Download png, svg
AI explanation
As household spending on bakery products rises, more people experience carb-induced happiness. This leads to an uptick in overall consumer satisfaction. With consumers in a better mood, there's increased demand for electronic devices, including those with QUALCOMM components, as people 'knead' more entertainment and connectivity. This surge in demand for tech products boosts QUALCOMM's stock price as investors realize that the company is on a roll.Model: dalle-3
Prompt: Prompt: Generate an image of a hyper-realistic cozy bakery scene with customers indulging in freshly baked pastries while a group outside shares positive news about QUALCOMM's latest technological advancements, particularly in camera features, leading to a steady rise in QUALCOMM's stock price on a digital screen in the background. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:
Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Annual US household spending on bakery products and QUALCOMM's stock price (QCOM). 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: Whimsical illustration Cybernetic art inspired by bauhaus Hyper-realistic Low poly
ChatGPT: Hyper-realistic
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Annual US household spending on bakery products and QUALCOMM's stock price (QCOM), in the following situation: Because as more households spend dough on bakery products, the demand for sweet treats rises. This leads to an increase in happiness levels, causing people to share positive news on social media. This, in turn, boosts engagement on platforms like Instagram, where QUALCOMM's advanced technology is praised for its high-quality camera features. The positive sentiment translates into increased investor confidence, driving up the stock price. It's a rising tide that lifts all buns – I mean, boats.. Keep the description simple.
ChatGPT: Picture a cozy bakery bustling with customers happily selecting delicious pastries and bread. The air is filled with the warm aroma of freshly baked goods as families and individuals make their purchases. Meanwhile, outside the bakery, a group of people are gathered around a smartphone, sharing and commenting on positive news about QUALCOMM's latest advancements in technology, particularly their exceptional camera features, on social media. In the background, the stock price for QUALCOMM (QCOM) steadily rises on a digital screen, reflecting the positive sentiment and investor confidence stemming from the widespread praise for the tech company's innovations.
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: [ Hyper-realistic ] and depicting this scene: Picture a cozy bakery bustling with customers happily selecting delicious pastries and bread. The air is filled with the warm aroma of freshly baked goods as families and individuals make their purchases. Meanwhile, outside the bakery, a group of people are gathered around a smartphone, sharing and commenting on positive news about QUALCOMM's latest advancements in technology, particularly their exceptional camera features, on social media. In the background, the stock price for QUALCOMM (QCOM) steadily rises on a digital screen, reflecting the positive sentiment and investor confidence stemming from the widespread praise for the tech company's innovations. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image of a hyper-realistic cozy bakery scene with customers indulging in freshly baked pastries while a group outside shares positive news about QUALCOMM's latest technological advancements, particularly in camera features, leading to a steady rise in QUALCOMM's stock price on a digital screen in the background.
*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 Annual US household spending on bakery products caused QUALCOMM's stock price (QCOM) to increase.
AI academic paper
Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price The Journal of Culinary Economics and Financial Analysis Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You 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 Annual US household spending on bakery products and QUALCOMM's stock price (QCOM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Make the title punny if you can come up with clever pun. If not, make it sound serious.
Your research team used data from Bureau of Labor Statistics and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9098264 and p < 0.01 for 2002 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]]
Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price
[[ABSTRACT]]
This research delves into the often overlooked connection between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). Through the meticulous analysis of data obtained from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), a correlation coefficient of 0.9098264 and p < 0.01 was established for the time period spanning from 2002 to 2022. These findings suggest a remarkably robust relationship, raising the dough of whether bakery product consumption holds the key to the stock performance of the telecommunications equipment company. Our investigation prompts further inquiry into the potential "buttery effect" between consumer indulgence in baked goods and technological enterprise profitability.
Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the 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 Annual US household spending on bakery products and QUALCOMM's stock price (QCOM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Here is the title and abstract of the paper:
[[TITLE]]
Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price
[[ABSTRACT]]
This research delves into the often overlooked connection between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). Through the meticulous analysis of data obtained from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), a correlation coefficient of 0.9098264 and p < 0.01 was established for the time period spanning from 2002 to 2022. These findings suggest a remarkably robust relationship, raising the dough of whether bakery product consumption holds the key to the stock performance of the telecommunications equipment company. Our investigation prompts further inquiry into the potential "buttery effect" between consumer indulgence in baked goods and technological enterprise profitability.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
In the annals of economic research, certain connections may at first seem as unlikely as a croissant and a cup of coffee. Yet, as we delve deeper into the mysteries of consumer behavior and stock market dynamics, we find ourselves drawn to unexpected parallels, much like the magnetic attraction between a fresh baguette and a pat of butter.
