about · email me · subscribe
Spurious correlation #1,642 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Lamar and the second variable is Arson in Illinois.  The chart goes from 1985 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

Lamar is a name often associated with a smooth, laid-back attitude. As fewer parents chose this name for their children, the overall chill vibe in the state increased. With people being less easily agitated, there were fewer fiery conflicts, leading to a decrease in arson cases in Illinois. Guess you could say the name Lamar was the real extinguisher in Illinois!

Model: dalle-3
Prompt: Prompt: Generate a comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s, depicting a bustling Illinois town. A street lined with houses is filled with people chatting and waving to each other. In the center of the street, a large bonfire casts a warm glow, while a group of friends gathers around, roasting marshmallows. Among them, one person is named Lamar, who is known and loved by everyone in the neighborhood. Ensure that the popularity of the name Lamar is evident as many people call out to him with warmth and admiration. However, in the distance, a faint smell of smoke and the sound of fire engines can be heard, as firefighters work to extinguish an isolated incident of arson, causing concern and sadness among the community. Keep the visual depiction simple. Do not include any words or speech bubbles. 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: Popularity of the first name Lamar and Arson in Illinois. 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: Psychedelic Pop art Steampunk Voxel art A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s
ChatGPT: A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s

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 Popularity of the first name Lamar and Arson in Illinois together. Keep the description simple.
ChatGPT: In a bustling Illinois town, a street lined with houses is filled with people chatting and waving to each other. In the center of the street, a large bonfire casts a warm glow, while a group of friends gathers around, roasting marshmallows. Among them, one person is named Lamar, who is known and loved by everyone in the neighborhood. The popularity of the name Lamar is evident as many people call out to him with warmth and admiration. However, in the distance, a faint smell of smoke and the sound of fire engines can be heard, as firefighters work to extinguish an isolated incident of arson, causing concern and sadness among the community.

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 comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s ] and depicting this scene: In a bustling Illinois town, a street lined with houses is filled with people chatting and waving to each other. In the center of the street, a large bonfire casts a warm glow, while a group of friends gathers around, roasting marshmallows. Among them, one person is named Lamar, who is known and loved by everyone in the neighborhood. The popularity of the name Lamar is evident as many people call out to him with warmth and admiration. However, in the distance, a faint smell of smoke and the sound of fire engines can be heard, as firefighters work to extinguish an isolated incident of arson, causing concern and sadness among the community. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate a comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s, depicting a bustling Illinois town. A street lined with houses is filled with people chatting and waving to each other. In the center of the street, a large bonfire casts a warm glow, while a group of friends gathers around, roasting marshmallows. Among them, one person is named Lamar, who is known and loved by everyone in the neighborhood. Ensure that the popularity of the name Lamar is evident as many people call out to him with warmth and admiration. However, in the distance, a faint smell of smoke and the sound of fire engines can be heard, as firefighters work to extinguish an isolated incident of arson, causing concern and sadness among the community. Keep the visual depiction simple. Do not include any words or speech bubbles.

*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.

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 a decrease in Popularity of the first name Lamar caused Arson in Illinois to decrease. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)
Burning Up: A Hot Pursuit of the Lamar Name-Arson Association in Illinois

International Journal of Fire Science and Arson Investigation

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 witty academic researcher. Your writing sounds like it belongs in a statistics journal.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Popularity of the first name Lamar and Arson in Illinois. Make lots of jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, make it sound serious.

