Download png, svg
AI explanation
Due to the smog drifting all the way to Europe, Austrian gasoline pumps were experiencing a 'haze' of confusion!
Model: dalle-3
Prompt: An image that looks like it is a scene from a Pixar movie: In Phoenix, the skyline is hazy, with smog hanging in the air. Nearby, a gas station sits quiet, with fewer cars stopping to fill up. Meanwhile, in Austria, gas pumps stand idle, as the lack of demand has caused a decrease in gasoline pumped. The link between the two cities is evident - the decrease in air quality in Phoenix has indeed led to a decrease in gasoline pumped in Austria. Enhanced visual prompt: Generate an image reminiscent of a scene from a Pixar movie, contrasting the hazy skyline of Phoenix with a quiet gas station and the idle gas pumps in Austria. Depict the smog hanging in the air in Phoenix and the noticeable decrease in demand for gasoline in Austria. The overall image should relay the connection between the decrease in air quality and the subsequent impact on gasoline consumption in a simple and visually striking manner. 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: Air quality in Phoenix and Gasoline pumped in Austria. 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: Oragami inspired by bauhaus Low poly An image that looks like it is a scene from a Pixar movie Cybernetic art
ChatGPT: An image that looks like it is a scene from a Pixar movie
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 Air quality in Phoenix and Gasoline pumped in Austria, in the following situation: Due to the decrease in air quality in Phoenix, the demand for gasoline decreased. This caused a ripple effect, leading to a decrease in gasoline pumped in Austria. Turns out, when the air quality's bad, people just can't "fuel" themselves to pump gas! Sucks to be gas-trapped!. Keep the description simple.
ChatGPT: In Phoenix, the skyline is hazy, with smog hanging in the air. Nearby, a gas station sits quiet, with fewer cars stopping to fill up. Meanwhile, in Austria, gas pumps stand idle, as the lack of demand has caused a decrease in gasoline pumped. The link between the two cities is evident - the decrease in air quality in Phoenix has indeed led to a decrease in gasoline pumped in Austria.
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: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: In Phoenix, the skyline is hazy, with smog hanging in the air. Nearby, a gas station sits quiet, with fewer cars stopping to fill up. Meanwhile, in Austria, gas pumps stand idle, as the lack of demand has caused a decrease in gasoline pumped. The link between the two cities is evident - the decrease in air quality in Phoenix has indeed led to a decrease in gasoline pumped in Austria. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: An image that looks like it is a scene from a Pixar movie: In Phoenix, the skyline is hazy, with smog hanging in the air. Nearby, a gas station sits quiet, with fewer cars stopping to fill up. Meanwhile, in Austria, gas pumps stand idle, as the lack of demand has caused a decrease in gasoline pumped. The link between the two cities is evident - the decrease in air quality in Phoenix has indeed led to a decrease in gasoline pumped in Austria. Enhanced visual prompt: Generate an image reminiscent of a scene from a Pixar movie, contrasting the hazy skyline of Phoenix with a quiet gas station and the idle gas pumps in Austria. Depict the smog hanging in the air in Phoenix and the noticeable decrease in demand for gasoline in Austria. The overall image should relay the connection between the decrease in air quality and the subsequent impact on gasoline consumption in a simple and visually striking manner.
*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.
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in Air quality in Phoenix caused Gasoline pumped in Austria to decrease. Add a funny one-liner at the end.
AI academic paper
 |
Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix? International Journal of Energy Transposition Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Air quality in Phoenix and Gasoline pumped in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Make the title punny if you can come up with clever pun. If not, make it sound serious.
Your research team used data from Environmental Protection Agency and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.7564606 and p < 0.01 for 1980 to 2022.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix?
[[ABSTRACT]]
The association between air quality in Phoenix and the amount of gasoline pumped in Austria has been a matter of curiosity for researchers and pun enthusiasts alike *chuckles*. In this study, we utilized data from the Environmental Protection Agency and the Energy Information Administration to delve into this enigmatic connection. Our findings revealed a 0.7564606 correlation coefficient and p < 0.01, providing compelling evidence to support a link between these two seemingly unrelated variables.
Despite the geographical distance and the puzzling nature of this correlation, the results highlight the surprising interdependence of global environmental factors *cue the eye-rolling from my colleagues*. Additionally, we couldn't help but wonder if a "Gas-o-line" could be drawn between these diverse locations, much to the amusement of our team.
We hope this research brings some levity to the traditionally serious field of environmental science *wink*.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Air quality in Phoenix and Gasoline pumped in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Here is the title and abstract of the paper:
[[TITLE]]
Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix?
[[ABSTRACT]]
The association between air quality in Phoenix and the amount of gasoline pumped in Austria has been a matter of curiosity for researchers and pun enthusiasts alike *chuckles*. In this study, we utilized data from the Environmental Protection Agency and the Energy Information Administration to delve into this enigmatic connection. Our findings revealed a 0.7564606 correlation coefficient and p < 0.01, providing compelling evidence to support a link between these two seemingly unrelated variables.
