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Spurious correlation #1,728 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Associates degrees awarded in Agriculture and natural resources and the second variable is Annual sales of the U.S. auto industry.  The chart goes from 2011 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As more people got involved in agriculture and natural resources, they realized the tractor-nology was advancing and it was time to plow money into buying new vehicles. This led to a growing demand for trucks and other auto vehicles, sowing the seeds for higher annual sales in the U.S. auto industry.

Model: dalle-3
Prompt: Generate an image showcasing the scene from Skyrim where a spacious university hall is depicted. In the hall, a group of students is proudly wearing graduation gowns, holding Associate degrees in Agriculture and Natural Resources. They are smiling as they pose for photos. In the bustling city, a line of sleek cars is seen stretching down the road, showcasing the thriving annual sales of the U.S. auto industry. The imagery should be rich in detail, highlighting the contrast between the academic setting of the university and the urban environment of the city. 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: Associates degrees awarded in Agriculture and natural resources and Annual sales of the U.S. auto industry. 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 TIME magazine cover image Woodblock painting Cubism A scene from Skyrim An image that looks like it is a scene from A Disney Movie
ChatGPT: A scene from Skyrim

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 Associates degrees awarded in Agriculture and natural resources and Annual sales of the U.S. auto industry together. Keep the description simple.
ChatGPT: In a spacious university hall, a group of students proudly wearing graduation gowns are holding their Associate degrees in Agriculture and Natural Resources, smiling as they pose for photos. Meanwhile, in the bustling city, a line of sleek cars is seen stretching down the road, showcasing the thriving annual sales of the U.S. auto 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: [ A scene from Skyrim ] and depicting this scene: In a spacious university hall, a group of students proudly wearing graduation gowns are holding their Associate degrees in Agriculture and Natural Resources, smiling as they pose for photos. Meanwhile, in the bustling city, a line of sleek cars is seen stretching down the road, showcasing the thriving annual sales of the U.S. auto industry. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image showcasing the scene from Skyrim where a spacious university hall is depicted. In the hall, a group of students is proudly wearing graduation gowns, holding Associate degrees in Agriculture and Natural Resources. They are smiling as they pose for photos. In the bustling city, a line of sleek cars is seen stretching down the road, showcasing the thriving annual sales of the U.S. auto industry. The imagery should be rich in detail, highlighting the contrast between the academic setting of the university and the urban environment of the city.

*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 Associates degrees awarded in Agriculture and natural resources caused Annual sales of the U.S. auto industry to increase. Include one good pun.

AI academic paper

(Because p < 0.01)
Digging into the Dirt: How Associates Degrees in Agriculture and Natural Resources Plow the Path for U.S. Auto Industry Sales

Journal of Ecological Economics & Agricultural Innovations

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 witty academic researcher. Your writing sounds like it belongs in a statistics 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 Associates degrees awarded in Agriculture and natural resources and Annual sales of the U.S. auto industry. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Include a pun in the title.

Your research team used data from National Center for Education Statistics and Good Car Bad Car to assess this nagging question. You found a correlation coefficient of 0.9123458 and p < 0.01 for 2011 to 2021.

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]]
"Digging into the Dirt: How Associates Degrees in Agriculture and Natural Resources Plow the Path for U.S. Auto Industry Sales"

[[ABSTRACT]]
This research delves into the intriguing and scarcely explored relationship between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry. Leveraging data from the National Center for Education Statistics and Good Car Bad Car, we uncovered a correlation coefficient of 0.9123458 with a statistically significant p-value less than 0.01 for the period spanning 2011 to 2021. Our findings unveil a surprising interplay between the nurturing of our earth and the vehicular backbone of the nation's economy, shedding light on the potential impact of greener pastures on wheels. We unearth a rich soil of insights that augur a fertile ground for further exploration of this captivating correlation.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Associates degrees awarded in Agriculture and natural resources and Annual sales of the U.S. auto industry. 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]]
"Digging into the Dirt: How Associates Degrees in Agriculture and Natural Resources Plow the Path for U.S. Auto Industry Sales"

[[ABSTRACT]]
This research delves into the intriguing and scarcely explored relationship between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry. Leveraging data from the National Center for Education Statistics and Good Car Bad Car, we uncovered a correlation coefficient of 0.9123458 with a statistically significant p-value less than 0.01 for the period spanning 2011 to 2021. Our findings unveil a surprising interplay between the nurturing of our earth and the vehicular backbone of the nation's economy, shedding light on the potential impact of greener pastures on wheels. We unearth a rich soil of insights that augur a fertile ground for further exploration of this captivating correlation.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The interconnectedness of seemingly disparate realms continues to captivate and bewilder researchers across various domains. In this study, we embark on an odyssey that unearths a hitherto overlooked connection between the fields of Agriculture and natural resources and the robust turf of the U.S. auto industry. While at first glance, these two sectors appear as unrelated as a carrot and a carburetor, our research unearths a surprising correlation that leaves us plowing through new avenues of inquiry.

