Spurious correlation #3,609 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Google searches for 'roblox' and the second variable is T-Mobile Us' stock price (TMUS). The chart goes from 2008 to 2023, 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 Google searches for 'roblox' and the second variable is T-Mobile Us' stock price (TMUS). The chart goes from 2008 to 2023, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As people spent more time building their virtual empires in Roblox, they were also inadvertently boosting T-Mobile's stock by constructing a stronger connection to the internet. It seems the key to T-Mobile's success was just a better 'networking' strategy!

^{Show image generation prompt} Model: dalle-3
Prompt: An image that looks like it is a scene from A Disney Movie, depicting this scene: In a vibrant and bustling cyber world, a colorful cityscape of computer screens and neon lights extends as far as the eye can see. Amidst the frenzy of digital activity, a distinctive Google search bar glows prominently, displaying the word "Roblox" in bold letters, drawing attention to a group of energetic young gamers immersed in the latest updates of the virtual universe. Simultaneously, a dynamic stream of stock market information features the rising ticker symbol TMUS, illuminating the faces of another group of individuals passionately tracking the stock's upward trajectory. The vibrant scene radiates shared excitement and anticipation, capturing the joy of discovery and the thrill of technological advancement. 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: Google searches for 'roblox' and T-Mobile Us' stock price (TMUS). 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: Data cyber art Hyper-realistic An image that looks like it is a scene from A Disney Movie Cubism Glitch art
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 Google searches for 'roblox' and T-Mobile Us' stock price (TMUS), in the following situation: Because the surge in Roblox searches led to more people engaging with the online gaming platform, T-Mobile US' stock price saw a boost as gamers couldn't resist sharing their excitement over Roblox's latest updates and T-Mobile's stellar network coverage. The increased online activity created a positive buzz that attracted more investors, propelling TMUS to new heights as gamers and stock enthusiasts alike hopped on board the Roblox-T-Mobile train.. Keep the description simple.
ChatGPT: Amidst a flurry of activity on computer screens, the Google search bar prominently displays "Roblox," while a stream of stock market information features T-Mobile US' ticker symbol TMUS rising steadily. A group of enthusiastic gamers, clearly caught up in the excitement of exploring Roblox's latest updates, can be seen animatedly discussing the game, while another group, tracking stock prices, excitedly gestures towards the upward trajectory of TMUS, creating a shared buzz of anticipation and enthusiasm.

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: Amidst a flurry of activity on computer screens, the Google search bar prominently displays "Roblox," while a stream of stock market information features T-Mobile US' ticker symbol TMUS rising steadily. A group of enthusiastic gamers, clearly caught up in the excitement of exploring Roblox's latest updates, can be seen animatedly discussing the game, while another group, tracking stock prices, excitedly gestures towards the upward trajectory of TMUS, creating a shared buzz of anticipation and enthusiasm. 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, depicting this scene: In a vibrant and bustling cyber world, a colorful cityscape of computer screens and neon lights extends as far as the eye can see. Amidst the frenzy of digital activity, a distinctive Google search bar glows prominently, displaying the word "Roblox" in bold letters, drawing attention to a group of energetic young gamers immersed in the latest updates of the virtual universe. Simultaneously, a dynamic stream of stock market information features the rising ticker symbol TMUS, illuminating the faces of another group of individuals passionately tracking the stock's upward trajectory. The vibrant scene radiates shared excitement and anticipation, capturing the joy of discovery and the thrill of technological advancement.

*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 roblox (Google searches for 'roblox') caused T-Mobile Us' stock price (TMUS) to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Unlocking the Connection: Investigating the Relationship Between Google Searches for 'Roblox' and T-Mobile Us' Stock Price

The Journal of Digital Diversions

Jan 2024

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

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

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Google searches for 'roblox' and T-Mobile Us' stock price (TMUS). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
Unlocking the Connection: Investigating the Relationship Between Google Searches for 'Roblox' and T-Mobile Us' Stock Price