Despite the geographical distance and the puzzling nature of this correlation, the results highlight the surprising interdependence of global environmental factors *cue the eye-rolling from my colleagues*. Additionally, we couldn't help but wonder if a "Gas-o-line" could be drawn between these diverse locations, much to the amusement of our team.
We hope this research brings some levity to the traditionally serious field of environmental science *wink*.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
When it comes to the curious connections between seemingly unrelated variables, researchers are constantly in pursuit of that "Eureka!" moment. It's like a never-ending game of "connect the dots," with each discovery unveiling a new piece of the scientific puzzle. Speaking of puzzles, have you heard about the scientist who fell into a lab experiment? She ended up making a splash in the scientific community!
In the realm of environmental science, uncovering the intricate web of interactions between various factors can often lead to unexpected and downright quirky findings. Take, for instance, the perplexing relationship between air quality in Phoenix and the amount of gasoline pumped in Austria. At first glance, one might think these two variables would have as much in common as a fish on a bicycle. But as we delved into the data, we stumbled upon a correlation that left us scratching our heads – and reaching for the carbonated water for some fizzy inspiration.
You see, in the land of research, the hunt for knowledge can lead us down some truly fascinating paths. And sometimes, those paths intersect in the most unexpected ways. For example, did you hear about the statistician who got an award? He was overwhelmed with gratitude - it really tugged at his heartstrings! Okay, I'll stop with the puns... for now.
In this study, our goal was to explore the connection – or should we say, "combustible chemistry" – between these two variables. The environmental landscape in Phoenix, with its unique blend of desert air and urban emissions, may seem worlds apart from the quaint villages and alpine roads of Austria where fuel pumps hum away. Yet, as we crunched the numbers and sifted through the data, we found a statistical relationship that was as clear as a cloudless sky – a rare occurrence, indeed, in environmental research.
Now, I'd like to introduce you to our findings, but first, did you hear about the statistician who was asked what causes forest fires? He replied, "Well, a combination of chlorophyll, heat, and some burning questions!" *ba dum tss* Okay, I promise that was the last one, at least in this section. Let's dive into the remarkable connection between air quality in Phoenix and gasoline pumped in Austria, and see if we can't inject a little humor into the serious world of environmental science.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Air quality in Phoenix and Gasoline pumped in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
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 a few real TV shows that sound like they might be relevant to the topic that you watched as research.
Here is the title and abstract of the paper:
[[TITLE]]
Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix?
[[ABSTRACT]]
The association between air quality in Phoenix and the amount of gasoline pumped in Austria has been a matter of curiosity for researchers and pun enthusiasts alike *chuckles*. In this study, we utilized data from the Environmental Protection Agency and the Energy Information Administration to delve into this enigmatic connection. Our findings revealed a 0.7564606 correlation coefficient and p < 0.01, providing compelling evidence to support a link between these two seemingly unrelated variables.
Despite the geographical distance and the puzzling nature of this correlation, the results highlight the surprising interdependence of global environmental factors *cue the eye-rolling from my colleagues*. Additionally, we couldn't help but wonder if a "Gas-o-line" could be drawn between these diverse locations, much to the amusement of our team.
We hope this research brings some levity to the traditionally serious field of environmental science *wink*.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
When it comes to the curious connections between seemingly unrelated variables, researchers are constantly in pursuit of that "Eureka!" moment. It's like a never-ending game of "connect the dots," with each discovery unveiling a new piece of the scientific puzzle. Speaking of puzzles, have you heard about the scientist who fell into a lab experiment? She ended up making a splash in the scientific community!
In the realm of environmental science, uncovering the intricate web of interactions between various factors can often lead to unexpected and downright quirky findings. Take, for instance, the perplexing relationship between air quality in Phoenix and the amount of gasoline pumped in Austria. At first glance, one might think these two variables would have as much in common as a fish on a bicycle. But as we delved into the data, we stumbled upon a correlation that left us scratching our heads – and reaching for the carbonated water for some fizzy inspiration.
You see, in the land of research, the hunt for knowledge can lead us down some truly fascinating paths. And sometimes, those paths intersect in the most unexpected ways. For example, did you hear about the statistician who got an award? He was overwhelmed with gratitude - it really tugged at his heartstrings! Okay, I'll stop with the puns... for now.
In this study, our goal was to explore the connection – or should we say, "combustible chemistry" – between these two variables. The environmental landscape in Phoenix, with its unique blend of desert air and urban emissions, may seem worlds apart from the quaint villages and alpine roads of Austria where fuel pumps hum away. Yet, as we crunched the numbers and sifted through the data, we found a statistical relationship that was as clear as a cloudless sky – a rare occurrence, indeed, in environmental research.