The subject of this investigation is the relationship between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). While it may seem as disparate as dark rye and brioche, our examination has unearthed compelling evidence of a surprisingly strong correlation between these seemingly unrelated domains.
As we embark on this bread-crumb trail of analysis, we are reminded of the adage, "follow the yeast, and the breadcrumbs will follow." Our quest is guided by a rigorous study of data, drawn from the esteemed Bureau of Labor Statistics and LSEG Analytics (Refinitiv). These sources have provided us with a rich tapestry of information, enabling us to chart the intricate dance between the purchase of pastries, pies, and breads, and the fluctuations of QUALCOMM's stock price.
Our initial inquiry has yielded a correlation coefficient of 0.9098264 and p < 0.01 over the course of the years 2002 to 2022. This statistical coupling stands as a testament to the robustness of the link we have uncovered, akin to the firmness of a well-kneaded dough.
Our findings pose a tantalizing question: could the buttery layers of a croissant be emblematic of the hidden layers of influence that bakery product consumption holds over the stock performance of a telecommunications equipment company? As we savor this thought, we are spurred on to delve deeper into the potential "buttery effect" between consumer indulgence in baked goods and the profitability of technological enterprises.
In the pages that follow, we shall undertake a thorough exploration of this unexpected nexus, peeling back the layers of conventional analysis to uncover the tantalizing aroma of interconnectedness between consumer choices and market dynamics. This study stands as a testament to the richness of insight that can be gained from embracing unexpected parallels, much like the surprise of finding an unexpected filling in a seemingly ordinary pastry.
Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between Annual US household spending on bakery products and QUALCOMM's stock price (QCOM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.
Here is the title and abstract of the paper:
[[TITLE]]
Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price
[[ABSTRACT]]
This research delves into the often overlooked connection between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). Through the meticulous analysis of data obtained from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), a correlation coefficient of 0.9098264 and p < 0.01 was established for the time period spanning from 2002 to 2022. These findings suggest a remarkably robust relationship, raising the dough of whether bakery product consumption holds the key to the stock performance of the telecommunications equipment company. Our investigation prompts further inquiry into the potential "buttery effect" between consumer indulgence in baked goods and technological enterprise profitability.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the annals of economic research, certain connections may at first seem as unlikely as a croissant and a cup of coffee. Yet, as we delve deeper into the mysteries of consumer behavior and stock market dynamics, we find ourselves drawn to unexpected parallels, much like the magnetic attraction between a fresh baguette and a pat of butter.
The subject of this investigation is the relationship between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). While it may seem as disparate as dark rye and brioche, our examination has unearthed compelling evidence of a surprisingly strong correlation between these seemingly unrelated domains.
As we embark on this bread-crumb trail of analysis, we are reminded of the adage, "follow the yeast, and the breadcrumbs will follow." Our quest is guided by a rigorous study of data, drawn from the esteemed Bureau of Labor Statistics and LSEG Analytics (Refinitiv). These sources have provided us with a rich tapestry of information, enabling us to chart the intricate dance between the purchase of pastries, pies, and breads, and the fluctuations of QUALCOMM's stock price.
Our initial inquiry has yielded a correlation coefficient of 0.9098264 and p < 0.01 over the course of the years 2002 to 2022. This statistical coupling stands as a testament to the robustness of the link we have uncovered, akin to the firmness of a well-kneaded dough.
Our findings pose a tantalizing question: could the buttery layers of a croissant be emblematic of the hidden layers of influence that bakery product consumption holds over the stock performance of a telecommunications equipment company? As we savor this thought, we are spurred on to delve deeper into the potential "buttery effect" between consumer indulgence in baked goods and the profitability of technological enterprises.
