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Spurious correlation #4,763 · 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 Alaska and the second variable is The number of ticket agents in Alaska.  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 the Democrat votes for Senators in Alaska soared, there was a huge push for change in the state. This led to a surge in demand for political rallies and events, creating the need for more ticket agents to handle the influx of attendees. You could say the political climate really "ticketed" the growth of this profession in Alaska!

Model: dalle-3
Prompt: [ Cute 2D animation ] Using DALL·E-3, create an image of downtown Juneau, Alaska, bustling with vibrant energy. Capture a lively scene outside the Capitol building, where a large crowd adorned with blue "Vote Democrat" badges is joyously celebrating the increase in Democrat votes for Senators. The crowd exudes a sense of unity and excitement. Illustrate the ticket office of the Alaska Convention Center, depicting buzzing activity as new employees are trained to handle the surge in demand for political rallies and events. Show the line of people waiting to purchase tickets spilling out onto the sidewalk, portraying the growth of the ticket agent profession in response to the changing political climate. Emphasize the jubilant atmosphere while keeping the visual depiction simple and colorful. 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: Democrat votes for Senators in Alaska and The number of ticket agents in Alaska. 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: A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Cute 2D animation Oragami Cute 2D animation 3D Pixar Style
ChatGPT: Cute 2D animation

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 Democrat votes for Senators in Alaska and The number of ticket agents in Alaska, in the following situation: As the Democrat votes for Senators in Alaska soared, there was a huge push for change in the state. This led to a surge in demand for political rallies and events, creating the need for more ticket agents to handle the influx of attendees. You could say the political climate really "ticketed" the growth of this profession in Alaska!. Keep the description simple.
ChatGPT: In downtown Juneau, the hub of political activity in Alaska, a large crowd of people sporting blue "Vote Democrat" badges gathered outside the Capitol building, celebrating the increase in Democrat votes for Senators. Nearby, the ticket office of the Alaska Convention Center buzzed with activity as new employees were being trained to handle the surge in demand for political rallies and events. The line of people waiting to purchase tickets spilled out onto the sidewalk, reflecting the growth of the ticket agent profession in response to the changing political climate.

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: [ Cute 2D animation ] and depicting this scene: In downtown Juneau, the hub of political activity in Alaska, a large crowd of people sporting blue "Vote Democrat" badges gathered outside the Capitol building, celebrating the increase in Democrat votes for Senators. Nearby, the ticket office of the Alaska Convention Center buzzed with activity as new employees were being trained to handle the surge in demand for political rallies and events. The line of people waiting to purchase tickets spilled out onto the sidewalk, reflecting the growth of the ticket agent profession in response to the changing political climate. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Cute 2D animation ] Using DALL·E-3, create an image of downtown Juneau, Alaska, bustling with vibrant energy. Capture a lively scene outside the Capitol building, where a large crowd adorned with blue "Vote Democrat" badges is joyously celebrating the increase in Democrat votes for Senators. The crowd exudes a sense of unity and excitement. Illustrate the ticket office of the Alaska Convention Center, depicting buzzing activity as new employees are trained to handle the surge in demand for political rallies and events. Show the line of people waiting to purchase tickets spilling out onto the sidewalk, portraying the growth of the ticket agent profession in response to the changing political climate. Emphasize the jubilant atmosphere while keeping the visual depiction simple and colorful.

*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 increases in Democrat votes for Senators in Alaska positively influenced The number of ticket agents in Alaska. Include one good pun.

AI academic paper

(Because p < 0.01)
The Alaska Ballot and Ticket Tally: A Correlation Between Democrat Votes for Senators and Ticket Agents

The Journal of Political Paradoxes

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 dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Democrat votes for Senators in Alaska and The number of ticket agents in Alaska. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Rhyme words in the title.

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 0.9226673 and p < 0.01 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]]
The Alaska Ballot and Ticket Tally: A Correlation Between Democrat Votes for Senators and Ticket Agents

[[ABSTRACT]]
This paper investigates the relationship between Democrat votes for Senators in the state of Alaska and the number of ticket agents employed in the same region. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, our research team delved into this unconventional and whimsical inquiry. Employing rigorous statistical methods, including calculating a correlation coefficient of 0.9226673 and p < 0.01 for the time period spanning from 2003 to 2020, our findings bring to light a surprising yet compelling connection. As we delve deeper into this correlation, we uncover a unique interplay between political preference and the labor force in the Last Frontier. While the results may seem far-fetched, they speak volumes about the interwoven fabric of political representation and workforce dynamics in the Alaskan context. We invite readers to embark on this peculiar yet insightful journey, replete with unexpected twists and turns, as we unravel the curious case of Democrat votes and ticket agents in the land of glaciers and midnight sun.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Democrat votes for Senators in Alaska and The number of ticket agents in Alaska. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
The Alaska Ballot and Ticket Tally: A Correlation Between Democrat Votes for Senators and Ticket Agents

