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AI explanation
As the number of breweries in the United States increased, so did the demand for artisanal coasters. This unexpected surge in coaster sales led to higher than projected revenue for Salesforce, causing their stock price to jump.Model: dalle-3
Prompt: Generate an image inspired by a TIME magazine cover, showcasing a futuristic cityscape filled with modern skyscrapers. Each building represents a different brewery, distinguishing itself with unique architecture and signage. The evening sky is illuminated by the glowing digital ticker displaying the current stock price of Salesforce, dominating the skyline with its bright numbers. The scene captures the bustling energy of a city's beer industry and the ever-present influence of the stock market. 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: The number of Breweries in the United States and Salesforce's stock price. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Vaporwave Cyber folk Surrealism A TIME magazine cover image Charcoal
ChatGPT: A TIME magazine cover image
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 The number of Breweries in the United States and Salesforce's stock price together. Keep the description simple.
ChatGPT: In a bustling cityscape, a row of modern buildings represents the number of breweries in the United States, with each building housing a different brewery. Above the skyline, a digital ticker displays Salesforce's stock price, its numbers glowing brightly against the evening sky.
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: [ A TIME magazine cover image ] and depicting this scene: In a bustling cityscape, a row of modern buildings represents the number of breweries in the United States, with each building housing a different brewery. Above the skyline, a digital ticker displays Salesforce's stock price, its numbers glowing brightly against the evening sky. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image inspired by a TIME magazine cover, showcasing a futuristic cityscape filled with modern skyscrapers. Each building represents a different brewery, distinguishing itself with unique architecture and signage. The evening sky is illuminated by the glowing digital ticker displaying the current stock price of Salesforce, dominating the skyline with its bright numbers. The scene captures the bustling energy of a city's beer industry and the ever-present influence of the stock market.
*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.
I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in The number of Breweries in the United States caused Salesforce's stock price (CRM) to increase.
AI academic paper
Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price The Journal of Fermentation Finance Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between The number of Breweries in the United States 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.
Include a pun in the title.
Your research team used data from Brewers Association and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9349908 and p < 0.01 for 2005 to 2022.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price
[[ABSTRACT]]
This research paper investigates the hopped-up relationship between the number of breweries in the United States and the stock price of Salesforce (CRM). Using data from the Brewers Association and LSEG Analytics (Refinitiv), our study covers the period spanning from 2005 to 2022. Through rigorous statistical analysis, we determined a robust correlation coefficient of 0.9349908 with a statistically significant p-value of less than 0.01. The findings unveil a noteworthy link between the burgeoning craft beer industry and the fluctuations in Salesforce's stock price. Stay tuned as we tap into the frothy details and uncover the malt-titude of factors at play in this unexpectedly refreshing correlation.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States 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. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Here is the title and abstract of the paper:
[[TITLE]]
Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price
[[ABSTRACT]]
This research paper investigates the hopped-up relationship between the number of breweries in the United States and the stock price of Salesforce (CRM). Using data from the Brewers Association and LSEG Analytics (Refinitiv), our study covers the period spanning from 2005 to 2022. Through rigorous statistical analysis, we determined a robust correlation coefficient of 0.9349908 with a statistically significant p-value of less than 0.01. The findings unveil a noteworthy link between the burgeoning craft beer industry and the fluctuations in Salesforce's stock price. Stay tuned as we tap into the frothy details and uncover the malt-titude of factors at play in this unexpectedly refreshing correlation.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
The unquenchable thirst for knowledge often drives researchers to explore unexpected correlations and connections, just like chasing the perfect blend of hops and malt to create the ideal craft beer. In this spirit of exploration, we delve into the frothy world of breweries and the financial domain, seeking to uncover the surprising interplay between the number of breweries in the United States and the stock price of Salesforce (CRM). This research seeks to tap into the intricacies of this relationship, frothy with possibilities, and offer a refreshing blend of statistical analysis, market trends, and a dash of humor.
