Spurious correlation #1,156 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Zdeno Chara's Seasonal Total Goal Assists and the second variable is Liquefied petroleum gas used in Israel. The chart goes from 1998 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Zdeno Chara's Seasonal Total Goal Assists and the second variable is Liquefied petroleum gas used in Israel. The chart goes from 1998 to 2022, and the two variables track closely in value over that time.

AI explanation

As Zdeno Chara's Seasonal Total Goal Assists increase, more power is generated from the sheer force of his slapshot. This increased power somehow leads to a chain reaction ultimately causing a spike in the production of Liquefied petroleum gas used in Israel. It's like Chara is scoring goals and inadvertently fueling the energy needs of an entire country! Imagine the possibilities if he keeps racking up those assists. It's a real gas, I tell you.

^{Show image generation prompt} Model: dalle-3
Prompt: Visual Prompt for DALL-E 3: Style: A black-and-white newspaper illustration Scene: In a bustling kitchen in Israel, a large pot of stew bubbles on a stovetop as people gather around, smiling and laughing. The stove is fueled by a bright blue bottle of Liquefied petroleum gas, with the flames dancing underneath the pot. In the background, a hockey game plays on the TV, and fans cheer enthusiastically as Zdeno Chara scores a goal. The energy of the fans is palpable, and the atmosphere is filled with excitement and celebration. Enhancement: Add subtle textures and shading to emphasize the movement of the flames, the expressions on the faces of the people, and the action of the hockey game on the TV. Create a dynamic composition that captures the liveliness of the scene, with nuanced details that give depth and character to the illustration. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

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

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: Zdeno Chara's Seasonal Total Goal Assists increased which boosted the morale of hockey fans worldwide. This surge in positive energy caused an increase in productivity in Israel, leading to more demand for Liquefied petroleum gas as people cooked festive meals to celebrate Chara's achievement. . Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: Symbolism A black-and-white newspaper illustration Charcoal Cute 2D animation Low poly
ChatGPT: A black-and-white newspaper illustration

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. Zdeno Chara's Seasonal Total Goal Assists increased which boosted the morale of hockey fans worldwide. This surge in positive energy caused an increase in productivity in Israel, leading to more demand for Liquefied petroleum gas as people cooked festive meals to celebrate Chara's achievement.
ChatGPT: In a bustling kitchen in Israel, a large pot of stew bubbles on a stovetop as people gathered around, smiling and laughing. The stove is fueled by a bright blue bottle of Liquefied petroleum gas, with the flames dancing underneath the pot. In the background, a hockey game plays on the TV, and fans cheer enthusiastically as Zdeno Chara scores a goal. The energy of the fans is palpable, and the atmosphere is filled with excitement and celebration.

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 black-and-white newspaper illustration ] and depicting this scene: In a bustling kitchen in Israel, a large pot of stew bubbles on a stovetop as people gathered around, smiling and laughing. The stove is fueled by a bright blue bottle of Liquefied petroleum gas, with the flames dancing underneath the pot. In the background, a hockey game plays on the TV, and fans cheer enthusiastically as Zdeno Chara scores a goal. The energy of the fans is palpable, and the atmosphere is filled with excitement and celebration. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Visual Prompt for DALL-E 3: Style: A black-and-white newspaper illustration Scene: In a bustling kitchen in Israel, a large pot of stew bubbles on a stovetop as people gather around, smiling and laughing. The stove is fueled by a bright blue bottle of Liquefied petroleum gas, with the flames dancing underneath the pot. In the background, a hockey game plays on the TV, and fans cheer enthusiastically as Zdeno Chara scores a goal. The energy of the fans is palpable, and the atmosphere is filled with excitement and celebration. Enhancement: Add subtle textures and shading to emphasize the movement of the flames, the expressions on the faces of the people, and the action of the hockey game on the TV. Create a dynamic composition that captures the liveliness of the scene, with nuanced details that give depth and character to the illustration.

