Spurious correlation #2,927 · 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 Sunny and the second variable is Salesforce's stock price (CRM). The chart goes from 2005 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 Sunny and the second variable is Salesforce's stock price (CRM). The chart goes from 2005 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of Sunnys grew, so did the demand for sunshine, leading to an overall increase in positivity. This positivity somehow found its way into the stock market, specifically boosting the performance of Salesforce, the leading provider of cloud-based solutions. It's like a ray of financial sunshine beaming down on CRM!

^{Show image generation prompt} Model: dalle-3
Prompt: [An image that looks like it is a scene from A Disney Movie] In the heart of a lush, vibrant park, the sun's golden rays illuminate the joyous setting. Families gather under towering trees, and the air is abuzz with laughter and playful chatter. Children with beaming smiles skip merrily through the meadows, their spirits lifted by the enchanting ambiance. As the lively scene unfolds, a majestic building stands in the distance, adorned with a digital stock ticker displaying the steady rise of Salesforce's stock (CRM). The scene captures the harmonious blend of nature's energy and the optimistic influence it has on the world, symbolized by the increasing success of companies like Salesforce. 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 Sunny and Salesforce's stock price (CRM). 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 Cyberpunk An image that looks like it is a scene from A Disney Movie Data cyber art Futuristic
ChatGPT: An image that looks like it is a scene from A Disney 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 Popularity of the first name Sunny and Salesforce's stock price (CRM), in the following situation: As the number of people named Sunny increases, so does the amount of positive energy in the world, which leads to increased productivity and success, including for companies like Salesforce, thus causing their stock price to rise.. Keep the description simple.
ChatGPT: A sunny park is filled with people enjoying the warm weather. Children are laughing and playing, and the sound of chatter and laughter fills the air. In the background, a digital stock ticker on a nearby building shows the price of Salesforce's stock (CRM) steadily rising. The joyful atmosphere seems to be creating a positive ripple effect in the world, leading to increased productivity and success for companies like Salesforce.

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 Disney Movie ] and depicting this scene: A sunny park is filled with people enjoying the warm weather. Children are laughing and playing, and the sound of chatter and laughter fills the air. In the background, a digital stock ticker on a nearby building shows the price of Salesforce's stock (CRM) steadily rising. The joyful atmosphere seems to be creating a positive ripple effect in the world, leading to increased productivity and success for companies like Salesforce. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [An image that looks like it is a scene from A Disney Movie] In the heart of a lush, vibrant park, the sun's golden rays illuminate the joyous setting. Families gather under towering trees, and the air is abuzz with laughter and playful chatter. Children with beaming smiles skip merrily through the meadows, their spirits lifted by the enchanting ambiance. As the lively scene unfolds, a majestic building stands in the distance, adorned with a digital stock ticker displaying the steady rise of Salesforce's stock (CRM). The scene captures the harmonious blend of nature's energy and the optimistic influence it has on the world, symbolized by the increasing success of companies like Salesforce.

*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 Sunny caused Salesforce's stock price (CRM) to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)

Sunny Bunny, Money Honey: Investing in CRM with a Name that’s Funny

Journal of Marketing Humor

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 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 Sunny and Salesforce's stock price (CRM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
Sunny Bunny, Money Honey: Investing in CRM with a Name that’s Funny

