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AI explanation
As the Worldwide Count of Nokia Employees increased, so did the number of individuals skilled at "cell" service. These new employees had a knack for "locking down" success, leading to a ripple effect in California's job market. It's clear that when Nokia expands, so does the need for handling "cellular" security! Looks like Nokia isn't just in the business of making connections; they're also boosting the "cell" block workforce in an unexpected partnership with the California correctional facilities. Who knew that a company known for its phones would also be dialing up employment opportunities in the state's prisons!Model: dalle-3
Prompt: Create an image of a comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s. Depict a scene of an increase in the Worldwide Count of Nokia Employees with more people wearing Nokia T-shirts and corporate badges. At the same time, show a line of correctional officers and jailers in California, with more officers being hired and wearing their uniforms, along with their specialized equipment to handle the "Nokia-fueled" uprisings in prisons. In the background, include homemade weapons made from old Nokia phones being confiscated from inmates. The visual representation should be simple without any words or speech bubbles. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: As the Worldwide Count of Nokia Employees increased, there was a corresponding rise in the number of correctional officers and jailers in California. This unique correlation can be traced back to the fact that Nokia's indestructible old school phones became so popular that they were being used by inmates as improvised weapons, prompting the state to hire more officers to handle the "Nokia-fueled" uprisings in prisons.. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: Glitch art a Polaroid photo A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Cute 2D animation Low poly
ChatGPT: A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. As the Worldwide Count of Nokia Employees increased, there was a corresponding rise in the number of correctional officers and jailers in California. This unique correlation can be traced back to the fact that Nokia's indestructible old school phones became so popular that they were being used by inmates as improvised weapons, prompting the state to hire more officers to handle the "Nokia-fueled" uprisings in prisons.
ChatGPT: A scene showing an increase in the Worldwide Count of Nokia Employees with more people wearing Nokia T-shirts and corporate badges. At the same time, there is a line of correctional officers and jailers in California, with more officers being hired and wearing their uniforms, along with their specialized equipment to handle the "Nokia-fueled" uprisings in prisons. In the background, there are homemade weapons made from old Nokia phones being confiscated from inmates.
Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s ] and depicting this scene: A scene showing an increase in the Worldwide Count of Nokia Employees with more people wearing Nokia T-shirts and corporate badges. At the same time, there is a line of correctional officers and jailers in California, with more officers being hired and wearing their uniforms, along with their specialized equipment to handle the "Nokia-fueled" uprisings in prisons. In the background, there are homemade weapons made from old Nokia phones being confiscated from inmates. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s. Depict a scene of an increase in the Worldwide Count of Nokia Employees with more people wearing Nokia T-shirts and corporate badges. At the same time, show a line of correctional officers and jailers in California, with more officers being hired and wearing their uniforms, along with their specialized equipment to handle the "Nokia-fueled" uprisings in prisons. In the background, include homemade weapons made from old Nokia phones being confiscated from inmates. The visual representation should be simple without any words or speech bubbles.
*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.
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 Worldwide Count of Nokia Employees caused The number of correctional officers and jailers in California to increase. Include one good pun.
AI academic paper
Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers The Journal of Technological Sociology Jan 2024 Reminder: This paper is AI-generated. Not real! |
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 write titles and abstracts of goofy academic research papers.
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, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Worldwide Count of Nokia Employees and The number of correctional officers and jailers in California. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Include a pun in the title.
Your research team used data from Statista and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.8334491 and p < 0.01 for 2005 to 2022.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
"Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers"
[[ABSTRACT]]
This research paper delves into the curious correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in the state of California. While one may assume these two entities have about as much in common as a cell phone and a prison cell, our investigation reveals a surprisingly strong statistical link. Utilizing data from Statista and the Bureau of Labor Statistics, our research team meticulously examined the period from 2005 to 2022, unearthing a remarkable correlation coefficient of 0.8334491 and a statistically significant p-value of less than 0.01. As we pondered over the startling findings, we couldn't help but wonder if Nokia's phones were so "cell"ular that they inadvertently influenced the need for more correctional officers in California.
It is no "cellfie" how this relationship came to be, but our analysis offers thought-provoking insights into the unexpected interconnectedness of seemingly unrelated variables. Perhaps we can attribute this curious link to the "cell-ebrity" status of Nokia's products, but further investigation is required to unravel the full "corded" of this intriguing association.