*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 Zdeno Chara's Seasonal Total Goal Assists caused Liquefied petroleum gas used in Israel to increase.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Slap Shots and Gas Tanks: Uncovering the Surprising Link Between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas Consumption in Israel

Journal of Sports Analytics and Energy Consumption

Jan 2024

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Zdeno Chara's Seasonal Total Goal Assists and Liquefied petroleum gas used in Israel. 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 cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
Slap Shots and Gas Tanks: Uncovering the Surprising Link Between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas Consumption in Israel

[[ABSTRACT]]
In this paper, we delve into the unexpected connection between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) used in Israel. Utilizing data from Hockey Reference and the Energy Information Administration, we apply statistical analysis to explore this intriguing correlation. Our findings reveal a noteworthy correlation coefficient of 0.7496272 and a significant p-value of less than 0.01 from 1998 to 2022. The results not only shed light on the interplay between athletic achievements and energy consumption but also serve as a quirky reminder of the eccentricities that can emerge from data analysis.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
When it comes to uncovering unexpected connections, it seems that statistical analysis has a knack for turning up results that are as perplexing as they are entertaining. In this paper, we embark on a curious journey to explore the surprising relationship between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) consumption in Israel. One might ponder what a towering defenseman's hockey performance could possibly have to do with the utilization of LPG halfway across the globe. As we dig deeper into the data, one thing becomes clear: statistical analysis is full of surprises, much like finding a hockey puck in the desert or an ice rink in the tropics.
Of course, we could spend hours speculating about the potential associations between slap shots and gas tanks, but let's not skate circles around the real issue here. We are here to examine the correlation between two seemingly unrelated entities and determine whether there is more to these numbers than meets the eye. After all, who wouldn't be intrigued by a study that unites the world of professional ice hockey with the consumption of liquefied petroleum gas? It's like discovering that peanut butter and pickles actually go well together, or that pineapples might just belong on a pizza after all.
Before we delve into the details, we must acknowledge that this study is not merely a lighthearted endeavor. It is rooted in the diligent collection of data from reputable sources such as Hockey Reference and the Energy Information Administration, and it is governed by the principles of rigorous statistical analysis. With a playful spirit and a dedication to thorough investigation, we aim to unravel the enigmatic association between Zdeno Chara's on-ice exploits and the LPG consumption trends in Israel.
So, grab your lab coat and your hockey stick, because we are about to embark on a quirky scientific expedition that seeks to shed light on the unexpected intersections of sports and energy consumption. It's time to uncover the intricacies of this peculiar correlation and perhaps even score a few unexpected goals along the way.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

To lay a solid foundation for our exploration of the perplexing nexus between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) consumption in Israel, we turn our attention to previous literature and research on seemingly unrelated phenomena that, upon closer examination, revealed unsuspected connections. Smith et al. (2013) investigated the relationship between sustainable energy sources and athletic performance, offering initial insights into the potential interplay between sports and energy consumption. Similarly, Doe and Jones (2017) delved into the enigmatic correlations between seemingly unrelated variables, setting the stage for our endeavor to unravel the mysterious bond between a hockey giant's on-ice prowess and the utilization of LPG in a distant land.

As we venture further into the academic landscape, however, we encounter a delightful array of literature that highlights the interconnectedness of seemingly disparate entities—a veritable treasure trove of knowledge for the curious and the whimsical. In "The Hockey Almanac," lorem, and ipsum expound upon the eccentricities of the sport, unveiling the droll and the unexpected that lurk beneath the veneer of the rink. Simultaneously, "Energy Economics" by Ipsum demonstrates the serious—and often sobering—undertones of energy consumption analysis, reminding us that statistical investigations, no matter how amusing, are rooted in practical considerations.

Transitioning from the realm of non-fiction, we are compelled to touch upon works of fiction that, albeit fictional, offer subtle parallels to our unconventional inquiry. In "The Art of the Hockey Goal," Lorem provides a whimsical take on the artistry of scoring goals, drawing intriguing parallels to the nuanced dance between player performance and external factors. Conversely, "The Energy Chronicles" by Ipsum invites readers to envision fantastical worlds where energy sources hold unexpected sway over unlikely events, setting the stage for our own exploration of the fantastical bond between a hockey legend's feats and LPG utilization.

In a lighthearted yet poignant departure, let us not overlook the subtle influences of animated entertainment on our perception of intricate relationships. Who could forget the comical scenes from "Hockey and Propane: An Unlikely Tale," a whimsical cartoon that playfully weaves together the worlds of sports and energy sources, leaving an indelible mark on impressionable young minds? Similarly, the beloved children's show "The Adventures of LPG Man and Hockey Hero" playfully explores the adventures of two unlikely allies, gently nudging audiences to consider the unexplored connections between athletic prowess and energy consumption.

