Spurious correlation #2,790 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Robberies in Montana and the second variable is US Hospital Occupancy Rate. The chart goes from 2002 to 2019, 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 Robberies in Montana and the second variable is US Hospital Occupancy Rate. The chart goes from 2002 to 2019, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As robberies decreased in Montana, there was a corresponding drop in the number of 'bandit-related injuries' requiring hospitalization. With fewer bandits on the loose, people were engaging in fewer wild west-style showdowns, thus leading to a decrease in overall hospital admissions. It seems even the healthcare system couldn't escape the far-reaching influence of the rootin' tootin' law enforcement trends in the great state of Montana. Yeehaw for public safety and unforeseen effects on hospital capacity!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a serene street in Montana, with the focus on a hospital in the distance. Illuminate the calm neighborhood scene with soft lighting, and pay attention to the details of the surrounding buildings and landscape—perhaps a certain tranquility in the air, subtly reflecting the decrease in criminal activity and hospital occupancy rate. Capture the essence of a peaceful environment where safety and well-being thrive, and allow the viewer to observe the positive impact of decreased criminal incidents on the community. 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: Robberies in Montana and US Hospital Occupancy Rate. 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: Cubism Realistic inspired by bauhaus Glitch art Macabre
ChatGPT: Realistic

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Robberies in Montana and US Hospital Occupancy Rate, in the following situation: Because the decrease in robberies in Montana led to fewer criminals seeking medical attention, the US Hospital Occupancy Rate decreased. With less bandits getting banged up, hospital beds were left unoccupied. It seems crime really doesn't pay – for the hospitals, at least!. Keep the description simple.
ChatGPT: Picture a quiet street in Montana with fewer incidents of robberies. In the distance, a hospital looms with a noticeably reduced number of occupied beds. The empty beds stand as a testament to the decrease in criminals seeking medical attention, mirroring the decline in robberies and resulting in a lower US Hospital Occupancy Rate.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Realistic ] and depicting this scene: Picture a quiet street in Montana with fewer incidents of robberies. In the distance, a hospital looms with a noticeably reduced number of occupied beds. The empty beds stand as a testament to the decrease in criminals seeking medical attention, mirroring the decline in robberies and resulting in a lower US Hospital Occupancy Rate. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a serene street in Montana, with the focus on a hospital in the distance. Illuminate the calm neighborhood scene with soft lighting, and pay attention to the details of the surrounding buildings and landscape—perhaps a certain tranquility in the air, subtly reflecting the decrease in criminal activity and hospital occupancy rate. Capture the essence of a peaceful environment where safety and well-being thrive, and allow the viewer to observe the positive impact of decreased criminal incidents on the community.

*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 a decrease in Robberies in Montana caused US Hospital Occupancy Rate to decrease. Make it feel plausible.

AI academic paper

(Because p < 0.01)

The Great Montana Heist: A Robbery on Hospital Resources?

The Journal of Hospital Resource Management

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 Robberies in Montana and US Hospital Occupancy Rate. 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 name some cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
"The Great Montana Heist: A Robbery on Hospital Resources?"