Craft beer enthusiasts may liken the meticulous process of brewing to the precision of statistical analysis - both requiring careful measurement, a keen eye for detail, and a sprinkle of creativity. Similarly, navigating the stock market demands a balancing act akin to the delicate art of brewing, blending different flavors and personalities to produce a successful outcome. These parallels serve as a flavorful backdrop against which we aim to uncork the surprising correlations and relationships that intertwine the two seemingly disparate realms.
In a world where data is brewed and distilled into actionable insights, we bring a comprehensive analysis spanning from 2005 to 2022, meticulously concocted using information from the Brewers Association and LSEG Analytics (Refinitiv). Like a brewmaster fine-tuning a recipe, we meticulously craft this study to bring forth a robust correlation coefficient of 0.9349908 and a statistically significant p-value of less than 0.01, demonstrating a strong link between the number of breweries and Salesforce's stock performance. As we tap into this tantalizing convergence of craft beer and financial markets, we invite readers to savor the complex bouquet of statistical data and market dynamics that blend together to create this unexpectedly effervescent correlation. Stay tuned as we embark on this adventuresome quest, trying to balance the gravity of the research with the lightheartedness of a well-crafted pun. Cheers to the unexpected, and may this research be as refreshing as a perfectly chilled pint of ale on a hot summer day!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States 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 name a few real TV shows that sound like they might be relevant to the topic that you watched as research.
Here is the title and abstract of the paper:
[[TITLE]]
Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price
[[ABSTRACT]]
This research paper investigates the hopped-up relationship between the number of breweries in the United States and the stock price of Salesforce (CRM). Using data from the Brewers Association and LSEG Analytics (Refinitiv), our study covers the period spanning from 2005 to 2022. Through rigorous statistical analysis, we determined a robust correlation coefficient of 0.9349908 with a statistically significant p-value of less than 0.01. The findings unveil a noteworthy link between the burgeoning craft beer industry and the fluctuations in Salesforce's stock price. Stay tuned as we tap into the frothy details and uncover the malt-titude of factors at play in this unexpectedly refreshing correlation.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The unquenchable thirst for knowledge often drives researchers to explore unexpected correlations and connections, just like chasing the perfect blend of hops and malt to create the ideal craft beer. In this spirit of exploration, we delve into the frothy world of breweries and the financial domain, seeking to uncover the surprising interplay between the number of breweries in the United States and the stock price of Salesforce (CRM). This research seeks to tap into the intricacies of this relationship, frothy with possibilities, and offer a refreshing blend of statistical analysis, market trends, and a dash of humor.
Craft beer enthusiasts may liken the meticulous process of brewing to the precision of statistical analysis - both requiring careful measurement, a keen eye for detail, and a sprinkle of creativity. Similarly, navigating the stock market demands a balancing act akin to the delicate art of brewing, blending different flavors and personalities to produce a successful outcome. These parallels serve as a flavorful backdrop against which we aim to uncork the surprising correlations and relationships that intertwine the two seemingly disparate realms.
In a world where data is brewed and distilled into actionable insights, we bring a comprehensive analysis spanning from 2005 to 2022, meticulously concocted using information from the Brewers Association and LSEG Analytics (Refinitiv). Like a brewmaster fine-tuning a recipe, we meticulously craft this study to bring forth a robust correlation coefficient of 0.9349908 and a statistically significant p-value of less than 0.01, demonstrating a strong link between the number of breweries and Salesforce's stock performance. As we tap into this tantalizing convergence of craft beer and financial markets, we invite readers to savor the complex bouquet of statistical data and market dynamics that blend together to create this unexpectedly effervescent correlation. Stay tuned as we embark on this adventuresome quest, trying to balance the gravity of the research with the lightheartedness of a well-crafted pun. Cheers to the unexpected, and may this research be as refreshing as a perfectly chilled pint of ale on a hot summer day!
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The connection between the number of breweries in the United States and the stock price of Salesforce (CRM) has not been well-explored in academic literature, prompting our thirst for further investigation. Smith et al. (2016) delved into the financial implications of the craft beer industry, but their focus was primarily on market valuation rather than examining specific correlations with individual stock prices. Similarly, Doe and Jones (2019) discussed the burgeoning nature of microbreweries in the US, yet their analysis did not extend to the impact on specific companies within the tech sector.
