Spurious correlation #2,270 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of bailiffs in Kansas and the second variable is Google searches for 'that is sus'. The chart goes from 2004 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of bailiffs in Kansas and the second variable is Google searches for 'that is sus'. The chart goes from 2004 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of bailiffs in Kansas rose, so did the sense of suspicion in the air. This led to a surge in people pondering what was truly sus, slowly turning the state into a hotbed of detective work. It seems the bailiffs weren't just serving justice, but also serving up some real sus-pense, leading to a criminal increase in sus-pect behavior overall. It's safe to say, the bailiffs inadvertently became the sus-pects of this strange correlation, leaving everyone to wonder, "To bailiff or not to bailiff?"

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an inviting visual of a lively Kansas courthouse scene, where a group of bailiffs stands ready at the entrance, exuding authority and preparedness. Inside the courthouse, capture the opening of the courtroom doors to reveal judges and lawyers in session, creating a sense of anticipation and the legal process in action. Meanwhile, showcase a nearby café, where a group of friends huddles around a table, their smartphones aglow as they excitedly search for "that is sus" on Google, adding a modern and relatable element to the scene. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: The number of bailiffs in Kansas and Google searches for 'that is sus'. 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: A Discovery magazine cover image inspired by bauhaus Realistic A TIME magazine cover image Charcoal
ChatGPT: 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 The number of bailiffs in Kansas and Google searches for 'that is sus' together. Keep the description simple.
ChatGPT: In a lively Kansas courthouse, a group of bailiffs stands ready at the entrance, while inside, courtroom doors open to reveal judges and lawyers in session. Meanwhile, at a nearby café, a group of friends huddles around a table, their smartphones aglow as they excitedly search for "that is sus" on Google.

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: [ Realistic ] and depicting this scene: In a lively Kansas courthouse, a group of bailiffs stands ready at the entrance, while inside, courtroom doors open to reveal judges and lawyers in session. Meanwhile, at a nearby café, a group of friends huddles around a table, their smartphones aglow as they excitedly search for "that is sus" on Google. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an inviting visual of a lively Kansas courthouse scene, where a group of bailiffs stands ready at the entrance, exuding authority and preparedness. Inside the courthouse, capture the opening of the courtroom doors to reveal judges and lawyers in session, creating a sense of anticipation and the legal process in action. Meanwhile, showcase a nearby café, where a group of friends huddles around a table, their smartphones aglow as they excitedly search for "that is sus" on Google, adding a modern and relatable element to the scene.

*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 The number of bailiffs in Kansas caused that is sus (Google searches for 'that is sus') to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

The Bailiff Ballyhoo: Examining the Correlation Between Bailiff Employment in Kansas and Google Searches for 'That is sus'

The Journal of Legal Laughter

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of bailiffs in Kansas and Google searches for 'that is sus'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some movies that you watched that are tangentially related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
"The Bailiff Ballyhoo: Examining the Correlation Between Bailiff Employment in Kansas and Google Searches for 'That is sus'"

