Spurious correlation #1,199 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is American cheese consumption and the second variable is Google's Annual Global Revenue. The chart goes from 2002 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is American cheese consumption and the second variable is Google's Annual Global Revenue. The chart goes from 2002 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As American cheese consumption melted, so did Google's competition, allowing them to brie the top dog in annual revenue. It's grate for Google, but they'll need to be careful not to get too cheesy with their success!

^{Show image generation prompt} Model: dalle-3
Prompt: [ A Discovery magazine cover image ] Generate an image of a vibrant kitchen scene with people searching for "grilled cheese recipes" on their phones and tablets. Show a large stack of American cheese on the counter, emitting an inviting aroma. The setting should exude a lively atmosphere as the scent of sizzling grilled cheese sandwiches fills the air. In the background, a TV screen streams cheese-related videos, and a bustling team at Google headquarters celebrates as more ads related to cooking and food play on their platforms, contributing to an increase in revenue. The depiction should be visually rich and bustling while maintaining a sense of simplicity. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: Increase in American cheese consumption led to Google's Annual Global Revenue increase due to a surge in people searching for "grilled cheese recipes" and watching cheese-related videos, causing an uptick in ad revenue and driving more traffic to Google's platforms.. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: Woodblock painting A Discovery magazine cover image Surrealism Realistic Symbolism
ChatGPT: A Discovery magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. Increase in American cheese consumption led to Google's Annual Global Revenue increase due to a surge in people searching for "grilled cheese recipes" and watching cheese-related videos, causing an uptick in ad revenue and driving more traffic to Google's platforms.
ChatGPT: Imagine a bustling kitchen with people searching for "grilled cheese recipes" on their phones and tablets, while a large stack of American cheese sits on the counter. The aroma of sizzling grilled cheese sandwiches fills the air, and in the background, a TV screen streams cheese-related videos. At the same time, a bustling team at Google headquarters celebrates as more and more ads related to cooking and food play on their platforms, contributing to an increase in revenue.

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 Discovery magazine cover image ] and depicting this scene: Imagine a bustling kitchen with people searching for "grilled cheese recipes" on their phones and tablets, while a large stack of American cheese sits on the counter. The aroma of sizzling grilled cheese sandwiches fills the air, and in the background, a TV screen streams cheese-related videos. At the same time, a bustling team at Google headquarters celebrates as more and more ads related to cooking and food play on their platforms, contributing to an increase in revenue. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A Discovery magazine cover image ] Generate an image of a vibrant kitchen scene with people searching for "grilled cheese recipes" on their phones and tablets. Show a large stack of American cheese on the counter, emitting an inviting aroma. The setting should exude a lively atmosphere as the scent of sizzling grilled cheese sandwiches fills the air. In the background, a TV screen streams cheese-related videos, and a bustling team at Google headquarters celebrates as more ads related to cooking and food play on their platforms, contributing to an increase in revenue. The depiction should be visually rich and bustling while maintaining a sense of simplicity.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in American cheese consumption caused Google's Annual Global Revenue to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Put to the Test: Does American Cheese Bring Google's Profits to Their Knees?

Journal of Whimsical Economic Studies

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between American cheese consumption and Google's Annual Global Revenue. 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]]
Put to the Test: Does American Cheese Bring Google's Profits to Their Knees?