Your research team used data from US Social Security Administration and FBI Criminal Justice Information Services to assess this nagging question. You found a correlation coefficient of 0.9362410 and p < 0.01 for 1985 to 2022.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Burning Up: A Hot Pursuit of the Lamar Name-Arson Association in Illinois

[[ABSTRACT]]
This paper takes on the sizzling inquiry into the potential link between the popularity of the first name Lamar and the incidence of arson in the state of Illinois. Leveraging an eclectic assemblage of data from the US Social Security Administration and the FBI Criminal Justice Information Services, our study unveils a scorching correlation coefficient of 0.9362410 and a p-value less than 0.01 for the years spanning 1985 to 2022. The findings scintillate as they propose that there may be fire in the relationship between the name Lamar and arson. We offer scintillating insights into this fiery connection, igniting further discourse and kindling new avenues for research.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between Popularity of the first name Lamar and Arson in Illinois. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
Burning Up: A Hot Pursuit of the Lamar Name-Arson Association in Illinois

[[ABSTRACT]]
This paper takes on the sizzling inquiry into the potential link between the popularity of the first name Lamar and the incidence of arson in the state of Illinois. Leveraging an eclectic assemblage of data from the US Social Security Administration and the FBI Criminal Justice Information Services, our study unveils a scorching correlation coefficient of 0.9362410 and a p-value less than 0.01 for the years spanning 1985 to 2022. The findings scintillate as they propose that there may be fire in the relationship between the name Lamar and arson. We offer scintillating insights into this fiery connection, igniting further discourse and kindling new avenues for research.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The enthralling dance between the popularity of first names and societal phenomena has long captivated researchers across diverse fields. From the waxing and waning of names like Gertrude and Mildred to the meteoric rise of monikers like Ashton and Nevaeh, the ebb and flow of naming fashions mirrors the ever-shifting currents of human culture and zeitgeist. In this scintillating study, we turn our attention to the incendiary relationship between the prevalence of the first name Lamar and the occurrence of arson in the state of Illinois.

As we embark on this fiery pursuit, we aim to ignite the flames of curiosity and unveil the uncharted terrain in the domain of nomenclature-based statistical analyses. The curious confluence of naming trends and criminal activities begs the query: Could there be a spark, a flame, or even a raging inferno of a connection between the first name Lamar and incidents of arson? Our expedition seeks to unravel this sizzling mystery, with a fervent hope to shed light on the searing intersection of nomenclature and nefarious behavior.

Drawing upon a confluence of data from the US Social Security Administration and the FBI Criminal Justice Information Services, we embark on a statistical odyssey to uncover any correlations and potential causative threads between the omnipresence of the name Lamar and the occurrence of arson in the Land of Lincoln. By deploying a diverse array of statistical methodologies, including the scorching correlation coefficient and the blazing p-value, we endeavor to heat up the realm of empirical inquiry in a manner that would make even the sun itself feel a twinge of envy.

We invite our readers to strap on their asbestos suits and join us in this blazing quest as we unravel the enigmatic link between the name Lamar and the fiery specter of arson in Illinois. In the incendiary world of statistical analysis, sometimes it's not just the outliers that are on fire!


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Popularity of the first name Lamar and Arson in Illinois. Make lots of 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]]
Burning Up: A Hot Pursuit of the Lamar Name-Arson Association in Illinois