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 introduction 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 introduction section of an academic research paper presenting the findings of the connection between Worldwide Count of Nokia Employees and The number of correctional officers and jailers in California. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Here is the title and abstract of the paper:
[[TITLE]]
"Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers"
[[ABSTRACT]]
This research paper delves into the curious correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in the state of California. While one may assume these two entities have about as much in common as a cell phone and a prison cell, our investigation reveals a surprisingly strong statistical link. Utilizing data from Statista and the Bureau of Labor Statistics, our research team meticulously examined the period from 2005 to 2022, unearthing a remarkable correlation coefficient of 0.8334491 and a statistically significant p-value of less than 0.01. As we pondered over the startling findings, we couldn't help but wonder if Nokia's phones were so "cell"ular that they inadvertently influenced the need for more correctional officers in California.
It is no "cellfie" how this relationship came to be, but our analysis offers thought-provoking insights into the unexpected interconnectedness of seemingly unrelated variables. Perhaps we can attribute this curious link to the "cell-ebrity" status of Nokia's products, but further investigation is required to unravel the full "corded" of this intriguing association.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
The surprising link between the worldwide count of Nokia employees and the number of correctional officers and jailers in California has raised more than a few eyebrows. It is as unexpected as finding a flip-phone in a museum – a real "cellular" mystery. Despite initial skepticism, our research aims to shed light on this correlation and explore potential explanations for its existence. As we dive into this peculiar relationship, we must ask ourselves: is there more to this connection than meets the "i"?
From a purely empirical perspective, the connection between a global telecommunications company and the staffing needs of a specific correctional system seems downright "cell-u-lar." However, as the saying goes, "When it comes to statistics, correlation does not imply causation" – but it does warrant investigation! Could it be that Nokia's rise and fall has inadvertently influenced California's corrections field?
In this paper, we will unravel the statistical relationship by examining the data from 2005 to 2022, with a focus on the period when Nokia's influence on the global market was at its peak. We must "ring-tone" down our initial presumptions and objectively analyze the empirical evidence before we "hang-up" on the possibility of a meaningful connection.
Our findings may prompt further inquiries and perhaps give birth to additional research questions. Maybe this surprising correlation is simply a "facet" of the complex web of interconnected economic and social factors, or perhaps it's a sign that we should "cell-abrate" the unexpected ways in which companies' global presence can leave a "lasting impression" on seemingly unrelated local systems.
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 Worldwide Count of Nokia Employees and The number of correctional officers and jailers in California. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.
Here is the title and abstract of the paper:
[[TITLE]]
"Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers"
[[ABSTRACT]]
This research paper delves into the curious correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in the state of California. While one may assume these two entities have about as much in common as a cell phone and a prison cell, our investigation reveals a surprisingly strong statistical link. Utilizing data from Statista and the Bureau of Labor Statistics, our research team meticulously examined the period from 2005 to 2022, unearthing a remarkable correlation coefficient of 0.8334491 and a statistically significant p-value of less than 0.01. As we pondered over the startling findings, we couldn't help but wonder if Nokia's phones were so "cell"ular that they inadvertently influenced the need for more correctional officers in California.
It is no "cellfie" how this relationship came to be, but our analysis offers thought-provoking insights into the unexpected interconnectedness of seemingly unrelated variables. Perhaps we can attribute this curious link to the "cell-ebrity" status of Nokia's products, but further investigation is required to unravel the full "corded" of this intriguing association.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The surprising link between the worldwide count of Nokia employees and the number of correctional officers and jailers in California has raised more than a few eyebrows. It is as unexpected as finding a flip-phone in a museum – a real "cellular" mystery. Despite initial skepticism, our research aims to shed light on this correlation and explore potential explanations for its existence. As we dive into this peculiar relationship, we must ask ourselves: is there more to this connection than meets the "i"?
From a purely empirical perspective, the connection between a global telecommunications company and the staffing needs of a specific correctional system seems downright "cell-u-lar." However, as the saying goes, "When it comes to statistics, correlation does not imply causation" – but it does warrant investigation! Could it be that Nokia's rise and fall has inadvertently influenced California's corrections field?
In this paper, we will unravel the statistical relationship by examining the data from 2005 to 2022, with a focus on the period when Nokia's influence on the global market was at its peak. We must "ring-tone" down our initial presumptions and objectively analyze the empirical evidence before we "hang-up" on the possibility of a meaningful connection.
Our findings may prompt further inquiries and perhaps give birth to additional research questions. Maybe this surprising correlation is simply a "facet" of the complex web of interconnected economic and social factors, or perhaps it's a sign that we should "cell-abrate" the unexpected ways in which companies' global presence can leave a "lasting impression" on seemingly unrelated local systems.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The literature surrounding the curious correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in California is surprisingly sparse. Smith and Doe (2010) examined the impact of technological advancements on labor markets, but their focus was squarely on the broader implications for employment trends, rather than the specific interplay between cell phone manufacturers and the correctional industry. Similarly, Jones (2015) explored the socioeconomic factors influencing the demand for public safety workers, but Nokia's global workforce was not a focal point of the analysis.
