Spurious correlation #5,304 · 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 Democratic Senators in Nebraska and the second variable is The number of production, planning, and expediting clerks in Nebraska. The chart goes from 2003 to 2020, 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 Votes for Democratic Senators in Nebraska and the second variable is The number of production, planning, and expediting clerks in Nebraska. The chart goes from 2003 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the Democrat votes for Senators in Nebraska decreased, the state experienced a ripple effect in the labor market. Due to the intricacies of political workforce dynamics, there was a surprising but substantial impact on the demand for production, planning, and expediting clerks. It appears that the bureaucratic shift led to a reevaluation of optimization processes, prompting a gradual phasing out of certain clerical positions. It's truly a testament to the interconnectedness of politics and production - a textbook case of how legislative preferences can unexpectedly shape the occupational landscape. Who would have thought that the ebb and flow of senatorial support could reach such granular levels of the workforce? It's a fascinating revelation that highlights the multifaceted nature of electoral influence!

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Generate an image of a futuristic office building in Nebraska, with sophisticated robotic clerks processing data and coordinating production seamlessly. Despite the decrease in Democratic votes for Senators, the high-tech infrastructure remains efficient, showcasing the resilience of technology in adapting to changes in the occupational landscape. 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 Democratic Senators in Nebraska and The number of production, planning, and expediting clerks in Nebraska. 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: Minimalism Cubism Symbolism Magic realism High-tech
ChatGPT: High-tech

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 Democratic Senators in Nebraska and The number of production, planning, and expediting clerks in Nebraska, in the following situation: As the Democrat votes for Senators in Nebraska decreased, the state experienced a ripple effect in the labor market. Due to the intricacies of political workforce dynamics, there was a surprising but substantial impact on the demand for production, planning, and expediting clerks. It appears that the bureaucratic shift led to a reevaluation of optimization processes, prompting a gradual phasing out of certain clerical positions. It's truly a testament to the interconnectedness of politics and production - a textbook case of how legislative preferences can unexpectedly shape the occupational landscape. Who would have thought that the ebb and flow of senatorial support could reach such granular levels of the workforce? It's a fascinating revelation that highlights the multifaceted nature of electoral influence!. Keep the description simple.
ChatGPT: In Nebraska, as Democratic votes for Senators decreased, offices and factories saw a decline in the demand for production, planning, and expediting clerks. This led to a reevaluation of staff needs and a gradual reduction in certain clerical positions, illustrating the unexpected link between political shifts and the occupational landscape.

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: [ High-tech ] and depicting this scene: In Nebraska, as Democratic votes for Senators decreased, offices and factories saw a decline in the demand for production, planning, and expediting clerks. This led to a reevaluation of staff needs and a gradual reduction in certain clerical positions, illustrating the unexpected link between political shifts and the occupational landscape. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image of a futuristic office building in Nebraska, with sophisticated robotic clerks processing data and coordinating production seamlessly. Despite the decrease in Democratic votes for Senators, the high-tech infrastructure remains efficient, showcasing the resilience of technology in adapting to changes in the occupational landscape.

*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 a decrease in Democrat votes for Senators in Nebraska caused The number of production, planning, and expediting clerks in Nebraska to decrease.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

The Ballot and the Bureau: A Correlation Between Democrat Votes for Senators in Nebraska and the Number of Production, Planning, and Expediting Clerks

The Journal of Political and Occupational Metrics

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 Democrat votes for Senators in Nebraska and The number of production, planning, and expediting clerks in Nebraska. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
"The Ballot and the Bureau: A Correlation Between Democrat Votes for Senators in Nebraska and the Number of Production, Planning, and Expediting Clerks"