[[ABSTRACT]]
The relationship between bailiff employment and online activity has been a subject of growing interest in the field of socio-digital dynamics. In this study, we explore the potential connection between the number of bailiffs in the state of Kansas and Google searches for the colloquial expression "that is sus." Leveraging data from the Bureau of Labor Statistics and Google Trends, we conducted a comprehensive analysis spanning the years 2004 to 2022. Our findings revealed a remarkably strong correlation coefficient of 0.9367474, with a significance level of p < 0.01, underscoring the intriguing relationship between these seemingly disparate phenomena. The implications of these results extend beyond mere statistical curiosities, hinting at underlying socio-cultural undercurrents and possibly the existence of a "bailiff effect" on online discourse. This research sheds light on the often unpredictable intersections of digital behavior and societal structures, highlighting the whimsical nature of modern data analysis.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The intertwining of technological advancements, societal behaviors, and institutional dynamics has led to a burgeoning interest in the study of socio-digital dynamics. As digital footprints become increasingly ubiquitous, researchers seek to unravel the enigmatic connections between seemingly unrelated phenomena. One such endeavor delves into the intriguing relationship between the number of bailiffs in a state and the online vernacular encompassed by the colloquial phrase "that is sus."
At first blush, the correlation between bailiff employment in the state of Kansas and Google searches for "that is sus" may appear as tangential as a non-significant p-value. However, as we embark on this investigation, we are compelled to discern whether there exists a potent statistical liaison between these seemingly disparate domains.
As we endeavor to unravel this perplexing correlation, we confront the ever-present challenge of disentangling causation from mere co-occurrence. The inherent complexities of socio-digital interactions and their multifaceted underpinnings beckon us to delve into the treasure trove of statistical analyses with the same fervor as a hungry scholar scavenging for methodology insights.
Our pursuit of this connection is not merely motivated by statistical curiosity but rather by the insatiable thirst for knowledge of the serendipitous corollaries that emerge from our analysis. Through this research, we aim to illuminate the often capricious confluence of online behaviors and institutional constructs, revealing the whimsical interplay of socio-cultural nuances akin to a scholarly game of hide-and-seek with elusive data patterns.
Thus, as we embark on this scholarly escapade, we brace ourselves for an exploration that promises to unravel the clandestine associations between bailiff employment and online colloquialisms. With one foot poised in the realm of empirical rigor and the other in the realm of digital lexicon, we tiptoe through the academic landscape, poised to unearth revelations that exemplify the playful nature of modern data analysis.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith and Doe," the authors find a nuanced relationship between institutional employment and digital discourse, shedding light on the intricate interplay of socio-digital dynamics. Similarly, Jones et al. emphasize the need to scrutinize the often enigmatic connections that transcend conventional disciplinary boundaries, compelling researchers to examine the unexpected alliances that emerge in the digital age.

Turning to the broader discourse surrounding socio-digital interactions, "The Digital Footprint Phenomenon" by Brown and Miller delves into the ubiquity of online activities and their potential implications for institutional phenomena. Their work highlights the need to navigate the labyrinth of digital footprints with the same meticulousness as a detective combing through clues, seeking to unearth the underlying connections that elude the untrained eye.

To expand beyond the confines of specific academic research, the exploration of sociocultural phenomena and their digital reverberations prompts us to consider non-fiction works such as "The Social Fabric of Online Interactions" by Johnson and "Digital Echoes: Exploring Virtual Social Constructs" by Clark. These works, metaphorically speaking, act as guiding stars in our quest to decipher the whimsical dance between social institutions and digital expressions.

In addition, the landscape of fiction literature offers tantalizing narratives that, although not steeped in empirical evidence, nevertheless capture the imagination and prompt us to contemplate the parallels between online phenomena and institutional realities. Titles such as "The Bailiff's Dilemma" by A. Finch and "Digital Suspicions: A Cyberthriller" by R. J. Evans, while purely fictional, provide a lighthearted entry point into the whimsical nature of our scholarly pursuit.

Furthermore, our interdisciplinary exploration wouldn't be complete without a nod to cinematic representations that, in their own cinematic universe, offer glimpses of tangentially related themes. Films such as "Suspect Pursuit" and "Digital Bailiffs: The Cyber-Infiltration" dip their toes into the realm of the unexpected, inviting us to ponder the playful crossovers between offline institutions and online expressions.

As we wade through this interdisciplinary tapestry, it's imperative to maintain a sense of scholarly curiosity while recognizing the lighthearted and capricious nature of this pursuit. Our journey into the realm of bailiff employment and online colloquialisms promises to be as unexpected and humorous as stumbling upon a statistical anomaly in the labyrinth of data analysis.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between The number of bailiffs in Kansas and Google searches for 'that is sus'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Larbor Statistics and Google Trends . You used data from 2004 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]]
"The Bailiff Ballyhoo: Examining the Correlation Between Bailiff Employment in Kansas and Google Searches for 'That is sus'"

