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AI explanation
As Lionel Messi's goal count for Argentina rises, the demand for chemical equipment in Florida grows, leading to an increase in operators and tenders wanting to be in on the action. It's a Messi chemical reaction that's just too enticing to resist!
Model: dalle-3
Prompt: Generate a cybernetic art representation capturing the dynamic energy of a packed soccer stadium in Argentina where Lionel Messi, in his national team's colors, jubilantly celebrates scoring a goal. In the same digital canvas, contrast the vibrancy with a futuristic industrial scene in Florida, featuring chemical equipment operators and tenders engrossed in the precise management of high-tech machinery. Let the visual merge the raw emotions of sports with the technical skill of industrial operation, blending the settings seamlessly in a captivating and evocative cybernetic style. 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: Lionel Messi's goal count for Argentina and The number of chemical equipment operators and tenders in Florida. 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: Cybernetic art Cyberpunk Steampunk An image that looks like it is a scene from A Disney Movie Cybernetic art
ChatGPT: Cybernetic art
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 Lionel Messi's goal count for Argentina and The number of chemical equipment operators and tenders in Florida together. Keep the description simple.
ChatGPT: A soccer stadium in Argentina is filled with cheering fans as Lionel Messi celebrates scoring a goal for his national team. Meanwhile, in Florida, a group of chemical equipment operators and tenders work diligently in a manufacturing facility, ensuring the safe and efficient operation of the chemical equipment.
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: [ Cybernetic art ] and depicting this scene: A soccer stadium in Argentina is filled with cheering fans as Lionel Messi celebrates scoring a goal for his national team. Meanwhile, in Florida, a group of chemical equipment operators and tenders work diligently in a manufacturing facility, ensuring the safe and efficient operation of the chemical equipment. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate a cybernetic art representation capturing the dynamic energy of a packed soccer stadium in Argentina where Lionel Messi, in his national team's colors, jubilantly celebrates scoring a goal. In the same digital canvas, contrast the vibrancy with a futuristic industrial scene in Florida, featuring chemical equipment operators and tenders engrossed in the precise management of high-tech machinery. Let the visual merge the raw emotions of sports with the technical skill of industrial operation, blending the settings seamlessly in a captivating and evocative cybernetic style.
*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 an increase in Lionel Messi's goal count for Argentina caused The number of chemical equipment operators and tenders in Florida to increase. Include one good pun.
AI academic paper
 |
Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida The Journal of Athletic Alchemy Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Lionel Messi's goal count for Argentina and The number of chemical equipment operators and tenders in Florida. 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, just make it sound clever.
Your research team used data from Wikipedia and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.8685682 and p < 0.01 for 2006 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]]
"Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida"
[[ABSTRACT]]
In this study, we tackle the riveting question of how the prolific goal-scoring prowess of renowned footballer Lionel Messi for the Argentina national team influences the employment status of chemical equipment operators and tenders in the Sunshine State of Florida. With a dash of statistical rigor and a sprinkle of soccer spirit, we delved into the data from Wikipedia and the Bureau of Labor Statistics to uncover the potential correlation between these seemingly unrelated fields.
Our findings revealed a correlation coefficient of 0.8685682 with a p-value less than 0.01 for the years spanning 2006 to 2022. It seems that Messi's goal-counting expertise on the pitch may indeed have an unexpected impact on the demand for chemical equipment operators and tenders in Florida. Who would have thought that soccer goals and chemical compound mixtures could be so romantically intertwined?
Nevertheless, as researchers, we must exercise caution in drawing strict causal associations between these variables. As the classic dad joke goes, correlation does not necessarily imply causation – after all, we wouldn't want to jump to conclusions as fast as Messi takes a free-kick.
The implications of our findings stretch beyond the realm of sport or chemistry, highlighting the interconnectedness of seemingly disparate elements in our world. As we continue to unravel the mysterious web of cause and effect, we are reminded of the whimsical and sometimes downright magical nature of scientific inquiry. Who knows, perhaps Messi's next hat-trick will spark a boom in the detergent industry – the Messi effect in full swing!
Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Lionel Messi's goal count for Argentina and The number of chemical equipment operators and tenders in Florida. 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]]
"Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida"
[[ABSTRACT]]
In this study, we tackle the riveting question of how the prolific goal-scoring prowess of renowned footballer Lionel Messi for the Argentina national team influences the employment status of chemical equipment operators and tenders in the Sunshine State of Florida. With a dash of statistical rigor and a sprinkle of soccer spirit, we delved into the data from Wikipedia and the Bureau of Labor Statistics to uncover the potential correlation between these seemingly unrelated fields.
Our findings revealed a correlation coefficient of 0.8685682 with a p-value less than 0.01 for the years spanning 2006 to 2022. It seems that Messi's goal-counting expertise on the pitch may indeed have an unexpected impact on the demand for chemical equipment operators and tenders in Florida. Who would have thought that soccer goals and chemical compound mixtures could be so romantically intertwined?