[[ABSTRACT]]
This paper delves into the mysterious connection between the frequency of robberies in the state of Montana and the occupancy rate of hospitals across the United States. Utilizing data from the FBI Criminal Justice Information Services and Statista, our research team presents findings that suggest a rather surprising correlation. With a correlation coefficient of 0.7472633 and statistically significant p-value (p < 0.01) for the years 2002 to 2019, our study uncovers an unexpected link between criminal activity in the wild west and the strain it may surprisingly place on hospital resources nationwide. Join us in unraveling this peculiar phenomenon and exploring the potential implications of this seemingly unlikely relationship.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
Robberies in Montana and US Hospital Occupancy Rate - an unusual pairing that sets the stage for a thought-provoking investigation. As researchers, we are accustomed to uncovering surprising correlations and unearthing unexpected connections, but this particular investigation left us both perplexed and amused.
Picture this: a group of bandits riding through the rugged terrain of Montana, the "Treasure State," amidst the backdrop of stunning mountain ranges and picturesque landscapes. And yet, amidst this wild west charm, a statistical anomaly emerged, raising questions about the potential impact of criminal activity on far-reaching hospital resources.
As we embark on this journey of inquiry, it is essential to approach the subject matter with the requisite gravity and scholarly seriousness – but hey, a little levity never hurt anyone! So, saddle up and prepare to ride through the data, as we delve into the surprising relationship between robberies in Montana and the nationwide hospital occupancy rate.
Our investigation into this intriguing correlation aims to shed light on the underlying dynamics at play. Perhaps it is more than mere happenstance that the frequency of criminal incidents in Montana appears to align with fluctuations in hospital occupancy rates across the United States. Could it be that banditry in the "Big Sky Country" contributes to the strain on hospital resources nationwide? Or is this simply a statistical quirk, akin to finding gold nuggets in a riverbed?
In this pursuit of knowledge, we invite our fellow academics and esteemed readers to join us in unraveling this peculiar phenomenon. By examining the data from the FBI Criminal Justice Information Services and Statista, we present our findings with the hope of provoking both intellectual curiosity and, dare we say, a touch of bemusement.
So, fasten your seatbelts (or, in this case, secure your cowboy hats), as we embark on a gripping exploration of the unexpected link between the lands of Montana and the bustling corridors of hospitals across America. The stage is set, the data beckons, and the wild, wild insights await. Let's rustle up some fresh knowledge, shall we? Yeehaw!

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith and Doe's Study on Crime Patterns in Rural America," the authors find intriguing patterns of criminal activity in the vast expanse of the American countryside. Specifically, the study provides detailed insights into the prevalence of robberies in Montana, shedding light on the unique challenges posed by criminal incidents in this region. Moreover, "Jones and Smith's Analysis of Healthcare Utilization and Hospital Occupancy" uncovers the complex factors influencing hospital occupancy rates across the United States, offering a comprehensive examination of the diverse dynamics at play.

Moving beyond the confines of traditional scholarly research, the work of "Big Sky Country Chronicles: Exploring Montana's Criminal History" offers a compelling narrative on the colorful history of banditry in Montana, providing a rich tapestry of wild narratives and daring heists. Moreover, "The Economics of Wild West Banditry" by W. Banker delves into the curious intersection of criminal activities and their potential impact on societal infrastructure, including unforeseen consequences on hospital resources.

An unexpected addition to the literature comes in the form of "Bandits and Bedpans: A Tale of Montana Mischief," a work of fiction that weaves a thrilling story of robbers and their unforeseen effects on the healthcare system. Furthermore, "The Great Montana Hospital Caper" by A. Robber is a fictional account that presents a whimsical take on the impact of criminal escapades on hospital resources, intertwining humor with the unexpected consequences of banditry.

In a surprising turn of events, it appears that "The Adventures of Wild West Willy" and "Bandit Bonnie's Bizarre Escapades" are children's cartoons that, albeit indirectly, provide a lighthearted portrayal of the notorious activities in the "Big Sky Country," potentially offering an insightful, albeit unconventional, perspective to our investigation. Similarly, the popular children's show "Hospital Hijinks: Bandits in the ER" features comical scenarios of banditry within a hospital setting, providing an unexpected avenue for exploring the interplay between criminal antics and healthcare resources.

Thus, as we survey the diverse literature pertaining to the connection between robberies in Montana and the US hospital occupancy rate, we encounter a varied landscape of factual accounts, fictional narratives, and even children's portrayals. These sources offer a multifaceted lens through which to scrutinize the intersection of criminal activities in the wild west and the broader implications for hospital resources nationwide.

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 Robberies in Montana and US Hospital Occupancy Rate. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from FBI Criminal Justice Information Services and Statista . You used data from 2002 to 2019

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 Great Montana Heist: A Robbery on Hospital Resources?"

[[ABSTRACT]]
This paper delves into the mysterious connection between the frequency of robberies in the state of Montana and the occupancy rate of hospitals across the United States. Utilizing data from the FBI Criminal Justice Information Services and Statista, our research team presents findings that suggest a rather surprising correlation. With a correlation coefficient of 0.7472633 and statistically significant p-value (p < 0.01) for the years 2002 to 2019, our study uncovers an unexpected link between criminal activity in the wild west and the strain it may surprisingly place on hospital resources nationwide. Join us in unraveling this peculiar phenomenon and exploring the potential implications of this seemingly unlikely relationship.