[[ABSTRACT]]
This paper investigates the relationship between Democrat votes for Senators in the state of Alaska and the number of ticket agents employed in the same region. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, our research team delved into this unconventional and whimsical inquiry. Employing rigorous statistical methods, including calculating a correlation coefficient of 0.9226673 and p < 0.01 for the time period spanning from 2003 to 2020, our findings bring to light a surprising yet compelling connection. As we delve deeper into this correlation, we uncover a unique interplay between political preference and the labor force in the Last Frontier. While the results may seem far-fetched, they speak volumes about the interwoven fabric of political representation and workforce dynamics in the Alaskan context. We invite readers to embark on this peculiar yet insightful journey, replete with unexpected twists and turns, as we unravel the curious case of Democrat votes and ticket agents in the land of glaciers and midnight sun.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The intersection of politics and economics has long been a subject of scholarly fascination, yielding insights that often defy conventional expectations. As researchers, it is our duty to examine patterns and correlations that may initially appear whimsical or even preposterous in nature. In recent years, the state of Alaska has captured the attention of both political analysts and labor economists due to a peculiar trend observed in the voting patterns for Senators and the composition of the labor force. This study seeks to shed light on the unexpected relationship between Democrat votes for Senators in Alaska and the number of ticket agents employed in the region.

Situated at the confluence of North America and the Arctic, Alaska presents a unique backdrop for this investigation. The state’s rugged terrain, frigid temperatures, and vibrant wildlife stand in stark contrast to the intricacies of its political and economic landscapes. As such, delving into the connection between political affiliation and employment in the region is akin to venturing into unchartered territory, or perhaps, setting sail on uncharted waters.

Through meticulous analysis of data spanning nearly two decades, our research team aims to demystify this enigmatic correlation and offer a perspective that challenges conventional wisdom. As we embark on this academic odyssey, we invite readers to join us in unraveling the cryptic bond between the political inclinations of Alaskan voters and the labor market dynamics, revealing unexpected insights that may prompt observers to exclaim, “only in Alaska!”


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Democrat votes for Senators in Alaska and The number of ticket agents in Alaska. 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
The Alaska Ballot and Ticket Tally: A Correlation Between Democrat Votes for Senators and Ticket Agents

[[ABSTRACT]]
This paper investigates the relationship between Democrat votes for Senators in the state of Alaska and the number of ticket agents employed in the same region. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, our research team delved into this unconventional and whimsical inquiry. Employing rigorous statistical methods, including calculating a correlation coefficient of 0.9226673 and p < 0.01 for the time period spanning from 2003 to 2020, our findings bring to light a surprising yet compelling connection. As we delve deeper into this correlation, we uncover a unique interplay between political preference and the labor force in the Last Frontier. While the results may seem far-fetched, they speak volumes about the interwoven fabric of political representation and workforce dynamics in the Alaskan context. We invite readers to embark on this peculiar yet insightful journey, replete with unexpected twists and turns, as we unravel the curious case of Democrat votes and ticket agents in the land of glaciers and midnight sun.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of politics and economics has long been a subject of scholarly fascination, yielding insights that often defy conventional expectations. As researchers, it is our duty to examine patterns and correlations that may initially appear whimsical or even preposterous in nature. In recent years, the state of Alaska has captured the attention of both political analysts and labor economists due to a peculiar trend observed in the voting patterns for Senators and the composition of the labor force. This study seeks to shed light on the unexpected relationship between Democrat votes for Senators in Alaska and the number of ticket agents employed in the region.
Situated at the confluence of North America and the Arctic, Alaska presents a unique backdrop for this investigation. The state’s rugged terrain, frigid temperatures, and vibrant wildlife stand in stark contrast to the intricacies of its political and economic landscapes. As such, delving into the connection between political affiliation and employment in the region is akin to venturing into unchartered territory, or perhaps, setting sail on uncharted waters.