[[ABSTRACT]]
This study delves into the peculiar connection between two seemingly unrelated phenomena: Google searches for the popular online game 'Roblox', and the stock price of T-Mobile Us (TMUS). Using data from Google Trends and LSEG Analytics (Refinitiv), we sought to unlock the mystery behind this enigmatic relationship. Our research team uncovered a remarkably high correlation coefficient of 0.9674306 and a statistically significant p-value of less than 0.01 for the period spanning from 2008 to 2023. While the implications of this connection remain shrouded in ambiguity, our findings provoke intriguing thoughts about the curious interplay of digital entertainment and telecommunications in the modern era. This paper serves as a testament to the captivating and often unexpected observations that can be gleaned from the convergence of data analytics and market dynamics.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the realm of financial analysis, uncovering unusual and seemingly nonsensical relationships between market phenomena has been a pursuit both revered and ridiculed by many. In this paper, we present our investigation into the perplexing connection between the search interest in the virtual paradise of 'Roblox' and the stock price movements of T-Mobile Us (TMUS). At first glance, one might scoff at the idea of any meaningful correlation between a digital playground for creative youth and a telecommunications giant. However, as data scientists, we have learned not to dismiss any possibility, no matter how whimsical it may seem.
The advent of digital advances and the proliferation of online platforms have brought with them a new frontier for analysis – that of the intersection between virtual experiences and market behavior. The realm of ‘Roblox,’ a universe where players can construct their own games and immerse themselves in a sea of virtual creativity, has permeated popular culture with an almost infectious ubiquity. Meanwhile, T-Mobile Us has carved a distinctive niche in the telecommunications industry with its unorthodox branding and magenta-clad persona. But what, one might ask, could enmesh these apparently disparate entities?
Our exploration into this unexpected relationship was not without its challenges and doubters. Many colleagues raised their eyebrows at our endeavor, some even suggesting that we had embarked on a fool’s errand. Nonetheless, armed with an insatiable curiosity and a compendium of statistical tools, we pressed onward. Utilizing the riches of Google Trends data and the robust market analytics of LSEG Analytics (Refinitiv), we endeavored to unravel the mystery that lay before us, undeterred by the perplexing nature of our topic.
In the following sections, we present our findings, which have raised more questions than answers and prompted us to reconsider the boundaries of traditional market analysis. It is our hope that this study, despite its unconventional premise, will shed light on the unexpected connections that can arise within the labyrinthine realms of modern data analysis and financial markets. For as we shall see, the world of data analytics can often be stranger than fiction, and the most fantastical relationships can yield impactful insights.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In their study, Smith and Jones (2015) explore the relationship between online search trends for digital entertainment and the stock performance of companies in the telecommunications industry. Their findings suggest that there may be unexpected connections between seemingly unrelated consumer behavior and market dynamics. Similarly, Doe and Johnson (2018) delve into the impact of virtual gaming platforms on digital economy, demonstrating the potential for unanticipated implications on stock prices of companies operating in the technology and communication sectors.

Moving beyond the conventional studies, our investigation delves into an uncharted territory where the virtual meets the financial. As we navigate through the literature landscape, we encounter non-fiction works such as "The Age of Surveillance Capitalism" by Shoshana Zuboff and "The Box: How the Shipping Container Made the World Smaller and the World Economy Bigger" by Marc Levinson, reflecting on the intersection of digital innovation and economic impact.

However, the realm of Roblox and stock prices leads us to fictional narratives with titles like "Ready Player One" by Ernest Cline and "Neuromancer" by William Gibson, where the integration of virtual realms and market forces extends into alternate realities. These literary works, while not academic in nature, provide a conceptual backdrop for the unpredictable interplay between virtual engagement and financial outcomes.

Nevertheless, in our pursuit of comprehensiveness, we did not limit ourselves to traditional sources. We expanded our horizon to unlikely realms, including the back covers of shampoo bottles, hoping to gain insight from the most unconventional sources. Though the yield of financial wisdom from such endeavors may be considered questionable at best, it did provide some unexpectedly entertaining reading material during the course of our research.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 Google searches for 'roblox' and T-Mobile Us' stock price (TMUS). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Google Trends and LSEG Analytics (Refinitiv) . You used data from 2008 to 2023

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]]
Unlocking the Connection: Investigating the Relationship Between Google Searches for 'Roblox' and T-Mobile Us' Stock Price

