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AI explanation
As more mathematicians and statisticians graduate, they start calculating all the possible trajectories of the stock market. Their complex equations and formulas lead to a surge in accurate stock predictions, making Lockheed Martin a top pick. This newfound demand for LMT stock drives up the price as these number-savvy individuals engage in some serious mathematical stock market manipulation. It's like they say, when math geeks crunch numbers, stock prices go up, up, and array!Model: dalle-3
Prompt: Create an image of a university graduation ceremony where students in formal caps and gowns cheerfully pose for a group photo, proudly holding up their Bachelor's degrees in Mathematics and Statistics. The students are surrounded by the traditional buildings of a university campus. In the background, a digital stock ticker displays the fluctuating stock price of Lockheed Martin, adding a touch of futuristic symbolism to the scene. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:
Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Bachelor's degrees awarded in Mathematics and statistics and Lockheed Martin's stock price. 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: Cyberpunk Symbolism Whimsical illustration A scene from Skyrim Scalar art
ChatGPT: Symbolism
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Bachelor's degrees awarded in Mathematics and statistics and Lockheed Martin's stock price together. Keep the description simple.
ChatGPT: A university graduation ceremony where students in caps and gowns proudly hold up their Bachelor's degrees in Mathematics and statistics, while a stock ticker displaying Lockheed Martin's stock price can be seen in the background.
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: [ Symbolism ] and depicting this scene: A university graduation ceremony where students in caps and gowns proudly hold up their Bachelor's degrees in Mathematics and statistics, while a stock ticker displaying Lockheed Martin's stock price can be seen in the background. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a university graduation ceremony where students in formal caps and gowns cheerfully pose for a group photo, proudly holding up their Bachelor's degrees in Mathematics and Statistics. The students are surrounded by the traditional buildings of a university campus. In the background, a digital stock ticker displays the fluctuating stock price of Lockheed Martin, adding a touch of futuristic symbolism to the scene.
*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.
I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Bachelor's degrees awarded in Mathematics and statistics caused Lockheed Martin's stock price (LMT) to increase. Make it feel plausible.
AI academic paper
Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price The Journal of Statistical Finance and Aerospace Engineering Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Bachelor's degrees awarded in Mathematics and statistics and Lockheed Martin's stock price (LMT). Make lots of jokes, goofy observations, and puns.
Include a pun in the title.
Your research team used data from National Center for Education Statistics and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9610188 and p < 0.01 for 2012 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]]
"Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price"
[[ABSTRACT]]
Who knew that crunching numbers could lead to soaring stock prices? In this research, we dive into the intriguing relationship between the number of Bachelor's degrees awarded in mathematics and statistics and the stock price of aerospace giant Lockheed Martin (LMT). Using data from the National Center for Education Statistics and LSEG Analytics, we meticulously analyzed the trends from 2012 to 2021. Astonishingly, our findings revealed a strikingly high correlation coefficient of 0.9610188 and p < 0.01. It seems that when it comes to predicting Lockheed Martin's stock performance, a little math and statistics can go a long way. So, next time you're pondering over stock investments, don't forget to factor in some numbers – it might just be the formula for multiplying your returns!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Bachelor's degrees awarded in Mathematics and statistics and Lockheed Martin's stock price (LMT). Make lots of jokes, goofy observations, and puns.
Here is the title and abstract of the paper:
[[TITLE]]
"Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price"
[[ABSTRACT]]
Who knew that crunching numbers could lead to soaring stock prices? In this research, we dive into the intriguing relationship between the number of Bachelor's degrees awarded in mathematics and statistics and the stock price of aerospace giant Lockheed Martin (LMT). Using data from the National Center for Education Statistics and LSEG Analytics, we meticulously analyzed the trends from 2012 to 2021. Astonishingly, our findings revealed a strikingly high correlation coefficient of 0.9610188 and p < 0.01. It seems that when it comes to predicting Lockheed Martin's stock performance, a little math and statistics can go a long way. So, next time you're pondering over stock investments, don't forget to factor in some numbers – it might just be the formula for multiplying your returns!
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
Alright folks, buckle up for a wild ride through the world of numbers, stock prices, and a sprinkle of mathematical magic! We all know that "math is everywhere," but did you ever think it could have such a profound impact on the stock market? Get ready to have your calculators and portfolios at the ready because we're about to explore the unexpected and downright baffling relationship between Bachelor's degrees awarded in mathematics and statistics and Lockheed Martin's (LMT) stock price.
You might be wondering, "What on earth do math nerds have to do with massive aerospace and defense companies?" Well, my dear reader, the answers lie within the labyrinth of data, trend-chasing, and a little sprinkle of statistical wizardry. As much as it might sound like we're embarking on a quest for the Holy Grail of stock market predictions, bear in mind that we're chasing correlations, not crystal balls!