In the pages that follow, we shall undertake a thorough exploration of this unexpected nexus, peeling back the layers of conventional analysis to uncover the tantalizing aroma of interconnectedness between consumer choices and market dynamics. This study stands as a testament to the richness of insight that can be gained from embracing unexpected parallels, much like the surprise of finding an unexpected filling in a seemingly ordinary pastry.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The investigation of seemingly disparate relationships in economic research is not without precedent. Smith (2010) explores the surprising link between consumer spending on coffee and the performance of coffee producers in the stock market, demonstrating a nuanced interplay between consumer indulgence and market dynamics. Doe (2015) similarly delves into the correlation between retail sales of confectionery products and the stock prices of major confectionery companies, revealing a sweet, yet robust, relationship. Jones (2018) investigates the connection between household spending on pet supplies and the stock performance of veterinary pharmaceutical companies, highlighting the unexpected influence of pet ownership on market trends.
As we transition from these serious inquiries into the domain of bakery products and stock prices, it is pertinent to consider relevant non-fiction literature that may provide valuable insights. "Flour Power: The Economics of Baking" (Baker, 2016) offers a comprehensive analysis of the economic impact of flour production and its implications for consumer spending on baked goods. "The Rise and Fall of Yeast: A Historical Perspective" (Leaven, 2019) provides a fascinating historical account of the economic significance of yeast production and its resonance with consumer preferences for bakery products.
Turning to fiction literature, the themes of indulgence and market influence can be seen in "Dough and Order: A Baker's Mystery" (Bunson, 2017), a delightful tale of amateur sleuths uncovering financial intrigue in a quaint bakery. "Stocks and Scones: A Wall Street Bakery Mystery" (Muffin, 2020) weaves a thrilling narrative of financial maneuvering amidst the delectable world of baked goods, underscoring the potential for unexpected connections between consumer behavior and market forces.
Furthermore, anecdotal evidence from social media posts has brought attention to the peculiar correlation between the proliferation of bread memes and the stock performance of major technology firms. One post on a popular platform asserts, "The loaf rises as the stocks rise - coincidence? I think Yeast!" Such informal observations, while light-hearted, may serve as a starting point for further investigation into the whimsical interplay between social media trends and market movements.
In summary, the literature surrounding the intersection of consumer behavior in bakery product consumption and stock prices demonstrates both serious and whimsical undertones, setting the stage for a comprehensive exploration of this surprising nexus.
Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between Annual US household spending on bakery products and QUALCOMM's stock price (QCOM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Your research team collected data from all across the internet, but mostly just used information from Bureau of Labor Statistics and LSEG Analytics (Refinitiv) . You used data from 2002 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]]
Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price
[[ABSTRACT]]
This research delves into the often overlooked connection between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). Through the meticulous analysis of data obtained from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), a correlation coefficient of 0.9098264 and p < 0.01 was established for the time period spanning from 2002 to 2022. These findings suggest a remarkably robust relationship, raising the dough of whether bakery product consumption holds the key to the stock performance of the telecommunications equipment company. Our investigation prompts further inquiry into the potential "buttery effect" between consumer indulgence in baked goods and technological enterprise profitability.
[[INTRODUCTION]]
In the annals of economic research, certain connections may at first seem as unlikely as a croissant and a cup of coffee. Yet, as we delve deeper into the mysteries of consumer behavior and stock market dynamics, we find ourselves drawn to unexpected parallels, much like the magnetic attraction between a fresh baguette and a pat of butter.
The subject of this investigation is the relationship between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). While it may seem as disparate as dark rye and brioche, our examination has unearthed compelling evidence of a surprisingly strong correlation between these seemingly unrelated domains.
As we embark on this bread-crumb trail of analysis, we are reminded of the adage, "follow the yeast, and the breadcrumbs will follow." Our quest is guided by a rigorous study of data, drawn from the esteemed Bureau of Labor Statistics and LSEG Analytics (Refinitiv). These sources have provided us with a rich tapestry of information, enabling us to chart the intricate dance between the purchase of pastries, pies, and breads, and the fluctuations of QUALCOMM's stock price.
Our initial inquiry has yielded a correlation coefficient of 0.9098264 and p < 0.01 over the course of the years 2002 to 2022. This statistical coupling stands as a testament to the robustness of the link we have uncovered, akin to the firmness of a well-kneaded dough.
Our findings pose a tantalizing question: could the buttery layers of a croissant be emblematic of the hidden layers of influence that bakery product consumption holds over the stock performance of a telecommunications equipment company? As we savor this thought, we are spurred on to delve deeper into the potential "buttery effect" between consumer indulgence in baked goods and the profitability of technological enterprises.
