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Spurious correlation #4,555 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Average views of Technology Connections YouTube videos and the second variable is The number of industrial truck and tractor operators in South Dakota.  The chart goes from 2015 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

South Dakotans were so inspired by the technology in the videos that they formed a fleet of high-tech, YouTube-educated operators, revolutionizing the industrial truck and tractor industry in the state. The power of internet knowledge and farm equipment - who would have thought?

Model: dalle-3
Prompt: Generate an image portraying a scene set in a vast South Dakota field where a group of futuristic industrial truck and tractor operators are surrounded by their sleek, high-tech vehicles. They stand proudly next to their machines, with a large screen in the background displaying the impressive average views of Technology Connections YouTube videos. The operators expertly operate their equipment, showcasing the influence and education they've gained from online knowledge, ushering in a new era of technology and innovation in the state's farming industry. The focus is on capturing the juxtaposition of traditional farming and cutting-edge technology in a visually striking and futuristic cybernetic style. 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: Average views of Technology Connections YouTube videos and The number of industrial truck and tractor operators in South Dakota. 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: a Polaroid photo inspired by bauhaus Oragami Cybernetic art Cubism
ChatGPT: Cybernetic art

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Average views of Technology Connections YouTube videos and The number of industrial truck and tractor operators in South Dakota, in the following situation: South Dakotans were so inspired by the technology in the videos that they formed a fleet of high-tech, YouTube-educated operators, revolutionizing the industrial truck and tractor industry in the state. The power of internet knowledge and farm equipment - who would have thought?. Keep the description simple.
ChatGPT: In a vast South Dakota field, a group of industrial truck and tractor operators stood proudly next to their gleaming, high-tech machines. In front of them, a large screen displayed the impressive average views of Technology Connections YouTube videos. As they expertly operated their equipment, it was clear that they had been influenced and educated by the online knowledge, bringing a new era of technology and innovation to the state's farming industry.

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: [ Cybernetic art ] and depicting this scene: In a vast South Dakota field, a group of industrial truck and tractor operators stood proudly next to their gleaming, high-tech machines. In front of them, a large screen displayed the impressive average views of Technology Connections YouTube videos. As they expertly operated their equipment, it was clear that they had been influenced and educated by the online knowledge, bringing a new era of technology and innovation to the state's farming industry. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image portraying a scene set in a vast South Dakota field where a group of futuristic industrial truck and tractor operators are surrounded by their sleek, high-tech vehicles. They stand proudly next to their machines, with a large screen in the background displaying the impressive average views of Technology Connections YouTube videos. The operators expertly operate their equipment, showcasing the influence and education they've gained from online knowledge, ushering in a new era of technology and innovation in the state's farming industry. The focus is on capturing the juxtaposition of traditional farming and cutting-edge technology in a visually striking and futuristic cybernetic style.

*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.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Average views of Technology Connections YouTube videos caused The number of industrial truck and tractor operators in South Dakota to increase.

AI academic paper

(Because p < 0.01)
Truckin' Technology: Examining the Correlation Between Average Views of Technology Connections YouTube Videos and the Number of Industrial Truck and Tractor Operators in South Dakota

Journal of Contemporary Technology Studies

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 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 Average views of Technology Connections YouTube videos and The number of industrial truck and tractor operators in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, make it sound serious.

Your research team used data from YouTube and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.9954744 and p < 0.01 for 2015 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]]
"Truckin' Technology: Examining the Correlation Between Average Views of Technology Connections YouTube Videos and the Number of Industrial Truck and Tractor Operators in South Dakota"

[[ABSTRACT]]
This study examines the intriguing relationship between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in the state of South Dakota. Utilizing data from the Bureau of Labor Statistics and YouTube analytics from 2015 to 2022, we found a remarkably high correlation coefficient of 0.9954744, with statistical significance at p < 0.01. Our findings suggest a potential connection between the consumption of technology-related content and the occupational choices of individuals in the trucking industry. The implications of these correlations are both thought-provoking and unexpectedly entertaining.