While the academic literature may lack direct investigation into our perplexing correlation, there are several related non-fiction publications that offer valuable insights. In "The Mobile Revolution: Understanding Cell Phone Impact on Society" by Tech Guru, the authors delve into the societal implications of the widespread use of mobile phones, shedding light on the far-reaching influence of telecommunications companies on everyday life. In a similar vein, "Prison Economics: The Nexus of Labor and Incarceration" by Policy Analyst provides a profound examination of the labor dynamics within correctional facilities, albeit without specific reference to Nokia.
A departure from the scholarly literature leads us to consider fictional works that may indirectly illuminate our peculiar correlation. In the dystopian novel "1984" by George Orwell, the omnipresent "Big Brother" surveillance state offers a chilling portrayal of a society where the dynamics of power and control intersect with technological advancements. While Nokia is not explicitly mentioned in this classic, the themes of social control and oversight are tangentially relevant to our investigation. Furthermore, in "Prison Break: A Novel" by Master Storyteller, the thrilling narrative of escaping confinement raises questions about the intricacies of prison administration and the personnel required to ensure security. Though entirely fictitious, this work prods at the core of our research inquiry.
Beyond the established canon of academic and literary sources, this investigation delved into the depths of unconventional research materials, including but not limited to, an assortment of receipts from retail stores and a highly scientific analysis of the potential correlation based on the length of mustaches sported by Nokia executives. While the former provided an unexpected glimpse into consumer behavior, the latter, albeit entirely fictional (or is it?), offered a brief respite from the rigorous pursuit of empirical evidence.
As we tread through the literature, it becomes evident that the line between rigorous academic inquiry and unexpected levity is perhaps as "blurred" as a low-resolution photograph captured on an early Nokia feature phone. Nevertheless, the breadth of sources explored underscores the interdisciplinary nature of our investigation, as we seek to uncover the "calling collect" phenomenon that links Nokia's global workforce to the staffing needs of California's correctional officers and jailers.
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 Worldwide Count of Nokia Employees and The number of correctional officers and jailers in California. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Your research team collected data from all across the internet, but mostly just used information from Statista and Bureau of Larbor Statistics . You used data from 2005 to 2022
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]]
"Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers"
[[ABSTRACT]]
This research paper delves into the curious correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in the state of California. While one may assume these two entities have about as much in common as a cell phone and a prison cell, our investigation reveals a surprisingly strong statistical link. Utilizing data from Statista and the Bureau of Labor Statistics, our research team meticulously examined the period from 2005 to 2022, unearthing a remarkable correlation coefficient of 0.8334491 and a statistically significant p-value of less than 0.01. As we pondered over the startling findings, we couldn't help but wonder if Nokia's phones were so "cell"ular that they inadvertently influenced the need for more correctional officers in California.
It is no "cellfie" how this relationship came to be, but our analysis offers thought-provoking insights into the unexpected interconnectedness of seemingly unrelated variables. Perhaps we can attribute this curious link to the "cell-ebrity" status of Nokia's products, but further investigation is required to unravel the full "corded" of this intriguing association.
[[INTRODUCTION]]
The surprising link between the worldwide count of Nokia employees and the number of correctional officers and jailers in California has raised more than a few eyebrows. It is as unexpected as finding a flip-phone in a museum – a real "cellular" mystery. Despite initial skepticism, our research aims to shed light on this correlation and explore potential explanations for its existence. As we dive into this peculiar relationship, we must ask ourselves: is there more to this connection than meets the "i"?
From a purely empirical perspective, the connection between a global telecommunications company and the staffing needs of a specific correctional system seems downright "cell-u-lar." However, as the saying goes, "When it comes to statistics, correlation does not imply causation" – but it does warrant investigation! Could it be that Nokia's rise and fall has inadvertently influenced California's corrections field?
In this paper, we will unravel the statistical relationship by examining the data from 2005 to 2022, with a focus on the period when Nokia's influence on the global market was at its peak. We must "ring-tone" down our initial presumptions and objectively analyze the empirical evidence before we "hang-up" on the possibility of a meaningful connection.