The robustness of the U.S. auto industry, like a sturdy oak in a tempest, has long been a subject of fascination for business analysts and industry aficionados. On the other hand, the world of Agriculture and natural resources has often been perceived as the fertile yet humble soil from which sustenance springs forth, a far cry from the gleaming assembly lines and tire treads of the automotive landscape. Yet, as we delve into the trove of educational and industry data, we begin to detect an intriguing dance between soil and steel, between the agrarian and the automotive, that defies traditional categorizations.

Our investigation draws upon data from the National Center for Education Statistics, uncovering the yearly bounty of Associates degrees awarded in Agriculture and natural resources. Concurrently, we harvest the annual sales figures of the U.S. auto industry from the fertile fields of Good Car Bad Car, allowing for a thorough examination of the ebbs and flows in both domains. The correlation coefficient that emerged from our analysis, akin to a rare bloom in a rugged terrain, stood at a striking 0.9123458, with a p-value that twinkled at us mischievously, gracing us with its insignificance of less than 0.01.

As we stand at the juncture where the plow meets the pavement, we are called to ponder the implications of this unexpected linkage. Could it be that the tilling of the soil and the cultivation of knowledge in Agriculture and natural resources cast a shadow, or perhaps more fittingly, a ray of sunlight, over the brisk oscillations of the U.S. auto industry sales? Does the nurturing of our earth, in its own unique way, contribute to the vehicular tapestry that cruises along the nation’s highways and byways?

As we peer through this unexpected vista, we cannot dismiss the whimsicality of this correlation, nor the tantalizing prospect of the verdant intertwining with the vehicular. While our findings unveil this captivating relationship, they beckon us to dig deeper, to plumb the fertile ground of insights that it presents. Our study aims to sow the seeds of curiosity for future explorations, inviting scholars and enthusiasts alike to join us in cultivating a greater understanding of this enigmatic bond.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Associates degrees awarded in Agriculture and natural resources and Annual sales of the U.S. auto industry. 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]]
"Digging into the Dirt: How Associates Degrees in Agriculture and Natural Resources Plow the Path for U.S. Auto Industry Sales"

[[ABSTRACT]]
This research delves into the intriguing and scarcely explored relationship between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry. Leveraging data from the National Center for Education Statistics and Good Car Bad Car, we uncovered a correlation coefficient of 0.9123458 with a statistically significant p-value less than 0.01 for the period spanning 2011 to 2021. Our findings unveil a surprising interplay between the nurturing of our earth and the vehicular backbone of the nation's economy, shedding light on the potential impact of greener pastures on wheels. We unearth a rich soil of insights that augur a fertile ground for further exploration of this captivating correlation.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The interconnectedness of seemingly disparate realms continues to captivate and bewilder researchers across various domains. In this study, we embark on an odyssey that unearths a hitherto overlooked connection between the fields of Agriculture and natural resources and the robust turf of the U.S. auto industry. While at first glance, these two sectors appear as unrelated as a carrot and a carburetor, our research unearths a surprising correlation that leaves us plowing through new avenues of inquiry.
The robustness of the U.S. auto industry, like a sturdy oak in a tempest, has long been a subject of fascination for business analysts and industry aficionados. On the other hand, the world of Agriculture and natural resources has often been perceived as the fertile yet humble soil from which sustenance springs forth, a far cry from the gleaming assembly lines and tire treads of the automotive landscape. Yet, as we delve into the trove of educational and industry data, we begin to detect an intriguing dance between soil and steel, between the agrarian and the automotive, that defies traditional categorizations.
Our investigation draws upon data from the National Center for Education Statistics, uncovering the yearly bounty of Associates degrees awarded in Agriculture and natural resources. Concurrently, we harvest the annual sales figures of the U.S. auto industry from the fertile fields of Good Car Bad Car, allowing for a thorough examination of the ebbs and flows in both domains. The correlation coefficient that emerged from our analysis, akin to a rare bloom in a rugged terrain, stood at a striking 0.9123458, with a p-value that twinkled at us mischievously, gracing us with its insignificance of less than 0.01.
As we stand at the juncture where the plow meets the pavement, we are called to ponder the implications of this unexpected linkage. Could it be that the tilling of the soil and the cultivation of knowledge in Agriculture and natural resources cast a shadow, or perhaps more fittingly, a ray of sunlight, over the brisk oscillations of the U.S. auto industry sales? Does the nurturing of our earth, in its own unique way, contribute to the vehicular tapestry that cruises along the nation’s highways and byways?
As we peer through this unexpected vista, we cannot dismiss the whimsicality of this correlation, nor the tantalizing prospect of the verdant intertwining with the vehicular. While our findings unveil this captivating relationship, they beckon us to dig deeper, to plumb the fertile ground of insights that it presents. Our study aims to sow the seeds of curiosity for future explorations, inviting scholars and enthusiasts alike to join us in cultivating a greater understanding of this enigmatic bond.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The surprising correlation between the awarding of Associates degrees in Agriculture and natural resources and the annual sales of the U.S. auto industry has sparked a curious blend of fascination and incredulity among researchers. In "Harvesting Insights: Exploring the Impact of Agricultural Education on Industry Dynamics," Smith et al. leveraged data from the National Center for Education Statistics to reveal a statistically significant relationship between the two seemingly disparate fields. Their findings, much like a tractor unexpectedly revving at a flower show, offer a compelling juxtaposition of education and economic performance.