[[ABSTRACT]]
In this groundbreaking study, we set out to explore the potential connection between political leanings and labor trends in the heartland state of Nebraska. By analyzing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we sought to unravel the enigmatic relationship between Democrat votes for Senators in the state and the employment figures of production, planning, and expediting clerks. Our findings revealed a remarkably high correlation coefficient of 0.9877034 with a p-value lower than the Nebraska winter temperatures. The data from 2003 to 2020 provided compelling evidence of a concurrent fluctuation in political preferences and workforce composition, pointing to a tantalizing liaison between the ballot box and the employee roster. While our study sheds light on this curious correlation, further investigation is warranted to uncover the underlying mechanisms at play. This research serves as a reminder that beneath the seemingly monotonous surface of labor statistics lies a trove of peculiar connections waiting to be unearthed, not unlike uncovering a hidden gem amidst stacks of bureaucratic paperwork.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The state of Nebraska, with its vast expanses of cornfields and the occasional sighting of a cornhusker, serves as an intriguing backdrop for our exploration into the relationship between political voting patterns and labor dynamics. While one might be forgiven for assuming that the only correlation in Nebraska is between the number of corn cobs and the level of corn consumption, our research aims to peel back the layers of this Midwestern mystery and reveal the unexpected ties between Democrat votes for Senators and the employment landscape of production, planning, and expediting clerks.
As we delve into this study, it is important to note that our pursuit of these connections is not driven solely by a desire to inject whimsy into the hallowed halls of academic research (although that is a delightful bonus). Rather, our endeavor is anchored in a quest to unearth the underlying forces that shape the ebb and flow of both political allegiances and labor composition in this diverse and industrious state. Nebraska, with its plains stretching farther than the eye can see, offers a canvas upon which patterns of political affiliation and labor roles intertwine in a manner reminiscent of a prime-time soap opera – with plot twists and dramatic turns, but hopefully with fewer commercial breaks.
The initial impetus for this investigation stemmed from a realization that there may be more to Nebraska's political landscape than meets the eye. While the Cornhusker State is renowned for its agricultural prowess, there appeared to be an unexplored narrative lurking in the statistical shadows. Much like a cunning detective in a mystery novel, we set out to scrutinize the Democrat votes for Senators, aiming to uncover whether these political leanings were mirrored by a curious parallel in the realm of production, planning, and expediting clerks – the unsung heroes of efficiency and organization, toiling away in the background like backstage crew members in a theatrical production.
With this proposal in mind, our study harnessed the formidable power of data analysis, employing a meticulous examination of figures from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics. Through this analytical lens, we sought to discern whether the political preferences of Nebraskan voters were mirrored by fluctuations in the workforce composition, akin to the synchronous movements of a pair of synchronized swimmers – albeit with less aquatic elegance and more paperwork.
The nebulous realm of statistics and political leanings may seem a world apart from the realm of production, planning, and expediting clerks, who navigate the intricacies of supply chains and operational logistics. However, as our findings unfolded like a carefully crafted cinematic plot twist, we were astounded to uncover a correlation coefficient that shimmered more brightly than a cornfield under the midday sun. With a correlation coefficient of 0.9877034, our data yielded a connection so robust that it could seemingly withstand the gusts of a Midwestern tornado – a metaphor that holds up until someone tries to test it in real life.
Our examination of the data from 2003 to 2020 illuminated a captivating dance between Democrat votes for Senators and the employment figures of production, planning, and expediting clerks. This intricate waltz between political ballots and occupational roles suggests that beneath the placid façade of labor statistics lies a hidden harmony of political proclivities and employment dynamics, not unlike discovering a harmonious blend of flavors in a hearty Midwestern casserole.
However, it is crucial to emphasize that while our findings tantalize and tease with the promise of correlation, they merely scratch the surface of a much deeper and undoubtedly more complex relationship. Like an intricately woven tapestry, this intricate connection between political preferences and labor roles beckons for further inquiry, inviting researchers to unravel the intricate threads that weave together the tapestry of Nebraskan society and employment practices. Our exploration serves as a reminder that beneath the veneer of bureaucratic categorization, there lie connections that defy conventional expectations, much like finding a unicorn in a corncob field – unexpected, but undeniably intriguing.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

To contextualize our investigation into the nexus of political voting behaviors and labor dynamics in Nebraska, we turn to a body of literature that seeks to illuminate the nuances of such seemingly disparate phenomena. Smith et al. (2015) conducted a comprehensive analysis of political affiliation in Midwestern states, shedding light on the multifaceted factors that underpin voters' decisions. While their work focused on a broad spectrum of political leanings, it laid the groundwork for our exploration of the specific case of Democrat votes for Senators in Nebraska and its potential ramifications on labor trends.

Expanding our purview, Doe's (2018) seminal work delved into the intricate web of labor economics, emphasizing the intricate dance between workforce composition and regional political landscapes. Through meticulous data analysis and theoretical modeling, Doe highlighted the interconnectedness of political dynamics and labor market shifts, providing a compelling backdrop for our study's focus on the Cornhusker State.

Jones (2019) contributed to our understanding of the influence of political sentiment on employment patterns, although her research primarily centered on urban areas. Nonetheless, the implications of her findings resonate with our investigation, prompting us to examine whether similar trends manifest in the distinct sociopolitical milieu of Nebraska.

Turning to the broader intellectual landscape, the works of renowned economists and sociologists provide invaluable insights into the intricate interplay of political leanings and labor dynamics. "Economic Forces and Political Alignments" (Rosenbaum, 2017) offers a macroscopic view of the symbiotic relationship between economic structures and political ideologies, serving as a theoretical scaffold for discerning the potential ramifications of political voting patterns on labor compositions in specific regions.

In the domain of more speculative literature, the fictitious narratives of "The Political Paradox" (Montgomery, 2020) and "Labor of Love" (Patterson, 2016) captivate readers with their imaginative musings on the enigmatic bonds between political allegiances and labor forces. While these works may not offer empirical substantiation, they serve as creative stimuli for contemplation, akin to the whimsical ponderings that occasionally infiltrate the realm of academic research.

Furthermore, our perusal of social media discourse revealed intriguing anecdotes and musings that alluded to the intersection of political sentiment and labor dynamics in Nebraska. A Twitter post by @CornhuskerInsights remarked on the uncanny resemblance between political campaign strategies and the logistical choreography of supply chain management, igniting a spark of curiosity that fueled our empirical inquiry. Similarly, a Reddit thread titled "Blue Ballots, White Collars: Unraveling Nebraska's Enigmatic Connection" engendered spirited discussions on the potential correlations between Democrat votes for Senators and the occupational tapestry of the Cornhusker State.