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 Average views of Technology Connections YouTube videos and The number of industrial truck and tractor operators in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
"Truckin' Technology: Examining the Correlation Between Average Views of Technology Connections YouTube Videos and the Number of Industrial Truck and Tractor Operators in South Dakota"

[[ABSTRACT]]
This study examines the intriguing relationship between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in the state of South Dakota. Utilizing data from the Bureau of Labor Statistics and YouTube analytics from 2015 to 2022, we found a remarkably high correlation coefficient of 0.9954744, with statistical significance at p < 0.01. Our findings suggest a potential connection between the consumption of technology-related content and the occupational choices of individuals in the trucking industry. The implications of these correlations are both thought-provoking and unexpectedly entertaining.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The trucking industry plays a vital role in the economy, transporting goods and materials across vast distances with the precision of a well-oiled machine. Similarly, the world of technology continues to evolve, connecting individuals to information and entertainment at unprecedented rates. In this study, we delved into the intersection of these seemingly disparate realms, aiming to uncover any underlying relationship between the consumption of technology-focused content and the occupational preferences of individuals within the trucking industry.

While these two domains may appear to be as unrelated as a semi-truck and a smartphone, the rise of online platforms, such as YouTube, has facilitated the widespread dissemination of information regarding technological advancements. Technology Connections, a YouTube channel specializing in all things tech, has garnered a substantial following, captivating viewers with its insightful and, dare we say, riveting content.

Furthermore, the state of South Dakota, known for its expansive landscapes and bustling trucking routes, served as the backdrop for our investigation. At first glance, one might question the rationale behind selecting this specific region for analysis. However, as we unraveled the data, the correlation between the average views of Technology Connections videos and the number of industrial truck and tractor operators in South Dakota proved to be as conspicuous as a bright, blinking turn signal on a country road at night.

The implications of our findings extend beyond the mere statistical association, venturing into the realm of cultural and occupational influence. Even though the relationship between technology consumption and occupational choices may seem as unexpected as an oversize load in a residential neighborhood, our results, like a pair of well-coordinated truck drivers zigzagging through traffic, pointed without a doubt to their interconnectedness.

With the stage set and the data ready for interpretation, we invite you on a journey of discovery, exploring a connection that, much like a sound truck engine, hums quietly beneath the surface of our modern world.


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 Average views of Technology Connections YouTube videos and The number of industrial truck and tractor operators in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Truckin' Technology: Examining the Correlation Between Average Views of Technology Connections YouTube Videos and the Number of Industrial Truck and Tractor Operators in South Dakota"

[[ABSTRACT]]
This study examines the intriguing relationship between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in the state of South Dakota. Utilizing data from the Bureau of Labor Statistics and YouTube analytics from 2015 to 2022, we found a remarkably high correlation coefficient of 0.9954744, with statistical significance at p < 0.01. Our findings suggest a potential connection between the consumption of technology-related content and the occupational choices of individuals in the trucking industry. The implications of these correlations are both thought-provoking and unexpectedly entertaining.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The trucking industry plays a vital role in the economy, transporting goods and materials across vast distances with the precision of a well-oiled machine. Similarly, the world of technology continues to evolve, connecting individuals to information and entertainment at unprecedented rates. In this study, we delved into the intersection of these seemingly disparate realms, aiming to uncover any underlying relationship between the consumption of technology-focused content and the occupational preferences of individuals within the trucking industry.
While these two domains may appear to be as unrelated as a semi-truck and a smartphone, the rise of online platforms, such as YouTube, has facilitated the widespread dissemination of information regarding technological advancements. Technology Connections, a YouTube channel specializing in all things tech, has garnered a substantial following, captivating viewers with its insightful and, dare we say, riveting content.
Furthermore, the state of South Dakota, known for its expansive landscapes and bustling trucking routes, served as the backdrop for our investigation. At first glance, one might question the rationale behind selecting this specific region for analysis. However, as we unraveled the data, the correlation between the average views of Technology Connections videos and the number of industrial truck and tractor operators in South Dakota proved to be as conspicuous as a bright, blinking turn signal on a country road at night.
The implications of our findings extend beyond the mere statistical association, venturing into the realm of cultural and occupational influence. Even though the relationship between technology consumption and occupational choices may seem as unexpected as an oversize load in a residential neighborhood, our results, like a pair of well-coordinated truck drivers zigzagging through traffic, pointed without a doubt to their interconnectedness.
With the stage set and the data ready for interpretation, we invite you on a journey of discovery, exploring a connection that, much like a sound truck engine, hums quietly beneath the surface of our modern world.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The matter of examining the correlation between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota has surprisingly not been extensively studied in academic literature. In "Smith et al." and "Doe and Jones," the authors find little to no mention of this peculiar relationship, leaving a gap in the existing body of knowledge. However, delving into related literature within the fields of technology consumption and occupational preferences, one can draw upon insights that may shed light on this unexplored correlation.

