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Spurious correlation #5,340 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Votes for Republican Senators in Montana and the second variable is The number of crane operators in Montana.  The chart goes from 2003 to 2020, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As more Republicans voted for Senators in Montana, there was a surge in support for heavy machinery industries. This newfound enthusiasm led to a statewide campaign to "Make Montana Lifty Again," resulting in an unexpected boom in the demand for crane operators. Guess you could say the political climate really lifted the job market!

Model: dalle-3
Prompt: Create an image of a colorful TIME magazine cover featuring a bustling city scene in Montana. Show a line of voters outside a polling station, proudly displaying support for Republican Senators. Meanwhile, depict a construction site buzzing with activity, with crane operators expertly maneuvering heavy machinery to construct new buildings. Include the "Make Montana Lifty Again" campaign banner fluttering in the background, symbolizing the surge in demand for crane operators due to increased support for heavy machinery industries. 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: Votes for Republican Senators in Montana and The number of crane operators in Montana. 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: Cute 2D animation Celtic art Cutsy art illustration Charcoal A TIME magazine cover image
ChatGPT: A TIME magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Votes for Republican Senators in Montana and The number of crane operators in Montana, in the following situation: As more Republicans voted for Senators in Montana, there was a surge in support for heavy machinery industries. This newfound enthusiasm led to a statewide campaign to "Make Montana Lifty Again," resulting in an unexpected boom in the demand for crane operators. Guess you could say the political climate really lifted the job market!. Keep the description simple.
ChatGPT: In a bustling city in Montana, a line of voters waits outside a polling station, with many proudly displaying their support for Republican Senators. Meanwhile, nearby, a construction site buzzes with activity as a group of crane operators expertly maneuver heavy machinery, lifting steel beams and constructing new buildings. The "Make Montana Lifty Again" campaign banner flutters in the background, symbolizing the surge in demand for crane operators due to the increased support for heavy machinery industries.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A TIME magazine cover image ] and depicting this scene: In a bustling city in Montana, a line of voters waits outside a polling station, with many proudly displaying their support for Republican Senators. Meanwhile, nearby, a construction site buzzes with activity as a group of crane operators expertly maneuver heavy machinery, lifting steel beams and constructing new buildings. The "Make Montana Lifty Again" campaign banner flutters in the background, symbolizing the surge in demand for crane operators due to the increased support for heavy machinery industries. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a colorful TIME magazine cover featuring a bustling city scene in Montana. Show a line of voters outside a polling station, proudly displaying support for Republican Senators. Meanwhile, depict a construction site buzzing with activity, with crane operators expertly maneuvering heavy machinery to construct new buildings. Include the "Make Montana Lifty Again" campaign banner fluttering in the background, symbolizing the surge in demand for crane operators due to increased support for heavy machinery industries.

*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.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Republican votes for Senators in Montana caused The number of crane operators in Montana to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.05)
Swinging Right: A Crane-tastic Correlation Between Republican Votes for Senators in Montana and the Number of Crane Operators

The Journal of Political Ornithology

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Republican votes for Senators in Montana and The number of crane operators in Montana. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Make the title a clever pun.

Your research team used data from MIT Election Data and Science Lab, Harvard Dataverse and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.8762824 and p < 0.05 for 2003 to 2020.

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]]
"Swinging Right: A Crane-tastic Correlation Between Republican Votes for Senators in Montana and the Number of Crane Operators"

[[ABSTRACT]]
In this paper, we investigate the curious and crane-tastic correlation between the Republican votes for Senators in Montana and the number of crane operators in the state. Using data from MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we analyzed the relationship between political preferences and the labor force, specifically focusing on the period from 2003 to 2020.

Our analysis revealed a surprisingly strong correlation coefficient of 0.8762824 with a statistically significant p-value of less than 0.05, indicating a largely crane-sequential relationship (pun intended). The findings suggest that as Republican votes for Senators in Montana increase, so does the number of crane operators in the state, leading to the quip: "With Republicans on the rise, the crane industry reaches new heights!"

This unexpected connection highlights the potential influence of political dynamics in shaping occupational patterns, and opens the door for further investigation into the interactions between political landscapes and labor market trends. As we delve deeper into the crane-nundrum, the interplay between political ideologies and career choices unravels with a comical twist, showing that when it comes to understanding labor trends, we need to crane our necks for unexpected correlations.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Republican votes for Senators in Montana and The number of crane operators in Montana. 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]]
"Swinging Right: A Crane-tastic Correlation Between Republican Votes for Senators in Montana and the Number of Crane Operators"

[[ABSTRACT]]
In this paper, we investigate the curious and crane-tastic correlation between the Republican votes for Senators in Montana and the number of crane operators in the state. Using data from MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we analyzed the relationship between political preferences and the labor force, specifically focusing on the period from 2003 to 2020.

Our analysis revealed a surprisingly strong correlation coefficient of 0.8762824 with a statistically significant p-value of less than 0.05, indicating a largely crane-sequential relationship (pun intended). The findings suggest that as Republican votes for Senators in Montana increase, so does the number of crane operators in the state, leading to the quip: "With Republicans on the rise, the crane industry reaches new heights!"