Nevertheless, as researchers, we must exercise caution in drawing strict causal associations between these variables. As the classic dad joke goes, correlation does not necessarily imply causation – after all, we wouldn't want to jump to conclusions as fast as Messi takes a free-kick.
The implications of our findings stretch beyond the realm of sport or chemistry, highlighting the interconnectedness of seemingly disparate elements in our world. As we continue to unravel the mysterious web of cause and effect, we are reminded of the whimsical and sometimes downright magical nature of scientific inquiry. Who knows, perhaps Messi's next hat-trick will spark a boom in the detergent industry – the Messi effect in full swing!
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
In the realm of research, it's often said that the pursuit of knowledge is a goal-oriented endeavor - and today, we're taking that quite literally. Our study delves into the unlikely connection between the prolific performance of the soccer sensation, Lionel Messi, and the employment dynamics of chemical equipment operators and tenders in Florida. As we explore this unconventional correlation, we are reminded of the timeless question: is it Messi-nic or just Messi-d up?
In the world of statistics, we are accustomed to seeking relationships between variables that are, well, a bit more expected. But who could resist investigating the tantalizing possibility that a goal scored by Messi could lead to the stirring up of job opportunities for chemical equipment operators and tenders? It's almost as unexpected as finding a Nobel Prize winner in a litter of compounds!
As researchers, we thrive on unearthing these unexpected connections – or should we say, Messi connections? It's a reminder that the web of cause and effect in the world is often as perplexing and intricate as a chemical reaction. After all, who would have thought that the path to understanding chemistry could lead us through the world of sports?
But before we dive into the data and unveil the statistical insights, let's acknowledge the potential pitfalls of making hasty assumptions. As the esteemed dad joke of research dictates, correlation does not imply causation - just like a perfectly balanced equation does not guarantee a successful experiment. We’ll tread cautiously, just like a midfielder tiptoeing along the edge of an offside position.
So, as we embark on this Messi-merizing journey of discovery, our aim is to shed light on the serendipitous and sometimes downright whimsical nature of scientific inquiry. Who knows, perhaps our findings will inspire a whole new field of study: Messi-matics. After all, in the world of research, unexpected findings are often the goal.
Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Lionel Messi's goal count for Argentina and The number of chemical equipment operators and tenders in Florida. 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 cite some social media posts you read that seem to be related.
Here is the title and abstract of the paper:
[[TITLE]]
"Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida"
[[ABSTRACT]]
In this study, we tackle the riveting question of how the prolific goal-scoring prowess of renowned footballer Lionel Messi for the Argentina national team influences the employment status of chemical equipment operators and tenders in the Sunshine State of Florida. With a dash of statistical rigor and a sprinkle of soccer spirit, we delved into the data from Wikipedia and the Bureau of Labor Statistics to uncover the potential correlation between these seemingly unrelated fields.
Our findings revealed a correlation coefficient of 0.8685682 with a p-value less than 0.01 for the years spanning 2006 to 2022. It seems that Messi's goal-counting expertise on the pitch may indeed have an unexpected impact on the demand for chemical equipment operators and tenders in Florida. Who would have thought that soccer goals and chemical compound mixtures could be so romantically intertwined?
Nevertheless, as researchers, we must exercise caution in drawing strict causal associations between these variables. As the classic dad joke goes, correlation does not necessarily imply causation – after all, we wouldn't want to jump to conclusions as fast as Messi takes a free-kick.
The implications of our findings stretch beyond the realm of sport or chemistry, highlighting the interconnectedness of seemingly disparate elements in our world. As we continue to unravel the mysterious web of cause and effect, we are reminded of the whimsical and sometimes downright magical nature of scientific inquiry. Who knows, perhaps Messi's next hat-trick will spark a boom in the detergent industry – the Messi effect in full swing!
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the realm of research, it's often said that the pursuit of knowledge is a goal-oriented endeavor - and today, we're taking that quite literally. Our study delves into the unlikely connection between the prolific performance of the soccer sensation, Lionel Messi, and the employment dynamics of chemical equipment operators and tenders in Florida. As we explore this unconventional correlation, we are reminded of the timeless question: is it Messi-nic or just Messi-d up?
In the world of statistics, we are accustomed to seeking relationships between variables that are, well, a bit more expected. But who could resist investigating the tantalizing possibility that a goal scored by Messi could lead to the stirring up of job opportunities for chemical equipment operators and tenders? It's almost as unexpected as finding a Nobel Prize winner in a litter of compounds!
As researchers, we thrive on unearthing these unexpected connections – or should we say, Messi connections? It's a reminder that the web of cause and effect in the world is often as perplexing and intricate as a chemical reaction. After all, who would have thought that the path to understanding chemistry could lead us through the world of sports?
But before we dive into the data and unveil the statistical insights, let's acknowledge the potential pitfalls of making hasty assumptions. As the esteemed dad joke of research dictates, correlation does not imply causation - just like a perfectly balanced equation does not guarantee a successful experiment. We’ll tread cautiously, just like a midfielder tiptoeing along the edge of an offside position.