In "The Technology Paradox" by Carl Mellmann, the author expounds upon the intricate dynamics of technological integration in various industries, touching on the potential influence of digital content consumption on professional inclinations. Similarly, "The Trucking Times" by John Freightliner provides a comprehensive overview of the trucking industry, offering insights into the occupational choices of individuals within this field.

Turning to more fictional works, "Digital Highways: Navigating the Tech Terrain" by A. Byte and "Trucking Tales: From Asphalt to Zenith" by Mindy Miles are imaginative narratives that, while not grounded in academic research, portray the intersection of technology and trucking in an engaging manner.

In conducting this literature review, the researchers also took a comprehensive approach, considering a wide range of sources, including, but not limited to, the back labels of shampoo bottles, fortune cookie fortunes, and the musings of a particularly existential AI chatbot. While these sources do not meet conventional scholarly criteria, they offer a unique and, at times, unexpectedly insightful perspective on the intertwined tapestry of technology and trucking.

As the academic community continues to expand its understanding of the relationship between technology consumption and occupational choices, it is essential to remain open to unconventional sources of knowledge, embracing the offbeat and the unexpected as potential wellsprings of enlightenment.


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 Average views of Technology Connections YouTube videos and The number of industrial truck and tractor operators in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from YouTube and Bureau of Larbor Statistics . You used data from 2015 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]]
"Truckin' Technology: Examining the Correlation Between Average Views of Technology Connections YouTube Videos and the Number of Industrial Truck and Tractor Operators in South Dakota"

[[ABSTRACT]]
This study examines the intriguing relationship between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in the state of South Dakota. Utilizing data from the Bureau of Labor Statistics and YouTube analytics from 2015 to 2022, we found a remarkably high correlation coefficient of 0.9954744, with statistical significance at p < 0.01. Our findings suggest a potential connection between the consumption of technology-related content and the occupational choices of individuals in the trucking industry. The implications of these correlations are both thought-provoking and unexpectedly entertaining.

[[INTRODUCTION]]
The trucking industry plays a vital role in the economy, transporting goods and materials across vast distances with the precision of a well-oiled machine. Similarly, the world of technology continues to evolve, connecting individuals to information and entertainment at unprecedented rates. In this study, we delved into the intersection of these seemingly disparate realms, aiming to uncover any underlying relationship between the consumption of technology-focused content and the occupational preferences of individuals within the trucking industry.
While these two domains may appear to be as unrelated as a semi-truck and a smartphone, the rise of online platforms, such as YouTube, has facilitated the widespread dissemination of information regarding technological advancements. Technology Connections, a YouTube channel specializing in all things tech, has garnered a substantial following, captivating viewers with its insightful and, dare we say, riveting content.
Furthermore, the state of South Dakota, known for its expansive landscapes and bustling trucking routes, served as the backdrop for our investigation. At first glance, one might question the rationale behind selecting this specific region for analysis. However, as we unraveled the data, the correlation between the average views of Technology Connections videos and the number of industrial truck and tractor operators in South Dakota proved to be as conspicuous as a bright, blinking turn signal on a country road at night.
The implications of our findings extend beyond the mere statistical association, venturing into the realm of cultural and occupational influence. Even though the relationship between technology consumption and occupational choices may seem as unexpected as an oversize load in a residential neighborhood, our results, like a pair of well-coordinated truck drivers zigzagging through traffic, pointed without a doubt to their interconnectedness.
With the stage set and the data ready for interpretation, we invite you on a journey of discovery, exploring a connection that, much like a sound truck engine, hums quietly beneath the surface of our modern world.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To unravel the mysterious connection between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota, an array of data sources and analytical methods were employed.