Similarly, in "Cultivating Success: The Impact of Agricultural Knowledge on Industrial Growth," Doe and Jones sifted through the fertile soil of educational and industry data to uncover an unexpected correlation that defied traditional categorizations. Their work, akin to a tractor plowing through conventional wisdom, broadened the scope of inquiry into the interconnectedness of agricultural education and the dynamism of the auto industry.

Expanding beyond the academic realm, non-fiction works such as "The Omnivore's Dilemma" and "A Sand County Almanac" provide rich insights into the complexities of agricultural practices and their repercussions on the natural environment. These texts, like a robust field of sunflowers swaying in the wind, paint a vivid picture of the deeply intertwined relationship between agriculture and the ecosystem, raising thought-provoking questions about the potential ripple effects on industrial sectors.

Turning to fiction, "Agriculture of the Gods" and "The Auto Mechanic's Apprentice" offer imaginative explorations of the intersection between the cultivation of the land and the mechanical marvels that populate our roads. While these works may not offer empirical evidence, they serve as a testament to the enduring fascination with the interplay of agriculture and automotive themes in popular culture.

In a whimsical turn, the authors also conducted an extensive review of unconventional sources, including the backs of shampoo bottles and the musings of fortune cookies, to glean any hidden nuggets of wisdom relating to this enigmatic correlation. While yielding more amusement than scholarly insight, these unconventional endeavors underscore the humorous and exploratory spirit with which the researchers approached this captivating topic.

As we navigate this meandering pathway of literature and cultural expressions, we are reminded that the unexpected interconnections between seemingly unrelated domains often hold the potential for delightful discoveries and lighthearted musings. In the pages of academia and beyond, the agrarian and the automotive intersect in ways that continue to surprise and delight, inviting us to embrace the unexpected and revel in the quirky harmony of scholarly inquiry and everyday amusement.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Associates degrees awarded in Agriculture and natural resources and Annual sales of the U.S. auto industry. 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 National Center for Education Statistics and Good Car Bad Car . You used data from 2011 to 2021

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Digging into the Dirt: How Associates Degrees in Agriculture and Natural Resources Plow the Path for U.S. Auto Industry Sales"

[[ABSTRACT]]
This research delves into the intriguing and scarcely explored relationship between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry. Leveraging data from the National Center for Education Statistics and Good Car Bad Car, we uncovered a correlation coefficient of 0.9123458 with a statistically significant p-value less than 0.01 for the period spanning 2011 to 2021. Our findings unveil a surprising interplay between the nurturing of our earth and the vehicular backbone of the nation's economy, shedding light on the potential impact of greener pastures on wheels. We unearth a rich soil of insights that augur a fertile ground for further exploration of this captivating correlation.

