Spurious correlation #3,969 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Annual US household spending on healthcare and the second variable is AvalonBay Communities' stock price (AVB). The chart goes from 2002 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Annual US household spending on healthcare and the second variable is AvalonBay Communities' stock price (AVB). The chart goes from 2002 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As household spending on healthcare rises, more people become interested in healthy living. This leads to a surge in demand for homes with amenities like gyms and outdoor spaces, causing AvalonBay Communities' stock price to soar. After all, a house with a built-in hospital bed is the new American dream!

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image that looks like it is a scene from a Pixar movie, where in a bustling city, a graph showing the rise in Annual US household spending on healthcare is displayed against a backdrop of a modern apartment building. People are walking in and out of the building, showcasing the high demand for apartments near healthcare facilities. Meanwhile, a stock ticker board beside the building shows AvalonBay Communities' stock price (AVB) shooting up, representing the increase in demand for their properties and the rise in their stock price. The scene is vibrant, with colorful characters and dynamic city life all around. 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: Annual US household spending on healthcare and AvalonBay Communities' stock price (AVB). 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: Brutalism Surrealism Whimsical illustration Magic realism An image that looks like it is a scene from a Pixar movie
ChatGPT: An image that looks like it is a scene from a Pixar movie

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 Annual US household spending on healthcare and AvalonBay Communities' stock price (AVB), in the following situation: Because as household spending on healthcare increases, more people seek medical care, leading to a higher demand for apartments near healthcare facilities. AvalonBay Communities, as a leading provider of such apartments, experiences an increase in demand for their properties, thus driving up their stock price. It's a real "sick" investment opportunity!. Keep the description simple.
ChatGPT: In a bustling city, a graph showing the rise in Annual US household spending on healthcare is displayed against a backdrop of a modern apartment building. People are walking in and out of the building, showcasing the high demand for apartments near healthcare facilities. Meanwhile, a stock ticker board beside the building shows AvalonBay Communities' stock price (AVB) shooting up, representing the increase in demand for their properties and the rise in their stock price.

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: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: In a bustling city, a graph showing the rise in Annual US household spending on healthcare is displayed against a backdrop of a modern apartment building. People are walking in and out of the building, showcasing the high demand for apartments near healthcare facilities. Meanwhile, a stock ticker board beside the building shows AvalonBay Communities' stock price (AVB) shooting up, representing the increase in demand for their properties and the rise in their stock price. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image that looks like it is a scene from a Pixar movie, where in a bustling city, a graph showing the rise in Annual US household spending on healthcare is displayed against a backdrop of a modern apartment building. People are walking in and out of the building, showcasing the high demand for apartments near healthcare facilities. Meanwhile, a stock ticker board beside the building shows AvalonBay Communities' stock price (AVB) shooting up, representing the increase in demand for their properties and the rise in their stock price. The scene is vibrant, with colorful characters and dynamic city life all around.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Annual US household spending on healthcare caused AvalonBay Communities' stock price (AVB) to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)

Healthy Investments: The Correlation Between Annual US Household Healthcare Spending and AvalonBay Communities' Stock Price

Journal of Financial Health and Wellness

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Annual US household spending on healthcare and AvalonBay Communities' stock price (AVB). 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
"Healthy Investments: The Correlation Between Annual US Household Healthcare Spending and AvalonBay Communities' Stock Price"

[[ABSTRACT]]
This paper investigates the relationship between annual US household spending on healthcare and the stock price of AvalonBay Communities (AVB) over the period of 2002 to 2022. The data, sourced from the Bureau of Labor Statistics and refined with the utilization of LSEG Analytics (Refinitiv), was subject to rigorous statistical analysis to determine the extent of any correlation. The results notably divulge a striking correlation coefficient of 0.9174117 and a statistically significant p-value of less than 0.01. This study provides valuable insights into the intriguing intersection of personal healthcare expenditures and the financial performance of a real estate investment trust, offering a new perspective on the interconnectedness of seemingly disparate economic indicators. With these findings, we hope to shed light on the somewhat enigmatic relationship between real estate and healthcare - a relationship that is evidently no longer confined to the clichéd saying "location, location, location," but has now seemingly expanded to "healthcare, healthcare, healthcare!"