Data Collection:
The data utilized in this study were sourced from the Bureau of Labor Statistics (BLS) and YouTube analytics. The BLS provided comprehensive information on the employment and occupational trends of industrial truck and tractor operators in South Dakota from 2015 to 2022. Meanwhile, the paragons of knowledge and entertainment at Technology Connections bestowed upon us the average views of their YouTube videos within the same time frame. The combination of these seemingly disparate datasets enabled our investigation into the potential correlation between technological curiosity and the realm of trucking.

Statistical Analysis:
The statistical significance of the relationship between average YouTube video views and industrial truck and tractor operator employment was assessed using Pearson's correlation coefficient. We must admit, the strength of the correlation coefficient surprised even the most seasoned members of our research team, not unlike stumbling upon an unexpected yet harmonious blend of gears in a well-oiled machine. The resulting coefficient of 0.9954744, with a p-value less than 0.01, indicated an exceptionally strong association, prompting further intrigue into the underlying mechanisms at play.

Regression Modeling:
To delve deeper into this unprecedented correlation, a regression model was employed to ascertain the predictive capacity of average YouTube views on the number of industrial truck and tractor operators in South Dakota. The model, akin to a GPS guiding us through uncharted territory, provided insights into the potential influence of technology-related content consumption on occupational preferences within the trucking industry.

Data Interpretation:
Upon procuring the statistical results, we delved into the interpretation of these findings with the same fervor as a trucker wisely navigating through fluctuating freight demands. The implications of the correlations were explored through a multidimensional lens, considering both the statistical significance and the broader socio-economic context. Our commitment to thorough analysis led us to conclusions that shed light on the unexpected interplay between technology consumption and occupational choices, much like the first rays of dawn illuminating a previously unseen stretch of highway.

Limitations:
It is essential to acknowledge the limitations of our methodology, akin to recognizing the blind spots in a rearview mirror. While our findings present a remarkably strong association, they do not establish causation. Additionally, the specific focus on South Dakota may limit the generalizability of our results to other regions. Future research endeavors could explore a wider geographic scope and incorporate additional variables to further elucidate the intricate relationship between technological engagement and occupational preferences.



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 Average views of Technology Connections YouTube videos and The number of industrial truck and tractor operators in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from YouTube and Bureau of Larbor Statistics .

For the time period 2015 to 2022, you found a correlation 0.9954744, r-squared of 0.9909693, 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]]
"Truckin' Technology: Examining the Correlation Between Average Views of Technology Connections YouTube Videos and the Number of Industrial Truck and Tractor Operators in South Dakota"

[[ABSTRACT]]
This study examines the intriguing relationship between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in the state of South Dakota. Utilizing data from the Bureau of Labor Statistics and YouTube analytics from 2015 to 2022, we found a remarkably high correlation coefficient of 0.9954744, with statistical significance at p < 0.01. Our findings suggest a potential connection between the consumption of technology-related content and the occupational choices of individuals in the trucking industry. The implications of these correlations are both thought-provoking and unexpectedly entertaining.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The trucking industry plays a vital role in the economy, transporting goods and materials across vast distances with the precision of a well-oiled machine. Similarly, the world of technology continues to evolve, connecting individuals to information and entertainment at unprecedented rates. In this study, we delved into the intersection of these seemingly disparate realms, aiming to uncover any underlying relationship between the consumption of technology-focused content and the occupational preferences of individuals within the trucking industry.
While these two domains may appear to be as unrelated as a semi-truck and a smartphone, the rise of online platforms, such as YouTube, has facilitated the widespread dissemination of information regarding technological advancements. Technology Connections, a YouTube channel specializing in all things tech, has garnered a substantial following, captivating viewers with its insightful and, dare we say, riveting content.
Furthermore, the state of South Dakota, known for its expansive landscapes and bustling trucking routes, served as the backdrop for our investigation. At first glance, one might question the rationale behind selecting this specific region for analysis. However, as we unraveled the data, the correlation between the average views of Technology Connections videos and the number of industrial truck and tractor operators in South Dakota proved to be as conspicuous as a bright, blinking turn signal on a country road at night.
The implications of our findings extend beyond the mere statistical association, venturing into the realm of cultural and occupational influence. Even though the relationship between technology consumption and occupational choices may seem as unexpected as an oversize load in a residential neighborhood, our results, like a pair of well-coordinated truck drivers zigzagging through traffic, pointed without a doubt to their interconnectedness.
With the stage set and the data ready for interpretation, we invite you on a journey of discovery, exploring a connection that, much like a sound truck engine, hums quietly beneath the surface of our modern world.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our analysis revealed a strikingly high correlation coefficient of 0.9954744 between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota over the period from 2015 to 2022. The r-squared value of 0.9909693 further underscored the robustness of this relationship, affirming that approximately 99.1% of the variability in the number of industrial truck and tractor operators could be explained by the average views of Technology Connections videos. The statistical significance of p < 0.01 indicated a highly unlikely scenario of these results occurring by chance, emphasizing the reliability of our findings.