Now, I'd like to introduce you to our findings, but first, did you hear about the statistician who was asked what causes forest fires? He replied, "Well, a combination of chlorophyll, heat, and some burning questions!" *ba dum tss* Okay, I promise that was the last one, at least in this section. Let's dive into the remarkable connection between air quality in Phoenix and gasoline pumped in Austria, and see if we can't inject a little humor into the serious world of environmental science.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The relationship between air quality in Phoenix and the amount of gasoline pumped in Austria has been the subject of interest for scientists and dad joke aficionados alike. Smith and Doe (2018) conducted a comprehensive analysis of air quality in urban areas and its association with transportation-related emissions. Their study provided valuable insight into the impact of vehicular exhaust on environmental air quality, shedding light on the potential global implications of such findings. Speaking of global implications, have you heard about the comedian who told a joke about pollution? It was a real gas!
In a parallel investigation, Jones (2019) explored the patterns of gasoline consumption in European countries, including the notable case of Austria. The study highlighted the diverse factors influencing fuel usage and its resonance with regional economic dynamics. It's like they say, "Austria's the word" when it comes to gasoline consumption data – pardon the cheesy play on words!
Turning to non-fiction books, Maas and Racz (2017) delved into the intricacies of air pollution and its impact on public health in their work, "Breathless Cities." Their research underscored the far-reaching consequences of poor air quality, raising awareness about the urgent need for environmental stewardship. The book sheds light on the importance of pristine air – after all, nobody wants to breathe in the exhaust of a schnitzel truck!
On the fiction front, Orwell's "1984" may not seem directly related to the topic at hand, but one could argue that the notion of oppressive air quality and societal control aligns with the critical importance of clean air. Plus, who wouldn't want to throw in a reference to a literary classic amidst all this research chatter, right?
As for TV shows, "Breaking Bad" provided a unique glimpse into the world of chemistry and its unexpected twists – much like the surprising correlation we uncovered in our study. And let's not forget "The Office,” where Michael Scott's humorous escapades at Dunder Mifflin provide a welcome break from the rigor of academia. We can all use a bit of comedic relief in the lab, just like Michael can use a gas station for his car debacle!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Air quality in Phoenix and Gasoline pumped in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Energy Information Administration . You used data from 1980 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]]
Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix?
[[ABSTRACT]]
The association between air quality in Phoenix and the amount of gasoline pumped in Austria has been a matter of curiosity for researchers and pun enthusiasts alike *chuckles*. In this study, we utilized data from the Environmental Protection Agency and the Energy Information Administration to delve into this enigmatic connection. Our findings revealed a 0.7564606 correlation coefficient and p < 0.01, providing compelling evidence to support a link between these two seemingly unrelated variables.
Despite the geographical distance and the puzzling nature of this correlation, the results highlight the surprising interdependence of global environmental factors *cue the eye-rolling from my colleagues*. Additionally, we couldn't help but wonder if a "Gas-o-line" could be drawn between these diverse locations, much to the amusement of our team.
We hope this research brings some levity to the traditionally serious field of environmental science *wink*.
[[INTRODUCTION]]
When it comes to the curious connections between seemingly unrelated variables, researchers are constantly in pursuit of that "Eureka!" moment. It's like a never-ending game of "connect the dots," with each discovery unveiling a new piece of the scientific puzzle. Speaking of puzzles, have you heard about the scientist who fell into a lab experiment? She ended up making a splash in the scientific community!
In the realm of environmental science, uncovering the intricate web of interactions between various factors can often lead to unexpected and downright quirky findings. Take, for instance, the perplexing relationship between air quality in Phoenix and the amount of gasoline pumped in Austria. At first glance, one might think these two variables would have as much in common as a fish on a bicycle. But as we delved into the data, we stumbled upon a correlation that left us scratching our heads – and reaching for the carbonated water for some fizzy inspiration.
You see, in the land of research, the hunt for knowledge can lead us down some truly fascinating paths. And sometimes, those paths intersect in the most unexpected ways. For example, did you hear about the statistician who got an award? He was overwhelmed with gratitude - it really tugged at his heartstrings! Okay, I'll stop with the puns... for now.
In this study, our goal was to explore the connection – or should we say, "combustible chemistry" – between these two variables. The environmental landscape in Phoenix, with its unique blend of desert air and urban emissions, may seem worlds apart from the quaint villages and alpine roads of Austria where fuel pumps hum away. Yet, as we crunched the numbers and sifted through the data, we found a statistical relationship that was as clear as a cloudless sky – a rare occurrence, indeed, in environmental research.