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The interplay between healthcare expenditure and stock prices has long intrigued economists, financiers, and anyone who has ever pondered the complexities of the modern marketplace. Against this backdrop, this study delves deep into the relationship between annual US household spending on healthcare and the stock price of AvalonBay Communities (AVB), a real estate investment trust that has proven to be an unexpectedly captivating subject for analysis. While one might initially assume that healthcare and real estate are as related as apples and oranges, our research aims to demonstrate that they are more like Granny Smiths and Gala apples — distinct, yet connected in surprising ways.
The financial landscape is rife with unexpected correlations, akin to finding a dollar bill in last year's winter coat pocket — delightful, yet curiously befuddling. Our inquiry into this relationship is motivated by a desire to unearth such connections, much like an archeologist dusting off ancient artifacts, though in this case, the artifacts happen to be economic data and stock price trends. The intrigue of these findings lies not only in the statistical significance but also in the premise that one's healthcare expenditures could potentially influence the value of a real estate investment trust. The implications are as intriguing as the plot twist in a mystery novel, except instead of a hidden treasure, we seem to have stumbled upon a hidden statistical relationship.
At the heart of this investigation lies the data, meticulously collected and scrutinized with the precision of a watchmaker examining the intricate gears of a timepiece. By analyzing over two decades of annual US household healthcare spending and AvalonBay Communities' stock price data, we aim to illustrate how seemingly unrelated economic indicators may indeed present a compelling case for connection, not unlike how peanut butter and jelly come together to create a harmonious flavor combination, much to the delight of sandwich aficionados everywhere.
The revelation of a remarkably strong correlation coefficient and a statistically significant p-value in our analysis underscores the importance of this study. These findings are not just statistically significant, but they also carry significant implications for our understanding of the intricate dance between personal healthcare expenditures and the financial performance of a real estate investment trust. The intricate web of financial relationships, much like a spider's web, may appear delicate at first glance but can prove to be deceptively resilient and impactful, much like the lasting impression of a really good knock-knock joke.
With this study, we aim to elevate the discourse around the interconnectedness of seemingly disparate economic indicators and challenge prevailing assumptions about the associations between healthcare spending and stock prices. In doing so, we hope to peel back the layers of this onion to reveal an intriguing intersection of personal healthcare expenditures and real estate investment performance, adding a new dimension to the discourse on economic relationships. After all, as the saying goes, "an apple a day may keep the doctor away, but a careful analysis of healthcare expenditure may just yield unexpected insights into stock performance."

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find that there is a positive correlation between annual US household spending on healthcare and the stock price of AvalonBay Communities (AVB). This result serves as a precursor to our investigation, hinting at the intriguing relationship we seek to unravel. As we delve into the literature surrounding this topic, it becomes apparent that the intersection of personal healthcare expenditures and real estate investment performance has not received the attention it truly deserves. This oversight is perhaps akin to overlooking the importance of a well-placed avocado in a salad – an undervalued component that can greatly enhance the overall experience.

Doe's study explores the impact of healthcare spending on stock prices, highlighting the multifaceted nature of this relationship. The findings serve as a reminder that economic connections can be as intricate as a game of chess, with each move influencing the subsequent outcome. In this metaphorical game of economic chess, healthcare spending emerges as a key player, capable of shaping the trajectory of stock prices much like the grandmaster strategically maneuvering their pieces across the board.

Jones' research delves into the nuances of healthcare expenditure and its potential influence on real estate investment trusts, laying the groundwork for our own investigation. The intricate web of economic relationships portrayed in this study mirrors the complexities of a jigsaw puzzle, challenging us to piece together the interrelated factors that contribute to stock price movements. Just as completing a jigsaw puzzle brings about a sense of accomplishment, so too does gaining a deeper understanding of the relationship between healthcare spending and stock performance.

Turning to non-fiction works, "The Healing of America" by T.R. Reid offers valuable insights into the complexities of healthcare systems worldwide. While our focus is on US household spending, the global perspective presented in this work serves as a reminder of the broader implications of healthcare economics. It's like taking a brief detour from a hike to appreciate the panoramic view – a momentary shift in perspective that enriches the overall experience.

"The Big Short" by Michael Lewis, though a work of fiction, provides a captivating portrayal of the interconnectedness of financial markets. While not directly related to our specific research, the underlying theme of unexpected correlations serves as a thought-provoking backdrop for our study. In a way, it's like stumbling upon a vintage board game while clearing out the attic – a nostalgic find that triggers unexpected reflections on the nature of interconnectedness.

Board games such as "Monopoly" and "Operation" may seem worlds apart, but they share a common thread when viewed through the lens of our research. Just as "Monopoly" simulates real estate investment strategies, "Operation" playfully illustrates the importance of healthcare – a juxtaposition that encapsulates the essence of our investigation with a touch of whimsy.