This unexpected connection highlights the potential influence of political dynamics in shaping occupational patterns, and opens the door for further investigation into the interactions between political landscapes and labor market trends. As we delve deeper into the crane-nundrum, the interplay between political ideologies and career choices unravels with a comical twist, showing that when it comes to understanding labor trends, we need to crane our necks for unexpected correlations.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

As researchers, we are always on the lookout for unexpected connections and correlations in the vast landscape of data. Sometimes, the findings are as surprising as seeing a crane operator at a political rally! In this study, we delve into the peculiar relationship between Republican votes for Senators in Montana and the number of crane operators in the state. It's a crane-tastic correlation that demands further investigation, and we can't help but crane our necks to get a better view of this curious phenomenon.

Picture this: a Republican senatorial candidate harnessing the power of their campaign and, at the same time, unwittingly driving the number of crane operators in Montana to new heights. It's a high-flying scenario that caught our attention, and we just couldn't resist temptations to lift the veil on this unexpected link.

The idea of exploring this political-labor market relationship struck us with the force of a falling wrecking ball. After all, it's not every day that we stumble upon statistical evidence that practically screams, "Let's crane our data and analyze this crane-undrum!" It’s a reminder that in the world of data analysis, unexpected correlations can often tower above the rest.

Our study aims to add a new dimension to the discourse on the influence of political preferences on labor market trends. There's no doubt that the connection between Republican votes and crane operators is a bit of a head-scratcher, but as researchers, we're always prepared to hoist the sail and navigate through uncharted statistical waters.

Further delving into this crane-tastic correlation not only provides an entertaining twist to our academic pursuits but also underscores the importance of exploring unforeseen connections in the realm of data analysis. After all, who knew that political ideologies could be so influential in shaping the occupational landscape? It truly highlights the need to approach statistical analysis with a sense of humor – because sometimes, the correlations that emerge from the data can crane-dle a few surprises!

As we embark on this statistical journey into the crane-spiracy, let's not forget that even the most unexpected correlations can offer valuable insights into the complex interplay between political dynamics and labor market trends. With that in mind, let's raise our analytical cranes and explore this crane-tastic correlation with a blend of statistical rigor and a pinch of humor. Because when it comes to unraveling unexpected connections, a good laugh can often be the cherry on top of the data-driven cake.



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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Republican votes for Senators in Montana and The number of crane operators in Montana. 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
"Swinging Right: A Crane-tastic Correlation Between Republican Votes for Senators in Montana and the Number of Crane Operators"

[[ABSTRACT]]
In this paper, we investigate the curious and crane-tastic correlation between the Republican votes for Senators in Montana and the number of crane operators in the state. Using data from MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we analyzed the relationship between political preferences and the labor force, specifically focusing on the period from 2003 to 2020.

Our analysis revealed a surprisingly strong correlation coefficient of 0.8762824 with a statistically significant p-value of less than 0.05, indicating a largely crane-sequential relationship (pun intended). The findings suggest that as Republican votes for Senators in Montana increase, so does the number of crane operators in the state, leading to the quip: "With Republicans on the rise, the crane industry reaches new heights!"

This unexpected connection highlights the potential influence of political dynamics in shaping occupational patterns, and opens the door for further investigation into the interactions between political landscapes and labor market trends. As we delve deeper into the crane-nundrum, the interplay between political ideologies and career choices unravels with a comical twist, showing that when it comes to understanding labor trends, we need to crane our necks for unexpected correlations.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As researchers, we are always on the lookout for unexpected connections and correlations in the vast landscape of data. Sometimes, the findings are as surprising as seeing a crane operator at a political rally! In this study, we delve into the peculiar relationship between Republican votes for Senators in Montana and the number of crane operators in the state. It's a crane-tastic correlation that demands further investigation, and we can't help but crane our necks to get a better view of this curious phenomenon.
Picture this: a Republican senatorial candidate harnessing the power of their campaign and, at the same time, unwittingly driving the number of crane operators in Montana to new heights. It's a high-flying scenario that caught our attention, and we just couldn't resist temptations to lift the veil on this unexpected link.
The idea of exploring this political-labor market relationship struck us with the force of a falling wrecking ball. After all, it's not every day that we stumble upon statistical evidence that practically screams, "Let's crane our data and analyze this crane-undrum!" It’s a reminder that in the world of data analysis, unexpected correlations can often tower above the rest.
Our study aims to add a new dimension to the discourse on the influence of political preferences on labor market trends. There's no doubt that the connection between Republican votes and crane operators is a bit of a head-scratcher, but as researchers, we're always prepared to hoist the sail and navigate through uncharted statistical waters.
Further delving into this crane-tastic correlation not only provides an entertaining twist to our academic pursuits but also underscores the importance of exploring unforeseen connections in the realm of data analysis. After all, who knew that political ideologies could be so influential in shaping the occupational landscape? It truly highlights the need to approach statistical analysis with a sense of humor – because sometimes, the correlations that emerge from the data can crane-dle a few surprises!
As we embark on this statistical journey into the crane-spiracy, let's not forget that even the most unexpected correlations can offer valuable insights into the complex interplay between political dynamics and labor market trends. With that in mind, let's raise our analytical cranes and explore this crane-tastic correlation with a blend of statistical rigor and a pinch of humor. Because when it comes to unraveling unexpected connections, a good laugh can often be the cherry on top of the data-driven cake.