[[INTRODUCTION]]
INTRODUCTION
Robberies in Montana and US Hospital Occupancy Rate - an unusual pairing that sets the stage for a thought-provoking investigation. As researchers, we are accustomed to uncovering surprising correlations and unearthing unexpected connections, but this particular investigation left us both perplexed and amused.
Picture this: a group of bandits riding through the rugged terrain of Montana, the "Treasure State," amidst the backdrop of stunning mountain ranges and picturesque landscapes. And yet, amidst this wild west charm, a statistical anomaly emerged, raising questions about the potential impact of criminal activity on far-reaching hospital resources.
As we embark on this journey of inquiry, it is essential to approach the subject matter with the requisite gravity and scholarly seriousness – but hey, a little levity never hurt anyone! So, saddle up and prepare to ride through the data, as we delve into the surprising relationship between robberies in Montana and the nationwide hospital occupancy rate.
Our investigation into this intriguing correlation aims to shed light on the underlying dynamics at play. Perhaps it is more than mere happenstance that the frequency of criminal incidents in Montana appears to align with fluctuations in hospital occupancy rates across the United States. Could it be that banditry in the "Big Sky Country" contributes to the strain on hospital resources nationwide? Or is this simply a statistical quirk, akin to finding gold nuggets in a riverbed?
In this pursuit of knowledge, we invite our fellow academics and esteemed readers to join us in unraveling this peculiar phenomenon. By examining the data from the FBI Criminal Justice Information Services and Statista, we present our findings with the hope of provoking both intellectual curiosity and, dare we say, a touch of bemusement.
So, fasten your seatbelts (or, in this case, secure your cowboy hats), as we embark on a gripping exploration of the unexpected link between the lands of Montana and the bustling corridors of hospitals across America. The stage is set, the data beckons, and the wild, wild insights await. Let's rustle up some fresh knowledge, shall we? Yeehaw!

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection:
The research team scoured the vast expanse of the internet, much like prospectors panning for gold, gathering data from the FBI Criminal Justice Information Services and the bountiful troves of information in Statista. The years 2002 to 2019 were the chosen hunting ground, offering a rich tapestry of data to scrutinize.

Robbery Data Acquisition:
The frequency of robberies in lovely Montana was captured through the meticulous mining of the FBI Crime Data Explorer. This required sifting through the digital haystack to extract the elusive needles of criminal incidents. The reported counts of robberies in Montana became an essential piece of our larcenous puzzle.

Hospital Occupancy Rate Unearthing:
Delving into the labyrinthine corridors of Statista, the team excavated the occupancy rates of hospitals across the United States. This involved navigating through a veritable jungle of statistical reports and databases, akin to embarking on an expedition through uncharted terrain. The occupancy rates were obtained through a combination of statistical reports and analytical findings, providing a comprehensive portrayal of the ebb and flow of hospital resources.

Data Calibration and Cleansing:
The acquired datasets were subjected to rigorous calibration and cleansing procedures, akin to separating fool's gold from genuine nuggets. Anomalies and irregularities were scrutinized and rectified, ensuring the integrity of the data extracted from the digital mines. This process was imperative to cultivate a dataset that was as free from impurities as a crystal-clear Montana mountain stream.

Correlation Analysis:
The statistical connection between the frequency of robberies in Montana and the hospital occupancy rates across the United States was unveiled through a fascinating symphony of mathematical scrutiny. The mighty correlation coefficient, the herald of statistical relationships, emerged from the depths of the data, casting light on the mysterious bond between criminal activities in the land of mountains and the operational strain on hospitals nationwide.

Statistical Significance Testing:
To ascertain the robustness of the identified relationship, the p-values were calculated with the precision of a watchmaker crafting a timepiece. This rigorous scrutiny determined the statistical significance of the correlation, affirming the credibility of the unexpected link between Montana's outlaw behavior and the pulse of hospital resources across the nation.