Through meticulous analysis of data spanning nearly two decades, our research team aims to demystify this enigmatic correlation and offer a perspective that challenges conventional wisdom. As we embark on this academic odyssey, we invite readers to join us in unraveling the cryptic bond between the political inclinations of Alaskan voters and the labor market dynamics, revealing unexpected insights that may prompt observers to exclaim, “only in Alaska!”

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Prior research has delved into the complex interplay of political dynamics and labor market trends, yielding insights into the enigmatic relationship between voter behavior and employment patterns. Smith and Doe (2015) conducted a comprehensive analysis of political affiliation and workforce composition, shedding light on the nuanced connections that transcend traditional disciplinary boundaries. In "The Political Economy of Employment," the authors find that political preferences can indeed influence the occupational choices and preferences of individuals, offering a compelling framework for understanding the interplay of politics and labor.

Jones et al. (2017) further expound on this theme in their seminal work, "Labor in the Land of the Midnight Sun," elucidating the intricate nexus between political representation and economic activity in the state of Alaska. The authors underscore the significance of regional peculiarities in shaping the labor market, hinting at subtle forces that may sway political allegiance and labor dynamics in unexpected ways.

Aside from these scholarly inquiries, a diverse array of non-fiction literature has also contributed to the exploration of similar themes. "Economic Landscapes of the Last Frontier" by Walker (2019) and "Politics and Sustainability in the Arctic" by Frost (2018) offer nuanced perspectives on the economic and political contours of the Alaskan landscape, setting the stage for our investigation into the curious relationship between Democrat votes for Senators and the number of ticket agents employed in the region.

Turning to the realm of fiction, the works of Jack London, particularly "The Call of the Wild" and "White Fang," evoke the rugged terrain and resilient spirit of Alaska, providing a backdrop against which our study unfolds. While these literary works may not directly address the specific correlation under scrutiny, they infuse our exploration with a sense of adventure and rugged individualism that resonates with the spirit of the Last Frontier.

In a tangentially related vein, the board game "Ticket to Ride: Alaska Edition" captures the essence of traversing the Alaskan wilderness, transporting players to the remote corners of the state through a whimsical and captivating journey. While the game itself does not directly address the correlation between Democrat votes and ticket agents, its thematic resonance adds a touch of levity to our academic inquiry, inviting us to navigate the intriguing terrain of political affiliation and workforce composition with a sense of playfulness and curiosity.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Democrat votes for Senators in Alaska and The number of ticket agents in Alaska. 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 Alaska Ballot and Ticket Tally: A Correlation Between Democrat Votes for Senators and Ticket Agents

[[ABSTRACT]]
This paper investigates the relationship between Democrat votes for Senators in the state of Alaska and the number of ticket agents employed in the same region. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, our research team delved into this unconventional and whimsical inquiry. Employing rigorous statistical methods, including calculating a correlation coefficient of 0.9226673 and p < 0.01 for the time period spanning from 2003 to 2020, our findings bring to light a surprising yet compelling connection. As we delve deeper into this correlation, we uncover a unique interplay between political preference and the labor force in the Last Frontier. While the results may seem far-fetched, they speak volumes about the interwoven fabric of political representation and workforce dynamics in the Alaskan context. We invite readers to embark on this peculiar yet insightful journey, replete with unexpected twists and turns, as we unravel the curious case of Democrat votes and ticket agents in the land of glaciers and midnight sun.

[[INTRODUCTION]]
The intersection of politics and economics has long been a subject of scholarly fascination, yielding insights that often defy conventional expectations. As researchers, it is our duty to examine patterns and correlations that may initially appear whimsical or even preposterous in nature. In recent years, the state of Alaska has captured the attention of both political analysts and labor economists due to a peculiar trend observed in the voting patterns for Senators and the composition of the labor force. This study seeks to shed light on the unexpected relationship between Democrat votes for Senators in Alaska and the number of ticket agents employed in the region.
Situated at the confluence of North America and the Arctic, Alaska presents a unique backdrop for this investigation. The state’s rugged terrain, frigid temperatures, and vibrant wildlife stand in stark contrast to the intricacies of its political and economic landscapes. As such, delving into the connection between political affiliation and employment in the region is akin to venturing into unchartered territory, or perhaps, setting sail on uncharted waters.

Through meticulous analysis of data spanning nearly two decades, our research team aims to demystify this enigmatic correlation and offer a perspective that challenges conventional wisdom. As we embark on this academic odyssey, we invite readers to join us in unraveling the cryptic bond between the political inclinations of Alaskan voters and the labor market dynamics, revealing unexpected insights that may prompt observers to exclaim, “only in Alaska!”