-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The connection between political preferences and labor force dynamics has garnered much attention in recent years, with studies exploring the impact of partisan affiliations on occupational trends. Smith and Doe (2017) conducted a comprehensive analysis of the relationship between political voting patterns and labor market fluctuations, shedding light on the intricate interplay between ideology and employment choices.

In "Book," the authors find that lorem and ipsum, demonstrating a nuanced understanding of the multifaceted influences that shape occupational distributions within states. This scholarly work offers valuable insights into the socio-economic factors that underpin the choice of professions and the potential correlation with political landscapes.

Moving beyond the conventional paradigms of examining political phenomena in relation to occupational choices, the unexpected connection between Republican votes for Senators in Montana and the number of crane operators presents a crane-tastic opportunity for unconventional inquiry. As we crane our necks to explore this peculiar correlation, it's worth noting that this research also takes a lighthearted approach to uncovering intriguing statistical associations.

As the scholarly pursuit of uncovering the crane-undrum continues, it's essential to consider the broader implications of this unexpected bond. After all, who would have thought that political inclinations could extend their influence into the realm of crane operations? It's a thought-provoking situation that prompts us to crane our minds for a viable explanation, and perhaps, even a dad joke or two to lighten the statistical mood.

In "Game," the authors dissect the intricacies of strategy and correlation, paving the way for a playful exploration of statistical conjecture. While this board game may seem disconnected from the world of labor economics, its emphasis on unexpected linkages and strategic maneuvering inadvertently mirrors the academic venture of unravelling the crane-tastic correlation.

Turning to the realm of literature, the fictional works of "The Towering Crane Chronicles" and "The Republican Operator's Manifesto" present imaginative narratives that playfully intersect themes of politics and labor, offering a whimsical take on the themes inherent to our investigation. As we traverse the boundaries of reality and fiction, it becomes evident that the crane-tastic correlation not only captures statistical intrigue but also inspires creative renderings in various forms of storytelling.

In "The Statistical Sleuth," the authors delve into the art of uncovering unexpected patterns in data, reminding us that statistical analysis can often unearth amusing and offbeat connections. This notion resonates with our endeavor to unravel the correlation between Republican votes for Senators in Montana and the number of crane operators, prompting us to approach the task with a statistical rigor and a sprinkle of humor.

It is within the realm of scholarly pursuit that we find ourselves entwined in the curious interplay of politics and crane operators, navigating through data-driven insights with a buoyant spirit and a penchant for unexpected statistical musings. As we synthesize the varying dimensions of this crane-tastic correlation, it becomes clear that statistical inquiry need not be devoid of levity, and that even the most surreal connections can offer valuable insights within the realms of labor economics and political dynamics. After all, who would have thought that statistical investigation could be a crane-tastically humorous pursuit?



Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Republican votes for Senators in Montana and The number of crane operators in Montana. 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 MIT Election Data and Science Lab, Harvard Dataverse and Bureau of Larbor Statistics . You used data from 2003 to 2020

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]]
"Swinging Right: A Crane-tastic Correlation Between Republican Votes for Senators in Montana and the Number of Crane Operators"

[[ABSTRACT]]
In this paper, we investigate the curious and crane-tastic correlation between the Republican votes for Senators in Montana and the number of crane operators in the state. Using data from MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we analyzed the relationship between political preferences and the labor force, specifically focusing on the period from 2003 to 2020.

Our analysis revealed a surprisingly strong correlation coefficient of 0.8762824 with a statistically significant p-value of less than 0.05, indicating a largely crane-sequential relationship (pun intended). The findings suggest that as Republican votes for Senators in Montana increase, so does the number of crane operators in the state, leading to the quip: "With Republicans on the rise, the crane industry reaches new heights!"

This unexpected connection highlights the potential influence of political dynamics in shaping occupational patterns, and opens the door for further investigation into the interactions between political landscapes and labor market trends. As we delve deeper into the crane-nundrum, the interplay between political ideologies and career choices unravels with a comical twist, showing that when it comes to understanding labor trends, we need to crane our necks for unexpected correlations.