As we navigate through the literature, it becomes clear that the relationship between annual US household spending on healthcare and AvalonBay Communities' stock price is not merely a matter of numbers and trends. It encompasses a rich tapestry of interconnected forces, much like the intricate plot of a mystery novel, waiting to be unraveled. With this understanding, we set out to shed light on this captivating interplay with the hope of bringing a touch of levity to the often-serious world of economic analysis.

As we move forward, it is imperative to approach this investigation with the precision of a watchmaker and the curiosity of a treasure hunter, as we seek to uncover the hidden gems within this enigmatic relationship.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Annual US household spending on healthcare and AvalonBay Communities' stock price (AVB). 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 Bureau of Labor Statistics and LSEG Analytics (Refinitiv) .

For the time period 2002 to 2022, you found a correlation 0.9174117, r-squared of 0.8416442, 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]]
"Healthy Investments: The Correlation Between Annual US Household Healthcare Spending and AvalonBay Communities' Stock Price"

[[ABSTRACT]]
This paper investigates the relationship between annual US household spending on healthcare and the stock price of AvalonBay Communities (AVB) over the period of 2002 to 2022. The data, sourced from the Bureau of Labor Statistics and refined with the utilization of LSEG Analytics (Refinitiv), was subject to rigorous statistical analysis to determine the extent of any correlation. The results notably divulge a striking correlation coefficient of 0.9174117 and a statistically significant p-value of less than 0.01. This study provides valuable insights into the intriguing intersection of personal healthcare expenditures and the financial performance of a real estate investment trust, offering a new perspective on the interconnectedness of seemingly disparate economic indicators. With these findings, we hope to shed light on the somewhat enigmatic relationship between real estate and healthcare - a relationship that is evidently no longer confined to the clichéd saying "location, location, location," but has now seemingly expanded to "healthcare, healthcare, healthcare!"

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The interplay between healthcare expenditure and stock prices has long intrigued economists, financiers, and anyone who has ever pondered the complexities of the modern marketplace. Against this backdrop, this study delves deep into the relationship between annual US household spending on healthcare and the stock price of AvalonBay Communities (AVB), a real estate investment trust that has proven to be an unexpectedly captivating subject for analysis. While one might initially assume that healthcare and real estate are as related as apples and oranges, our research aims to demonstrate that they are more like Granny Smiths and Gala apples — distinct, yet connected in surprising ways.
The financial landscape is rife with unexpected correlations, akin to finding a dollar bill in last year's winter coat pocket — delightful, yet curiously befuddling. Our inquiry into this relationship is motivated by a desire to unearth such connections, much like an archeologist dusting off ancient artifacts, though in this case, the artifacts happen to be economic data and stock price trends. The intrigue of these findings lies not only in the statistical significance but also in the premise that one's healthcare expenditures could potentially influence the value of a real estate investment trust. The implications are as intriguing as the plot twist in a mystery novel, except instead of a hidden treasure, we seem to have stumbled upon a hidden statistical relationship.
At the heart of this investigation lies the data, meticulously collected and scrutinized with the precision of a watchmaker examining the intricate gears of a timepiece. By analyzing over two decades of annual US household healthcare spending and AvalonBay Communities' stock price data, we aim to illustrate how seemingly unrelated economic indicators may indeed present a compelling case for connection, not unlike how peanut butter and jelly come together to create a harmonious flavor combination, much to the delight of sandwich aficionados everywhere.
The revelation of a remarkably strong correlation coefficient and a statistically significant p-value in our analysis underscores the importance of this study. These findings are not just statistically significant, but they also carry significant implications for our understanding of the intricate dance between personal healthcare expenditures and the financial performance of a real estate investment trust. The intricate web of financial relationships, much like a spider's web, may appear delicate at first glance but can prove to be deceptively resilient and impactful, much like the lasting impression of a really good knock-knock joke.
With this study, we aim to elevate the discourse around the interconnectedness of seemingly disparate economic indicators and challenge prevailing assumptions about the associations between healthcare spending and stock prices. In doing so, we hope to peel back the layers of this onion to reveal an intriguing intersection of personal healthcare expenditures and real estate investment performance, adding a new dimension to the discourse on economic relationships. After all, as the saying goes, "an apple a day may keep the doctor away, but a careful analysis of healthcare expenditure may just yield unexpected insights into stock performance."

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis of the relationship between annual US household spending on healthcare and AvalonBay Communities' stock price (AVB) yielded intriguing results. The correlation coefficient between these two variables was calculated to be 0.9174117, indicating a remarkably strong positive linear relationship. This finding suggests that as annual US household spending on healthcare increased, there was a corresponding upward trend in AvalonBay Communities' stock price. In other words, it appears that as healthcare spending soared, so did the stock price of AVB - a curious coalescence of personal healthcare expenditures and real estate investment trust performance.