In the vein of these diverse and often unexpected sources of inspiration, we align our investigation with the spirit of genuine curiosity, recognizing that remarkable discoveries often emerge from the most unlikely pairings. It is with this unabashed enthusiasm and a twinkle of mischief in our eyes that we forge ahead, ready to unravel the wondrous tie between Zdeno Chara's sporting triumphs and the enigmatic dance of LPG usage in distant lands.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Zdeno Chara's Seasonal Total Goal Assists and Liquefied petroleum gas used in Israel. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Hockey Reference and Energy Information Administration . You used data from 1998 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]]
Slap Shots and Gas Tanks: Uncovering the Surprising Link Between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas Consumption in Israel

[[ABSTRACT]]
In this paper, we delve into the unexpected connection between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) used in Israel. Utilizing data from Hockey Reference and the Energy Information Administration, we apply statistical analysis to explore this intriguing correlation. Our findings reveal a noteworthy correlation coefficient of 0.7496272 and a significant p-value of less than 0.01 from 1998 to 2022. The results not only shed light on the interplay between athletic achievements and energy consumption but also serve as a quirky reminder of the eccentricities that can emerge from data analysis.

[[INTRODUCTION]]
When it comes to uncovering unexpected connections, it seems that statistical analysis has a knack for turning up results that are as perplexing as they are entertaining. In this paper, we embark on a curious journey to explore the surprising relationship between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) consumption in Israel. One might ponder what a towering defenseman's hockey performance could possibly have to do with the utilization of LPG halfway across the globe. As we dig deeper into the data, one thing becomes clear: statistical analysis is full of surprises, much like finding a hockey puck in the desert or an ice rink in the tropics.
Of course, we could spend hours speculating about the potential associations between slap shots and gas tanks, but let's not skate circles around the real issue here. We are here to examine the correlation between two seemingly unrelated entities and determine whether there is more to these numbers than meets the eye. After all, who wouldn't be intrigued by a study that unites the world of professional ice hockey with the consumption of liquefied petroleum gas? It's like discovering that peanut butter and pickles actually go well together, or that pineapples might just belong on a pizza after all.
Before we delve into the details, we must acknowledge that this study is not merely a lighthearted endeavor. It is rooted in the diligent collection of data from reputable sources such as Hockey Reference and the Energy Information Administration, and it is governed by the principles of rigorous statistical analysis. With a playful spirit and a dedication to thorough investigation, we aim to unravel the enigmatic association between Zdeno Chara's on-ice exploits and the LPG consumption trends in Israel.
So, grab your lab coat and your hockey stick, because we are about to embark on a quirky scientific expedition that seeks to shed light on the unexpected intersections of sports and energy consumption. It's time to uncover the intricacies of this peculiar correlation and perhaps even score a few unexpected goals along the way.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the perplexing link between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) consumption in Israel, our research team embarked on a data-gathering odyssey that would make Odysseus proud. Our approach combined elements of statistical analysis, data mining, and a dash of good old-fashioned detective work, akin to Sherlock Holmes dissecting a particularly enigmatic case.

Data Collection:
We scoured the digital landscape, venturing through the virtual arenas of Hockey Reference and the Energy Information Administration with the determination of a puck-hungry forward chasing a game-winning goal. From these treasure troves of information, we meticulously extracted data spanning from 1998 to 2022, encompassing Zdeno Chara's illustrious career and the ebbs and flows of LPG usage in the Land of Milk and Honey.

Statistical Wizardry:
Armed with an arsenal of statistical tools, including regression analysis, correlation assessment, and time series modeling, we sought to illuminate the patterns hidden within these seemingly incongruous datasets. Picture Gandalf wielding his staff, summoning the forces of statistical magic as he unveils the mysteries of Middle-earth – only in our case, the enigma lay in the realms of hockey rinks and energy markets.

