Spurious correlation #3,421 · 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 logisticians in District of Columbia and the second variable is Liquefied petroleum gas used in Qatar. The chart goes from 2004 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of logisticians in District of Columbia and the second variable is Liquefied petroleum gas used in Qatar. The chart goes from 2004 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of logisticians in District of Columbia rises, so does their expert handling of supply chain management. This leads to a surplus of Liquefied Petroleum Puns in the form of well-organized and smoothly delivered gas-related goods. Qatar, catching wind of this, naturally increases their demand for the pun-believable product, creating a gas frenzy and ultimately fueling the need for more Liquefied Petroleum Gas usage. It's a logistical and gas-tastic chain reaction, proving that when it comes to the world of fuel, the delivery of laughs is just as important as the delivery of gas!

^{Show image generation prompt} Model: dalle-3
Prompt: [ A photo-realistic image ] A group of logisticians in the District of Columbia stands in front of a large Liquefied Petroleum Gas (LPG) cylinder, with happy expressions as they embrace the cylinder, symbolizing their love for LPG. In the background, a line of shipping containers labeled with "Qatar" waits, ready to be loaded with LPG. The logisticians are preparing to relocate and open LPG-themed restaurants in the desert, portraying a sense of excitement and purpose. The scene is bathed in warm, inviting light, adding to the sense of anticipation and adventure. 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 logisticians in District of Columbia and Liquefied petroleum gas used in Qatar. 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: Art nouveau Concept art A photo-realistic image Cutsy graphics Psychedelic
ChatGPT: A photo-realistic image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both The number of logisticians in District of Columbia and Liquefied petroleum gas used in Qatar, in the following situation: As the number of logisticians in District of Columbia increased, so did their love for Liquefied petroleum gas, leading to a surge in demand from Qatar as logisticians relocated to open LPG-themed restaurants in the desert.. Keep the description simple.
ChatGPT: A group of logisticians in District of Columbia happily embrace a large Liquefied Petroleum Gas (LPG) cylinder, symbolizing their love for LPG. Meanwhile, in the background, a line of shipping containers labeled with "Qatar" waits to be loaded with LPG as the logisticians prepare to relocate and open LPG-themed restaurants in the desert.

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 photo-realistic image ] and depicting this scene: A group of logisticians in District of Columbia happily embrace a large Liquefied Petroleum Gas (LPG) cylinder, symbolizing their love for LPG. Meanwhile, in the background, a line of shipping containers labeled with "Qatar" waits to be loaded with LPG as the logisticians prepare to relocate and open LPG-themed restaurants in the desert. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A photo-realistic image ] A group of logisticians in the District of Columbia stands in front of a large Liquefied Petroleum Gas (LPG) cylinder, with happy expressions as they embrace the cylinder, symbolizing their love for LPG. In the background, a line of shipping containers labeled with "Qatar" waits, ready to be loaded with LPG. The logisticians are preparing to relocate and open LPG-themed restaurants in the desert, portraying a sense of excitement and purpose. The scene is bathed in warm, inviting light, adding to the sense of anticipation and adventure.

*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 logisticians in District of Columbia caused Liquefied petroleum gas used in Qatar to increase. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Up in the Air: The Gas-tifying Link Between Logisticians in the District of Columbia and Liquefied Petroleum Gas in Qatar

The Journal of Global Logistics and Energy Dynamics

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of logisticians in District of Columbia and Liquefied petroleum gas used in Qatar. 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
"Up in the Air: The Gas-tifying Link Between Logisticians in the District of Columbia and Liquefied Petroleum Gas in Qatar"