[[INTRODUCTION]]
As researchers, we are always on the lookout for unexpected connections and correlations in the vast landscape of data. Sometimes, the findings are as surprising as seeing a crane operator at a political rally! In this study, we delve into the peculiar relationship between Republican votes for Senators in Montana and the number of crane operators in the state. It's a crane-tastic correlation that demands further investigation, and we can't help but crane our necks to get a better view of this curious phenomenon.
Picture this: a Republican senatorial candidate harnessing the power of their campaign and, at the same time, unwittingly driving the number of crane operators in Montana to new heights. It's a high-flying scenario that caught our attention, and we just couldn't resist temptations to lift the veil on this unexpected link.
The idea of exploring this political-labor market relationship struck us with the force of a falling wrecking ball. After all, it's not every day that we stumble upon statistical evidence that practically screams, "Let's crane our data and analyze this crane-undrum!" It’s a reminder that in the world of data analysis, unexpected correlations can often tower above the rest.
Our study aims to add a new dimension to the discourse on the influence of political preferences on labor market trends. There's no doubt that the connection between Republican votes and crane operators is a bit of a head-scratcher, but as researchers, we're always prepared to hoist the sail and navigate through uncharted statistical waters.
Further delving into this crane-tastic correlation not only provides an entertaining twist to our academic pursuits but also underscores the importance of exploring unforeseen connections in the realm of data analysis. After all, who knew that political ideologies could be so influential in shaping the occupational landscape? It truly highlights the need to approach statistical analysis with a sense of humor – because sometimes, the correlations that emerge from the data can crane-dle a few surprises!
As we embark on this statistical journey into the crane-spiracy, let's not forget that even the most unexpected correlations can offer valuable insights into the complex interplay between political dynamics and labor market trends. With that in mind, let's raise our analytical cranes and explore this crane-tastic correlation with a blend of statistical rigor and a pinch of humor. Because when it comes to unraveling unexpected connections, a good laugh can often be the cherry on top of the data-driven cake.


-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To investigate the crane-tastic correlation between Republican votes for Senators in Montana and the number of crane operators in the state, we utilized a fusion of statistical wizardry, data mining, and a dash of good old-fashioned sleuthing. Our data collection process was akin to a treasure hunt, as we scoured the depths of the MIT Election Data and Science Lab, Harvard Dataverse, and Bureau of Labor Statistics to assemble a comprehensive dataset spanning the years 2003 to 2020. It was a bit like panning for gold – except in this case, we were prospecting for political and labor data nuggets.

Now, let’s talk turkey... or should I say, crane? Our primary data sources provided us with valuable insights into the election outcomes and labor statistics in Montana. We meticulously documented the number of Republican votes for Senators in Montana elections and diligently counted the crane operators working in the state. Our approach was as precise as a crane operator expertly maneuvering a heavy load, ensuring that every data point was securely fastened for analysis.

In our quest for statistical enlightenment, we subjected the gathered data to the arduous process of verification and cleaning. Just like a crane operator meticulously inspects their equipment before a task, we rigorously examined the data for any anomalies, outliers, or inaccuracies that could lead us astray. We then performed a series of robust statistical analyses to disentangle the complexities of the relationship between Republican votes and the number of crane operators, carefully navigating through the statistical terrain like skilled crane operators manipulating their machinery through a construction site.

The heart of our statistical inquiry lay in the application of correlation analysis, where we sought to quantify the strength and direction of the association between Republican votes for Senators and the abundance of crane operators. With bated breath and a touch of anticipation, we calculated the Pearson correlation coefficient and its accompanying p-value, eagerly awaiting the results like spectators waiting for a crane to hoist a heavy load – they were lifting the suspense, so to speak.

Additionally, we employed time series analysis to examine the temporal fluctuations in both the political and labor market variables. This allowed us to unravel the nuances of the crane-tastic correlation across different time periods, akin to carefully observing the ebb and flow of crane movements at a construction site. Our approach was as methodical as a crane operator orchestrating a delicate ballet of movements, ensuring that we captured the rhythm of the political and labor dynamics with precision.

In summary, our methodology blended a curious concoction of data collection, rigorous cleaning, and robust statistical analysis, akin to the careful orchestration of a complex construction project. With the statistical cranes at our disposal, we ventured into uncharted analytical territories, ultimately unveiling the surprising relationship between Republican votes for Senators in Montana and the abundance of crane operators with a blend of scientific rigor and a touch of humor.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Republican votes for Senators in Montana and The number of crane operators in Montana. 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 MIT Election Data and Science Lab, Harvard Dataverse and Bureau of Larbor Statistics .

For the time period 2003 to 2020, you found a correlation 0.8762824, r-squared of 0.7678708, and p < 0.05.

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]]
"Swinging Right: A Crane-tastic Correlation Between Republican Votes for Senators in Montana and the Number of Crane Operators"

[[ABSTRACT]]
In this paper, we investigate the curious and crane-tastic correlation between the Republican votes for Senators in Montana and the number of crane operators in the state. Using data from MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we analyzed the relationship between political preferences and the labor force, specifically focusing on the period from 2003 to 2020.

Our analysis revealed a surprisingly strong correlation coefficient of 0.8762824 with a statistically significant p-value of less than 0.05, indicating a largely crane-sequential relationship (pun intended). The findings suggest that as Republican votes for Senators in Montana increase, so does the number of crane operators in the state, leading to the quip: "With Republicans on the rise, the crane industry reaches new heights!"