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Data Collection:
The data for this study was sourced primarily from the MIT Election Data and Science Lab, the Harvard Dataverse, and the Bureau of Labor Statistics. After navigating through numerous online repositories and statistical databases, our research team compiled a comprehensive dataset spanning the years 2003 to 2020. Given the unconventional nature of our inquiry, meticulous attention was given to the representativeness and integrity of the data sources, ensuring that the information obtained reflected the idiosyncratic political and labor dynamics of the Alaskan context.

Variable Selection:
The key variables of interest in this analysis consisted of Democrat votes for Senators in Alaska and the number of ticket agents employed in the state. To capture the varying political sentiments over time, election data for Senate races in Alaska was meticulously gathered, parsing through the throngs of electoral statistics to isolate the Democrat votes. Concurrently, data pertaining to the employment of ticket agents was extracted from the Bureau of Labor Statistics' occupational employment surveys, emphasizing the need for exactitude in identifying and delineating the specific occupational category under study.

Correlation Analysis:
To unravel the potential relationship between Democrat votes for Senators and the number of ticket agents, a correlation analysis was conducted. Through the utilization of statistical software, the Pearson correlation coefficient was computed, enabling a robust quantitative assessment of the association between the aforementioned variables. Furthermore, the significance level (p-value) of the correlation was ascertained, supplementing the correlation coefficient with a rigorous test of statistical significance. The correlation analysis sought to unearth any underlying patterns or trends that could potentially underpin the interplay between political preferences and labor market dynamics in Alaska.

Control Variables:
In recognition of the multifaceted influences that may impinge on the relationship between Democrat votes for Senators and the employment of ticket agents, several control variables were incorporated. These encompassed demographic, economic, and geographical factors that could plausibly confound the observed connection, including population size, economic indicators, and regional variations. The inclusion of these control variables aimed to mitigate the potential spuriousness of the correlation, fortifying the robustness of the analysis by attenuating extraneous influences.

Temporal Analysis:
Given the longitudinal nature of the data encompassing the years 2003 to 2020, a temporal analysis was integral to discerning any temporal evolution or fluctuations in the correlation between political inclinations and the labor market in Alaska. This entailed delineating the correlation coefficient and p-values across distinct time intervals, enabling a nuanced examination of how the relationship between Democrat votes for Senators and the employment of ticket agents may have shifted over the years. Additionally, this temporal analysis offered insights into the stability or transience of the observed correlation, shedding light on its persistence or transiency amidst the dynamic socio-political and economic landscape of Alaska.

Validity and Limitations:
Throughout the methodological underpinnings of this research, assiduity was exercised in upholding the validity and integrity of the findings. Nevertheless, it is imperative to acknowledge the limitations inherent in this study. The nature of observational data inherently precludes causal inference, and thus, while this research illuminates a compelling correlation, caution must be exercised in deducing causal relationships. Moreover, the generalizability of the findings may be circumscribed by the distinct characteristics of the Alaskan context, tempering the extrapolation of the observed correlation to other geographic locales. Despite these caveats, the convergence of corroborative evidence and the rigorous analytical approach imbue the findings with a level of credibility that invites scholarly scrutiny and further inquiry.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Democrat votes for Senators in Alaska and The number of ticket agents in Alaska. 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 0.9226673, r-squared of 0.8513149, 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 Alaska Ballot and Ticket Tally: A Correlation Between Democrat Votes for Senators and Ticket Agents

[[ABSTRACT]]
This paper investigates the relationship between Democrat votes for Senators in the state of Alaska and the number of ticket agents employed in the same region. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, our research team delved into this unconventional and whimsical inquiry. Employing rigorous statistical methods, including calculating a correlation coefficient of 0.9226673 and p < 0.01 for the time period spanning from 2003 to 2020, our findings bring to light a surprising yet compelling connection. As we delve deeper into this correlation, we uncover a unique interplay between political preference and the labor force in the Last Frontier. While the results may seem far-fetched, they speak volumes about the interwoven fabric of political representation and workforce dynamics in the Alaskan context. We invite readers to embark on this peculiar yet insightful journey, replete with unexpected twists and turns, as we unravel the curious case of Democrat votes and ticket agents in the land of glaciers and midnight sun.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intersection of politics and economics has long been a subject of scholarly fascination, yielding insights that often defy conventional expectations. As researchers, it is our duty to examine patterns and correlations that may initially appear whimsical or even preposterous in nature. In recent years, the state of Alaska has captured the attention of both political analysts and labor economists due to a peculiar trend observed in the voting patterns for Senators and the composition of the labor force. This study seeks to shed light on the unexpected relationship between Democrat votes for Senators in Alaska and the number of ticket agents employed in the region.
Situated at the confluence of North America and the Arctic, Alaska presents a unique backdrop for this investigation. The state’s rugged terrain, frigid temperatures, and vibrant wildlife stand in stark contrast to the intricacies of its political and economic landscapes. As such, delving into the connection between political affiliation and employment in the region is akin to venturing into unchartered territory, or perhaps, setting sail on uncharted waters.

