Spurious correlation #4,080 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Ruth and the second variable is Analog Devices' stock price (ADI). 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 Popularity of the first name Ruth and the second variable is Analog Devices' stock price (ADI). The chart goes from 2002 to 2022, and the two variables track closely in value over that time.

AI explanation

As the name Ruth became more popular, there was a coinciding surge in grandmothers knitting. This unexpected demand for yarn caused a chain reaction, leading to an increase in sales of electronic devices cozily tucked away in knitted cozies. As Analog Devices found their products in high demand for this unexpected trend, their stock price naturally rose, stitching together a bizarre connection between a timeless name and modern technology. It's like the market was wrapped in a warm, fuzzy sweater of success!

^{Show image generation prompt} Model: dalle-3
Prompt: Style: Whimsical illustration Scene: A grandmother with spectacles and a warm smile knitting a colorful yarn cozy for a sleek smartphone. In the background, a stock chart with the Analog Devices (ADI) stock price, in the form of a cozy knitted pattern, steadily rising. The cozy smartphone is surrounded by other knitted cozies for various electronic devices like tablets, laptops, and smartwatches, all emanating a cozy, warm glow. 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: Popularity of the first name Ruth and Analog Devices' stock price (ADI). 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: Macabre 3D Pixar Style Cutsy art illustration Magic realism Whimsical illustration
ChatGPT: Whimsical illustration

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 Popularity of the first name Ruth and Analog Devices' stock price (ADI), in the following situation: As the name Ruth became more popular, there was a coinciding surge in grandmothers knitting. This unexpected demand for yarn caused a chain reaction, leading to an increase in sales of electronic devices cozily tucked away in knitted cozies. As Analog Devices found their products in high demand for this unexpected trend, their stock price naturally rose, stitching together a bizarre connection between a timeless name and modern technology. It's like the market was wrapped in a warm, fuzzy sweater of success!. Keep the description simple.
ChatGPT: As the name Ruth saw a rise in popularity, grandmothers across the country picked up their knitting needles, creating a surge in demand for yarn. This unexpected increase led to a cozy trend of knitted cozies for electronic devices, causing a sharp rise in sales for Analog Devices. As a result, the stock price of Analog Devices (ADI) warmly surged, weaving a unique connection between a traditional name and modern technology into a fuzzy sweater of success in the market!

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: [ Whimsical illustration ] and depicting this scene: As the name Ruth saw a rise in popularity, grandmothers across the country picked up their knitting needles, creating a surge in demand for yarn. This unexpected increase led to a cozy trend of knitted cozies for electronic devices, causing a sharp rise in sales for Analog Devices. As a result, the stock price of Analog Devices (ADI) warmly surged, weaving a unique connection between a traditional name and modern technology into a fuzzy sweater of success in the market! Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Style: Whimsical illustration Scene: A grandmother with spectacles and a warm smile knitting a colorful yarn cozy for a sleek smartphone. In the background, a stock chart with the Analog Devices (ADI) stock price, in the form of a cozy knitted pattern, steadily rising. The cozy smartphone is surrounded by other knitted cozies for various electronic devices like tablets, laptops, and smartwatches, all emanating a cozy, warm glow.

*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 Popularity of the first name Ruth caused Analog Devices' stock price (ADI) to increase. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Ruth-lessly Predicting Stock Prices: The Correlation Between the Popularity of the Name Ruth and Analog Devices' Stock Price (ADI)

The Journal of Quirky Quantitative Analysis

Jan 2024

^{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 dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Popularity of the first name Ruth and Analog Devices' stock price (ADI). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Ruth-lessly Predicting Stock Prices: The Correlation Between the Popularity of the Name Ruth and Analog Devices' Stock Price (ADI)"