Upon visual inspection of the data, it became evident that the relationship between these variables was not just an idle fluctuation, but rather a strong and persistent phenomenon resembling a steadfast truck driver navigating through diverse terrains. This was succinctly captured in the scatterplot (Fig. 1), which graphically demonstrated the clear positive linear trend between the average views of Technology Connections videos and the number of industrial truck and tractor operators in South Dakota.

The substantial correlation uncovered in our study may initially appear as unexpected as a high-tech gadget in the cab of a vintage truck, yet it presents an intriguing avenue for further exploration. Whether this association reflects a genuine influence of technology content consumption on occupational choices or simply represents a quirk of statistical fate is a question worthy of contemplation. The pronounced correlation observed in our analysis prompts a reevaluation of the potential impact of online technological discourse on occupational preferences, a notion that may have previously been as inconspicuous as a chameleon blending into its surroundings.

Overall, the robustness of the relationship between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota posits intriguing implications for the interplay between technology consumption and occupational decision-making. Our research opens the door to a domain as unexplored and unexpected as finding a yet-to-be-charted route on a long-haul drive, inviting further inquiry into the intricacies of human behavior within the ever-evolving landscape of technology and industry.


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 Average views of Technology Connections YouTube videos and The number of industrial truck and tractor operators in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
"Truckin' Technology: Examining the Correlation Between Average Views of Technology Connections YouTube Videos and the Number of Industrial Truck and Tractor Operators in South Dakota"

[[ABSTRACT]]
This study examines the intriguing relationship between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in the state of South Dakota. Utilizing data from the Bureau of Labor Statistics and YouTube analytics from 2015 to 2022, we found a remarkably high correlation coefficient of 0.9954744, with statistical significance at p < 0.01. Our findings suggest a potential connection between the consumption of technology-related content and the occupational choices of individuals in the trucking industry. The implications of these correlations are both thought-provoking and unexpectedly entertaining.

[[LITERATURE REVIEW]]
The matter of examining the correlation between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota has surprisingly not been extensively studied in academic literature. In "Smith et al." and "Doe and Jones," the authors find little to no mention of this peculiar relationship, leaving a gap in the existing body of knowledge. However, delving into related literature within the fields of technology consumption and occupational preferences, one can draw upon insights that may shed light on this unexplored correlation.
In "The Technology Paradox" by Carl Mellmann, the author expounds upon the intricate dynamics of technological integration in various industries, touching on the potential influence of digital content consumption on professional inclinations. Similarly, "The Trucking Times" by John Freightliner provides a comprehensive overview of the trucking industry, offering insights into the occupational choices of individuals within this field.
Turning to more fictional works, "Digital Highways: Navigating the Tech Terrain" by A. Byte and "Trucking Tales: From Asphalt to Zenith" by Mindy Miles are imaginative narratives that, while not grounded in academic research, portray the intersection of technology and trucking in an engaging manner.
In conducting this literature review, the researchers also took a comprehensive approach, considering a wide range of sources, including, but not limited to, the back labels of shampoo bottles, fortune cookie fortunes, and the musings of a particularly existential AI chatbot. While these sources do not meet conventional scholarly criteria, they offer a unique and, at times, unexpectedly insightful perspective on the intertwined tapestry of technology and trucking.
As the academic community continues to expand its understanding of the relationship between technology consumption and occupational choices, it is essential to remain open to unconventional sources of knowledge, embracing the offbeat and the unexpected as potential wellsprings of enlightenment.