Control Variables Management:
To ensure the robustness of our findings, we diligently accounted for potential confounding factors, resembling a juggler skillfully keeping multiple balls in the air. Player performance metrics, economic indicators, and even celestial disturbances (though we jest) were considered in our analytical framework, preventing any rogue variables from sneaking onto the ice and disrupting the game.

Sensitivity Analysis:
In order to gauge the reliability of our results, we conducted sensitivity analyses that would make a highly-strung musician tuning a symphony orchestra seem relaxed by comparison. Our aim was to ascertain the resilience of our observed correlation under varying scenarios, thereby fortifying the foundations of our scholarly endeavor.

Ethical Considerations:
Amidst the lighthearted ambiance of our investigation, we remained steadfast in upholding the ethical standards of academic research. All data were handled with the utmost integrity and respect, akin to the delicate treatment of a priceless artifact in a museum, ensuring the veracity and propriety of our analytical pursuits.

So, just as Chara delivers bone-rattling checks on the ice, we endeavored to deliver robust, reliable analysis in our quest to illuminate the unexpected connection between his hockey prowess and Israel's LPG consumption. With tongues firmly in cheeks and statistical acumen at the ready, we ventured forth into the unknown, ready to uncover the delightful quirks and correlations that linger in the annals of data analysis. Onward we march, armed with spreadsheets and skates, to reveal the hidden threads that connect slap shots and gas tanks.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Zdeno Chara's Seasonal Total Goal Assists and Liquefied petroleum gas used in Israel. 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]]
Slap Shots and Gas Tanks: Uncovering the Surprising Link Between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas Consumption in Israel

[[ABSTRACT]]
In this paper, we delve into the unexpected connection between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) used in Israel. Utilizing data from Hockey Reference and the Energy Information Administration, we apply statistical analysis to explore this intriguing correlation. Our findings reveal a noteworthy correlation coefficient of 0.7496272 and a significant p-value of less than 0.01 from 1998 to 2022. The results not only shed light on the interplay between athletic achievements and energy consumption but also serve as a quirky reminder of the eccentricities that can emerge from data analysis.

[[LITERATURE REVIEW]]
To lay a solid foundation for our exploration of the perplexing nexus between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) consumption in Israel, we turn our attention to previous literature and research on seemingly unrelated phenomena that, upon closer examination, revealed unsuspected connections. Smith et al. (2013) investigated the relationship between sustainable energy sources and athletic performance, offering initial insights into the potential interplay between sports and energy consumption. Similarly, Doe and Jones (2017) delved into the enigmatic correlations between seemingly unrelated variables, setting the stage for our endeavor to unravel the mysterious bond between a hockey giant's on-ice prowess and the utilization of LPG in a distant land.
As we venture further into the academic landscape, however, we encounter a delightful array of literature that highlights the interconnectedness of seemingly disparate entities—a veritable treasure trove of knowledge for the curious and the whimsical. In "The Hockey Almanac," lorem, and ipsum expound upon the eccentricities of the sport, unveiling the droll and the unexpected that lurk beneath the veneer of the rink. Simultaneously, "Energy Economics" by Ipsum demonstrates the serious—and often sobering—undertones of energy consumption analysis, reminding us that statistical investigations, no matter how amusing, are rooted in practical considerations.
Transitioning from the realm of non-fiction, we are compelled to touch upon works of fiction that, albeit fictional, offer subtle parallels to our unconventional inquiry. In "The Art of the Hockey Goal," Lorem provides a whimsical take on the artistry of scoring goals, drawing intriguing parallels to the nuanced dance between player performance and external factors. Conversely, "The Energy Chronicles" by Ipsum invites readers to envision fantastical worlds where energy sources hold unexpected sway over unlikely events, setting the stage for our own exploration of the fantastical bond between a hockey legend's feats and LPG utilization.
In a lighthearted yet poignant departure, let us not overlook the subtle influences of animated entertainment on our perception of intricate relationships. Who could forget the comical scenes from "Hockey and Propane: An Unlikely Tale," a whimsical cartoon that playfully weaves together the worlds of sports and energy sources, leaving an indelible mark on impressionable young minds? Similarly, the beloved children's show "The Adventures of LPG Man and Hockey Hero" playfully explores the adventures of two unlikely allies, gently nudging audiences to consider the unexplored connections between athletic prowess and energy consumption.
In the vein of these diverse and often unexpected sources of inspiration, we align our investigation with the spirit of genuine curiosity, recognizing that remarkable discoveries often emerge from the most unlikely pairings. It is with this unabashed enthusiasm and a twinkle of mischief in our eyes that we forge ahead, ready to unravel the wondrous tie between Zdeno Chara's sporting triumphs and the enigmatic dance of LPG usage in distant lands.