[[ABSTRACT]]
Investors often seek unconventional indicators for stock performance, and our study delves into the potential relationship between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM). Leveraging data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a thorough analysis of the time period from 2005 to 2022. Our findings reveal a striking correlation coefficient of 0.9853491 and a statistically significant p-value of less than 0.01. This unexpected connection beckons further examination and prompts a lighthearted exploration of the whimsical ways in which human behavior and financial markets intertwine. While this correlation may seem sunny, investors should approach with caution and ample skepticism, as causation and correlation may just be engaging in a quirky pas de deux.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between human behavior and financial markets has been a subject of fascination and intrigue for researchers and investors alike. While conventional economic theory emphasizes rational decision-making and efficient market mechanisms, the realm of behavioral finance acknowledges the idiosyncratic and, dare I say, whimsical nature of market participants. In this study, we embark on an unconventional exploration of the potential connection between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM).
Investors are no strangers to seeking out curious and offbeat indicators to bolster their investment decisions. From the classic "hemline index" to the "lipstick effect," financial markets have been the canvas for creative and, at times, eyebrow-raising analytical approaches. Our investigation into the correlation between the prevalence of the name "Sunny" and the fluctuations in Salesforce's stock price presents an opportunity to further expand the repertoire of unorthodox indicators, without losing sight of the profound statistical rigor and methodological soundness that underpin our analysis.
Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv), we scrutinized the time frame from 2005 to 2022, capturing the ebbs and flows of both linguistic trends and financial dynamics. Our analytical lens revealed a striking correlation coefficient of 0.9853491 and a statistically significant p-value of less than 0.01, illuminating a noteworthy association that demands scholarly contemplation and yes, perhaps even a chuckle or two.
As we embark on this journey of examining the unexpected allure of a name and its purported influence on stock prices, it is essential to employ a blend of diligence and quirkiness in our approach. While we acknowledge the allure of a correlation as high as a cloudless summer sky, we are also mindful of the cautionary winds of skepticism, reminding us that correlation does not imply causation and that the allure of a name may be mere whimsy in the dance of financial markets.
Join us, as we bask in the radiance of "Sunny Bunny, Money Honey," and endeavor to shine a light on the unexpected interplay of nomenclature and financial fortunes.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The potential relationship between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM) has not been extensively explored in the existing literature. However, a few studies have delved into the intriguing realm of linguistic trends and their possible connections to societal phenomena and economic indicators.

Smith and Doe (2010) conducted a linguistic analysis of names and their perceived connotations in consumer behavior, shedding light on the subtle influence of nomenclature on product preferences. Similarly, Jones et al. (2015) examined the correlation between the phonetic qualities of names and their impact on career success, offering insight into the broader implications of names in professional contexts.

Moving beyond the realm of academia, "The Power of Names" by Smith (2008) provides a comprehensive exploration of the cultural and psychological significance of names, highlighting the multifaceted ways in which names shape individual identities and societal perceptions. In a more whimsical vein, "The Name of the Wind" by Rothfuss (2007) captures the enchanting allure of names, albeit in a fictional context, inviting readers to ponder the evocative power of linguistic symbols.

In the realm of social media, an intriguing tweet from @StockSleuth21 caught our attention, positing a playful correlation between sunny weather patterns and bullish trends in stock prices, albeit in a lighthearted and speculative manner. While social media posts are often characterized by anecdotal musings, the proliferation of such discussions underscores the public's fascination with offbeat indicators and their potential impact on investment decisions.

As we navigate through the existing literature and diverse sources of information, it becomes evident that the connection between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM) holds an unusual, yet captivating allure that beckons further exploration and perhaps a dash of whimsy.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Popularity of the first name Sunny and Salesforce's stock price (CRM). 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 US Social Security Administration and LSEG Analytics (Refinitiv) . You used data from 2005 to 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Sunny Bunny, Money Honey: Investing in CRM with a Name that’s Funny

[[ABSTRACT]]
Investors often seek unconventional indicators for stock performance, and our study delves into the potential relationship between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM). Leveraging data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a thorough analysis of the time period from 2005 to 2022. Our findings reveal a striking correlation coefficient of 0.9853491 and a statistically significant p-value of less than 0.01. This unexpected connection beckons further examination and prompts a lighthearted exploration of the whimsical ways in which human behavior and financial markets intertwine. While this correlation may seem sunny, investors should approach with caution and ample skepticism, as causation and correlation may just be engaging in a quirky pas de deux.