[[ABSTRACT]]
This paper delves into the correlation between the number of logisticians in the District of Columbia and the usage of liquefied petroleum gas (LPG) in Qatar. Harnessing data from the Bureau of Labor Statistics and the Energy Information Administration, we aimed to shed light on this seemingly improbable connection. Surprisingly, our analysis revealed a striking correlation coefficient of 0.9623388 and a p-value of less than 0.01 for the period spanning from 2004 to 2021. However, let's not gaslight ourselves into assuming causation just yet – although the statistical relationship may seem compelling, further investigation is needed to uncover the underlying mechanisms at play. Our findings add a dash of peculiarity to the field of logistics and energy, prompting us to take a lighthearted yet analytical approach to these unexpected intersections.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The world of research often takes us on unexpected journeys, uncovering curious connections that leave us scratching our heads in disbelief. In the realm of logistics and energy, the intertwining of seemingly disparate elements can sometimes lead to eyebrow-raising revelations. Our investigation into the link between the number of logisticians in the District of Columbia and the usage of liquefied petroleum gas (LPG) in Qatar is a prime example of this delightful quirkiness.
As the saying goes, "Don't go jumping to conclusions like a gas molecule in a LPG tank!" This study was born out of a blend of curiosity and amusement, spurred by the juxtaposition of these two variables that, at first glance, appear about as related as a camel in Antarctica. However, as scholars, we dare not recoil from the peculiar, but instead, we embark on the quest to unravel its enigmatic thread.
Our endeavor harnessed the formidable powers of data from the Bureau of Labor Statistics and the Energy Information Administration, wielding them with the precision of a seasoned sleuth probing for clues. What we unearthed amidst the numbers and trends was nothing short of surprising – a correlation coefficient of 0.9623388 and a p-value that would make even the strictest statisticians raise an intrigued eyebrow.
Yet, before we get carried away like a gust of wind sweeping across the Qatari desert, a note of caution is in order. As scholars with a predilection for precision, we acknowledge that correlation does not imply causation. While the statistical dance between these variables may seem compelling, we must approach it with the measured skepticism of a sommelier tasting a fine wine – savoring the flavor without jumping to unwarranted conclusions.
Our findings add a whimsical twist to the world of logistics and energy, propelling us to gaze upon the confluence of disciplines with a keen eye for the unexpected. So, buckle up and prepare for an intellectual journey filled with surprising connections and a hearty dose of statistical intrigue.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In their comprehensive study, Smith et al. (2017) investigate the nuanced relationship between the number of logisticians in urban centers and the consumption of liquefied petroleum gas in regions reliant on energy exports. Their findings highlight the intricate dance of supply chains and energy dynamics, paving the way for our exploration into the seemingly incongruous correlation between logisticians in the District of Columbia and the utilization of liquefied petroleum gas (LPG) in Qatar.

Expanding on this theme, Doe and Jones (2019) delve into the global patterns of energy consumption and logistical expertise, offering insights that transcend geographic boundaries and speak to the interconnected nature of our modern world. Their work sets the stage for our investigation into the transcontinental interplay of the logistics landscape in the United States and the LPG market dynamics in Qatar.

Drawing from the realms of non-fiction literature, "The Box: How the Shipping Container Made the World Smaller and the World Economy Bigger" (Levinson, 2006) presents a thought-provoking exploration of the impact of logistics on global trade. While the focus remains on physical goods, the underlying principles of supply chain management and distribution resonate with our study's emphasis on the underpinnings of logistical networks and their influence on energy dynamics.

In a similar vein, "The Prize: The Epic Quest for Oil, Money, and Power" (Yergin, 1991) offers a panoramic view of the global energy landscape, weaving a narrative that intertwines geopolitical maneuverings, technological advancements, and the intricate web of energy supply and demand. Though our study's scope narrows in on a specific aspect of energy usage, the broader themes of energy economics and international relations bear relevance to our examination of the relationship between logisticians in the District of Columbia and LPG consumption in Qatar.

Transitioning to the realm of fiction, "The Shipping News" (Proulx, 1993) unfolds a tale of personal reinvention against the backdrop of Newfoundland's maritime industry. While the setting and themes may seem far removed from our study's focus, the resilience and adaptability portrayed in the novel serve as a metaphor for the multifaceted nature of logistical networks and their ability to adapt to changing circumstances, much like the intriguing correlation we have uncovered.

Segueing into more whimsical sources of inspiration, it is worth noting that the authors embarked on an experiential journey through a variety of unconventional literary outlets. The backs of shampoo bottles, with their tantalizing promises of "ultimate volume" and "revitalizing moisture," offered a surprising wellspring of unconventional wisdom and unanticipated puns ("lather, rinse, repeat? More like logistician, analyze, interpret!"). Similarly, the authors found unexpected intellectual stimulation in the enigmatic musings of fortune cookies, where cryptic messages such as "opportunity knocks frequently, but you have to let it in" sparked a momentary reflection on the interconnectedness of opportunity and the open doors of quantitative analysis.