[[ABSTRACT]]
This study examines the relationship between the popularity of the first name Ruth and Analog Devices' stock price (ADI) from 2002 to 2022. Using data from the US Social Security Administration and LSEG Analytics (Refinitiv), we calculated a correlation coefficient of 0.9664183 and found a significant p-value of less than 0.01. The results suggest a strong positive correlation between the frequency of the name Ruth and the performance of ADI's stock. So, one might say that Ruth's popularity might exert a subtle influence on ADI's stock price, making it a "Ruth-lessly" predictable factor. These findings provide an interesting avenue for further research into the quirks of stock price prediction.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between individual names and various societal phenomena has long been a subject of interest and speculation. Whether it's the tumultuous love life of a "Jennifer" or the uncanny ability of "Karen" to speak to the manager, names seem to carry a certain mystique that extends beyond mere nomenclature. One such name that has piqued the interest of researchers is "Ruth," a name with biblical roots and a timeless appeal. In this paper, we delve into the intriguing correlation between the popularity of the first name Ruth and the stock price of Analog Devices Inc. (ADI).
The choice of the name "Ruth" as the focal point of this study was not made lightly. Its rich historical and cultural significance, coupled with its enduring popularity, rendered it a compelling candidate for investigation. As Mark Twain might have quipped, "The reports of Ruth's influence on stock prices are not greatly exaggerated." This study seeks to shed light on the existence of any correlation between the frequency of the name Ruth and the performance of ADI's stock over a two-decade period.
The significance of this analysis lies in the potential implications for both the financial and sociocultural spheres. If indeed a connection is established, it may open the floodgates for a new era of stock prediction, underpinned not only by economic indicators but also by the ebb and flow of popular nomenclature. One might say that this correlation could hold the "Ruth" to unlocking a new frontier in stock market analysis.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Certainly, the connection between the popularity of the first name "Ruth" and Analog Devices' stock price (ADI) has been an area of interest for researchers across various disciplines. In "The Name Game: Cultural Implications of Monikers," Smith et al. shed light on the societal perceptions and impacts associated with different names. Furthermore, Doe's study "Naming Trends and Financial Markets" delves into the potential influence of popular names on stock market dynamics. These serious academic works lay the foundation for understanding the underlying mechanisms at play in our investigation.

Moving beyond academic research, works such as "The Power of Names" by Malcolm Gladwell and "Freakonomics: A Rogue Economist Explores the Hidden Side of Everything" by Steven D. Levitt and Stephen J. Dubner offer intriguing insights into the potential effects of names on individual behavior and societal trends. Meanwhile, fictional narratives such as "The Name of the Wind" by Patrick Rothfuss and "The Shadow of the Wind" by Carlos Ruiz Zafón, while not directly related to our topic, demonstrate the enduring fascination with the power and significance of names in human culture and imagination.

As we delve deeper into the literature, it is important to note the diverse sources of information that have been considered in this investigation. While conventional scholarly articles and renowned publications form the bedrock of our theoretical framework, it is worth acknowledging the unorthodox sources that have contributed to the breadth and depth of this review. From perusing the labels of soup cans to reviewing the backs of shampoo bottles, the exhaustive nature of this literature review is a testament to the thoroughness with which we have approached this research endeavor.

In summary, the foundational studies establish a theoretical basis for the potential influence of popular names on stock market dynamics, while the interdisciplinary insights and unconventional sources add a layer of richness to the scope of our investigation. With this comprehensive understanding as our backdrop, we are poised to analyze the empirical data and unravel the intriguing relationship between the name "Ruth" and Analog Devices' stock price. It is only fitting to say that, in the words of a stock trader-turned-philosopher, "When it comes to predicting stock prices, one must always take names into account - it's a 'stock' secret!"

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Ruth and Analog Devices' stock price (ADI). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Ruth-lessly Predicting Stock Prices: The Correlation Between the Popularity of the Name Ruth and Analog Devices' Stock Price (ADI)"

[[ABSTRACT]]
This study examines the relationship between the popularity of the first name Ruth and Analog Devices' stock price (ADI) from 2002 to 2022. Using data from the US Social Security Administration and LSEG Analytics (Refinitiv), we calculated a correlation coefficient of 0.9664183 and found a significant p-value of less than 0.01. The results suggest a strong positive correlation between the frequency of the name Ruth and the performance of ADI's stock. So, one might say that Ruth's popularity might exert a subtle influence on ADI's stock price, making it a "Ruth-lessly" predictable factor. These findings provide an interesting avenue for further research into the quirks of stock price prediction.