[[INTRODUCTION]]
The interconnectedness of seemingly disparate realms continues to captivate and bewilder researchers across various domains. In this study, we embark on an odyssey that unearths a hitherto overlooked connection between the fields of Agriculture and natural resources and the robust turf of the U.S. auto industry. While at first glance, these two sectors appear as unrelated as a carrot and a carburetor, our research unearths a surprising correlation that leaves us plowing through new avenues of inquiry.
The robustness of the U.S. auto industry, like a sturdy oak in a tempest, has long been a subject of fascination for business analysts and industry aficionados. On the other hand, the world of Agriculture and natural resources has often been perceived as the fertile yet humble soil from which sustenance springs forth, a far cry from the gleaming assembly lines and tire treads of the automotive landscape. Yet, as we delve into the trove of educational and industry data, we begin to detect an intriguing dance between soil and steel, between the agrarian and the automotive, that defies traditional categorizations.
Our investigation draws upon data from the National Center for Education Statistics, uncovering the yearly bounty of Associates degrees awarded in Agriculture and natural resources. Concurrently, we harvest the annual sales figures of the U.S. auto industry from the fertile fields of Good Car Bad Car, allowing for a thorough examination of the ebbs and flows in both domains. The correlation coefficient that emerged from our analysis, akin to a rare bloom in a rugged terrain, stood at a striking 0.9123458, with a p-value that twinkled at us mischievously, gracing us with its insignificance of less than 0.01.
As we stand at the juncture where the plow meets the pavement, we are called to ponder the implications of this unexpected linkage. Could it be that the tilling of the soil and the cultivation of knowledge in Agriculture and natural resources cast a shadow, or perhaps more fittingly, a ray of sunlight, over the brisk oscillations of the U.S. auto industry sales? Does the nurturing of our earth, in its own unique way, contribute to the vehicular tapestry that cruises along the nation’s highways and byways?
As we peer through this unexpected vista, we cannot dismiss the whimsicality of this correlation, nor the tantalizing prospect of the verdant intertwining with the vehicular. While our findings unveil this captivating relationship, they beckon us to dig deeper, to plumb the fertile ground of insights that it presents. Our study aims to sow the seeds of curiosity for future explorations, inviting scholars and enthusiasts alike to join us in cultivating a greater understanding of this enigmatic bond.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To tackle the investigative journey at hand, we employed an array of research methods that would make even the most seasoned detective green with envy. Our data collection process involved scouring the depths of the internet, wielding the potent tools of the National Center for Education Statistics and the fertile fields of Good Car Bad Car as our primary sources of information. We meticulously gathered data spanning the years 2011 to 2021, carefully cultivating a robust dataset for our analysis.

The first step in our convoluted but captivating journey was to gather the number of Associates degrees awarded in Agriculture and natural resources from the ever-fertile fields of the National Center for Education Statistics. This involved tilling through the digital soil of their databases, sowing the seeds of data collection, and reaping the rich harvest of information to be distilled and analyzed.

In parallel, our plucky band of researchers embarked on a quest to harvest the annual sales figures of the U.S. auto industry from the automotive orchard of Good Car Bad Car. Delving into the labyrinthine pathways of vehicular sales data, we carefully plucked the ripest and most reliable figures, eschewing the rotten apples of inaccuracy and bias.

With these ripe fruits of data in hand, we threshed and winnowed through the numbers, conducting a thorough examination of the correlation between the two seemingly unrelated realms. Our statistical analysis, akin to coaxing secrets from the earth itself, brought forth a correlation coefficient of 0.9123458, a stout and robust figure that stood tall amidst the statistical underbrush. The mischievous p-value, which whimsically teased us with its insubstantiality of less than 0.01, further bolstered the significance of our findings, much like a sturdy trellis supporting a vine heavy with research fruit.

In essence, our research approach embodies the spirit of a daring explorer venturing into uncharted territories, armed with the tools of statistical analysis and a steadfast determination to unveil the hidden connections between the fields of Agriculture and natural resources and the thriving domain of U.S. auto industry sales. As we till the soil of data and sow the seeds of inquiry, we unearth a landscape of unexpected interplay, beckoning us to plow through new avenues of investigation and cultivate a greater understanding of this captivating correlation.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Associates degrees awarded in Agriculture and natural resources and Annual sales of the U.S. auto industry. 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 National Center for Education Statistics and Good Car Bad Car .

For the time period 2011 to 2021, you found a correlation 0.9123458, r-squared of 0.8323748, 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]]
"Digging into the Dirt: How Associates Degrees in Agriculture and Natural Resources Plow the Path for U.S. Auto Industry Sales"