This unexpected connection highlights the potential influence of political dynamics in shaping occupational patterns, and opens the door for further investigation into the interactions between political landscapes and labor market trends. As we delve deeper into the crane-nundrum, the interplay between political ideologies and career choices unravels with a comical twist, showing that when it comes to understanding labor trends, we need to crane our necks for unexpected correlations.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
As researchers, we are always on the lookout for unexpected connections and correlations in the vast landscape of data. Sometimes, the findings are as surprising as seeing a crane operator at a political rally! In this study, we delve into the peculiar relationship between Republican votes for Senators in Montana and the number of crane operators in the state. It's a crane-tastic correlation that demands further investigation, and we can't help but crane our necks to get a better view of this curious phenomenon.
Picture this: a Republican senatorial candidate harnessing the power of their campaign and, at the same time, unwittingly driving the number of crane operators in Montana to new heights. It's a high-flying scenario that caught our attention, and we just couldn't resist temptations to lift the veil on this unexpected link.
The idea of exploring this political-labor market relationship struck us with the force of a falling wrecking ball. After all, it's not every day that we stumble upon statistical evidence that practically screams, "Let's crane our data and analyze this crane-undrum!" It’s a reminder that in the world of data analysis, unexpected correlations can often tower above the rest.
Our study aims to add a new dimension to the discourse on the influence of political preferences on labor market trends. There's no doubt that the connection between Republican votes and crane operators is a bit of a head-scratcher, but as researchers, we're always prepared to hoist the sail and navigate through uncharted statistical waters.
Further delving into this crane-tastic correlation not only provides an entertaining twist to our academic pursuits but also underscores the importance of exploring unforeseen connections in the realm of data analysis. After all, who knew that political ideologies could be so influential in shaping the occupational landscape? It truly highlights the need to approach statistical analysis with a sense of humor – because sometimes, the correlations that emerge from the data can crane-dle a few surprises!
As we embark on this statistical journey into the crane-spiracy, let's not forget that even the most unexpected correlations can offer valuable insights into the complex interplay between political dynamics and labor market trends. With that in mind, let's raise our analytical cranes and explore this crane-tastic correlation with a blend of statistical rigor and a pinch of humor. Because when it comes to unraveling unexpected connections, a good laugh can often be the cherry on top of the data-driven cake.


-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of data from the period between 2003 and 2020 revealed a surprisingly strong positive correlation of 0.8762824 between Republican votes for Senators in Montana and the number of crane operators in the state. This statistically significant relationship, with an r-squared of 0.7678708 and a p-value of less than 0.05, suggests that the increase in Republican support is associated with a proportional rise in the number of crane operators in Montana. It seems that as the political landscape in Montana tilts to the right, the crane industry is hoisting itself to new heights!

Fig. 1 presents a scatterplot illustrating this robust correlation, highlighting the upward trend of crane operators alongside the Republican votes for Senators in Montana. It's as clear as day – when it comes to the influence of political preferences on the labor force, we can't help but crane our necks for these unexpected connections!

The humorous spin on these unexpected findings certainly creates a stir. After all, who would have thought that political inclinations could have such a profound impact on the labor market? This revelation opens the door for a plethora of tongue-in-cheek quips, such as "Republican votes causing a crane-ival in Montana!" or "With conservative support soaring, the crane industry takes flight!" Indeed, the statistical analysis may be serious, but there's no harm in craning up the humor to lighten the scholarly mood.

The findings from this study not only underscore the need to approach data analysis with a sense of amusement but also emphasize the importance of exploring unforeseen connections in the realm of statistical research. As we crane our statistical necks towards this unexpected correlation, let's not forget the invaluable insights it provides into the intricate relationship between political dynamics and labor market trends. Who knew that political preferences could crane-dle such surprising consequences?


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Republican votes for Senators in Montana and The number of crane operators in Montana. 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]]
"Swinging Right: A Crane-tastic Correlation Between Republican Votes for Senators in Montana and the Number of Crane Operators"

[[ABSTRACT]]
In this paper, we investigate the curious and crane-tastic correlation between the Republican votes for Senators in Montana and the number of crane operators in the state. Using data from MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we analyzed the relationship between political preferences and the labor force, specifically focusing on the period from 2003 to 2020.

Our analysis revealed a surprisingly strong correlation coefficient of 0.8762824 with a statistically significant p-value of less than 0.05, indicating a largely crane-sequential relationship (pun intended). The findings suggest that as Republican votes for Senators in Montana increase, so does the number of crane operators in the state, leading to the quip: "With Republicans on the rise, the crane industry reaches new heights!"

This unexpected connection highlights the potential influence of political dynamics in shaping occupational patterns, and opens the door for further investigation into the interactions between political landscapes and labor market trends. As we delve deeper into the crane-nundrum, the interplay between political ideologies and career choices unravels with a comical twist, showing that when it comes to understanding labor trends, we need to crane our necks for unexpected correlations.