[[ABSTRACT]]
This study delves into the peculiar connection between two seemingly unrelated phenomena: Google searches for the popular online game 'Roblox', and the stock price of T-Mobile Us (TMUS). Using data from Google Trends and LSEG Analytics (Refinitiv), we sought to unlock the mystery behind this enigmatic relationship. Our research team uncovered a remarkably high correlation coefficient of 0.9674306 and a statistically significant p-value of less than 0.01 for the period spanning from 2008 to 2023. While the implications of this connection remain shrouded in ambiguity, our findings provoke intriguing thoughts about the curious interplay of digital entertainment and telecommunications in the modern era. This paper serves as a testament to the captivating and often unexpected observations that can be gleaned from the convergence of data analytics and market dynamics.

[[INTRODUCTION]]
In the realm of financial analysis, uncovering unusual and seemingly nonsensical relationships between market phenomena has been a pursuit both revered and ridiculed by many. In this paper, we present our investigation into the perplexing connection between the search interest in the virtual paradise of 'Roblox' and the stock price movements of T-Mobile Us (TMUS). At first glance, one might scoff at the idea of any meaningful correlation between a digital playground for creative youth and a telecommunications giant. However, as data scientists, we have learned not to dismiss any possibility, no matter how whimsical it may seem.
The advent of digital advances and the proliferation of online platforms have brought with them a new frontier for analysis – that of the intersection between virtual experiences and market behavior. The realm of ‘Roblox,’ a universe where players can construct their own games and immerse themselves in a sea of virtual creativity, has permeated popular culture with an almost infectious ubiquity. Meanwhile, T-Mobile Us has carved a distinctive niche in the telecommunications industry with its unorthodox branding and magenta-clad persona. But what, one might ask, could enmesh these apparently disparate entities?
Our exploration into this unexpected relationship was not without its challenges and doubters. Many colleagues raised their eyebrows at our endeavor, some even suggesting that we had embarked on a fool’s errand. Nonetheless, armed with an insatiable curiosity and a compendium of statistical tools, we pressed onward. Utilizing the riches of Google Trends data and the robust market analytics of LSEG Analytics (Refinitiv), we endeavored to unravel the mystery that lay before us, undeterred by the perplexing nature of our topic.
In the following sections, we present our findings, which have raised more questions than answers and prompted us to reconsider the boundaries of traditional market analysis. It is our hope that this study, despite its unconventional premise, will shed light on the unexpected connections that can arise within the labyrinthine realms of modern data analysis and financial markets. For as we shall see, the world of data analytics can often be stranger than fiction, and the most fantastical relationships can yield impactful insights.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To embark on our quixotic quest of uncovering the clandestine connection between Google searches for 'Roblox' and T-Mobile Us' stock price, we employed a plethora of analytical methods and data sources. Our journey began with the extraction of Google search data for the term 'Roblox' from the fathomless depths of Google Trends. This primary data source provided us with a glimpse into the ebb and flow of public fascination with the virtual realm of 'Roblox' over the course of 2008 to 2023. The volume of 'Roblox' searches was our navigator through the murky waters of digital trends, guiding us toward the shores of statistical enlightenment.

In parallel, we turned to the towering citadel of LSEG Analytics (Refinitiv), harnessing its formidable resources to chart the undulating landscape of T-Mobile Us' stock price over the same temporal expanse. This bestowed upon us the means to scrutinize the capricious undulations of the market's perception of T-Mobile Us, as though observing the enigmatic dance of the stock price amidst the tempestuous sea of investor sentiment.

With these two datasets in hand, we embarked on our arduous labor of love in the realm of statistical analysis. Our tool of choice, the venerable Pearson correlation coefficient, served as our compass, guiding us through the uncharted territories of data examination. As we meticulously calculated the correlation coefficient between 'Roblox' searches and T-Mobile Us' stock price, each data point became akin to a line in an intricate web, weaving a tapestry of inexplicable interconnectedness.

Our statistical odyssey did not culminate with a mere correlation coefficient, however; it required the felling of the formidable p-value, a seemingly unyielding barrier guarding the gates of statistical significance. With collective fortitude, we breached this threshold and arrived at a p-value of less than 0.01, solidifying the significance of the unearthed correlation. This was a triumph akin to discovering a hidden treasure chest, filled not with gold doubloons, but with statistical validation and a sense of vindication.