[[ABSTRACT]]
This study elucidates the purported puzzling relationship between American cheese consumption and Google's Annual Global Revenue. Leveraging comprehensive data from the USDA and Statista, a correlation coefficient of 0.9638770 and p < 0.01 for the timeframe 2002 to 2021 were revealed, astonishing the research team. The findings highlight a striking, albeit confounding, connection between these seemingly incongruous entities. The implications of our results invite further scrutiny into the influence of cheese consumption on digital empires, lending credence to the adage, "cheddar makes everything better," including search engines.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between American cheese consumption and corporate financial performance has long been an enigma in both the culinary and economic realms, provoking curiosity and skepticism alike. Despite their apparent disparity, the luscious world of creamy, processed cheese slices and the cerebral domain of algorithms and search engine dominance have been linked, albeit tentatively, in the annals of popular culture and scholarly discourse.
Historically, the influence of American cheese on the fiscal health of global corporations has been overlooked, overshadowed by more conventional factors such as market demand, technological advancements, and global economic conditions. However, recent anecdotal evidence and murmurs within the blogosphere have suggested an unforeseen connection between American cheese and the staggering profits of a certain ubiquitous internet company.
The present study aims to probe this purported association with a meticulous and systematic approach, applying a rigorous statistical analysis to disentangle the complex web of potential causative factors and confounding variables. Leveraging extensive datasets from the USDA and Statista, encompassing a span of two decades, the research team sought to unveil the veracity of the speculated bond between American cheese consumption and Google's Annual Global Revenue.
Indeed, the preliminary findings yielded a coefficient of correlation that seized the attention of the entire research cohort, with a value of 0.9638770 and a statistically significant p-value below 0.01, defying initial expectations and prompting fervent discussions and raised eyebrows among the academic circles involved. The implications of these results, though far-reaching, remain perplexing, raising intriguing questions about the underlying mechanisms that could underpin such an unexpected affiliation.
As we delve into the multifaceted layers of this unlikely alliance, it becomes evident that the intertwining of these ostensibly distinct entities may hold implications that extend beyond the mere intersection of gastronomic delights and corporate prowess. As our foray into this uncharted terrain unfolds, the enigmatic relationship between American cheese and Google's financial fortunes beckons further investigation, inviting scholars to contemplate the unfathomable ways in which the world of dairy and the digital domain may intertwine.
The perplexing connection revealed by our analysis serves as a stark reminder of the unconventional pathways through which economic forces may manifest, prompting us to reflect on the intriguing aphorism, "cheddar makes everything better," which now seems to extend its influence even to the digital landscape. As we navigate through the intricate labyrinth of associations and correlations, the implications of our findings may not only illuminate the curious bond between American cheese and corporate prosperity but also redefine the contours of synergy in an increasingly interlinked global economy.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The investigation into the purported relationship between American cheese consumption and Google's Annual Global Revenue represents a substantial departure from conventional economic analyses. While the entanglement of these two seemingly incongruent entities may defy logic and strain the bounds of credulity, the extant literature provides a foundation for this unexpected inquiry.

Smith et al. (2014) assert that the correlation between gastronomic trends and corporate financial performance remains an underexplored domain within economic scholarship. Similarly, Doe and Jones (2018) remark that unconventional factors, such as cultural phenomena and consumer behavior, may exert unforeseen influences on the market dynamics of multinational corporations. However, the examination of a direct nexus between American cheese consumption and the fiscal fortunes of a technology behemoth such as Google remains scarce in the scholarly sphere.

Moving beyond the realm of conventional economic discourse, the present investigation draws insights from a nuanced examination of culinary trends and their enigmatic manifestations in the corporate arena. In "The Economics of Cheese: A Gouda Guide to Dairy Dynamics" by von Meltzer (2016), the author articulates the profound impact of cheese consumption on societal structures and consumer preferences, laying the groundwork for an expanded understanding of the potential influence of such gustatory inclinations on larger economic phenomena.

In a departure from traditional economic texts, the fictitious work "The Sinister Science of Swiss: How Cheese Dictates Destiny" by Cheddar, Brie, and Roquefort (2019) delves into the whimsical and whimsically exaggerated world of cheese-related conspiracies, providing an offbeat yet thought-provoking exploration of the interconnectedness between dairy delicacies and global hegemony. The satirical treatment of this subject matter offers a departure from the conventional scholarly rigueur, challenging readers to consider the unorthodox and unexplored avenues of economic inquiry.

Furthermore, anecdotal evidence gleaned from the blogosphere and social media platforms has contributed to the discourse surrounding the unlikely entwining of American cheese and Google's financial trajectories. A Twitter user, @CheeseEnthusiast47, mused that "perhaps Google's algorithm finds inspiration in the nuanced flavors of American cheese, leading to superior search results," prompting a mixture of amusement and bewilderment within the digital enclave. Similarly, a Reddit thread titled "Cheese, Please: A Quest for Profitable Palates" featured a lively debate on the potential synergies between dairy products and corporate profitability, underscoring the pervasive curiosity surrounding this peculiar confluence.

The confluence of these diverse sources, ranging from erudite treatises to whimsical works of fiction and informal online conversations, underscores the multidimensionality of this perplexing association. As the investigation unfolds, the interplay between serious scholarly inquiry and the lighthearted musings of cheese aficionados offers a captivating tapestry for unraveling the mysteries of the enigmatic bond between American cheese consumption and Google's Annual Global Revenue.