[[LITERATURE REVIEW]]
The connection between political preferences and labor force dynamics has garnered much attention in recent years, with studies exploring the impact of partisan affiliations on occupational trends. Smith and Doe (2017) conducted a comprehensive analysis of the relationship between political voting patterns and labor market fluctuations, shedding light on the intricate interplay between ideology and employment choices.
In "Book," the authors find that lorem and ipsum, demonstrating a nuanced understanding of the multifaceted influences that shape occupational distributions within states. This scholarly work offers valuable insights into the socio-economic factors that underpin the choice of professions and the potential correlation with political landscapes.
Moving beyond the conventional paradigms of examining political phenomena in relation to occupational choices, the unexpected connection between Republican votes for Senators in Montana and the number of crane operators presents a crane-tastic opportunity for unconventional inquiry. As we crane our necks to explore this peculiar correlation, it's worth noting that this research also takes a lighthearted approach to uncovering intriguing statistical associations.
As the scholarly pursuit of uncovering the crane-undrum continues, it's essential to consider the broader implications of this unexpected bond. After all, who would have thought that political inclinations could extend their influence into the realm of crane operations? It's a thought-provoking situation that prompts us to crane our minds for a viable explanation, and perhaps, even a dad joke or two to lighten the statistical mood.
In "Game," the authors dissect the intricacies of strategy and correlation, paving the way for a playful exploration of statistical conjecture. While this board game may seem disconnected from the world of labor economics, its emphasis on unexpected linkages and strategic maneuvering inadvertently mirrors the academic venture of unravelling the crane-tastic correlation.
Turning to the realm of literature, the fictional works of "The Towering Crane Chronicles" and "The Republican Operator's Manifesto" present imaginative narratives that playfully intersect themes of politics and labor, offering a whimsical take on the themes inherent to our investigation. As we traverse the boundaries of reality and fiction, it becomes evident that the crane-tastic correlation not only captures statistical intrigue but also inspires creative renderings in various forms of storytelling.
In "The Statistical Sleuth," the authors delve into the art of uncovering unexpected patterns in data, reminding us that statistical analysis can often unearth amusing and offbeat connections. This notion resonates with our endeavor to unravel the correlation between Republican votes for Senators in Montana and the number of crane operators, prompting us to approach the task with a statistical rigor and a sprinkle of humor.
It is within the realm of scholarly pursuit that we find ourselves entwined in the curious interplay of politics and crane operators, navigating through data-driven insights with a buoyant spirit and a penchant for unexpected statistical musings. As we synthesize the varying dimensions of this crane-tastic correlation, it becomes clear that statistical inquiry need not be devoid of levity, and that even the most surreal connections can offer valuable insights within the realms of labor economics and political dynamics. After all, who would have thought that statistical investigation could be a crane-tastically humorous pursuit?


[[RESULTS]]
The analysis of data from the period between 2003 and 2020 revealed a surprisingly strong positive correlation of 0.8762824 between Republican votes for Senators in Montana and the number of crane operators in the state. This statistically significant relationship, with an r-squared of 0.7678708 and a p-value of less than 0.05, suggests that the increase in Republican support is associated with a proportional rise in the number of crane operators in Montana. It seems that as the political landscape in Montana tilts to the right, the crane industry is hoisting itself to new heights!
Fig. 1 presents a scatterplot illustrating this robust correlation, highlighting the upward trend of crane operators alongside the Republican votes for Senators in Montana. It's as clear as day – when it comes to the influence of political preferences on the labor force, we can't help but crane our necks for these unexpected connections!
The humorous spin on these unexpected findings certainly creates a stir. After all, who would have thought that political inclinations could have such a profound impact on the labor market? This revelation opens the door for a plethora of tongue-in-cheek quips, such as "Republican votes causing a crane-ival in Montana!" or "With conservative support soaring, the crane industry takes flight!" Indeed, the statistical analysis may be serious, but there's no harm in craning up the humor to lighten the scholarly mood.
The findings from this study not only underscore the need to approach data analysis with a sense of amusement but also emphasize the importance of exploring unforeseen connections in the realm of statistical research. As we crane our statistical necks towards this unexpected correlation, let's not forget the invaluable insights it provides into the intricate relationship between political dynamics and labor market trends. Who knew that political preferences could crane-dle such surprising consequences?

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The uncanny correlation between Republican votes for Senators in Montana and the number of crane operators in the state unravels an unexpected and thought-provoking relationship that warrants both serious consideration and a good sense of humor. As we delve into the implications of our findings, it becomes evident that statistical research, much like the operation of cranes, requires a careful balance of precision and levity.

Our study's results not only support the prior research that explored the influence of political voting patterns on labor market fluctuations but also add a crane-tastic twist to the ongoing discourse. The robust correlation coefficient of 0.8762824 and the statistically significant p-value of less than 0.05 affirm the existence of a strikingly positive relationship, reinforcing the prior scholarly investigations. This finding humorously echoes the sentiments expressed in "The Statistical Sleuth," reminding us that statistical analysis can indeed uncover amusing and offbeat connections. One might say that the statistical tale we unravelled here is "crane-fully" intriguing.

The lighthearted approach to uncovering this unforeseen correlation not only adds a touch of amusement to the scholarly pursuit but also emphasizes the importance of exploring unexpected statistical musings. The unexpectedly strong positive correlation leads us to ponder the implications of political landscape on labor market dynamics, prompting us to crane our minds for a viable explanation – and perhaps even a dad joke or two to lighten the statistical mood. It's indeed fascinating (and quite the "crane-undrum") how political inclinations could extend their influence into the labor force dynamics.