[[ABSTRACT]]
This research delves into the intriguing and scarcely explored relationship between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry. Leveraging data from the National Center for Education Statistics and Good Car Bad Car, we uncovered a correlation coefficient of 0.9123458 with a statistically significant p-value less than 0.01 for the period spanning 2011 to 2021. Our findings unveil a surprising interplay between the nurturing of our earth and the vehicular backbone of the nation's economy, shedding light on the potential impact of greener pastures on wheels. We unearth a rich soil of insights that augur a fertile ground for further exploration of this captivating correlation.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The interconnectedness of seemingly disparate realms continues to captivate and bewilder researchers across various domains. In this study, we embark on an odyssey that unearths a hitherto overlooked connection between the fields of Agriculture and natural resources and the robust turf of the U.S. auto industry. While at first glance, these two sectors appear as unrelated as a carrot and a carburetor, our research unearths a surprising correlation that leaves us plowing through new avenues of inquiry.
The robustness of the U.S. auto industry, like a sturdy oak in a tempest, has long been a subject of fascination for business analysts and industry aficionados. On the other hand, the world of Agriculture and natural resources has often been perceived as the fertile yet humble soil from which sustenance springs forth, a far cry from the gleaming assembly lines and tire treads of the automotive landscape. Yet, as we delve into the trove of educational and industry data, we begin to detect an intriguing dance between soil and steel, between the agrarian and the automotive, that defies traditional categorizations.
Our investigation draws upon data from the National Center for Education Statistics, uncovering the yearly bounty of Associates degrees awarded in Agriculture and natural resources. Concurrently, we harvest the annual sales figures of the U.S. auto industry from the fertile fields of Good Car Bad Car, allowing for a thorough examination of the ebbs and flows in both domains. The correlation coefficient that emerged from our analysis, akin to a rare bloom in a rugged terrain, stood at a striking 0.9123458, with a p-value that twinkled at us mischievously, gracing us with its insignificance of less than 0.01.
As we stand at the juncture where the plow meets the pavement, we are called to ponder the implications of this unexpected linkage. Could it be that the tilling of the soil and the cultivation of knowledge in Agriculture and natural resources cast a shadow, or perhaps more fittingly, a ray of sunlight, over the brisk oscillations of the U.S. auto industry sales? Does the nurturing of our earth, in its own unique way, contribute to the vehicular tapestry that cruises along the nation’s highways and byways?
As we peer through this unexpected vista, we cannot dismiss the whimsicality of this correlation, nor the tantalizing prospect of the verdant intertwining with the vehicular. While our findings unveil this captivating relationship, they beckon us to dig deeper, to plumb the fertile ground of insights that it presents. Our study aims to sow the seeds of curiosity for future explorations, inviting scholars and enthusiasts alike to join us in cultivating a greater understanding of this enigmatic bond.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our analysis reveal a remarkably strong and positive correlation between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry for the period spanning 2011 to 2021. The correlation coefficient of 0.9123458 signifies a robust relationship between these seemingly incongruous domains. This value is supported by an r-squared of 0.8323748, indicating that approximately 83.24% of the variance in U.S. auto industry sales can be accounted for by the number of Associates degrees awarded in Agriculture and natural resources. Moreover, the p-value of less than 0.01 attests to the statistical significance of this correlation, further bolstering the credibility of our findings.

To visually encapsulate the strength of this relationship, we present a scatterplot in Fig. 1, which delineates the clear and compelling pattern of association between the two variables. The scatterplot provides a vivid depiction of the dynamic interplay between the cultivation of agricultural knowledge and the vehicular commerce, underscoring the robustness of the observed correlation.

This unexpected linkage between the agricultural and automotive spheres prompts us to plow through new avenues of inquiry and sow the seeds of curiosity for future explorations. While our study has unearthed a rich soil of insights, it also invites scholars and enthusiasts alike to join us in cultivating a greater understanding of this captivating correlation. This intriguing relationship between plows and pedals serves as a reminder that, in the vast landscape of interconnected economic and educational endeavors, the intertwining of disparate industries may yield surprising and fertile ground for further exploration.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Associates degrees awarded in Agriculture and natural resources and Annual sales of the U.S. auto industry. 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]]
"Digging into the Dirt: How Associates Degrees in Agriculture and Natural Resources Plow the Path for U.S. Auto Industry Sales"

[[ABSTRACT]]
This research delves into the intriguing and scarcely explored relationship between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry. Leveraging data from the National Center for Education Statistics and Good Car Bad Car, we uncovered a correlation coefficient of 0.9123458 with a statistically significant p-value less than 0.01 for the period spanning 2011 to 2021. Our findings unveil a surprising interplay between the nurturing of our earth and the vehicular backbone of the nation's economy, shedding light on the potential impact of greener pastures on wheels. We unearth a rich soil of insights that augur a fertile ground for further exploration of this captivating correlation.