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 American cheese consumption and Google's Annual Global Revenue. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from USDA and Statista . You used data from 2002 to 2021

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]]
Put to the Test: Does American Cheese Bring Google's Profits to Their Knees?

[[ABSTRACT]]
This study elucidates the purported puzzling relationship between American cheese consumption and Google's Annual Global Revenue. Leveraging comprehensive data from the USDA and Statista, a correlation coefficient of 0.9638770 and p < 0.01 for the timeframe 2002 to 2021 were revealed, astonishing the research team. The findings highlight a striking, albeit confounding, connection between these seemingly incongruous entities. The implications of our results invite further scrutiny into the influence of cheese consumption on digital empires, lending credence to the adage, "cheddar makes everything better," including search engines.

[[INTRODUCTION]]
The relationship between American cheese consumption and corporate financial performance has long been an enigma in both the culinary and economic realms, provoking curiosity and skepticism alike. Despite their apparent disparity, the luscious world of creamy, processed cheese slices and the cerebral domain of algorithms and search engine dominance have been linked, albeit tentatively, in the annals of popular culture and scholarly discourse.
Historically, the influence of American cheese on the fiscal health of global corporations has been overlooked, overshadowed by more conventional factors such as market demand, technological advancements, and global economic conditions. However, recent anecdotal evidence and murmurs within the blogosphere have suggested an unforeseen connection between American cheese and the staggering profits of a certain ubiquitous internet company.
The present study aims to probe this purported association with a meticulous and systematic approach, applying a rigorous statistical analysis to disentangle the complex web of potential causative factors and confounding variables. Leveraging extensive datasets from the USDA and Statista, encompassing a span of two decades, the research team sought to unveil the veracity of the speculated bond between American cheese consumption and Google's Annual Global Revenue.
Indeed, the preliminary findings yielded a coefficient of correlation that seized the attention of the entire research cohort, with a value of 0.9638770 and a statistically significant p-value below 0.01, defying initial expectations and prompting fervent discussions and raised eyebrows among the academic circles involved. The implications of these results, though far-reaching, remain perplexing, raising intriguing questions about the underlying mechanisms that could underpin such an unexpected affiliation.
As we delve into the multifaceted layers of this unlikely alliance, it becomes evident that the intertwining of these ostensibly distinct entities may hold implications that extend beyond the mere intersection of gastronomic delights and corporate prowess. As our foray into this uncharted terrain unfolds, the enigmatic relationship between American cheese and Google's financial fortunes beckons further investigation, inviting scholars to contemplate the unfathomable ways in which the world of dairy and the digital domain may intertwine.
The perplexing connection revealed by our analysis serves as a stark reminder of the unconventional pathways through which economic forces may manifest, prompting us to reflect on the intriguing aphorism, "cheddar makes everything better," which now seems to extend its influence even to the digital landscape. As we navigate through the intricate labyrinth of associations and correlations, the implications of our findings may not only illuminate the curious bond between American cheese and corporate prosperity but also redefine the contours of synergy in an increasingly interlinked global economy.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The determination of the potential relationship between American cheese consumption and Google's Annual Global Revenue commenced with the acquisition and curation of extensive datasets spanning the years 2002 to 2021. The preeminent sources of data included the United States Department of Agriculture (USDA) and Statista, both renowned repositories of information pertaining to the consumption of dairy products and the financial performance of corporate entities, respectively.

The research team employed a multifaceted approach, integrating methods from econometrics, market analysis, and gastronomic sociology to navigate the labyrinthine landscape of cheese consumption and corporate profit margins. Utilizing advanced statistical techniques, including linear regression analysis and time series modeling, the team endeavored to distill the essence of the purported nexus between these seemingly dichotomous entities.

Moreover, in an effort to capture the nuances of American cheese consumption and its potential impact on Google's financial fortunes, the research team also conducted sentiment analysis of online discourse pertaining to cheese preferences and digital market trends. Leveraging natural language processing algorithms and sentiment classification models, the team sought to unravel the latent sentiments and subconscious inclinations that may underscore the observed correlation.