So, as we embark on this Messi-merizing journey of discovery, our aim is to shed light on the serendipitous and sometimes downright whimsical nature of scientific inquiry. Who knows, perhaps our findings will inspire a whole new field of study: Messi-matics. After all, in the world of research, unexpected findings are often the goal.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The influential work of Smith and colleagues (2015) examined the performance of Lionel Messi for the Argentina national team in relation to his goal-scoring prowess. The authors find a consistent pattern of Messi's exceptional ability to find the back of the net, even when faced with the most formidable opponents. It's almost as if Messi has a chemistry with the goal that rivals the most stable chemical compounds.
On the other hand, Doe and Jones (2018) carried out an analysis of the employment trends in Florida's chemical industry. Their study reveals an upward trajectory in the demand for chemical equipment operators and tenders, particularly during the years coinciding with major international football tournaments. It's almost like the employment trend is doing a Messi dance of its own, isn't it?
Now, turning to some non-fiction sources that lend insight into the intricate relationship between sports and employment, "Socceronomics" by Kuper and Szymanski touches upon the economic impacts of football on various aspects of society. In a somewhat unexpected twist, the book delves into workforce trends influenced by the beautiful game, raising intriguing parallels to our current study. It's as if soccer and chemistry are about to engage in a game of employment catenaccio.
In a similar vein, "Freakonomics" by Levitt and Dubner delves into the unexpected connections that underpin our world. While not directly related to our subject matter, one cannot help but wonder if Messi's goals hold the power to influence economic phenomena far beyond the football pitch. It's almost like Messi's goals have the potential to turn the economic world upside down – or, in this case, "Freakonomics" it.
On a more whimsical note, the fictitious novel "The Goal Whisperer" by Fictional Author explores the mystical connection between a legendary soccer player's goals and their impact on the fabric of reality. While we may not take the book's content as empirical evidence, the notion of Messi's goals holding a mystical sway over the employment market makes for an entertaining and Messi-merizing read.
Moreover, "The Elements of Style" by Strunk and White offers a compelling guide to the nuances of writing and communication. While unrelated to our study, the element of surprise and style in Messi's goals may have inadvertently contributed to the employment trends we observe. It's almost as if Messi's goals are a literary masterpiece, weaving their way through the employment statistics with a lyrical finesse.
In an era of social media dominance, a tweet from @FootballStats2020 catches our attention: "Messi's hat-trick coincides with a sudden surge in job postings for chemical equipment operators in Florida – coincidence or Messi's hidden talent in catalyzing job markets?" While we must exercise caution in attributing these findings solely to Messi's on-field heroics, the tweet raises a thought-provoking hypothesis. It's almost as if Messi's hat-trick goals have the potential to stir up employment opportunities with the same fervor as a well-mixed chemical solution.
As we consider the curious mesh of statistical data and unexpected connections, it's essential to maintain a lighthearted perspective. Just as a chemist wouldn't mix the wrong elements, we must approach these findings with due diligence and a sprinkling of humor. After all, in the game of research, a good pun is Messi as a vital finding!
Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Lionel Messi's goal count for Argentina and The number of chemical equipment operators and tenders in Florida. 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 Wikipedia and Bureau of Larbor Statistics . You used data from 2006 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]]
"Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida"
[[ABSTRACT]]
In this study, we tackle the riveting question of how the prolific goal-scoring prowess of renowned footballer Lionel Messi for the Argentina national team influences the employment status of chemical equipment operators and tenders in the Sunshine State of Florida. With a dash of statistical rigor and a sprinkle of soccer spirit, we delved into the data from Wikipedia and the Bureau of Labor Statistics to uncover the potential correlation between these seemingly unrelated fields.
Our findings revealed a correlation coefficient of 0.8685682 with a p-value less than 0.01 for the years spanning 2006 to 2022. It seems that Messi's goal-counting expertise on the pitch may indeed have an unexpected impact on the demand for chemical equipment operators and tenders in Florida. Who would have thought that soccer goals and chemical compound mixtures could be so romantically intertwined?
Nevertheless, as researchers, we must exercise caution in drawing strict causal associations between these variables. As the classic dad joke goes, correlation does not necessarily imply causation – after all, we wouldn't want to jump to conclusions as fast as Messi takes a free-kick.
The implications of our findings stretch beyond the realm of sport or chemistry, highlighting the interconnectedness of seemingly disparate elements in our world. As we continue to unravel the mysterious web of cause and effect, we are reminded of the whimsical and sometimes downright magical nature of scientific inquiry. Who knows, perhaps Messi's next hat-trick will spark a boom in the detergent industry – the Messi effect in full swing!
[[INTRODUCTION]]
In the realm of research, it's often said that the pursuit of knowledge is a goal-oriented endeavor - and today, we're taking that quite literally. Our study delves into the unlikely connection between the prolific performance of the soccer sensation, Lionel Messi, and the employment dynamics of chemical equipment operators and tenders in Florida. As we explore this unconventional correlation, we are reminded of the timeless question: is it Messi-nic or just Messi-d up?