Armed with the insights derived from Google Trends and LSEG Analytics (Refinitiv), and fortified by the statistical rigor of correlation and p-value analysis, we emerged from the labyrinth of data, bearing a newfound appreciation for the unexpected and the comically convoluted. These gallant efforts laid the foundation for our elucidation of the confounding relationship between 'Roblox' searches and T-Mobile Us' stock price, marking the culmination of our intrepid foray into the realm of whimsical data analysis.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 Google searches for 'roblox' and T-Mobile Us' stock price (TMUS). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Google Trends and LSEG Analytics (Refinitiv) .

For the time period 2008 to 2023, you found a correlation 0.9674306, r-squared of 0.9359219, 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]]
Unlocking the Connection: Investigating the Relationship Between Google Searches for 'Roblox' and T-Mobile Us' Stock Price

[[ABSTRACT]]
This study delves into the peculiar connection between two seemingly unrelated phenomena: Google searches for the popular online game 'Roblox', and the stock price of T-Mobile Us (TMUS). Using data from Google Trends and LSEG Analytics (Refinitiv), we sought to unlock the mystery behind this enigmatic relationship. Our research team uncovered a remarkably high correlation coefficient of 0.9674306 and a statistically significant p-value of less than 0.01 for the period spanning from 2008 to 2023. While the implications of this connection remain shrouded in ambiguity, our findings provoke intriguing thoughts about the curious interplay of digital entertainment and telecommunications in the modern era. This paper serves as a testament to the captivating and often unexpected observations that can be gleaned from the convergence of data analytics and market dynamics.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the realm of financial analysis, uncovering unusual and seemingly nonsensical relationships between market phenomena has been a pursuit both revered and ridiculed by many. In this paper, we present our investigation into the perplexing connection between the search interest in the virtual paradise of 'Roblox' and the stock price movements of T-Mobile Us (TMUS). At first glance, one might scoff at the idea of any meaningful correlation between a digital playground for creative youth and a telecommunications giant. However, as data scientists, we have learned not to dismiss any possibility, no matter how whimsical it may seem.
The advent of digital advances and the proliferation of online platforms have brought with them a new frontier for analysis – that of the intersection between virtual experiences and market behavior. The realm of ‘Roblox,’ a universe where players can construct their own games and immerse themselves in a sea of virtual creativity, has permeated popular culture with an almost infectious ubiquity. Meanwhile, T-Mobile Us has carved a distinctive niche in the telecommunications industry with its unorthodox branding and magenta-clad persona. But what, one might ask, could enmesh these apparently disparate entities?
Our exploration into this unexpected relationship was not without its challenges and doubters. Many colleagues raised their eyebrows at our endeavor, some even suggesting that we had embarked on a fool’s errand. Nonetheless, armed with an insatiable curiosity and a compendium of statistical tools, we pressed onward. Utilizing the riches of Google Trends data and the robust market analytics of LSEG Analytics (Refinitiv), we endeavored to unravel the mystery that lay before us, undeterred by the perplexing nature of our topic.
In the following sections, we present our findings, which have raised more questions than answers and prompted us to reconsider the boundaries of traditional market analysis. It is our hope that this study, despite its unconventional premise, will shed light on the unexpected connections that can arise within the labyrinthine realms of modern data analysis and financial markets. For as we shall see, the world of data analytics can often be stranger than fiction, and the most fantastical relationships can yield impactful insights.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

After conducting an exhaustive analysis of the data collected from 2008 to 2023, our research team unearthed a strikingly high correlation between Google searches for 'Roblox' and the stock price of T-Mobile Us (TMUS). The correlation coefficient between these two seemingly unrelated variables was calculated to be 0.9674306. In other words, the relationship between the two can be described as tighter than a pair of skinny jeans on a hipster at a coffee shop.

Additionally, our analysis yielded an r-squared value of 0.9359219, indicating that a whopping 93.59% of the variance in TMUS stock price can be explained by the fluctuations in the search interest for 'Roblox'. This handsomely high r-squared value further underscores the undeniable link between these two disparate entities.

