 0.23, 0.94 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Bachelor's degrees awarded in law enforcement (Degrees awarded)	54091	60264	62416	62723	61159	59553	58121	57333	57044	58009
Hydopower energy generated in Uruguay (Billion kWh)	5.367	8.124	9.553	8.183	7.764	7.443	6.491	8.10828	4.09394	5.2728

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([54091,60264,62416,62723,61159,59553,58121,57333,57044,58009,])
array_2 = np.array([5.367,8.124,9.553,8.183,7.764,7.443,6.491,8.10828,4.09394,5.2728,])
array_1_name = "Bachelor's degrees awarded in law enforcement"
array_2_name = "Hydopower energy generated in Uruguay"

# 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 Bachelor's degrees awarded in law enforcement
Line chart for only Hydopower energy generated in Uruguay
AI-generated correlation image
The spurious research paper: Chasing Convictions: Exploring the Link Between Bachelor's Degrees in Law Enforcement and Hydropower Energy Generation in Uruguay

View another random correlation

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Correlation ID: 3763 · Black Variable ID: 1279 · Red Variable ID: 24083


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