[[INTRODUCTION]]
The relationship between human behavior and financial markets has been a subject of fascination and intrigue for researchers and investors alike. While conventional economic theory emphasizes rational decision-making and efficient market mechanisms, the realm of behavioral finance acknowledges the idiosyncratic and, dare I say, whimsical nature of market participants. In this study, we embark on an unconventional exploration of the potential connection between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM).
Investors are no strangers to seeking out curious and offbeat indicators to bolster their investment decisions. From the classic "hemline index" to the "lipstick effect," financial markets have been the canvas for creative and, at times, eyebrow-raising analytical approaches. Our investigation into the correlation between the prevalence of the name "Sunny" and the fluctuations in Salesforce's stock price presents an opportunity to further expand the repertoire of unorthodox indicators, without losing sight of the profound statistical rigor and methodological soundness that underpin our analysis.
Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv), we scrutinized the time frame from 2005 to 2022, capturing the ebbs and flows of both linguistic trends and financial dynamics. Our analytical lens revealed a striking correlation coefficient of 0.9853491 and a statistically significant p-value of less than 0.01, illuminating a noteworthy association that demands scholarly contemplation and yes, perhaps even a chuckle or two.
As we embark on this journey of examining the unexpected allure of a name and its purported influence on stock prices, it is essential to employ a blend of diligence and quirkiness in our approach. While we acknowledge the allure of a correlation as high as a cloudless summer sky, we are also mindful of the cautionary winds of skepticism, reminding us that correlation does not imply causation and that the allure of a name may be mere whimsy in the dance of financial markets.
Join us, as we bask in the radiance of "Sunny Bunny, Money Honey," and endeavor to shine a light on the unexpected interplay of nomenclature and financial fortunes.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the purported relationship between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM), we employed a methodological approach that danced between the realms of linguistic trends and financial data. Our research team synthesized data sources from the US Social Security Administration and LSEG Analytics (Refinitiv) to construct a comprehensive dataset spanning the years 2005 to 2022.

The first step of our convoluted investigation involved harnessing the power of web scraping techniques to gather all instances of the name "Sunny" from various online repositories. We then cross-referenced this data with the Social Security Administration's records to ascertain the annual prevalence of this moniker, ensuring the utmost accuracy in capturing the ebbs and flows of its popularity.

Next, we pirouetted into the realm of finance, pirating... I mean, procuring historical stock price data for Salesforce (CRM) from trusted financial data providers. This treasure trove of information allowed us to track the undulating movements of CRM's stock price over the same time frame, aligning our temporal sequences with the precision of a seasoned tailor.

Applying a method as intricate as untangling a kite string in a gusty wind, we performed statistical analyses to elucidate the potential correlation between the popularity of the name "Sunny" and Salesforce's stock price. With bated breath, we computed correlation coefficients and p-values, employing the robustness of our methodology to derive meaningful insights from the hues of our data.

While our approach may seem whimsical, it is essential to note the unyielding rigor and precision with which we executed our methodological framework. Among the somber hum of statistical analyses and data manipulation, a tinge of mirth may have occasionally flickered, but rest assured, the solemnity of scientific inquiry remained our guiding star.

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

Please make up the results section of an academic research paper presenting the findings of the connection between Popularity of the first name Sunny and Salesforce's stock price (CRM). 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 US Social Security Administration and LSEG Analytics (Refinitiv) .

For the time period 2005 to 2022, you found a correlation 0.9853491, r-squared of 0.9709129, 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]]
Sunny Bunny, Money Honey: Investing in CRM with a Name that’s Funny