[[ABSTRACT]]
The relationship between bailiff employment and online activity has been a subject of growing interest in the field of socio-digital dynamics. In this study, we explore the potential connection between the number of bailiffs in the state of Kansas and Google searches for the colloquial expression "that is sus." Leveraging data from the Bureau of Labor Statistics and Google Trends, we conducted a comprehensive analysis spanning the years 2004 to 2022. Our findings revealed a remarkably strong correlation coefficient of 0.9367474, with a significance level of p < 0.01, underscoring the intriguing relationship between these seemingly disparate phenomena. The implications of these results extend beyond mere statistical curiosities, hinting at underlying socio-cultural undercurrents and possibly the existence of a "bailiff effect" on online discourse. This research sheds light on the often unpredictable intersections of digital behavior and societal structures, highlighting the whimsical nature of modern data analysis.

[[INTRODUCTION]]
INTRODUCTION
The intertwining of technological advancements, societal behaviors, and institutional dynamics has led to a burgeoning interest in the study of socio-digital dynamics. As digital footprints become increasingly ubiquitous, researchers seek to unravel the enigmatic connections between seemingly unrelated phenomena. One such endeavor delves into the intriguing relationship between the number of bailiffs in a state and the online vernacular encompassed by the colloquial phrase "that is sus."
At first blush, the correlation between bailiff employment in the state of Kansas and Google searches for "that is sus" may appear as tangential as a non-significant p-value. However, as we embark on this investigation, we are compelled to discern whether there exists a potent statistical liaison between these seemingly disparate domains.
As we endeavor to unravel this perplexing correlation, we confront the ever-present challenge of disentangling causation from mere co-occurrence. The inherent complexities of socio-digital interactions and their multifaceted underpinnings beckon us to delve into the treasure trove of statistical analyses with the same fervor as a hungry scholar scavenging for methodology insights.
Our pursuit of this connection is not merely motivated by statistical curiosity but rather by the insatiable thirst for knowledge of the serendipitous corollaries that emerge from our analysis. Through this research, we aim to illuminate the often capricious confluence of online behaviors and institutional constructs, revealing the whimsical interplay of socio-cultural nuances akin to a scholarly game of hide-and-seek with elusive data patterns.
Thus, as we embark on this scholarly escapade, we brace ourselves for an exploration that promises to unravel the clandestine associations between bailiff employment and online colloquialisms. With one foot poised in the realm of empirical rigor and the other in the realm of digital lexicon, we tiptoe through the academic landscape, poised to unearth revelations that exemplify the playful nature of modern data analysis.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

METHODOLOGY

Gathering data for this beguiling investigation involved a whimsical blend of statistical sleuthing and online reconnaissance, akin to a scholarly expedition through the digital savannah. Our intrepid team embarked on a triumphant quest for information, scouring the digital archives with a fervor reminiscent of a turkey searching for breadcrumbs in a forest of statistical significance.

Data on the number of bailiffs employed in the state of Kansas was obtained from the venerable Bureau of Labor Statistics, a veritable treasure trove of employment information. We navigated through the labyrinthine corridors of labor data, employing our keen analytical prowess to extricate the pertinent figures from the sea of bureaucratic jargon and statistical esoterica.

In parallel, our foray into the digital realm of colloquial expression was facilitated by the esteemed Google Trends, a beacon of insight into the curious ebbs and flows of online vernacular. Using this digital oracle, we harnessed the power of search query data to track the frequency of Google searches for the phrase "that is sus" from the year 2004 to 2022, akin to eavesdropping on a conclave of lexical aficionados discussing the latest parlance trends.

The disparate nature of these data sources, akin to an unexpected fusion of spaghetti and marshmallows, presented unique challenges in reconciling the divergent variables. Our rigorous statistical framework meticulously integrated these various data streams, fashioning an analytical tapestry that interwove the austere realities of bailiff employment with the whimsical cadence of digital lexicon.

With the data firmly in our grasp, we harnessed the formidable powers of statistical analysis, akin to wielding a multidimensional telescope to discern the celestial ballet of bailiffs and online vernacular. Employing a variety of analytical techniques, including correlation analysis and regression modeling, we embarked on a statistical odyssey, navigating through the treacherous waters of confounding variables and spurious correlations with the dexterity of a sommelier discerning the nuances of statistical vintages.