Furthermore, our statistical tests revealed a p-value of less than 0.01, signifying a level of statistical significance that even the snootiest of statisticians couldn't scoff at. This means the likelihood of the observed correlation occurring by chance is about as rare as spotting a unicorn in the wild.

Fig. 1 visualizes this formidable correlation in all its glory, showcasing a scatterplot that graphically illustrates the robust relationship between the search interest for 'Roblox' and the stock price of T-Mobile Us. Admire it not just for its scientific value but also for its sheer aesthetic prowess. Just like a delightful piece of art, this plot captures the essence of an unexpected and captivating relationship between virtual entertainment and corporate market dynamics.

In conclusion, our findings not only provide empirical evidence of the connection between 'Roblox' searches and TMUS stock price but also prompt contemplation on the whimsical interplay of digital entertainment and telecommunications in the modern age. The results of this study serve as a testament to the intriguing and often surprising discoveries that can emerge from the amalgamation of data analytics and market behavior. The next time someone doubts the value of analyzing random market correlations, we can confidently point to this curious connection and say, "Believe it or not, it's statistically significant!"

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Google searches for 'roblox' and T-Mobile Us' stock price (TMUS). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
Unlocking the Connection: Investigating the Relationship Between Google Searches for 'Roblox' and T-Mobile Us' Stock Price

[[ABSTRACT]]
This study delves into the peculiar connection between two seemingly unrelated phenomena: Google searches for the popular online game 'Roblox', and the stock price of T-Mobile Us (TMUS). Using data from Google Trends and LSEG Analytics (Refinitiv), we sought to unlock the mystery behind this enigmatic relationship. Our research team uncovered a remarkably high correlation coefficient of 0.9674306 and a statistically significant p-value of less than 0.01 for the period spanning from 2008 to 2023. While the implications of this connection remain shrouded in ambiguity, our findings provoke intriguing thoughts about the curious interplay of digital entertainment and telecommunications in the modern era. This paper serves as a testament to the captivating and often unexpected observations that can be gleaned from the convergence of data analytics and market dynamics.

[[LITERATURE REVIEW]]
In their study, Smith and Jones (2015) explore the relationship between online search trends for digital entertainment and the stock performance of companies in the telecommunications industry. Their findings suggest that there may be unexpected connections between seemingly unrelated consumer behavior and market dynamics. Similarly, Doe and Johnson (2018) delve into the impact of virtual gaming platforms on digital economy, demonstrating the potential for unanticipated implications on stock prices of companies operating in the technology and communication sectors.
Moving beyond the conventional studies, our investigation delves into an uncharted territory where the virtual meets the financial. As we navigate through the literature landscape, we encounter non-fiction works such as "The Age of Surveillance Capitalism" by Shoshana Zuboff and "The Box: How the Shipping Container Made the World Smaller and the World Economy Bigger" by Marc Levinson, reflecting on the intersection of digital innovation and economic impact.
However, the realm of Roblox and stock prices leads us to fictional narratives with titles like "Ready Player One" by Ernest Cline and "Neuromancer" by William Gibson, where the integration of virtual realms and market forces extends into alternate realities. These literary works, while not academic in nature, provide a conceptual backdrop for the unpredictable interplay between virtual engagement and financial outcomes.
Nevertheless, in our pursuit of comprehensiveness, we did not limit ourselves to traditional sources. We expanded our horizon to unlikely realms, including the back covers of shampoo bottles, hoping to gain insight from the most unconventional sources. Though the yield of financial wisdom from such endeavors may be considered questionable at best, it did provide some unexpectedly entertaining reading material during the course of our research.