Indeed, our literature review traversed conventional and unconventional terrain, exemplifying the eclectic sources of inspiration that fuel scholarly inquiry. As we journey through the intersection of logistics and energy, a tapestry of scholarly research, literary works, and unorthodox musings invites us to explore the unexpected connections that punctuate our intellectual landscape.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of logisticians in District of Columbia and Liquefied petroleum gas used in Qatar. Make lots of jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Up in the Air: The Gas-tifying Link Between Logisticians in the District of Columbia and Liquefied Petroleum Gas in Qatar"

[[ABSTRACT]]
This paper delves into the correlation between the number of logisticians in the District of Columbia and the usage of liquefied petroleum gas (LPG) in Qatar. Harnessing data from the Bureau of Labor Statistics and the Energy Information Administration, we aimed to shed light on this seemingly improbable connection. Surprisingly, our analysis revealed a striking correlation coefficient of 0.9623388 and a p-value of less than 0.01 for the period spanning from 2004 to 2021. However, let's not gaslight ourselves into assuming causation just yet – although the statistical relationship may seem compelling, further investigation is needed to uncover the underlying mechanisms at play. Our findings add a dash of peculiarity to the field of logistics and energy, prompting us to take a lighthearted yet analytical approach to these unexpected intersections.

[[LITERATURE REVIEW]]
In their comprehensive study, Smith et al. (2017) investigate the nuanced relationship between the number of logisticians in urban centers and the consumption of liquefied petroleum gas in regions reliant on energy exports. Their findings highlight the intricate dance of supply chains and energy dynamics, paving the way for our exploration into the seemingly incongruous correlation between logisticians in the District of Columbia and the utilization of liquefied petroleum gas (LPG) in Qatar.
Expanding on this theme, Doe and Jones (2019) delve into the global patterns of energy consumption and logistical expertise, offering insights that transcend geographic boundaries and speak to the interconnected nature of our modern world. Their work sets the stage for our investigation into the transcontinental interplay of the logistics landscape in the United States and the LPG market dynamics in Qatar.
Drawing from the realms of non-fiction literature, "The Box: How the Shipping Container Made the World Smaller and the World Economy Bigger" (Levinson, 2006) presents a thought-provoking exploration of the impact of logistics on global trade. While the focus remains on physical goods, the underlying principles of supply chain management and distribution resonate with our study's emphasis on the underpinnings of logistical networks and their influence on energy dynamics.
In a similar vein, "The Prize: The Epic Quest for Oil, Money, and Power" (Yergin, 1991) offers a panoramic view of the global energy landscape, weaving a narrative that intertwines geopolitical maneuverings, technological advancements, and the intricate web of energy supply and demand. Though our study's scope narrows in on a specific aspect of energy usage, the broader themes of energy economics and international relations bear relevance to our examination of the relationship between logisticians in the District of Columbia and LPG consumption in Qatar.
Transitioning to the realm of fiction, "The Shipping News" (Proulx, 1993) unfolds a tale of personal reinvention against the backdrop of Newfoundland's maritime industry. While the setting and themes may seem far removed from our study's focus, the resilience and adaptability portrayed in the novel serve as a metaphor for the multifaceted nature of logistical networks and their ability to adapt to changing circumstances, much like the intriguing correlation we have uncovered.
Segueing into more whimsical sources of inspiration, it is worth noting that the authors embarked on an experiential journey through a variety of unconventional literary outlets. The backs of shampoo bottles, with their tantalizing promises of "ultimate volume" and "revitalizing moisture," offered a surprising wellspring of unconventional wisdom and unanticipated puns ("lather, rinse, repeat? More like logistician, analyze, interpret!"). Similarly, the authors found unexpected intellectual stimulation in the enigmatic musings of fortune cookies, where cryptic messages such as "opportunity knocks frequently, but you have to let it in" sparked a momentary reflection on the interconnectedness of opportunity and the open doors of quantitative analysis.
Indeed, our literature review traversed conventional and unconventional terrain, exemplifying the eclectic sources of inspiration that fuel scholarly inquiry. As we journey through the intersection of logistics and energy, a tapestry of scholarly research, literary works, and unorthodox musings invites us to explore the unexpected connections that punctuate our intellectual landscape.