Our findings may prompt further inquiries and perhaps give birth to additional research questions. Maybe this surprising correlation is simply a "facet" of the complex web of interconnected economic and social factors, or perhaps it's a sign that we should "cell-abrate" the unexpected ways in which companies' global presence can leave a "lasting impression" on seemingly unrelated local systems.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
This investigation employed a combination of quantitative research methods to analyze the relationship between the worldwide count of Nokia employees and the number of correctional officers and jailers in California. The data used in this study were obtained from reputable sources such as Statista and the Bureau of Labor Statistics, covering the period from 2005 to 2022.
To begin, the primary focus was on gathering accurate and comprehensive data on the global employment figures for Nokia, as well as the detailed staffing records of correctional officers and jailers in California. This endeavor, much like a game of "phone tag," required meticulous sifting through various databases and reports to ensure the reliability and validity of the information.
One of the key challenges of this research was to ensure that the data collection process was as smooth as a well-rehearsed "ringtone," minimizing the likelihood of errors or misinterpretations. As with many research endeavors, this phase of the study called for both the patience of a saint and the discerning eye of an experienced investigator.
The quantitative analyses were conducted using sophisticated statistical software, which can crunch numbers faster than a speedy text message, allowing for the calculation of correlation coefficients and the verification of statistical significance. The research team ensured that all analyses were performed with the precision and rigor expected of a study of this nature, avoiding missteps as if walking through a "cell tower" minefield.
To understand the relationship between Nokia's global employment and California's corrections staffing needs, a series of regression analyses were performed to determine the extent of the association between these variables. This involved a careful examination of data patterns, resembling an intricate "puzzle" where each piece was essential to uncovering the bigger picture.
A validation process was also implemented to confirm the robustness of the statistical findings, akin to a "reverse charge call" – it required double-checking the results to ensure that the conclusions were not the product of random chance or an unforeseen data anomaly.
During the analysis, the research team also periodically indulged in lighthearted discussions about the various "cell"ular puns that could be included in the manuscript, always keeping in mind the paramount importance of maintaining the scholarly tone of the work while injecting a touch of levity.
Lastly, acknowledging the uncertainty and unpredictability inherent in research endeavors, the team remained open to unexpected discoveries or correlations that may have eluded initial expectations, much like finding a hidden "app" on a smartphone.
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 Worldwide Count of Nokia Employees and The number of correctional officers and jailers in California. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Your research team collected data from all across the internet, but mostly just used information from Statista and Bureau of Larbor Statistics .
For the time period 2005 to 2022, you found a correlation 0.8334491, r-squared of 0.6946374, 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]]
"Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers"
[[ABSTRACT]]
This research paper delves into the curious correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in the state of California. While one may assume these two entities have about as much in common as a cell phone and a prison cell, our investigation reveals a surprisingly strong statistical link. Utilizing data from Statista and the Bureau of Labor Statistics, our research team meticulously examined the period from 2005 to 2022, unearthing a remarkable correlation coefficient of 0.8334491 and a statistically significant p-value of less than 0.01. As we pondered over the startling findings, we couldn't help but wonder if Nokia's phones were so "cell"ular that they inadvertently influenced the need for more correctional officers in California.
It is no "cellfie" how this relationship came to be, but our analysis offers thought-provoking insights into the unexpected interconnectedness of seemingly unrelated variables. Perhaps we can attribute this curious link to the "cell-ebrity" status of Nokia's products, but further investigation is required to unravel the full "corded" of this intriguing association.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
The surprising link between the worldwide count of Nokia employees and the number of correctional officers and jailers in California has raised more than a few eyebrows. It is as unexpected as finding a flip-phone in a museum – a real "cellular" mystery. Despite initial skepticism, our research aims to shed light on this correlation and explore potential explanations for its existence. As we dive into this peculiar relationship, we must ask ourselves: is there more to this connection than meets the "i"?
From a purely empirical perspective, the connection between a global telecommunications company and the staffing needs of a specific correctional system seems downright "cell-u-lar." However, as the saying goes, "When it comes to statistics, correlation does not imply causation" – but it does warrant investigation! Could it be that Nokia's rise and fall has inadvertently influenced California's corrections field?
In this paper, we will unravel the statistical relationship by examining the data from 2005 to 2022, with a focus on the period when Nokia's influence on the global market was at its peak. We must "ring-tone" down our initial presumptions and objectively analyze the empirical evidence before we "hang-up" on the possibility of a meaningful connection.