Furthermore, to ensure the robustness and generalizability of our findings, we conducted rigorous sensitivity analyses and validation procedures, akin to stress-testing a theoretical theorem in the high-stakes arena of academia. By scrutinizing the stability of our results across different time periods and geographical regions, we endeavored to fortify the foundations of our research, fortifying our scholarly bastion against the tides of statistical skepticism.

In summary, our methodology encapsulated a vibrant mosaic of data collection, statistical jousting, and rigorous validation, culminating in a rigorously crafted framework that sought to unravel the enigmatic alliance between bailiff employment and online colloquialisms. With the data at our command, we ventured forth into the volatile territory of statistical inquiry, armed with the conviction that even the most whimsical relationships may harbor profound empirical insights.

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

Please make up the results section of an academic research paper presenting the findings of the connection between The number of bailiffs in Kansas and Google searches for 'that is sus'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Larbor Statistics and Google Trends .

For the time period 2004 to 2022, you found a correlation 0.9367474, r-squared of 0.8774957, 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]]
"The Bailiff Ballyhoo: Examining the Correlation Between Bailiff Employment in Kansas and Google Searches for 'That is sus'"

[[ABSTRACT]]
The relationship between bailiff employment and online activity has been a subject of growing interest in the field of socio-digital dynamics. In this study, we explore the potential connection between the number of bailiffs in the state of Kansas and Google searches for the colloquial expression "that is sus." Leveraging data from the Bureau of Labor Statistics and Google Trends, we conducted a comprehensive analysis spanning the years 2004 to 2022. Our findings revealed a remarkably strong correlation coefficient of 0.9367474, with a significance level of p < 0.01, underscoring the intriguing relationship between these seemingly disparate phenomena. The implications of these results extend beyond mere statistical curiosities, hinting at underlying socio-cultural undercurrents and possibly the existence of a "bailiff effect" on online discourse. This research sheds light on the often unpredictable intersections of digital behavior and societal structures, highlighting the whimsical nature of modern data analysis.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
The intertwining of technological advancements, societal behaviors, and institutional dynamics has led to a burgeoning interest in the study of socio-digital dynamics. As digital footprints become increasingly ubiquitous, researchers seek to unravel the enigmatic connections between seemingly unrelated phenomena. One such endeavor delves into the intriguing relationship between the number of bailiffs in a state and the online vernacular encompassed by the colloquial phrase "that is sus."
At first blush, the correlation between bailiff employment in the state of Kansas and Google searches for "that is sus" may appear as tangential as a non-significant p-value. However, as we embark on this investigation, we are compelled to discern whether there exists a potent statistical liaison between these seemingly disparate domains.
As we endeavor to unravel this perplexing correlation, we confront the ever-present challenge of disentangling causation from mere co-occurrence. The inherent complexities of socio-digital interactions and their multifaceted underpinnings beckon us to delve into the treasure trove of statistical analyses with the same fervor as a hungry scholar scavenging for methodology insights.
Our pursuit of this connection is not merely motivated by statistical curiosity but rather by the insatiable thirst for knowledge of the serendipitous corollaries that emerge from our analysis. Through this research, we aim to illuminate the often capricious confluence of online behaviors and institutional constructs, revealing the whimsical interplay of socio-cultural nuances akin to a scholarly game of hide-and-seek with elusive data patterns.
Thus, as we embark on this scholarly escapade, we brace ourselves for an exploration that promises to unravel the clandestine associations between bailiff employment and online colloquialisms. With one foot poised in the realm of empirical rigor and the other in the realm of digital lexicon, we tiptoe through the academic landscape, poised to unearth revelations that exemplify the playful nature of modern data analysis.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis of the data gathered from the Bureau of Labor Statistics and Google Trends unearthed a strikingly robust correlation between the number of bailiffs in Kansas and Google searches for "that is sus." The correlation coefficient of 0.9367474, accompanied by an r-squared value of 0.8774957, signifies a remarkably strong linear relationship between the two variables. With a p-value of less than 0.01, the evidence overwhelmingly supports the existence of a significant association, leaving naysayers with no room to squabble, much like a precise statistical model leaves no room for outliers.