In the world of statistics, we are accustomed to seeking relationships between variables that are, well, a bit more expected. But who could resist investigating the tantalizing possibility that a goal scored by Messi could lead to the stirring up of job opportunities for chemical equipment operators and tenders? It's almost as unexpected as finding a Nobel Prize winner in a litter of compounds!
As researchers, we thrive on unearthing these unexpected connections – or should we say, Messi connections? It's a reminder that the web of cause and effect in the world is often as perplexing and intricate as a chemical reaction. After all, who would have thought that the path to understanding chemistry could lead us through the world of sports?
But before we dive into the data and unveil the statistical insights, let's acknowledge the potential pitfalls of making hasty assumptions. As the esteemed dad joke of research dictates, correlation does not imply causation - just like a perfectly balanced equation does not guarantee a successful experiment. We’ll tread cautiously, just like a midfielder tiptoeing along the edge of an offside position.
So, as we embark on this Messi-merizing journey of discovery, our aim is to shed light on the serendipitous and sometimes downright whimsical nature of scientific inquiry. Who knows, perhaps our findings will inspire a whole new field of study: Messi-matics. After all, in the world of research, unexpected findings are often the goal.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To navigate this Messi-merizing journey of discovery, we first scoured the vast expanses of the internet to gather data on Lionel Messi's goal count for the Argentina national team. Our primary source of this goal-tastic information was the ever-reliable haven of soccer stats – Wikipedia. Of course, anyone can edit Wikipedia, but we promise we didn't sneak in any extra goals for Messi – that would be quite the own goal for our research integrity!
Simultaneously, we dipped our toes into the statistical pool and obtained employment data for chemical equipment operators and tenders in the illustrious state of Florida from the Bureau of Labor Statistics. Florida, with its sunshine and coastal charm, provided the backdrop for our unexpected exploration of the Messi effect on chemistry-related employment. It was a bit like venturing into uncharted territory, trudging through the data jungle in search of that elusive correlation – a bit Messi, but definitely adventurous!
To uncover the potential relationship between Messi's goal-scoring exploits and the employment fluctuations of chemical equipment operators and tenders, we deployed the venerable statistical method of correlation analysis. We meticulously tabulated and crunched the numbers for the years 2006 to 2022, blending the Messi magic with the chemical data in a concoction fit for the most unconventional experiment in the lab. It was statistics-meets-soccer meets-chemistry, a veritable triple threat of academic inquiry!
As we delved deeper into the statistical undercurrents, we performed a thorough examination of the correlation coefficient and associated p-values – the bread and butter of any self-respecting statistical analysis. The correlation coefficient emerged as a shining beacon in our research odyssey, coming in at a tantalizing 0.8685682, with a cheeky p-value less than 0.01. It seems that Messi's goal-scoring prowess indeed stirs up quite the chemical reaction in the employment landscape of Florida – a finding as shocking as a red card in injury time.
Our scrupulous methodology ensured that we accounted for potential confounding variables and sources of bias, akin to ensuring that all the laboratory equipment was calibrated and the experiment was conducted with precision. After all, just like in science, we must control for external factors to ensure the purity of our findings – a concept as fundamental as the periodic table itself!
Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Lionel Messi's goal count for Argentina and The number of chemical equipment operators and tenders in Florida. 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 Wikipedia and Bureau of Larbor Statistics .
For the time period 2006 to 2022, you found a correlation 0.8685682, r-squared of 0.7544107, 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]]
"Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida"
[[ABSTRACT]]
In this study, we tackle the riveting question of how the prolific goal-scoring prowess of renowned footballer Lionel Messi for the Argentina national team influences the employment status of chemical equipment operators and tenders in the Sunshine State of Florida. With a dash of statistical rigor and a sprinkle of soccer spirit, we delved into the data from Wikipedia and the Bureau of Labor Statistics to uncover the potential correlation between these seemingly unrelated fields.
Our findings revealed a correlation coefficient of 0.8685682 with a p-value less than 0.01 for the years spanning 2006 to 2022. It seems that Messi's goal-counting expertise on the pitch may indeed have an unexpected impact on the demand for chemical equipment operators and tenders in Florida. Who would have thought that soccer goals and chemical compound mixtures could be so romantically intertwined?
Nevertheless, as researchers, we must exercise caution in drawing strict causal associations between these variables. As the classic dad joke goes, correlation does not necessarily imply causation – after all, we wouldn't want to jump to conclusions as fast as Messi takes a free-kick.
The implications of our findings stretch beyond the realm of sport or chemistry, highlighting the interconnectedness of seemingly disparate elements in our world. As we continue to unravel the mysterious web of cause and effect, we are reminded of the whimsical and sometimes downright magical nature of scientific inquiry. Who knows, perhaps Messi's next hat-trick will spark a boom in the detergent industry – the Messi effect in full swing!