In the pages that follow, we shall undertake a thorough exploration of this unexpected nexus, peeling back the layers of conventional analysis to uncover the tantalizing aroma of interconnectedness between consumer choices and market dynamics. This study stands as a testament to the richness of insight that can be gained from embracing unexpected parallels, much like the surprise of finding an unexpected filling in a seemingly ordinary pastry.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
The data utilized in this research were collected from diverse sources including the Bureau of Labor Statistics and LSEG Analytics (Refinitiv). The data covered the period from 2002 to 2022, encompassing a broad swath of economic and market movements.
To examine the relationship between annual US household spending on bakery products and QUALCOMM's stock price, a series of convoluted yet carefully crafted statistical methods were employed. Firstly, annual household expenditures on bakery products were meticulously extracted from the Consumer Expenditure Survey conducted by the Bureau of Labor Statistics. These expenditure patterns were then categorized, analyzed, and scrutinized with the thoroughness of a discerning baker examining the proofing of sourdough.
Simultaneously, QUALCOMM's stock performance, captured in the form of daily stock prices, was procured from the databases of LSEG Analytics (Refinitiv). These chronicles of market movements were subjected to rigorous statistical scrutiny, akin to the inspection of the intricate latticework on a lattice pie crust, to uncover any hidden patterns or connections.
Subsequently, the acquired datasets were harmoniously reconciled, much like the blending of ingredients in a finely prepared batter, and subjected to various time-series and correlation analyses. The statistical relations were unfurled with the same care and precision one would employ in rolling out puff pastry, making sure not to misinterpret any flaky layers of the relationship.
Finally, the statistical measures of correlation coefficients and significance levels, along with utilizing robust regression models, were employed to gauge the strength and direction of the interplay between annual household spending on bakery products and QUALCOMM's stock price. These analytical techniques were leveraged to unveil the subtle yet compelling linkage between these seemingly disparate realms, much like the revelation of a hidden compartment within a loaf of artisanal bread.
The execution of these methodologies has allowed us to bring forth intriguing insights into the potential influence of bakery product consumption on the stock performance of a prominent technological company, shedding light on a dynamic as unexpected as finding a cherry filling in a loaf of bread.
Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Annual US household spending on bakery products and QUALCOMM's stock price (QCOM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Your research team collected data from all across the internet, but mostly just used information from Bureau of Labor Statistics and LSEG Analytics (Refinitiv) .
For the time period 2002 to 2022, you found a correlation 0.9098264, r-squared of 0.8277840, 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]]
Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price
[[ABSTRACT]]
This research delves into the often overlooked connection between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). Through the meticulous analysis of data obtained from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), a correlation coefficient of 0.9098264 and p < 0.01 was established for the time period spanning from 2002 to 2022. These findings suggest a remarkably robust relationship, raising the dough of whether bakery product consumption holds the key to the stock performance of the telecommunications equipment company. Our investigation prompts further inquiry into the potential "buttery effect" between consumer indulgence in baked goods and technological enterprise profitability.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the annals of economic research, certain connections may at first seem as unlikely as a croissant and a cup of coffee. Yet, as we delve deeper into the mysteries of consumer behavior and stock market dynamics, we find ourselves drawn to unexpected parallels, much like the magnetic attraction between a fresh baguette and a pat of butter.
The subject of this investigation is the relationship between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). While it may seem as disparate as dark rye and brioche, our examination has unearthed compelling evidence of a surprisingly strong correlation between these seemingly unrelated domains.
As we embark on this bread-crumb trail of analysis, we are reminded of the adage, "follow the yeast, and the breadcrumbs will follow." Our quest is guided by a rigorous study of data, drawn from the esteemed Bureau of Labor Statistics and LSEG Analytics (Refinitiv). These sources have provided us with a rich tapestry of information, enabling us to chart the intricate dance between the purchase of pastries, pies, and breads, and the fluctuations of QUALCOMM's stock price.
Our initial inquiry has yielded a correlation coefficient of 0.9098264 and p < 0.01 over the course of the years 2002 to 2022. This statistical coupling stands as a testament to the robustness of the link we have uncovered, akin to the firmness of a well-kneaded dough.
Our findings pose a tantalizing question: could the buttery layers of a croissant be emblematic of the hidden layers of influence that bakery product consumption holds over the stock performance of a telecommunications equipment company? As we savor this thought, we are spurred on to delve deeper into the potential "buttery effect" between consumer indulgence in baked goods and the profitability of technological enterprises.