Moving further afield, "The Economics of Beer" by Swinnen and Briskin (2011) provides a comprehensive overview of the economic forces at play in the brewing industry. Although this work offers valuable insights into the market dynamics of brewing, it fails to draw a direct parallel to the performance of technology stocks. In a more fictional vein, "Brew Ha Ha! The Craft Beer Board Game" by Spiral Galaxy Games (2018) takes a playful approach to simulating the brewery business, but its findings are limited to the realm of gaming rather than financial analysis.
As the search for relevant insights delves into unexpected realms, TV shows such as "Brew Dogs" and "Punk’d Brewery" have been explored to gain a deeper understanding of the brewery culture and its potential impacts on the broader market. While these shows may not offer direct financial data, the quirky ambiance and creative energy of the craft beer scene provide an offbeat backdrop from which to approach our investigation. Cheers to the unexpected connections, and humorously named breweries, as we froth up the academia with our un-beer-lievably unique approach to stock market analysis. Here’s to tap into the world of hop-portunities!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States 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. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Your research team collected data from all across the internet, but mostly just used information from Brewers Association 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]]
Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price
[[ABSTRACT]]
This research paper investigates the hopped-up relationship between the number of breweries in the United States and the stock price of Salesforce (CRM). Using data from the Brewers Association and LSEG Analytics (Refinitiv), our study covers the period spanning from 2005 to 2022. Through rigorous statistical analysis, we determined a robust correlation coefficient of 0.9349908 with a statistically significant p-value of less than 0.01. The findings unveil a noteworthy link between the burgeoning craft beer industry and the fluctuations in Salesforce's stock price. Stay tuned as we tap into the frothy details and uncover the malt-titude of factors at play in this unexpectedly refreshing correlation.
[[INTRODUCTION]]
The unquenchable thirst for knowledge often drives researchers to explore unexpected correlations and connections, just like chasing the perfect blend of hops and malt to create the ideal craft beer. In this spirit of exploration, we delve into the frothy world of breweries and the financial domain, seeking to uncover the surprising interplay between the number of breweries in the United States and the stock price of Salesforce (CRM). This research seeks to tap into the intricacies of this relationship, frothy with possibilities, and offer a refreshing blend of statistical analysis, market trends, and a dash of humor.
Craft beer enthusiasts may liken the meticulous process of brewing to the precision of statistical analysis - both requiring careful measurement, a keen eye for detail, and a sprinkle of creativity. Similarly, navigating the stock market demands a balancing act akin to the delicate art of brewing, blending different flavors and personalities to produce a successful outcome. These parallels serve as a flavorful backdrop against which we aim to uncork the surprising correlations and relationships that intertwine the two seemingly disparate realms.
In a world where data is brewed and distilled into actionable insights, we bring a comprehensive analysis spanning from 2005 to 2022, meticulously concocted using information from the Brewers Association and LSEG Analytics (Refinitiv). Like a brewmaster fine-tuning a recipe, we meticulously craft this study to bring forth a robust correlation coefficient of 0.9349908 and a statistically significant p-value of less than 0.01, demonstrating a strong link between the number of breweries and Salesforce's stock performance. As we tap into this tantalizing convergence of craft beer and financial markets, we invite readers to savor the complex bouquet of statistical data and market dynamics that blend together to create this unexpectedly effervescent correlation. Stay tuned as we embark on this adventuresome quest, trying to balance the gravity of the research with the lightheartedness of a well-crafted pun. Cheers to the unexpected, and may this research be as refreshing as a perfectly chilled pint of ale on a hot summer day!
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
Our research methodology was as meticulously crafted as the most sought-after IPA, blending elements of data collection, statistical analysis, and a sprinkle of whimsy. We embarked on this frothy venture by first scouring the digital landscape, much like a dedicated brewer seeking the finest hops, to collect data on the number of breweries in the United States. The Brewers Association emerged as our main maltster, providing an extensive and comprehensive dataset that forms the backbone of our exploratory journey.