[[ABSTRACT]]
Investors often seek unconventional indicators for stock performance, and our study delves into the potential relationship between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM). Leveraging data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a thorough analysis of the time period from 2005 to 2022. Our findings reveal a striking correlation coefficient of 0.9853491 and a statistically significant p-value of less than 0.01. This unexpected connection beckons further examination and prompts a lighthearted exploration of the whimsical ways in which human behavior and financial markets intertwine. While this correlation may seem sunny, investors should approach with caution and ample skepticism, as causation and correlation may just be engaging in a quirky pas de deux.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The relationship between human behavior and financial markets has been a subject of fascination and intrigue for researchers and investors alike. While conventional economic theory emphasizes rational decision-making and efficient market mechanisms, the realm of behavioral finance acknowledges the idiosyncratic and, dare I say, whimsical nature of market participants. In this study, we embark on an unconventional exploration of the potential connection between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM).
Investors are no strangers to seeking out curious and offbeat indicators to bolster their investment decisions. From the classic "hemline index" to the "lipstick effect," financial markets have been the canvas for creative and, at times, eyebrow-raising analytical approaches. Our investigation into the correlation between the prevalence of the name "Sunny" and the fluctuations in Salesforce's stock price presents an opportunity to further expand the repertoire of unorthodox indicators, without losing sight of the profound statistical rigor and methodological soundness that underpin our analysis.
Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv), we scrutinized the time frame from 2005 to 2022, capturing the ebbs and flows of both linguistic trends and financial dynamics. Our analytical lens revealed a striking correlation coefficient of 0.9853491 and a statistically significant p-value of less than 0.01, illuminating a noteworthy association that demands scholarly contemplation and yes, perhaps even a chuckle or two.
As we embark on this journey of examining the unexpected allure of a name and its purported influence on stock prices, it is essential to employ a blend of diligence and quirkiness in our approach. While we acknowledge the allure of a correlation as high as a cloudless summer sky, we are also mindful of the cautionary winds of skepticism, reminding us that correlation does not imply causation and that the allure of a name may be mere whimsy in the dance of financial markets.
Join us, as we bask in the radiance of "Sunny Bunny, Money Honey," and endeavor to shine a light on the unexpected interplay of nomenclature and financial fortunes.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The examination of the relationship between the popularity of the first name "Sunny" and Salesforce's (CRM) stock price unveiled a remarkably high correlation coefficient of 0.9853491, signaling a robust association between these seemingly disparate variables. The coefficient of determination (r-squared) stood at an impressive 0.9709129, indicating that approximately 97.09% of the variability in CRM stock price could be explained by the prevalence of the name "Sunny." Accordingly, the p-value of less than 0.01 lent further credence to the statistical significance of this correlation, affirming its reliability and importance in our analysis. As illustrated in Fig. 1, the scatterplot depicts a clear and compelling linear relationship between the prevalence of the name "Sunny" and the fluctuations in Salesforce's stock price.

The striking correlation encountered in this study invites a moment of levity amidst the rigors of empirical research. While the allure of a high correlation coefficient may be as compelling as a sun-drenched day, it is crucial to approach these findings with a dose of skepticism and a raised eyebrow, recognizing that correlation does not imply causation. Investors and researchers alike are encouraged to embrace the playful serendipity of this unexpected connection while heeding the warning signs of spurious correlations and chance relationships. For as tempting as it may be to bask in the warmth of an almost too-perfect correlation, we are reminded that in the world of finance, cautious scrutiny and critical inquiry are the navigational tools that guide us through the whimsical dance of market dynamics.

In summary, the data illuminate a noteworthy alignment between the popularity of the first name "Sunny" and the movements in Salesforce's stock price, prompting further investigation into the idiosyncratic and often amusing ways in which human behavior and financial markets intersect. This correlation may indeed cast a sunny glow on the investment landscape, but our analysis implores stakeholders to tread carefully, for beneath the sunshine may lie a subtler, more complex interplay that calls for judicious interpretation and perhaps a touch of lighthearted bemusement.

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 Sunny and Salesforce's stock price (CRM). 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]]
Sunny Bunny, Money Honey: Investing in CRM with a Name that’s Funny

[[ABSTRACT]]
Investors often seek unconventional indicators for stock performance, and our study delves into the potential relationship between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM). Leveraging data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a thorough analysis of the time period from 2005 to 2022. Our findings reveal a striking correlation coefficient of 0.9853491 and a statistically significant p-value of less than 0.01. This unexpected connection beckons further examination and prompts a lighthearted exploration of the whimsical ways in which human behavior and financial markets intertwine. While this correlation may seem sunny, investors should approach with caution and ample skepticism, as causation and correlation may just be engaging in a quirky pas de deux.

[[LITERATURE REVIEW]]
The potential relationship between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM) has not been extensively explored in the existing literature. However, a few studies have delved into the intriguing realm of linguistic trends and their possible connections to societal phenomena and economic indicators.
Smith and Doe (2010) conducted a linguistic analysis of names and their perceived connotations in consumer behavior, shedding light on the subtle influence of nomenclature on product preferences. Similarly, Jones et al. (2015) examined the correlation between the phonetic qualities of names and their impact on career success, offering insight into the broader implications of names in professional contexts.
Moving beyond the realm of academia, "The Power of Names" by Smith (2008) provides a comprehensive exploration of the cultural and psychological significance of names, highlighting the multifaceted ways in which names shape individual identities and societal perceptions. In a more whimsical vein, "The Name of the Wind" by Rothfuss (2007) captures the enchanting allure of names, albeit in a fictional context, inviting readers to ponder the evocative power of linguistic symbols.
In the realm of social media, an intriguing tweet from @StockSleuth21 caught our attention, positing a playful correlation between sunny weather patterns and bullish trends in stock prices, albeit in a lighthearted and speculative manner. While social media posts are often characterized by anecdotal musings, the proliferation of such discussions underscores the public's fascination with offbeat indicators and their potential impact on investment decisions.
As we navigate through the existing literature and diverse sources of information, it becomes evident that the connection between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM) holds an unusual, yet captivating allure that beckons further exploration and perhaps a dash of whimsy.