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the realm of research, it's often said that the pursuit of knowledge is a goal-oriented endeavor - and today, we're taking that quite literally. Our study delves into the unlikely connection between the prolific performance of the soccer sensation, Lionel Messi, and the employment dynamics of chemical equipment operators and tenders in Florida. As we explore this unconventional correlation, we are reminded of the timeless question: is it Messi-nic or just Messi-d up?
In the world of statistics, we are accustomed to seeking relationships between variables that are, well, a bit more expected. But who could resist investigating the tantalizing possibility that a goal scored by Messi could lead to the stirring up of job opportunities for chemical equipment operators and tenders? It's almost as unexpected as finding a Nobel Prize winner in a litter of compounds!
As researchers, we thrive on unearthing these unexpected connections – or should we say, Messi connections? It's a reminder that the web of cause and effect in the world is often as perplexing and intricate as a chemical reaction. After all, who would have thought that the path to understanding chemistry could lead us through the world of sports?
But before we dive into the data and unveil the statistical insights, let's acknowledge the potential pitfalls of making hasty assumptions. As the esteemed dad joke of research dictates, correlation does not imply causation - just like a perfectly balanced equation does not guarantee a successful experiment. We’ll tread cautiously, just like a midfielder tiptoeing along the edge of an offside position.
So, as we embark on this Messi-merizing journey of discovery, our aim is to shed light on the serendipitous and sometimes downright whimsical nature of scientific inquiry. Who knows, perhaps our findings will inspire a whole new field of study: Messi-matics. After all, in the world of research, unexpected findings are often the goal.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
Our investigation into the relationship between Lionel Messi's goal count for Argentina and the number of chemical equipment operators and tenders in the sunny state of Florida uncovered a striking correlation. Drumroll, please! The correlation coefficient between these seemingly unrelated variables was found to be 0.8685682, with an r-squared value of 0.7544107. If we were to translate that into football terms, Messi's influence is about as clear as a penalty kick right down the middle – a solid connection indeed.
Fig. 1 vividly illustrates the unmistakable pattern we observed in our data, showcasing a scatterplot that practically screams, "Look at the chemistry between these variables!" It's as clear as... well, Messi's exceptional ball-handling skills.
Now, before we get too carried away with visions of chemical compounds playing soccer, it's essential to recognize the limitations of our results. As any responsible researcher would tell you, correlation does not imply causation – much like having a lab coat doesn't make you a chemist. We must approach our findings with the same caution one would exercise when handling volatile substances in the lab.
Nevertheless, our findings hold profound implications for the interconnected web of cause and effect in our world. Who would have thought that Messi's stellar performances on the pitch could have a ripple effect on the demand for chemical equipment operators and tenders in Florida? It's a reminder that in the world of statistics, as in life, unexpected connections – and perhaps a good dad joke or two – are often just around the corner.
Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Lionel Messi's goal count for Argentina and The number of chemical equipment operators and tenders in Florida. 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]]
"Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida"
[[ABSTRACT]]
In this study, we tackle the riveting question of how the prolific goal-scoring prowess of renowned footballer Lionel Messi for the Argentina national team influences the employment status of chemical equipment operators and tenders in the Sunshine State of Florida. With a dash of statistical rigor and a sprinkle of soccer spirit, we delved into the data from Wikipedia and the Bureau of Labor Statistics to uncover the potential correlation between these seemingly unrelated fields.
Our findings revealed a correlation coefficient of 0.8685682 with a p-value less than 0.01 for the years spanning 2006 to 2022. It seems that Messi's goal-counting expertise on the pitch may indeed have an unexpected impact on the demand for chemical equipment operators and tenders in Florida. Who would have thought that soccer goals and chemical compound mixtures could be so romantically intertwined?
Nevertheless, as researchers, we must exercise caution in drawing strict causal associations between these variables. As the classic dad joke goes, correlation does not necessarily imply causation – after all, we wouldn't want to jump to conclusions as fast as Messi takes a free-kick.
The implications of our findings stretch beyond the realm of sport or chemistry, highlighting the interconnectedness of seemingly disparate elements in our world. As we continue to unravel the mysterious web of cause and effect, we are reminded of the whimsical and sometimes downright magical nature of scientific inquiry. Who knows, perhaps Messi's next hat-trick will spark a boom in the detergent industry – the Messi effect in full swing!
[[LITERATURE REVIEW]]
The influential work of Smith and colleagues (2015) examined the performance of Lionel Messi for the Argentina national team in relation to his goal-scoring prowess. The authors find a consistent pattern of Messi's exceptional ability to find the back of the net, even when faced with the most formidable opponents. It's almost as if Messi has a chemistry with the goal that rivals the most stable chemical compounds.
On the other hand, Doe and Jones (2018) carried out an analysis of the employment trends in Florida's chemical industry. Their study reveals an upward trajectory in the demand for chemical equipment operators and tenders, particularly during the years coinciding with major international football tournaments. It's almost like the employment trend is doing a Messi dance of its own, isn't it?
