Spurious correlation #1,257 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of geography teachers in Texas and the second variable is Points Scored by the losing team in the Super Bowl. The chart goes from 2003 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of geography teachers in Texas and the second variable is Points Scored by the losing team in the Super Bowl. The chart goes from 2003 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As more geography teachers flooded into Texas, they couldn't help but emphasize the importance of knowing where the end zone is. This led to a keen understanding of the field layout among the losing team in the Super Bowl, allowing them to navigate the game with a heightened sense of direction, and ultimately score more points.

^{Show image generation prompt} Model: dalle-3
Prompt: Certainly! Generate an image of a seesaw with one end occupied by a map of the state of Texas and the other end by a football field. On the Texas side, include figurative representations of geography teachers coming and going, causing the seesaw to tilt back and forth. As the seesaw moves, depict the football field experiencing changes in gravity, leading to a visual representation of the difficulty faced by the losing team in the Super Bowl related to kicking field goals and scoring points. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

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

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: Because as the number of geography teachers in Texas fluctuates, so does the gravitational pull on the losing team in the Super Bowl, affecting their ability to kick field goals and score points.. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: Symbolism Realistic Scalar art Realistic Sci-fi fantacy
ChatGPT: Symbolism

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. Because as the number of geography teachers in Texas fluctuates, so does the gravitational pull on the losing team in the Super Bowl, affecting their ability to kick field goals and score points.
ChatGPT: Imagine a seesaw with the state of Texas on one end and a football field on the other. On the Texas side, there are geography teachers coming and going, causing the seesaw to tilt back and forth. As the seesaw moves, the football field on the other end experiences changes in gravity, making it difficult for the losing team in the Super Bowl to kick field goals and score points.

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: [ Symbolism ] and depicting this scene: Imagine a seesaw with the state of Texas on one end and a football field on the other. On the Texas side, there are geography teachers coming and going, causing the seesaw to tilt back and forth. As the seesaw moves, the football field on the other end experiences changes in gravity, making it difficult for the losing team in the Super Bowl to kick field goals and score points. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Certainly! Generate an image of a seesaw with one end occupied by a map of the state of Texas and the other end by a football field. On the Texas side, include figurative representations of geography teachers coming and going, causing the seesaw to tilt back and forth. As the seesaw moves, depict the football field experiencing changes in gravity, leading to a visual representation of the difficulty faced by the losing team in the Super Bowl related to kicking field goals and scoring points.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in The number of geography teachers in Texas positively influenced Points Scored by the losing team in the Super Bowl.

AI academic paper

(Because p < 0.01)

Texas Teachers and Super Bowl Defeats: Unraveling the Tightened Ties

The Journal of Americana Studies

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of geography teachers in Texas and Points Scored by the losing team in the Super Bowl. 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]]
"Texas Teachers and Super Bowl Defeats: Unraveling the Tightened Ties"

[[ABSTRACT]]
The perplexing correlation between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl has long confounded researchers. In this study, we employed data from the Bureau of Labor Statistics and Wikipedia to scrutinize this enigmatic relationship. Our analysis revealed a significant positive correlation, with a correlation coefficient of 0.6226698 and p < 0.01 for the years 2003 to 2022.

As we delved into the connection between geography teachers in the Lone Star State and gridiron defeats, we couldn't help but marvel at the unexpected bond. It seems that when it comes to Super Bowl losses, geography teachers in Texas might hold some peculiar sway over the outcome. It's almost like they've been giving their students a lesson in geographical titillation!

Upon diving deeper into the data, we uncovered a striking trend. It appears that as the number of geography teachers in Texas increases, the points scored by the losing team in the Super Bowl also rise. It's as if these educators are inadvertently charting a path to gridiron defeat, one lesson at a time. Perhaps they're using their geographical knowledge to guide teams to the end zone – just not their own!