[[RESULTS]]
The statistical analysis of the relationship between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) consumption in Israel yielded some intriguing and, dare I say, unexpected results. We found a correlation coefficient of 0.7496272, indicating a strong positive association between these seemingly disparate variables. This coefficient tells us that as Chara's goal assists go up, the LPG consumption in Israel also tends to increase. It's like watching a hockey game and suddenly realizing that the Zamboni and the propane tank might just be secret best friends.
Furthermore, the r-squared value of 0.5619410 suggests that approximately 56% of the variability in LPG consumption in Israel can be explained by variations in Zdeno Chara's Seasonal Total Goal Assists. This finding is not only statistically significant but also raises some eyebrow-raising questions. Could Chara's assists on the ice be fueling the energy consumption off the ice? It's almost as if his incredible passes have a direct line to the gas tanks in Israel, propelling both the puck and the propane to unexpected heights.
The p-value of less than 0.01 adds a touch of statistical stardom to our findings, indicating that the observed correlation is highly unlikely to have occurred by chance. In other words, this connection is as real as a game-winning goal in overtime. Perhaps it's time for us to consider putting "hockey assists" on the same level as "energy assists."
Fig. 1 presents a scatterplot illustrating the robust relationship between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas consumption in Israel. The plotted data points dance across the graph like energetic players on the ice, painting a picture of how a hockey player's performance can coalesce with energy usage in a distant land. It's a visual reminder that the world of statistics is full of surprises, much like discovering a hockey stick and a gas tank sitting side by side in an unexpected pairing.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The empirical findings from our investigation not only reaffirm the unexpected correlation we postulated but also unravel a quirky dance between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) consumption in Israel. We were initially skeptical, much like discovering a secret handshake between a hockey puck and a propane tank, but our statistical analysis confirms the uncanny connection, much to our amusement.

Building upon the literature review, which cheekily hinted at the potential cohesion between seemingly unrelated variables, our results culminate in a statistical waltz that twirls away any lingering doubts. The correlation coefficient of 0.7496272—reminiscent of a goalie's stellar save percentage—reveals a robust positive association between Chara's assists and LPG consumption. It's as if Chara's passes on the ice whisper secrets of propane to the gas tanks in Israel, cultivating a bond akin to that of a defenseman and their trusty stick.

The notable r-squared value of 0.5619410, akin to Chara's towering presence on the ice, demonstrates that over half of the variation in LPG consumption in Israel can be linked to fluctuations in Chara's Seasonal Total Goal Assists. This statistical revelation invites us to ponder the unanticipated ways in which an athlete's performance can synchronize with energy usage, much like discovering a harmonious symphony between a slap shot and the hiss of a gas burner.

Moreover, the p-value of less than 0.01 validates this unique connection with a level of confidence that rivals a seasoned coach's unwavering belief in the team. We can't help but contemplate the notion of "assists" taking on a whole new meaning, transcending the realm of hockey and etching its mark in the annals of energy economics.

In sum, our findings not only affirm the unexpected correlation alluded to in the literature but also underscore the whimsical and thought-provoking nature of statistical inquiry. Just as Zdeno Chara's on-ice prowess astonishes and intrigues, our study stands as a testament to the incalculable surprises that emerge when one embarks on a statistical journey with an open mind and a touch of whimsy.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Zdeno Chara's Seasonal Total Goal Assists and Liquefied petroleum gas used in Israel. 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]]
Slap Shots and Gas Tanks: Uncovering the Surprising Link Between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas Consumption in Israel

[[ABSTRACT]]
In this paper, we delve into the unexpected connection between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) used in Israel. Utilizing data from Hockey Reference and the Energy Information Administration, we apply statistical analysis to explore this intriguing correlation. Our findings reveal a noteworthy correlation coefficient of 0.7496272 and a significant p-value of less than 0.01 from 1998 to 2022. The results not only shed light on the interplay between athletic achievements and energy consumption but also serve as a quirky reminder of the eccentricities that can emerge from data analysis.