Limitations and Caveats:
As with any scientific pursuit, this investigation encountered its own intrinsic limitations and caveats. The potential influence of confounding variables and unexplored factors, much like elusive outlaws on the loose, present avenues for future research to traverse. Additionally, the reliance on publicly available data sources introduces the possibility of data idiosyncrasies, serving as a reminder that no dataset is free from imperfections.

In sum, the calibration, scrutiny, and analysis of the acquired datasets laid the groundwork for unraveling the enigmatic connection between Montana's felonious activities and the nationwide occupancy rates of hospitals. This convoluted yet exhilarating journey through data mining and statistical inquiry has illuminated a correlation that defies conventional expectations, beckoning further exploration and scholarly contemplation.

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 results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Robberies in Montana and US Hospital Occupancy Rate. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from FBI Criminal Justice Information Services and Statista .

For the time period 2002 to 2019, you found a correlation 0.7472633, r-squared of 0.5584025, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"The Great Montana Heist: A Robbery on Hospital Resources?"

[[ABSTRACT]]
This paper delves into the mysterious connection between the frequency of robberies in the state of Montana and the occupancy rate of hospitals across the United States. Utilizing data from the FBI Criminal Justice Information Services and Statista, our research team presents findings that suggest a rather surprising correlation. With a correlation coefficient of 0.7472633 and statistically significant p-value (p < 0.01) for the years 2002 to 2019, our study uncovers an unexpected link between criminal activity in the wild west and the strain it may surprisingly place on hospital resources nationwide. Join us in unraveling this peculiar phenomenon and exploring the potential implications of this seemingly unlikely relationship.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
Robberies in Montana and US Hospital Occupancy Rate - an unusual pairing that sets the stage for a thought-provoking investigation. As researchers, we are accustomed to uncovering surprising correlations and unearthing unexpected connections, but this particular investigation left us both perplexed and amused.
Picture this: a group of bandits riding through the rugged terrain of Montana, the "Treasure State," amidst the backdrop of stunning mountain ranges and picturesque landscapes. And yet, amidst this wild west charm, a statistical anomaly emerged, raising questions about the potential impact of criminal activity on far-reaching hospital resources.
As we embark on this journey of inquiry, it is essential to approach the subject matter with the requisite gravity and scholarly seriousness – but hey, a little levity never hurt anyone! So, saddle up and prepare to ride through the data, as we delve into the surprising relationship between robberies in Montana and the nationwide hospital occupancy rate.
Our investigation into this intriguing correlation aims to shed light on the underlying dynamics at play. Perhaps it is more than mere happenstance that the frequency of criminal incidents in Montana appears to align with fluctuations in hospital occupancy rates across the United States. Could it be that banditry in the "Big Sky Country" contributes to the strain on hospital resources nationwide? Or is this simply a statistical quirk, akin to finding gold nuggets in a riverbed?
In this pursuit of knowledge, we invite our fellow academics and esteemed readers to join us in unraveling this peculiar phenomenon. By examining the data from the FBI Criminal Justice Information Services and Statista, we present our findings with the hope of provoking both intellectual curiosity and, dare we say, a touch of bemusement.
So, fasten your seatbelts (or, in this case, secure your cowboy hats), as we embark on a gripping exploration of the unexpected link between the lands of Montana and the bustling corridors of hospitals across America. The stage is set, the data beckons, and the wild, wild insights await. Let's rustle up some fresh knowledge, shall we? Yeehaw!

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis revealed a strong and positive correlation between the frequency of robberies in Montana and the occupancy rate of hospitals across the United States for the years 2002 to 2019. The correlation coefficient of 0.7472633 suggests a robust relationship between these seemingly disparate variables. This finding is rather remarkable, considering the physical distance and thematic incongruity between banditry in the "Treasure State" and the operation of hospitals nationwide.

Furthermore, the r-squared value of 0.5584025 indicates that approximately 55.84% of the variation in hospital occupancy rates can be explained by the variation in robbery frequency in Montana. While correlation does not imply causation, one cannot help but wonder if there might be more to this relationship than meets the eye. Could it be that criminal escapades in the frontier state exert an unforeseen influence on the nationwide ebb and flow of hospital admissions? It's a conundrum that merits further investigation.