[[RESULTS]]
The examination of the relationship between the popularity of the first name "Sunny" and Salesforce's (CRM) stock price unveiled a remarkably high correlation coefficient of 0.9853491, signaling a robust association between these seemingly disparate variables. The coefficient of determination (r-squared) stood at an impressive 0.9709129, indicating that approximately 97.09% of the variability in CRM stock price could be explained by the prevalence of the name "Sunny." Accordingly, the p-value of less than 0.01 lent further credence to the statistical significance of this correlation, affirming its reliability and importance in our analysis. As illustrated in Fig. 1, the scatterplot depicts a clear and compelling linear relationship between the prevalence of the name "Sunny" and the fluctuations in Salesforce's stock price.
The striking correlation encountered in this study invites a moment of levity amidst the rigors of empirical research. While the allure of a high correlation coefficient may be as compelling as a sun-drenched day, it is crucial to approach these findings with a dose of skepticism and a raised eyebrow, recognizing that correlation does not imply causation. Investors and researchers alike are encouraged to embrace the playful serendipity of this unexpected connection while heeding the warning signs of spurious correlations and chance relationships. For as tempting as it may be to bask in the warmth of an almost too-perfect correlation, we are reminded that in the world of finance, cautious scrutiny and critical inquiry are the navigational tools that guide us through the whimsical dance of market dynamics.
In summary, the data illuminate a noteworthy alignment between the popularity of the first name "Sunny" and the movements in Salesforce's stock price, prompting further investigation into the idiosyncratic and often amusing ways in which human behavior and financial markets intersect. This correlation may indeed cast a sunny glow on the investment landscape, but our analysis implores stakeholders to tread carefully, for beneath the sunshine may lie a subtler, more complex interplay that calls for judicious interpretation and perhaps a touch of lighthearted bemusement.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study not only illuminate the unexpectedly robust correlation between the prevalence of the name "Sunny" and Salesforce's (CRM) stock price but also impart a sense of whimsy and wonder to the realm of financial analysis. Our findings align with prior research that has delved into the influence of linguistic trends and nomenclature on consumer behavior and economic indicators. Indeed, much like a sunny day can bring a smile to one's face, our data echo the intriguing musings of @StockSleuth21 and invite a playful exploration of the interplay between names and financial markets.

The positive correlation coefficient of 0.9853491 and the high coefficient of determination (r-squared) of 0.9709129 speak to a compelling association between the name "Sunny" and the fluctuations in CRM stock price. However, we must exercise caution and resist the temptation to bask in the glow of this correlation, as we remain acutely aware of the adage that correlation does not imply causation. After all, while a sunny disposition can brighten one's day, it does not single-handedly dictate the ebbs and flows of stock prices.

Our findings intertwine with the broader implications of names on societal phenomena and professional contexts, as evinced by the studies of Smith, Doe, Jones, and Rothfuss. The multifaceted power of names and their influence on human behavior reverberate in our examination of the financial markets, reaffirming the notion that linguistic symbols, even in the form of names, hold a captivating allure that extends into the domain of investment decisions.

In essence, the serendipitous alignment between the popularity of the first name "Sunny" and Salesforce's stock price not only informs investment strategies but also beckons us to embrace the whimsical dance of market dynamics with a healthy dose of skepticism and a dash of lighthearted bemusement. As we navigate through the unpredictable terrain of financial markets, we are reminded that behind every correlation lies a rich tapestry of potential confounding variables and chance relationships, urging us to approach our findings with a keen eye for nuance and an appreciation for the playful intrigue of this unexpected connection.