Furthermore, to probe the anecdotal conjectures and recurring whispers within the digital sphere, the research team also embarked on a qualitative inquiry, engaging in in-depth interviews with industry experts, cheese connoisseurs, and tech aficionados. The aim of these interviews was to glean insights into the subtle undercurrents of consumer behavior and the intricacies of digital advertising dynamics, shedding light on the covert influences that could underpin the unexpected convergence of cheese and corporate prosperity.

In amalgamating these diverse methodological modalities, the research team aspired to construct a comprehensive, panoramic view of the purported association, endeavoring to capture the elusive essence of the enigmatic bond between American cheese and Google's financial eminence. The convergence of disparate disciplines and analytical techniques aimed to not only uncover statistical correlations but also to unravel the underlying narratives and latent forces that may animate this captivating interplay of gastronomy and commerce.

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 American cheese consumption and Google's Annual Global Revenue. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from USDA and Statista .

For the time period 2002 to 2021, you found a correlation 0.9638770, r-squared of 0.9290588, 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]]
Put to the Test: Does American Cheese Bring Google's Profits to Their Knees?

[[ABSTRACT]]
This study elucidates the purported puzzling relationship between American cheese consumption and Google's Annual Global Revenue. Leveraging comprehensive data from the USDA and Statista, a correlation coefficient of 0.9638770 and p < 0.01 for the timeframe 2002 to 2021 were revealed, astonishing the research team. The findings highlight a striking, albeit confounding, connection between these seemingly incongruous entities. The implications of our results invite further scrutiny into the influence of cheese consumption on digital empires, lending credence to the adage, "cheddar makes everything better," including search engines.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The relationship between American cheese consumption and corporate financial performance has long been an enigma in both the culinary and economic realms, provoking curiosity and skepticism alike. Despite their apparent disparity, the luscious world of creamy, processed cheese slices and the cerebral domain of algorithms and search engine dominance have been linked, albeit tentatively, in the annals of popular culture and scholarly discourse.
Historically, the influence of American cheese on the fiscal health of global corporations has been overlooked, overshadowed by more conventional factors such as market demand, technological advancements, and global economic conditions. However, recent anecdotal evidence and murmurs within the blogosphere have suggested an unforeseen connection between American cheese and the staggering profits of a certain ubiquitous internet company.
The present study aims to probe this purported association with a meticulous and systematic approach, applying a rigorous statistical analysis to disentangle the complex web of potential causative factors and confounding variables. Leveraging extensive datasets from the USDA and Statista, encompassing a span of two decades, the research team sought to unveil the veracity of the speculated bond between American cheese consumption and Google's Annual Global Revenue.
Indeed, the preliminary findings yielded a coefficient of correlation that seized the attention of the entire research cohort, with a value of 0.9638770 and a statistically significant p-value below 0.01, defying initial expectations and prompting fervent discussions and raised eyebrows among the academic circles involved. The implications of these results, though far-reaching, remain perplexing, raising intriguing questions about the underlying mechanisms that could underpin such an unexpected affiliation.
As we delve into the multifaceted layers of this unlikely alliance, it becomes evident that the intertwining of these ostensibly distinct entities may hold implications that extend beyond the mere intersection of gastronomic delights and corporate prowess. As our foray into this uncharted terrain unfolds, the enigmatic relationship between American cheese and Google's financial fortunes beckons further investigation, inviting scholars to contemplate the unfathomable ways in which the world of dairy and the digital domain may intertwine.
The perplexing connection revealed by our analysis serves as a stark reminder of the unconventional pathways through which economic forces may manifest, prompting us to reflect on the intriguing aphorism, "cheddar makes everything better," which now seems to extend its influence even to the digital landscape. As we navigate through the intricate labyrinth of associations and correlations, the implications of our findings may not only illuminate the curious bond between American cheese and corporate prosperity but also redefine the contours of synergy in an increasingly interlinked global economy.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of the relationship between American cheese consumption and Google's Annual Global Revenue from 2002 to 2021 revealed a remarkably high correlation coefficient of 0.9638770, indicating a strong positive relationship between the two variables. The coefficient of determination (r-squared) of 0.9290588 further underscores the robustness of this association, suggesting that approximately 92.9% of the variability in Google's Annual Global Revenue can be explained by fluctuations in American cheese consumption. The p-value of less than 0.01 indicates that the observed correlation is statistically significant, dispelling any initial doubts about the legitimacy of this peculiar connection.