The scatterplot (Fig. 1) illustrates the positively inclined data points, illustrating the synchronization between bailiff employment and the digital expression "that is sus." The steep incline of the trend line serves as a visual testament to the compelling statistical coupling, much like synchronized swimmers moving in perfect harmony, or a well-choreographed dance routine depicting the elegant correlation between bailiff deployment and digital vernacular.

These findings not only defy conventional wisdom but also beckon us to ponder the intertwining of institutional phenomena and online behavior in the grand dance of statistics, reminiscent of an intricate waltz between societal structures and digital echoes. The robustness of the relationship uncovered echoes through the corridors of academia, challenging preconceived notions and inviting further exploration, much like a riveting mystery novel that compels readers to turn the page in search of more unexpected twists and turns.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of bailiffs in Kansas and Google searches for 'that is sus'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"The Bailiff Ballyhoo: Examining the Correlation Between Bailiff Employment in Kansas and Google Searches for 'That is sus'"

[[ABSTRACT]]
The relationship between bailiff employment and online activity has been a subject of growing interest in the field of socio-digital dynamics. In this study, we explore the potential connection between the number of bailiffs in the state of Kansas and Google searches for the colloquial expression "that is sus." Leveraging data from the Bureau of Labor Statistics and Google Trends, we conducted a comprehensive analysis spanning the years 2004 to 2022. Our findings revealed a remarkably strong correlation coefficient of 0.9367474, with a significance level of p < 0.01, underscoring the intriguing relationship between these seemingly disparate phenomena. The implications of these results extend beyond mere statistical curiosities, hinting at underlying socio-cultural undercurrents and possibly the existence of a "bailiff effect" on online discourse. This research sheds light on the often unpredictable intersections of digital behavior and societal structures, highlighting the whimsical nature of modern data analysis.

[[LITERATURE REVIEW]]
In "Smith and Doe," the authors find a nuanced relationship between institutional employment and digital discourse, shedding light on the intricate interplay of socio-digital dynamics. Similarly, Jones et al. emphasize the need to scrutinize the often enigmatic connections that transcend conventional disciplinary boundaries, compelling researchers to examine the unexpected alliances that emerge in the digital age.
Turning to the broader discourse surrounding socio-digital interactions, "The Digital Footprint Phenomenon" by Brown and Miller delves into the ubiquity of online activities and their potential implications for institutional phenomena. Their work highlights the need to navigate the labyrinth of digital footprints with the same meticulousness as a detective combing through clues, seeking to unearth the underlying connections that elude the untrained eye.
To expand beyond the confines of specific academic research, the exploration of sociocultural phenomena and their digital reverberations prompts us to consider non-fiction works such as "The Social Fabric of Online Interactions" by Johnson and "Digital Echoes: Exploring Virtual Social Constructs" by Clark. These works, metaphorically speaking, act as guiding stars in our quest to decipher the whimsical dance between social institutions and digital expressions.
In addition, the landscape of fiction literature offers tantalizing narratives that, although not steeped in empirical evidence, nevertheless capture the imagination and prompt us to contemplate the parallels between online phenomena and institutional realities. Titles such as "The Bailiff's Dilemma" by A. Finch and "Digital Suspicions: A Cyberthriller" by R. J. Evans, while purely fictional, provide a lighthearted entry point into the whimsical nature of our scholarly pursuit.
Furthermore, our interdisciplinary exploration wouldn't be complete without a nod to cinematic representations that, in their own cinematic universe, offer glimpses of tangentially related themes. Films such as "Suspect Pursuit" and "Digital Bailiffs: The Cyber-Infiltration" dip their toes into the realm of the unexpected, inviting us to ponder the playful crossovers between offline institutions and online expressions.
As we wade through this interdisciplinary tapestry, it's imperative to maintain a sense of scholarly curiosity while recognizing the lighthearted and capricious nature of this pursuit. Our journey into the realm of bailiff employment and online colloquialisms promises to be as unexpected and humorous as stumbling upon a statistical anomaly in the labyrinth of data analysis.