The significant p-value (p < 0.01) provides compelling evidence to reject the null hypothesis that there is no correlation between robberies in Montana and US hospital occupancy rate. It seems that there is indeed something intriguing at play, akin to a plot twist in a classic Western movie.

Additionally, the scatterplot (Fig. 1) visually encapsulates the strong correlation between these unlikely bedfellows. The data points align in a manner that would make even the most seasoned cattle rustler do a double take. It's as if Sherlock Holmes himself were tracking clues across the statistical terrain!

In conclusion, our findings present a fascinating puzzle for future research to unravel. The connection between robberies in Montana and the occupancy rate of hospitals across the United States continues to defy easy explanation. As we contemplate the potential implications of this unlikely relationship, one cannot help but marvel at the whims of statistical fate. Just when one thought the data landscape couldn't get any more wild, along comes a correlation that could rival the most sensational of train robberies. What a wild ride it has been – both statistically and conceptually!

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 Robberies in Montana and US Hospital Occupancy Rate. 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 Great Montana Heist: A Robbery on Hospital Resources?"

[[ABSTRACT]]
This paper delves into the mysterious connection between the frequency of robberies in the state of Montana and the occupancy rate of hospitals across the United States. Utilizing data from the FBI Criminal Justice Information Services and Statista, our research team presents findings that suggest a rather surprising correlation. With a correlation coefficient of 0.7472633 and statistically significant p-value (p < 0.01) for the years 2002 to 2019, our study uncovers an unexpected link between criminal activity in the wild west and the strain it may surprisingly place on hospital resources nationwide. Join us in unraveling this peculiar phenomenon and exploring the potential implications of this seemingly unlikely relationship.

[[LITERATURE REVIEW]]
In "Smith and Doe's Study on Crime Patterns in Rural America," the authors find intriguing patterns of criminal activity in the vast expanse of the American countryside. Specifically, the study provides detailed insights into the prevalence of robberies in Montana, shedding light on the unique challenges posed by criminal incidents in this region. Moreover, "Jones and Smith's Analysis of Healthcare Utilization and Hospital Occupancy" uncovers the complex factors influencing hospital occupancy rates across the United States, offering a comprehensive examination of the diverse dynamics at play.
Moving beyond the confines of traditional scholarly research, the work of "Big Sky Country Chronicles: Exploring Montana's Criminal History" offers a compelling narrative on the colorful history of banditry in Montana, providing a rich tapestry of wild narratives and daring heists. Moreover, "The Economics of Wild West Banditry" by W. Banker delves into the curious intersection of criminal activities and their potential impact on societal infrastructure, including unforeseen consequences on hospital resources.
An unexpected addition to the literature comes in the form of "Bandits and Bedpans: A Tale of Montana Mischief," a work of fiction that weaves a thrilling story of robbers and their unforeseen effects on the healthcare system. Furthermore, "The Great Montana Hospital Caper" by A. Robber is a fictional account that presents a whimsical take on the impact of criminal escapades on hospital resources, intertwining humor with the unexpected consequences of banditry.
In a surprising turn of events, it appears that "The Adventures of Wild West Willy" and "Bandit Bonnie's Bizarre Escapades" are children's cartoons that, albeit indirectly, provide a lighthearted portrayal of the notorious activities in the "Big Sky Country," potentially offering an insightful, albeit unconventional, perspective to our investigation. Similarly, the popular children's show "Hospital Hijinks: Bandits in the ER" features comical scenarios of banditry within a hospital setting, providing an unexpected avenue for exploring the interplay between criminal antics and healthcare resources.
Thus, as we survey the diverse literature pertaining to the connection between robberies in Montana and the US hospital occupancy rate, we encounter a varied landscape of factual accounts, fictional narratives, and even children's portrayals. These sources offer a multifaceted lens through which to scrutinize the intersection of criminal activities in the wild west and the broader implications for hospital resources nationwide.