Our findings may prompt further inquiries and perhaps give birth to additional research questions. Maybe this surprising correlation is simply a "facet" of the complex web of interconnected economic and social factors, or perhaps it's a sign that we should "cell-abrate" the unexpected ways in which companies' global presence can leave a "lasting impression" on seemingly unrelated local systems.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The analysis of the relationship between the worldwide count of Nokia employees and the number of correctional officers and jailers in California from 2005 to 2022 revealed a remarkably strong positive correlation with a coefficient of 0.8334491. This finding suggests that as the count of Nokia employees worldwide increased, so did the number of correctional officers and jailers in California. It seems that Nokia's impact extended beyond the realm of telecommunications to the confines of California's correctional facilities, making for a truly "cell-ular" association.
The coefficient of determination (r-squared) of 0.6946374 indicates that approximately 69.46% of the variation in the number of correctional officers and jailers in California can be explained by changes in the worldwide count of Nokia employees. This substantial explanatory power further emphasizes the strength of the observed relationship, leaving us to wonder if Nokia's influence had indeed "cell-ebrity" status in shaping California's staffing needs.
The p-value of less than 0.01 provides strong evidence against the null hypothesis of no relationship between the two variables. With such a low p-value, we can confidently reject the notion that the correlation observed was merely due to random chance. It seems that there is more to this "cell-tivating" connection than meets the "i".
The scatterplot (Fig. 1) visually represents the strong positive correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in California. The data points form a clear upward trend, illustrating the synchronous rise of both variables over the study period.
In spite of the initial incredulity surrounding the juxtaposition of Nokia's global employment and California's correctional staffing, the statistical evidence presents a compelling case for further investigation into the mechanisms underlying this unexpected correlation. It's clear that when it comes to Nokia's influence, there's more than meets the "i," and it might be time to "ring-tone" down the skepticism and delve deeper into this intriguing phenomenon.
As we contemplate the implications of this unexpected linkage, perhaps we can "cell-abrate" the chance discovery of such an unforeseen connection between global corporate dynamics and the localized needs of California's corrections system.
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 Worldwide Count of Nokia Employees and The number of correctional officers and jailers in California. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
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]]
"Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers"
[[ABSTRACT]]
This research paper delves into the curious correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in the state of California. While one may assume these two entities have about as much in common as a cell phone and a prison cell, our investigation reveals a surprisingly strong statistical link. Utilizing data from Statista and the Bureau of Labor Statistics, our research team meticulously examined the period from 2005 to 2022, unearthing a remarkable correlation coefficient of 0.8334491 and a statistically significant p-value of less than 0.01. As we pondered over the startling findings, we couldn't help but wonder if Nokia's phones were so "cell"ular that they inadvertently influenced the need for more correctional officers in California.
It is no "cellfie" how this relationship came to be, but our analysis offers thought-provoking insights into the unexpected interconnectedness of seemingly unrelated variables. Perhaps we can attribute this curious link to the "cell-ebrity" status of Nokia's products, but further investigation is required to unravel the full "corded" of this intriguing association.
[[LITERATURE REVIEW]]
The literature surrounding the curious correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in California is surprisingly sparse. Smith and Doe (2010) examined the impact of technological advancements on labor markets, but their focus was squarely on the broader implications for employment trends, rather than the specific interplay between cell phone manufacturers and the correctional industry. Similarly, Jones (2015) explored the socioeconomic factors influencing the demand for public safety workers, but Nokia's global workforce was not a focal point of the analysis.
While the academic literature may lack direct investigation into our perplexing correlation, there are several related non-fiction publications that offer valuable insights. In "The Mobile Revolution: Understanding Cell Phone Impact on Society" by Tech Guru, the authors delve into the societal implications of the widespread use of mobile phones, shedding light on the far-reaching influence of telecommunications companies on everyday life. In a similar vein, "Prison Economics: The Nexus of Labor and Incarceration" by Policy Analyst provides a profound examination of the labor dynamics within correctional facilities, albeit without specific reference to Nokia.
A departure from the scholarly literature leads us to consider fictional works that may indirectly illuminate our peculiar correlation. In the dystopian novel "1984" by George Orwell, the omnipresent "Big Brother" surveillance state offers a chilling portrayal of a society where the dynamics of power and control intersect with technological advancements. While Nokia is not explicitly mentioned in this classic, the themes of social control and oversight are tangentially relevant to our investigation. Furthermore, in "Prison Break: A Novel" by Master Storyteller, the thrilling narrative of escaping confinement raises questions about the intricacies of prison administration and the personnel required to ensure security. Though entirely fictitious, this work prods at the core of our research inquiry.
Beyond the established canon of academic and literary sources, this investigation delved into the depths of unconventional research materials, including but not limited to, an assortment of receipts from retail stores and a highly scientific analysis of the potential correlation based on the length of mustaches sported by Nokia executives. While the former provided an unexpected glimpse into consumer behavior, the latter, albeit entirely fictional (or is it?), offered a brief respite from the rigorous pursuit of empirical evidence.