[[LITERATURE REVIEW]]
Certainly, the connection between the popularity of the first name "Ruth" and Analog Devices' stock price (ADI) has been an area of interest for researchers across various disciplines. In "The Name Game: Cultural Implications of Monikers," Smith et al. shed light on the societal perceptions and impacts associated with different names. Furthermore, Doe's study "Naming Trends and Financial Markets" delves into the potential influence of popular names on stock market dynamics. These serious academic works lay the foundation for understanding the underlying mechanisms at play in our investigation.
Moving beyond academic research, works such as "The Power of Names" by Malcolm Gladwell and "Freakonomics: A Rogue Economist Explores the Hidden Side of Everything" by Steven D. Levitt and Stephen J. Dubner offer intriguing insights into the potential effects of names on individual behavior and societal trends. Meanwhile, fictional narratives such as "The Name of the Wind" by Patrick Rothfuss and "The Shadow of the Wind" by Carlos Ruiz Zafón, while not directly related to our topic, demonstrate the enduring fascination with the power and significance of names in human culture and imagination.
As we delve deeper into the literature, it is important to note the diverse sources of information that have been considered in this investigation. While conventional scholarly articles and renowned publications form the bedrock of our theoretical framework, it is worth acknowledging the unorthodox sources that have contributed to the breadth and depth of this review. From perusing the labels of soup cans to reviewing the backs of shampoo bottles, the exhaustive nature of this literature review is a testament to the thoroughness with which we have approached this research endeavor.
In summary, the foundational studies establish a theoretical basis for the potential influence of popular names on stock market dynamics, while the interdisciplinary insights and unconventional sources add a layer of richness to the scope of our investigation. With this comprehensive understanding as our backdrop, we are poised to analyze the empirical data and unravel the intriguing relationship between the name "Ruth" and Analog Devices' stock price. It is only fitting to say that, in the words of a stock trader-turned-philosopher, "When it comes to predicting stock prices, one must always take names into account - it's a 'stock' secret!"

[[RESULTS]]
The results of the analysis revealed a remarkably strong correlation between the popularity of the first name Ruth and Analog Devices Inc. (ADI) stock price from 2002 to 2022. The correlation coefficient of 0.9664183 indicates a near-perfect positive relationship between the two variables, signifying that as the popularity of the name Ruth increased, so did the stock price of ADI. One could say that the influence of Ruth's popularity on ADI's stock price is as undeniable as a classic dad joke.
The high r-squared value of 0.9339643 further supports the robustness of the relationship. This indicates that approximately 93.4% of the variability in ADI's stock price can be explained by the frequency of the name Ruth. It seems that Ruth's influence on ADI's stock price is more predictable than a dad's love for telling bad jokes.
The statistically significant p-value of less than 0.01 provides strong evidence against the null hypothesis, confirming that the observed correlation is unlikely to be a result of random chance. This suggests that the relationship is not a mere coincidence but rather a genuine connection worthy of further exploration. One might say that Ruth's impact on ADI's stock price is not to be taken lightly, much like the gravitational force between two pun-loving dads.
In Fig. 1, a scatterplot illustrates the unmistakable positive correlation between the frequency of the name Ruth and ADI's stock price. The upward trend in the scatterplot confirms the findings, leaving little room for skepticism about the influence of Ruth's popularity on ADI's stock performance. One could quip that this correlation is as clear as a dad's insistence on wearing socks with sandals.
The results of this study highlight the potential significance of seemingly unrelated factors, such as personal names, in influencing stock market dynamics. Further research into the underlying mechanisms of this correlation could provide valuable insights into the intricacies of stock price prediction. It appears that Ruth's popularity may indeed hold the "Ruth" to unlocking a new frontier in the field of stock market analysis, much like how a dad holds "the key" to his favorite dad joke, ready to unlock it at any given opportunity.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study provide compelling evidence supporting the hypothesis that there exists a strong positive correlation between the popularity of the first name Ruth and the stock price of Analog Devices Inc. (ADI). These results mirror and bolster the claims put forth by previous research, emphasizing the potential influence of seemingly unrelated factors, such as personal names, on stock market dynamics. Much like a well-timed dad joke, the correlation unearthed in this investigation is both intriguing and remarkable.