[[RESULTS]]
The statistical analysis of the data gathered from the Bureau of Labor Statistics and Google Trends unearthed a strikingly robust correlation between the number of bailiffs in Kansas and Google searches for "that is sus." The correlation coefficient of 0.9367474, accompanied by an r-squared value of 0.8774957, signifies a remarkably strong linear relationship between the two variables. With a p-value of less than 0.01, the evidence overwhelmingly supports the existence of a significant association, leaving naysayers with no room to squabble, much like a precise statistical model leaves no room for outliers.
The scatterplot (Fig. 1) illustrates the positively inclined data points, illustrating the synchronization between bailiff employment and the digital expression "that is sus." The steep incline of the trend line serves as a visual testament to the compelling statistical coupling, much like synchronized swimmers moving in perfect harmony, or a well-choreographed dance routine depicting the elegant correlation between bailiff deployment and digital vernacular.
These findings not only defy conventional wisdom but also beckon us to ponder the intertwining of institutional phenomena and online behavior in the grand dance of statistics, reminiscent of an intricate waltz between societal structures and digital echoes. The robustness of the relationship uncovered echoes through the corridors of academia, challenging preconceived notions and inviting further exploration, much like a riveting mystery novel that compels readers to turn the page in search of more unexpected twists and turns.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this research inexorably reinforce the unprecedented correlation between the number of bailiffs in Kansas and Google searches for "that is sus." These results, which may seem as unexpected as encountering a statistically significant anomaly while frolicking through the meadows of data analysis, align closely with prior scholarly musings that underscore the whimsical and capricious nature of socio-digital interactions.

Much like a synchronized performance by a troupe of statistical acrobats, our results demonstrate a remarkably strong linear relationship, leaving skeptics with no foothold for contention. The robust correlation coefficient, akin to a sturdy oak tree weathering the statistical storm, bolsters the growing body of evidence pertaining to the entwined dance between institutional employment and the lexicon of online vernacular.

In a nod to prior scholarly ventures delving into the labyrinthine tapestry of socio-digital dynamics, our findings support and extend previous work that has hinted at the enigmatic connections transcending the conventional disciplinary boundaries. The implications of this study stretch beyond the realm of statistical curiosities, much like a brisk jog transcends the confines of a mere stroll in the park, hinting at the existence of a noteworthy "bailiff effect" on the digital discourse.

Moreover, our results echo the sentiments expressed in the whimsical works of fiction and cinema, reminding us of the lively and unpredictable nature of scholarly pursuits. The emergent parallels between bailiff deployment and online colloquialisms are akin to stumbling upon a hidden trinket in the expansive attic of socio-digital interactions, inviting further exploration and prompting academic merriment akin to a pun weaving its way through a dense scientific text.

In essence, our research affirms the need to embrace the playful and lighthearted facets of academic endeavors, recognizing that the realm of data analysis is replete with unexpected twists and turns, much like a riveting mystery novel. This study, therefore, stands as a testament to the enduring and delightful capriciousness inherent in the scholarly pursuit of unraveling the interconnected web of social institutions and digital expressions.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of bailiffs in Kansas and Google searches for 'that is sus'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"The Bailiff Ballyhoo: Examining the Correlation Between Bailiff Employment in Kansas and Google Searches for 'That is sus'"

[[ABSTRACT]]
The relationship between bailiff employment and online activity has been a subject of growing interest in the field of socio-digital dynamics. In this study, we explore the potential connection between the number of bailiffs in the state of Kansas and Google searches for the colloquial expression "that is sus." Leveraging data from the Bureau of Labor Statistics and Google Trends, we conducted a comprehensive analysis spanning the years 2004 to 2022. Our findings revealed a remarkably strong correlation coefficient of 0.9367474, with a significance level of p < 0.01, underscoring the intriguing relationship between these seemingly disparate phenomena. The implications of these results extend beyond mere statistical curiosities, hinting at underlying socio-cultural undercurrents and possibly the existence of a "bailiff effect" on online discourse. This research sheds light on the often unpredictable intersections of digital behavior and societal structures, highlighting the whimsical nature of modern data analysis.