The scatterplot visually illustrates the upward trend of crane operators alongside the Republican votes for Senators in Montana, highlighting the undeniable link between the two variables. It's crystal clear – with Republicans on the rise, the crane industry reaches new heights! This comical quip might succinctly capture the essence of our unexpected findings, reminding us that statistical inquiry need not be devoid of levity, and that even the most surreal connections can offer valuable insights within the realms of labor economics and political dynamics.

This study, albeit its humorous tone, underscores the importance of approaching data analysis with a sense of amusement and playfulness. The statistical investigation may be a serious endeavor, but there's no harm in craning up the humor to lighten the scholarly mood. The unexpected correlation between Republican votes for Senators in Montana and the number of crane operators not only exemplifies the curious interplay of politics and labor force but also serves as a reminder that statistical analysis can often unearth amusing and offbeat connections. After all, who would have thought that statistical investigation could be a crane-tastically humorous pursuit?


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Republican votes for Senators in Montana and The number of crane operators in Montana. 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]]
"Swinging Right: A Crane-tastic Correlation Between Republican Votes for Senators in Montana and the Number of Crane Operators"

[[ABSTRACT]]
In this paper, we investigate the curious and crane-tastic correlation between the Republican votes for Senators in Montana and the number of crane operators in the state. Using data from MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we analyzed the relationship between political preferences and the labor force, specifically focusing on the period from 2003 to 2020.

Our analysis revealed a surprisingly strong correlation coefficient of 0.8762824 with a statistically significant p-value of less than 0.05, indicating a largely crane-sequential relationship (pun intended). The findings suggest that as Republican votes for Senators in Montana increase, so does the number of crane operators in the state, leading to the quip: "With Republicans on the rise, the crane industry reaches new heights!"

This unexpected connection highlights the potential influence of political dynamics in shaping occupational patterns, and opens the door for further investigation into the interactions between political landscapes and labor market trends. As we delve deeper into the crane-nundrum, the interplay between political ideologies and career choices unravels with a comical twist, showing that when it comes to understanding labor trends, we need to crane our necks for unexpected correlations.

[[INTRDUCTION]]
As researchers, we are always on the lookout for unexpected connections and correlations in the vast landscape of data. Sometimes, the findings are as surprising as seeing a crane operator at a political rally! In this study, we delve into the peculiar relationship between Republican votes for Senators in Montana and the number of crane operators in the state. It's a crane-tastic correlation that demands further investigation, and we can't help but crane our necks to get a better view of this curious phenomenon.
Picture this: a Republican senatorial candidate harnessing the power of their campaign and, at the same time, unwittingly driving the number of crane operators in Montana to new heights. It's a high-flying scenario that caught our attention, and we just couldn't resist temptations to lift the veil on this unexpected link.
The idea of exploring this political-labor market relationship struck us with the force of a falling wrecking ball. After all, it's not every day that we stumble upon statistical evidence that practically screams, "Let's crane our data and analyze this crane-undrum!" It’s a reminder that in the world of data analysis, unexpected correlations can often tower above the rest.
Our study aims to add a new dimension to the discourse on the influence of political preferences on labor market trends. There's no doubt that the connection between Republican votes and crane operators is a bit of a head-scratcher, but as researchers, we're always prepared to hoist the sail and navigate through uncharted statistical waters.
Further delving into this crane-tastic correlation not only provides an entertaining twist to our academic pursuits but also underscores the importance of exploring unforeseen connections in the realm of data analysis. After all, who knew that political ideologies could be so influential in shaping the occupational landscape? It truly highlights the need to approach statistical analysis with a sense of humor – because sometimes, the correlations that emerge from the data can crane-dle a few surprises!
As we embark on this statistical journey into the crane-spiracy, let's not forget that even the most unexpected correlations can offer valuable insights into the complex interplay between political dynamics and labor market trends. With that in mind, let's raise our analytical cranes and explore this crane-tastic correlation with a blend of statistical rigor and a pinch of humor. Because when it comes to unraveling unexpected connections, a good laugh can often be the cherry on top of the data-driven cake.


[[RESULTS]]
The analysis of data from the period between 2003 and 2020 revealed a surprisingly strong positive correlation of 0.8762824 between Republican votes for Senators in Montana and the number of crane operators in the state. This statistically significant relationship, with an r-squared of 0.7678708 and a p-value of less than 0.05, suggests that the increase in Republican support is associated with a proportional rise in the number of crane operators in Montana. It seems that as the political landscape in Montana tilts to the right, the crane industry is hoisting itself to new heights!
Fig. 1 presents a scatterplot illustrating this robust correlation, highlighting the upward trend of crane operators alongside the Republican votes for Senators in Montana. It's as clear as day – when it comes to the influence of political preferences on the labor force, we can't help but crane our necks for these unexpected connections!
The humorous spin on these unexpected findings certainly creates a stir. After all, who would have thought that political inclinations could have such a profound impact on the labor market? This revelation opens the door for a plethora of tongue-in-cheek quips, such as "Republican votes causing a crane-ival in Montana!" or "With conservative support soaring, the crane industry takes flight!" Indeed, the statistical analysis may be serious, but there's no harm in craning up the humor to lighten the scholarly mood.
The findings from this study not only underscore the need to approach data analysis with a sense of amusement but also emphasize the importance of exploring unforeseen connections in the realm of statistical research. As we crane our statistical necks towards this unexpected correlation, let's not forget the invaluable insights it provides into the intricate relationship between political dynamics and labor market trends. Who knew that political preferences could crane-dle such surprising consequences?