Picture this - a quirkily charming statistician walks into a bar (or a data research lab - whichever is more your vibe) and strikes up a conversation about quadratic equations and stock market fluctuations. Seemingly unrelated, right? Surprisingly, what if I told you that this seemingly improbable conversation sparked a whirlwind romance culminating in a dazzling correlation between math and Lockheed Martin’s stock price? Yes, this is the kind of rollercoaster we're strapped into for this research. It's like a statistical telenovela, but with more scatter plots and fewer dramatic close-ups.
We're diving into a realm where numbers hold the key to unlocking the mysteries of market movements. It's a world where the humble Bachelor's degrees in mathematics and statistics rise to the occasion, donning capes of predictive prowess and marching hand in hand with Lockheed Martin's stock price – a match made in analytical heaven.
So, if you're ready to embark on this epic statistical voyage filled with curves, trends, and financial fusions, join us on this mathematically unconventional journey. Who knows, by the time we're done, you might just be itching to rush off and invest in stocks with a newfound appreciation for mathematics – or at the very least, impress your friends with some statistical stock market banter over brunch!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Bachelor's degrees awarded in Mathematics and statistics and Lockheed Martin's stock price (LMT). Make lots of jokes, goofy observations, and puns.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some cartoons and childrens' shows that you watched that are related to the topic.
Here is the title and abstract of the paper:
[[TITLE]]
"Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price"
[[ABSTRACT]]
Who knew that crunching numbers could lead to soaring stock prices? In this research, we dive into the intriguing relationship between the number of Bachelor's degrees awarded in mathematics and statistics and the stock price of aerospace giant Lockheed Martin (LMT). Using data from the National Center for Education Statistics and LSEG Analytics, we meticulously analyzed the trends from 2012 to 2021. Astonishingly, our findings revealed a strikingly high correlation coefficient of 0.9610188 and p < 0.01. It seems that when it comes to predicting Lockheed Martin's stock performance, a little math and statistics can go a long way. So, next time you're pondering over stock investments, don't forget to factor in some numbers – it might just be the formula for multiplying your returns!
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Alright folks, buckle up for a wild ride through the world of numbers, stock prices, and a sprinkle of mathematical magic! We all know that "math is everywhere," but did you ever think it could have such a profound impact on the stock market? Get ready to have your calculators and portfolios at the ready because we're about to explore the unexpected and downright baffling relationship between Bachelor's degrees awarded in mathematics and statistics and Lockheed Martin's (LMT) stock price.
You might be wondering, "What on earth do math nerds have to do with massive aerospace and defense companies?" Well, my dear reader, the answers lie within the labyrinth of data, trend-chasing, and a little sprinkle of statistical wizardry. As much as it might sound like we're embarking on a quest for the Holy Grail of stock market predictions, bear in mind that we're chasing correlations, not crystal balls!
Picture this - a quirkily charming statistician walks into a bar (or a data research lab - whichever is more your vibe) and strikes up a conversation about quadratic equations and stock market fluctuations. Seemingly unrelated, right? Surprisingly, what if I told you that this seemingly improbable conversation sparked a whirlwind romance culminating in a dazzling correlation between math and Lockheed Martin’s stock price? Yes, this is the kind of rollercoaster we're strapped into for this research. It's like a statistical telenovela, but with more scatter plots and fewer dramatic close-ups.
We're diving into a realm where numbers hold the key to unlocking the mysteries of market movements. It's a world where the humble Bachelor's degrees in mathematics and statistics rise to the occasion, donning capes of predictive prowess and marching hand in hand with Lockheed Martin's stock price – a match made in analytical heaven.
So, if you're ready to embark on this epic statistical voyage filled with curves, trends, and financial fusions, join us on this mathematically unconventional journey. Who knows, by the time we're done, you might just be itching to rush off and invest in stocks with a newfound appreciation for mathematics – or at the very least, impress your friends with some statistical stock market banter over brunch!
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The relationship between academic degrees in mathematics and statistics and stock prices has been a subject of interest for researchers and investors alike. Smith et al. (2010) conducted a thorough analysis of the correlation between the number of mathematics and statistics degrees awarded and stock performance, revealing statistically significant connections in various industries. Similarly, Doe and Jones (2015) explored the impact of mathematical expertise on financial markets, shedding light on the potential predictive power of quantitative skills.
However, as we venture deeper into the labyrinths of literature, we find ourselves in a whimsical landscape where numbers and stock prices collide with unexpected and downright quirky intersections. In "The Mathematics of Love" by Hannah Fry, the author ingeniously intertwines mathematical principles with real-world phenomena, proving that even matters of the heart can be dissected with statistical wizardry. Moving from the land of non-fiction to the realm of fiction, we encounter "The Probability of Miracles" by Wendy Wunder, where probability and chance intertwine in a tapestry of awe and wonderment.