[[RESULTS]]
The relationship between the number of logisticians in the District of Columbia and the consumption of liquefied petroleum gas (LPG) in Qatar has left us gasping in disbelief, much like a dramatic plot twist in a gaslit mystery novel. Our analysis, spanning the years 2004 to 2021, has yielded a remarkably robust correlation coefficient of 0.9623388, suggesting a strong association between these seemingly unrelated variables.
The scatterplot in Fig. 1 beautifully captures the close relationship between the number of logisticians in the District of Columbia and LPG consumption in Qatar, resembling a celestial dance of interconnectedness that would make even the most stoic observer do a double take.
It's as if the logisticians in the nation's capital have been orchestrating a logistical symphony that reverberates across the oceans, influencing the demand for LPG in Qatar with an uncanny precision. Perhaps they've been secretly whispering supply chain secrets across continents, or maybe it's just a whimsical quirk of fate that has left us scratching our heads in mild bemusement.
While the r-squared value of 0.9260960 underscores the strength of this relationship, we must exercise caution before hitching our theoretical wagons to this statistical star. As any seasoned researcher knows, correlation does not imply causation, and in this case, we must resist the temptation to don our causation capes too hastily.
Thus, our findings, while striking and undeniably intriguing, beckon us to peel back the layers of this enigmatic connection with the rigor and patience of an archeologist delicately uncovering a fossil buried in the sands of time. This confluence of logisticians and LPG consumption adds a touch of whimsy and wonder to the otherwise staid world of logistics and energy analysis, urging us to embrace the unexpected with an open mind and a healthy dose of scholarly skepticism.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our study has illuminated a remarkably robust correlation between the number of logisticians in the District of Columbia and the consumption of liquefied petroleum gas (LPG) in Qatar, akin to stumbling upon an unexpected gem in the labyrinth of statistical analysis. The findings not only corroborate the prior research conducted by Smith et al. (2017) and Doe and Jones (2019) but also add a whimsical twist to the seemingly incongruent relationship between logistical expertise and energy consumption.

The correlation coefficient of 0.9623388 uncovered in our study not only surpassed our expectations but also surpassed the bounds of rational expectation, prompting us to replace our proverbial thinking caps with ones befitting a riveting mystery novel – for could the logisticians in the District of Columbia truly be pulling the strings of LPG consumption in Qatar from across the Atlantic? The statistical relationship revealed by our analysis lends itself to countless fanciful hypotheses, though we remain grounded in the reality that correlation does not equate to causation.

Our study implores future scholars to delve into the underlying mechanisms that may underpin this uncanny correlation—perhaps delving into the possibility of transcontinental communication channels being constructed through symbols hidden within shipping crates, or envisaging a transoceanic echo of logistical whispers carried by the winds. These whimsical fancies aside, the gravity of our findings urges a meticulous pursuit of understanding, akin to the patient search of a detective navigating through the twists and turns of a perplexing case.

However, despite the enigmatic nature of our results, the statistical rigor underpinning our study cannot be discounted. The r-squared value of 0.9260960 attests to the substantial strength of the relationship observed between logisticians in the District of Columbia and LPG consumption in Qatar. This, in turn, emphasizes the importance of delving further into this improbable yet compelling association, lest we overlook a facet of energy dynamics that defies conventional expectations.

In conclusion, our study has unveiled a remarkable correlation that not only aligns with prior research but also introduces an air of whimsy and wonder into the realms of logistics and energy analysis. As we navigate this uncharted terrain of improbable connections, our scholarly compass must remain guided by caution and inquisitiveness, navigating the interplay of logisticians and LPG consumption with the carefully honed skepticism of a researcher versed in the mysteries of statistical inference.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of logisticians in District of Columbia and Liquefied petroleum gas used in Qatar. Make lots of jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Up in the Air: The Gas-tifying Link Between Logisticians in the District of Columbia and Liquefied Petroleum Gas in Qatar"

[[ABSTRACT]]
This paper delves into the correlation between the number of logisticians in the District of Columbia and the usage of liquefied petroleum gas (LPG) in Qatar. Harnessing data from the Bureau of Labor Statistics and the Energy Information Administration, we aimed to shed light on this seemingly improbable connection. Surprisingly, our analysis revealed a striking correlation coefficient of 0.9623388 and a p-value of less than 0.01 for the period spanning from 2004 to 2021. However, let's not gaslight ourselves into assuming causation just yet – although the statistical relationship may seem compelling, further investigation is needed to uncover the underlying mechanisms at play. Our findings add a dash of peculiarity to the field of logistics and energy, prompting us to take a lighthearted yet analytical approach to these unexpected intersections.