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]
In conclusion, our study has unveiled a crane-tastic correlation between Republican votes for Senators in Montana and the number of crane operators in the state. The statistically significant relationship, with an r-squared of 0.7678708 and a p-value of less than 0.05, suggests that as the political landscape in Montana tilts to the right, the crane industry is hoisting itself to new heights - pun intended! It's as if the Republican votes are acting as a crane operator, lifting the labor market to unforeseen levels of productivity and, dare I say, "elevating" the occupational landscape (excuse the pun).

As we crane our necks to comprehend this unexpected connection, it's clear that this correlation has far-reaching implications. Who would have thought that political dynamics could steer the labor market in such a crane-azy direction? These findings certainly carry weight in highlighting the influential nature of political preferences on career choices. It seems that in Montana, conservative support isn't just voting at the polls – it's also casting its crane-tal over the labor force!

Now, as tempting as it may be to extend this crane-tastic journey of discovery, it's safe to say that this particular correlation, like a well-operated crane, has reached its zenith for exploration. Our study has shed light on this peculiar connection, and it's time to lower the statistical boom, so to speak. We can confidently conclude that no more research is needed in this area, as we've certainly craned out all the significant insights and puns!

In the end, as researchers, we must not only crane our data but also crane our necks to spot those unexpected correlations that bring a smile to our faces. After all, a good laugh in statistical research can be as uplifting as a well-timed dad joke. It's a reminder that in the serious world of academia, there's always room to crane-dle a bit of humor!


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 Swinging Right: A Crane-tastic Correlation Between Republican Votes for Senators in Montana and the Number of Crane Operators. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Political Ornithology


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 Swinging Right: A Crane-tastic Correlation Between Republican Votes for Senators in Montana and the Number of Crane Operators. Respond only with the name of a fictional organization.

ChatGPT:

Society for Applied Ecological and Political Analysis


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 Swinging Right: A Crane-tastic Correlation Between Republican Votes for Senators in Montana and the Number of Crane Operators with an abstract of In this paper, we investigate the curious and crane-tastic correlation between the Republican votes for Senators in Montana and the number of crane operators in the state. Using data from MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we analyzed the relationship between political preferences and the labor force, specifically focusing on the period from 2003 to 2020.
Our analysis revealed a surprisingly strong correlation coefficient of 0.8762824 with a statistically significant p-value of less than 0.05, indicating a largely crane-sequential relationship (pun intended). The findings suggest that as Republican votes for Senators in Montana increase, so does the number of crane operators in the state, leading to the quip: "With Republicans on the rise, the crane industry reaches new heights!"
This unexpected connection highlights the potential influence of political dynamics in shaping occupational patterns, and opens the door for further investigation into the interactions between political landscapes and labor market trends. As we delve deeper into the crane-nundrum, the interplay between political ideologies and career choices unravels with a comical twist, showing that when it comes to understanding labor trends, we need to crane our necks for unexpected correlations.

ChatGPT:

Republican votes, Senators, Montana, crane operators, correlation, MIT Election Data and Science Lab, Harvard Dataverse, Bureau of Labor Statistics, political preferences, labor force, occupational patterns, political dynamics, labor market trends, political landscapes, career choices, correlation coefficient, p-value, statistical significance, labor trends, political ideologies.

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



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Data details

Votes for Republican Senators in Montana
Detailed data title: Percentage of votes cast for Federal Republican Senate candidates in Montana
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for Republican Senators in Montana

The number of crane operators in Montana
Detailed data title: BLS estimate of crane and tower operators in Montana
Source: Bureau of Larbor Statistics
See what else correlates with The number of crane operators in Montana

Correlation r = 0.8762824 (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 = 0.7678708 (Coefficient of determination)
This means 76.8% of the change in the one variable (i.e., The number of crane operators in Montana) is predictable based on the change in the other (i.e., Votes for Republican Senators in Montana) over the 6 years from 2003 through 2020.

p < 0.05, which statistically significant(Null hypothesis significance test)
The p-value is 0.022. 0.0220122643887202900000000000
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 0.88 in 2.2% of random cases. Said differently, if you correlated 45 random variables Which I absolutely did.
with the same 5 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 5 because we have two variables measured over a period of 6 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.

[ 0.22, 0.99 ] 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.
200620082012201420182020
Votes for Republican Senators in Montana (Percentage of votes)48.285527.08444.860457.786446.782455.0122
The number of crane operators in Montana (Laborers)11080120160100130




Why this works

  1. Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 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.
  2. 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.
  3. 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.
  4. Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.




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([48.2855,27.084,44.8604,57.7864,46.7824,55.0122,])
array_2 = np.array([110,80,120,160,100,130,])
array_1_name = "Votes for Republican Senators in Montana"
array_2_name = "The number of crane operators in Montana"

# 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)



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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."

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Correlation ID: 5340 · Black Variable ID: 26418 · Red Variable ID: 10830
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