Venturing into the realm of childhood nostalgia, we recall the mathematically inclined mishaps of Lisa Simpson in "The Simpsons" and the cryptic number puzzles unravelled by the enigmatic Agent P in "Phineas and Ferb." Here, we witness the playful integration of mathematics and problem-solving, proving that even in the animated domain, numbers know no boundaries.
As our academic journey takes an esoteric turn, we stumble upon the realization that the allure of mathematics and statistics transcends conventional boundaries, infusing humor and peculiarity into our exploration of the uncanny relationship between Bachelor's degrees in mathematics and statistics and Lockheed Martin's stock price.
Stay tuned as we unravel this enigmatic connection with a touch of whimsy and a sprinkle of statistical stardust - for in the world of numbers and stock prices, the unexpected reigns supreme.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between Bachelor's degrees awarded in Mathematics and statistics and Lockheed Martin's stock price (LMT). Make lots of jokes, goofy observations, and puns.
Your research team collected data from all across the internet, but mostly just used information from National Center for Education Statistics and LSEG Analytics (Refinitiv) . You used data from 2012 to 2021
Make up the research methods you don't know. Make them a bit goofy and convoluted.
Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price"
[[ABSTRACT]]
Who knew that crunching numbers could lead to soaring stock prices? In this research, we dive into the intriguing relationship between the number of Bachelor's degrees awarded in mathematics and statistics and the stock price of aerospace giant Lockheed Martin (LMT). Using data from the National Center for Education Statistics and LSEG Analytics, we meticulously analyzed the trends from 2012 to 2021. Astonishingly, our findings revealed a strikingly high correlation coefficient of 0.9610188 and p < 0.01. It seems that when it comes to predicting Lockheed Martin's stock performance, a little math and statistics can go a long way. So, next time you're pondering over stock investments, don't forget to factor in some numbers – it might just be the formula for multiplying your returns!
[[INTRODUCTION]]
Alright folks, buckle up for a wild ride through the world of numbers, stock prices, and a sprinkle of mathematical magic! We all know that "math is everywhere," but did you ever think it could have such a profound impact on the stock market? Get ready to have your calculators and portfolios at the ready because we're about to explore the unexpected and downright baffling relationship between Bachelor's degrees awarded in mathematics and statistics and Lockheed Martin's (LMT) stock price.
You might be wondering, "What on earth do math nerds have to do with massive aerospace and defense companies?" Well, my dear reader, the answers lie within the labyrinth of data, trend-chasing, and a little sprinkle of statistical wizardry. As much as it might sound like we're embarking on a quest for the Holy Grail of stock market predictions, bear in mind that we're chasing correlations, not crystal balls!
Picture this - a quirkily charming statistician walks into a bar (or a data research lab - whichever is more your vibe) and strikes up a conversation about quadratic equations and stock market fluctuations. Seemingly unrelated, right? Surprisingly, what if I told you that this seemingly improbable conversation sparked a whirlwind romance culminating in a dazzling correlation between math and Lockheed Martin’s stock price? Yes, this is the kind of rollercoaster we're strapped into for this research. It's like a statistical telenovela, but with more scatter plots and fewer dramatic close-ups.
We're diving into a realm where numbers hold the key to unlocking the mysteries of market movements. It's a world where the humble Bachelor's degrees in mathematics and statistics rise to the occasion, donning capes of predictive prowess and marching hand in hand with Lockheed Martin's stock price – a match made in analytical heaven.
So, if you're ready to embark on this epic statistical voyage filled with curves, trends, and financial fusions, join us on this mathematically unconventional journey. Who knows, by the time we're done, you might just be itching to rush off and invest in stocks with a newfound appreciation for mathematics – or at the very least, impress your friends with some statistical stock market banter over brunch!
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
Now, before we get into the nitty-gritty of our data analysis, let's take a moment to appreciate the sheer absurdity of this endeavor. We set out to bridge the gap between the realm of academia and the seemingly unrelated world of stock prices, and boy, did we uncover some unexpected connections along the way!
To kick things off, we employed a combination of quantitative research methods that would have made Pythagoras himself raise an eyebrow in disbelief. Using data sourced from the National Center for Education Statistics and LSEG Analytics (Refinitiv), we embarked on a digital treasure hunt for the elusive numbers that would encapsulate the essence of this peculiar relationship.
Our data collection process resembled a high-stakes game of digital hopscotch, where we leaped from one database to another, navigating through the virtual minefield of spreadsheets and statistical archives. It often felt like we were spelunkers delving deep into the cavernous depths of the internet, armed only with our wits and an insatiable curiosity for numerical patterns.