In parallel, akin to the alchemy of crafting a unique batch of beer, we tapped into the resources of LSEG Analytics (Refinitiv) to extract intricate market data relevant to Salesforce's stock price (CRM). This comprehensive approach allowed us to blend the flavors of the craft beer industry with the effervescence of stock market dynamics, sparking an unexpectedly refreshing correlation that we subsequently uncorked with statistical precision.
The timeline of our study encompassed the years 2005 to 2022, akin to allowing a particularly complex brew to mature and develop its full character. Throughout this period, we meticulously measured the fluctuations in both the number of breweries and Salesforce's stock performance, in a manner reminiscent of a vigilant brewmaster monitoring the fermenting process. The robust dataset obtained from our sources provided the prime ingredients for our statistical analysis, ensuring a balanced blend of data points and trends.
To determine the correlation between the number of breweries and Salesforce's stock price, we employed the stalwart tools of statistical analysis. Using advanced regression models, we quantified the relationship between our variables with the precision and finesse of a sommelier discerning the subtle notes of a fine wine. Our statistical toolkit, as diverse as a palette of malt varieties, included Pearson's correlation coefficient, multivariate regression, and time series analysis, resulting in a heady brew of insights poised for uncorking.
It is worth noting that our research approach retained a flavor of levity, much like the frothy head atop a well-poured pint. As we gingerly navigated the intricate pathways of statistics and market dynamics, we sprinkled in a dash of humor and wit to infuse our work with a lively essence. This lighthearted touch, akin to the zest of a citrusy ale, brought a delightful dimension to our exploration of this unexpected correlation.
In conclusion, much like blending the perfect combination of malt and hops, our methodological concoction harmoniously combined the precision of statistical analysis with the lightheartedness of a well-crafted pun, resulting in a refreshing study that invites readers to savor the complexities of this tantalizing correlation.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States 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. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Your research team collected data from all across the internet, but mostly just used information from Brewers Association and LSEG Analytics (Refinitiv) .
For the time period 2005 to 2022, you found a correlation 0.9349908, r-squared of 0.8742078, 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]]
Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price
[[ABSTRACT]]
This research paper investigates the hopped-up relationship between the number of breweries in the United States and the stock price of Salesforce (CRM). Using data from the Brewers Association and LSEG Analytics (Refinitiv), our study covers the period spanning from 2005 to 2022. Through rigorous statistical analysis, we determined a robust correlation coefficient of 0.9349908 with a statistically significant p-value of less than 0.01. The findings unveil a noteworthy link between the burgeoning craft beer industry and the fluctuations in Salesforce's stock price. Stay tuned as we tap into the frothy details and uncover the malt-titude of factors at play in this unexpectedly refreshing correlation.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
The unquenchable thirst for knowledge often drives researchers to explore unexpected correlations and connections, just like chasing the perfect blend of hops and malt to create the ideal craft beer. In this spirit of exploration, we delve into the frothy world of breweries and the financial domain, seeking to uncover the surprising interplay between the number of breweries in the United States and the stock price of Salesforce (CRM). This research seeks to tap into the intricacies of this relationship, frothy with possibilities, and offer a refreshing blend of statistical analysis, market trends, and a dash of humor.
Craft beer enthusiasts may liken the meticulous process of brewing to the precision of statistical analysis - both requiring careful measurement, a keen eye for detail, and a sprinkle of creativity. Similarly, navigating the stock market demands a balancing act akin to the delicate art of brewing, blending different flavors and personalities to produce a successful outcome. These parallels serve as a flavorful backdrop against which we aim to uncork the surprising correlations and relationships that intertwine the two seemingly disparate realms.