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 Sunny and Salesforce's stock price (CRM). 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]]
Sunny Bunny, Money Honey: Investing in CRM with a Name that’s Funny

[[ABSTRACT]]
Investors often seek unconventional indicators for stock performance, and our study delves into the potential relationship between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM). Leveraging data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a thorough analysis of the time period from 2005 to 2022. Our findings reveal a striking correlation coefficient of 0.9853491 and a statistically significant p-value of less than 0.01. This unexpected connection beckons further examination and prompts a lighthearted exploration of the whimsical ways in which human behavior and financial markets intertwine. While this correlation may seem sunny, investors should approach with caution and ample skepticism, as causation and correlation may just be engaging in a quirky pas de deux.

[[INTRDUCTION]]
The relationship between human behavior and financial markets has been a subject of fascination and intrigue for researchers and investors alike. While conventional economic theory emphasizes rational decision-making and efficient market mechanisms, the realm of behavioral finance acknowledges the idiosyncratic and, dare I say, whimsical nature of market participants. In this study, we embark on an unconventional exploration of the potential connection between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM).
Investors are no strangers to seeking out curious and offbeat indicators to bolster their investment decisions. From the classic "hemline index" to the "lipstick effect," financial markets have been the canvas for creative and, at times, eyebrow-raising analytical approaches. Our investigation into the correlation between the prevalence of the name "Sunny" and the fluctuations in Salesforce's stock price presents an opportunity to further expand the repertoire of unorthodox indicators, without losing sight of the profound statistical rigor and methodological soundness that underpin our analysis.
Drawing on data from the US Social Security Administration and LSEG Analytics (Refinitiv), we scrutinized the time frame from 2005 to 2022, capturing the ebbs and flows of both linguistic trends and financial dynamics. Our analytical lens revealed a striking correlation coefficient of 0.9853491 and a statistically significant p-value of less than 0.01, illuminating a noteworthy association that demands scholarly contemplation and yes, perhaps even a chuckle or two.
As we embark on this journey of examining the unexpected allure of a name and its purported influence on stock prices, it is essential to employ a blend of diligence and quirkiness in our approach. While we acknowledge the allure of a correlation as high as a cloudless summer sky, we are also mindful of the cautionary winds of skepticism, reminding us that correlation does not imply causation and that the allure of a name may be mere whimsy in the dance of financial markets.
Join us, as we bask in the radiance of "Sunny Bunny, Money Honey," and endeavor to shine a light on the unexpected interplay of nomenclature and financial fortunes.

[[RESULTS]]
The examination of the relationship between the popularity of the first name "Sunny" and Salesforce's (CRM) stock price unveiled a remarkably high correlation coefficient of 0.9853491, signaling a robust association between these seemingly disparate variables. The coefficient of determination (r-squared) stood at an impressive 0.9709129, indicating that approximately 97.09% of the variability in CRM stock price could be explained by the prevalence of the name "Sunny." Accordingly, the p-value of less than 0.01 lent further credence to the statistical significance of this correlation, affirming its reliability and importance in our analysis. As illustrated in Fig. 1, the scatterplot depicts a clear and compelling linear relationship between the prevalence of the name "Sunny" and the fluctuations in Salesforce's stock price.
The striking correlation encountered in this study invites a moment of levity amidst the rigors of empirical research. While the allure of a high correlation coefficient may be as compelling as a sun-drenched day, it is crucial to approach these findings with a dose of skepticism and a raised eyebrow, recognizing that correlation does not imply causation. Investors and researchers alike are encouraged to embrace the playful serendipity of this unexpected connection while heeding the warning signs of spurious correlations and chance relationships. For as tempting as it may be to bask in the warmth of an almost too-perfect correlation, we are reminded that in the world of finance, cautious scrutiny and critical inquiry are the navigational tools that guide us through the whimsical dance of market dynamics.
In summary, the data illuminate a noteworthy alignment between the popularity of the first name "Sunny" and the movements in Salesforce's stock price, prompting further investigation into the idiosyncratic and often amusing ways in which human behavior and financial markets intersect. This correlation may indeed cast a sunny glow on the investment landscape, but our analysis implores stakeholders to tread carefully, for beneath the sunshine may lie a subtler, more complex interplay that calls for judicious interpretation and perhaps a touch of lighthearted bemusement.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has shed light on the curious correlation between the prevalence of the first name "Sunny" and the stock price of Salesforce (CRM). The remarkably high correlation coefficient, along with the statistically significant p-value, raises eyebrows and beckons a whimsical exploration of the interplay between linguistic trends and financial markets. While the allure of such a correlation may be as captivating as a sunny day, we must approach these findings with a hint of skepticism and a dash of caution, for the dance of finance is as capricious as a spring breeze.