Once we had amassed a treasure trove of relevant data spanning the years 2012 to 2021, it was time to don our metaphorical lab coats and unleash the power of statistical analysis. Our trusty tools of the trade included regression analysis, correlation coefficients, and enough pivot tables to make even the most dedicated numbers enthusiast question their sanity.
Picture this: a team of intrepid researchers huddled around computer screens, eyes darting between rows and columns like seasoned detectives solving a mystery. Each click of the mouse and keystroke held the potential to unravel the enigma of how Bachelor's degrees in mathematics and statistics could sway the fortunes of Lockheed Martin's stock price.
Our methodological concoction included a hearty blend of time series analysis and trend-spotting, reminiscent of a digital séance where we summoned the spirits of financial trends past, present, and future. If there's one thing we learned from this process, it's that navigating the labyrinth of stock market data requires not just mathematical expertise, but a touch of the daring and a pinch of statistical audacity.
In the end, after countless hours of code-cracking and analysis, our findings emerged like a mythical creature stepping out of the statistical mist – a correlation coefficient of 0.9610188 and a p-value of less than 0.01. It was a eureka moment that felt akin to stumbling upon the fabled pot of gold at the end of a mathematical rainbow.
So, dear readers, take a deep breath and gird your loins for the mind-bending journey that lies ahead. As we delve into the heart of our data analysis, be prepared for a rollercoaster ride of statistical revelations and stock market surprises that will have you questioning the very fabric of reality – or at least the correlation between numbers and financial fortuity!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Bachelor's degrees awarded in Mathematics and statistics and Lockheed Martin's stock price (LMT). Make lots of jokes, goofy observations, and puns.
Your research team collected data from all across the internet, but mostly just used information from National Center for Education Statistics and LSEG Analytics (Refinitiv) .
For the time period 2012 to 2021, you found a correlation 0.9610188, r-squared of 0.9235572, 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]]
"Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price"
[[ABSTRACT]]
Who knew that crunching numbers could lead to soaring stock prices? In this research, we dive into the intriguing relationship between the number of Bachelor's degrees awarded in mathematics and statistics and the stock price of aerospace giant Lockheed Martin (LMT). Using data from the National Center for Education Statistics and LSEG Analytics, we meticulously analyzed the trends from 2012 to 2021. Astonishingly, our findings revealed a strikingly high correlation coefficient of 0.9610188 and p < 0.01. It seems that when it comes to predicting Lockheed Martin's stock performance, a little math and statistics can go a long way. So, next time you're pondering over stock investments, don't forget to factor in some numbers – it might just be the formula for multiplying your returns!
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
Alright folks, buckle up for a wild ride through the world of numbers, stock prices, and a sprinkle of mathematical magic! We all know that "math is everywhere," but did you ever think it could have such a profound impact on the stock market? Get ready to have your calculators and portfolios at the ready because we're about to explore the unexpected and downright baffling relationship between Bachelor's degrees awarded in mathematics and statistics and Lockheed Martin's (LMT) stock price.
You might be wondering, "What on earth do math nerds have to do with massive aerospace and defense companies?" Well, my dear reader, the answers lie within the labyrinth of data, trend-chasing, and a little sprinkle of statistical wizardry. As much as it might sound like we're embarking on a quest for the Holy Grail of stock market predictions, bear in mind that we're chasing correlations, not crystal balls!
Picture this - a quirkily charming statistician walks into a bar (or a data research lab - whichever is more your vibe) and strikes up a conversation about quadratic equations and stock market fluctuations. Seemingly unrelated, right? Surprisingly, what if I told you that this seemingly improbable conversation sparked a whirlwind romance culminating in a dazzling correlation between math and Lockheed Martin’s stock price? Yes, this is the kind of rollercoaster we're strapped into for this research. It's like a statistical telenovela, but with more scatter plots and fewer dramatic close-ups.
We're diving into a realm where numbers hold the key to unlocking the mysteries of market movements. It's a world where the humble Bachelor's degrees in mathematics and statistics rise to the occasion, donning capes of predictive prowess and marching hand in hand with Lockheed Martin's stock price – a match made in analytical heaven.
So, if you're ready to embark on this epic statistical voyage filled with curves, trends, and financial fusions, join us on this mathematically unconventional journey. Who knows, by the time we're done, you might just be itching to rush off and invest in stocks with a newfound appreciation for mathematics – or at the very least, impress your friends with some statistical stock market banter over brunch!
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The moment you've all been waiting for – drumroll, please! After pouring over mountains of data and engaging in some serious mathematical matchmaking, we are thrilled to reveal the tantalizing results of our investigation into the perplexing relationship between the number of Bachelor's degrees awarded in mathematics and statistics and Lockheed Martin's (LMT) stock price.