Building upon the existing literature, which includes the serious academic works expounded by Smith et al. and Doe, as well as the more light-hearted forays into name-related phenomena as illuminated by Gladwell, Levitt, and Dubner, the outcomes of this study both affirm and amplify the propositions set forth by these sources. The robust correlation coefficient and high r-squared value observed in our analysis substantiate the influence of Ruth's popularity on ADI's stock price, providing empirical validation for the theoretical constructs elucidated in prior studies. This interplay between empirical data and theoretical frameworks serves to enrich the discourse on the potential ramifications of name popularity on financial markets, much like how an unexpected pun enlivens an otherwise prosaic conversation.

The statistically significant p-value further buttresses the argument that the observed relationship between the frequency of the name Ruth and ADI's stock price is not merely coincidental. This outcome aligns with the theoretical underpinnings posited in the literature review, reinforcing the proposition that popular names may indeed harbor subtle yet tangible effects on stock market dynamics. Much like a well-crafted dad joke, the evidence presented in this study leaves little room for skepticism, pointing towards a legitimate and non-trivial connection that merits meticulous exploration.

The unmistakable positive correlation depicted in the scatterplot serves as a visual testament to the robustness of the relationship identified in this investigation, evoking a sense of clarity reminiscent of a clever quip spontaneously delivered by a witty dad. It is evident that the influence of Ruth's popularity on ADI's stock price is not a matter of happenstance, but rather a discernible and potent force that warrants thorough investigation. Therefore, we must acknowledge the need for future research endeavors aimed at unraveling the underlying mechanisms and potential implications of the connection elucidated in this study, much like how a seasoned dad recognizes the need to patiently explain the punchline of a pun to an uncomprehending audience.

In conclusion, the compelling evidence presented in this study not only affirms the theoretical propositions articulated in the existing literature but also sets the stage for further in-depth inquiries into the intricate interplay between personal names and stock market dynamics. It is clear that the popularity of the name Ruth may hold sway over Analog Devices' stock price, and exploring this relationship could unveil a novel frontier in financial market analysis. This correlation serves as a gentle reminder that even seemingly inconspicuous factors, such as personal names, may harbor unsuspected influences on complex systems, much like how a dad's seemingly innocuous joke can unexpectedly brighten an otherwise mundane situation.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Popularity of the first name Ruth and Analog Devices' stock price (ADI). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Ruth-lessly Predicting Stock Prices: The Correlation Between the Popularity of the Name Ruth and Analog Devices' Stock Price (ADI)"

[[ABSTRACT]]
This study examines the relationship between the popularity of the first name Ruth and Analog Devices' stock price (ADI) from 2002 to 2022. Using data from the US Social Security Administration and LSEG Analytics (Refinitiv), we calculated a correlation coefficient of 0.9664183 and found a significant p-value of less than 0.01. The results suggest a strong positive correlation between the frequency of the name Ruth and the performance of ADI's stock. So, one might say that Ruth's popularity might exert a subtle influence on ADI's stock price, making it a "Ruth-lessly" predictable factor. These findings provide an interesting avenue for further research into the quirks of stock price prediction.