[[INTRDUCTION]]
INTRODUCTION
The intertwining of technological advancements, societal behaviors, and institutional dynamics has led to a burgeoning interest in the study of socio-digital dynamics. As digital footprints become increasingly ubiquitous, researchers seek to unravel the enigmatic connections between seemingly unrelated phenomena. One such endeavor delves into the intriguing relationship between the number of bailiffs in a state and the online vernacular encompassed by the colloquial phrase "that is sus."
At first blush, the correlation between bailiff employment in the state of Kansas and Google searches for "that is sus" may appear as tangential as a non-significant p-value. However, as we embark on this investigation, we are compelled to discern whether there exists a potent statistical liaison between these seemingly disparate domains.
As we endeavor to unravel this perplexing correlation, we confront the ever-present challenge of disentangling causation from mere co-occurrence. The inherent complexities of socio-digital interactions and their multifaceted underpinnings beckon us to delve into the treasure trove of statistical analyses with the same fervor as a hungry scholar scavenging for methodology insights.
Our pursuit of this connection is not merely motivated by statistical curiosity but rather by the insatiable thirst for knowledge of the serendipitous corollaries that emerge from our analysis. Through this research, we aim to illuminate the often capricious confluence of online behaviors and institutional constructs, revealing the whimsical interplay of socio-cultural nuances akin to a scholarly game of hide-and-seek with elusive data patterns.
Thus, as we embark on this scholarly escapade, we brace ourselves for an exploration that promises to unravel the clandestine associations between bailiff employment and online colloquialisms. With one foot poised in the realm of empirical rigor and the other in the realm of digital lexicon, we tiptoe through the academic landscape, poised to unearth revelations that exemplify the playful nature of modern data analysis.

[[RESULTS]]
The statistical analysis of the data gathered from the Bureau of Labor Statistics and Google Trends unearthed a strikingly robust correlation between the number of bailiffs in Kansas and Google searches for "that is sus." The correlation coefficient of 0.9367474, accompanied by an r-squared value of 0.8774957, signifies a remarkably strong linear relationship between the two variables. With a p-value of less than 0.01, the evidence overwhelmingly supports the existence of a significant association, leaving naysayers with no room to squabble, much like a precise statistical model leaves no room for outliers.
The scatterplot (Fig. 1) illustrates the positively inclined data points, illustrating the synchronization between bailiff employment and the digital expression "that is sus." The steep incline of the trend line serves as a visual testament to the compelling statistical coupling, much like synchronized swimmers moving in perfect harmony, or a well-choreographed dance routine depicting the elegant correlation between bailiff deployment and digital vernacular.
These findings not only defy conventional wisdom but also beckon us to ponder the intertwining of institutional phenomena and online behavior in the grand dance of statistics, reminiscent of an intricate waltz between societal structures and digital echoes. The robustness of the relationship uncovered echoes through the corridors of academia, challenging preconceived notions and inviting further exploration, much like a riveting mystery novel that compels readers to turn the page in search of more unexpected twists and turns.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

CONCLUSION

In culmination, our investigation into the correlation between the number of bailiffs in Kansas and Google searches for "that is sus" has illuminated a remarkably robust statistical liaison. The compelling correlation coefficient of 0.9367474 reveals a synchronicity that defies conventional wisdom, akin to a surprising plot twist in a mystery novel or uncovering the punchline to an elaborate statistical joke.

The implications of this correlation extend beyond statistical curiosities, hinting at deeper socio-cultural undercurrents and possibly the existence of a "bailiff effect" on online discourse. Much like a skilled comedian who knows how to deliver a punchline, our findings underscore the whimsical and unpredictable intersections of digital behavior and institutional constructs.

In light of these revelatory findings, it is evident that no further research is needed in this area, as our exploration has unveiled a statistical connection worthy of standing as a quirky anecdote in the annals of socio-digital dynamics. The synergy between seemingly disparate variables has been unmasked, leaving us with a statistical tale that tickles the scientific fancy, much like stumbling upon a delightful surprise at the end of a rigorous research journey.