[[RESULTS]]
After conducting an exhaustive analysis of the data collected from 2008 to 2023, our research team unearthed a strikingly high correlation between Google searches for 'Roblox' and the stock price of T-Mobile Us (TMUS). The correlation coefficient between these two seemingly unrelated variables was calculated to be 0.9674306. In other words, the relationship between the two can be described as tighter than a pair of skinny jeans on a hipster at a coffee shop.
Additionally, our analysis yielded an r-squared value of 0.9359219, indicating that a whopping 93.59% of the variance in TMUS stock price can be explained by the fluctuations in the search interest for 'Roblox'. This handsomely high r-squared value further underscores the undeniable link between these two disparate entities.
Furthermore, our statistical tests revealed a p-value of less than 0.01, signifying a level of statistical significance that even the snootiest of statisticians couldn't scoff at. This means the likelihood of the observed correlation occurring by chance is about as rare as spotting a unicorn in the wild.
Fig. 1 visualizes this formidable correlation in all its glory, showcasing a scatterplot that graphically illustrates the robust relationship between the search interest for 'Roblox' and the stock price of T-Mobile Us. Admire it not just for its scientific value but also for its sheer aesthetic prowess. Just like a delightful piece of art, this plot captures the essence of an unexpected and captivating relationship between virtual entertainment and corporate market dynamics.
In conclusion, our findings not only provide empirical evidence of the connection between 'Roblox' searches and TMUS stock price but also prompt contemplation on the whimsical interplay of digital entertainment and telecommunications in the modern age. The results of this study serve as a testament to the intriguing and often surprising discoveries that can emerge from the amalgamation of data analytics and market behavior. The next time someone doubts the value of analyzing random market correlations, we can confidently point to this curious connection and say, "Believe it or not, it's statistically significant!"

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study affirm the curious conjectures put forth by Smith and Jones (2015) and Doe and Johnson (2018), who hinted at the potential interplay between online entertainment trends and stock performance in the telecommunications sector. Our findings not only confirm their suspicions but also elevate the seemingly whimsical relationship between 'Roblox' searches and TMUS stock price to a level of statistical significance previously unmatched. It's like finding a diamond the size of a watermelon in a pile of coal—unexpected, but undeniably significant.

The literature review, in its exhaustive exploration, referenced works like "Ready Player One" by Ernest Cline and "Neuromancer" by William Gibson, underscoring the narrative backdrop for our findings and affirming the surreal nature of this connection. These literary references, though seemingly far-fetched, surprisingly align with the underlying essence of our empirical observations. It's as if fiction and reality have collided in a game of financial charades, where 'Roblox' and stock prices engage in an unanticipated dance of correlation.

Furthermore, while traditional sources often form the backbone of scholarly inquiry, our foray into the back covers of shampoo bottles yielded unexpected, yet oddly insightful, musings. It's a testament to the unconventional paths that can lead to understanding, akin to stumbling upon a treasure map within a cracker jack box. In the same vein, our study has uncovered a treasure trove of information hidden within the search trends for 'Roblox', shining a light on the untrodden path of virtual realms and financial markets.

The robust correlation coefficient and the commanding r-squared value unveiled in our results substantiate the undeniable link between 'Roblox' searches and TMUS stock price. If statistical significance had a mascot, it would likely resemble a unicorn prancing amidst a statistical forest, symbolizing the rarity and enchantment of our findings. Much like the unexpected discovery of a four-leaf clover on the path less traveled, our study stands as a testament to the serendipitous nature of academic inquiry.

In light of our results, it's tempting to envision the financial markets as a virtual gaming arena, where the actions of digital denizens reverberate through the stock tickers, creating a symphony of market movements. Perhaps, in the arcane language of market analytics, 'Roblox' searches communicate a narrative that resonates with T-Mobile Us, akin to a secret handshake exchanged between disparate realms. We cannot help but marvel at the whimsy and wonder of this connection, much like stumbling upon a leprechaun's pot of gold at the end of a rainbow.

In conclusion, our study not only sheds light on the unexpected connection between 'Roblox' searches and TMUS stock price, but also hints at the intriguing potential for uncharted synergies between digital entertainment and telecommunications in the modern era. As we contemplate the implications of this connection, we find ourselves embarking on a journey akin to Alice falling down the rabbit hole—enchanting, unpredictable, and above all, endlessly compelling.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Google searches for 'roblox' and T-Mobile Us' stock price (TMUS). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Unlocking the Connection: Investigating the Relationship Between Google Searches for 'Roblox' and T-Mobile Us' Stock Price

[[ABSTRACT]]
This study delves into the peculiar connection between two seemingly unrelated phenomena: Google searches for the popular online game 'Roblox', and the stock price of T-Mobile Us (TMUS). Using data from Google Trends and LSEG Analytics (Refinitiv), we sought to unlock the mystery behind this enigmatic relationship. Our research team uncovered a remarkably high correlation coefficient of 0.9674306 and a statistically significant p-value of less than 0.01 for the period spanning from 2008 to 2023. While the implications of this connection remain shrouded in ambiguity, our findings provoke intriguing thoughts about the curious interplay of digital entertainment and telecommunications in the modern era. This paper serves as a testament to the captivating and often unexpected observations that can be gleaned from the convergence of data analytics and market dynamics.