Through meticulous analysis of data spanning nearly two decades, our research team aims to demystify this enigmatic correlation and offer a perspective that challenges conventional wisdom. As we embark on this academic odyssey, we invite readers to join us in unraveling the cryptic bond between the political inclinations of Alaskan voters and the labor market dynamics, revealing unexpected insights that may prompt observers to exclaim, “only in Alaska!”

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The data analysis revealed a strong positive correlation of 0.9226673 between Democrat votes for Senators in Alaska and the number of ticket agents employed in the region for the period from 2003 to 2020. The coefficient of determination (r-squared) calculated at 0.8513149 indicated that a staggering 85% of the variation in the number of ticket agents could be explained by changes in Democrat votes for Senators. The statistical significance, with a p-value of less than 0.01, further bolstered the robustness of this association.

As depicted in Figure 1, the scatterplot visually illustrates the remarkable alignment between the two variables, providing a striking visual representation of the correlation. It is remarkable to witness such a compelling connection emerge from an ostensibly unlikely pairing – who would have thought that the fate of ticket agents in Alaska could be intertwined with the political leanings of the state's voters? It is perhaps a testament to the old adage, "expect the unexpected," as we navigate the complexities of statistical analysis in the Alaskan context.

Our findings not only stand as a testament to the unusual nature of this relationship but also underscore the intricate tapestry of factors influencing labor market dynamics. The unearthing of this correlation neither ceases to amaze nor fails to provoke further contemplation. The intersection of political choice and labor market conditions has rarely been quite so straightforward, and the curious case of Democrat votes and ticket agents in Alaska serves as an intriguing example of the whimsicality of empirical inquiry.

While our results may prompt a furrowed brow or an incredulous glance, they beckon further exploration and invite a re-evaluation of the interconnections between seemingly disparate spheres. The fusion of political science and labor economics in the Alaskan context has proven to be a venture rich in surprises and revelations, compelling us to reconsider the boundaries of conventional wisdom and embrace the unexpected correlations that lie beneath the surface.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Democrat votes for Senators in Alaska and The number of ticket agents in Alaska. 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 Alaska Ballot and Ticket Tally: A Correlation Between Democrat Votes for Senators and Ticket Agents

[[ABSTRACT]]
This paper investigates the relationship between Democrat votes for Senators in the state of Alaska and the number of ticket agents employed in the same region. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, our research team delved into this unconventional and whimsical inquiry. Employing rigorous statistical methods, including calculating a correlation coefficient of 0.9226673 and p < 0.01 for the time period spanning from 2003 to 2020, our findings bring to light a surprising yet compelling connection. As we delve deeper into this correlation, we uncover a unique interplay between political preference and the labor force in the Last Frontier. While the results may seem far-fetched, they speak volumes about the interwoven fabric of political representation and workforce dynamics in the Alaskan context. We invite readers to embark on this peculiar yet insightful journey, replete with unexpected twists and turns, as we unravel the curious case of Democrat votes and ticket agents in the land of glaciers and midnight sun.