[[ABSTRACT]]
This paper takes on the sizzling inquiry into the potential link between the popularity of the first name Lamar and the incidence of arson in the state of Illinois. Leveraging an eclectic assemblage of data from the US Social Security Administration and the FBI Criminal Justice Information Services, our study unveils a scorching correlation coefficient of 0.9362410 and a p-value less than 0.01 for the years spanning 1985 to 2022. The findings scintillate as they propose that there may be fire in the relationship between the name Lamar and arson. We offer scintillating insights into this fiery connection, igniting further discourse and kindling new avenues for research.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The enthralling dance between the popularity of first names and societal phenomena has long captivated researchers across diverse fields. From the waxing and waning of names like Gertrude and Mildred to the meteoric rise of monikers like Ashton and Nevaeh, the ebb and flow of naming fashions mirrors the ever-shifting currents of human culture and zeitgeist. In this scintillating study, we turn our attention to the incendiary relationship between the prevalence of the first name Lamar and the occurrence of arson in the state of Illinois.
As we embark on this fiery pursuit, we aim to ignite the flames of curiosity and unveil the uncharted terrain in the domain of nomenclature-based statistical analyses. The curious confluence of naming trends and criminal activities begs the query: Could there be a spark, a flame, or even a raging inferno of a connection between the first name Lamar and incidents of arson? Our expedition seeks to unravel this sizzling mystery, with a fervent hope to shed light on the searing intersection of nomenclature and nefarious behavior.
Drawing upon a confluence of data from the US Social Security Administration and the FBI Criminal Justice Information Services, we embark on a statistical odyssey to uncover any correlations and potential causative threads between the omnipresence of the name Lamar and the occurrence of arson in the Land of Lincoln. By deploying a diverse array of statistical methodologies, including the scorching correlation coefficient and the blazing p-value, we endeavor to heat up the realm of empirical inquiry in a manner that would make even the sun itself feel a twinge of envy.
We invite our readers to strap on their asbestos suits and join us in this blazing quest as we unravel the enigmatic link between the name Lamar and the fiery specter of arson in Illinois. In the incendiary world of statistical analysis, sometimes it's not just the outliers that are on fire!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In "The Sizzle of Statistics: A Comparative Analysis of Name-Related Phenomena" by Smith et al., the authors find a scorching interest in the connection between first names and societal trends, shedding light on the combustible potential of nomenclature-based statistical analyses. Building upon this foundation, "The Flame of Nomenclature: A Study of Name Popularity and Incendiary Activities" by Doe and Jones delves into the fiery depths of naming fashions and their potential influence on criminal behaviors, fanning the flames of curiosity in the domain of statistical inquiry.

As we stoke the fires of exploration, we turn to "Fire and Names: A Historical Inquiry" by Blaze, which kindles the imagination with its incendiary exploration of historical naming practices and their potential ties to fiery phenomena. Furthermore, "Smoke Signals: An Investigation into Name-Related Combustible Consequences" by Ember captures the reader's attention with its smoldering investigation into the potential correlation between names and incendiary incidents.

Moving from non-fiction to fiction, the scorching sensation of the first name Lamar is not a stranger to the world of literature. In "Inferno Identity: The Name Lamar in Arson Mysteries" by Kindle Sparks, the author ignites the readers' interest with a captivating tale of intrigue and arson, weaving a fiery narrative around the enigmatic aura of the name Lamar. Similarly, "Blaze of Destiny: A Sizzling Tale of Names and Fires" by Flame Writer tantalizes the imagination, offering a smoldering narrative that beckons the reader into the sultry world where names and arson collide.

Shifting into the realm of motion pictures, our foray into the cinematic world yields tangentially related narratives that spark the flames of curiosity. From "Smokin' Aces" to "Heat" and "Backdraft," the celluloid representations of fiery pursuits and criminal activities set the stage for our scintillating inquiry, fueling the inferno of our intrigue into the potential link between the name Lamar and arson in Illinois.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Popularity of the first name Lamar and Arson in Illinois. Make lots of 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 US Social Security Administration and FBI Criminal Justice Information Services . You used data from 1985 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]]
Burning Up: A Hot Pursuit of the Lamar Name-Arson Association in Illinois

[[ABSTRACT]]
This paper takes on the sizzling inquiry into the potential link between the popularity of the first name Lamar and the incidence of arson in the state of Illinois. Leveraging an eclectic assemblage of data from the US Social Security Administration and the FBI Criminal Justice Information Services, our study unveils a scorching correlation coefficient of 0.9362410 and a p-value less than 0.01 for the years spanning 1985 to 2022. The findings scintillate as they propose that there may be fire in the relationship between the name Lamar and arson. We offer scintillating insights into this fiery connection, igniting further discourse and kindling new avenues for research.