In Figure 1, the scatterplot visually depicts the striking correlation between American cheese consumption and Google's Annual Global Revenue, with the data points aligning closely along a positively sloped trend line.

The strength of the association uncovered in this investigation has left the research team astounded, prompting contemplation of the potential mechanisms underlying this unexpected nexus. These findings challenge conventional notions about the factors influencing corporate financial performance, offering a tantalizing glimpse into the uncharted interplay between gastronomic preferences and digital prosperity.

The implications of this study extend far beyond the realm of statistical analysis, challenging preconceived notions about the role of American cheese in shaping the fortunes of global corporations. The unexpected alignment of these seemingly disparate entities invites further scholarly inquiry into the intricate interdependencies within the global economy, reinforcing the enduring adage that "cheddar makes everything better," even in the most unanticipated contexts.

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 American cheese consumption and Google's Annual Global Revenue. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Put to the Test: Does American Cheese Bring Google's Profits to Their Knees?

[[ABSTRACT]]
This study elucidates the purported puzzling relationship between American cheese consumption and Google's Annual Global Revenue. Leveraging comprehensive data from the USDA and Statista, a correlation coefficient of 0.9638770 and p < 0.01 for the timeframe 2002 to 2021 were revealed, astonishing the research team. The findings highlight a striking, albeit confounding, connection between these seemingly incongruous entities. The implications of our results invite further scrutiny into the influence of cheese consumption on digital empires, lending credence to the adage, "cheddar makes everything better," including search engines.

[[LITERATURE REVIEW]]
The investigation into the purported relationship between American cheese consumption and Google's Annual Global Revenue represents a substantial departure from conventional economic analyses. While the entanglement of these two seemingly incongruent entities may defy logic and strain the bounds of credulity, the extant literature provides a foundation for this unexpected inquiry.
Smith et al. (2014) assert that the correlation between gastronomic trends and corporate financial performance remains an underexplored domain within economic scholarship. Similarly, Doe and Jones (2018) remark that unconventional factors, such as cultural phenomena and consumer behavior, may exert unforeseen influences on the market dynamics of multinational corporations. However, the examination of a direct nexus between American cheese consumption and the fiscal fortunes of a technology behemoth such as Google remains scarce in the scholarly sphere.
Moving beyond the realm of conventional economic discourse, the present investigation draws insights from a nuanced examination of culinary trends and their enigmatic manifestations in the corporate arena. In "The Economics of Cheese: A Gouda Guide to Dairy Dynamics" by von Meltzer (2016), the author articulates the profound impact of cheese consumption on societal structures and consumer preferences, laying the groundwork for an expanded understanding of the potential influence of such gustatory inclinations on larger economic phenomena.
In a departure from traditional economic texts, the fictitious work "The Sinister Science of Swiss: How Cheese Dictates Destiny" by Cheddar, Brie, and Roquefort (2019) delves into the whimsical and whimsically exaggerated world of cheese-related conspiracies, providing an offbeat yet thought-provoking exploration of the interconnectedness between dairy delicacies and global hegemony. The satirical treatment of this subject matter offers a departure from the conventional scholarly rigueur, challenging readers to consider the unorthodox and unexplored avenues of economic inquiry.
Furthermore, anecdotal evidence gleaned from the blogosphere and social media platforms has contributed to the discourse surrounding the unlikely entwining of American cheese and Google's financial trajectories. A Twitter user, @CheeseEnthusiast47, mused that "perhaps Google's algorithm finds inspiration in the nuanced flavors of American cheese, leading to superior search results," prompting a mixture of amusement and bewilderment within the digital enclave. Similarly, a Reddit thread titled "Cheese, Please: A Quest for Profitable Palates" featured a lively debate on the potential synergies between dairy products and corporate profitability, underscoring the pervasive curiosity surrounding this peculiar confluence.
The confluence of these diverse sources, ranging from erudite treatises to whimsical works of fiction and informal online conversations, underscores the multidimensionality of this perplexing association. As the investigation unfolds, the interplay between serious scholarly inquiry and the lighthearted musings of cheese aficionados offers a captivating tapestry for unraveling the mysteries of the enigmatic bond between American cheese consumption and Google's Annual Global Revenue.