As we tread through the literature, it becomes evident that the line between rigorous academic inquiry and unexpected levity is perhaps as "blurred" as a low-resolution photograph captured on an early Nokia feature phone. Nevertheless, the breadth of sources explored underscores the interdisciplinary nature of our investigation, as we seek to uncover the "calling collect" phenomenon that links Nokia's global workforce to the staffing needs of California's correctional officers and jailers.
[[RESULTS]]
The analysis of the relationship between the worldwide count of Nokia employees and the number of correctional officers and jailers in California from 2005 to 2022 revealed a remarkably strong positive correlation with a coefficient of 0.8334491. This finding suggests that as the count of Nokia employees worldwide increased, so did the number of correctional officers and jailers in California. It seems that Nokia's impact extended beyond the realm of telecommunications to the confines of California's correctional facilities, making for a truly "cell-ular" association.
The coefficient of determination (r-squared) of 0.6946374 indicates that approximately 69.46% of the variation in the number of correctional officers and jailers in California can be explained by changes in the worldwide count of Nokia employees. This substantial explanatory power further emphasizes the strength of the observed relationship, leaving us to wonder if Nokia's influence had indeed "cell-ebrity" status in shaping California's staffing needs.
The p-value of less than 0.01 provides strong evidence against the null hypothesis of no relationship between the two variables. With such a low p-value, we can confidently reject the notion that the correlation observed was merely due to random chance. It seems that there is more to this "cell-tivating" connection than meets the "i".
The scatterplot (Fig. 1) visually represents the strong positive correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in California. The data points form a clear upward trend, illustrating the synchronous rise of both variables over the study period.
In spite of the initial incredulity surrounding the juxtaposition of Nokia's global employment and California's correctional staffing, the statistical evidence presents a compelling case for further investigation into the mechanisms underlying this unexpected correlation. It's clear that when it comes to Nokia's influence, there's more than meets the "i," and it might be time to "ring-tone" down the skepticism and delve deeper into this intriguing phenomenon.
As we contemplate the implications of this unexpected linkage, perhaps we can "cell-abrate" the chance discovery of such an unforeseen connection between global corporate dynamics and the localized needs of California's corrections system.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The results of our analysis shed light on the surprising connection between the worldwide count of Nokia employees and the number of correctional officers and jailers in California. The robust positive correlation coefficient of 0.8334491 and the significant p-value of less than 0.01 validate the notion that Nokia's global workforce dynamics are, indeed, intertwined with the staffing needs of California's correctional facilities. It appears that Nokia's impact extends beyond the realm of mobile devices to the operation of the state's criminal justice system. One might say that Nokia's influence has reached impressive "cell-ebrity" status in shaping California's labor market trends.
The substantial explanatory power, as indicated by the coefficient of determination (r-squared) of 0.6946374, emphasizes that a considerable portion of the variation in the number of correctional officers and jailers in California can be attributed to changes in the worldwide count of Nokia employees. As we ponder over the far-reaching implications of this unexpected correlation, it becomes evident that Nokia's corporate dynamics are more than just phone-y business, affording a new perspective on the intertwined nature of seemingly disparate sectors of the economy.
The implication of such findings calls for a deepened understanding of the underlying mechanisms driving this unexpected association. While the literature review, with its eclectic assortment of sources, may have introduced a light-hearted tone with puns and playful connections, our results suggest that the relationship between Nokia's global employment and California's correctional staffing is no laughing matter. Perhaps it's time for researchers to "ring-tone" down the skepticism and "cell-abrate" this intriguing discovery with a "call" for further investigation.
Furthermore, the visualization of the strong positive correlation through the scatterplot bolsters the statistical evidence, providing a compelling visual representation of the synchronous rise of both variables. It becomes clear that when it comes to Nokia's influence, there's more than meets the "i," compelling scholars to "cellular-ly" delve into the depths of this unexpected linkage.
Indeed, the unexpected interconnectedness of seemingly unrelated variables reminds us of a profound dad joke: "Why don't we ever tell secrets on a farm? Because the potatoes have eyes and the corn has ears." Just as the potatoes and corn are more closely related than they seem, so too are Nokia's global employment and California's correctional staffing. The lines between different spheres of influence in the economy may be as "blurred" as the images captured on early Nokia feature phones, urging us to heed the call for further investigation into this curious correlation.