In synthesizing these diverse sources, our literature review underscores the dearth of empirical investigations into the entwined narratives of political voting behaviors and labor compositions in Nebraska. By drawing on a multidisciplinary array of scholarly and speculative works, we aim to fortify our study's foundation with nuanced perspectives and imaginative provocations that propel our pursuit of understanding this intriguing confluence.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Nebraska and The number of production, planning, and expediting clerks in Nebraska. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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]]
"The Ballot and the Bureau: A Correlation Between Democrat Votes for Senators in Nebraska and the Number of Production, Planning, and Expediting Clerks"

[[ABSTRACT]]
In this groundbreaking study, we set out to explore the potential connection between political leanings and labor trends in the heartland state of Nebraska. By analyzing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we sought to unravel the enigmatic relationship between Democrat votes for Senators in the state and the employment figures of production, planning, and expediting clerks. Our findings revealed a remarkably high correlation coefficient of 0.9877034 with a p-value lower than the Nebraska winter temperatures. The data from 2003 to 2020 provided compelling evidence of a concurrent fluctuation in political preferences and workforce composition, pointing to a tantalizing liaison between the ballot box and the employee roster. While our study sheds light on this curious correlation, further investigation is warranted to uncover the underlying mechanisms at play. This research serves as a reminder that beneath the seemingly monotonous surface of labor statistics lies a trove of peculiar connections waiting to be unearthed, not unlike uncovering a hidden gem amidst stacks of bureaucratic paperwork.

[[INTRODUCTION]]
The state of Nebraska, with its vast expanses of cornfields and the occasional sighting of a cornhusker, serves as an intriguing backdrop for our exploration into the relationship between political voting patterns and labor dynamics. While one might be forgiven for assuming that the only correlation in Nebraska is between the number of corn cobs and the level of corn consumption, our research aims to peel back the layers of this Midwestern mystery and reveal the unexpected ties between Democrat votes for Senators and the employment landscape of production, planning, and expediting clerks.
As we delve into this study, it is important to note that our pursuit of these connections is not driven solely by a desire to inject whimsy into the hallowed halls of academic research (although that is a delightful bonus). Rather, our endeavor is anchored in a quest to unearth the underlying forces that shape the ebb and flow of both political allegiances and labor composition in this diverse and industrious state. Nebraska, with its plains stretching farther than the eye can see, offers a canvas upon which patterns of political affiliation and labor roles intertwine in a manner reminiscent of a prime-time soap opera – with plot twists and dramatic turns, but hopefully with fewer commercial breaks.
The initial impetus for this investigation stemmed from a realization that there may be more to Nebraska's political landscape than meets the eye. While the Cornhusker State is renowned for its agricultural prowess, there appeared to be an unexplored narrative lurking in the statistical shadows. Much like a cunning detective in a mystery novel, we set out to scrutinize the Democrat votes for Senators, aiming to uncover whether these political leanings were mirrored by a curious parallel in the realm of production, planning, and expediting clerks – the unsung heroes of efficiency and organization, toiling away in the background like backstage crew members in a theatrical production.
With this proposal in mind, our study harnessed the formidable power of data analysis, employing a meticulous examination of figures from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics. Through this analytical lens, we sought to discern whether the political preferences of Nebraskan voters were mirrored by fluctuations in the workforce composition, akin to the synchronous movements of a pair of synchronized swimmers – albeit with less aquatic elegance and more paperwork.
The nebulous realm of statistics and political leanings may seem a world apart from the realm of production, planning, and expediting clerks, who navigate the intricacies of supply chains and operational logistics. However, as our findings unfolded like a carefully crafted cinematic plot twist, we were astounded to uncover a correlation coefficient that shimmered more brightly than a cornfield under the midday sun. With a correlation coefficient of 0.9877034, our data yielded a connection so robust that it could seemingly withstand the gusts of a Midwestern tornado – a metaphor that holds up until someone tries to test it in real life.
Our examination of the data from 2003 to 2020 illuminated a captivating dance between Democrat votes for Senators and the employment figures of production, planning, and expediting clerks. This intricate waltz between political ballots and occupational roles suggests that beneath the placid façade of labor statistics lies a hidden harmony of political proclivities and employment dynamics, not unlike discovering a harmonious blend of flavors in a hearty Midwestern casserole.
However, it is crucial to emphasize that while our findings tantalize and tease with the promise of correlation, they merely scratch the surface of a much deeper and undoubtedly more complex relationship. Like an intricately woven tapestry, this intricate connection between political preferences and labor roles beckons for further inquiry, inviting researchers to unravel the intricate threads that weave together the tapestry of Nebraskan society and employment practices. Our exploration serves as a reminder that beneath the veneer of bureaucratic categorization, there lie connections that defy conventional expectations, much like finding a unicorn in a corncob field – unexpected, but undeniably intriguing.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To reveal the mysterious bond between Democrat votes for Senators in Nebraska and the number of production, planning, and expediting clerks, we journeyed into the labyrinth of research methodology with the eagerness of explorers venturing into uncharted territories, armed with data and an unwavering determination to illuminate the shadows of correlation. Our methodology, while devoid of compasses and machetes, relied on the strategic selection and analysis of data acquired from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, akin to a flavorful stew prepared with the choicest ingredients from diverse culinary traditions.

First and foremost, our research approach harnessed the power of quantitative analysis, akin to scrutinizing the intricate patterns of a tapestry to discern the underlying motifs. We collated and meticulously examined data spanning the years 2003 to 2020, a temporal expanse akin to the rise and fall of empires in the annals of history, albeit with a far more bureaucratic flavor. The utilization of data from this extensive time frame allowed us to capture the undulating currents of political preferences and labor figures, akin to observing the ebbs and flows of a Midwestern river meandering through the heartland.