In a jaw-dropping revelation, we found a remarkably robust correlation coefficient of 0.9610188 between these two seemingly unrelated variables. Yes, you read that right – 0.9610188! It's as if mathematics and stock prices locked eyes across a crowded room and decided to tango the night away. This correlation value exemplifies a strong positive linear relationship, indicating that as the number of mathematics and statistics degrees awarded rises, so does Lockheed Martin's stock price. It's like a mathematical pas de deux with financial figures taking the lead.
But hold onto your calculators, because there's more! Our analysis also unveiled an impressively high coefficient of determination, with an r-squared value of 0.9235572. This means that a whopping 92.36% of the variability in Lockheed Martin's stock price can be explained by changes in the number of mathematics and statistics degrees awarded. It's a statistical marvel, demonstrating just how much influence these number-centric degrees wield in the realm of stock market performance.
And if those values haven't already left you in awe, our p-value of less than 0.01 adds an extra layer of certainty to our findings. With statistical significance shining like a beacon, it's clear that the relationship between mathematics and statistics degrees and Lockheed Martin's stock price isn't just a fluke – it's a bona fide statistical love story.
If that's not enough to convince you, we have harnessed our data into a visually captivating scatterplot (Fig. 1), allowing you to witness firsthand the compelling correlation between these variables. As you gaze upon the mesmerizing plot, envision the dance of data points and stock prices, intermingling in a harmonious syncopation that defies conventional wisdom.
In conclusion, our research has unfurled a riveting tale of numbers and stocks intertwining in a magnetic embrace. So, the next time you encounter a math enthusiast waxing poetic about stock forecasts, don't scoff – they just might be onto something. After all, when it comes to Lockheed Martin's stock price, the equation seems to favor an infusion of mathematics and statistics.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between Bachelor's degrees awarded in Mathematics and statistics and Lockheed Martin's stock price (LMT). Make lots of jokes, goofy observations, and puns.
Limit your response to 500 tokens.
Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.
Do not write a conclusion. I will add a conclusion after this.
[[TITLE]]
"Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price"
[[ABSTRACT]]
Who knew that crunching numbers could lead to soaring stock prices? In this research, we dive into the intriguing relationship between the number of Bachelor's degrees awarded in mathematics and statistics and the stock price of aerospace giant Lockheed Martin (LMT). Using data from the National Center for Education Statistics and LSEG Analytics, we meticulously analyzed the trends from 2012 to 2021. Astonishingly, our findings revealed a strikingly high correlation coefficient of 0.9610188 and p < 0.01. It seems that when it comes to predicting Lockheed Martin's stock performance, a little math and statistics can go a long way. So, next time you're pondering over stock investments, don't forget to factor in some numbers – it might just be the formula for multiplying your returns!
[[LITERATURE REVIEW]]
The relationship between academic degrees in mathematics and statistics and stock prices has been a subject of interest for researchers and investors alike. Smith et al. (2010) conducted a thorough analysis of the correlation between the number of mathematics and statistics degrees awarded and stock performance, revealing statistically significant connections in various industries. Similarly, Doe and Jones (2015) explored the impact of mathematical expertise on financial markets, shedding light on the potential predictive power of quantitative skills.
However, as we venture deeper into the labyrinths of literature, we find ourselves in a whimsical landscape where numbers and stock prices collide with unexpected and downright quirky intersections. In "The Mathematics of Love" by Hannah Fry, the author ingeniously intertwines mathematical principles with real-world phenomena, proving that even matters of the heart can be dissected with statistical wizardry. Moving from the land of non-fiction to the realm of fiction, we encounter "The Probability of Miracles" by Wendy Wunder, where probability and chance intertwine in a tapestry of awe and wonderment.
Venturing into the realm of childhood nostalgia, we recall the mathematically inclined mishaps of Lisa Simpson in "The Simpsons" and the cryptic number puzzles unravelled by the enigmatic Agent P in "Phineas and Ferb." Here, we witness the playful integration of mathematics and problem-solving, proving that even in the animated domain, numbers know no boundaries.
As our academic journey takes an esoteric turn, we stumble upon the realization that the allure of mathematics and statistics transcends conventional boundaries, infusing humor and peculiarity into our exploration of the uncanny relationship between Bachelor's degrees in mathematics and statistics and Lockheed Martin's stock price.
Stay tuned as we unravel this enigmatic connection with a touch of whimsy and a sprinkle of statistical stardust - for in the world of numbers and stock prices, the unexpected reigns supreme.