The coefficient of determination (r-squared) provided further insight into this association, with a value of 0.8416442. This indicates that approximately 84% of the variability in AvalonBay Communities' stock price can be explained by changes in annual US household healthcare spending. While we generally shy away from making bold claims, this degree of explanatory power does prompt one to pause and marvel at the unexpected intricacies of economic relationships.

Moreover, the p-value obtained from the analysis was less than 0.01, signifying strong evidence against the null hypothesis of no correlation. This lends additional support to the notion that there exists a statistically significant relationship between annual US household healthcare spending and the stock price of AvalonBay Communities. It seems that in the grand theater of economic indicators, the performance of a real estate investment trust may indeed be influenced by the healthcare expenditure decisions made at household level. This finding gives new meaning to the phrase "healthy investments" and suggests that the pulse of personal healthcare spending resonates through the financial heartbeat of real estate investment trusts, potentially causing them to skip a beat now and then.

For the visual learners among us, the data is further elucidated in Figure 1. The scatterplot in Figure 1 illustrates the strong positive correlation between annual US household healthcare spending and AvalonBay Communities' stock price. Each data point within the scatterplot serves as a testament to the robust relationship uncovered by this study, akin to a constellation of stars aligning in perfect harmony, or perhaps more mundanely, akin to a family of sourdough starters thriving in the symphony of a baker's kitchen.

With such compelling statistical evidence, our study not only contributes to the understanding of financial markets but also underscores the interconnectedness of seemingly discrete economic factors. The implications of these findings extend beyond the realm of statistics and may compel a reevaluation of the conventional wisdom surrounding healthcare spending and stock performance. As we dissect these findings further, we find ourselves marveling at the serendipitous nature of economic relationships, akin to stumbling upon a four-leaf clover in a bustling financial marketplace.

Though this study focused on the specific relationship between annual US household healthcare spending and AvalonBay Communities' stock price, the broader implications of our findings beckon further inquiry into the intricate web of economic interdependencies. As we move forward, we may find ourselves continually surprised by the nuanced connections that underpin the modern financial landscape, much like discovering a long-lost treasure trove in the attic of economic theory.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Annual US household spending on healthcare and AvalonBay Communities' stock price (AVB). 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]]
"Healthy Investments: The Correlation Between Annual US Household Healthcare Spending and AvalonBay Communities' Stock Price"

[[ABSTRACT]]
This paper investigates the relationship between annual US household spending on healthcare and the stock price of AvalonBay Communities (AVB) over the period of 2002 to 2022. The data, sourced from the Bureau of Labor Statistics and refined with the utilization of LSEG Analytics (Refinitiv), was subject to rigorous statistical analysis to determine the extent of any correlation. The results notably divulge a striking correlation coefficient of 0.9174117 and a statistically significant p-value of less than 0.01. This study provides valuable insights into the intriguing intersection of personal healthcare expenditures and the financial performance of a real estate investment trust, offering a new perspective on the interconnectedness of seemingly disparate economic indicators. With these findings, we hope to shed light on the somewhat enigmatic relationship between real estate and healthcare - a relationship that is evidently no longer confined to the clichéd saying "location, location, location," but has now seemingly expanded to "healthcare, healthcare, healthcare!"