The data obtained from the MIT Election Data and Science Lab and Harvard Dataverse provided us with a glimpse into the complex kaleidoscope of political voting patterns, offering a panoramic view of Democrat votes for Senators in Nebraska. In parallel, our endeavor encompassed delving into the terrain of labor statistics, drawing upon the Bureau of Labor Statistics to extract employment figures for production, planning, and expediting clerks - the unsung heroes of organizational efficiency, not unlike the tireless conductors orchestrating an intricate symphony of operations.

Furthermore, we engaged in the art of statistical analysis, akin to conducting a symphony with precision and finesse, to unravel the potential interconnectedness between political ballots and the composition of the workforce. Employing sophisticated statistical measures such as correlation analysis, we sought to unveil the clandestine dance between Democrat votes for Senators and the employment figures of production, planning, and expediting clerks, an exploration akin to unraveling the intertwined plotlines of an enigmatic novel.

As we ventured deeper into the statistical labyrinth, our exhaustive exploration culminated in the computation of a correlation coefficient, signaling the strength and direction of the relationship between our variables of interest. This coefficient, akin to the guiding star of our expedition, illuminated the path towards our compelling findings, establishing a connection so robust that it beckoned forth an exclamation not unlike the discovery of a hidden treasure trove.

In summation, our methodology employed a meticulous synthesis of data from diverse sources, a rigorous application of statistical techniques, and a fervent dedication to unraveling the enigmatic relationship between political ballots and labor compositions. While our approach refrained from the inclusion of jungle expeditions and nautical adventures, it nonetheless led to the unveiling of a compelling correlation between Democrat votes for Senators in Nebraska and the employment figures of production, planning, and expediting clerks - a revelation not unlike stumbling upon a surprise twist in the plot of an enthralling mystery novel.

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 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 Democrat votes for Senators in Nebraska and The number of production, planning, and expediting clerks in Nebraska. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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 0.9877034, r-squared of 0.9755581, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"The Ballot and the Bureau: A Correlation Between Democrat Votes for Senators in Nebraska and the Number of Production, Planning, and Expediting Clerks"

[[ABSTRACT]]
In this groundbreaking study, we set out to explore the potential connection between political leanings and labor trends in the heartland state of Nebraska. By analyzing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we sought to unravel the enigmatic relationship between Democrat votes for Senators in the state and the employment figures of production, planning, and expediting clerks. Our findings revealed a remarkably high correlation coefficient of 0.9877034 with a p-value lower than the Nebraska winter temperatures. The data from 2003 to 2020 provided compelling evidence of a concurrent fluctuation in political preferences and workforce composition, pointing to a tantalizing liaison between the ballot box and the employee roster. While our study sheds light on this curious correlation, further investigation is warranted to uncover the underlying mechanisms at play. This research serves as a reminder that beneath the seemingly monotonous surface of labor statistics lies a trove of peculiar connections waiting to be unearthed, not unlike uncovering a hidden gem amidst stacks of bureaucratic paperwork.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The state of Nebraska, with its vast expanses of cornfields and the occasional sighting of a cornhusker, serves as an intriguing backdrop for our exploration into the relationship between political voting patterns and labor dynamics. While one might be forgiven for assuming that the only correlation in Nebraska is between the number of corn cobs and the level of corn consumption, our research aims to peel back the layers of this Midwestern mystery and reveal the unexpected ties between Democrat votes for Senators and the employment landscape of production, planning, and expediting clerks.
As we delve into this study, it is important to note that our pursuit of these connections is not driven solely by a desire to inject whimsy into the hallowed halls of academic research (although that is a delightful bonus). Rather, our endeavor is anchored in a quest to unearth the underlying forces that shape the ebb and flow of both political allegiances and labor composition in this diverse and industrious state. Nebraska, with its plains stretching farther than the eye can see, offers a canvas upon which patterns of political affiliation and labor roles intertwine in a manner reminiscent of a prime-time soap opera – with plot twists and dramatic turns, but hopefully with fewer commercial breaks.
The initial impetus for this investigation stemmed from a realization that there may be more to Nebraska's political landscape than meets the eye. While the Cornhusker State is renowned for its agricultural prowess, there appeared to be an unexplored narrative lurking in the statistical shadows. Much like a cunning detective in a mystery novel, we set out to scrutinize the Democrat votes for Senators, aiming to uncover whether these political leanings were mirrored by a curious parallel in the realm of production, planning, and expediting clerks – the unsung heroes of efficiency and organization, toiling away in the background like backstage crew members in a theatrical production.
With this proposal in mind, our study harnessed the formidable power of data analysis, employing a meticulous examination of figures from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics. Through this analytical lens, we sought to discern whether the political preferences of Nebraskan voters were mirrored by fluctuations in the workforce composition, akin to the synchronous movements of a pair of synchronized swimmers – albeit with less aquatic elegance and more paperwork.
The nebulous realm of statistics and political leanings may seem a world apart from the realm of production, planning, and expediting clerks, who navigate the intricacies of supply chains and operational logistics. However, as our findings unfolded like a carefully crafted cinematic plot twist, we were astounded to uncover a correlation coefficient that shimmered more brightly than a cornfield under the midday sun. With a correlation coefficient of 0.9877034, our data yielded a connection so robust that it could seemingly withstand the gusts of a Midwestern tornado – a metaphor that holds up until someone tries to test it in real life.
Our examination of the data from 2003 to 2020 illuminated a captivating dance between Democrat votes for Senators and the employment figures of production, planning, and expediting clerks. This intricate waltz between political ballots and occupational roles suggests that beneath the placid façade of labor statistics lies a hidden harmony of political proclivities and employment dynamics, not unlike discovering a harmonious blend of flavors in a hearty Midwestern casserole.
However, it is crucial to emphasize that while our findings tantalize and tease with the promise of correlation, they merely scratch the surface of a much deeper and undoubtedly more complex relationship. Like an intricately woven tapestry, this intricate connection between political preferences and labor roles beckons for further inquiry, inviting researchers to unravel the intricate threads that weave together the tapestry of Nebraskan society and employment practices. Our exploration serves as a reminder that beneath the veneer of bureaucratic categorization, there lie connections that defy conventional expectations, much like finding a unicorn in a corncob field – unexpected, but undeniably intriguing.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis revealed a striking correlation between Democrat votes for Senators in Nebraska and the number of production, planning, and expediting clerks. The correlation coefficient of 0.9877034 points to a relationship that is stronger than the gravitational pull of a black hole, indicating a robust association between these seemingly disparate variables. The r-squared value of 0.9755581 further reinforces the solidity of this connection, akin to the unyielding strength of a Nebraskan steer.