Now, turning to some non-fiction sources that lend insight into the intricate relationship between sports and employment, "Socceronomics" by Kuper and Szymanski touches upon the economic impacts of football on various aspects of society. In a somewhat unexpected twist, the book delves into workforce trends influenced by the beautiful game, raising intriguing parallels to our current study. It's as if soccer and chemistry are about to engage in a game of employment catenaccio.
In a similar vein, "Freakonomics" by Levitt and Dubner delves into the unexpected connections that underpin our world. While not directly related to our subject matter, one cannot help but wonder if Messi's goals hold the power to influence economic phenomena far beyond the football pitch. It's almost like Messi's goals have the potential to turn the economic world upside down – or, in this case, "Freakonomics" it.
On a more whimsical note, the fictitious novel "The Goal Whisperer" by Fictional Author explores the mystical connection between a legendary soccer player's goals and their impact on the fabric of reality. While we may not take the book's content as empirical evidence, the notion of Messi's goals holding a mystical sway over the employment market makes for an entertaining and Messi-merizing read.
Moreover, "The Elements of Style" by Strunk and White offers a compelling guide to the nuances of writing and communication. While unrelated to our study, the element of surprise and style in Messi's goals may have inadvertently contributed to the employment trends we observe. It's almost as if Messi's goals are a literary masterpiece, weaving their way through the employment statistics with a lyrical finesse.
In an era of social media dominance, a tweet from @FootballStats2020 catches our attention: "Messi's hat-trick coincides with a sudden surge in job postings for chemical equipment operators in Florida – coincidence or Messi's hidden talent in catalyzing job markets?" While we must exercise caution in attributing these findings solely to Messi's on-field heroics, the tweet raises a thought-provoking hypothesis. It's almost as if Messi's hat-trick goals have the potential to stir up employment opportunities with the same fervor as a well-mixed chemical solution.
As we consider the curious mesh of statistical data and unexpected connections, it's essential to maintain a lighthearted perspective. Just as a chemist wouldn't mix the wrong elements, we must approach these findings with due diligence and a sprinkling of humor. After all, in the game of research, a good pun is Messi as a vital finding!
[[RESULTS]]
Our investigation into the relationship between Lionel Messi's goal count for Argentina and the number of chemical equipment operators and tenders in the sunny state of Florida uncovered a striking correlation. Drumroll, please! The correlation coefficient between these seemingly unrelated variables was found to be 0.8685682, with an r-squared value of 0.7544107. If we were to translate that into football terms, Messi's influence is about as clear as a penalty kick right down the middle – a solid connection indeed.
Fig. 1 vividly illustrates the unmistakable pattern we observed in our data, showcasing a scatterplot that practically screams, "Look at the chemistry between these variables!" It's as clear as... well, Messi's exceptional ball-handling skills.
Now, before we get too carried away with visions of chemical compounds playing soccer, it's essential to recognize the limitations of our results. As any responsible researcher would tell you, correlation does not imply causation – much like having a lab coat doesn't make you a chemist. We must approach our findings with the same caution one would exercise when handling volatile substances in the lab.
Nevertheless, our findings hold profound implications for the interconnected web of cause and effect in our world. Who would have thought that Messi's stellar performances on the pitch could have a ripple effect on the demand for chemical equipment operators and tenders in Florida? It's a reminder that in the world of statistics, as in life, unexpected connections – and perhaps a good dad joke or two – are often just around the corner.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our findings have admirably borne out the connections hinted at in the literature review, showing that Messi's goal-scoring triumphs indeed seem to have a Messi-nic influence on the employment of chemical equipment operators and tenders in Florida. It's almost as if Messi's goals are the catalyst for the proverbial chemical reaction in the job market, sparking a chain of employment events as surprising as an unexpected chemical compound in a lab experiment.
Our results align with the prior research of Smith et al. (2015) and Doe and Jones (2018), emphasizing the robustness of the relationship between Messi's goal counts and the demand for chemical equipment operators and tenders. It's almost as if Messi's goals are as reliable as the periodic table, consistently leading to a reaction in the employment statistics.
The correlation coefficient of 0.8685682 and the r-squared value of 0.7544107 firmly cement the statistical link between Messi's accomplishments on the field and the employment trends in Florida's chemical industry. It's almost as if Messi's goals are akin to the precision of a well-controlled laboratory experiment, yielding definitive results that cannot be overlooked.
Our findings emphasize the need for caution in interpreting correlation as causation, echoing the sentiments of many a wise researcher. As the old saying goes, just because Messi scores goals, we can't immediately assume job demand follows suit – it's almost as if we need to dissect these connections with the precise maneuvers of a skilled chemist.
The implications of this study extend beyond the world of soccer and chemistry, shedding light on the unanticipated interplay between sports and employment outcomes. It's almost as if Messi's goals possess a transmutative power that extends beyond the football pitch, much like a sneaky chemical reaction occurring in plain sight.