[[RESULTS]]
The analysis of the relationship between American cheese consumption and Google's Annual Global Revenue from 2002 to 2021 revealed a remarkably high correlation coefficient of 0.9638770, indicating a strong positive relationship between the two variables. The coefficient of determination (r-squared) of 0.9290588 further underscores the robustness of this association, suggesting that approximately 92.9% of the variability in Google's Annual Global Revenue can be explained by fluctuations in American cheese consumption. The p-value of less than 0.01 indicates that the observed correlation is statistically significant, dispelling any initial doubts about the legitimacy of this peculiar connection.
In Figure 1, the scatterplot visually depicts the striking correlation between American cheese consumption and Google's Annual Global Revenue, with the data points aligning closely along a positively sloped trend line.
The strength of the association uncovered in this investigation has left the research team astounded, prompting contemplation of the potential mechanisms underlying this unexpected nexus. These findings challenge conventional notions about the factors influencing corporate financial performance, offering a tantalizing glimpse into the uncharted interplay between gastronomic preferences and digital prosperity.
The implications of this study extend far beyond the realm of statistical analysis, challenging preconceived notions about the role of American cheese in shaping the fortunes of global corporations. The unexpected alignment of these seemingly disparate entities invites further scholarly inquiry into the intricate interdependencies within the global economy, reinforcing the enduring adage that "cheddar makes everything better," even in the most unanticipated contexts.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study lend support to the prior research investigating the perplexing connection between American cheese consumption and Google's Annual Global Revenue. The correlation coefficient of 0.9638770 echoes the sentiments expressed by von Meltzer (2016), who emphasized the profound impact of cheese consumption on societal structures and consumer preferences. The robust association uncovered in this investigation aligns with the implications advanced by Doe and Jones (2018), who underscored the potential influence of cultural phenomena and consumer behavior on the market dynamics of multinational corporations. The statistical significance of the observed correlation, with a p-value of less than 0.01, affirms the assertions made by Smith et al. (2014) regarding the underexplored domain of gastronomic trends and corporate financial performance. The unexpected nexus elucidated in this study thus resonates with the foundational insights provided by prior scholarship, underscoring the validity of expanding the economic discourse to encompass non-traditional influences.

Furthermore, the seemingly incongruous relationship between American cheese consumption and Google's financial prosperity challenges established paradigms, echoing the whimsical insights put forth by Cheddar, Brie, and Roquefort (2019) in their fictitious work "The Sinister Science of Swiss: How Cheese Dictates Destiny." By inviting a departure from traditional economic discourse, this peculiar correlation prompts contemplation of unorthodox and unexplored avenues of economic inquiry, aligning with the provocatively exaggerated musings of the authors. In this sense, the present investigation echoes the multidimensionality of economic phenomena, encapsulated in a tapestry that juxtaposes rigorous statistical analysis with the enigmatic whimsy of culinary conspiracies.

The unexpected alignment of American cheese consumption and Google's Annual Global Revenue challenges conventional wisdom about the drivers of corporate financial performance, echoing the lighthearted musings of @CheeseEnthusiast47 on Twitter and the lively debate featured in the Reddit thread "Cheese, Please: A Quest for Profitable Palates." The pervasive curiosity surrounding this unconventional confluence underscores the intricate interdependencies within the global economy, underscoring the enduring adage that "cheddar makes everything better," even in the most unanticipated contexts. The implications of this study extend beyond statistical analysis, beckoning further scholarly inquiry into the entwined dynamics of gastronomic preferences and digital empires, aligning with the adage and lending credence to the potential influence of cheese consumption on digital magnates.

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 American cheese consumption and Google's Annual Global Revenue. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Put to the Test: Does American Cheese Bring Google's Profits to Their Knees?

[[ABSTRACT]]
This study elucidates the purported puzzling relationship between American cheese consumption and Google's Annual Global Revenue. Leveraging comprehensive data from the USDA and Statista, a correlation coefficient of 0.9638770 and p < 0.01 for the timeframe 2002 to 2021 were revealed, astonishing the research team. The findings highlight a striking, albeit confounding, connection between these seemingly incongruous entities. The implications of our results invite further scrutiny into the influence of cheese consumption on digital empires, lending credence to the adage, "cheddar makes everything better," including search engines.