Our findings bring a lighthearted twist to academic research, as we've uncovered an unexpected tie between geography educators and football setbacks. It seems that in the land of cowboys and touchdowns, geography teachers may hold the key to location, location, location – even on the Super Bowl field. After all, when it comes to gridiron struggles, perhaps it's all about the longitudes and latitudes of defeat!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Texas, the land of larger-than-life personalities and a deep love for football, has played host to an intriguing relationship that has puzzled academics and football fanatics alike. The unlikely bond between the number of geography teachers in the Lone Star State and the points scored by the losing team in the Super Bowl has left many scratching their heads. It's almost as perplexing as trying to find your way out of a maze made entirely of Texas-shaped puzzles!
The connection between football defeats and geography educators in Texas raises eyebrows and sparks curiosity. After all, who would have thought that the number of longitude and latitude enthusiasts could have any influence on the outcome of one of America's most beloved sporting events? It's almost like the football field becomes a giant map, and these teachers are secretly plotting the course for defeat – their own version of "The Texas Chainsaw (Football) Massacre."
As we embarked on our research journey, we couldn't help but revel in the delightful absurdity of this peculiar association. Imagine, if you will, a group of geography teachers huddled around a map of the United States, strategizing how to influence the outcome of the Super Bowl – or at least their presence inadvertently doing so! It's as if they're using geographical knowledge to pave the way for touchdowns, field goals, and the occasional fumble – all from the comfort of their classroom.
Our research aims to shed light on this offbeat correlation, offering a whimsical take on the impact of educators on the world of sports. After all, who would have thought that the historical rivalry between geographical accuracy and football prowess would result in such an intriguing yarn? It's like a real-life game of "Where in the World is Carmen Sandiego?" – except this time, the elusive culprit might just be a group of unsuspecting geography teachers in Texas.
Join us on this lighthearted academic adventure as we unravel the tangled web of Texas teachers and Super Bowl defeats, exploring the unexpected ties that bind these seemingly disparate entities. Grab your maps, football jerseys, and a sense of humor, because we're about to embark on a journey that blurs the lines between the football field and the classroom – where X marks the spot for touchdown – or, in this case, the end zone of academic curiosity!

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Texas Geography Teachers and Super Bowl Woes," Smith et al. examined the curious relationship between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl. The authors found a statistically significant positive correlation, leading them to ponder the unexpected influence geography educators may wield on the outcomes of America's most celebrated sporting event.

As we navigate this uncharted territory of academic research, we are reminded of the age-old adage: "Why don't scientists trust atoms? Because they make up everything!" Speaking of making things up, it seems the correlation between geography teachers in Texas and Super Bowl defeats is more than just a theoretical construct – it's a curious reality that begs for further investigation.

Doe and Jones, in their study "Geography Education and Gridiron Grief," delved into the historical context of geographical knowledge and its potential impact on football performance. Their findings highlighted the uncanny connection between the spatial awareness instilled by geography teachers and the navigational prowess required on the gridiron. It's almost as if these educators are plotting coordinates for defeats like a game of "Battleship," but instead of sinking ships, they're sinking football dreams. As they say, "You win some, you lose some – but when geography teachers are involved, you might just lose the game."

Turning to non-fiction literature related to geographical influence and athletic endeavors, we can't help but consider books such as "Longitude" and "Latitude 45," both of which offer insights into the power of geographical coordinates. It's as if the very fabric of geographical positioning exerts an invisible force on the outcome of sporting contests, much like the allure of a magnetic North Pole for compass needles – or perhaps, in this case, footballs flying through the goalposts.

In the realm of fiction, works like "The Map of Love" and "The Geography of You and Me" beckon us to ponder the intricacies of location and its impact on human experiences, and apparently, football scores. It's almost as if the protagonists of these fictional tales are unwitting players in a real-life drama, where the stakes include more than just love and longing – they include touchdowns and field goals. Who knew that romance and gridiron defeats could share the same geographical stage? It's like a game of "Twister," but with emotive entanglements and football fumbles!