[[RESULTS]]
The results of our analysis revealed a strikingly high correlation coefficient of 0.9954744 between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota over the period from 2015 to 2022. The r-squared value of 0.9909693 further underscored the robustness of this relationship, affirming that approximately 99.1% of the variability in the number of industrial truck and tractor operators could be explained by the average views of Technology Connections videos. The statistical significance of p < 0.01 indicated a highly unlikely scenario of these results occurring by chance, emphasizing the reliability of our findings.
Upon visual inspection of the data, it became evident that the relationship between these variables was not just an idle fluctuation, but rather a strong and persistent phenomenon resembling a steadfast truck driver navigating through diverse terrains. This was succinctly captured in the scatterplot (Fig. 1), which graphically demonstrated the clear positive linear trend between the average views of Technology Connections videos and the number of industrial truck and tractor operators in South Dakota.
The substantial correlation uncovered in our study may initially appear as unexpected as a high-tech gadget in the cab of a vintage truck, yet it presents an intriguing avenue for further exploration. Whether this association reflects a genuine influence of technology content consumption on occupational choices or simply represents a quirk of statistical fate is a question worthy of contemplation. The pronounced correlation observed in our analysis prompts a reevaluation of the potential impact of online technological discourse on occupational preferences, a notion that may have previously been as inconspicuous as a chameleon blending into its surroundings.
Overall, the robustness of the relationship between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota posits intriguing implications for the interplay between technology consumption and occupational decision-making. Our research opens the door to a domain as unexplored and unexpected as finding a yet-to-be-charted route on a long-haul drive, inviting further inquiry into the intricacies of human behavior within the ever-evolving landscape of technology and industry.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The remarkably strong correlation coefficient of 0.9954744 between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota supports the compelling connection between technology-related content consumption and occupational preferences. This finding is as surprising as stumbling upon a vintage truck inside a state-of-the-art technology facility. Our results are consistent with prior research that has accentuated the potential impact of digital content consumption on professional inclinations, echoing the sentiments of "The Technology Paradox" by Carl Mellmann. Just as a truck driver navigates the roads with precision, our findings navigate the uncharted territory of the intersection between technology and occupational choices with robustness and persistence.

The empirical evidence presented in our study aligns with the limited literature discussing the influence of digital content consumption on occupational decisions, reinforcing the notion put forth by "The Trucking Times" by John Freightliner. This unexpected alignment of technology consumption and occupational preferences evokes the image of a technological terrain seamlessly merging with the traditional highways of the trucking industry. Our research, conducted with the precision of a well-trained truck driver, expands the scholarly understanding of this correlation, emphasizing the need to remain open to unconventional sources of knowledge in this emerging field.

The statistical significance of our results, with a p-value of less than 0.01, strengthens the reliability of our findings, as unlikely as finding a high-tech gadget in the cab of a vintage truck. The high r-squared value of 0.9909693 further exemplifies the robustness of the relationship, highlighting the extent to which the average views of Technology Connections videos can explain the variability in the number of industrial truck and tractor operators in South Dakota. Just as a steadfast driver navigates diverse terrains, our analysis elucidates the persistent and substantial nature of this correlation.

Our study opens up a fresh avenue for further inquiry into the interplay between technology consumption and occupational decision-making. The unexpected nature of this correlation calls for continued exploration into the potential influence of online technological discourse on professional inclinations. Much like discovering a yet-to-be-charted route on a long-haul drive, our research hints at the enigmatic nature of the impact of technology on occupational choices, inviting scholars to delve into the intricacies of human behavior within the ever-evolving landscape of technology and industry.


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 Average views of Technology Connections YouTube videos and The number of industrial truck and tractor operators in South Dakota. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
"Truckin' Technology: Examining the Correlation Between Average Views of Technology Connections YouTube Videos and the Number of Industrial Truck and Tractor Operators in South Dakota"

[[ABSTRACT]]
This study examines the intriguing relationship between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in the state of South Dakota. Utilizing data from the Bureau of Labor Statistics and YouTube analytics from 2015 to 2022, we found a remarkably high correlation coefficient of 0.9954744, with statistical significance at p < 0.01. Our findings suggest a potential connection between the consumption of technology-related content and the occupational choices of individuals in the trucking industry. The implications of these correlations are both thought-provoking and unexpectedly entertaining.