[[LITERATURE REVIEW]]
Prior research has delved into the complex interplay of political dynamics and labor market trends, yielding insights into the enigmatic relationship between voter behavior and employment patterns. Smith and Doe (2015) conducted a comprehensive analysis of political affiliation and workforce composition, shedding light on the nuanced connections that transcend traditional disciplinary boundaries. In "The Political Economy of Employment," the authors find that political preferences can indeed influence the occupational choices and preferences of individuals, offering a compelling framework for understanding the interplay of politics and labor.
Jones et al. (2017) further expound on this theme in their seminal work, "Labor in the Land of the Midnight Sun," elucidating the intricate nexus between political representation and economic activity in the state of Alaska. The authors underscore the significance of regional peculiarities in shaping the labor market, hinting at subtle forces that may sway political allegiance and labor dynamics in unexpected ways.
Aside from these scholarly inquiries, a diverse array of non-fiction literature has also contributed to the exploration of similar themes. "Economic Landscapes of the Last Frontier" by Walker (2019) and "Politics and Sustainability in the Arctic" by Frost (2018) offer nuanced perspectives on the economic and political contours of the Alaskan landscape, setting the stage for our investigation into the curious relationship between Democrat votes for Senators and the number of ticket agents employed in the region.
Turning to the realm of fiction, the works of Jack London, particularly "The Call of the Wild" and "White Fang," evoke the rugged terrain and resilient spirit of Alaska, providing a backdrop against which our study unfolds. While these literary works may not directly address the specific correlation under scrutiny, they infuse our exploration with a sense of adventure and rugged individualism that resonates with the spirit of the Last Frontier.
In a tangentially related vein, the board game "Ticket to Ride: Alaska Edition" captures the essence of traversing the Alaskan wilderness, transporting players to the remote corners of the state through a whimsical and captivating journey. While the game itself does not directly address the correlation between Democrat votes and ticket agents, its thematic resonance adds a touch of levity to our academic inquiry, inviting us to navigate the intriguing terrain of political affiliation and workforce composition with a sense of playfulness and curiosity.

[[RESULTS]]
The data analysis revealed a strong positive correlation of 0.9226673 between Democrat votes for Senators in Alaska and the number of ticket agents employed in the region for the period from 2003 to 2020. The coefficient of determination (r-squared) calculated at 0.8513149 indicated that a staggering 85% of the variation in the number of ticket agents could be explained by changes in Democrat votes for Senators. The statistical significance, with a p-value of less than 0.01, further bolstered the robustness of this association.
As depicted in Figure 1, the scatterplot visually illustrates the remarkable alignment between the two variables, providing a striking visual representation of the correlation. It is remarkable to witness such a compelling connection emerge from an ostensibly unlikely pairing – who would have thought that the fate of ticket agents in Alaska could be intertwined with the political leanings of the state's voters? It is perhaps a testament to the old adage, "expect the unexpected," as we navigate the complexities of statistical analysis in the Alaskan context.
Our findings not only stand as a testament to the unusual nature of this relationship but also underscore the intricate tapestry of factors influencing labor market dynamics. The unearthing of this correlation neither ceases to amaze nor fails to provoke further contemplation. The intersection of political choice and labor market conditions has rarely been quite so straightforward, and the curious case of Democrat votes and ticket agents in Alaska serves as an intriguing example of the whimsicality of empirical inquiry.
While our results may prompt a furrowed brow or an incredulous glance, they beckon further exploration and invite a re-evaluation of the interconnections between seemingly disparate spheres. The fusion of political science and labor economics in the Alaskan context has proven to be a venture rich in surprises and revelations, compelling us to reconsider the boundaries of conventional wisdom and embrace the unexpected correlations that lie beneath the surface.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The correlation between Democrat votes for Senators in Alaska and the number of ticket agents employed in the region has yielded intriguing insights, inviting a reevaluation of the interplay between political preferences and labor market dynamics. Our findings align with prior research (Smith and Doe, 2015; Jones et al., 2017) that underscores the influence of political representation on workforce composition, adding a whimsical twist to the otherwise conventional framework. Despite the initial incredulity that may accompany such an association, our study has not only supported, but also enhanced, the existing literature by unveiling a robust and statistically significant correlation.

The unexpected alignment between political preferences and employment patterns in the context of Alaska serves as a testament to the intricate tapestry of regional dynamics. While the peculiar juxtaposition of Democrat votes and ticket agents may prompt a furrowed brow akin to a hiker's furrowed brow navigating the rugged terrain, the statistical robustness of our findings cannot be discounted. The significant correlation coefficient and the high coefficient of determination emphasize the substantial explanatory power of Democrat votes for Senators in predicting the variation in the number of ticket agents, evoking a sense of astonishment not unlike stumbling upon an unexpected vista in the Alaskan wilderness.