Moreover, social media musings have not escaped our attention, as posts proclaiming, "It's not just a game – it's geography in action," and "In a battle of grids, the map may reign supreme," seem to underscore the gravity of this unconventional correlation. It's as if the digital sphere has become a virtual arena for debating the nuanced influence of geographical acumen on football outcomes, turning Twitter threads into veritable playgrounds for intellectual jousting and pun-laden banter.

As we unravel the enigmatic ties between Texas geography teachers and Super Bowl defeats, we find ourselves at a crossroads of discovery and amusement, where the pursuit of knowledge meets the whimsy of unexpected connections. Indeed, it seems that in the grand tapestry of life, geography teachers and football defeats may share more than just a passing glance – they may, in fact, be two sides of the same coin, both navigating the intricacies of victory and defeat with equal measures of earnestness and jest.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of geography teachers in Texas and Points Scored by the losing team in the Super Bowl. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
"Texas Teachers and Super Bowl Defeats: Unraveling the Tightened Ties"

[[ABSTRACT]]
The perplexing correlation between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl has long confounded researchers. In this study, we employed data from the Bureau of Labor Statistics and Wikipedia to scrutinize this enigmatic relationship. Our analysis revealed a significant positive correlation, with a correlation coefficient of 0.6226698 and p < 0.01 for the years 2003 to 2022.

As we delved into the connection between geography teachers in the Lone Star State and gridiron defeats, we couldn't help but marvel at the unexpected bond. It seems that when it comes to Super Bowl losses, geography teachers in Texas might hold some peculiar sway over the outcome. It's almost like they've been giving their students a lesson in geographical titillation!

Upon diving deeper into the data, we uncovered a striking trend. It appears that as the number of geography teachers in Texas increases, the points scored by the losing team in the Super Bowl also rise. It's as if these educators are inadvertently charting a path to gridiron defeat, one lesson at a time. Perhaps they're using their geographical knowledge to guide teams to the end zone – just not their own!

Our findings bring a lighthearted twist to academic research, as we've uncovered an unexpected tie between geography educators and football setbacks. It seems that in the land of cowboys and touchdowns, geography teachers may hold the key to location, location, location – even on the Super Bowl field. After all, when it comes to gridiron struggles, perhaps it's all about the longitudes and latitudes of defeat!

[[LITERATURE REVIEW]]
In "Texas Geography Teachers and Super Bowl Woes," Smith et al. examined the curious relationship between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl. The authors found a statistically significant positive correlation, leading them to ponder the unexpected influence geography educators may wield on the outcomes of America's most celebrated sporting event.
As we navigate this uncharted territory of academic research, we are reminded of the age-old adage: "Why don't scientists trust atoms? Because they make up everything!" Speaking of making things up, it seems the correlation between geography teachers in Texas and Super Bowl defeats is more than just a theoretical construct – it's a curious reality that begs for further investigation.
Doe and Jones, in their study "Geography Education and Gridiron Grief," delved into the historical context of geographical knowledge and its potential impact on football performance. Their findings highlighted the uncanny connection between the spatial awareness instilled by geography teachers and the navigational prowess required on the gridiron. It's almost as if these educators are plotting coordinates for defeats like a game of "Battleship," but instead of sinking ships, they're sinking football dreams. As they say, "You win some, you lose some – but when geography teachers are involved, you might just lose the game."
Turning to non-fiction literature related to geographical influence and athletic endeavors, we can't help but consider books such as "Longitude" and "Latitude 45," both of which offer insights into the power of geographical coordinates. It's as if the very fabric of geographical positioning exerts an invisible force on the outcome of sporting contests, much like the allure of a magnetic North Pole for compass needles – or perhaps, in this case, footballs flying through the goalposts.
In the realm of fiction, works like "The Map of Love" and "The Geography of You and Me" beckon us to ponder the intricacies of location and its impact on human experiences, and apparently, football scores. It's almost as if the protagonists of these fictional tales are unwitting players in a real-life drama, where the stakes include more than just love and longing – they include touchdowns and field goals. Who knew that romance and gridiron defeats could share the same geographical stage? It's like a game of "Twister," but with emotive entanglements and football fumbles!
Moreover, social media musings have not escaped our attention, as posts proclaiming, "It's not just a game – it's geography in action," and "In a battle of grids, the map may reign supreme," seem to underscore the gravity of this unconventional correlation. It's as if the digital sphere has become a virtual arena for debating the nuanced influence of geographical acumen on football outcomes, turning Twitter threads into veritable playgrounds for intellectual jousting and pun-laden banter.
As we unravel the enigmatic ties between Texas geography teachers and Super Bowl defeats, we find ourselves at a crossroads of discovery and amusement, where the pursuit of knowledge meets the whimsy of unexpected connections. Indeed, it seems that in the grand tapestry of life, geography teachers and football defeats may share more than just a passing glance – they may, in fact, be two sides of the same coin, both navigating the intricacies of victory and defeat with equal measures of earnestness and jest.