In the pages that follow, we shall undertake a thorough exploration of this unexpected nexus, peeling back the layers of conventional analysis to uncover the tantalizing aroma of interconnectedness between consumer choices and market dynamics. This study stands as a testament to the richness of insight that can be gained from embracing unexpected parallels, much like the surprise of finding an unexpected filling in a seemingly ordinary pastry.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The statistical analysis revealed a strong correlation between annual US household spending on bakery products and QUALCOMM's stock price over the period of 2002 to 2022. The correlation coefficient of 0.9098264 indicates a robust positive relationship between these seemingly distinct domains. The r-squared value of 0.8277840 further illustrates the substantial proportion of the variability in QUALCOMM's stock price that can be explained by changes in annual household spending on bakery products.
Furthermore, the p-value of less than 0.01 provides strong evidence against the null hypothesis, suggesting that the relationship observed is unlikely to be due to random chance. This statistical significance reinforces the notion that the connection between these variables is not merely a flaky coincidence, but a substantive relationship worth exploring further.
Notably, the scatterplot (Fig. 1) visually depicts the close correspondence between annual US household spending on bakery products and QUALCOMM's stock price. The tight clustering of data points reinforces the robustness of the relationship, akin to the precision of a well-timed kneading process.
These findings invite contemplation on the potential implications of consumer indulgence in baked goods on the stock performance of technological enterprises. Could the aroma of freshly baked bread carry subtle hints about shifts in the telecommunications equipment market? While this study does not provide definitive answers, it does prompt further inquiry into the complex interplay between consumer behavior and market dynamics.
In conclusion, the results of this analysis offer compelling evidence of a meaningful connection between annual US household spending on bakery products and QUALCOMM's stock price. This unexpected nexus leaves us pondering the layers of influence that may be at play beneath the surface of consumer indulgence and market performance.
Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between Annual US household spending on bakery products and QUALCOMM's stock price (QCOM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Limit your response to 500 tokens.
Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.
Do not write a conclusion. I will add a conclusion after this.
[[TITLE]]
Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price
[[ABSTRACT]]
This research delves into the often overlooked connection between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). Through the meticulous analysis of data obtained from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), a correlation coefficient of 0.9098264 and p < 0.01 was established for the time period spanning from 2002 to 2022. These findings suggest a remarkably robust relationship, raising the dough of whether bakery product consumption holds the key to the stock performance of the telecommunications equipment company. Our investigation prompts further inquiry into the potential "buttery effect" between consumer indulgence in baked goods and technological enterprise profitability.
[[LITERATURE REVIEW]]
The investigation of seemingly disparate relationships in economic research is not without precedent. Smith (2010) explores the surprising link between consumer spending on coffee and the performance of coffee producers in the stock market, demonstrating a nuanced interplay between consumer indulgence and market dynamics. Doe (2015) similarly delves into the correlation between retail sales of confectionery products and the stock prices of major confectionery companies, revealing a sweet, yet robust, relationship. Jones (2018) investigates the connection between household spending on pet supplies and the stock performance of veterinary pharmaceutical companies, highlighting the unexpected influence of pet ownership on market trends.
As we transition from these serious inquiries into the domain of bakery products and stock prices, it is pertinent to consider relevant non-fiction literature that may provide valuable insights. "Flour Power: The Economics of Baking" (Baker, 2016) offers a comprehensive analysis of the economic impact of flour production and its implications for consumer spending on baked goods. "The Rise and Fall of Yeast: A Historical Perspective" (Leaven, 2019) provides a fascinating historical account of the economic significance of yeast production and its resonance with consumer preferences for bakery products.
Turning to fiction literature, the themes of indulgence and market influence can be seen in "Dough and Order: A Baker's Mystery" (Bunson, 2017), a delightful tale of amateur sleuths uncovering financial intrigue in a quaint bakery. "Stocks and Scones: A Wall Street Bakery Mystery" (Muffin, 2020) weaves a thrilling narrative of financial maneuvering amidst the delectable world of baked goods, underscoring the potential for unexpected connections between consumer behavior and market forces.
Furthermore, anecdotal evidence from social media posts has brought attention to the peculiar correlation between the proliferation of bread memes and the stock performance of major technology firms. One post on a popular platform asserts, "The loaf rises as the stocks rise - coincidence? I think Yeast!" Such informal observations, while light-hearted, may serve as a starting point for further investigation into the whimsical interplay between social media trends and market movements.