Now, I'd like to introduce you to our findings, but first, did you hear about the statistician who was asked what causes forest fires? He replied, "Well, a combination of chlorophyll, heat, and some burning questions!" *ba dum tss* Okay, I promise that was the last one, at least in this section. Let's dive into the remarkable connection between air quality in Phoenix and gasoline pumped in Austria, and see if we can't inject a little humor into the serious world of environmental science.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To unravel the enigmatic correlation between air quality in Phoenix and gasoline usage in Austria, we employed a meticulously crafted research methodology that combined a mix of traditional statistical analyses with a dash of unconventional approaches, not unlike whipping up a scientific soufflé at the research kitchen. Our data collection spanned from 1980 to 2022, ensuring a comprehensive examination of the long-standing relationship between these variables.
First, we gathered data on air quality in Phoenix, focusing on key air pollutants such as carbon monoxide, ozone, nitrogen dioxide, and sulfur dioxide. We then made sure to season our data with meteorological factors, including temperature, humidity, and wind patterns *insert chuckle about weather jokes*. As for the gasoline usage in Austria, we diligently extracted information on gasoline consumption patterns, fuel efficiency, and vehicular emissions, thanks to the treasure trove of data provided by the Energy Information Administration.
Next, we embarked on a wild statistical safari, where we tamed multivariate regression models to capture the interplay of various factors influencing air quality. The resulting model was as complex as a DNA helix and just as twisty! We then scrutinized the relationship between gasoline usage in Austria and air quality in Phoenix using correlation analyses, seeking to untangle the web of interconnections between these seemingly unrelated variables.
In order to ensure the statistical robustness of our findings, we applied rigorous quality control measures, including data validation and outlier detection. We also performed sensitivity analyses to test the stability of our results, akin to conducting a thorough taste test to ensure the statistical soup didn't leave a bad aftertaste. Our meticulous approach aimed to eliminate any potential confounding variables that could cloud the clarity of the relationship between gasoline usage in Austria and air quality in Phoenix.
Additionally, to spice up our methodology, we introduced a novel component – the incorporation of comedic relief during data analysis. The inclusion of puns and dad jokes during the statistical crunching process brought a lighthearted touch to our research team's work, proving that humor and rigorous scientific inquiry can indeed go hand in hand. After all, who says statistical analyses can't be peppered with playful pizzazz?
Finally, we conducted sensitivity analyses to test the reliability of our findings and used robust statistical techniques to account for any potential lurking variables that could threaten the validity of our results. Our approach aimed to leave no stone unturned, much like an investigative reporter in pursuit of the truth in a Hollywood mystery!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Air quality in Phoenix and Gasoline pumped in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Energy Information Administration .
For the time period 1980 to 2022, you found a correlation 0.7564606, r-squared of 0.5722326, and p < 0.01.
One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.
Here is the title and abstract of the paper:
[[TITLE]]
Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix?
[[ABSTRACT]]
The association between air quality in Phoenix and the amount of gasoline pumped in Austria has been a matter of curiosity for researchers and pun enthusiasts alike *chuckles*. In this study, we utilized data from the Environmental Protection Agency and the Energy Information Administration to delve into this enigmatic connection. Our findings revealed a 0.7564606 correlation coefficient and p < 0.01, providing compelling evidence to support a link between these two seemingly unrelated variables.
Despite the geographical distance and the puzzling nature of this correlation, the results highlight the surprising interdependence of global environmental factors *cue the eye-rolling from my colleagues*. Additionally, we couldn't help but wonder if a "Gas-o-line" could be drawn between these diverse locations, much to the amusement of our team.
We hope this research brings some levity to the traditionally serious field of environmental science *wink*.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
When it comes to the curious connections between seemingly unrelated variables, researchers are constantly in pursuit of that "Eureka!" moment. It's like a never-ending game of "connect the dots," with each discovery unveiling a new piece of the scientific puzzle. Speaking of puzzles, have you heard about the scientist who fell into a lab experiment? She ended up making a splash in the scientific community!
In the realm of environmental science, uncovering the intricate web of interactions between various factors can often lead to unexpected and downright quirky findings. Take, for instance, the perplexing relationship between air quality in Phoenix and the amount of gasoline pumped in Austria. At first glance, one might think these two variables would have as much in common as a fish on a bicycle. But as we delved into the data, we stumbled upon a correlation that left us scratching our heads – and reaching for the carbonated water for some fizzy inspiration.
You see, in the land of research, the hunt for knowledge can lead us down some truly fascinating paths. And sometimes, those paths intersect in the most unexpected ways. For example, did you hear about the statistician who got an award? He was overwhelmed with gratitude - it really tugged at his heartstrings! Okay, I'll stop with the puns... for now.
In this study, our goal was to explore the connection – or should we say, "combustible chemistry" – between these two variables. The environmental landscape in Phoenix, with its unique blend of desert air and urban emissions, may seem worlds apart from the quaint villages and alpine roads of Austria where fuel pumps hum away. Yet, as we crunched the numbers and sifted through the data, we found a statistical relationship that was as clear as a cloudless sky – a rare occurrence, indeed, in environmental research.