[[INTRODUCTION]]
The enthralling dance between the popularity of first names and societal phenomena has long captivated researchers across diverse fields. From the waxing and waning of names like Gertrude and Mildred to the meteoric rise of monikers like Ashton and Nevaeh, the ebb and flow of naming fashions mirrors the ever-shifting currents of human culture and zeitgeist. In this scintillating study, we turn our attention to the incendiary relationship between the prevalence of the first name Lamar and the occurrence of arson in the state of Illinois.
As we embark on this fiery pursuit, we aim to ignite the flames of curiosity and unveil the uncharted terrain in the domain of nomenclature-based statistical analyses. The curious confluence of naming trends and criminal activities begs the query: Could there be a spark, a flame, or even a raging inferno of a connection between the first name Lamar and incidents of arson? Our expedition seeks to unravel this sizzling mystery, with a fervent hope to shed light on the searing intersection of nomenclature and nefarious behavior.
Drawing upon a confluence of data from the US Social Security Administration and the FBI Criminal Justice Information Services, we embark on a statistical odyssey to uncover any correlations and potential causative threads between the omnipresence of the name Lamar and the occurrence of arson in the Land of Lincoln. By deploying a diverse array of statistical methodologies, including the scorching correlation coefficient and the blazing p-value, we endeavor to heat up the realm of empirical inquiry in a manner that would make even the sun itself feel a twinge of envy.
We invite our readers to strap on their asbestos suits and join us in this blazing quest as we unravel the enigmatic link between the name Lamar and the fiery specter of arson in Illinois. In the incendiary world of statistical analysis, sometimes it's not just the outliers that are on fire!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To illuminate the scorching association between the first name Lamar and the occurrence of arson in the state of Illinois, our methodology harnessed a conflagration of data from the US Social Security Administration and the FBI Criminal Justice Information Services. We carried out a pyrotechnic investigation over the time period of 1985 to 2022, utilizing a series of incendiary statistical techniques to stoke the flames of empirical inquiry.

First and foremost, we conducted a fervent data collection effort, harnessing records of the prevalence of the first name Lamar from the US Social Security Administration. Our team probed the depths of historical data, sifting through the scorching archives in pursuit of any flickers of naming trends. Additionally, we obtained data on arson incidents from the FBI Criminal Justice Information Services, carefully aggregating records of conflagrations, ignitions, and fiery mishaps that blazed across the Illinois landscape during the study period.

Turning to the statistical inferno, we stoked the coals of correlation analysis, utilizing a scorching correlation coefficient to measure the strength and direction of the relationship between the prevalence of the name Lamar and the frequency of arson incidents. Our inferno of analysis also blazed with the dazzling spark of hypothesis testing, as we invoked the searing power of the p-value to assess the statistical significance of our findings.

Our methodology was not without the scintillating influence of control variables, as we vigilantly monitored the influence of confounding factors such as population trends, socioeconomic indicators, and weather patterns on the sizzling connection between the name Lamar and arson. By fanning the flames of robust statistical modeling, we endeavored to sear away any extraneous influences to capture the true essence of the Lamar name-arson relationship.

Finally, we plunged headlong into the fiery cauldron of regression analysis, unleashing the blazing power of regression models to unearth any potential nuanced nuances and searing subtleties in the Lamar name-arson linkage.

In sum, our methodological approach blazed a trail through the statistical inferno, harnessing a fervent array of techniques and tools to illuminate the fiery nexus between the first name Lamar and the searing occurrence of arson in the Land of Lincoln.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Popularity of the first name Lamar and Arson in Illinois. Make lots of 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 US Social Security Administration and FBI Criminal Justice Information Services .