[[RESULTS]]
The analysis of the data covering the years 2003 to 2022 yielded intriguing findings that left us not just scratching our heads but also chuckling at the unexpected connection between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl. It seems that there's more to Texas geography educators than meets the eye – they might just hold the keys to the end zones of defeat (figuratively speaking, of course).
The correlation coefficient of 0.6226698 indicates a strong positive relationship between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl. This result suggests that as the count of geography teachers in the Lone Star State rises, so too does the score of the unfortunate losing team. It's almost like a geographic version of the butterfly effect – a teacher flapping a map in Texas might just cause a touchdown in the Super Bowl. Talk about putting the "geo" in "geographical influence"!
The r-squared value of 0.3877176 further solidifies the significance of this correlation, indicating that a substantial portion of the variability in the points scored by the losing team can be explained by the number of geography teachers in Texas. It's as if these educators have inadvertently become the unsung heroes of not just geographical knowledge, but also unwitting contributors to the world of football scores. Who would have thought that longitudes and latitudes could be the secret spices in the recipe for gridiron defeat?
The p-value of less than 0.01 adds another layer of legitimacy to our findings, firmly establishing the statistical significance of the relationship between Texas geography teachers and Super Bowl losses. This result further cements the idea that there's more at play here than meets the eye. It's like a geographical treasure hunt, where X marks the spot for statistical significance, surrounded by a sea of good-natured perplexity and whimsy.
The scatterplot (Fig. 1) showcases the robust correlation we uncovered, visually demonstrating the upward trend between the number of geography teachers in Texas and the points scored by the unfortunate losing team. It's as clear as a sunny day in the Lone Star State – there's something uniquely and unexpectedly fascinating about the influence of geography educators on the pigskin battleground. It's almost like they're giving a whole new meaning to "map out a strategy"!
Overall, our results shed light on the offbeat and delightful relationship between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl. It seems that in the land of big hats and even bigger dreams, geography educators may just hold the key to orchestrating not just geographical knowledge, but the very fabric of football defeat. After all, when it comes to unexpected correlations, this one takes the trophy – possibly a Lombardi Trophy, in this case!

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our study has brought forth intriguing findings that elevate the seemingly whimsical connection between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl to the forefront of academic curiosity. It turns out that there might indeed be more than meets the eye when it comes to the influence of geographical acumen on the gridiron, and it's not just because Texas is known for its wide-reaching horizons and football fervor.

Our results aptly support the prior research conducted by Smith et al. and Doe and Jones, who highlighted the confounding relationship between geographical knowledge and football outcomes. By unveiling a substantial positive correlation between the number of geography teachers in Texas and the points amassed by the unfortunate losing team in the Super Bowl, our study not only corroborates the earlier findings but also pulls back the curtain on the unforeseen impact of educational stalwarts in shaping the arena of athletic defeats. It's a bit like discovering that the real MVPs of Super Bowl battles may not be the players on the field, but the geography gurus charting their way from The Alamo to Arlington – talk about a true touchdown in unexpected discoveries!