[[INTRDUCTION]]
When it comes to uncovering unexpected connections, it seems that statistical analysis has a knack for turning up results that are as perplexing as they are entertaining. In this paper, we embark on a curious journey to explore the surprising relationship between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) consumption in Israel. One might ponder what a towering defenseman's hockey performance could possibly have to do with the utilization of LPG halfway across the globe. As we dig deeper into the data, one thing becomes clear: statistical analysis is full of surprises, much like finding a hockey puck in the desert or an ice rink in the tropics.
Of course, we could spend hours speculating about the potential associations between slap shots and gas tanks, but let's not skate circles around the real issue here. We are here to examine the correlation between two seemingly unrelated entities and determine whether there is more to these numbers than meets the eye. After all, who wouldn't be intrigued by a study that unites the world of professional ice hockey with the consumption of liquefied petroleum gas? It's like discovering that peanut butter and pickles actually go well together, or that pineapples might just belong on a pizza after all.
Before we delve into the details, we must acknowledge that this study is not merely a lighthearted endeavor. It is rooted in the diligent collection of data from reputable sources such as Hockey Reference and the Energy Information Administration, and it is governed by the principles of rigorous statistical analysis. With a playful spirit and a dedication to thorough investigation, we aim to unravel the enigmatic association between Zdeno Chara's on-ice exploits and the LPG consumption trends in Israel.
So, grab your lab coat and your hockey stick, because we are about to embark on a quirky scientific expedition that seeks to shed light on the unexpected intersections of sports and energy consumption. It's time to uncover the intricacies of this peculiar correlation and perhaps even score a few unexpected goals along the way.

[[RESULTS]]
The statistical analysis of the relationship between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) consumption in Israel yielded some intriguing and, dare I say, unexpected results. We found a correlation coefficient of 0.7496272, indicating a strong positive association between these seemingly disparate variables. This coefficient tells us that as Chara's goal assists go up, the LPG consumption in Israel also tends to increase. It's like watching a hockey game and suddenly realizing that the Zamboni and the propane tank might just be secret best friends.
Furthermore, the r-squared value of 0.5619410 suggests that approximately 56% of the variability in LPG consumption in Israel can be explained by variations in Zdeno Chara's Seasonal Total Goal Assists. This finding is not only statistically significant but also raises some eyebrow-raising questions. Could Chara's assists on the ice be fueling the energy consumption off the ice? It's almost as if his incredible passes have a direct line to the gas tanks in Israel, propelling both the puck and the propane to unexpected heights.
The p-value of less than 0.01 adds a touch of statistical stardom to our findings, indicating that the observed correlation is highly unlikely to have occurred by chance. In other words, this connection is as real as a game-winning goal in overtime. Perhaps it's time for us to consider putting "hockey assists" on the same level as "energy assists."
Fig. 1 presents a scatterplot illustrating the robust relationship between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas consumption in Israel. The plotted data points dance across the graph like energetic players on the ice, painting a picture of how a hockey player's performance can coalesce with energy usage in a distant land. It's a visual reminder that the world of statistics is full of surprises, much like discovering a hockey stick and a gas tank sitting side by side in an unexpected pairing.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has unearthed a remarkable correlation between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) consumption in Israel. The statistically significant connection between these seemingly unrelated entities suggests that the world of sports and energy usage may be more intertwined than we ever imagined. It's as if hockey assists can extend beyond the rink and into the realm of fueling energy needs—an unexpected power play indeed!

As we wrap up our analysis, it's hard not to marvel at the unexpected twists and turns that statistics can reveal. It's like finding out that the power play in hockey is not so different from the power play involved in energy consumption. And just like a well-executed slap shot, our findings have hit the target, demonstrating a strong relationship that beckons us to ponder the quirky intersections of athletic achievements and energy dynamics.

So, what's the punchline here? Well, it seems that Zdeno Chara's adeptness at setting up goals on the ice might just have a hand in influencing the consumption of LPG across the miles. It's a revelation that could make anyone do a double take, much like witnessing a goalie score a goal. It's clear that this unexpected link evokes a sense of awe and amusement, much like finding a puck in a sandpit or an ice rink in a tropical paradise—both improbable and undeniably fascinating.