As depicted in Figure 1, the scatterplot unequivocally illustrates the strong positive correlation between Democrat votes for Senators and the employment figures of production, planning, and expediting clerks. The data points align so neatly that they evoke images of a well-organized supply chain, speaking volumes about the synchronicity of these two domains.

The p-value, exceeding meteorological significance levels, underscores the statistical significance of this correlation, bearing evidence that is as substantial as a Nebraska corn harvest. This level of significance leaves little room for doubt, akin to discovering a needle in a cornfield – highly improbable, yet undeniably compelling.

The findings from this in-depth analysis not only offer a lens through which to understand the interplay of political preferences and labor dynamics in Nebraska but also serve as a poignant reminder that behind every humdrum dataset lies a story waiting to be uncovered, not unlike finding a captivating narrative hidden within a laundry list.

The remarkable correlation unearthed in this study opens the door to further explorations and inquiries into the complex web of interconnectedness between political choices and labor compositions. It beckons for continued scrutiny, much like the allure of an enigmatic puzzle that begs to be solved, promising insights that extend far beyond the parameters of this research and into the heart of Nebraska's intricate social and economic tapestry.

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 Democrat votes for Senators in Nebraska and The number of production, planning, and expediting clerks in Nebraska. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
"The Ballot and the Bureau: A Correlation Between Democrat Votes for Senators in Nebraska and the Number of Production, Planning, and Expediting Clerks"

[[ABSTRACT]]
In this groundbreaking study, we set out to explore the potential connection between political leanings and labor trends in the heartland state of Nebraska. By analyzing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we sought to unravel the enigmatic relationship between Democrat votes for Senators in the state and the employment figures of production, planning, and expediting clerks. Our findings revealed a remarkably high correlation coefficient of 0.9877034 with a p-value lower than the Nebraska winter temperatures. The data from 2003 to 2020 provided compelling evidence of a concurrent fluctuation in political preferences and workforce composition, pointing to a tantalizing liaison between the ballot box and the employee roster. While our study sheds light on this curious correlation, further investigation is warranted to uncover the underlying mechanisms at play. This research serves as a reminder that beneath the seemingly monotonous surface of labor statistics lies a trove of peculiar connections waiting to be unearthed, not unlike uncovering a hidden gem amidst stacks of bureaucratic paperwork.

[[LITERATURE REVIEW]]
To contextualize our investigation into the nexus of political voting behaviors and labor dynamics in Nebraska, we turn to a body of literature that seeks to illuminate the nuances of such seemingly disparate phenomena. Smith et al. (2015) conducted a comprehensive analysis of political affiliation in Midwestern states, shedding light on the multifaceted factors that underpin voters' decisions. While their work focused on a broad spectrum of political leanings, it laid the groundwork for our exploration of the specific case of Democrat votes for Senators in Nebraska and its potential ramifications on labor trends.
Expanding our purview, Doe's (2018) seminal work delved into the intricate web of labor economics, emphasizing the intricate dance between workforce composition and regional political landscapes. Through meticulous data analysis and theoretical modeling, Doe highlighted the interconnectedness of political dynamics and labor market shifts, providing a compelling backdrop for our study's focus on the Cornhusker State.
Jones (2019) contributed to our understanding of the influence of political sentiment on employment patterns, although her research primarily centered on urban areas. Nonetheless, the implications of her findings resonate with our investigation, prompting us to examine whether similar trends manifest in the distinct sociopolitical milieu of Nebraska.
Turning to the broader intellectual landscape, the works of renowned economists and sociologists provide invaluable insights into the intricate interplay of political leanings and labor dynamics. "Economic Forces and Political Alignments" (Rosenbaum, 2017) offers a macroscopic view of the symbiotic relationship between economic structures and political ideologies, serving as a theoretical scaffold for discerning the potential ramifications of political voting patterns on labor compositions in specific regions.
In the domain of more speculative literature, the fictitious narratives of "The Political Paradox" (Montgomery, 2020) and "Labor of Love" (Patterson, 2016) captivate readers with their imaginative musings on the enigmatic bonds between political allegiances and labor forces. While these works may not offer empirical substantiation, they serve as creative stimuli for contemplation, akin to the whimsical ponderings that occasionally infiltrate the realm of academic research.
Furthermore, our perusal of social media discourse revealed intriguing anecdotes and musings that alluded to the intersection of political sentiment and labor dynamics in Nebraska. A Twitter post by @CornhuskerInsights remarked on the uncanny resemblance between political campaign strategies and the logistical choreography of supply chain management, igniting a spark of curiosity that fueled our empirical inquiry. Similarly, a Reddit thread titled "Blue Ballots, White Collars: Unraveling Nebraska's Enigmatic Connection" engendered spirited discussions on the potential correlations between Democrat votes for Senators and the occupational tapestry of the Cornhusker State.
In synthesizing these diverse sources, our literature review underscores the dearth of empirical investigations into the entwined narratives of political voting behaviors and labor compositions in Nebraska. By drawing on a multidisciplinary array of scholarly and speculative works, we aim to fortify our study's foundation with nuanced perspectives and imaginative provocations that propel our pursuit of understanding this intriguing confluence.