For the time period 1985 to 2022, you found a correlation 0.9362410, r-squared of 0.8765471, 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]]
Burning Up: A Hot Pursuit of the Lamar Name-Arson Association in Illinois

[[ABSTRACT]]
This paper takes on the sizzling inquiry into the potential link between the popularity of the first name Lamar and the incidence of arson in the state of Illinois. Leveraging an eclectic assemblage of data from the US Social Security Administration and the FBI Criminal Justice Information Services, our study unveils a scorching correlation coefficient of 0.9362410 and a p-value less than 0.01 for the years spanning 1985 to 2022. The findings scintillate as they propose that there may be fire in the relationship between the name Lamar and arson. We offer scintillating insights into this fiery connection, igniting further discourse and kindling new avenues for research.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The enthralling dance between the popularity of first names and societal phenomena has long captivated researchers across diverse fields. From the waxing and waning of names like Gertrude and Mildred to the meteoric rise of monikers like Ashton and Nevaeh, the ebb and flow of naming fashions mirrors the ever-shifting currents of human culture and zeitgeist. In this scintillating study, we turn our attention to the incendiary relationship between the prevalence of the first name Lamar and the occurrence of arson in the state of Illinois.
As we embark on this fiery pursuit, we aim to ignite the flames of curiosity and unveil the uncharted terrain in the domain of nomenclature-based statistical analyses. The curious confluence of naming trends and criminal activities begs the query: Could there be a spark, a flame, or even a raging inferno of a connection between the first name Lamar and incidents of arson? Our expedition seeks to unravel this sizzling mystery, with a fervent hope to shed light on the searing intersection of nomenclature and nefarious behavior.
Drawing upon a confluence of data from the US Social Security Administration and the FBI Criminal Justice Information Services, we embark on a statistical odyssey to uncover any correlations and potential causative threads between the omnipresence of the name Lamar and the occurrence of arson in the Land of Lincoln. By deploying a diverse array of statistical methodologies, including the scorching correlation coefficient and the blazing p-value, we endeavor to heat up the realm of empirical inquiry in a manner that would make even the sun itself feel a twinge of envy.
We invite our readers to strap on their asbestos suits and join us in this blazing quest as we unravel the enigmatic link between the name Lamar and the fiery specter of arson in Illinois. In the incendiary world of statistical analysis, sometimes it's not just the outliers that are on fire!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The scorching investigation into the potential correlation between the popularity of the first name Lamar and the incidence of arson in Illinois yields a fiery uncovering. We found a blistering correlation coefficient of 0.9362410, indicating a robust relationship between the two variables. The red-hot r-squared value of 0.8765471 further cements the strength of this association, suggesting that the popularity of the name Lamar may have a blazing impact on the occurrence of arson in the Land of Lincoln.

With a sizzling p-value of less than 0.01, we can confidently reject the null hypothesis and embrace the incendiary notion that there is indeed a scorching connection between the name Lamar and arsons in Illinois. This statistical significance blazes a trail for further inquiry and practically sets the data on fire with excitement.

Moreover, Figure 1 illustrates the searing correlation between the popularity of the first name Lamar and the occurrence of arson. The data points are so hot, they're practically smoking! The figure exudes a sense of heat, quite fitting for a research endeavor that delves into the combustible relationship between nomenclature and societal phenomena.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Popularity of the first name Lamar and Arson in Illinois. Make lots of 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]]
Burning Up: A Hot Pursuit of the Lamar Name-Arson Association in Illinois

[[ABSTRACT]]
This paper takes on the sizzling inquiry into the potential link between the popularity of the first name Lamar and the incidence of arson in the state of Illinois. Leveraging an eclectic assemblage of data from the US Social Security Administration and the FBI Criminal Justice Information Services, our study unveils a scorching correlation coefficient of 0.9362410 and a p-value less than 0.01 for the years spanning 1985 to 2022. The findings scintillate as they propose that there may be fire in the relationship between the name Lamar and arson. We offer scintillating insights into this fiery connection, igniting further discourse and kindling new avenues for research.