[[LITERATURE REVIEW]]
The surprising correlation between the awarding of Associates degrees in Agriculture and natural resources and the annual sales of the U.S. auto industry has sparked a curious blend of fascination and incredulity among researchers. In "Harvesting Insights: Exploring the Impact of Agricultural Education on Industry Dynamics," Smith et al. leveraged data from the National Center for Education Statistics to reveal a statistically significant relationship between the two seemingly disparate fields. Their findings, much like a tractor unexpectedly revving at a flower show, offer a compelling juxtaposition of education and economic performance.
Similarly, in "Cultivating Success: The Impact of Agricultural Knowledge on Industrial Growth," Doe and Jones sifted through the fertile soil of educational and industry data to uncover an unexpected correlation that defied traditional categorizations. Their work, akin to a tractor plowing through conventional wisdom, broadened the scope of inquiry into the interconnectedness of agricultural education and the dynamism of the auto industry.
Expanding beyond the academic realm, non-fiction works such as "The Omnivore's Dilemma" and "A Sand County Almanac" provide rich insights into the complexities of agricultural practices and their repercussions on the natural environment. These texts, like a robust field of sunflowers swaying in the wind, paint a vivid picture of the deeply intertwined relationship between agriculture and the ecosystem, raising thought-provoking questions about the potential ripple effects on industrial sectors.
Turning to fiction, "Agriculture of the Gods" and "The Auto Mechanic's Apprentice" offer imaginative explorations of the intersection between the cultivation of the land and the mechanical marvels that populate our roads. While these works may not offer empirical evidence, they serve as a testament to the enduring fascination with the interplay of agriculture and automotive themes in popular culture.
In a whimsical turn, the authors also conducted an extensive review of unconventional sources, including the backs of shampoo bottles and the musings of fortune cookies, to glean any hidden nuggets of wisdom relating to this enigmatic correlation. While yielding more amusement than scholarly insight, these unconventional endeavors underscore the humorous and exploratory spirit with which the researchers approached this captivating topic.
As we navigate this meandering pathway of literature and cultural expressions, we are reminded that the unexpected interconnections between seemingly unrelated domains often hold the potential for delightful discoveries and lighthearted musings. In the pages of academia and beyond, the agrarian and the automotive intersect in ways that continue to surprise and delight, inviting us to embrace the unexpected and revel in the quirky harmony of scholarly inquiry and everyday amusement.

[[RESULTS]]
The results of our analysis reveal a remarkably strong and positive correlation between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry for the period spanning 2011 to 2021. The correlation coefficient of 0.9123458 signifies a robust relationship between these seemingly incongruous domains. This value is supported by an r-squared of 0.8323748, indicating that approximately 83.24% of the variance in U.S. auto industry sales can be accounted for by the number of Associates degrees awarded in Agriculture and natural resources. Moreover, the p-value of less than 0.01 attests to the statistical significance of this correlation, further bolstering the credibility of our findings.
To visually encapsulate the strength of this relationship, we present a scatterplot in Fig. 1, which delineates the clear and compelling pattern of association between the two variables. The scatterplot provides a vivid depiction of the dynamic interplay between the cultivation of agricultural knowledge and the vehicular commerce, underscoring the robustness of the observed correlation.
This unexpected linkage between the agricultural and automotive spheres prompts us to plow through new avenues of inquiry and sow the seeds of curiosity for future explorations. While our study has unearthed a rich soil of insights, it also invites scholars and enthusiasts alike to join us in cultivating a greater understanding of this captivating correlation. This intriguing relationship between plows and pedals serves as a reminder that, in the vast landscape of interconnected economic and educational endeavors, the intertwining of disparate industries may yield surprising and fertile ground for further exploration.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of our study offer compelling support for the previously posited correlation between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry. Our findings align with prior research that, much like a tractor unexpectedly revving at a flower show, illuminated the unexpected link between the nurturing of our earth and the vehicular backbone of the nation's economy.

The statistically significant correlation coefficient of 0.9123458 and the high r-squared value of 0.8323748 underscore the robustness of the relationship between these seemingly incongruous domains. This strong statistical evidence buttresses the compelling narrative that has been cultivated by scholarly inquiries into the unexpected interplay of agricultural education and the dynamism of the auto industry.

Furthermore, our results lend credence to the thought-provoking questions raised in fictional works such as "Agriculture of the Gods" and "The Auto Mechanic's Apprentice," which whimsically explore the intersection between the cultivation of the land and the mechanical marvels that populate our roads. While these works may have been designed for amusement, they offer a prescient insight into the interconnectedness of agriculture and automotive themes in popular culture, reflecting the enduring fascination with this enigmatic correlation.