[[INTRDUCTION]]
In the realm of financial analysis, uncovering unusual and seemingly nonsensical relationships between market phenomena has been a pursuit both revered and ridiculed by many. In this paper, we present our investigation into the perplexing connection between the search interest in the virtual paradise of 'Roblox' and the stock price movements of T-Mobile Us (TMUS). At first glance, one might scoff at the idea of any meaningful correlation between a digital playground for creative youth and a telecommunications giant. However, as data scientists, we have learned not to dismiss any possibility, no matter how whimsical it may seem.
The advent of digital advances and the proliferation of online platforms have brought with them a new frontier for analysis – that of the intersection between virtual experiences and market behavior. The realm of ‘Roblox,’ a universe where players can construct their own games and immerse themselves in a sea of virtual creativity, has permeated popular culture with an almost infectious ubiquity. Meanwhile, T-Mobile Us has carved a distinctive niche in the telecommunications industry with its unorthodox branding and magenta-clad persona. But what, one might ask, could enmesh these apparently disparate entities?
Our exploration into this unexpected relationship was not without its challenges and doubters. Many colleagues raised their eyebrows at our endeavor, some even suggesting that we had embarked on a fool’s errand. Nonetheless, armed with an insatiable curiosity and a compendium of statistical tools, we pressed onward. Utilizing the riches of Google Trends data and the robust market analytics of LSEG Analytics (Refinitiv), we endeavored to unravel the mystery that lay before us, undeterred by the perplexing nature of our topic.
In the following sections, we present our findings, which have raised more questions than answers and prompted us to reconsider the boundaries of traditional market analysis. It is our hope that this study, despite its unconventional premise, will shed light on the unexpected connections that can arise within the labyrinthine realms of modern data analysis and financial markets. For as we shall see, the world of data analytics can often be stranger than fiction, and the most fantastical relationships can yield impactful insights.

[[RESULTS]]
After conducting an exhaustive analysis of the data collected from 2008 to 2023, our research team unearthed a strikingly high correlation between Google searches for 'Roblox' and the stock price of T-Mobile Us (TMUS). The correlation coefficient between these two seemingly unrelated variables was calculated to be 0.9674306. In other words, the relationship between the two can be described as tighter than a pair of skinny jeans on a hipster at a coffee shop.
Additionally, our analysis yielded an r-squared value of 0.9359219, indicating that a whopping 93.59% of the variance in TMUS stock price can be explained by the fluctuations in the search interest for 'Roblox'. This handsomely high r-squared value further underscores the undeniable link between these two disparate entities.
Furthermore, our statistical tests revealed a p-value of less than 0.01, signifying a level of statistical significance that even the snootiest of statisticians couldn't scoff at. This means the likelihood of the observed correlation occurring by chance is about as rare as spotting a unicorn in the wild.
Fig. 1 visualizes this formidable correlation in all its glory, showcasing a scatterplot that graphically illustrates the robust relationship between the search interest for 'Roblox' and the stock price of T-Mobile Us. Admire it not just for its scientific value but also for its sheer aesthetic prowess. Just like a delightful piece of art, this plot captures the essence of an unexpected and captivating relationship between virtual entertainment and corporate market dynamics.
In conclusion, our findings not only provide empirical evidence of the connection between 'Roblox' searches and TMUS stock price but also prompt contemplation on the whimsical interplay of digital entertainment and telecommunications in the modern age. The results of this study serve as a testament to the intriguing and often surprising discoveries that can emerge from the amalgamation of data analytics and market behavior. The next time someone doubts the value of analyzing random market correlations, we can confidently point to this curious connection and say, "Believe it or not, it's statistically significant!"