[[RESULTS]]
The statistical analysis revealed a strong and positive correlation between the frequency of robberies in Montana and the occupancy rate of hospitals across the United States for the years 2002 to 2019. The correlation coefficient of 0.7472633 suggests a robust relationship between these seemingly disparate variables. This finding is rather remarkable, considering the physical distance and thematic incongruity between banditry in the "Treasure State" and the operation of hospitals nationwide.
Furthermore, the r-squared value of 0.5584025 indicates that approximately 55.84% of the variation in hospital occupancy rates can be explained by the variation in robbery frequency in Montana. While correlation does not imply causation, one cannot help but wonder if there might be more to this relationship than meets the eye. Could it be that criminal escapades in the frontier state exert an unforeseen influence on the nationwide ebb and flow of hospital admissions? It's a conundrum that merits further investigation.
The significant p-value (p < 0.01) provides compelling evidence to reject the null hypothesis that there is no correlation between robberies in Montana and US hospital occupancy rate. It seems that there is indeed something intriguing at play, akin to a plot twist in a classic Western movie.
Additionally, the scatterplot (Fig. 1) visually encapsulates the strong correlation between these unlikely bedfellows. The data points align in a manner that would make even the most seasoned cattle rustler do a double take. It's as if Sherlock Holmes himself were tracking clues across the statistical terrain!
In conclusion, our findings present a fascinating puzzle for future research to unravel. The connection between robberies in Montana and the occupancy rate of hospitals across the United States continues to defy easy explanation. As we contemplate the potential implications of this unlikely relationship, one cannot help but marvel at the whims of statistical fate. Just when one thought the data landscape couldn't get any more wild, along comes a correlation that could rival the most sensational of train robberies. What a wild ride it has been – both statistically and conceptually!

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study have shed light on the rather unexpected connection between the frequency of robberies in Montana and the occupancy rate of hospitals across the United States. Our findings echo and support the earlier works in our literature review, from the serious quantitative analyses to the more whimsical and, dare I say, adventurous tales of banditry in the "Big Sky Country."

Drawing from "Smith and Doe's Study on Crime Patterns in Rural America," we observed a resonance with our own findings of intriguing patterns of criminal activity in the vast expanse of the American countryside, particularly in Montana. Furthermore, "The Economics of Wild West Banditry" by W. Banker seems to have foreseen the very correlation we uncovered, albeit in a more tongue-in-cheek manner.

Our study's results not only support the existing literature but also bolster the validity of the unexpected additions to the literature. The fictional accounts, such as "The Great Montana Hospital Caper" by A. Robber and "Bandits and Bedpans: A Tale of Montana Mischief," provided rather prescient and lighthearted insights into the potential impact of criminal escapades on hospital resources, which our study has now substantiated.

As we reflect on the findings, one cannot help but marvel at the unforeseen intersection of statistical analysis and the wild narratives and daring heists portrayed in these literary works. The robust correlation we uncovered between robbery frequency in Montana and the nationwide hospital occupancy rates is akin to a plot twist that even the most seasoned readers of frontier folklore would find intriguing.

In conclusion, our study has illuminated an unexpected and thought-provoking relationship between criminal activity in Montana and its potential impact on hospital resources across the United States. The implications of this correlation provide fodder for further investigation and, dare we say, speculation on the potential influence of "wild west" dynamics on the modern-day healthcare landscape. This unveiling of an unlikely alliance between banditry and hospital occupancy rates invites further scholarly scrutiny and, perhaps, a touch of the adventurous spirit that characterizes the tales from the "Treasure State."

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 Robberies in Montana and US Hospital Occupancy Rate. 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 Great Montana Heist: A Robbery on Hospital Resources?"

[[ABSTRACT]]
This paper delves into the mysterious connection between the frequency of robberies in the state of Montana and the occupancy rate of hospitals across the United States. Utilizing data from the FBI Criminal Justice Information Services and Statista, our research team presents findings that suggest a rather surprising correlation. With a correlation coefficient of 0.7472633 and statistically significant p-value (p < 0.01) for the years 2002 to 2019, our study uncovers an unexpected link between criminal activity in the wild west and the strain it may surprisingly place on hospital resources nationwide. Join us in unraveling this peculiar phenomenon and exploring the potential implications of this seemingly unlikely relationship.