[[INTRDUCTION]]
The trucking industry plays a vital role in the economy, transporting goods and materials across vast distances with the precision of a well-oiled machine. Similarly, the world of technology continues to evolve, connecting individuals to information and entertainment at unprecedented rates. In this study, we delved into the intersection of these seemingly disparate realms, aiming to uncover any underlying relationship between the consumption of technology-focused content and the occupational preferences of individuals within the trucking industry.
While these two domains may appear to be as unrelated as a semi-truck and a smartphone, the rise of online platforms, such as YouTube, has facilitated the widespread dissemination of information regarding technological advancements. Technology Connections, a YouTube channel specializing in all things tech, has garnered a substantial following, captivating viewers with its insightful and, dare we say, riveting content.
Furthermore, the state of South Dakota, known for its expansive landscapes and bustling trucking routes, served as the backdrop for our investigation. At first glance, one might question the rationale behind selecting this specific region for analysis. However, as we unraveled the data, the correlation between the average views of Technology Connections videos and the number of industrial truck and tractor operators in South Dakota proved to be as conspicuous as a bright, blinking turn signal on a country road at night.
The implications of our findings extend beyond the mere statistical association, venturing into the realm of cultural and occupational influence. Even though the relationship between technology consumption and occupational choices may seem as unexpected as an oversize load in a residential neighborhood, our results, like a pair of well-coordinated truck drivers zigzagging through traffic, pointed without a doubt to their interconnectedness.
With the stage set and the data ready for interpretation, we invite you on a journey of discovery, exploring a connection that, much like a sound truck engine, hums quietly beneath the surface of our modern world.

[[RESULTS]]
The results of our analysis revealed a strikingly high correlation coefficient of 0.9954744 between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota over the period from 2015 to 2022. The r-squared value of 0.9909693 further underscored the robustness of this relationship, affirming that approximately 99.1% of the variability in the number of industrial truck and tractor operators could be explained by the average views of Technology Connections videos. The statistical significance of p < 0.01 indicated a highly unlikely scenario of these results occurring by chance, emphasizing the reliability of our findings.
Upon visual inspection of the data, it became evident that the relationship between these variables was not just an idle fluctuation, but rather a strong and persistent phenomenon resembling a steadfast truck driver navigating through diverse terrains. This was succinctly captured in the scatterplot (Fig. 1), which graphically demonstrated the clear positive linear trend between the average views of Technology Connections videos and the number of industrial truck and tractor operators in South Dakota.
The substantial correlation uncovered in our study may initially appear as unexpected as a high-tech gadget in the cab of a vintage truck, yet it presents an intriguing avenue for further exploration. Whether this association reflects a genuine influence of technology content consumption on occupational choices or simply represents a quirk of statistical fate is a question worthy of contemplation. The pronounced correlation observed in our analysis prompts a reevaluation of the potential impact of online technological discourse on occupational preferences, a notion that may have previously been as inconspicuous as a chameleon blending into its surroundings.
Overall, the robustness of the relationship between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota posits intriguing implications for the interplay between technology consumption and occupational decision-making. Our research opens the door to a domain as unexplored and unexpected as finding a yet-to-be-charted route on a long-haul drive, inviting further inquiry into the intricacies of human behavior within the ever-evolving landscape of technology and industry.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study has shed light on the surprising connection between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota. The remarkably high correlation coefficient of 0.9954744, coupled with the substantial r-squared value of 0.9909693, has highlighted a relationship as strong as the grip of a well-treaded tire on a winding road. It is quite remarkable that the variability in the number of industrial truck and tractor operators in South Dakota can be explained by the average views of Technology Connections videos to an extent of approximately 99.1%. This implies a close intertwining of technological interest and occupational choices, much like the fusion of an expertly synchronized gear shift.

The statistical significance at p < 0.01 has firmly established the validity of our findings, painting a picture as clear as a meticulously clean windshield on a cross-country journey. The robustness of this relationship, akin to a sturdy trailer hitch, points to the potential influence of technology-focused content consumption on occupational decisions within the trucking industry. However, one must tread cautiously before drawing definitive conclusions, much like navigating through a precarious hairpin turn on a mountainside highway.

The unexpected nature of our findings elevates them to a level of interest as striking as a roadside attraction on a long, monotonous drive. While we have delved into this uncharted territory, it is important to exercise caution and not veer into unwarranted generalizations, as unforeseen factors could be at play, comparable to a surprise detour on a well-traveled route.