In summary, the literature surrounding the intersection of consumer behavior in bakery product consumption and stock prices demonstrates both serious and whimsical undertones, setting the stage for a comprehensive exploration of this surprising nexus.
[[RESULTS]]
The statistical analysis revealed a strong correlation between annual US household spending on bakery products and QUALCOMM's stock price over the period of 2002 to 2022. The correlation coefficient of 0.9098264 indicates a robust positive relationship between these seemingly distinct domains. The r-squared value of 0.8277840 further illustrates the substantial proportion of the variability in QUALCOMM's stock price that can be explained by changes in annual household spending on bakery products.
Furthermore, the p-value of less than 0.01 provides strong evidence against the null hypothesis, suggesting that the relationship observed is unlikely to be due to random chance. This statistical significance reinforces the notion that the connection between these variables is not merely a flaky coincidence, but a substantive relationship worth exploring further.
Notably, the scatterplot (Fig. 1) visually depicts the close correspondence between annual US household spending on bakery products and QUALCOMM's stock price. The tight clustering of data points reinforces the robustness of the relationship, akin to the precision of a well-timed kneading process.
These findings invite contemplation on the potential implications of consumer indulgence in baked goods on the stock performance of technological enterprises. Could the aroma of freshly baked bread carry subtle hints about shifts in the telecommunications equipment market? While this study does not provide definitive answers, it does prompt further inquiry into the complex interplay between consumer behavior and market dynamics.
In conclusion, the results of this analysis offer compelling evidence of a meaningful connection between annual US household spending on bakery products and QUALCOMM's stock price. This unexpected nexus leaves us pondering the layers of influence that may be at play beneath the surface of consumer indulgence and market performance.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The results of this study have provided compelling evidence in support of the hypothesis that there exists a significant relationship between annual US household spending on bakery products and QUALCOMM's stock price. The robust correlation coefficient of 0.9098264 and the high level of statistical significance with a p-value of less than 0.01 affirm the substantive nature of this connection. These findings align with prior research that has uncovered surprising correlations between consumer behavior and market dynamics, such as the link between coffee consumption and stock performance in the coffee industry (Smith, 2010).
The literature review also introduced some seemingly whimsical yet thought-provoking connections, such as the correlation between pet ownership and the stock performance of veterinary pharmaceutical companies (Jones, 2018). These lighthearted observations, while initially amusing, have proven to hold relevance in shedding light on the intricate interplay between consumer indulgence and market trends. Similarly, the anecdotal evidence from social media posts regarding the relationship between bread memes and the stock performance of technology firms, though light-hearted, underscores the potential for surprising connections between consumer behavior and market forces.
The statistical significance of the relationship observed in this study belies the light-hearted nature of the subject matter, demonstrating that the connection between annual US household spending on bakery products and QUALCOMM's stock price is not merely a flaky coincidence, but rather a substantial relationship worth serious consideration. The r-squared value of 0.8277840 further supports the notion that changes in annual household spending on bakery products explain a substantial proportion of the variability in QUALCOMM's stock price, akin to the precision of a well-timed kneading process.
While this study has not elucidated the precise mechanisms underlying this connection, the findings prompt further investigation into the potential influence of consumer indulgence in baked goods on the stock performance of technological enterprises. As we contemplate the potential implications of this unexpected nexus, it is clear that the aroma of freshly baked bread may carry subtle hints about shifts in the telecommunications equipment market, providing food for thought in the realm of market analysis.
In conclusion, the findings of this research underscore the need for continued exploration of the complex interplay between consumer behavior and market dynamics. As we peel back the layers of this intriguing relationship, it becomes evident that the economics of baked goods may hold insights that are not just half-baked theories but rather significant contributors to our understanding of market trends. The "buttery effect" observed in this study may serve as a springboard for further investigations into the nuanced connections between seemingly disparate domains, inviting us to consider the yeast of these worries with a newfound seriousness.
Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between Annual US household spending on bakery products and QUALCOMM's stock price (QCOM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.
Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price
[[ABSTRACT]]
This research delves into the often overlooked connection between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). Through the meticulous analysis of data obtained from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), a correlation coefficient of 0.9098264 and p < 0.01 was established for the time period spanning from 2002 to 2022. These findings suggest a remarkably robust relationship, raising the dough of whether bakery product consumption holds the key to the stock performance of the telecommunications equipment company. Our investigation prompts further inquiry into the potential "buttery effect" between consumer indulgence in baked goods and technological enterprise profitability.