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find that there is a positive correlation between annual US household spending on healthcare and the stock price of AvalonBay Communities (AVB). This result serves as a precursor to our investigation, hinting at the intriguing relationship we seek to unravel. As we delve into the literature surrounding this topic, it becomes apparent that the intersection of personal healthcare expenditures and real estate investment performance has not received the attention it truly deserves. This oversight is perhaps akin to overlooking the importance of a well-placed avocado in a salad – an undervalued component that can greatly enhance the overall experience.
Doe's study explores the impact of healthcare spending on stock prices, highlighting the multifaceted nature of this relationship. The findings serve as a reminder that economic connections can be as intricate as a game of chess, with each move influencing the subsequent outcome. In this metaphorical game of economic chess, healthcare spending emerges as a key player, capable of shaping the trajectory of stock prices much like the grandmaster strategically maneuvering their pieces across the board.
Jones' research delves into the nuances of healthcare expenditure and its potential influence on real estate investment trusts, laying the groundwork for our own investigation. The intricate web of economic relationships portrayed in this study mirrors the complexities of a jigsaw puzzle, challenging us to piece together the interrelated factors that contribute to stock price movements. Just as completing a jigsaw puzzle brings about a sense of accomplishment, so too does gaining a deeper understanding of the relationship between healthcare spending and stock performance.
Turning to non-fiction works, "The Healing of America" by T.R. Reid offers valuable insights into the complexities of healthcare systems worldwide. While our focus is on US household spending, the global perspective presented in this work serves as a reminder of the broader implications of healthcare economics. It's like taking a brief detour from a hike to appreciate the panoramic view – a momentary shift in perspective that enriches the overall experience.
"The Big Short" by Michael Lewis, though a work of fiction, provides a captivating portrayal of the interconnectedness of financial markets. While not directly related to our specific research, the underlying theme of unexpected correlations serves as a thought-provoking backdrop for our study. In a way, it's like stumbling upon a vintage board game while clearing out the attic – a nostalgic find that triggers unexpected reflections on the nature of interconnectedness.
Board games such as "Monopoly" and "Operation" may seem worlds apart, but they share a common thread when viewed through the lens of our research. Just as "Monopoly" simulates real estate investment strategies, "Operation" playfully illustrates the importance of healthcare – a juxtaposition that encapsulates the essence of our investigation with a touch of whimsy.
As we navigate through the literature, it becomes clear that the relationship between annual US household spending on healthcare and AvalonBay Communities' stock price is not merely a matter of numbers and trends. It encompasses a rich tapestry of interconnected forces, much like the intricate plot of a mystery novel, waiting to be unraveled. With this understanding, we set out to shed light on this captivating interplay with the hope of bringing a touch of levity to the often-serious world of economic analysis.
As we move forward, it is imperative to approach this investigation with the precision of a watchmaker and the curiosity of a treasure hunter, as we seek to uncover the hidden gems within this enigmatic relationship.

[[RESULTS]]
The statistical analysis of the relationship between annual US household spending on healthcare and AvalonBay Communities' stock price (AVB) yielded intriguing results. The correlation coefficient between these two variables was calculated to be 0.9174117, indicating a remarkably strong positive linear relationship. This finding suggests that as annual US household spending on healthcare increased, there was a corresponding upward trend in AvalonBay Communities' stock price. In other words, it appears that as healthcare spending soared, so did the stock price of AVB - a curious coalescence of personal healthcare expenditures and real estate investment trust performance.
The coefficient of determination (r-squared) provided further insight into this association, with a value of 0.8416442. This indicates that approximately 84% of the variability in AvalonBay Communities' stock price can be explained by changes in annual US household healthcare spending. While we generally shy away from making bold claims, this degree of explanatory power does prompt one to pause and marvel at the unexpected intricacies of economic relationships.
Moreover, the p-value obtained from the analysis was less than 0.01, signifying strong evidence against the null hypothesis of no correlation. This lends additional support to the notion that there exists a statistically significant relationship between annual US household healthcare spending and the stock price of AvalonBay Communities. It seems that in the grand theater of economic indicators, the performance of a real estate investment trust may indeed be influenced by the healthcare expenditure decisions made at household level. This finding gives new meaning to the phrase "healthy investments" and suggests that the pulse of personal healthcare spending resonates through the financial heartbeat of real estate investment trusts, potentially causing them to skip a beat now and then.
For the visual learners among us, the data is further elucidated in Figure 1. The scatterplot in Figure 1 illustrates the strong positive correlation between annual US household healthcare spending and AvalonBay Communities' stock price. Each data point within the scatterplot serves as a testament to the robust relationship uncovered by this study, akin to a constellation of stars aligning in perfect harmony, or perhaps more mundanely, akin to a family of sourdough starters thriving in the symphony of a baker's kitchen.
With such compelling statistical evidence, our study not only contributes to the understanding of financial markets but also underscores the interconnectedness of seemingly discrete economic factors. The implications of these findings extend beyond the realm of statistics and may compel a reevaluation of the conventional wisdom surrounding healthcare spending and stock performance. As we dissect these findings further, we find ourselves marveling at the serendipitous nature of economic relationships, akin to stumbling upon a four-leaf clover in a bustling financial marketplace.
Though this study focused on the specific relationship between annual US household healthcare spending and AvalonBay Communities' stock price, the broader implications of our findings beckon further inquiry into the intricate web of economic interdependencies. As we move forward, we may find ourselves continually surprised by the nuanced connections that underpin the modern financial landscape, much like discovering a long-lost treasure trove in the attic of economic theory.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study provide substantial support for the prior research, echoing the positive correlation identified by Smith et al. between annual US household spending on healthcare and AvalonBay Communities' stock price (AVB) - a correlation that is as undeniable as the inherent appeal of a well-placed avocado in a salad. The statistical analysis revealed a remarkably strong correlation coefficient of 0.9174117, lending credence to the notion that healthcare spending at the household level is intricately entwined with the financial performance of real estate investment trusts.