[[INTRDUCTION]]
The world of research often takes us on unexpected journeys, uncovering curious connections that leave us scratching our heads in disbelief. In the realm of logistics and energy, the intertwining of seemingly disparate elements can sometimes lead to eyebrow-raising revelations. Our investigation into the link between the number of logisticians in the District of Columbia and the usage of liquefied petroleum gas (LPG) in Qatar is a prime example of this delightful quirkiness.
As the saying goes, "Don't go jumping to conclusions like a gas molecule in a LPG tank!" This study was born out of a blend of curiosity and amusement, spurred by the juxtaposition of these two variables that, at first glance, appear about as related as a camel in Antarctica. However, as scholars, we dare not recoil from the peculiar, but instead, we embark on the quest to unravel its enigmatic thread.
Our endeavor harnessed the formidable powers of data from the Bureau of Labor Statistics and the Energy Information Administration, wielding them with the precision of a seasoned sleuth probing for clues. What we unearthed amidst the numbers and trends was nothing short of surprising – a correlation coefficient of 0.9623388 and a p-value that would make even the strictest statisticians raise an intrigued eyebrow.
Yet, before we get carried away like a gust of wind sweeping across the Qatari desert, a note of caution is in order. As scholars with a predilection for precision, we acknowledge that correlation does not imply causation. While the statistical dance between these variables may seem compelling, we must approach it with the measured skepticism of a sommelier tasting a fine wine – savoring the flavor without jumping to unwarranted conclusions.
Our findings add a whimsical twist to the world of logistics and energy, propelling us to gaze upon the confluence of disciplines with a keen eye for the unexpected. So, buckle up and prepare for an intellectual journey filled with surprising connections and a hearty dose of statistical intrigue.

[[RESULTS]]
The relationship between the number of logisticians in the District of Columbia and the consumption of liquefied petroleum gas (LPG) in Qatar has left us gasping in disbelief, much like a dramatic plot twist in a gaslit mystery novel. Our analysis, spanning the years 2004 to 2021, has yielded a remarkably robust correlation coefficient of 0.9623388, suggesting a strong association between these seemingly unrelated variables.
The scatterplot in Fig. 1 beautifully captures the close relationship between the number of logisticians in the District of Columbia and LPG consumption in Qatar, resembling a celestial dance of interconnectedness that would make even the most stoic observer do a double take.
It's as if the logisticians in the nation's capital have been orchestrating a logistical symphony that reverberates across the oceans, influencing the demand for LPG in Qatar with an uncanny precision. Perhaps they've been secretly whispering supply chain secrets across continents, or maybe it's just a whimsical quirk of fate that has left us scratching our heads in mild bemusement.
While the r-squared value of 0.9260960 underscores the strength of this relationship, we must exercise caution before hitching our theoretical wagons to this statistical star. As any seasoned researcher knows, correlation does not imply causation, and in this case, we must resist the temptation to don our causation capes too hastily.
Thus, our findings, while striking and undeniably intriguing, beckon us to peel back the layers of this enigmatic connection with the rigor and patience of an archeologist delicately uncovering a fossil buried in the sands of time. This confluence of logisticians and LPG consumption adds a touch of whimsy and wonder to the otherwise staid world of logistics and energy analysis, urging us to embrace the unexpected with an open mind and a healthy dose of scholarly skepticism.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our examination of the correlation between the number of logisticians in the District of Columbia and the consumption of liquefied petroleum gas (LPG) in Qatar has unearthed a captivating statistical entanglement. The robust correlation coefficient and p-value are as electrifying as a gas spark, igniting our curiosity and prompting us to tread cautiously through this uncharted territory of logistics and energy.

The orchestration of the logistical symphony from the nation's capital seems to have resonated across continents, influencing the demand for LPG in Qatar with an unexpected finesse. It's as if a secret society of logisticians has been clandestinely exchanging supply chain secrets across the oceans, creating a whimsical dance of interconnectedness that challenges our preconceived notions.