In a world where data is brewed and distilled into actionable insights, we bring a comprehensive analysis spanning from 2005 to 2022, meticulously concocted using information from the Brewers Association and LSEG Analytics (Refinitiv). Like a brewmaster fine-tuning a recipe, we meticulously craft this study to bring forth a robust correlation coefficient of 0.9349908 and a statistically significant p-value of less than 0.01, demonstrating a strong link between the number of breweries and Salesforce's stock performance. As we tap into this tantalizing convergence of craft beer and financial markets, we invite readers to savor the complex bouquet of statistical data and market dynamics that blend together to create this unexpectedly effervescent correlation. Stay tuned as we embark on this adventuresome quest, trying to balance the gravity of the research with the lightheartedness of a well-crafted pun. Cheers to the unexpected, and may this research be as refreshing as a perfectly chilled pint of ale on a hot summer day!
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The analysis of the relationship between the number of breweries in the United States and Salesforce's stock price (CRM) yielded a surprising and rather hoppy correlation coefficient of 0.9349908. This robust correlation was accompanied by an r-squared value of 0.8742078, indicating that approximately 87.42% of the variance in Salesforce's stock price can be explained by the number of breweries. The p-value of less than 0.01 further confirms the statistical significance of this correlation, allowing us to confidently raise a toast to the validity of our findings.
Fig. 1 depicts a scatterplot illustrating the strong positive correlation between the number of breweries and Salesforce's stock price. The data points form a pattern reminiscent of bubbles rising in a glass of finely carbonated beer, accentuating the effervescence of this unexpected relationship.
These results not only highlight the interconnectedness of seemingly unrelated industries but also underscore the importance of approaching data analysis with an open mind, much like a craft brewer experimenting with new ingredients to create a unique and palatable beer. The robustness of the correlation coefficient echoes the intricacy and depth found in a finely crafted brew, demonstrating the complexity of the relationship between these two variables.
In essence, this unexpected and refreshing correlation between the number of breweries in the United States and Salesforce's stock price opens up a frothy frontier for further exploration and analysis. As we continue to unravel the multifaceted layers of this relationship, we invite readers to join us in savoring this unexpectedly delightful blend of statistical precision, market dynamics, and perhaps a sprinkle of humor. Let's raise a glass to the serendipitous discoveries hidden within the depths of data - cheers to the unexpected!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States 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. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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]]
Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price
[[ABSTRACT]]
This research paper investigates the hopped-up relationship between the number of breweries in the United States and the stock price of Salesforce (CRM). Using data from the Brewers Association and LSEG Analytics (Refinitiv), our study covers the period spanning from 2005 to 2022. Through rigorous statistical analysis, we determined a robust correlation coefficient of 0.9349908 with a statistically significant p-value of less than 0.01. The findings unveil a noteworthy link between the burgeoning craft beer industry and the fluctuations in Salesforce's stock price. Stay tuned as we tap into the frothy details and uncover the malt-titude of factors at play in this unexpectedly refreshing correlation.
[[LITERATURE REVIEW]]
The connection between the number of breweries in the United States and the stock price of Salesforce (CRM) has not been well-explored in academic literature, prompting our thirst for further investigation. Smith et al. (2016) delved into the financial implications of the craft beer industry, but their focus was primarily on market valuation rather than examining specific correlations with individual stock prices. Similarly, Doe and Jones (2019) discussed the burgeoning nature of microbreweries in the US, yet their analysis did not extend to the impact on specific companies within the tech sector.
Moving further afield, "The Economics of Beer" by Swinnen and Briskin (2011) provides a comprehensive overview of the economic forces at play in the brewing industry. Although this work offers valuable insights into the market dynamics of brewing, it fails to draw a direct parallel to the performance of technology stocks. In a more fictional vein, "Brew Ha Ha! The Craft Beer Board Game" by Spiral Galaxy Games (2018) takes a playful approach to simulating the brewery business, but its findings are limited to the realm of gaming rather than financial analysis.
As the search for relevant insights delves into unexpected realms, TV shows such as "Brew Dogs" and "Punk’d Brewery" have been explored to gain a deeper understanding of the brewery culture and its potential impacts on the broader market. While these shows may not offer direct financial data, the quirky ambiance and creative energy of the craft beer scene provide an offbeat backdrop from which to approach our investigation. Cheers to the unexpected connections, and humorously named breweries, as we froth up the academia with our un-beer-lievably unique approach to stock market analysis. Here’s to tap into the world of hop-portunities!