In a manner reminiscent of a strategic chess move, the results of this investigation align closely with Doe's findings, underscoring the multifaceted nature of the relationship between healthcare spending and stock prices. The striking correlation coefficient of 0.9174117 acts as a poignant reminder of the strategic interplay between these economic factors, akin to a grandmaster expertly maneuvering their pieces on the board of financial markets. Just as in a game of chess, every nuanced move carries the potential to shape the outcome, and so too does each dollar allocated to healthcare expenses seem to exert a discernible influence on the stock price of AVB.

Jones' pioneering exploration of the nuances of healthcare expenditure and its impact on real estate investment trusts laid a solid foundation for our study, much like a crucial puzzle piece that ultimately contributes to the completion of the larger economic picture. The findings of our investigation resonate with the intricate web of economic relationships portrayed in Jones' research, further emphasizing the complex nature of the interplay between healthcare spending and stock performance - a relationship that is as enigmatic as it is impactful.

Drawing inspiration from the world of fiction, "The Big Short" by Michael Lewis serves as a thought-provoking backdrop for our study, with the unexpected correlations depicted in the narrative weaving a compelling parallel to the strong empirical link uncovered between annual US household healthcare spending and AvalonBay Communities' stock price. While not a direct portrayal of our specific research, the underlying theme of unexpected correlations proves to be a captivating reflection of the surprising interconnectedness of economic factors. In a way, it's akin to stumbling upon a vintage board game while clearing out the attic - a nostalgic find that triggers unexpected reflections on the nature of interconnectedness, much like the unexpected correlations revealed in our statistical analysis.

As we delve deeper into the implications of our findings, it becomes evident that the relationship between annual US household spending on healthcare and AvalonBay Communities' stock price is not merely a matter of numbers and trends. It embodies a rich tapestry of interconnected forces, akin to the intricate plot of a mystery novel, waiting to be unraveled. With a touch of whimsy, this investigation seeks to bring to light the captivating interplay between personal healthcare expenditures and the financial heartbeat of real estate investment trusts, much like a lighthearted moment amid the serious discourse of economic analysis.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Annual US household spending on healthcare and AvalonBay Communities' stock price (AVB). 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]]
"Healthy Investments: The Correlation Between Annual US Household Healthcare Spending and AvalonBay Communities' Stock Price"

[[ABSTRACT]]
This paper investigates the relationship between annual US household spending on healthcare and the stock price of AvalonBay Communities (AVB) over the period of 2002 to 2022. The data, sourced from the Bureau of Labor Statistics and refined with the utilization of LSEG Analytics (Refinitiv), was subject to rigorous statistical analysis to determine the extent of any correlation. The results notably divulge a striking correlation coefficient of 0.9174117 and a statistically significant p-value of less than 0.01. This study provides valuable insights into the intriguing intersection of personal healthcare expenditures and the financial performance of a real estate investment trust, offering a new perspective on the interconnectedness of seemingly disparate economic indicators. With these findings, we hope to shed light on the somewhat enigmatic relationship between real estate and healthcare - a relationship that is evidently no longer confined to the clichéd saying "location, location, location," but has now seemingly expanded to "healthcare, healthcare, healthcare!"

[[INTRDUCTION]]
The interplay between healthcare expenditure and stock prices has long intrigued economists, financiers, and anyone who has ever pondered the complexities of the modern marketplace. Against this backdrop, this study delves deep into the relationship between annual US household spending on healthcare and the stock price of AvalonBay Communities (AVB), a real estate investment trust that has proven to be an unexpectedly captivating subject for analysis. While one might initially assume that healthcare and real estate are as related as apples and oranges, our research aims to demonstrate that they are more like Granny Smiths and Gala apples — distinct, yet connected in surprising ways.
The financial landscape is rife with unexpected correlations, akin to finding a dollar bill in last year's winter coat pocket — delightful, yet curiously befuddling. Our inquiry into this relationship is motivated by a desire to unearth such connections, much like an archeologist dusting off ancient artifacts, though in this case, the artifacts happen to be economic data and stock price trends. The intrigue of these findings lies not only in the statistical significance but also in the premise that one's healthcare expenditures could potentially influence the value of a real estate investment trust. The implications are as intriguing as the plot twist in a mystery novel, except instead of a hidden treasure, we seem to have stumbled upon a hidden statistical relationship.
At the heart of this investigation lies the data, meticulously collected and scrutinized with the precision of a watchmaker examining the intricate gears of a timepiece. By analyzing over two decades of annual US household healthcare spending and AvalonBay Communities' stock price data, we aim to illustrate how seemingly unrelated economic indicators may indeed present a compelling case for connection, not unlike how peanut butter and jelly come together to create a harmonious flavor combination, much to the delight of sandwich aficionados everywhere.
The revelation of a remarkably strong correlation coefficient and a statistically significant p-value in our analysis underscores the importance of this study. These findings are not just statistically significant, but they also carry significant implications for our understanding of the intricate dance between personal healthcare expenditures and the financial performance of a real estate investment trust. The intricate web of financial relationships, much like a spider's web, may appear delicate at first glance but can prove to be deceptively resilient and impactful, much like the lasting impression of a really good knock-knock joke.
With this study, we aim to elevate the discourse around the interconnectedness of seemingly disparate economic indicators and challenge prevailing assumptions about the associations between healthcare spending and stock prices. In doing so, we hope to peel back the layers of this onion to reveal an intriguing intersection of personal healthcare expenditures and real estate investment performance, adding a new dimension to the discourse on economic relationships. After all, as the saying goes, "an apple a day may keep the doctor away, but a careful analysis of healthcare expenditure may just yield unexpected insights into stock performance."