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research uncovers a remarkably robust and statistically significant correlation between Google searches for 'Roblox' and the stock price of T-Mobile Us (TMUS). The findings highlight a connection so strong, it's as if they're holding hands at a virtual theme park. The proverbial needle in the haystack, our study emphasizes the enchanting and unexpected bond between digital entertainment and corporate market dynamics. As we close this chapter, we urge the scholarly community to embrace the whimsical and the unusual in their analytical pursuits. After all, in the vast landscape of data analytics and market behavior, the most unlikely relationships can yield illuminating insights. With that said, further research in this area is about as necessary as an umbrella in a submarine - unnecessary!

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 Unlocking the Connection: Investigating the Relationship Between Google Searches for 'Roblox' and T-Mobile Us' Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Digital Diversions

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 Unlocking the Connection: Investigating the Relationship Between Google Searches for 'Roblox' and T-Mobile Us' Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Digital Entertainment Research and Analysis

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 Unlocking the Connection: Investigating the Relationship Between Google Searches for 'Roblox' and T-Mobile Us' Stock Price with an abstract of This study delves into the peculiar connection between two seemingly unrelated phenomena: Google searches for the popular online game 'Roblox', and the stock price of T-Mobile Us (TMUS). Using data from Google Trends and LSEG Analytics (Refinitiv), we sought to unlock the mystery behind this enigmatic relationship. Our research team uncovered a remarkably high correlation coefficient of 0.9674306 and a statistically significant p-value of less than 0.01 for the period spanning from 2008 to 2023. While the implications of this connection remain shrouded in ambiguity, our findings provoke intriguing thoughts about the curious interplay of digital entertainment and telecommunications in the modern era. This paper serves as a testament to the captivating and often unexpected observations that can be gleaned from the convergence of data analytics and market dynamics.

ChatGPT:

'Roblox' Google searches, T-Mobile US stock price, correlation analysis, Google Trends data, LSEG Analytics, Refinitiv, digital entertainment, telecommunications, data analytics, market dynamics, correlation coefficient, statistical significance

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

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Data details

Google searches for 'roblox'
Detailed data title: Relative volume of Google searches for 'roblox' (Worldwide, without quotes)
Source: Google Trends
Additional Info: ^{See full details} Relative search volume (not absolute numbers)

See what else correlates with Google searches for 'roblox'

T-Mobile Us' stock price (TMUS)
Detailed data title: Opening price of T-Mobile US (TMUS) 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 T-Mobile Us' stock price (TMUS)

Correlation r = 0.9674306 (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 = 0.9359219 (Coefficient of determination)
This means 93.6% of the change in the one variable (i.e., T-Mobile Us' stock price (TMUS)) is predictable based on the change in the other (i.e., Google searches for 'roblox') over the 16 years from 2008 through 2023.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 9.6E-10.^Show 0.0000000009563893250837460000
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 9.6E-8% of random cases. Said differently, if you correlated 1,045,599,291 random variables^Note You don't actually need 1 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 15 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 15 because we have two variables measured over a period of 16 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.

[ 0.91, 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.

	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022	2023
Google searches for 'roblox' (Rel. search volume)	1.14286	2.66667	3.58333	4.33333	5.33333	6.83333	7.41667	8.5	16.9167	31.25	39.6667	41	63.0833	80.75	82.8333	82
T-Mobile Us' stock price (TMUS) (Stock price)	39.22	29.86	15.48	25.52	17.82	20	33.03	27.1	38.86	58.1	63.9	62.87	78.88	134.3	115.76	139

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([1.14286,2.66667,3.58333,4.33333,5.33333,6.83333,7.41667,8.5,16.9167,31.25,39.6667,41,63.0833,80.75,82.8333,82,])
array_2 = np.array([39.22,29.86,15.48,25.52,17.82,20,33.03,27.1,38.86,58.1,63.9,62.87,78.88,134.3,115.76,139,])
array_1_name = "Google searches for 'roblox'"
array_2_name = "T-Mobile Us' stock price (TMUS)"

# 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 Google searches for 'roblox'
Line chart for only T-Mobile Us' stock price (TMUS)
AI-generated correlation image
The spurious research paper: Unlocking the Connection: Investigating the Relationship Between Google Searches for 'Roblox' and T-Mobile Us' Stock Price

View another random correlation

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Correlation ID: 3609 · Black Variable ID: 1470 · Red Variable ID: 1586


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