In light of these findings, one cannot deny that delving into unexpected research pursuits may yield unexpected fruits, much like how a grape slips and lands with a "wine-cident." As we ponder over the implications and cogitate upon the prospects for further inquiry, it becomes evident that the world of academia is ripe with surprising connections waiting to be "cell-ved."
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 Worldwide Count of Nokia Employees and The number of correctional officers and jailers in California. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
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]]
"Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers"
[[ABSTRACT]]
This research paper delves into the curious correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in the state of California. While one may assume these two entities have about as much in common as a cell phone and a prison cell, our investigation reveals a surprisingly strong statistical link. Utilizing data from Statista and the Bureau of Labor Statistics, our research team meticulously examined the period from 2005 to 2022, unearthing a remarkable correlation coefficient of 0.8334491 and a statistically significant p-value of less than 0.01. As we pondered over the startling findings, we couldn't help but wonder if Nokia's phones were so "cell"ular that they inadvertently influenced the need for more correctional officers in California.
It is no "cellfie" how this relationship came to be, but our analysis offers thought-provoking insights into the unexpected interconnectedness of seemingly unrelated variables. Perhaps we can attribute this curious link to the "cell-ebrity" status of Nokia's products, but further investigation is required to unravel the full "corded" of this intriguing association.
[[INTRDUCTION]]
The surprising link between the worldwide count of Nokia employees and the number of correctional officers and jailers in California has raised more than a few eyebrows. It is as unexpected as finding a flip-phone in a museum – a real "cellular" mystery. Despite initial skepticism, our research aims to shed light on this correlation and explore potential explanations for its existence. As we dive into this peculiar relationship, we must ask ourselves: is there more to this connection than meets the "i"?
From a purely empirical perspective, the connection between a global telecommunications company and the staffing needs of a specific correctional system seems downright "cell-u-lar." However, as the saying goes, "When it comes to statistics, correlation does not imply causation" – but it does warrant investigation! Could it be that Nokia's rise and fall has inadvertently influenced California's corrections field?
In this paper, we will unravel the statistical relationship by examining the data from 2005 to 2022, with a focus on the period when Nokia's influence on the global market was at its peak. We must "ring-tone" down our initial presumptions and objectively analyze the empirical evidence before we "hang-up" on the possibility of a meaningful connection.
Our findings may prompt further inquiries and perhaps give birth to additional research questions. Maybe this surprising correlation is simply a "facet" of the complex web of interconnected economic and social factors, or perhaps it's a sign that we should "cell-abrate" the unexpected ways in which companies' global presence can leave a "lasting impression" on seemingly unrelated local systems.
[[RESULTS]]
The analysis of the relationship between the worldwide count of Nokia employees and the number of correctional officers and jailers in California from 2005 to 2022 revealed a remarkably strong positive correlation with a coefficient of 0.8334491. This finding suggests that as the count of Nokia employees worldwide increased, so did the number of correctional officers and jailers in California. It seems that Nokia's impact extended beyond the realm of telecommunications to the confines of California's correctional facilities, making for a truly "cell-ular" association.
The coefficient of determination (r-squared) of 0.6946374 indicates that approximately 69.46% of the variation in the number of correctional officers and jailers in California can be explained by changes in the worldwide count of Nokia employees. This substantial explanatory power further emphasizes the strength of the observed relationship, leaving us to wonder if Nokia's influence had indeed "cell-ebrity" status in shaping California's staffing needs.
The p-value of less than 0.01 provides strong evidence against the null hypothesis of no relationship between the two variables. With such a low p-value, we can confidently reject the notion that the correlation observed was merely due to random chance. It seems that there is more to this "cell-tivating" connection than meets the "i".
The scatterplot (Fig. 1) visually represents the strong positive correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in California. The data points form a clear upward trend, illustrating the synchronous rise of both variables over the study period.
In spite of the initial incredulity surrounding the juxtaposition of Nokia's global employment and California's correctional staffing, the statistical evidence presents a compelling case for further investigation into the mechanisms underlying this unexpected correlation. It's clear that when it comes to Nokia's influence, there's more than meets the "i," and it might be time to "ring-tone" down the skepticism and delve deeper into this intriguing phenomenon.
As we contemplate the implications of this unexpected linkage, perhaps we can "cell-abrate" the chance discovery of such an unforeseen connection between global corporate dynamics and the localized needs of California's corrections system.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our research has unequivocally demonstrated a robust and statistically significant correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in California. The findings of this study raise important questions about the potential influence of global corporate dynamics on local labor demand. It's as if Nokia's reach "cell-ulated" far beyond the telecommunication industry, leaving an unexpected imprint on California's correctional staffing needs.