While the inherent humor and novelty of this correlation cannot be overlooked, our rigorous statistical analysis underscores the legitimacy of this fascinating tie. The strong positive correlation coefficient, substantiated by the r-squared value and the low p-value, imparts a sense of solidity to the unexpected union between geographical educators and the turf of thwarted touchdowns. It's almost as if these teachers, armed with their knowledge of cartography and landforms, are inadvertently influencing the outcome of gridiron clashes, turning the very essence of Texas geography into an unwitting playbook for football struggles. Who would have thought that combining the world of maps and touchdowns could yield such a cheerfully confounding result?

Moreover, our findings offer an intriguing perspective on the playful intermingling of geography and football, underscoring the capricious nature of academic exploration and the joyous art of uncovering unforeseen patterns. As we navigate this whirlwind of unanticipated connections, our study not only encourages a reconsideration of the nuanced influence of geographical acumen on sporting contests but also infuses a dose of lighthearted amusement into the scholarly discourse. It's almost as if we've stumbled upon the pot of geographical gold at the end of a Super Bowl rainbow – and in true Texan fashion, it's as big and as catchy as the Lone Star State itself. After all, when it comes to reveling in the unexpected, it's hard to resist the lure of good-natured academic jests and pun-derful revelations.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of geography teachers in Texas and Points Scored by the losing team in the Super Bowl. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
"Texas Teachers and Super Bowl Defeats: Unraveling the Tightened Ties"

[[ABSTRACT]]
The perplexing correlation between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl has long confounded researchers. In this study, we employed data from the Bureau of Labor Statistics and Wikipedia to scrutinize this enigmatic relationship. Our analysis revealed a significant positive correlation, with a correlation coefficient of 0.6226698 and p < 0.01 for the years 2003 to 2022.

As we delved into the connection between geography teachers in the Lone Star State and gridiron defeats, we couldn't help but marvel at the unexpected bond. It seems that when it comes to Super Bowl losses, geography teachers in Texas might hold some peculiar sway over the outcome. It's almost like they've been giving their students a lesson in geographical titillation!

Upon diving deeper into the data, we uncovered a striking trend. It appears that as the number of geography teachers in Texas increases, the points scored by the losing team in the Super Bowl also rise. It's as if these educators are inadvertently charting a path to gridiron defeat, one lesson at a time. Perhaps they're using their geographical knowledge to guide teams to the end zone – just not their own!

Our findings bring a lighthearted twist to academic research, as we've uncovered an unexpected tie between geography educators and football setbacks. It seems that in the land of cowboys and touchdowns, geography teachers may hold the key to location, location, location – even on the Super Bowl field. After all, when it comes to gridiron struggles, perhaps it's all about the longitudes and latitudes of defeat!

[[INTRDUCTION]]
Texas, the land of larger-than-life personalities and a deep love for football, has played host to an intriguing relationship that has puzzled academics and football fanatics alike. The unlikely bond between the number of geography teachers in the Lone Star State and the points scored by the losing team in the Super Bowl has left many scratching their heads. It's almost as perplexing as trying to find your way out of a maze made entirely of Texas-shaped puzzles!
The connection between football defeats and geography educators in Texas raises eyebrows and sparks curiosity. After all, who would have thought that the number of longitude and latitude enthusiasts could have any influence on the outcome of one of America's most beloved sporting events? It's almost like the football field becomes a giant map, and these teachers are secretly plotting the course for defeat – their own version of "The Texas Chainsaw (Football) Massacre."
As we embarked on our research journey, we couldn't help but revel in the delightful absurdity of this peculiar association. Imagine, if you will, a group of geography teachers huddled around a map of the United States, strategizing how to influence the outcome of the Super Bowl – or at least their presence inadvertently doing so! It's as if they're using geographical knowledge to pave the way for touchdowns, field goals, and the occasional fumble – all from the comfort of their classroom.
Our research aims to shed light on this offbeat correlation, offering a whimsical take on the impact of educators on the world of sports. After all, who would have thought that the historical rivalry between geographical accuracy and football prowess would result in such an intriguing yarn? It's like a real-life game of "Where in the World is Carmen Sandiego?" – except this time, the elusive culprit might just be a group of unsuspecting geography teachers in Texas.
Join us on this lighthearted academic adventure as we unravel the tangled web of Texas teachers and Super Bowl defeats, exploring the unexpected ties that bind these seemingly disparate entities. Grab your maps, football jerseys, and a sense of humor, because we're about to embark on a journey that blurs the lines between the football field and the classroom – where X marks the spot for touchdown – or, in this case, the end zone of academic curiosity!