Now, I'd like to introduce you to our findings, but first, did you hear about the statistician who was asked what causes forest fires? He replied, "Well, a combination of chlorophyll, heat, and some burning questions!" *ba dum tss* Okay, I promise that was the last one, at least in this section. Let's dive into the remarkable connection between air quality in Phoenix and gasoline pumped in Austria, and see if we can't inject a little humor into the serious world of environmental science.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The analysis of the data from 1980 to 2022 revealed a significant positive correlation of 0.7564606 between air quality in Phoenix and the amount of gasoline pumped in Austria. This finding suggests that as the level of gasoline pumping in Austria increased, air quality in Phoenix improved, leaving us pondering if gasoline fumes could be the next eco-friendly solution *wink*.
Our team also calculated the r-squared value, which stood at 0.5722326, indicating that approximately 57.2% of the variability in air quality in Phoenix can be explained by the variability in gasoline pumped in Austria. This result further solidifies the strength of the relationship and left us gasping for breath at the unexpected connection.
In addition, the p-value being less than 0.01 provides strong evidence against the null hypothesis. If only all scientific conclusions were this clear-cut! It's as if the universe decided to throw us a bone and make this correlation as unambiguous as possible *chuckles*.
Ultimately, our findings underscore the interdependence of global environmental factors and the unforeseen relationships that can emerge from the maze of data. It’s like stumbling upon a hidden treasure in a statistical jungle, or as I like to call it, a statistical "gold" mine *winks*.
As Fig. 1 showcases, the scatterplot graphically illustrates the robust positive correlation between air quality in Phoenix and gasoline pumped in Austria. It's a plot twist worthy of a best-selling mystery novel, highlighting the unexpected and thought-provoking nature of this scientific discovery.
In conclusion, our research illuminates a previously unidentified link between these two variables, challenging our assumptions and adding a touch of whimsy to the oftentimes staid world of environmental science. After all, who would have thought that the fumes from Austrian gas pumps could have a breath-taking impact on air quality in Phoenix? It’s both a scientific marvel and a source of endless dad jokes *smirks*.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Air quality in Phoenix and Gasoline pumped in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Limit your response to 500 tokens.
Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.
Do not write a conclusion. I will add a conclusion after this.
[[TITLE]]
Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix?
[[ABSTRACT]]
The association between air quality in Phoenix and the amount of gasoline pumped in Austria has been a matter of curiosity for researchers and pun enthusiasts alike *chuckles*. In this study, we utilized data from the Environmental Protection Agency and the Energy Information Administration to delve into this enigmatic connection. Our findings revealed a 0.7564606 correlation coefficient and p < 0.01, providing compelling evidence to support a link between these two seemingly unrelated variables.
Despite the geographical distance and the puzzling nature of this correlation, the results highlight the surprising interdependence of global environmental factors *cue the eye-rolling from my colleagues*. Additionally, we couldn't help but wonder if a "Gas-o-line" could be drawn between these diverse locations, much to the amusement of our team.
We hope this research brings some levity to the traditionally serious field of environmental science *wink*.
[[LITERATURE REVIEW]]
The relationship between air quality in Phoenix and the amount of gasoline pumped in Austria has been the subject of interest for scientists and dad joke aficionados alike. Smith and Doe (2018) conducted a comprehensive analysis of air quality in urban areas and its association with transportation-related emissions. Their study provided valuable insight into the impact of vehicular exhaust on environmental air quality, shedding light on the potential global implications of such findings. Speaking of global implications, have you heard about the comedian who told a joke about pollution? It was a real gas!
In a parallel investigation, Jones (2019) explored the patterns of gasoline consumption in European countries, including the notable case of Austria. The study highlighted the diverse factors influencing fuel usage and its resonance with regional economic dynamics. It's like they say, "Austria's the word" when it comes to gasoline consumption data – pardon the cheesy play on words!
Turning to non-fiction books, Maas and Racz (2017) delved into the intricacies of air pollution and its impact on public health in their work, "Breathless Cities." Their research underscored the far-reaching consequences of poor air quality, raising awareness about the urgent need for environmental stewardship. The book sheds light on the importance of pristine air – after all, nobody wants to breathe in the exhaust of a schnitzel truck!
On the fiction front, Orwell's "1984" may not seem directly related to the topic at hand, but one could argue that the notion of oppressive air quality and societal control aligns with the critical importance of clean air. Plus, who wouldn't want to throw in a reference to a literary classic amidst all this research chatter, right?
As for TV shows, "Breaking Bad" provided a unique glimpse into the world of chemistry and its unexpected twists – much like the surprising correlation we uncovered in our study. And let's not forget "The Office,” where Michael Scott's humorous escapades at Dunder Mifflin provide a welcome break from the rigor of academia. We can all use a bit of comedic relief in the lab, just like Michael can use a gas station for his car debacle!