Furthermore, the coefficient of determination (r-squared) of 0.6946374 indicates that approximately 69.46% of the variation in the number of correctional officers and jailers in California can be attributed to changes in the worldwide count of Nokia employees. It appears that Nokia's global presence was more than just a "cell service provider" – it inadvertently affected California's correctional officer headcount.
As we ponder over the mechanisms underlying this correlation, we can't help but wonder if Nokia's products were so "cell-ebrated" that they steered the employment trends in California's corrections system. While this study offers a "cell" of insight into the unexpected interconnectedness of seemingly unrelated variables, the exact causal pathways remain to be fully "un-locked" through future research.
It's clear that there is no need to "dial" back the significance of this finding, and we can confidently assert that no more research is needed in this area. The results of this study leave us with one inevitable conclusion: when it comes to the count of Nokia employees and California's correctional officer and jailer numbers, the connection is overwhelmingly "cell-tivating."
No further investigation is warranted in this area.
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 Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Technological Sociology
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 Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers. Respond only with the name of a fictional organization.
ChatGPT:
The Institute for Global Workforce Dynamics
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 Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers with an abstract of This research paper delves into the curious correlation between the worldwide count of Nokia employees and the number of correctional officers and jailers in the state of California. While one may assume these two entities have about as much in common as a cell phone and a prison cell, our investigation reveals a surprisingly strong statistical link. Utilizing data from Statista and the Bureau of Labor Statistics, our research team meticulously examined the period from 2005 to 2022, unearthing a remarkable correlation coefficient of 0.8334491 and a statistically significant p-value of less than 0.01. As we pondered over the startling findings, we couldn't help but wonder if Nokia's phones were so "cell"ular that they inadvertently influenced the need for more correctional officers in California.
It is no "cellfie" how this relationship came to be, but our analysis offers thought-provoking insights into the unexpected interconnectedness of seemingly unrelated variables. Perhaps we can attribute this curious link to the "cell-ebrity" status of Nokia's products, but further investigation is required to unravel the full "corded" of this intriguing association.
ChatGPT:
Nokia, global employment, California correctional officers, jailers, Statista, Bureau of Labor Statistics, correlation coefficient, p-value, Nokia phones, interconnectedness of variables, unusual statistical link
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Worldwide Count of Nokia EmployeesSource: Statista
See what else correlates with Worldwide Count of Nokia Employees
The number of correctional officers and jailers in California
Detailed data title: BLS estimate of correctional officers and jailers in California
Source: Bureau of Larbor Statistics
See what else correlates with The number of correctional officers and jailers in California
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 = 0.6946374 (Coefficient of determination)
This means 69.5% of the change in the one variable (i.e., The number of correctional officers and jailers in California) is predictable based on the change in the other (i.e., Worldwide Count of Nokia Employees) over the 18 years from 2005 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.7E-5. 0.0000174044547938594500000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. 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 0.83 in 0.0017% of random cases. Said differently, if you correlated 57,457 random variables You don't actually need 57 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.
p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.
In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.
Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 17 degrees of freedom, 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.
[ 0.6, 0.94 ] 95% correlation confidence interval (using the Fisher z-transformation)
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: 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.
2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | |
Worldwide Count of Nokia Employees (Employees) | 58870 | 68480 | 112260 | 125830 | 123550 | 132430 | 130050 | 97800 | 58900 | 55400 | 55720 | 100880 | 102760 | 103080 | 98320 | 92040 | 87900 | 86900 |
The number of correctional officers and jailers in California (Laborers) | 33760 | 35570 | 38370 | 40260 | 42060 | 44120 | 42410 | 37210 | 35960 | 35480 | 34640 | 37050 | 36730 | 34980 | 36090 | 37810 | 37640 | 35310 |
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
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
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.
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. 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([58870,68480,112260,125830,123550,132430,130050,97800,58900,55400,55720,100880,102760,103080,98320,92040,87900,86900,])
array_2 = np.array([33760,35570,38370,40260,42060,44120,42410,37210,35960,35480,34640,37050,36730,34980,36090,37810,37640,35310,])
array_1_name = "Worldwide Count of Nokia Employees"
array_2_name = "The number of correctional officers and jailers in California"
# 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. 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
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 Worldwide Count of Nokia Employees
- Line chart for only The number of correctional officers and jailers in California
- The spurious research paper: Calling Collect: The Nokia Connection between Global Employment and California Correctional Officers
Your correlation inspection deserves a standing ovation!
Correlation ID: 1183 · Black Variable ID: 467 · Red Variable ID: 5472