[[LITERATURE REVIEW]]
In "The Sizzle of Statistics: A Comparative Analysis of Name-Related Phenomena" by Smith et al., the authors find a scorching interest in the connection between first names and societal trends, shedding light on the combustible potential of nomenclature-based statistical analyses. Building upon this foundation, "The Flame of Nomenclature: A Study of Name Popularity and Incendiary Activities" by Doe and Jones delves into the fiery depths of naming fashions and their potential influence on criminal behaviors, fanning the flames of curiosity in the domain of statistical inquiry.
As we stoke the fires of exploration, we turn to "Fire and Names: A Historical Inquiry" by Blaze, which kindles the imagination with its incendiary exploration of historical naming practices and their potential ties to fiery phenomena. Furthermore, "Smoke Signals: An Investigation into Name-Related Combustible Consequences" by Ember captures the reader's attention with its smoldering investigation into the potential correlation between names and incendiary incidents.
Moving from non-fiction to fiction, the scorching sensation of the first name Lamar is not a stranger to the world of literature. In "Inferno Identity: The Name Lamar in Arson Mysteries" by Kindle Sparks, the author ignites the readers' interest with a captivating tale of intrigue and arson, weaving a fiery narrative around the enigmatic aura of the name Lamar. Similarly, "Blaze of Destiny: A Sizzling Tale of Names and Fires" by Flame Writer tantalizes the imagination, offering a smoldering narrative that beckons the reader into the sultry world where names and arson collide.
Shifting into the realm of motion pictures, our foray into the cinematic world yields tangentially related narratives that spark the flames of curiosity. From "Smokin' Aces" to "Heat" and "Backdraft," the celluloid representations of fiery pursuits and criminal activities set the stage for our scintillating inquiry, fueling the inferno of our intrigue into the potential link between the name Lamar and arson in Illinois.

[[RESULTS]]
The scorching investigation into the potential correlation between the popularity of the first name Lamar and the incidence of arson in Illinois yields a fiery uncovering. We found a blistering correlation coefficient of 0.9362410, indicating a robust relationship between the two variables. The red-hot r-squared value of 0.8765471 further cements the strength of this association, suggesting that the popularity of the name Lamar may have a blazing impact on the occurrence of arson in the Land of Lincoln.
With a sizzling p-value of less than 0.01, we can confidently reject the null hypothesis and embrace the incendiary notion that there is indeed a scorching connection between the name Lamar and arsons in Illinois. This statistical significance blazes a trail for further inquiry and practically sets the data on fire with excitement.
Moreover, Figure 1 illustrates the searing correlation between the popularity of the first name Lamar and the occurrence of arson. The data points are so hot, they're practically smoking! The figure exudes a sense of heat, quite fitting for a research endeavor that delves into the combustible relationship between nomenclature and societal phenomena.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The incendiary illumination brought forth by our scorching study aligns with the prior research that has sizzled in the arena of name-related phenomena. Our findings stoke the flames of interest, fanning the conflagration of curiosity ignited by esteemed researchers such as Smith et al. and Doe and Jones. The searing correlation coefficient of 0.9362410 and the sizzling r-squared value of 0.8765471 not only bolster the earlier works but also set the stage for a pyrotechnic parade of statistical implications, illuminating the nexus between the name Lamar and arson in Illinois.

Our study, akin to a spark that kindles a conflagration, blazes a trail in the domain of arms-length correlations, surpassing the scorching p-value threshold of 0.01 with such fervor that one might almost feel the heat emanating from the data. The statistics are so hot, they could set the p-value on fire! This fiery significance not only challenges the null hypothesis but also ignites fervent discussions regarding the potential causal mechanisms underlying the association between the name Lamar and the incidence of arson.

The searing visualization presented in Figure 1, akin to a smoldering beacon of statistical revelation, not only captivates the eye but also engulfs the mind in a conflagration of contemplation. The data points appear to be emitting a fervent heat, practically daring the onlooker to dispute the blazing connection between Lamar and arson in Illinois.

As we bask in the glow of our findings, it becomes apparent that the fiery allure of first names and their potential influence on societal trends cannot be extinguished. The research landscape is ripe for further exploration, and one might say that our study has, quite literally, set the field on fire.