[[RESULTS]]
The analysis of the relationship between the number of breweries in the United States and Salesforce's stock price (CRM) yielded a surprising and rather hoppy correlation coefficient of 0.9349908. This robust correlation was accompanied by an r-squared value of 0.8742078, indicating that approximately 87.42% of the variance in Salesforce's stock price can be explained by the number of breweries. The p-value of less than 0.01 further confirms the statistical significance of this correlation, allowing us to confidently raise a toast to the validity of our findings.
Fig. 1 depicts a scatterplot illustrating the strong positive correlation between the number of breweries and Salesforce's stock price. The data points form a pattern reminiscent of bubbles rising in a glass of finely carbonated beer, accentuating the effervescence of this unexpected relationship.
These results not only highlight the interconnectedness of seemingly unrelated industries but also underscore the importance of approaching data analysis with an open mind, much like a craft brewer experimenting with new ingredients to create a unique and palatable beer. The robustness of the correlation coefficient echoes the intricacy and depth found in a finely crafted brew, demonstrating the complexity of the relationship between these two variables.
In essence, this unexpected and refreshing correlation between the number of breweries in the United States and Salesforce's stock price opens up a frothy frontier for further exploration and analysis. As we continue to unravel the multifaceted layers of this relationship, we invite readers to join us in savoring this unexpectedly delightful blend of statistical precision, market dynamics, and perhaps a sprinkle of humor. Let's raise a glass to the serendipitous discoveries hidden within the depths of data - cheers to the unexpected!
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The frothy connection uncovered in our study defies the conventional wisdom of industry juxtapositions, inviting us to embrace the unexpected and perhaps hop onto new opportunities in statistical and market analysis. The robust correlation coefficient of 0.9349908 not only confirms the fervent linkage between the number of breweries in the United States and Salesforce's stock price, but also pours into the depths of our understanding of inter-industry dynamics. We were reminded of Swinnen and Briskin's comprehensive overview of the economic forces at play in the brewing industry - while they didn't directly forecast the hoppiness of tech stocks, our findings certainly give them a run for their money.
As we drink in the significance of this correlation, it's impossible not to consider the unconventional sources of inspiration that have propelled our research forward. The playful simulations of brewery business in "Brew Ha Ha! The Craft Beer Board Game" whisper a tantalizing possibility - could this correlation just be the tip of the iceberg, or rather the froth on a richly crafted pint of market analysis?
Moreover, the uncanny resemblance of the scatterplot to bubbles rising in a glass of carbonated beer prompts us to reflect on the effervescence of this unexpected relationship. In the words of "Brew Dogs" and "Punk’d Brewery," the brewery culture has indeed provided us with a spirited backdrop - granting a new perspective in understanding the quirky interactions between seemingly distant industries. The craft beer scene, with its offbeat ambiance and peculiarly named breweries, perhaps embodies the unpredictability and spontaneity that characterize the hidden connections in our data.
Our findings serve as a resounding testament to the intricacy of market dynamics, likening the exploration of statistical relationships to the adventurous experimentation of craft brewers. As we raise a glass to this serendipitous discovery, we echo the sentiments of those who live by the art of brewing - embracing the unexpected yet delightful blend of statistical precision, market forces, and, just maybe, a sprinkling of humor. Let's imbibe in the frothy frontier of unforeseen correlations and approach the data with the open-mindedness of a craft brewer sampling new ingredients. Here's to indulging in the nuanced layers of industry interplay and to the serendipitous discoveries hidden within the depths of data - cheers to the unexpected!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of Breweries in the United States 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. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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]]
Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price
[[ABSTRACT]]
This research paper investigates the hopped-up relationship between the number of breweries in the United States and the stock price of Salesforce (CRM). Using data from the Brewers Association and LSEG Analytics (Refinitiv), our study covers the period spanning from 2005 to 2022. Through rigorous statistical analysis, we determined a robust correlation coefficient of 0.9349908 with a statistically significant p-value of less than 0.01. The findings unveil a noteworthy link between the burgeoning craft beer industry and the fluctuations in Salesforce's stock price. Stay tuned as we tap into the frothy details and uncover the malt-titude of factors at play in this unexpectedly refreshing correlation.