In conclusion, our research highlights the importance of considering seemingly unrelated factors in understanding economic trends. After all, it seems that in the grand scheme of scientific exploration, there's always room for a good laugh or a clever pun – much like finding unexpected patterns amidst seemingly unrelated variables.
Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Lionel Messi's goal count for Argentina and The number of chemical equipment operators and tenders in Florida. 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]]
"Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida"
[[ABSTRACT]]
In this study, we tackle the riveting question of how the prolific goal-scoring prowess of renowned footballer Lionel Messi for the Argentina national team influences the employment status of chemical equipment operators and tenders in the Sunshine State of Florida. With a dash of statistical rigor and a sprinkle of soccer spirit, we delved into the data from Wikipedia and the Bureau of Labor Statistics to uncover the potential correlation between these seemingly unrelated fields.
Our findings revealed a correlation coefficient of 0.8685682 with a p-value less than 0.01 for the years spanning 2006 to 2022. It seems that Messi's goal-counting expertise on the pitch may indeed have an unexpected impact on the demand for chemical equipment operators and tenders in Florida. Who would have thought that soccer goals and chemical compound mixtures could be so romantically intertwined?
Nevertheless, as researchers, we must exercise caution in drawing strict causal associations between these variables. As the classic dad joke goes, correlation does not necessarily imply causation – after all, we wouldn't want to jump to conclusions as fast as Messi takes a free-kick.
The implications of our findings stretch beyond the realm of sport or chemistry, highlighting the interconnectedness of seemingly disparate elements in our world. As we continue to unravel the mysterious web of cause and effect, we are reminded of the whimsical and sometimes downright magical nature of scientific inquiry. Who knows, perhaps Messi's next hat-trick will spark a boom in the detergent industry – the Messi effect in full swing!
[[INTRDUCTION]]
In the realm of research, it's often said that the pursuit of knowledge is a goal-oriented endeavor - and today, we're taking that quite literally. Our study delves into the unlikely connection between the prolific performance of the soccer sensation, Lionel Messi, and the employment dynamics of chemical equipment operators and tenders in Florida. As we explore this unconventional correlation, we are reminded of the timeless question: is it Messi-nic or just Messi-d up?
In the world of statistics, we are accustomed to seeking relationships between variables that are, well, a bit more expected. But who could resist investigating the tantalizing possibility that a goal scored by Messi could lead to the stirring up of job opportunities for chemical equipment operators and tenders? It's almost as unexpected as finding a Nobel Prize winner in a litter of compounds!
As researchers, we thrive on unearthing these unexpected connections – or should we say, Messi connections? It's a reminder that the web of cause and effect in the world is often as perplexing and intricate as a chemical reaction. After all, who would have thought that the path to understanding chemistry could lead us through the world of sports?
But before we dive into the data and unveil the statistical insights, let's acknowledge the potential pitfalls of making hasty assumptions. As the esteemed dad joke of research dictates, correlation does not imply causation - just like a perfectly balanced equation does not guarantee a successful experiment. We’ll tread cautiously, just like a midfielder tiptoeing along the edge of an offside position.
So, as we embark on this Messi-merizing journey of discovery, our aim is to shed light on the serendipitous and sometimes downright whimsical nature of scientific inquiry. Who knows, perhaps our findings will inspire a whole new field of study: Messi-matics. After all, in the world of research, unexpected findings are often the goal.
[[RESULTS]]
Our investigation into the relationship between Lionel Messi's goal count for Argentina and the number of chemical equipment operators and tenders in the sunny state of Florida uncovered a striking correlation. Drumroll, please! The correlation coefficient between these seemingly unrelated variables was found to be 0.8685682, with an r-squared value of 0.7544107. If we were to translate that into football terms, Messi's influence is about as clear as a penalty kick right down the middle – a solid connection indeed.
Fig. 1 vividly illustrates the unmistakable pattern we observed in our data, showcasing a scatterplot that practically screams, "Look at the chemistry between these variables!" It's as clear as... well, Messi's exceptional ball-handling skills.
Now, before we get too carried away with visions of chemical compounds playing soccer, it's essential to recognize the limitations of our results. As any responsible researcher would tell you, correlation does not imply causation – much like having a lab coat doesn't make you a chemist. We must approach our findings with the same caution one would exercise when handling volatile substances in the lab.
Nevertheless, our findings hold profound implications for the interconnected web of cause and effect in our world. Who would have thought that Messi's stellar performances on the pitch could have a ripple effect on the demand for chemical equipment operators and tenders in Florida? It's a reminder that in the world of statistics, as in life, unexpected connections – and perhaps a good dad joke or two – are often just around the corner.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our study has revealed a "Messi-nic" relationship between Lionel Messi's goal-counting prowess and the employment demand for chemical equipment operators and tenders in Florida, proving that statistical analysis can be as entertaining as a Messi hat-trick. Our findings, akin to a perfectly timed bicycle kick, displayed a robust correlation coefficient of 0.8685682, with a p-value resembling a dazzling through-ball, prompting us to wax lyrical about the unexpected dance between soccer goals and chemical equations.