This unexpected connection between a name and financial performance provides a moment of levity, amidst the often serious and academic discourse of market analysis. However, investors and scholars alike must proceed with a thoughtful balance of diligence and quirkiness, recognizing that correlation does not imply causation. Indeed, the waltz of market dynamics can be as unpredictable and amusing as a game of musical chairs.

Therefore, while the correlation between the first name "Sunny" and Salesforce's stock price may appear as clear as day, our study urges us to embrace the whimsy with caution, acknowledging that the market's melodies may hide subtle complexities and surprise harmonies beneath the surface.
In light of our findings, we assert that no further research is warranted in this area, as we cherish the delightfully quirky nature of this offbeat correlation and bid adieu to this topic with a wink and a nod. After all, in the end, perhaps "Sunny Bunny, Money Honey" is all the cheerful magic we need in the world of finance.

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 Sunny Bunny, Money Honey: Investing in CRM with a Name that’s Funny. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Marketing Humor

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 Sunny Bunny, Money Honey: Investing in CRM with a Name that’s Funny. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Whimsical Economic 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 Sunny Bunny, Money Honey: Investing in CRM with a Name that’s Funny with an abstract of Investors often seek unconventional indicators for stock performance, and our study delves into the potential relationship between the popularity of the first name "Sunny" and the stock price of Salesforce (CRM). Leveraging data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a thorough analysis of the time period from 2005 to 2022. Our findings reveal a striking correlation coefficient of 0.9853491 and a statistically significant p-value of less than 0.01. This unexpected connection beckons further examination and prompts a lighthearted exploration of the whimsical ways in which human behavior and financial markets intertwine. While this correlation may seem sunny, investors should approach with caution and ample skepticism, as causation and correlation may just be engaging in a quirky pas de deux.

ChatGPT:

"Sunny name popularity stock performance correlation," "Salesforce stock performance," "First name popularity stock correlation," "US Social Security Administration data," "LSEG Analytics Refinitiv data," "Causation vs correlation in stock performance," "Human behavior financial markets correlation," "Unconventional stock performance indicators," "Financial market whimsical correlations," "Stock price analysis of first name popularity."

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

Salesforce's stock price (CRM)
Detailed data title: Opening price of Salesforce (CRM) 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 Salesforce's stock price (CRM)

Correlation r = 0.9853491 (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 = 0.9709129 (Coefficient of determination)
This means 97.1% of the change in the one variable (i.e., Salesforce's stock price (CRM)) is predictable based on the change in the other (i.e., Popularity of the first name Sunny) over the 18 years from 2005 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.02E-13.^Show 0.0000000000001019503482698508
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 0.99 in 1.02E-11% of random cases. Said differently, if you correlated 9,808,696,262,156 random variables^Note You don't actually need 9 trillion 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 17 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 17 because we have two variables measured over a period of 18 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.

[ 0.96, 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.

	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Popularity of the first name Sunny (Babies born)	210	196	193	165	227	254	226	251	270	247	292	285	324	390	459	523	598	707
Salesforce's stock price (CRM) (Stock price)	4.1	8.03	9.14	15.76	8.03	18.65	33.28	26.05	42.94	55.2	59.9	77.14	69.29	102.88	133.4	163.92	222.64	255.01

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([210,196,193,165,227,254,226,251,270,247,292,285,324,390,459,523,598,707,])
array_2 = np.array([4.1,8.03,9.14,15.76,8.03,18.65,33.28,26.05,42.94,55.2,59.9,77.14,69.29,102.88,133.4,163.92,222.64,255.01,])
array_1_name = "Popularity of the first name Sunny"
array_2_name = "Salesforce's stock price (CRM)"

# 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 Sunny
Line chart for only Salesforce's stock price (CRM)
AI-generated correlation image
The spurious research paper: Sunny Bunny, Money Honey: Investing in CRM with a Name that’s Funny

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Correlation ID: 2927 · Black Variable ID: 3898 · Red Variable ID: 1573


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