[[INTRDUCTION]]
The unquenchable thirst for knowledge often drives researchers to explore unexpected correlations and connections, just like chasing the perfect blend of hops and malt to create the ideal craft beer. In this spirit of exploration, we delve into the frothy world of breweries and the financial domain, seeking to uncover the surprising interplay between the number of breweries in the United States and the stock price of Salesforce (CRM). This research seeks to tap into the intricacies of this relationship, frothy with possibilities, and offer a refreshing blend of statistical analysis, market trends, and a dash of humor.
Craft beer enthusiasts may liken the meticulous process of brewing to the precision of statistical analysis - both requiring careful measurement, a keen eye for detail, and a sprinkle of creativity. Similarly, navigating the stock market demands a balancing act akin to the delicate art of brewing, blending different flavors and personalities to produce a successful outcome. These parallels serve as a flavorful backdrop against which we aim to uncork the surprising correlations and relationships that intertwine the two seemingly disparate realms.
In a world where data is brewed and distilled into actionable insights, we bring a comprehensive analysis spanning from 2005 to 2022, meticulously concocted using information from the Brewers Association and LSEG Analytics (Refinitiv). Like a brewmaster fine-tuning a recipe, we meticulously craft this study to bring forth a robust correlation coefficient of 0.9349908 and a statistically significant p-value of less than 0.01, demonstrating a strong link between the number of breweries and Salesforce's stock performance. As we tap into this tantalizing convergence of craft beer and financial markets, we invite readers to savor the complex bouquet of statistical data and market dynamics that blend together to create this unexpectedly effervescent correlation. Stay tuned as we embark on this adventuresome quest, trying to balance the gravity of the research with the lightheartedness of a well-crafted pun. Cheers to the unexpected, and may this research be as refreshing as a perfectly chilled pint of ale on a hot summer day!
[[RESULTS]]
The analysis of the relationship between the number of breweries in the United States and Salesforce's stock price (CRM) yielded a surprising and rather hoppy correlation coefficient of 0.9349908. This robust correlation was accompanied by an r-squared value of 0.8742078, indicating that approximately 87.42% of the variance in Salesforce's stock price can be explained by the number of breweries. The p-value of less than 0.01 further confirms the statistical significance of this correlation, allowing us to confidently raise a toast to the validity of our findings.
Fig. 1 depicts a scatterplot illustrating the strong positive correlation between the number of breweries and Salesforce's stock price. The data points form a pattern reminiscent of bubbles rising in a glass of finely carbonated beer, accentuating the effervescence of this unexpected relationship.
These results not only highlight the interconnectedness of seemingly unrelated industries but also underscore the importance of approaching data analysis with an open mind, much like a craft brewer experimenting with new ingredients to create a unique and palatable beer. The robustness of the correlation coefficient echoes the intricacy and depth found in a finely crafted brew, demonstrating the complexity of the relationship between these two variables.
In essence, this unexpected and refreshing correlation between the number of breweries in the United States and Salesforce's stock price opens up a frothy frontier for further exploration and analysis. As we continue to unravel the multifaceted layers of this relationship, we invite readers to join us in savoring this unexpectedly delightful blend of statistical precision, market dynamics, and perhaps a sprinkle of humor. Let's raise a glass to the serendipitous discoveries hidden within the depths of data - cheers to the unexpected!
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our investigation into the relationship between the number of breweries in the United States and Salesforce's stock price (CRM) has provided some unexpectedly frothy insights. The robust correlation coefficient of 0.9349908, akin to the perfect head on a well-poured beer, suggests a strong positive relationship between these seemingly unrelated variables. The substantial r-squared value of 0.8742078 underscores the depth of this connection, much like the complexity of flavors found in a meticulously crafted brew. The statistically significant p-value of less than 0.01 serves as a reassuringly solid foundation for these findings, akin to the firmness of a barstool in a bustling brewery taproom.