With this study, we have journeyed through the whimsical nature of modern data analysis, and in unpacking this statistical phenomena, we have embraced the unexpected twists and turns that make academic pursuits uniquely intriguing. Therefore, we assert with confidence that the bailiff ballyhoo has been thoroughly investigated, and our findings serve as a testament to the playful intrigue that underlies the scientific endeavor.

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 The Bailiff Ballyhoo: Examining the Correlation Between Bailiff Employment in Kansas and Google Searches for 'That is sus'. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Legal Laughter

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 The Bailiff Ballyhoo: Examining the Correlation Between Bailiff Employment in Kansas and Google Searches for 'That is sus'. Respond only with the name of a fictional organization.

ChatGPT:

The Society for the Advancement of Quirky Inquiries and Research (SAQIR)

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 The Bailiff Ballyhoo: Examining the Correlation Between Bailiff Employment in Kansas and Google Searches for 'That is sus' with an abstract of The relationship between bailiff employment and online activity has been a subject of growing interest in the field of socio-digital dynamics. In this study, we explore the potential connection between the number of bailiffs in the state of Kansas and Google searches for the colloquial expression "that is sus." Leveraging data from the Bureau of Labor Statistics and Google Trends, we conducted a comprehensive analysis spanning the years 2004 to 2022. Our findings revealed a remarkably strong correlation coefficient of 0.9367474, with a significance level of p < 0.01, underscoring the intriguing relationship between these seemingly disparate phenomena. The implications of these results extend beyond mere statistical curiosities, hinting at underlying socio-cultural undercurrents and possibly the existence of a "bailiff effect" on online discourse. This research sheds light on the often unpredictable intersections of digital behavior and societal structures, highlighting the whimsical nature of modern data analysis.

ChatGPT:

bailiff employment, bailiff statistics, Kansas bailiff data, Google search trends, online activity correlation, colloquial expressions, "that is sus" search trends, socio-digital dynamics, digital behavior, societal structures

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

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Data details

The number of bailiffs in Kansas
Detailed data title: BLS estimate of bailiffs in Kansas
Source: Bureau of Larbor Statistics
See what else correlates with The number of bailiffs in Kansas

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

See what else correlates with Google searches for 'that is sus'

Correlation r = 0.9367474 (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 = 0.8774957 (Coefficient of determination)
This means 87.7% of the change in the one variable (i.e., Google searches for 'that is sus') is predictable based on the change in the other (i.e., The number of bailiffs in Kansas) over the 19 years from 2004 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.6E-9.^Show 0.0000000035880319581632303000
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 0.94 in 3.6E-7% of random cases. Said differently, if you correlated 278,704,318 random variables^Note You don't actually need 278 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 18 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 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.

[ 0.84, 0.98 ] 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.

	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
The number of bailiffs in Kansas (Bailiffs)	50	50	70	70	90	60	60	70	90	60	50	40	60	60	80	60	390	370	420
Google searches for 'that is sus' (Rel. search volume)	3.83333	7.08333	8.66667	3.83333	1.33333	6.41667	5.58333	6.91667	10.25	10.0833	8.66667	8.66667	11.0833	12.5	15.4167	14.4167	40.8333	58.1667	81.6667

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([50,50,70,70,90,60,60,70,90,60,50,40,60,60,80,60,390,370,420,])
array_2 = np.array([3.83333,7.08333,8.66667,3.83333,1.33333,6.41667,5.58333,6.91667,10.25,10.0833,8.66667,8.66667,11.0833,12.5,15.4167,14.4167,40.8333,58.1667,81.6667,])
array_1_name = "The number of bailiffs in Kansas"
array_2_name = "Google searches for 'that is sus'"

# 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. ^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.

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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
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Line chart for only The number of bailiffs in Kansas
Line chart for only Google searches for 'that is sus'
AI-generated correlation image
The spurious research paper: The Bailiff Ballyhoo: Examining the Correlation Between Bailiff Employment in Kansas and Google Searches for 'That is sus'

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Correlation ID: 2270 · Black Variable ID: 8225 · Red Variable ID: 1367


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