[[RESULTS]]
The analysis of the data covering the years 2003 to 2022 yielded intriguing findings that left us not just scratching our heads but also chuckling at the unexpected connection between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl. It seems that there's more to Texas geography educators than meets the eye – they might just hold the keys to the end zones of defeat (figuratively speaking, of course).
The correlation coefficient of 0.6226698 indicates a strong positive relationship between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl. This result suggests that as the count of geography teachers in the Lone Star State rises, so too does the score of the unfortunate losing team. It's almost like a geographic version of the butterfly effect – a teacher flapping a map in Texas might just cause a touchdown in the Super Bowl. Talk about putting the "geo" in "geographical influence"!
The r-squared value of 0.3877176 further solidifies the significance of this correlation, indicating that a substantial portion of the variability in the points scored by the losing team can be explained by the number of geography teachers in Texas. It's as if these educators have inadvertently become the unsung heroes of not just geographical knowledge, but also unwitting contributors to the world of football scores. Who would have thought that longitudes and latitudes could be the secret spices in the recipe for gridiron defeat?
The p-value of less than 0.01 adds another layer of legitimacy to our findings, firmly establishing the statistical significance of the relationship between Texas geography teachers and Super Bowl losses. This result further cements the idea that there's more at play here than meets the eye. It's like a geographical treasure hunt, where X marks the spot for statistical significance, surrounded by a sea of good-natured perplexity and whimsy.
The scatterplot (Fig. 1) showcases the robust correlation we uncovered, visually demonstrating the upward trend between the number of geography teachers in Texas and the points scored by the unfortunate losing team. It's as clear as a sunny day in the Lone Star State – there's something uniquely and unexpectedly fascinating about the influence of geography educators on the pigskin battleground. It's almost like they're giving a whole new meaning to "map out a strategy"!
Overall, our results shed light on the offbeat and delightful relationship between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl. It seems that in the land of big hats and even bigger dreams, geography educators may just hold the key to orchestrating not just geographical knowledge, but the very fabric of football defeat. After all, when it comes to unexpected correlations, this one takes the trophy – possibly a Lombardi Trophy, in this case!

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has uncovered a fascinating and somewhat hilarious connection between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl. It's like these educators are inadvertently shaping the gridiron landscape, drawing invisible maps that lead teams straight to defeat – talk about a "tex"-book example of unexpected influence!

Our findings have brought a new meaning to the phrase "putting Texas on the map," as it appears that the Lone Star State's geography educators might just be charting a course for Super Bowl disappointment, one map lesson at a time. It's as if they have a magnetic pull towards touchdown underachievement – now that's what I call "magnetic declination" of victory!

With our study, it's clear that there's more at play here than a quirky coincidence. The correlation coefficient and the r-squared value paint a compelling picture of the impact these latitude-loving teachers have on the Super Bowl scores. They're like the silent conductors of a football symphony, orchestrating touchdowns and field goals in the key of "teach-flat minor."

In the end, our research has not only uncovered an unexpected link between geography educators and football defeats but has also added a touch of whimsy to the world of statistical analysis. It's like we stumbled upon a treasure map that led us straight to this delightfully puzzling correlation – "X" marks the spot for academic merriment!

In closing, we firmly assert that no further research is needed in this area. As much as we'd love to keep unraveling the mystifying ties between geography teachers in Texas and Super Bowl woes, it's time to hang up our academic cleats and simply marvel at the quirky wonder of this correlation. After all, sometimes, the best conclusions are the ones that leave us with a smile, a head shake, and the everlasting mystery of the Lone Star State's influence on football scores. It's like a true Texas tale – big, bold, and delightfully baffling!