The unexpected linkage that we have uncovered serves as a reminder that, in the vast landscape of interconnected economic and educational endeavors, the intertwining of disparate industries may yield surprising and fertile ground for further exploration. As we plow through new avenues of inquiry, our study opens the door to the cultivation of a greater understanding of this captivating correlation, inviting enthusiasts and scholars to join us in sowing the seeds of curiosity for future explorations.

In conclusion, the agricultural and automotive sectors continue to surprise and delight with their quirky harmony and unexpected synergy. Our study adds another layer to the rich tapestry of research that celebrates the interwoven nature of these domains, illustrating the potential for delightful discoveries and lighthearted musings in scholarly inquiry and everyday amusement.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Associates degrees awarded in Agriculture and natural resources and Annual sales of the U.S. auto industry. 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]]
"Digging into the Dirt: How Associates Degrees in Agriculture and Natural Resources Plow the Path for U.S. Auto Industry Sales"

[[ABSTRACT]]
This research delves into the intriguing and scarcely explored relationship between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry. Leveraging data from the National Center for Education Statistics and Good Car Bad Car, we uncovered a correlation coefficient of 0.9123458 with a statistically significant p-value less than 0.01 for the period spanning 2011 to 2021. Our findings unveil a surprising interplay between the nurturing of our earth and the vehicular backbone of the nation's economy, shedding light on the potential impact of greener pastures on wheels. We unearth a rich soil of insights that augur a fertile ground for further exploration of this captivating correlation.

[[INTRDUCTION]]
The interconnectedness of seemingly disparate realms continues to captivate and bewilder researchers across various domains. In this study, we embark on an odyssey that unearths a hitherto overlooked connection between the fields of Agriculture and natural resources and the robust turf of the U.S. auto industry. While at first glance, these two sectors appear as unrelated as a carrot and a carburetor, our research unearths a surprising correlation that leaves us plowing through new avenues of inquiry.
The robustness of the U.S. auto industry, like a sturdy oak in a tempest, has long been a subject of fascination for business analysts and industry aficionados. On the other hand, the world of Agriculture and natural resources has often been perceived as the fertile yet humble soil from which sustenance springs forth, a far cry from the gleaming assembly lines and tire treads of the automotive landscape. Yet, as we delve into the trove of educational and industry data, we begin to detect an intriguing dance between soil and steel, between the agrarian and the automotive, that defies traditional categorizations.
Our investigation draws upon data from the National Center for Education Statistics, uncovering the yearly bounty of Associates degrees awarded in Agriculture and natural resources. Concurrently, we harvest the annual sales figures of the U.S. auto industry from the fertile fields of Good Car Bad Car, allowing for a thorough examination of the ebbs and flows in both domains. The correlation coefficient that emerged from our analysis, akin to a rare bloom in a rugged terrain, stood at a striking 0.9123458, with a p-value that twinkled at us mischievously, gracing us with its insignificance of less than 0.01.
As we stand at the juncture where the plow meets the pavement, we are called to ponder the implications of this unexpected linkage. Could it be that the tilling of the soil and the cultivation of knowledge in Agriculture and natural resources cast a shadow, or perhaps more fittingly, a ray of sunlight, over the brisk oscillations of the U.S. auto industry sales? Does the nurturing of our earth, in its own unique way, contribute to the vehicular tapestry that cruises along the nation’s highways and byways?
As we peer through this unexpected vista, we cannot dismiss the whimsicality of this correlation, nor the tantalizing prospect of the verdant intertwining with the vehicular. While our findings unveil this captivating relationship, they beckon us to dig deeper, to plumb the fertile ground of insights that it presents. Our study aims to sow the seeds of curiosity for future explorations, inviting scholars and enthusiasts alike to join us in cultivating a greater understanding of this enigmatic bond.

[[RESULTS]]
The results of our analysis reveal a remarkably strong and positive correlation between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry for the period spanning 2011 to 2021. The correlation coefficient of 0.9123458 signifies a robust relationship between these seemingly incongruous domains. This value is supported by an r-squared of 0.8323748, indicating that approximately 83.24% of the variance in U.S. auto industry sales can be accounted for by the number of Associates degrees awarded in Agriculture and natural resources. Moreover, the p-value of less than 0.01 attests to the statistical significance of this correlation, further bolstering the credibility of our findings.
To visually encapsulate the strength of this relationship, we present a scatterplot in Fig. 1, which delineates the clear and compelling pattern of association between the two variables. The scatterplot provides a vivid depiction of the dynamic interplay between the cultivation of agricultural knowledge and the vehicular commerce, underscoring the robustness of the observed correlation.
This unexpected linkage between the agricultural and automotive spheres prompts us to plow through new avenues of inquiry and sow the seeds of curiosity for future explorations. While our study has unearthed a rich soil of insights, it also invites scholars and enthusiasts alike to join us in cultivating a greater understanding of this captivating correlation. This intriguing relationship between plows and pedals serves as a reminder that, in the vast landscape of interconnected economic and educational endeavors, the intertwining of disparate industries may yield surprising and fertile ground for further exploration.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study has succeeded in unearthing a remarkable correlation between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry. The robust correlation coefficient of 0.9123458, coupled with a statistically significant p-value of less than 0.01, offers compelling evidence of the intertwining of these seemingly disparate domains. It appears that the nurturing of our earth and the bustling automotive landscape are not as distant as they may initially seem.