Our study not only contributes to the discourse on regional labor market dynamics but also offers a departure from traditional scholarly inquiry, infusing the academic sphere with a touch of levity akin to the playfulness of the "Ticket to Ride: Alaska Edition." The whimsical interplay of politics and employment in the Last Frontier prompts us to navigate this peculiar terrain with a sense of curiosity, akin to embarking on an unexpected journey through the Alaskan wilderness. As we unravel the enigmatic relationship between Democrat votes and ticket agents, we are reminded of the myriad factors that shape the economic and political landscape, echoing the spirit of adventure evoked by Jack London's literary works.

Ultimately, our findings challenge the boundaries of conventional wisdom, urging a reconsideration of the interconnections between seemingly disparate spheres. The surprising nexus between political representation and workforce composition in Alaska is a whimsical reminder that beneath the surface lie correlations that defy traditional expectations. As we embark upon this peculiar yet insightful journey, we are prompted to embrace the unexpected correlations that enrich our understanding of the intricate fabric of regional dynamics in the Last Frontier.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Democrat votes for Senators in Alaska and The number of ticket agents in Alaska. 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 Alaska Ballot and Ticket Tally: A Correlation Between Democrat Votes for Senators and Ticket Agents

[[ABSTRACT]]
This paper investigates the relationship between Democrat votes for Senators in the state of Alaska and the number of ticket agents employed in the same region. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, our research team delved into this unconventional and whimsical inquiry. Employing rigorous statistical methods, including calculating a correlation coefficient of 0.9226673 and p < 0.01 for the time period spanning from 2003 to 2020, our findings bring to light a surprising yet compelling connection. As we delve deeper into this correlation, we uncover a unique interplay between political preference and the labor force in the Last Frontier. While the results may seem far-fetched, they speak volumes about the interwoven fabric of political representation and workforce dynamics in the Alaskan context. We invite readers to embark on this peculiar yet insightful journey, replete with unexpected twists and turns, as we unravel the curious case of Democrat votes and ticket agents in the land of glaciers and midnight sun.

[[INTRDUCTION]]
The intersection of politics and economics has long been a subject of scholarly fascination, yielding insights that often defy conventional expectations. As researchers, it is our duty to examine patterns and correlations that may initially appear whimsical or even preposterous in nature. In recent years, the state of Alaska has captured the attention of both political analysts and labor economists due to a peculiar trend observed in the voting patterns for Senators and the composition of the labor force. This study seeks to shed light on the unexpected relationship between Democrat votes for Senators in Alaska and the number of ticket agents employed in the region.
Situated at the confluence of North America and the Arctic, Alaska presents a unique backdrop for this investigation. The state’s rugged terrain, frigid temperatures, and vibrant wildlife stand in stark contrast to the intricacies of its political and economic landscapes. As such, delving into the connection between political affiliation and employment in the region is akin to venturing into unchartered territory, or perhaps, setting sail on uncharted waters.

Through meticulous analysis of data spanning nearly two decades, our research team aims to demystify this enigmatic correlation and offer a perspective that challenges conventional wisdom. As we embark on this academic odyssey, we invite readers to join us in unraveling the cryptic bond between the political inclinations of Alaskan voters and the labor market dynamics, revealing unexpected insights that may prompt observers to exclaim, “only in Alaska!”

[[RESULTS]]
The data analysis revealed a strong positive correlation of 0.9226673 between Democrat votes for Senators in Alaska and the number of ticket agents employed in the region for the period from 2003 to 2020. The coefficient of determination (r-squared) calculated at 0.8513149 indicated that a staggering 85% of the variation in the number of ticket agents could be explained by changes in Democrat votes for Senators. The statistical significance, with a p-value of less than 0.01, further bolstered the robustness of this association.
As depicted in Figure 1, the scatterplot visually illustrates the remarkable alignment between the two variables, providing a striking visual representation of the correlation. It is remarkable to witness such a compelling connection emerge from an ostensibly unlikely pairing – who would have thought that the fate of ticket agents in Alaska could be intertwined with the political leanings of the state's voters? It is perhaps a testament to the old adage, "expect the unexpected," as we navigate the complexities of statistical analysis in the Alaskan context.
Our findings not only stand as a testament to the unusual nature of this relationship but also underscore the intricate tapestry of factors influencing labor market dynamics. The unearthing of this correlation neither ceases to amaze nor fails to provoke further contemplation. The intersection of political choice and labor market conditions has rarely been quite so straightforward, and the curious case of Democrat votes and ticket agents in Alaska serves as an intriguing example of the whimsicality of empirical inquiry.
While our results may prompt a furrowed brow or an incredulous glance, they beckon further exploration and invite a re-evaluation of the interconnections between seemingly disparate spheres. The fusion of political science and labor economics in the Alaskan context has proven to be a venture rich in surprises and revelations, compelling us to reconsider the boundaries of conventional wisdom and embrace the unexpected correlations that lie beneath the surface.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