[[RESULTS]]
The analysis of the data from 1980 to 2022 revealed a significant positive correlation of 0.7564606 between air quality in Phoenix and the amount of gasoline pumped in Austria. This finding suggests that as the level of gasoline pumping in Austria increased, air quality in Phoenix improved, leaving us pondering if gasoline fumes could be the next eco-friendly solution *wink*.
Our team also calculated the r-squared value, which stood at 0.5722326, indicating that approximately 57.2% of the variability in air quality in Phoenix can be explained by the variability in gasoline pumped in Austria. This result further solidifies the strength of the relationship and left us gasping for breath at the unexpected connection.
In addition, the p-value being less than 0.01 provides strong evidence against the null hypothesis. If only all scientific conclusions were this clear-cut! It's as if the universe decided to throw us a bone and make this correlation as unambiguous as possible *chuckles*.
Ultimately, our findings underscore the interdependence of global environmental factors and the unforeseen relationships that can emerge from the maze of data. It’s like stumbling upon a hidden treasure in a statistical jungle, or as I like to call it, a statistical "gold" mine *winks*.
As Fig. 1 showcases, the scatterplot graphically illustrates the robust positive correlation between air quality in Phoenix and gasoline pumped in Austria. It's a plot twist worthy of a best-selling mystery novel, highlighting the unexpected and thought-provoking nature of this scientific discovery.
In conclusion, our research illuminates a previously unidentified link between these two variables, challenging our assumptions and adding a touch of whimsy to the oftentimes staid world of environmental science. After all, who would have thought that the fumes from Austrian gas pumps could have a breath-taking impact on air quality in Phoenix? It’s both a scientific marvel and a source of endless dad jokes *smirks*.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The results of our study provide compelling evidence to support the previously hinted-at connection between air quality in Phoenix and the amount of gasoline pumped in Austria. Our findings parallel those of Smith and Doe (2018) who emphasized the impact of vehicular exhaust on environmental air quality. It seems the correlation we stumbled upon was not just a fume-y fantasy after all *chuckles*.
The unexpected positive correlation coefficient of 0.7564606 and the r-squared value of 0.5722326 align with the surprising patterns of gasoline consumption in European countries noted by Jones (2019). It's like binging on a series that’s full of plot twists – you never know what you might find *winks*. The p-value being less than 0.01 also lends robust support to the notion that there's more to this correlation than meets the eye. It's as if the science deities decided to gift us with a statistical slam dunk!
Delving into the literature, the work of Maas and Racz (2017) underscored the far-reaching consequences of poor air quality, mirroring the real-world implications of our research findings. Plus, the nod to Orwell's "1984" serves as a friendly reminder of the significance of environmental stewardship amidst this sea of scientific discovery. Speaking of seas, did you hear about the oceanographer who broke up with her boyfriend? She said, "I'm tides of you!”
The scatterplot in Fig. 1 not only graphically illustrates the robust positive correlation between air quality in Phoenix and gasoline pumped in Austria, but it also highlights the unexpected and thought-provoking nature of this scientific discovery. It's like finding the punchline to a joke you didn't even know you were setting up *smirks*.
Our research, while undoubtedly quirky, sheds light on the interconnectedness of seemingly diverse variables and adds a dash of humor to the field of environmental science. It's as if the universe decided to engage in some "gas-lighting" of its own, leaving us all to marvel at the whimsical nature of scientific discovery. Stay tuned for the sequel – "Diesel Dynamics: A Tale of Two Cities" *smiles*!
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Air quality in Phoenix and Gasoline pumped in Austria. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.
Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix?
[[ABSTRACT]]
The association between air quality in Phoenix and the amount of gasoline pumped in Austria has been a matter of curiosity for researchers and pun enthusiasts alike *chuckles*. In this study, we utilized data from the Environmental Protection Agency and the Energy Information Administration to delve into this enigmatic connection. Our findings revealed a 0.7564606 correlation coefficient and p < 0.01, providing compelling evidence to support a link between these two seemingly unrelated variables.
Despite the geographical distance and the puzzling nature of this correlation, the results highlight the surprising interdependence of global environmental factors *cue the eye-rolling from my colleagues*. Additionally, we couldn't help but wonder if a "Gas-o-line" could be drawn between these diverse locations, much to the amusement of our team.
We hope this research brings some levity to the traditionally serious field of environmental science *wink*.
[[INTRDUCTION]]
When it comes to the curious connections between seemingly unrelated variables, researchers are constantly in pursuit of that "Eureka!" moment. It's like a never-ending game of "connect the dots," with each discovery unveiling a new piece of the scientific puzzle. Speaking of puzzles, have you heard about the scientist who fell into a lab experiment? She ended up making a splash in the scientific community!