In light of these compelling results, it is tempting to speculate on the potential mechanisms underlying this correlation. Could it be that the allure of technological advancements on YouTube subtly nudges individuals towards careers in the trucking industry, much like the gentle pull of gravity on a downhill slope? Or perhaps the increase in technology-related discussions incites a renewed appreciation for the practical applications of manual labor, akin to a rekindled interest in classic truck design.

While the findings of this investigation are as solid as a meticulously parked semi-truck, it is imperative to acknowledge the limitations of our study. The focus on a specific geographical region necessitates caution when generalizing the results to other areas, much like exercising vigilance when navigating a new, unfamiliar truck route. Additionally, the observational nature of our analysis precludes causal inferences; thus, further research is warranted to elucidate the underlying dynamics linking technology consumption and occupational preferences within the trucking industry.

In conclusion, the association between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in South Dakota presents a unique and thought-provoking avenue for future inquiry. Our study paves the way for a deeper exploration of the intricate interplay between technology, consumer behavior, and occupational choices. However, much like a well-maintained truck engine that purrs contentedly as it traverses through diverse landscapes, we assert that no further research in this area is needed.


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 Truckin' Technology: Examining the Correlation Between Average Views of Technology Connections YouTube Videos and the Number of Industrial Truck and Tractor Operators in South Dakota. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Contemporary Technology Studies


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Truckin' Technology: Examining the Correlation Between Average Views of Technology Connections YouTube Videos and the Number of Industrial Truck and Tractor Operators in South Dakota. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Advanced Technological Studies


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 Truckin' Technology: Examining the Correlation Between Average Views of Technology Connections YouTube Videos and the Number of Industrial Truck and Tractor Operators in South Dakota with an abstract of This study examines the intriguing relationship between the average views of Technology Connections YouTube videos and the number of industrial truck and tractor operators in the state of South Dakota. Utilizing data from the Bureau of Labor Statistics and YouTube analytics from 2015 to 2022, we found a remarkably high correlation coefficient of 0.9954744, with statistical significance at p < 0.01. Our findings suggest a potential connection between the consumption of technology-related content and the occupational choices of individuals in the trucking industry. The implications of these correlations are both thought-provoking and unexpectedly entertaining.

ChatGPT:

Truckin' Technology, YouTube videos, Technology Connections, industrial truck operators, tractor operators, South Dakota, Bureau of Labor Statistics, YouTube analytics, correlation coefficient, occupational choices, trucking industry, technology-related content, entertainment industry

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



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Data details

Average views of Technology Connections YouTube videos
Detailed data title: Average views of Technology Connections YouTube videos.
Source: YouTube
Additional Info: Current total views of videos released that year.

See what else correlates with Average views of Technology Connections YouTube videos

The number of industrial truck and tractor operators in South Dakota
Detailed data title: BLS estimate of industrial truck and tractor operators in South Dakota
Source: Bureau of Larbor Statistics
See what else correlates with The number of industrial truck and tractor operators in South Dakota

Correlation r = 0.9954744 (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 = 0.9909693 (Coefficient of determination)
This means 99.1% of the change in the one variable (i.e., The number of industrial truck and tractor operators in South Dakota) is predictable based on the change in the other (i.e., Average views of Technology Connections YouTube videos) over the 8 years from 2015 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.31E-7. 0.0000002309389255203995700000
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 1 in 2.31E-5% of random cases. Said differently, if you correlated 4,330,149 random variables You don't actually need 4 million 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 7 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 7 because we have two variables measured over a period of 8 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.97, 1 ] 95% correlation confidence interval (using the Fisher z-transformation)
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.
20152016201720182019202020212022
Average views of Technology Connections YouTube videos (Average views)38397432573886593211756101817230189012018422301475510
The number of industrial truck and tractor operators in South Dakota (Laborers)10701080132015001910198020001750




Why this works

  1. 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.
  2. 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.
  3. 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.
  4. Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.
  5. 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([383974,325738,865932,1175610,1817230,1890120,1842230,1475510,])
array_2 = np.array([1070,1080,1320,1500,1910,1980,2000,1750,])
array_1_name = "Average views of Technology Connections YouTube videos"
array_2_name = "The number of industrial truck and tractor operators in South Dakota"

# 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)



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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.

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Correlation ID: 4555 · Black Variable ID: 25699 · Red Variable ID: 14379
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