[[RESULTS]]
The moment you've all been waiting for – drumroll, please! After pouring over mountains of data and engaging in some serious mathematical matchmaking, we are thrilled to reveal the tantalizing results of our investigation into the perplexing relationship between the number of Bachelor's degrees awarded in mathematics and statistics and Lockheed Martin's (LMT) stock price.
In a jaw-dropping revelation, we found a remarkably robust correlation coefficient of 0.9610188 between these two seemingly unrelated variables. Yes, you read that right – 0.9610188! It's as if mathematics and stock prices locked eyes across a crowded room and decided to tango the night away. This correlation value exemplifies a strong positive linear relationship, indicating that as the number of mathematics and statistics degrees awarded rises, so does Lockheed Martin's stock price. It's like a mathematical pas de deux with financial figures taking the lead.
But hold onto your calculators, because there's more! Our analysis also unveiled an impressively high coefficient of determination, with an r-squared value of 0.9235572. This means that a whopping 92.36% of the variability in Lockheed Martin's stock price can be explained by changes in the number of mathematics and statistics degrees awarded. It's a statistical marvel, demonstrating just how much influence these number-centric degrees wield in the realm of stock market performance.
And if those values haven't already left you in awe, our p-value of less than 0.01 adds an extra layer of certainty to our findings. With statistical significance shining like a beacon, it's clear that the relationship between mathematics and statistics degrees and Lockheed Martin's stock price isn't just a fluke – it's a bona fide statistical love story.
If that's not enough to convince you, we have harnessed our data into a visually captivating scatterplot (Fig. 1), allowing you to witness firsthand the compelling correlation between these variables. As you gaze upon the mesmerizing plot, envision the dance of data points and stock prices, intermingling in a harmonious syncopation that defies conventional wisdom.
In conclusion, our research has unfurled a riveting tale of numbers and stocks intertwining in a magnetic embrace. So, the next time you encounter a math enthusiast waxing poetic about stock forecasts, don't scoff – they just might be onto something. After all, when it comes to Lockheed Martin's stock price, the equation seems to favor an infusion of mathematics and statistics.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Let's kick off this statistical soiree by revisiting the whimsical wonders we encountered in our literature review. Who would've thought that Lisa Simpson and Agent P's mathematical escapades could hold the key to deciphering the enigmatic dance between number of mathematics and statistics degrees awarded and Lockheed Martin's stock price? Well, our findings seem to corroborate those delightfully unexpected connections.
Our study, with a correlation coefficient of 0.9610188, not only validates the prior research conducted by Smith et al. (2010) and Doe and Jones (2015), but also adds a touch of statistical flair to the delightful tales and musings we encountered in the literature review. The union of mathematics and stock prices is no longer the stuff of fiction; it's a statistical reality akin to the whimsy of Fry's "The Mathematics of Love" and the unpredictability of Wunder's "The Probability of Miracles."
With an r-squared value of 0.9235572 and a p-value of less than 0.01, we are left with an overwhelming wave of certainty – a certainty that transcends the bounds of academic inquiry and plunges us into a realm where stock prices and mathematics engage in an inexplicable tango, defying the conventional expectations of statistical relationships.
In essence, our study has unearthed a treasure trove of statistical evidence, bringing into focus the undeniable influence of mathematics and statistics degrees on Lockheed Martin's stock price. So, the next time someone tells you that a degree in math won't add up to success, you might want to consider the compelling correlation we've unveiled. After all, when it comes to decoding the mysteries of stock performance, a sprinkle of statistical stardust might just be the key to unlocking the secrets of the market.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between Bachelor's degrees awarded in Mathematics and statistics and Lockheed Martin's stock price (LMT). Make lots of jokes, goofy observations, and puns.
Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.
Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price"
[[ABSTRACT]]
Who knew that crunching numbers could lead to soaring stock prices? In this research, we dive into the intriguing relationship between the number of Bachelor's degrees awarded in mathematics and statistics and the stock price of aerospace giant Lockheed Martin (LMT). Using data from the National Center for Education Statistics and LSEG Analytics, we meticulously analyzed the trends from 2012 to 2021. Astonishingly, our findings revealed a strikingly high correlation coefficient of 0.9610188 and p < 0.01. It seems that when it comes to predicting Lockheed Martin's stock performance, a little math and statistics can go a long way. So, next time you're pondering over stock investments, don't forget to factor in some numbers – it might just be the formula for multiplying your returns!
[[INTRDUCTION]]
Alright folks, buckle up for a wild ride through the world of numbers, stock prices, and a sprinkle of mathematical magic! We all know that "math is everywhere," but did you ever think it could have such a profound impact on the stock market? Get ready to have your calculators and portfolios at the ready because we're about to explore the unexpected and downright baffling relationship between Bachelor's degrees awarded in mathematics and statistics and Lockheed Martin's (LMT) stock price.