The enthralling journey through the labyrinthine landscape of Alaskan politics and labor economics has unveiled a captivating correlation between Democrat votes for Senators and the number of ticket agents employed in the region. The statistical analysis conducted in this study has brought to the fore an intriguing bond, with a correlation coefficient of 0.9226673 and a p-value of less than 0.01, signifying a profound interdependence between these ostensibly disparate variables. This unanticipated correlation serves as a poignant reminder that, in the realm of empirical inquiry, the most curious connections often materialize from the most unexpected pairings. It seems that in the unique context of the Last Frontier, the whims of political choice and the ebb and flow of labor market dynamics intertwine in a manner that challenges traditional expectations and prompts us to view the fabric of societal phenomena in a new light.

The discovery of this correlation invites us to reflect on the idiosyncrasies and complexities that underpin the interplay between political inclination and labor force composition, serving as a testament to the ceaseless capacity for surprise in the world of data analysis. As we conclude this odyssey into the enigmatic correlation between Democrat votes and ticket agents in Alaska, it becomes abundantly clear that the quirkiness of empirical inquiry knows no bounds, and the findings of this study will undoubtedly linger in the annals of unconventional yet thought-provoking research.

It is our earnest hope that this study will inspire further exploration and contemplation of the interconnections between ostensibly unrelated spheres, and that the unexpected correlation unveiled in these analyses will spark lively discourse and perhaps, a chuckle or two. However, in terms of further research in this area, we assert that no more investigation is needed.


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 Alaska Ballot and Ticket Tally: A Correlation Between Democrat Votes for Senators and Ticket Agents. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Political Paradoxes


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 Alaska Ballot and Ticket Tally: A Correlation Between Democrat Votes for Senators and Ticket Agents. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Interdisciplinary Political Analysis and Reporting


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 Alaska Ballot and Ticket Tally: A Correlation Between Democrat Votes for Senators and Ticket Agents with an abstract of This paper investigates the relationship between Democrat votes for Senators in the state of Alaska and the number of ticket agents employed in the same region. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Bureau of Labor Statistics, our research team delved into this unconventional and whimsical inquiry. Employing rigorous statistical methods, including calculating a correlation coefficient of 0.9226673 and p < 0.01 for the time period spanning from 2003 to 2020, our findings bring to light a surprising yet compelling connection. As we delve deeper into this correlation, we uncover a unique interplay between political preference and the labor force in the Last Frontier. While the results may seem far-fetched, they speak volumes about the interwoven fabric of political representation and workforce dynamics in the Alaskan context. We invite readers to embark on this peculiar yet insightful journey, replete with unexpected twists and turns, as we unravel the curious case of Democrat votes and ticket agents in the land of glaciers and midnight sun.

ChatGPT:

Alaska, Democrat votes, Senators, ticket agents, correlation, employment, MIT Election Data and Science Lab, Harvard Dataverse, Bureau of Labor Statistics, statistical methods, correlation coefficient, workforce dynamics, political representation

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

The number of ticket agents in Alaska
Detailed data title: BLS estimate of reservation and transportation ticket agents and travel clerks in Alaska
Source: Bureau of Larbor Statistics
See what else correlates with The number of ticket agents in Alaska

Correlation r = 0.9226673 (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 = 0.8513149 (Coefficient of determination)
This means 85.1% of the change in the one variable (i.e., The number of ticket agents in Alaska) is predictable based on the change in the other (i.e., Votes for Democratic Senators in Alaska) over the 6 years from 2003 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.0087. 0.0087392913230909560000000000
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 0.92 in 0.87% of random cases. Said differently, if you correlated 114 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.

[ 0.44, 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.
200420082010201420162020
Votes for Democratic Senators in Alaska (Percentage of votes)45.545647.767123.500745.832511.623441.1938
The number of ticket agents in Alaska (Laborers)10301120890970620940




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  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.
  5. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([45.5456,47.7671,23.5007,45.8325,11.6234,41.1938,])
array_2 = np.array([1030,1120,890,970,620,940,])
array_1_name = "Votes for Democratic Senators in Alaska"
array_2_name = "The number of ticket agents in Alaska"

# 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: 4763 · Black Variable ID: 26345 · Red Variable ID: 4799
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