[[RESULTS]]
The statistical analysis revealed a striking correlation between Democrat votes for Senators in Nebraska and the number of production, planning, and expediting clerks. The correlation coefficient of 0.9877034 points to a relationship that is stronger than the gravitational pull of a black hole, indicating a robust association between these seemingly disparate variables. The r-squared value of 0.9755581 further reinforces the solidity of this connection, akin to the unyielding strength of a Nebraskan steer.
As depicted in Figure 1, the scatterplot unequivocally illustrates the strong positive correlation between Democrat votes for Senators and the employment figures of production, planning, and expediting clerks. The data points align so neatly that they evoke images of a well-organized supply chain, speaking volumes about the synchronicity of these two domains.
The p-value, exceeding meteorological significance levels, underscores the statistical significance of this correlation, bearing evidence that is as substantial as a Nebraska corn harvest. This level of significance leaves little room for doubt, akin to discovering a needle in a cornfield – highly improbable, yet undeniably compelling.
The findings from this in-depth analysis not only offer a lens through which to understand the interplay of political preferences and labor dynamics in Nebraska but also serve as a poignant reminder that behind every humdrum dataset lies a story waiting to be uncovered, not unlike finding a captivating narrative hidden within a laundry list.
The remarkable correlation unearthed in this study opens the door to further explorations and inquiries into the complex web of interconnectedness between political choices and labor compositions. It beckons for continued scrutiny, much like the allure of an enigmatic puzzle that begs to be solved, promising insights that extend far beyond the parameters of this research and into the heart of Nebraska's intricate social and economic tapestry.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our investigation have provided compelling evidence to substantiate the earlier scholarly work and speculative narratives that we humorously, albeit earnestly, referenced in the literature review. It is rather serendipitous that our findings lend credence to the imaginative musings contained in such diverse sources, which on the surface may appear as lighthearted distractions but, in reality, offer glimpses of insight into the peculiar nexus we have brought to light.

Firstly, the strong correlation coefficient alludes to a robust connection, signifying that the fluctuation in Democrat votes for Senators in Nebraska is closely intertwined with the ebb and flow of production, planning, and expediting clerk employment figures. This alignment is not unlike the unexpected harmony found in an offbeat musical composition - an unlikely ensemble that, when aligned, produces a harmonious melody in the form of statistical significance.

The r-squared value further reinforces the solidity of this relationship, effectively behaving as the metaphorical foundation of a sturdy Midwestern barn, lending stability to our findings. It is a testament to the coherence and predictability of this correlation, much like the dependability of a perennial Cornhusker harvest.

The p-value, akin to a meteorological anomaly in the Great Plains, stands as a testament to the statistical significance of our observed correlation. Its magnitude mirrors the resilience and determination of a Nebraska corn harvest, leaving little room for doubt and upholding the weight of our findings with the gravity of an unyielding plow in the fields of empirical inquiry.

The scatterplot, with its neatly aligned data points, paints a picture not unlike the careful choreography of a well-oiled supply chain, embodying the synchronicity of these seemingly disparate variables. The interplay between political voting behaviors and occupational arrangements in Nebraska appears akin to a logistical dance, where the movements of one entity elegantly echo the rhythms of the other, much like the intricate steps of a lively polka at a Midwestern hoedown.

Perhaps, to borrow from the often-overlooked creative works we playfully touched upon, our investigation has unraveled a storyline that resonates with similar murmurings within the realm of social media discourse. The uncanny resemblance between political campaign strategies and the logistical choreography of supply chain management, whimsically alluded to in a tweet, now seems to carry a weight of empirical substantiation, much like finding a pearl of wisdom in a sea of social media ephemera.

In synthesizing these elements, our findings offer a cornucopia of insights into the enigmatic correlative tapestry of political choices and labor compositions, prompting further exploration and inquiry beyond the confines of this study. With the allure of this enigmatic puzzle, we are beckoned to delve deeper, much like uncovering a riveting narrative hidden within a mundane task list.

The entwined narratives of political voting behaviors and labor compositions in Nebraska, once seen as separate threads in the fabric of sociopolitical and economic discourse, have disclosed a pattern of interconnection that awaits further illustration and understanding. Our study, though a single brushstroke in the canvas of empirical inquiry, has set the stage for compelling continuations, not unlike a spark of curiosity igniting the imaginations of scholars and researchers eager to unravel the enigmatic connections woven into the fabric of Cornhusker society and economy.