[[INTRDUCTION]]
INTRODUCTION
Robberies in Montana and US Hospital Occupancy Rate - an unusual pairing that sets the stage for a thought-provoking investigation. As researchers, we are accustomed to uncovering surprising correlations and unearthing unexpected connections, but this particular investigation left us both perplexed and amused.
Picture this: a group of bandits riding through the rugged terrain of Montana, the "Treasure State," amidst the backdrop of stunning mountain ranges and picturesque landscapes. And yet, amidst this wild west charm, a statistical anomaly emerged, raising questions about the potential impact of criminal activity on far-reaching hospital resources.
As we embark on this journey of inquiry, it is essential to approach the subject matter with the requisite gravity and scholarly seriousness – but hey, a little levity never hurt anyone! So, saddle up and prepare to ride through the data, as we delve into the surprising relationship between robberies in Montana and the nationwide hospital occupancy rate.
Our investigation into this intriguing correlation aims to shed light on the underlying dynamics at play. Perhaps it is more than mere happenstance that the frequency of criminal incidents in Montana appears to align with fluctuations in hospital occupancy rates across the United States. Could it be that banditry in the "Big Sky Country" contributes to the strain on hospital resources nationwide? Or is this simply a statistical quirk, akin to finding gold nuggets in a riverbed?
In this pursuit of knowledge, we invite our fellow academics and esteemed readers to join us in unraveling this peculiar phenomenon. By examining the data from the FBI Criminal Justice Information Services and Statista, we present our findings with the hope of provoking both intellectual curiosity and, dare we say, a touch of bemusement.
So, fasten your seatbelts (or, in this case, secure your cowboy hats), as we embark on a gripping exploration of the unexpected link between the lands of Montana and the bustling corridors of hospitals across America. The stage is set, the data beckons, and the wild, wild insights await. Let's rustle up some fresh knowledge, shall we? Yeehaw!

[[RESULTS]]
The statistical analysis revealed a strong and positive correlation between the frequency of robberies in Montana and the occupancy rate of hospitals across the United States for the years 2002 to 2019. The correlation coefficient of 0.7472633 suggests a robust relationship between these seemingly disparate variables. This finding is rather remarkable, considering the physical distance and thematic incongruity between banditry in the "Treasure State" and the operation of hospitals nationwide.
Furthermore, the r-squared value of 0.5584025 indicates that approximately 55.84% of the variation in hospital occupancy rates can be explained by the variation in robbery frequency in Montana. While correlation does not imply causation, one cannot help but wonder if there might be more to this relationship than meets the eye. Could it be that criminal escapades in the frontier state exert an unforeseen influence on the nationwide ebb and flow of hospital admissions? It's a conundrum that merits further investigation.
The significant p-value (p < 0.01) provides compelling evidence to reject the null hypothesis that there is no correlation between robberies in Montana and US hospital occupancy rate. It seems that there is indeed something intriguing at play, akin to a plot twist in a classic Western movie.
Additionally, the scatterplot (Fig. 1) visually encapsulates the strong correlation between these unlikely bedfellows. The data points align in a manner that would make even the most seasoned cattle rustler do a double take. It's as if Sherlock Holmes himself were tracking clues across the statistical terrain!
In conclusion, our findings present a fascinating puzzle for future research to unravel. The connection between robberies in Montana and the occupancy rate of hospitals across the United States continues to defy easy explanation. As we contemplate the potential implications of this unlikely relationship, one cannot help but marvel at the whims of statistical fate. Just when one thought the data landscape couldn't get any more wild, along comes a correlation that could rival the most sensational of train robberies. What a wild ride it has been – both statistically and conceptually!

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In closing, our research has shone a spotlight on the unexpected correlation between the Wild West's criminal escapades and the bustling corridors of hospitals nationwide. The statistical analysis has unveiled a relationship that rivals the most captivating of stagecoach heists. With a correlation coefficient that would make Bonnie and Clyde envious, it's clear that there's more to this connection than meets the eye.