You might be wondering, "What on earth do math nerds have to do with massive aerospace and defense companies?" Well, my dear reader, the answers lie within the labyrinth of data, trend-chasing, and a little sprinkle of statistical wizardry. As much as it might sound like we're embarking on a quest for the Holy Grail of stock market predictions, bear in mind that we're chasing correlations, not crystal balls!
Picture this - a quirkily charming statistician walks into a bar (or a data research lab - whichever is more your vibe) and strikes up a conversation about quadratic equations and stock market fluctuations. Seemingly unrelated, right? Surprisingly, what if I told you that this seemingly improbable conversation sparked a whirlwind romance culminating in a dazzling correlation between math and Lockheed Martin’s stock price? Yes, this is the kind of rollercoaster we're strapped into for this research. It's like a statistical telenovela, but with more scatter plots and fewer dramatic close-ups.
We're diving into a realm where numbers hold the key to unlocking the mysteries of market movements. It's a world where the humble Bachelor's degrees in mathematics and statistics rise to the occasion, donning capes of predictive prowess and marching hand in hand with Lockheed Martin's stock price – a match made in analytical heaven.
So, if you're ready to embark on this epic statistical voyage filled with curves, trends, and financial fusions, join us on this mathematically unconventional journey. Who knows, by the time we're done, you might just be itching to rush off and invest in stocks with a newfound appreciation for mathematics – or at the very least, impress your friends with some statistical stock market banter over brunch!
[[RESULTS]]
The moment you've all been waiting for – drumroll, please! After pouring over mountains of data and engaging in some serious mathematical matchmaking, we are thrilled to reveal the tantalizing results of our investigation into the perplexing relationship between the number of Bachelor's degrees awarded in mathematics and statistics and Lockheed Martin's (LMT) stock price.
In a jaw-dropping revelation, we found a remarkably robust correlation coefficient of 0.9610188 between these two seemingly unrelated variables. Yes, you read that right – 0.9610188! It's as if mathematics and stock prices locked eyes across a crowded room and decided to tango the night away. This correlation value exemplifies a strong positive linear relationship, indicating that as the number of mathematics and statistics degrees awarded rises, so does Lockheed Martin's stock price. It's like a mathematical pas de deux with financial figures taking the lead.
But hold onto your calculators, because there's more! Our analysis also unveiled an impressively high coefficient of determination, with an r-squared value of 0.9235572. This means that a whopping 92.36% of the variability in Lockheed Martin's stock price can be explained by changes in the number of mathematics and statistics degrees awarded. It's a statistical marvel, demonstrating just how much influence these number-centric degrees wield in the realm of stock market performance.
And if those values haven't already left you in awe, our p-value of less than 0.01 adds an extra layer of certainty to our findings. With statistical significance shining like a beacon, it's clear that the relationship between mathematics and statistics degrees and Lockheed Martin's stock price isn't just a fluke – it's a bona fide statistical love story.
If that's not enough to convince you, we have harnessed our data into a visually captivating scatterplot (Fig. 1), allowing you to witness firsthand the compelling correlation between these variables. As you gaze upon the mesmerizing plot, envision the dance of data points and stock prices, intermingling in a harmonious syncopation that defies conventional wisdom.
In conclusion, our research has unfurled a riveting tale of numbers and stocks intertwining in a magnetic embrace. So, the next time you encounter a math enthusiast waxing poetic about stock forecasts, don't scoff – they just might be onto something. After all, when it comes to Lockheed Martin's stock price, the equation seems to favor an infusion of mathematics and statistics.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
Et voilà! Our mathematical mating dance with Lockheed Martin's stock price has proven to be a stellar performance, leaving us in awe of the statistical glamour. It's like watching a mathematical ballet unfold on the grand stage of the stock market, with numbers pirouetting and stock prices waltzing in perfect harmony.
This study has not only uncovered a robust correlation between the number of mathematics and statistics degrees awarded and Lockheed Martin's stock price but has also revealed a narrative of numerical symbiosis that tantalizes the financial imagination. If mathematics and statistics were characters in a classical play, this would undoubtedly be their Shakespearean love story, entwined with the threads of correlation and causation.
Now, before we all rush off with our calculators and portfolios in hand, let's not forget to take a moment to appreciate the quirky nature of this connection. It's as if the financial markets have a secret crush on the exact sciences, and who can blame them? After all, who can resist the allure of numbers intertwined with economic success?