Our findings, presented with a hint of whimsy and a dash of statistical rigor, encourage a toast to the unexpected connections that can be uncovered in the vast landscape of data and market dynamics. The scatterplot, resembling bubbles in a freshly poured pint, visually encapsulates the effervescence of this correlation, reminding us that even in the world of empirical analysis, there is room for the unexpected and the delightful.
As we raise our glasses to bid adieu to this research, we assert that no more brewing is needed in this area. The blend of statistical precision and unexpected correlations has fermented a satisfying and thought-provoking experience, leaving us with a taste of serendipity and curiosity about the myriad connections waiting to be discovered in the vast expanse of data. Cheers to the unexpected, and may this research be as refreshing as a well-crafted pun at the end of a long day of serious statistical analysis!
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 Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Fermentation Finance
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 Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price. Respond only with the name of a fictional organization.
ChatGPT:
The Foam and Finance Research Institute
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 Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price with an abstract of This research paper investigates the hopped-up relationship between the number of breweries in the United States and the stock price of Salesforce (CRM). Using data from the Brewers Association and LSEG Analytics (Refinitiv), our study covers the period spanning from 2005 to 2022. Through rigorous statistical analysis, we determined a robust correlation coefficient of 0.9349908 with a statistically significant p-value of less than 0.01. The findings unveil a noteworthy link between the burgeoning craft beer industry and the fluctuations in Salesforce's stock price. Stay tuned as we tap into the frothy details and uncover the malt-titude of factors at play in this unexpectedly refreshing correlation.
ChatGPT:
breweries, United States, Salesforce stock price, CRM, data analysis, Brewers Association, LSEG Analytics, Refinitiv, correlation coefficient, craft beer industry, stock price fluctuations, statistical analysis, research paper
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
The number of Breweries in the United StatesDetailed data title: Number of Breweries in the United States
Source: Brewers Association
See what else correlates with The number of Breweries in the United States
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: Via Microsoft Excel Stockhistory function
See what else correlates with Salesforce's stock price (CRM)
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 = 0.8742078 (Coefficient of determination)
This means 87.4% 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., The number of Breweries in the United States) over the 18 years from 2005 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.31E-8. 0.0000000130649597490129840000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.
But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.
Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.93 in 1.31E-6% of random cases. Said differently, if you correlated 76,540,611 random variables You don't actually need 76 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.
p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.
In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.
Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 17 degrees of freedom, 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.
[ 0.83, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | |
The number of Breweries in the United States (Number of breweries) | 1612 | 1741 | 1805 | 1896 | 1933 | 2131 | 2525 | 2670 | 3162 | 4014 | 4847 | 5780 | 6767 | 7722 | 8557 | 9092 | 9384 | 9709 |
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
Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied. - Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple
Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.Step 2: Open a plaintext editor like Notepad and paste the code below into it.
Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"
Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.
Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.
Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.
Step 7: Run the Python script by typing "python calculate_correlation.py"
If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:
"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."
# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats
# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):
# Calculate Pearson correlation coefficient and p-value
correlation, p_value = stats.pearsonr(array1, array2)
# Calculate R-squared as the square of the correlation coefficient
r_squared = correlation**2
return correlation, r_squared, p_value
# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([1612,1741,1805,1896,1933,2131,2525,2670,3162,4014,4847,5780,6767,7722,8557,9092,9384,9709,])
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 = "The number of Breweries in the United States"
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. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.
For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.
Download images for these variables:
- High resolution line chart
The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
Alternatively you can use a tool like Inkscape. - High resolution line chart, optimized for mobile
- Alternative high resolution line chart
- Scatterplot
- Portable line chart (png)
- Portable line chart (png), optimized for mobile
- Line chart for only The number of Breweries in the United States
- Line chart for only Salesforce's stock price (CRM)
- AI-generated correlation image
- The spurious research paper: Pouring Over Data: The Hoppy Connection Between Breweries and Salesforce's Stock Price
You're the rating guru we've been waiting for!
Correlation ID: 2158 · Black Variable ID: 34 · Red Variable ID: 1573