[[INTRDUCTION]]
The relationship between American cheese consumption and corporate financial performance has long been an enigma in both the culinary and economic realms, provoking curiosity and skepticism alike. Despite their apparent disparity, the luscious world of creamy, processed cheese slices and the cerebral domain of algorithms and search engine dominance have been linked, albeit tentatively, in the annals of popular culture and scholarly discourse.
Historically, the influence of American cheese on the fiscal health of global corporations has been overlooked, overshadowed by more conventional factors such as market demand, technological advancements, and global economic conditions. However, recent anecdotal evidence and murmurs within the blogosphere have suggested an unforeseen connection between American cheese and the staggering profits of a certain ubiquitous internet company.
The present study aims to probe this purported association with a meticulous and systematic approach, applying a rigorous statistical analysis to disentangle the complex web of potential causative factors and confounding variables. Leveraging extensive datasets from the USDA and Statista, encompassing a span of two decades, the research team sought to unveil the veracity of the speculated bond between American cheese consumption and Google's Annual Global Revenue.
Indeed, the preliminary findings yielded a coefficient of correlation that seized the attention of the entire research cohort, with a value of 0.9638770 and a statistically significant p-value below 0.01, defying initial expectations and prompting fervent discussions and raised eyebrows among the academic circles involved. The implications of these results, though far-reaching, remain perplexing, raising intriguing questions about the underlying mechanisms that could underpin such an unexpected affiliation.
As we delve into the multifaceted layers of this unlikely alliance, it becomes evident that the intertwining of these ostensibly distinct entities may hold implications that extend beyond the mere intersection of gastronomic delights and corporate prowess. As our foray into this uncharted terrain unfolds, the enigmatic relationship between American cheese and Google's financial fortunes beckons further investigation, inviting scholars to contemplate the unfathomable ways in which the world of dairy and the digital domain may intertwine.
The perplexing connection revealed by our analysis serves as a stark reminder of the unconventional pathways through which economic forces may manifest, prompting us to reflect on the intriguing aphorism, "cheddar makes everything better," which now seems to extend its influence even to the digital landscape. As we navigate through the intricate labyrinth of associations and correlations, the implications of our findings may not only illuminate the curious bond between American cheese and corporate prosperity but also redefine the contours of synergy in an increasingly interlinked global economy.

[[RESULTS]]
The analysis of the relationship between American cheese consumption and Google's Annual Global Revenue from 2002 to 2021 revealed a remarkably high correlation coefficient of 0.9638770, indicating a strong positive relationship between the two variables. The coefficient of determination (r-squared) of 0.9290588 further underscores the robustness of this association, suggesting that approximately 92.9% of the variability in Google's Annual Global Revenue can be explained by fluctuations in American cheese consumption. The p-value of less than 0.01 indicates that the observed correlation is statistically significant, dispelling any initial doubts about the legitimacy of this peculiar connection.
In Figure 1, the scatterplot visually depicts the striking correlation between American cheese consumption and Google's Annual Global Revenue, with the data points aligning closely along a positively sloped trend line.
The strength of the association uncovered in this investigation has left the research team astounded, prompting contemplation of the potential mechanisms underlying this unexpected nexus. These findings challenge conventional notions about the factors influencing corporate financial performance, offering a tantalizing glimpse into the uncharted interplay between gastronomic preferences and digital prosperity.
The implications of this study extend far beyond the realm of statistical analysis, challenging preconceived notions about the role of American cheese in shaping the fortunes of global corporations. The unexpected alignment of these seemingly disparate entities invites further scholarly inquiry into the intricate interdependencies within the global economy, reinforcing the enduring adage that "cheddar makes everything better," even in the most unanticipated contexts.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the prodigious correlation coefficient and statistically significant p-value unearthed in this investigation underscore the remarkable relationship between American cheese consumption and Google's Annual Global Revenue from 2002 to 2021. The findings have ripened into a delectable morsel of insight, challenging the conventional wisdom that economics and gastronomy operate in separate realms. This unexpected connection beckons us to ponder whether the soothing influence of melted cheese extends beyond palates into the digital stratosphere, shaping the profitability of tech giants. The data, much like a well-aged cheddar, has matured into a robust and flavorsome revelation, leaving us to savor the unlikely congruence between these seemingly incongruous entities.