In the grand scheme of things, our findings add a playful twist to the world of statistical analysis, reminding us that even the most unlikely connections can hold surprising significance. However, as much as we'd love to continue unraveling the mysteries of hockey-assisted energy dynamics, it seems we've reached the final buzzer. In the spirited spirit of statistical exploration, we assert that no further research is needed in this area. After all, we've already scored a hat trick of insights that are as captivating as they are unexpected. Let's toast to the delightful unpredictability of statistics, where even the most unlikely pairings can reveal fascinating truths.

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 Slap Shots and Gas Tanks: Uncovering the Surprising Link Between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas Consumption in Israel. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Sports Analytics and Energy Consumption

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 Slap Shots and Gas Tanks: Uncovering the Surprising Link Between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas Consumption in Israel. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Sports Analytics and Energy Consumption

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 Slap Shots and Gas Tanks: Uncovering the Surprising Link Between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas Consumption in Israel with an abstract of In this paper, we delve into the unexpected connection between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas (LPG) used in Israel. Utilizing data from Hockey Reference and the Energy Information Administration, we apply statistical analysis to explore this intriguing correlation. Our findings reveal a noteworthy correlation coefficient of 0.7496272 and a significant p-value of less than 0.01 from 1998 to 2022. The results not only shed light on the interplay between athletic achievements and energy consumption but also serve as a quirky reminder of the eccentricities that can emerge from data analysis.

ChatGPT:

Zdeno Chara, Seasonal, Total, Goal Assists, Liquefied Petroleum Gas, LPG, Israel, correlation, statistical analysis, Hockey Reference, Energy Information Administration, correlation coefficient, p-value, data analysis, athletic achievements, energy consumption

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

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Data details

Zdeno Chara's Seasonal Total Goal Assists
Source: Hockey Reference
See what else correlates with Zdeno Chara's Seasonal Total Goal Assists

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

Correlation r = 0.7496272 (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 = 0.5619410 (Coefficient of determination)
This means 56.2% of the change in the one variable (i.e., Liquefied petroleum gas used in Israel) is predictable based on the change in the other (i.e., Zdeno Chara's Seasonal Total Goal Assists) over the 25 years from 1998 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.61E-5.^Show 0.0000160860529418926800000000
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 0.75 in 0.00161% of random cases. Said differently, if you correlated 62,166 random variables^Note You don't actually need 62 thousand 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 24 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 24 because we have two variables measured over a period of 25 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.

[ 0.5, 0.88 ] 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.

	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Zdeno Chara's Seasonal Total Goal Assists (Goal Assist)	1	6	9	7	13	30	25	27	0	32	34	31	37	30	40	12	23	12	28	19	17	9	9	8	12
Liquefied petroleum gas used in Israel (Million Barrels/Day)	13.6247	12.6658	15.2104	13.9425	11.5836	17.2959	16.8934	16.9452	15.1205	19.411	17.1858	22.2137	23.1534	25.0027	29.9153	13.8438	13.6438	13.6	14.1858	14.3123	13.6603	14.4329	13.5383	13.7288	14.8301

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([1,6,9,7,13,30,25,27,0,32,34,31,37,30,40,12,23,12,28,19,17,9,9,8,12,])
array_2 = np.array([13.6247,12.6658,15.2104,13.9425,11.5836,17.2959,16.8934,16.9452,15.1205,19.411,17.1858,22.2137,23.1534,25.0027,29.9153,13.8438,13.6438,13.6,14.1858,14.3123,13.6603,14.4329,13.5383,13.7288,14.8301,])
array_1_name = "Zdeno Chara's Seasonal Total Goal Assists"
array_2_name = "Liquefied petroleum gas used in Israel"

# 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 Zdeno Chara's Seasonal Total Goal Assists
Line chart for only Liquefied petroleum gas used in Israel
The spurious research paper: Slap Shots and Gas Tanks: Uncovering the Surprising Link Between Zdeno Chara's Seasonal Total Goal Assists and Liquefied Petroleum Gas Consumption in Israel

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Correlation ID: 1156 · Black Variable ID: 268 · Red Variable ID: 24563


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