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 Democrat votes for Senators in Nebraska and The number of production, planning, and expediting clerks in Nebraska. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"The Ballot and the Bureau: A Correlation Between Democrat Votes for Senators in Nebraska and the Number of Production, Planning, and Expediting Clerks"

[[ABSTRACT]]
In this groundbreaking study, we set out to explore the potential connection between political leanings and labor trends in the heartland state of Nebraska. By analyzing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we sought to unravel the enigmatic relationship between Democrat votes for Senators in the state and the employment figures of production, planning, and expediting clerks. Our findings revealed a remarkably high correlation coefficient of 0.9877034 with a p-value lower than the Nebraska winter temperatures. The data from 2003 to 2020 provided compelling evidence of a concurrent fluctuation in political preferences and workforce composition, pointing to a tantalizing liaison between the ballot box and the employee roster. While our study sheds light on this curious correlation, further investigation is warranted to uncover the underlying mechanisms at play. This research serves as a reminder that beneath the seemingly monotonous surface of labor statistics lies a trove of peculiar connections waiting to be unearthed, not unlike uncovering a hidden gem amidst stacks of bureaucratic paperwork.

[[INTRDUCTION]]
The state of Nebraska, with its vast expanses of cornfields and the occasional sighting of a cornhusker, serves as an intriguing backdrop for our exploration into the relationship between political voting patterns and labor dynamics. While one might be forgiven for assuming that the only correlation in Nebraska is between the number of corn cobs and the level of corn consumption, our research aims to peel back the layers of this Midwestern mystery and reveal the unexpected ties between Democrat votes for Senators and the employment landscape of production, planning, and expediting clerks.
As we delve into this study, it is important to note that our pursuit of these connections is not driven solely by a desire to inject whimsy into the hallowed halls of academic research (although that is a delightful bonus). Rather, our endeavor is anchored in a quest to unearth the underlying forces that shape the ebb and flow of both political allegiances and labor composition in this diverse and industrious state. Nebraska, with its plains stretching farther than the eye can see, offers a canvas upon which patterns of political affiliation and labor roles intertwine in a manner reminiscent of a prime-time soap opera – with plot twists and dramatic turns, but hopefully with fewer commercial breaks.
The initial impetus for this investigation stemmed from a realization that there may be more to Nebraska's political landscape than meets the eye. While the Cornhusker State is renowned for its agricultural prowess, there appeared to be an unexplored narrative lurking in the statistical shadows. Much like a cunning detective in a mystery novel, we set out to scrutinize the Democrat votes for Senators, aiming to uncover whether these political leanings were mirrored by a curious parallel in the realm of production, planning, and expediting clerks – the unsung heroes of efficiency and organization, toiling away in the background like backstage crew members in a theatrical production.
With this proposal in mind, our study harnessed the formidable power of data analysis, employing a meticulous examination of figures from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics. Through this analytical lens, we sought to discern whether the political preferences of Nebraskan voters were mirrored by fluctuations in the workforce composition, akin to the synchronous movements of a pair of synchronized swimmers – albeit with less aquatic elegance and more paperwork.
The nebulous realm of statistics and political leanings may seem a world apart from the realm of production, planning, and expediting clerks, who navigate the intricacies of supply chains and operational logistics. However, as our findings unfolded like a carefully crafted cinematic plot twist, we were astounded to uncover a correlation coefficient that shimmered more brightly than a cornfield under the midday sun. With a correlation coefficient of 0.9877034, our data yielded a connection so robust that it could seemingly withstand the gusts of a Midwestern tornado – a metaphor that holds up until someone tries to test it in real life.
Our examination of the data from 2003 to 2020 illuminated a captivating dance between Democrat votes for Senators and the employment figures of production, planning, and expediting clerks. This intricate waltz between political ballots and occupational roles suggests that beneath the placid façade of labor statistics lies a hidden harmony of political proclivities and employment dynamics, not unlike discovering a harmonious blend of flavors in a hearty Midwestern casserole.
However, it is crucial to emphasize that while our findings tantalize and tease with the promise of correlation, they merely scratch the surface of a much deeper and undoubtedly more complex relationship. Like an intricately woven tapestry, this intricate connection between political preferences and labor roles beckons for further inquiry, inviting researchers to unravel the intricate threads that weave together the tapestry of Nebraskan society and employment practices. Our exploration serves as a reminder that beneath the veneer of bureaucratic categorization, there lie connections that defy conventional expectations, much like finding a unicorn in a corncob field – unexpected, but undeniably intriguing.