As we wrap up this Messi-merizing journey, it's important to heed the classic dictum of research: correlation does not imply causation, much like kicking a soccer ball doesn't automatically make you a chemical engineer. We must approach these connections with the same caution one would exercise when experimenting with a new set of chemicals – after all, no one wants to "Messi" up the findings.
The implications of our study extend far beyond statistics or chemistry, reminding us that the world is full of delightful surprises, much like the unexpected chemistry between soccer and chemical industries. In light of these revelations, it's clear that no further research is necessary in this area – because when it comes to Messi and chemistry, the unexpected findings are the goal.
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 Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Athletic Alchemy
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 Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida. Respond only with the name of a fictional organization.
ChatGPT:
The Institute for Sports Analytics and Workplace Dynamics
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 Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida with an abstract of In this study, we tackle the riveting question of how the prolific goal-scoring prowess of renowned footballer Lionel Messi for the Argentina national team influences the employment status of chemical equipment operators and tenders in the Sunshine State of Florida. With a dash of statistical rigor and a sprinkle of soccer spirit, we delved into the data from Wikipedia and the Bureau of Labor Statistics to uncover the potential correlation between these seemingly unrelated fields.
Our findings revealed a correlation coefficient of 0.8685682 with a p-value less than 0.01 for the years spanning 2006 to 2022. It seems that Messi's goal-counting expertise on the pitch may indeed have an unexpected impact on the demand for chemical equipment operators and tenders in Florida. Who would have thought that soccer goals and chemical compound mixtures could be so romantically intertwined?
Nevertheless, as researchers, we must exercise caution in drawing strict causal associations between these variables. As the classic dad joke goes, correlation does not necessarily imply causation – after all, we wouldn't want to jump to conclusions as fast as Messi takes a free-kick.
The implications of our findings stretch beyond the realm of sport or chemistry, highlighting the interconnectedness of seemingly disparate elements in our world. As we continue to unravel the mysterious web of cause and effect, we are reminded of the whimsical and sometimes downright magical nature of scientific inquiry. Who knows, perhaps Messi's next hat-trick will spark a boom in the detergent industry – the Messi effect in full swing!
ChatGPT:
Lionel Messi, chemical equipment operators, tenders, employment, Florida, correlation, statistical analysis, goal-scoring, soccer, Bureau of Labor Statistics, demand, data analysis, Argentina national team, correlation coefficient, p-value, variables interaction, causal association, interconnectedness, scientific inquiry
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Lionel Messi's goal count for ArgentinaDetailed data title: Lionel Messi's goal for Argentina
Source: Wikipedia
See what else correlates with Lionel Messi's goal count for Argentina
The number of chemical equipment operators and tenders in Florida
Detailed data title: BLS estimate of chemical equipment operators and tenders in Florida
Source: Bureau of Larbor Statistics
See what else correlates with The number of chemical equipment operators and tenders in Florida
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 = 0.7544107 (Coefficient of determination)
This means 75.4% of the change in the one variable (i.e., The number of chemical equipment operators and tenders in Florida) is predictable based on the change in the other (i.e., Lionel Messi's goal count for Argentina) over the 17 years from 2006 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.1E-6. 0.0000061155503824384420000000
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 0.87 in 0.00061% of random cases. Said differently, if you correlated 163,518 random variables You don't actually need 163 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 16 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 16 because we have two variables measured over a period of 17 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.
[ 0.67, 0.95 ] 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.
| 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | |
| Lionel Messi's goal count for Argentina (Goals scored) | 2 | 6 | 2 | 3 | 2 | 4 | 12 | 6 | 8 | 4 | 8 | 4 | 4 | 5 | 1 | 9 | 18 |
| The number of chemical equipment operators and tenders in Florida (Laborers) | 1080 | 800 | 850 | 760 | 1350 | 1720 | 2080 | 1600 | 1520 | 1430 | 1620 | 1430 | 1310 | 930 | 1180 | 2160 | 4030 |
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.
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([2,6,2,3,2,4,12,6,8,4,8,4,4,5,1,9,18,])
array_2 = np.array([1080,800,850,760,1350,1720,2080,1600,1520,1430,1620,1430,1310,930,1180,2160,4030,])
array_1_name = "Lionel Messi's goal count for Argentina"
array_2_name = "The number of chemical equipment operators and tenders in Florida"
# 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.
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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 Lionel Messi's goal count for Argentina
- Line chart for only The number of chemical equipment operators and tenders in Florida
- AI-generated correlation image
- The spurious research paper: Kicking Goals and Chemistry: The Messi-nic Influence of Lionel Messi's Performance on the Employment of Chemical Equipment Operators and Tenders in Florida
Your rating is much appreciated!
Correlation ID: 2140 · Black Variable ID: 72 · Red Variable ID: 6666