[[RESULTS]]
The statistical analysis of the relationship between annual US household spending on healthcare and AvalonBay Communities' stock price (AVB) yielded intriguing results. The correlation coefficient between these two variables was calculated to be 0.9174117, indicating a remarkably strong positive linear relationship. This finding suggests that as annual US household spending on healthcare increased, there was a corresponding upward trend in AvalonBay Communities' stock price. In other words, it appears that as healthcare spending soared, so did the stock price of AVB - a curious coalescence of personal healthcare expenditures and real estate investment trust performance.
The coefficient of determination (r-squared) provided further insight into this association, with a value of 0.8416442. This indicates that approximately 84% of the variability in AvalonBay Communities' stock price can be explained by changes in annual US household healthcare spending. While we generally shy away from making bold claims, this degree of explanatory power does prompt one to pause and marvel at the unexpected intricacies of economic relationships.
Moreover, the p-value obtained from the analysis was less than 0.01, signifying strong evidence against the null hypothesis of no correlation. This lends additional support to the notion that there exists a statistically significant relationship between annual US household healthcare spending and the stock price of AvalonBay Communities. It seems that in the grand theater of economic indicators, the performance of a real estate investment trust may indeed be influenced by the healthcare expenditure decisions made at household level. This finding gives new meaning to the phrase "healthy investments" and suggests that the pulse of personal healthcare spending resonates through the financial heartbeat of real estate investment trusts, potentially causing them to skip a beat now and then.
For the visual learners among us, the data is further elucidated in Figure 1. The scatterplot in Figure 1 illustrates the strong positive correlation between annual US household healthcare spending and AvalonBay Communities' stock price. Each data point within the scatterplot serves as a testament to the robust relationship uncovered by this study, akin to a constellation of stars aligning in perfect harmony, or perhaps more mundanely, akin to a family of sourdough starters thriving in the symphony of a baker's kitchen.
With such compelling statistical evidence, our study not only contributes to the understanding of financial markets but also underscores the interconnectedness of seemingly discrete economic factors. The implications of these findings extend beyond the realm of statistics and may compel a reevaluation of the conventional wisdom surrounding healthcare spending and stock performance. As we dissect these findings further, we find ourselves marveling at the serendipitous nature of economic relationships, akin to stumbling upon a four-leaf clover in a bustling financial marketplace.
Though this study focused on the specific relationship between annual US household healthcare spending and AvalonBay Communities' stock price, the broader implications of our findings beckon further inquiry into the intricate web of economic interdependencies. As we move forward, we may find ourselves continually surprised by the nuanced connections that underpin the modern financial landscape, much like discovering a long-lost treasure trove in the attic of economic theory.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has unearthed a robust and statistically significant relationship between annual US household healthcare spending and the stock price of AvalonBay Communities. The correlation coefficient of 0.9174117 and the compellingly low p-value indicate a strong positive association, as if healthcare spending and stock prices were engaged in a pas de deux of financial synchrony. This unexpected alliance between healthcare and real estate investment trust performance challenges traditional economic narratives, much like a plot twist in a classic novel that leaves readers both surprised and eager to reevaluate every previous chapter.

One might argue that our findings have injected a dose of "healthy" skepticism into the perception of investment dynamics, prompting a reconsideration of the conventional wisdom that has long prevailed in financial circles. The implications of this study extend beyond the immediate connection between healthcare spending and stock performance, shedding light on the organic interplay of economic variables in ways that we are only beginning to comprehend. Just as a charming anecdote may offer unexpected wisdom, so too do our findings underscore the complex, and often delightful, intricacies of financial markets.