The implications of this peculiar relationship are as vast as the Montana skyline. If criminal activity in the "Big Sky Country" can indeed impact hospital occupancy rates across the United States, it suggests a far-reaching influence that transcends state borders. Could it be that the specter of banditry casts a long shadow, influencing the ebb and flow of hospital admissions from sea to shining sea?

As we mull over the significance of this correlation, it's hard not to marvel at the whims of statistical fate. The data landscape has proven itself to be as wild and unpredictable as the frontier itself. However, as captivating as this correlation may be, it's important to remember that correlation does not imply causation. While we may be tempted to paint Montana's outlaws as the culprits behind nationwide hospital occupancy fluctuations, further investigation is needed to untangle this statistical web.

So, where does this leave us? Should we assemble a posse to pursue this correlation further? The answer, pardner, is a resounding "no." It's clear that this unlikely pairing of crime and healthcare has provided us with plenty of food for thought, but it's time to holster our statistical guns and declare that the mystery has been thoroughly examined. The stagecoaches can roll on without fear of statistical bandits – for now.

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 Great Montana Heist: A Robbery on Hospital Resources?. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Hospital Resource Management

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 Great Montana Heist: A Robbery on Hospital Resources?. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Ethical Allocation of Healthcare Resources

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 Great Montana Heist: A Robbery on Hospital Resources? with an abstract of This paper delves into the mysterious connection between the frequency of robberies in the state of Montana and the occupancy rate of hospitals across the United States. Utilizing data from the FBI Criminal Justice Information Services and Statista, our research team presents findings that suggest a rather surprising correlation. With a correlation coefficient of 0.7472633 and statistically significant p-value (p < 0.01) for the years 2002 to 2019, our study uncovers an unexpected link between criminal activity in the wild west and the strain it may surprisingly place on hospital resources nationwide. Join us in unraveling this peculiar phenomenon and exploring the potential implications of this seemingly unlikely relationship.

ChatGPT:

Montana, hospital occupancy, robbery frequency, criminal activity, FBI Criminal Justice Information Services, Statista, correlation coefficient, hospital resources, strain, United States, wild west, implications

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

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Data details

Robberies in Montana
Detailed data title: The robbery rate per 100,000 residents in Montana
Source: FBI Criminal Justice Information Services
See what else correlates with Robberies in Montana

US Hospital Occupancy Rate
Source: Statista
See what else correlates with US Hospital Occupancy Rate

Correlation r = 0.7472633 (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 = 0.5584025 (Coefficient of determination)
This means 55.8% of the change in the one variable (i.e., US Hospital Occupancy Rate) is predictable based on the change in the other (i.e., Robberies in Montana) over the 18 years from 2002 through 2019.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00037.^Show 0.0003650398171977726000000000
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 0.037% of random cases. Said differently, if you correlated 2,739 random variables^Note Which I absolutely did.
with the same 17 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 17 because we have two variables measured over a period of 18 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.

[ 0.43, 0.9 ] 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.

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019
Robberies in Montana (Robbery rate)	31.1	32.5	25.1	18.9	24.7	24.3	21.1	23.4	15.5	17.1	20.1	21.4	19.7	20.3	25.8	22.2	25.5	19.5
US Hospital Occupancy Rate (Occupancy Percentage Rate)	76.7	77.7	69.5	65.7	66.1	68.3	68.2	67.8	66.6	64.4	63.4	62.9	62.8	63.6	64	64.1	64.3	64.4

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([31.1,32.5,25.1,18.9,24.7,24.3,21.1,23.4,15.5,17.1,20.1,21.4,19.7,20.3,25.8,22.2,25.5,19.5,])
array_2 = np.array([76.7,77.7,69.5,65.7,66.1,68.3,68.2,67.8,66.6,64.4,63.4,62.9,62.8,63.6,64,64.1,64.3,64.4,])
array_1_name = "Robberies in Montana"
array_2_name = "US Hospital Occupancy Rate"

# 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 Robberies in Montana
Line chart for only US Hospital Occupancy Rate
AI-generated correlation image
The spurious research paper: The Great Montana Heist: A Robbery on Hospital Resources?

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Correlation ID: 2790 · Black Variable ID: 20200 · Red Variable ID: 443


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