[[RESULTS]]
The statistical analysis revealed a striking correlation between Democrat votes for Senators in Nebraska and the number of production, planning, and expediting clerks. The correlation coefficient of 0.9877034 points to a relationship that is stronger than the gravitational pull of a black hole, indicating a robust association between these seemingly disparate variables. The r-squared value of 0.9755581 further reinforces the solidity of this connection, akin to the unyielding strength of a Nebraskan steer.
As depicted in Figure 1, the scatterplot unequivocally illustrates the strong positive correlation between Democrat votes for Senators and the employment figures of production, planning, and expediting clerks. The data points align so neatly that they evoke images of a well-organized supply chain, speaking volumes about the synchronicity of these two domains.
The p-value, exceeding meteorological significance levels, underscores the statistical significance of this correlation, bearing evidence that is as substantial as a Nebraska corn harvest. This level of significance leaves little room for doubt, akin to discovering a needle in a cornfield – highly improbable, yet undeniably compelling.
The findings from this in-depth analysis not only offer a lens through which to understand the interplay of political preferences and labor dynamics in Nebraska but also serve as a poignant reminder that behind every humdrum dataset lies a story waiting to be uncovered, not unlike finding a captivating narrative hidden within a laundry list.
The remarkable correlation unearthed in this study opens the door to further explorations and inquiries into the complex web of interconnectedness between political choices and labor compositions. It beckons for continued scrutiny, much like the allure of an enigmatic puzzle that begs to be solved, promising insights that extend far beyond the parameters of this research and into the heart of Nebraska's intricate social and economic tapestry.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has delved into the captivating correlation between Democrat votes for Senators in Nebraska and the number of production, planning, and expediting clerks, revealing a connection as sturdy as a barn in a Nebraskan storm. The robust correlation coefficient, stronger than a linebacker's grip on a football, underscores the compelling liaison between political leanings and the workforce landscape. The findings not only shed light on the intertwined nature of political preferences and labor dynamics but also serve as a reminder that the seemingly mundane realm of labor statistics harbors hidden marvels, not unlike discovering a diamond in a haystack of data.

While our research tantalizingly uncovers this correlation, it merely scratches the surface of a relationship as complex as untangling Christmas lights. Engaging further in this inquiry is, therefore, as unnecessary as bringing a snow blower to a cornfield. The findings of this study provide a resounding conclusion – there's no need to dig deeper into this already enriching field of study. As the curtains close on this curious correlation, let us take with us the lesson that beneath the veil of mundanity lies a trove of interconnectedness waiting to be uncovered – much like discovering a dollar bill in a pair of old jeans.

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 The Ballot and the Bureau: A Correlation Between Democrat Votes for Senators in Nebraska and the Number of Production, Planning, and Expediting Clerks. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Political and Occupational Metrics

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 The Ballot and the Bureau: A Correlation Between Democrat Votes for Senators in Nebraska and the Number of Production, Planning, and Expediting Clerks. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Advanced Research in Social Sciences and Data 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 The Ballot and the Bureau: A Correlation Between Democrat Votes for Senators in Nebraska and the Number of Production, Planning, and Expediting Clerks with an abstract of In this groundbreaking study, we set out to explore the potential connection between political leanings and labor trends in the heartland state of Nebraska. By analyzing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, we sought to unravel the enigmatic relationship between Democrat votes for Senators in the state and the employment figures of production, planning, and expediting clerks. Our findings revealed a remarkably high correlation coefficient of 0.9877034 with a p-value lower than the Nebraska winter temperatures. The data from 2003 to 2020 provided compelling evidence of a concurrent fluctuation in political preferences and workforce composition, pointing to a tantalizing liaison between the ballot box and the employee roster. While our study sheds light on this curious correlation, further investigation is warranted to uncover the underlying mechanisms at play. This research serves as a reminder that beneath the seemingly monotonous surface of labor statistics lies a trove of peculiar connections waiting to be unearthed, not unlike uncovering a hidden gem amidst stacks of bureaucratic paperwork.

ChatGPT:

Nebraska Senator Democrat votes correlation, production planning expediting clerks Nebraska, political leanings labor trends Nebraska, MIT Election Data Science Lab Nebraska voting, Harvard Dataverse Nebraska labor statistics, Bureau of Labor Statistics Nebraska, workforce composition Nebraska, political preferences workforce Nebraska

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

The number of production, planning, and expediting clerks in Nebraska
Detailed data title: BLS estimate of production, planning, and expediting clerks in Nebraska
Source: Bureau of Larbor Statistics
See what else correlates with The number of production, planning, and expediting clerks in Nebraska

Correlation r = 0.9877034 (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 = 0.9755581 (Coefficient of determination)
This means 97.6% of the change in the one variable (i.e., The number of production, planning, and expediting clerks in Nebraska) is predictable based on the change in the other (i.e., Votes for Democratic Senators in Nebraska) over the 6 years from 2003 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00023.^Show 0.0002258781451876155000000000
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 0.99 in 0.023% of random cases. Said differently, if you correlated 4,427 random variables^Note Which I absolutely did.
with the same 5 degrees of freedom, ^Note 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.

[ 0.89, 1 ] 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.

	2006	2008	2012	2014	2018	2020
Votes for Democratic Senators in Nebraska (Percentage of votes)	63.8828	40.057	42.2256	31.4854	38.6212	24.4288
The number of production, planning, and expediting clerks in Nebraska (Laborers)	2400	1920	1860	1580	1840	1400

Why this works

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.
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.
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. ^{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([63.8828,40.057,42.2256,31.4854,38.6212,24.4288,])
array_2 = np.array([2400,1920,1860,1580,1840,1400,])
array_1_name = "Votes for Democratic Senators in Nebraska"
array_2_name = "The number of production, planning, and expediting clerks in Nebraska"

# 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 Votes for Democratic Senators in Nebraska
Line chart for only The number of production, planning, and expediting clerks in Nebraska
AI-generated correlation image
The spurious research paper: The Ballot and the Bureau: A Correlation Between Democrat Votes for Senators in Nebraska and the Number of Production, Planning, and Expediting Clerks

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Correlation ID: 5304 · Black Variable ID: 26419 · Red Variable ID: 11007


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