The conflagration of statistical evidence supports the hypothesis that the popularity of the first name Lamar may indeed be a smoldering catalyst for arson in Illinois. Our findings not only add fuel to the fire of curiosity but also blaze a trail for future investigations into the scorching interplay between nomenclature and societal phenomena.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Popularity of the first name Lamar and Arson in Illinois. Make lots of 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]]
Burning Up: A Hot Pursuit of the Lamar Name-Arson Association in Illinois

[[ABSTRACT]]
This paper takes on the sizzling inquiry into the potential link between the popularity of the first name Lamar and the incidence of arson in the state of Illinois. Leveraging an eclectic assemblage of data from the US Social Security Administration and the FBI Criminal Justice Information Services, our study unveils a scorching correlation coefficient of 0.9362410 and a p-value less than 0.01 for the years spanning 1985 to 2022. The findings scintillate as they propose that there may be fire in the relationship between the name Lamar and arson. We offer scintillating insights into this fiery connection, igniting further discourse and kindling new avenues for research.

[[INTRDUCTION]]
The enthralling dance between the popularity of first names and societal phenomena has long captivated researchers across diverse fields. From the waxing and waning of names like Gertrude and Mildred to the meteoric rise of monikers like Ashton and Nevaeh, the ebb and flow of naming fashions mirrors the ever-shifting currents of human culture and zeitgeist. In this scintillating study, we turn our attention to the incendiary relationship between the prevalence of the first name Lamar and the occurrence of arson in the state of Illinois.
As we embark on this fiery pursuit, we aim to ignite the flames of curiosity and unveil the uncharted terrain in the domain of nomenclature-based statistical analyses. The curious confluence of naming trends and criminal activities begs the query: Could there be a spark, a flame, or even a raging inferno of a connection between the first name Lamar and incidents of arson? Our expedition seeks to unravel this sizzling mystery, with a fervent hope to shed light on the searing intersection of nomenclature and nefarious behavior.
Drawing upon a confluence of data from the US Social Security Administration and the FBI Criminal Justice Information Services, we embark on a statistical odyssey to uncover any correlations and potential causative threads between the omnipresence of the name Lamar and the occurrence of arson in the Land of Lincoln. By deploying a diverse array of statistical methodologies, including the scorching correlation coefficient and the blazing p-value, we endeavor to heat up the realm of empirical inquiry in a manner that would make even the sun itself feel a twinge of envy.
We invite our readers to strap on their asbestos suits and join us in this blazing quest as we unravel the enigmatic link between the name Lamar and the fiery specter of arson in Illinois. In the incendiary world of statistical analysis, sometimes it's not just the outliers that are on fire!

[[RESULTS]]
The scorching investigation into the potential correlation between the popularity of the first name Lamar and the incidence of arson in Illinois yields a fiery uncovering. We found a blistering correlation coefficient of 0.9362410, indicating a robust relationship between the two variables. The red-hot r-squared value of 0.8765471 further cements the strength of this association, suggesting that the popularity of the name Lamar may have a blazing impact on the occurrence of arson in the Land of Lincoln.
With a sizzling p-value of less than 0.01, we can confidently reject the null hypothesis and embrace the incendiary notion that there is indeed a scorching connection between the name Lamar and arsons in Illinois. This statistical significance blazes a trail for further inquiry and practically sets the data on fire with excitement.
Moreover, Figure 1 illustrates the searing correlation between the popularity of the first name Lamar and the occurrence of arson. The data points are so hot, they're practically smoking! The figure exudes a sense of heat, quite fitting for a research endeavor that delves into the combustible relationship between nomenclature and societal phenomena.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our scorching investigation has shed light on the blazing connection between the first name Lamar and the incidence of arson in Illinois. The findings have ignited a fiery discourse in the realm of statistical analysis, leaving us all a little hot under the collar.

The searing correlation coefficient and the flaming p-value have heated up the empirical playing field, providing ample fuel for further research. As we bask in the glow of these findings, it’s clear that the name Lamar may have a fiery impact on the criminal landscape of Illinois.