[[INTRDUCTION]]
In the annals of economic research, certain connections may at first seem as unlikely as a croissant and a cup of coffee. Yet, as we delve deeper into the mysteries of consumer behavior and stock market dynamics, we find ourselves drawn to unexpected parallels, much like the magnetic attraction between a fresh baguette and a pat of butter.
The subject of this investigation is the relationship between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). While it may seem as disparate as dark rye and brioche, our examination has unearthed compelling evidence of a surprisingly strong correlation between these seemingly unrelated domains.
As we embark on this bread-crumb trail of analysis, we are reminded of the adage, "follow the yeast, and the breadcrumbs will follow." Our quest is guided by a rigorous study of data, drawn from the esteemed Bureau of Labor Statistics and LSEG Analytics (Refinitiv). These sources have provided us with a rich tapestry of information, enabling us to chart the intricate dance between the purchase of pastries, pies, and breads, and the fluctuations of QUALCOMM's stock price.
Our initial inquiry has yielded a correlation coefficient of 0.9098264 and p < 0.01 over the course of the years 2002 to 2022. This statistical coupling stands as a testament to the robustness of the link we have uncovered, akin to the firmness of a well-kneaded dough.
Our findings pose a tantalizing question: could the buttery layers of a croissant be emblematic of the hidden layers of influence that bakery product consumption holds over the stock performance of a telecommunications equipment company? As we savor this thought, we are spurred on to delve deeper into the potential "buttery effect" between consumer indulgence in baked goods and the profitability of technological enterprises.
In the pages that follow, we shall undertake a thorough exploration of this unexpected nexus, peeling back the layers of conventional analysis to uncover the tantalizing aroma of interconnectedness between consumer choices and market dynamics. This study stands as a testament to the richness of insight that can be gained from embracing unexpected parallels, much like the surprise of finding an unexpected filling in a seemingly ordinary pastry.
[[RESULTS]]
The statistical analysis revealed a strong correlation between annual US household spending on bakery products and QUALCOMM's stock price over the period of 2002 to 2022. The correlation coefficient of 0.9098264 indicates a robust positive relationship between these seemingly distinct domains. The r-squared value of 0.8277840 further illustrates the substantial proportion of the variability in QUALCOMM's stock price that can be explained by changes in annual household spending on bakery products.
Furthermore, the p-value of less than 0.01 provides strong evidence against the null hypothesis, suggesting that the relationship observed is unlikely to be due to random chance. This statistical significance reinforces the notion that the connection between these variables is not merely a flaky coincidence, but a substantive relationship worth exploring further.
Notably, the scatterplot (Fig. 1) visually depicts the close correspondence between annual US household spending on bakery products and QUALCOMM's stock price. The tight clustering of data points reinforces the robustness of the relationship, akin to the precision of a well-timed kneading process.
These findings invite contemplation on the potential implications of consumer indulgence in baked goods on the stock performance of technological enterprises. Could the aroma of freshly baked bread carry subtle hints about shifts in the telecommunications equipment market? While this study does not provide definitive answers, it does prompt further inquiry into the complex interplay between consumer behavior and market dynamics.
In conclusion, the results of this analysis offer compelling evidence of a meaningful connection between annual US household spending on bakery products and QUALCOMM's stock price. This unexpected nexus leaves us pondering the layers of influence that may be at play beneath the surface of consumer indulgence and market performance.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, the results of this study indicate a strikingly robust relationship between annual US household spending on bakery products and QUALCOMM's stock price. The correlation coefficient of 0.9098264 underscores the substantive connection between these seemingly unrelated domains. It appears that consumer cravings for croissants and bagels may indeed hold the key to understanding fluctuations in the stock price of a major telecommunications equipment company.
The tight clustering of data points in the scatterplot further reinforces the strength of this relationship, much like the texture of a well-kneaded dough. While this analysis sheds light on the dough-y connection between household bakery expenses and stock performance, it also prompts us to wonder about the potential buttery layers of influence that may be at play. Could the scent of freshly baked bread carry subtle hints about shifts in the technology market? These questions, much like a good loaf of bread, are ripe for further exploration.
It is important to note, however, that correlation does not imply causation. While our findings tantalizingly hint at a connection, we must resist the temptation to jump to hasty conclusions. As the saying goes, "let the dough rise, but don't let the data get stale." Further research and investigation are needed to fully understand the mechanisms underlying this intriguing relationship.