As we bid adieu to this enchanting saga of statistics and stocks, it's clear that no further research is warranted in this particular domain. The correlation between mathematics and statistics degrees and Lockheed Martin's stock price has been unveiled in all its numerical glory, leaving little room for additional exploration. So, let's raise our metaphorical statistical flags and declare this equation solved! No further investigation needed – we've crunched the numbers and stock prices, and the results are nothing short of a mathematical masterpiece. Cheers to the unexpected connections we stumble upon in the world of research – because sometimes, the most fascinating relationships defy all conventional logic.
And with that, dear readers, may your stock market endeavors be forever infused with the magic of mathematics and statistics. Cheers to the numbers that make the world go 'round!
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 Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Statistical Finance and Aerospace Engineering
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 Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price. Respond only with the name of a fictional organization.
ChatGPT:
The Society for Quantitative Analysis and Industrial Relations
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 Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price with an abstract of Who knew that crunching numbers could lead to soaring stock prices? In this research, we dive into the intriguing relationship between the number of Bachelor's degrees awarded in mathematics and statistics and the stock price of aerospace giant Lockheed Martin (LMT). Using data from the National Center for Education Statistics and LSEG Analytics, we meticulously analyzed the trends from 2012 to 2021. Astonishingly, our findings revealed a strikingly high correlation coefficient of 0.9610188 and p < 0.01. It seems that when it comes to predicting Lockheed Martin's stock performance, a little math and statistics can go a long way. So, next time you're pondering over stock investments, don't forget to factor in some numbers – it might just be the formula for multiplying your returns!
ChatGPT:
Lockheed Martin stock price, mathematics degrees, statistics degrees, correlation analysis, National Center for Education Statistics, LSEG Analytics, stock performance, predicting stock prices, aerospace industry, bachelor's degrees in mathematics, bachelor's degrees in statistics
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Bachelor's degrees awarded in Mathematics and statisticsDetailed data title: Bachelor's degrees conferred by postsecondary institutions, in field of study: Mathematics and statistics
Source: National Center for Education Statistics
See what else correlates with Bachelor's degrees awarded in Mathematics and statistics
Lockheed Martin's stock price (LMT)
Detailed data title: Opening price of Lockheed Martin (LMT) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function
See what else correlates with Lockheed Martin's stock price (LMT)
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 = 0.9235572 (Coefficient of determination)
This means 92.4% of the change in the one variable (i.e., Lockheed Martin's stock price (LMT)) is predictable based on the change in the other (i.e., Bachelor's degrees awarded in Mathematics and statistics) over the 10 years from 2012 through 2021.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 9.6E-6. 0.0000096368515738024960000000
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 0.96 in 0.00096% of random cases. Said differently, if you correlated 103,768 random variables You don't actually need 103 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.
p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.
In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.
Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 9 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.
[ 0.84, 0.99 ] 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.
2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | |
Bachelor's degrees awarded in Mathematics and statistics (Degrees awarded) | 18841 | 20449 | 20987 | 21854 | 22778 | 24075 | 25253 | 26155 | 27227 | 27092 |
Lockheed Martin's stock price (LMT) (Stock price) | 82.12 | 93.79 | 147.05 | 192.1 | 214 | 251.2 | 322 | 258.36 | 392.86 | 354.98 |
Why this works
- Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
- Lack of causal connection: There is probably
Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied. - Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple
Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is. - Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves.
Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.Step 2: Open a plaintext editor like Notepad and paste the code below into it.
Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"
Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.
Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.
Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.
Step 7: Run the Python script by typing "python calculate_correlation.py"
If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:
"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."
# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats
# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):
# Calculate Pearson correlation coefficient and p-value
correlation, p_value = stats.pearsonr(array1, array2)
# Calculate R-squared as the square of the correlation coefficient
r_squared = correlation**2
return correlation, r_squared, p_value
# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([18841,20449,20987,21854,22778,24075,25253,26155,27227,27092,])
array_2 = np.array([82.12,93.79,147.05,192.1,214,251.2,322,258.36,392.86,354.98,])
array_1_name = "Bachelor's degrees awarded in Mathematics and statistics"
array_2_name = "Lockheed Martin's stock price (LMT)"
# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)
# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)
Reuseable content
You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.
For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.
Download images for these variables:
- High resolution line chart
The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
Alternatively you can use a tool like Inkscape. - High resolution line chart, optimized for mobile
- Alternative high resolution line chart
- Scatterplot
- Portable line chart (png)
- Portable line chart (png), optimized for mobile
- Line chart for only Bachelor's degrees awarded in Mathematics and statistics
- Line chart for only Lockheed Martin's stock price (LMT)
- AI-generated correlation image
- The spurious research paper: Counting on Lockheed: A Statistical Analysis of the Relationship between Mathematics and Statistics Degrees and Lockheed Martin's Stock Price
You're a rater extraordinaire!
Correlation ID: 1954 · Black Variable ID: 1283 · Red Variable ID: 1630