This research has certainly stoked the flames of curiosity, but it’s time to extinguish any lingering doubts. It appears that no more research is needed in this area. We've turned up the heat and uncovered a spicy connection between the name Lamar and arson, leaving no need for further tinder in this scorching field of inquiry.


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 Burning Up: A Hot Pursuit of the Lamar Name-Arson Association in Illinois. Respond only with the name of a fictional academic journal.

ChatGPT:

International Journal of Fire Science and Arson Investigation


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 Burning Up: A Hot Pursuit of the Lamar Name-Arson Association in Illinois. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Unconventional Pyrotechnics Research


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 Burning Up: A Hot Pursuit of the Lamar Name-Arson Association in Illinois with an abstract of This paper takes on the sizzling inquiry into the potential link between the popularity of the first name Lamar and the incidence of arson in the state of Illinois. Leveraging an eclectic assemblage of data from the US Social Security Administration and the FBI Criminal Justice Information Services, our study unveils a scorching correlation coefficient of 0.9362410 and a p-value less than 0.01 for the years spanning 1985 to 2022. The findings scintillate as they propose that there may be fire in the relationship between the name Lamar and arson. We offer scintillating insights into this fiery connection, igniting further discourse and kindling new avenues for research.

ChatGPT:

Lamar name, arson, Illinois, correlation coefficient, US Social Security Administration, FBI Criminal Justice Information Services, data analysis, statistical significance, name popularity, crime correlation

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



Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error


Data details

Popularity of the first name Lamar
Detailed data title: Babies of all sexes born in the US named Lamar
Source: US Social Security Administration
See what else correlates with Popularity of the first name Lamar

Arson in Illinois
Detailed data title: The arson rate per 100,000 residents in Illinois
Source: FBI Criminal Justice Information Services
See what else correlates with Arson in Illinois

Correlation r = 0.9362410 (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 = 0.8765471 (Coefficient of determination)
This means 87.7% of the change in the one variable (i.e., Arson in Illinois) is predictable based on the change in the other (i.e., Popularity of the first name Lamar) over the 38 years from 1985 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.2E-18. 0.0000000000000000062346262340
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.94 in 6.2E-16% of random cases. Said differently, if you correlated 160,394,538,897,389,824 random variables You don't actually need 160 quadrillion 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 37 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 37 because we have two variables measured over a period of 38 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.

[ 0.88, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
19851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010201120122013201420152016201720182019202020212022
Popularity of the first name Lamar (Babies born)545625624674748699550503405372306296323251256286288242238268303353356332323361352317376318337289286234221200163164
Arson in Illinois (Arson rate)35.340.341.243.138.44135.633.8252012.215.515.112.912.110.510.610.615.78.17.113.713.612.514.516.524.125.818.218.518.419.814.210.710.312.756.5




Why this works

  1. 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.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([545,625,624,674,748,699,550,503,405,372,306,296,323,251,256,286,288,242,238,268,303,353,356,332,323,361,352,317,376,318,337,289,286,234,221,200,163,164,])
array_2 = np.array([35.3,40.3,41.2,43.1,38.4,41,35.6,33.8,25,20,12.2,15.5,15.1,12.9,12.1,10.5,10.6,10.6,15.7,8.1,7.1,13.7,13.6,12.5,14.5,16.5,24.1,25.8,18.2,18.5,18.4,19.8,14.2,10.7,10.3,12.7,5,6.5,])
array_1_name = "Popularity of the first name Lamar"
array_2_name = "Arson in Illinois"

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

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



Reuseable content

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

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

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

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

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

Download images for these variables:


View another random correlation

How fun was this correlation?

Your rating is pure awesomeness!


Correlation ID: 1642 · Black Variable ID: 3275 · Red Variable ID: 20041
about · subscribe · emailme@tylervigen.com · twitter

CC BY 4.0