In the realm of environmental science, uncovering the intricate web of interactions between various factors can often lead to unexpected and downright quirky findings. Take, for instance, the perplexing relationship between air quality in Phoenix and the amount of gasoline pumped in Austria. At first glance, one might think these two variables would have as much in common as a fish on a bicycle. But as we delved into the data, we stumbled upon a correlation that left us scratching our heads – and reaching for the carbonated water for some fizzy inspiration.
You see, in the land of research, the hunt for knowledge can lead us down some truly fascinating paths. And sometimes, those paths intersect in the most unexpected ways. For example, did you hear about the statistician who got an award? He was overwhelmed with gratitude - it really tugged at his heartstrings! Okay, I'll stop with the puns... for now.
In this study, our goal was to explore the connection – or should we say, "combustible chemistry" – between these two variables. The environmental landscape in Phoenix, with its unique blend of desert air and urban emissions, may seem worlds apart from the quaint villages and alpine roads of Austria where fuel pumps hum away. Yet, as we crunched the numbers and sifted through the data, we found a statistical relationship that was as clear as a cloudless sky – a rare occurrence, indeed, in environmental research.
Now, I'd like to introduce you to our findings, but first, did you hear about the statistician who was asked what causes forest fires? He replied, "Well, a combination of chlorophyll, heat, and some burning questions!" *ba dum tss* Okay, I promise that was the last one, at least in this section. Let's dive into the remarkable connection between air quality in Phoenix and gasoline pumped in Austria, and see if we can't inject a little humor into the serious world of environmental science.
[[RESULTS]]
The analysis of the data from 1980 to 2022 revealed a significant positive correlation of 0.7564606 between air quality in Phoenix and the amount of gasoline pumped in Austria. This finding suggests that as the level of gasoline pumping in Austria increased, air quality in Phoenix improved, leaving us pondering if gasoline fumes could be the next eco-friendly solution *wink*.
Our team also calculated the r-squared value, which stood at 0.5722326, indicating that approximately 57.2% of the variability in air quality in Phoenix can be explained by the variability in gasoline pumped in Austria. This result further solidifies the strength of the relationship and left us gasping for breath at the unexpected connection.
In addition, the p-value being less than 0.01 provides strong evidence against the null hypothesis. If only all scientific conclusions were this clear-cut! It's as if the universe decided to throw us a bone and make this correlation as unambiguous as possible *chuckles*.
Ultimately, our findings underscore the interdependence of global environmental factors and the unforeseen relationships that can emerge from the maze of data. It’s like stumbling upon a hidden treasure in a statistical jungle, or as I like to call it, a statistical "gold" mine *winks*.
As Fig. 1 showcases, the scatterplot graphically illustrates the robust positive correlation between air quality in Phoenix and gasoline pumped in Austria. It's a plot twist worthy of a best-selling mystery novel, highlighting the unexpected and thought-provoking nature of this scientific discovery.
In conclusion, our research illuminates a previously unidentified link between these two variables, challenging our assumptions and adding a touch of whimsy to the oftentimes staid world of environmental science. After all, who would have thought that the fumes from Austrian gas pumps could have a breath-taking impact on air quality in Phoenix? It’s both a scientific marvel and a source of endless dad jokes *smirks*.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our study has hilariously shed light on the unexpected link between air quality in Phoenix and the amount of gasoline pumped in Austria. This connection is as surprising as finding a nerdy statistician at a comic convention *wink*. Our findings have left us gasping for breath, not just from the air quality improvement but also from the humorous conundrum of this correlation.
The statistically significant positive correlation coefficient of 0.7564606 has left us wondering if these gasoline fumes are secretly the environmental superheroes we never knew we needed *chuckles*. The r-squared value of 0.5722326 also suggests that gasoline pumped in Austria explains approximately 57.2% of the variability in air quality in Phoenix - talk about a "gas-tastic" revelation, am I right? *ba dum tss*
And let's not forget the p-value being less than 0.01, providing us with evidence so strong, it's like the universe decided to shout, "Hey, look at this connection, it's as clear as day!" *winks*.
Our findings have added a sprinkle of levity to the typically serious world of environmental science, showing that even in the realm of data and statistics, there's room for some lighthearted amusement. It's as if science itself decided to pull the ultimate prank on our expectations – and the joke's on us, for not seeing this correlation earlier *chuckles*.
With these amusing results, we confidently assert that no further research in this peculiar area is needed. We've unmasked this unexpected connection, and it's time to let these gasoline and air quality findings fuel our laughter and imagination.
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 Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix?. Respond only with the name of a fictional academic journal.
ChatGPT:
International Journal of Energy Transposition
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 Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix?. Respond only with the name of a fictional organization.
ChatGPT:
The Institute for Transcontinental Fuel Studies
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 Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix? with an abstract of The association between air quality in Phoenix and the amount of gasoline pumped in Austria has been a matter of curiosity for researchers and pun enthusiasts alike *chuckles*. In this study, we utilized data from the Environmental Protection Agency and the Energy Information Administration to delve into this enigmatic connection. Our findings revealed a 0.7564606 correlation coefficient and p < 0.01, providing compelling evidence to support a link between these two seemingly unrelated variables.