Therefore, it is with a mixture of certainty and a twinge of whimsy that we declare the pursuit of further inquiry into this topic unnecessary, as we have unraveled an economic relationship that is as undeniable as the appeal of a well-crafted pun. Let this study stand as a testament to the serendipitous nature of financial connections, and may it inspire future researchers to approach their inquiries with the same curious spirit and penchant for discovery. After all, in the ever-unfolding story of economic analysis, sometimes the most compelling revelations emerge from the most unexpected places.

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 Healthy Investments: The Correlation Between Annual US Household Healthcare Spending and AvalonBay Communities' Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Financial Health and Wellness

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 Healthy Investments: The Correlation Between Annual US Household Healthcare Spending and AvalonBay Communities' Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Econo-Wellness Research

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 Healthy Investments: The Correlation Between Annual US Household Healthcare Spending and AvalonBay Communities' Stock Price with an abstract of This paper investigates the relationship between annual US household spending on healthcare and the stock price of AvalonBay Communities (AVB) over the period of 2002 to 2022. The data, sourced from the Bureau of Labor Statistics and refined with the utilization of LSEG Analytics (Refinitiv), was subject to rigorous statistical analysis to determine the extent of any correlation. The results notably divulge a striking correlation coefficient of 0.9174117 and a statistically significant p-value of less than 0.01. This study provides valuable insights into the intriguing intersection of personal healthcare expenditures and the financial performance of a real estate investment trust, offering a new perspective on the interconnectedness of seemingly disparate economic indicators. With these findings, we hope to shed light on the somewhat enigmatic relationship between real estate and healthcare - a relationship that is evidently no longer confined to the clichéd saying "location, location, location," but has now seemingly expanded to "healthcare, healthcare, healthcare!

ChatGPT:

AvalonBay Communities, AVB stock price, annual US household healthcare spending, correlation analysis, Bureau of Labor Statistics, LSEG Analytics, Refinitiv, real estate investment trust, healthcare expenditures, statistical analysis, economic indicators, healthcare and finance intersection, real estate and healthcare relationship

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

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Data details

Annual US household spending on healthcare
Detailed data title: Average annual household spend on healthcare
Source: Bureau of Labor Statistics
See what else correlates with Annual US household spending on healthcare

AvalonBay Communities' stock price (AVB)
Detailed data title: Opening price of AvalonBay Communities (AVB) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: ^{See full details} Via Microsoft Excel Stockhistory function

See what else correlates with AvalonBay Communities' stock price (AVB)

Correlation r = 0.9174117 (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 = 0.8416442 (Coefficient of determination)
This means 84.2% of the change in the one variable (i.e., AvalonBay Communities' stock price (AVB)) is predictable based on the change in the other (i.e., Annual US household spending on healthcare) over the 21 years from 2002 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.9E-9.^Show 0.0000000048640014404817630000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.92 in 4.9E-7% of random cases. Said differently, if you correlated 205,592,044 random variables^Note You don't actually need 205 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 20 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 20 because we have two variables measured over a period of 21 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.

[ 0.8, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Annual US household spending on healthcare (Household spend)	2350	2416	2574	2664	2766	2853	2976	3126	3157	3313	3556	3631	4290	4342	4612	4928	4968	5193	5177	5452	5850
AvalonBay Communities' stock price (AVB) (Stock price)	47.35	39.15	47.8	75.25	90.1	130.2	92.54	61.06	83.07	113.27	133.94	137.28	118.25	164.06	182.35	178.3	178.59	172.57	210.46	160.07	255.91

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([2350,2416,2574,2664,2766,2853,2976,3126,3157,3313,3556,3631,4290,4342,4612,4928,4968,5193,5177,5452,5850,])
array_2 = np.array([47.35,39.15,47.8,75.25,90.1,130.2,92.54,61.06,83.07,113.27,133.94,137.28,118.25,164.06,182.35,178.3,178.59,172.57,210.46,160.07,255.91,])
array_1_name = "Annual US household spending on healthcare"
array_2_name = "AvalonBay Communities' stock price (AVB)"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Annual US household spending on healthcare
Line chart for only AvalonBay Communities' stock price (AVB)
AI-generated correlation image
The spurious research paper: Healthy Investments: The Correlation Between Annual US Household Healthcare Spending and AvalonBay Communities' Stock Price

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Correlation ID: 3969 · Black Variable ID: 19933 · Red Variable ID: 1861


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