However, let's not be gullible like a balloon filled with pure helium and get carried away by the correlation coefficient just yet. As scholars, we must resist the temptation to don our causation capes too hastily and instead approach this enigmatic connection with the measured skepticism of a skeptical scientist scrutinizing an unsolicited hypothesis.

While our findings tantalizingly point to a relationship worthy of further elucidation, we assert that no more research is warranted in this quirky and delightful realm of logistics and energy. After all, unraveling this inexplicable connection may just turn out to be as elusive as finding a needle in a haystack filled with helium balloons.

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 Up in the Air: The Gas-tifying Link Between Logisticians in the District of Columbia and Liquefied Petroleum Gas in Qatar. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Global Logistics and Energy Dynamics

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 Up in the Air: The Gas-tifying Link Between Logisticians in the District of Columbia and Liquefied Petroleum Gas in Qatar. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Global Logistics and Sustainable Energy

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 Up in the Air: The Gas-tifying Link Between Logisticians in the District of Columbia and Liquefied Petroleum Gas in Qatar with an abstract of This paper delves into the correlation between the number of logisticians in the District of Columbia and the usage of liquefied petroleum gas (LPG) in Qatar. Harnessing data from the Bureau of Labor Statistics and the Energy Information Administration, we aimed to shed light on this seemingly improbable connection. Surprisingly, our analysis revealed a striking correlation coefficient of 0.9623388 and a p-value of less than 0.01 for the period spanning from 2004 to 2021. However, let's not gaslight ourselves into assuming causation just yet – although the statistical relationship may seem compelling, further investigation is needed to uncover the underlying mechanisms at play. Our findings add a dash of peculiarity to the field of logistics and energy, prompting us to take a lighthearted yet analytical approach to these unexpected intersections.

ChatGPT:

Logisticians, District of Columbia, liquefied petroleum gas, LPG, Qatar, correlation, Bureau of Labor Statistics, Energy Information Administration, statistical analysis, relationship, causation, investigation, logistics, energy, intersections

*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 logisticians in District of Columbia
Detailed data title: BLS estimate of logisticians in District of Columbia
Source: Bureau of Larbor Statistics
See what else correlates with The number of logisticians in District of Columbia

Liquefied petroleum gas used in Qatar
Detailed data title: Volume of liquefied petroleum gas used consumed in Qatar in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Liquefied petroleum gas used in Qatar

Correlation r = 0.9623388 (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 = 0.9260960 (Coefficient of determination)
This means 92.6% of the change in the one variable (i.e., Liquefied petroleum gas used in Qatar) is predictable based on the change in the other (i.e., The number of logisticians in District of Columbia) over the 18 years from 2004 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.81E-10.^Show 0.0000000001808043372413360200
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.96 in 1.81E-8% of random cases. Said differently, if you correlated 5,530,840,771 random variables^Note You don't actually need 5 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 17 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 17 because we have two variables measured over a period of 18 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.9, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
The number of logisticians in District of Columbia (Logisticians)	140	130	690	700	810	670	830	860	960	1070	1160	1370	1330	1300	1210	1150	1130	1050
Liquefied petroleum gas used in Qatar (Million Barrels/Day)	3.9773	4.10744	19.3194	17.6633	20.0182	20.0256	18.9802	21.6299	26.3114	28	30	31	30	31.463	32.0986	31.6219	32.6707	32.6707

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([140,130,690,700,810,670,830,860,960,1070,1160,1370,1330,1300,1210,1150,1130,1050,])
array_2 = np.array([3.9773,4.10744,19.3194,17.6633,20.0182,20.0256,18.9802,21.6299,26.3114,28,30,31,30,31.463,32.0986,31.6219,32.6707,32.6707,])
array_1_name = "The number of logisticians in District of Columbia"
array_2_name = "Liquefied petroleum gas used in Qatar"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only The number of logisticians in District of Columbia
Line chart for only Liquefied petroleum gas used in Qatar
AI-generated correlation image
The spurious research paper: Up in the Air: The Gas-tifying Link Between Logisticians in the District of Columbia and Liquefied Petroleum Gas in Qatar

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Correlation ID: 3421 · Black Variable ID: 16952 · Red Variable ID: 24835


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