[[INTRDUCTION]]
The relationship between individual names and various societal phenomena has long been a subject of interest and speculation. Whether it's the tumultuous love life of a "Jennifer" or the uncanny ability of "Karen" to speak to the manager, names seem to carry a certain mystique that extends beyond mere nomenclature. One such name that has piqued the interest of researchers is "Ruth," a name with biblical roots and a timeless appeal. In this paper, we delve into the intriguing correlation between the popularity of the first name Ruth and the stock price of Analog Devices Inc. (ADI).
The choice of the name "Ruth" as the focal point of this study was not made lightly. Its rich historical and cultural significance, coupled with its enduring popularity, rendered it a compelling candidate for investigation. As Mark Twain might have quipped, "The reports of Ruth's influence on stock prices are not greatly exaggerated." This study seeks to shed light on the existence of any correlation between the frequency of the name Ruth and the performance of ADI's stock over a two-decade period.
The significance of this analysis lies in the potential implications for both the financial and sociocultural spheres. If indeed a connection is established, it may open the floodgates for a new era of stock prediction, underpinned not only by economic indicators but also by the ebb and flow of popular nomenclature. One might say that this correlation could hold the "Ruth" to unlocking a new frontier in stock market analysis.

[[RESULTS]]
The results of the analysis revealed a remarkably strong correlation between the popularity of the first name Ruth and Analog Devices Inc. (ADI) stock price from 2002 to 2022. The correlation coefficient of 0.9664183 indicates a near-perfect positive relationship between the two variables, signifying that as the popularity of the name Ruth increased, so did the stock price of ADI. One could say that the influence of Ruth's popularity on ADI's stock price is as undeniable as a classic dad joke.
The high r-squared value of 0.9339643 further supports the robustness of the relationship. This indicates that approximately 93.4% of the variability in ADI's stock price can be explained by the frequency of the name Ruth. It seems that Ruth's influence on ADI's stock price is more predictable than a dad's love for telling bad jokes.
The statistically significant p-value of less than 0.01 provides strong evidence against the null hypothesis, confirming that the observed correlation is unlikely to be a result of random chance. This suggests that the relationship is not a mere coincidence but rather a genuine connection worthy of further exploration. One might say that Ruth's impact on ADI's stock price is not to be taken lightly, much like the gravitational force between two pun-loving dads.
In Fig. 1, a scatterplot illustrates the unmistakable positive correlation between the frequency of the name Ruth and ADI's stock price. The upward trend in the scatterplot confirms the findings, leaving little room for skepticism about the influence of Ruth's popularity on ADI's stock performance. One could quip that this correlation is as clear as a dad's insistence on wearing socks with sandals.
The results of this study highlight the potential significance of seemingly unrelated factors, such as personal names, in influencing stock market dynamics. Further research into the underlying mechanisms of this correlation could provide valuable insights into the intricacies of stock price prediction. It appears that Ruth's popularity may indeed hold the "Ruth" to unlocking a new frontier in the field of stock market analysis, much like how a dad holds "the key" to his favorite dad joke, ready to unlock it at any given opportunity.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the findings of this study illustrate a compelling correlation between the popularity of the first name Ruth and Analog Devices Inc. (ADI) stock price from 2002 to 2022. The near-perfect positive relationship, as indicated by the correlation coefficient of 0.9664183, is as undeniable as a classic dad joke. This suggests that as the popularity of the name Ruth increased, so did the stock price of ADI, much like a good dad joke – timeless and going up in value.

The high r-squared value of 0.9339643 further reinforces the substantial influence of Ruth's popularity on ADI's stock price, hinting at a predictability akin to a dad's love for telling bad jokes. The statistically significant p-value of less than 0.01 dismisses any notion of this relationship being a mere coincidence, akin to the gravitational force between two pun-loving dads.

The scatterplot visually confirms the unmistakable positive correlation, leaving little room for skepticism about the influence of Ruth's popularity on ADI's stock performance. This correlation is as clear as a dad's insistence on wearing socks with sandals - an undeniable relationship that defies the odds.

While this study sheds light on the curious connection between the name Ruth and stock price dynamics, it also highlights the need for further research into the underlying mechanisms of this correlation. However, it is evident that no more research is needed in this area; the findings speak for themselves, much like a well-timed dad joke.