In considering the potential implications of our findings, it is worth mulling over the idea that perhaps stock prices, much like a delicate soufflé, are subject to unforeseen influences. This study serves as a reminder that economic dynamics, like the delicate balance of ingredients in a recipe, may be shaped by factors that lie beyond the immediate purview of traditional analysis.
In summary, the interplay between consumer indulgence in baked goods and the stock performance of technological enterprises beckons for further examination. However, this study marks a significant step in unraveling the mysteries behind this curious connection. As we contemplate the potential "buttery effect" of bakery product consumption on stock market fluctuations, we are reminded that sometimes, the most unexpected pairings yield the most delectable insights. Nonetheless, no more research is needed in this area.
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 Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Culinary Economics and Financial Analysis
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price. Respond only with the name of a fictional organization.
ChatGPT:
The Institute for Economic Pastry Studies
Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price with an abstract of This research delves into the often overlooked connection between annual US household spending on bakery products and the stock price of QUALCOMM (QCOM). Through the meticulous analysis of data obtained from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), a correlation coefficient of 0.9098264 and p < 0.01 was established for the time period spanning from 2002 to 2022. These findings suggest a remarkably robust relationship, raising the dough of whether bakery product consumption holds the key to the stock performance of the telecommunications equipment company. Our investigation prompts further inquiry into the potential "buttery effect" between consumer indulgence in baked goods and technological enterprise profitability.
ChatGPT:
annual US household spending, bakery products, QUALCOMM, QCOM, stock price, correlation coefficient, Bureau of Labor Statistics, LSEG Analytics, Refinitiv, consumer spending, bakery product consumption, technological enterprise profitability
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Annual US household spending on bakery productsDetailed data title: Average annual household spend on bakery products
Source: Bureau of Labor Statistics
See what else correlates with Annual US household spending on bakery products
QUALCOMM's stock price (QCOM)
Detailed data title: Opening price of QUALCOMM (QCOM) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function
See what else correlates with QUALCOMM's stock price (QCOM)
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 = 0.8277840 (Coefficient of determination)
This means 82.8% of the change in the one variable (i.e., QUALCOMM's stock price (QCOM)) is predictable based on the change in the other (i.e., Annual US household spending on bakery products) over the 21 years from 2002 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.09E-8. 0.0000000108737820544970710000
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 0.91 in 1.09E-6% of random cases. Said differently, if you correlated 91,964,323 random variables You don't actually need 91 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.
p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.
In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.
Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 20 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 20 because we have two variables measured over a period of 21 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.
[ 0.79, 0.96 ] 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.
2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | |
Annual US household spending on bakery products (Household spend) | 296 | 292 | 307 | 302 | 304 | 317 | 337 | 334 | 337 | 356 | 356 | 359 | 343 | 346 | 353 | 388 | 392 | 400 | 428 | 462 | 497 |
QUALCOMM's stock price (QCOM) (Stock price) | 25.49 | 18.31 | 27.01 | 42.7 | 43.25 | 37.76 | 38.23 | 35.65 | 46.79 | 49.89 | 55.88 | 63.58 | 73.61 | 74.51 | 49.43 | 65.86 | 64.38 | 56.2 | 89.05 | 153.01 | 182.91 |
Why this works
- Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
- Lack of causal connection: There is probably
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. - Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves.
Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. 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([296,292,307,302,304,317,337,334,337,356,356,359,343,346,353,388,392,400,428,462,497,])
array_2 = np.array([25.49,18.31,27.01,42.7,43.25,37.76,38.23,35.65,46.79,49.89,55.88,63.58,73.61,74.51,49.43,65.86,64.38,56.2,89.05,153.01,182.91,])
array_1_name = "Annual US household spending on bakery products"
array_2_name = "QUALCOMM's stock price (QCOM)"
# 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)
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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 Annual US household spending on bakery products
- Line chart for only QUALCOMM's stock price (QCOM)
- AI-generated correlation image
- The spurious research paper: Dough or Dough-Nut: The Yeast of these Worries? Examining the Relationship Between Annual US Household Spending on Bakery Products and QUALCOMM's Stock Price
You're the rating guru we've been waiting for!
Correlation ID: 3644 · Black Variable ID: 19887 · Red Variable ID: 1612