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 Texas Teachers and Super Bowl Defeats: Unraveling the Tightened Ties. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Americana Studies

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 Texas Teachers and Super Bowl Defeats: Unraveling the Tightened Ties. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Gridiron Academics and Classroom 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 Texas Teachers and Super Bowl Defeats: Unraveling the Tightened Ties with an abstract of The perplexing correlation between the number of geography teachers in Texas and the points scored by the losing team in the Super Bowl has long confounded researchers. In this study, we employed data from the Bureau of Labor Statistics and Wikipedia to scrutinize this enigmatic relationship. Our analysis revealed a significant positive correlation, with a correlation coefficient of 0.6226698 and p < 0.01 for the years 2003 to 2022.
As we delved into the connection between geography teachers in the Lone Star State and gridiron defeats, we couldn't help but marvel at the unexpected bond. It seems that when it comes to Super Bowl losses, geography teachers in Texas might hold some peculiar sway over the outcome. It's almost like they've been giving their students a lesson in geographical titillation!
Upon diving deeper into the data, we uncovered a striking trend. It appears that as the number of geography teachers in Texas increases, the points scored by the losing team in the Super Bowl also rise. It's as if these educators are inadvertently charting a path to gridiron defeat, one lesson at a time. Perhaps they're using their geographical knowledge to guide teams to the end zone – just not their own!
Our findings bring a lighthearted twist to academic research, as we've uncovered an unexpected tie between geography educators and football setbacks. It seems that in the land of cowboys and touchdowns, geography teachers may hold the key to location, location, location – even on the Super Bowl field. After all, when it comes to gridiron struggles, perhaps it's all about the longitudes and latitudes of defeat!

ChatGPT:

Texas, teachers, geography, correlation, Super Bowl, defeats, points scored, losing team, Bureau of Labor Statistics, Wikipedia, correlation coefficient, gridiron, Lone Star State, educational influence, football outcomes, geographical influence, academic research

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

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Data details

The number of geography teachers in Texas
Detailed data title: BLS estimate of geography teachers, postsecondary in Texas
Source: Bureau of Larbor Statistics
See what else correlates with The number of geography teachers in Texas

Points Scored by the losing team in the Super Bowl
Source: Wikipedia
See what else correlates with Points Scored by the losing team in the Super Bowl

Correlation r = 0.6226698 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.3877176 (Coefficient of determination)
This means 38.8% of the change in the one variable (i.e., Points Scored by the losing team in the Super Bowl) is predictable based on the change in the other (i.e., The number of geography teachers in Texas) over the 20 years from 2003 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.0034.^Show 0.0033647603317670640000000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.62 in 0.34% of random cases. Said differently, if you correlated 297 random variables^Note Which I absolutely did.
with the same 19 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 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.

[ 0.25, 0.84 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
The number of geography teachers in Texas (Laborers)	260	270	220	190	210	200	230	230	260	240	230	200	220	230	250	280	220	200	230	260
Points Scored by the losing team in the Super Bowl (Points scored)	21	29	21	10	17	14	23	17	25	17	31	8	24	10	28	33	3	20	9	20

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([260,270,220,190,210,200,230,230,260,240,230,200,220,230,250,280,220,200,230,260,])
array_2 = np.array([21,29,21,10,17,14,23,17,25,17,31,8,24,10,28,33,3,20,9,20,])
array_1_name = "The number of geography teachers in Texas"
array_2_name = "Points Scored by the losing team in the Super Bowl"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only The number of geography teachers in Texas
Line chart for only Points Scored by the losing team in the Super Bowl
The spurious research paper: Texas Teachers and Super Bowl Defeats: Unraveling the Tightened Ties

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Correlation ID: 1257 · Black Variable ID: 14729 · Red Variable ID: 540


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