The implications of this intriguing relationship extend far beyond the realms of academia and industry analysis. As we traverse the fertile ground of this correlation, we cannot help but marvel at the unexpected dance between the plow and the pedal, the seed and the steel. The convergence of agricultural knowledge and vehicular commerce hints at a symbiotic relationship that defies traditional categorizations and leaves us pondering the verdant tapestry woven between these domains.

While our study provides a fertile foundation for further exploration, we are keenly aware of the fertile ground that awaits future researchers in this captivating area. The tantalizing prospect of delving deeper into this enigmatic linkage calls for continued cultivation of knowledge and insights. However, we assert, with a wry smile and perhaps a hint of whimsy, that no more research is needed in this area. After all, we wouldn't want to plow this field to death!


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 Digging into the Dirt: How Associates Degrees in Agriculture and Natural Resources Plow the Path for U.S. Auto Industry Sales. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Ecological Economics & Agricultural Innovations


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 Digging into the Dirt: How Associates Degrees in Agriculture and Natural Resources Plow the Path for U.S. Auto Industry Sales. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Agricultural Advancements and Resource Sustainability


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 Digging into the Dirt: How Associates Degrees in Agriculture and Natural Resources Plow the Path for U.S. Auto Industry Sales with an abstract of This research delves into the intriguing and scarcely explored relationship between the number of Associates degrees awarded in Agriculture and natural resources and the annual sales of the U.S. auto industry. Leveraging data from the National Center for Education Statistics and Good Car Bad Car, we uncovered a correlation coefficient of 0.9123458 with a statistically significant p-value less than 0.01 for the period spanning 2011 to 2021. Our findings unveil a surprising interplay between the nurturing of our earth and the vehicular backbone of the nation's economy, shedding light on the potential impact of greener pastures on wheels. We unearth a rich soil of insights that augur a fertile ground for further exploration of this captivating correlation.

ChatGPT:

associates degrees, agriculture and natural resources, U.S. auto industry, annual sales, correlation coefficient, National Center for Education Statistics, Good Car Bad Car, data analysis, greener pastures, earth nurturing, vehicular backbone, U.S. economy, exploration, correlation analysis

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



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Data details

Associates degrees awarded in Agriculture and natural resources
Detailed data title: Associate's degrees conferred by postsecondary institutions with a field of study of Agriculture and natural resources
Source: National Center for Education Statistics
See what else correlates with Associates degrees awarded in Agriculture and natural resources

Annual sales of the U.S. auto industry
Source: Good Car Bad Car
See what else correlates with Annual sales of the U.S. auto industry

Correlation r = 0.9123458 (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 = 0.8323748 (Coefficient of determination)
This means 83.2% of the change in the one variable (i.e., Annual sales of the U.S. auto industry) is predictable based on the change in the other (i.e., Associates degrees awarded in Agriculture and natural resources) over the 11 years from 2011 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 9.005E-5. 0.0000900481708197173000000000
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 0.91 in 0.009005% of random cases. Said differently, if you correlated 11,105 random variables Which I absolutely did.
with the same 10 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.69, 0.98 ] 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.
20112012201320142015201620172018201920202021
Associates degrees awarded in Agriculture and natural resources (Degrees awarded)1125712691127061265513759134841368613087132291274011847
Annual sales of the U.S. auto industry (USD)1292310015614700156726001653690017501500175958001727910017377900170532001471100014954800




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.




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([11257,12691,12706,12655,13759,13484,13686,13087,13229,12740,11847,])
array_2 = np.array([12923100,15614700,15672600,16536900,17501500,17595800,17279100,17377900,17053200,14711000,14954800,])
array_1_name = "Associates degrees awarded in Agriculture and natural resources"
array_2_name = "Annual sales of the U.S. auto industry"

# 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 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.

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Correlation ID: 1728 · Black Variable ID: 1206 · Red Variable ID: 283
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