In closing, the correlation between the popularity of the first name Ruth and Analog Devices Inc. (ADI) stock price has been established with a clarity that even a dad's most groan-worthy pun would envy. This study contributes to the ever-evolving landscape of stock market analysis, demonstrating that seemingly unrelated factors, such as personal names, may indeed hold the "Ruth" to unlocking new frontiers in predictive modeling.

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 Ruth-lessly Predicting Stock Prices: The Correlation Between the Popularity of the Name Ruth and Analog Devices' Stock Price (ADI). Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Quantitative Analysis

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 Ruth-lessly Predicting Stock Prices: The Correlation Between the Popularity of the Name Ruth and Analog Devices' Stock Price (ADI). Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Quirky Sociolinguistic Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Ruth-lessly Predicting Stock Prices: The Correlation Between the Popularity of the Name Ruth and Analog Devices' Stock Price (ADI) with an abstract of This study examines the relationship between the popularity of the first name Ruth and Analog Devices' stock price (ADI) from 2002 to 2022. Using data from the US Social Security Administration and LSEG Analytics (Refinitiv), we calculated a correlation coefficient of 0.9664183 and found a significant p-value of less than 0.01. The results suggest a strong positive correlation between the frequency of the name Ruth and the performance of ADI's stock. So, one might say that Ruth's popularity might exert a subtle influence on ADI's stock price, making it a "Ruth-lessly" predictable factor. These findings provide an interesting avenue for further research into the quirks of stock price prediction.

ChatGPT:

Ruth, stock price prediction, first name popularity, Analog Devices stock price, ADI, correlation analysis, stock market quirks, Ruth's influence on stock prices, Social Security Administration data, LSEG Analytics, Refinitiv, stock price correlation, Ruth's impact on stock performance

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

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Data details

Popularity of the first name Ruth
Detailed data title: Babies of all sexes born in the US named Ruth
Source: US Social Security Administration
See what else correlates with Popularity of the first name Ruth

Analog Devices' stock price (ADI)
Detailed data title: Opening price of Analog Devices (ADI) 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 Analog Devices' stock price (ADI)

Correlation r = 0.9664183 (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 = 0.9339643 (Coefficient of determination)
This means 93.4% of the change in the one variable (i.e., Analog Devices' stock price (ADI)) is predictable based on the change in the other (i.e., Popularity of the first name Ruth) over the 21 years from 2002 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.1E-12.^Show 0.0000000000011432278983924813
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 0.97 in 1.1E-10% of random cases. Said differently, if you correlated 874,716,232,351 random variables^Note You don't actually need 874 billion 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.

[ 0.92, 0.99 ] 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
Popularity of the first name Ruth (Babies born)	905	896	911	908	889	962	933	915	932	905	930	993	1062	1106	1102	1210	1247	1349	1324	1573	1656
Analog Devices' stock price (ADI) (Stock price)	44.75	24.25	45.95	37.02	36.13	32.93	31.19	19	31.79	37.68	36.46	42.8	49.52	55.68	54.24	72.6	89.24	84.03	120.11	148.45	175.17

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.
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. ^Note 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. ^{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([905,896,911,908,889,962,933,915,932,905,930,993,1062,1106,1102,1210,1247,1349,1324,1573,1656,])
array_2 = np.array([44.75,24.25,45.95,37.02,36.13,32.93,31.19,19,31.79,37.68,36.46,42.8,49.52,55.68,54.24,72.6,89.24,84.03,120.11,148.45,175.17,])
array_1_name = "Popularity of the first name Ruth"
array_2_name = "Analog Devices' stock price (ADI)"

# 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 Popularity of the first name Ruth
Line chart for only Analog Devices' stock price (ADI)
AI-generated correlation image
The spurious research paper: Ruth-lessly Predicting Stock Prices: The Correlation Between the Popularity of the Name Ruth and Analog Devices' Stock Price (ADI)

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Correlation ID: 4080 · Black Variable ID: 2645 · Red Variable ID: 1648


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