The apparent symbiosis between American cheese and Google's financial mettle poses a tantalizing enigma, dousing skepticism with a generous layer of melted provolone. However, it also underscores the need for further exploration into the intricacies of this unanticipated accord. While the current study has shed light on the tangible bond between these ostensibly unrelated variables, the mechanisms driving this interplay remain as enigmatic as the origins of Swiss cheese. As we nibble at the edges of this intriguing intersection, the tantalizing aroma of Gouda and the allure of search engine algorithms remind us that, in the tapestry of global commerce, unexpected partnerships can yield a surprising symphony.

As such, it is evident that the intersection of American cheese consumption and corporate revenue is a fertile ground for scholarly investigation, replete with flavor and potential far beyond what was initially imagined. However, in light of the compelling findings of this study, it can be confidently asserted that no further research in this area is warranted. For as the old saying goes, "When the cheese stands alone, there's no need for further digging." Therefore, it is concluded that this study has cheddar every insight into this intriguing relationship and that further research is not gouda-nough.

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 Put to the Test: Does American Cheese Bring Google's Profits to Their Knees?. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Whimsical Economic Studies

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 Put to the Test: Does American Cheese Bring Google's Profits to Their Knees?. Respond only with the name of a fictional organization.

ChatGPT:

The International Institute for Dairy Industry Research and Analysis

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Put to the Test: Does American Cheese Bring Google's Profits to Their Knees? with an abstract of This study elucidates the purported puzzling relationship between American cheese consumption and Google's Annual Global Revenue. Leveraging comprehensive data from the USDA and Statista, a correlation coefficient of 0.9638770 and p < 0.01 for the timeframe 2002 to 2021 were revealed, astonishing the research team. The findings highlight a striking, albeit confounding, connection between these seemingly incongruous entities. The implications of our results invite further scrutiny into the influence of cheese consumption on digital empires, lending credence to the adage, "cheddar makes everything better," including search engines.

ChatGPT:

"American cheese consumption," "Google's annual global revenue," "USDA data," "Statista data," "correlation coefficient," "cheese consumption influence on digital empires," "relationship between cheese consumption and technology companies," "food industry impact on tech companies," "impact of cheese consumption on search engines"

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

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Data details

American cheese consumption
Detailed data title: Per capita consumption of American cheese in the US
Source: USDA
See what else correlates with American cheese consumption

Google's Annual Global Revenue
Source: Statista
See what else correlates with Google's Annual Global Revenue

Correlation r = 0.9638770 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.9290588 (Coefficient of determination)
This means 92.9% of the change in the one variable (i.e., Google's Annual Global Revenue) is predictable based on the change in the other (i.e., American cheese consumption) over the 20 years from 2002 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 8.7E-12.^Show 0.0000000000087235793658296860
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.96 in 8.7E-10% of random cases. Said differently, if you correlated 114,631,845,263 random variables^Note You don't actually need 114 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 19 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.91, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
American cheese consumption (Pounds per person)	12.8314	12.5619	12.8612	12.649	13.0656	12.7929	13.1306	13.3553	13.3048	13.0392	13.2569	13.3573	13.6656	14.0444	14.3621	15.0901	15.4027	15.5389	15.5	16.1
Google's Annual Global Revenue (Dollars)	400000000	1500000000	3200000000	6100000000	10600000000	16600000000	21800000000	23700000000	29300000000	37900000000	50180000000	55810000000	65670000000	74540000000	89980000000	110550000000	136360000000	160740000000	181690000000	256740000000

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([12.8314,12.5619,12.8612,12.649,13.0656,12.7929,13.1306,13.3553,13.3048,13.0392,13.2569,13.3573,13.6656,14.0444,14.3621,15.0901,15.4027,15.5389,15.5,16.1,])
array_2 = np.array([400000000,1500000000,3200000000,6100000000,10600000000,16600000000,21800000000,23700000000,29300000000,37900000000,50180000000,55810000000,65670000000,74540000000,89980000000,110550000000,136360000000,160740000000,181690000000,256740000000,])
array_1_name = "American cheese consumption"
array_2_name = "Google's Annual Global Revenue"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only American cheese consumption
Line chart for only Google's Annual Global Revenue
The spurious research paper: Put to the Test: Does American Cheese Bring Google's Profits to Their Knees?

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Correlation ID: 1199 · Black Variable ID: 553 · Red Variable ID: 117


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