Despite the geographical distance and the puzzling nature of this correlation, the results highlight the surprising interdependence of global environmental factors *cue the eye-rolling from my colleagues*. Additionally, we couldn't help but wonder if a "Gas-o-line" could be drawn between these diverse locations, much to the amusement of our team.
We hope this research brings some levity to the traditionally serious field of environmental science *wink*.
ChatGPT:
gasoline consumption, air quality, correlation study, Environmental Protection Agency, Energy Information Administration, global environmental factors
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Air quality in PhoenixDetailed data title: Percentage of days with good air quality in Phoenix-Mesa-Scottsdale, AZ
Source: Environmental Protection Agency
See what else correlates with Air quality in Phoenix
Gasoline pumped in Austria
Detailed data title: Volume of gasoline pumped consumed in Austria in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Gasoline pumped in Austria
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 = 0.5722326 (Coefficient of determination)
This means 57.2% of the change in the one variable (i.e., Gasoline pumped in Austria) is predictable based on the change in the other (i.e., Air quality in Phoenix) over the 43 years from 1980 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.4E-9. 0.0000000044321052403070120000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.
But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.
Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.76 in 4.4E-7% of random cases. Said differently, if you correlated 225,626,411 random variables You don't actually need 225 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.
p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.
In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.
Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 42 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 42 because we have two variables measured over a period of 43 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.
[ 0.59, 0.86 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
| 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 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 | |
| Air quality in Phoenix (Good air quality) | 25.0689 | 17.2603 | 25.7534 | 24.3836 | 9.56284 | 11.5068 | 13.1507 | 18.1818 | 24.0437 | 24.3836 | 27.9452 | 26.5753 | 21.8579 | 27.6712 | 20.8219 | 14.2466 | 15.847 | 8.49315 | 9.31507 | 1.36986 | 5.7377 | 8.21918 | 8.49315 | 11.7808 | 16.3934 | 13.4247 | 3.0137 | 6.0274 | 11.7486 | 6.84932 | 16.1644 | 5.47945 | 6.28415 | 8.21918 | 6.0274 | 13.9726 | 7.10383 | 8.76712 | 11.5068 | 13.6986 | 3.00546 | 3.0137 | 9.31507 |
| Gasoline pumped in Austria (Million Barrels/Day) | 57 | 57 | 57 | 58 | 56.5628 | 56.2521 | 57.0192 | 57.9616 | 59.1011 | 60.0959 | 59.0603 | 64.611 | 61.8005 | 59.4959 | 57.4356 | 55.3973 | 51.2514 | 48.7342 | 51.0247 | 47.5753 | 45.735 | 46.074 | 49.6575 | 50.8356 | 49.8661 | 48.7726 | 46.1178 | 45.5151 | 43.9781 | 43.2247 | 42.9068 | 39.8027 | 39.5984 | 38.5534 | 37.5699 | 37.9781 | 37.8087 | 37.4767 | 38.389 | 38.1973 | 31.8306 | 33.3425 | 34.7233 |
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
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
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.
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. 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([25.0689,17.2603,25.7534,24.3836,9.56284,11.5068,13.1507,18.1818,24.0437,24.3836,27.9452,26.5753,21.8579,27.6712,20.8219,14.2466,15.847,8.49315,9.31507,1.36986,5.7377,8.21918,8.49315,11.7808,16.3934,13.4247,3.0137,6.0274,11.7486,6.84932,16.1644,5.47945,6.28415,8.21918,6.0274,13.9726,7.10383,8.76712,11.5068,13.6986,3.00546,3.0137,9.31507,])
array_2 = np.array([57,57,57,58,56.5628,56.2521,57.0192,57.9616,59.1011,60.0959,59.0603,64.611,61.8005,59.4959,57.4356,55.3973,51.2514,48.7342,51.0247,47.5753,45.735,46.074,49.6575,50.8356,49.8661,48.7726,46.1178,45.5151,43.9781,43.2247,42.9068,39.8027,39.5984,38.5534,37.5699,37.9781,37.8087,37.4767,38.389,38.1973,31.8306,33.3425,34.7233,])
array_1_name = "Air quality in Phoenix"
array_2_name = "Gasoline pumped in Austria"
# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)
# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)Reuseable content
You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.
For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.
Download images for these variables:
- High resolution line chart
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 Air quality in Phoenix
- Line chart for only Gasoline pumped in Austria
- AI-generated correlation image
- The spurious research paper: Gasoline Pumped in Austria: A Breath of Fresh Air for Phoenix?
Thanks for being the explorer we needed!
Correlation ID: 3453 · Black Variable ID: 21062 · Red Variable ID: 24162
