Spurious correlation #1,246 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Gasoline pumped in Eritrea and the second variable is Customer satisfaction with Macy's. The chart goes from 2005 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 Gasoline pumped in Eritrea and the second variable is Customer satisfaction with Macy's. The chart goes from 2005 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the gasoline consumption in Eritrea rises, so does the country's overall mood. The Eritrean people, feeling the rush of being able to travel more, unwittingly project their newfound contentment onto the world, thus inexplicably boosting customer satisfaction with Macy's. It's like a wave of positive energy transcending geographical boundaries and influencing the most unexpected places, proving that happiness at the pump can indeed fuel happiness in the retail realm!

^{Show image generation prompt} Model: dalle-3
Prompt: "Generate a whimsical illustration of a lively Eritrean gas station, with colorful cars filling up their tanks. As the scene transitions, depict a bustling city street with pedestrians bustling in and out of shops. Among them, illustrate a couple exiting a car and stumbling upon a 'Macy's' sign. Inside the store, portray them joyfully discovering an amazing deal on a winter coat. Finally, depict the couple leaving Macy's with satisfied smiles, happy with their unexpected find. Keep the illustration simple, avoiding any words or speech bubbles." The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

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

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: Because the increase in gasoline pumped in Eritrea led to more car travel, which increased the likelihood of people accidentally discovering amazing deals at Macy's while looking for a restroom. The excitement of finding unexpected bargains led to a surge in customer satisfaction with Macy's.. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: Sci-fi fantacy a Polaroid photo Glitch art Steampunk Whimsical illustration
ChatGPT: Whimsical illustration

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. Because the increase in gasoline pumped in Eritrea led to more car travel, which increased the likelihood of people accidentally discovering amazing deals at Macy's while looking for a restroom. The excitement of finding unexpected bargains led to a surge in customer satisfaction with Macy's.
ChatGPT: Imagine a busy Eritrean gas station, where more cars are filling up their tanks. As more people are driving, the scene shifts to a bustling city street, where pedestrians are walking in and out of shops. Among them, a couple exiting a car and looking for a restroom accidentally stumbles upon a "Macy's" sign. Inside the store, they excitedly discover an amazing deal on a winter coat. The couple smiles with satisfaction as they leave Macy's, happy with their unexpected find.

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: [ Whimsical illustration ] and depicting this scene: Imagine a busy Eritrean gas station, where more cars are filling up their tanks. As more people are driving, the scene shifts to a bustling city street, where pedestrians are walking in and out of shops. Among them, a couple exiting a car and looking for a restroom accidentally stumbles upon a "Macy's" sign. Inside the store, they excitedly discover an amazing deal on a winter coat. The couple smiles with satisfaction as they leave Macy's, happy with their unexpected find. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: "Generate a whimsical illustration of a lively Eritrean gas station, with colorful cars filling up their tanks. As the scene transitions, depict a bustling city street with pedestrians bustling in and out of shops. Among them, illustrate a couple exiting a car and stumbling upon a 'Macy's' sign. Inside the store, portray them joyfully discovering an amazing deal on a winter coat. Finally, depict the couple leaving Macy's with satisfied smiles, happy with their unexpected find. Keep the illustration simple, avoiding any words or speech bubbles."

*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 an increase in Gasoline pumped in Eritrea caused Customer satisfaction with Macy's to increase. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Fueling Satisfaction: Examining the Unlikely Relationship Between Gasoline Pumped in Eritrea and Customer Contentment at Macy's

The International Journal of Retail Petrology

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 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 Gasoline pumped in Eritrea and Customer satisfaction with Macy's. 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 name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
"Fueling Satisfaction: Examining the Unlikely Relationship Between Gasoline Pumped in Eritrea and Customer Contentment at Macy's"

[[ABSTRACT]]
This study explores the unexpected correlation between the volume of gasoline pumped in Eritrea and customer satisfaction levels at the renowned retail establishment, Macy's. Drawing on data from the Energy Information Administration and the American Customer Satisfaction Index, our research team conducted a robust analysis spanning the years 2005 to 2020. The analysis revealed a striking correlation coefficient of 0.7797306 and a statistically significant p-value of less than 0.01, highlighting a compelling relationship between these seemingly disparate variables. While conventional wisdom may suggest a lack of connection between Eritrean gasoline consumption and the shopping experience at a popular American department store, our findings challenge these assumptions. The implications of this study extend beyond the realm of retail and energy economics, opening novel avenues for interdisciplinary inquiry and underscoring the unpredictable nature of consumer behavior and market dynamics.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The world of consumer behavior and market dynamics is a vast and complex tapestry, woven with countless threads of interconnected variables. From the price of tea in China to the yield of wheat in Kansas, the global marketplace is a web of hidden connections and unexpected correlations. In this vein, our research embarks on an unconventional exploration of the relationship between the seemingly disparate realms of gasoline consumption in Eritrea and customer satisfaction at the esteemed emporium known as Macy's.
While the link between these two variables may appear as incongruous as mismatched socks, our study endeavors to unravel the enigmatic bond that binds them. Drawing on data from the Energy Information Administration and the American Customer Satisfaction Index, our research spans a fifteen-year period from 2005 to 2020. Our curiosity was piqued by the initial observation of a potential association, and thus began our journey into the labyrinth of data analysis and statistical inference.
The unexpected nature of our findings compels us to reevaluate preconceived notions regarding consumer behavior and economic interplay. As we venture into uncharted territory, it becomes clear that the world of retail and energy economics is not as straightforward as a well-organized retail display or a precisely calibrated fuel pump. The intersection of these seemingly dissimilar worlds beckons us to delve deeper into the intricate mechanisms that shape consumer preferences and market dynamics.
Our investigation has yielded a striking correlation coefficient of 0.7797306 and a statistically significant p-value of less than 0.01, cementing the validity of the connection between Eritrean gasoline consumption and the satisfaction of patrons at Macy's. This unexpected revelation challenges conventional wisdom and beckons us to embrace the unpredictable nature of consumer behavior.
As we navigate through the underexplored terrain of these remarkable findings, our study not only contributes to the literature on retail and energy economics but also unveils hitherto undiscovered avenues for interdisciplinary inquiry. The implications of this research stretch far beyond the confines of the department store and the gas pump, calling for a reevaluation of traditional paradigms and prompting an appreciation of the capricious dance of market forces.
In essence, the unanticipated correlation between Eritrean gasoline consumption and customer contentment at Macy's serves as a testament to the unfathomable intricacies of the marketplace, reminding us that beneath the surface of apparent randomness, patterns may emerge, and surprises may abound. Our endeavor is not merely an exploration of statistical relationships but an ode to the unpredictability and fascination that underpin the world of consumer behavior and economic phenomena.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Previous studies have delved into the relationship between seemingly incongruent variables, uncovering surprising connections in the labyrinth of consumer behavior and market dynamics. Smith et al. (2010) examined the correlation between national coffee consumption and the sales of lawnmowers, showcasing the intricate web of interdependence within the marketplace. Similarly, Doe and Jones (2015) conducted a comprehensive analysis of ice cream sales and the frequency of shark sightings at various coastal regions, shedding light on the enigmatic ties between summer treats and marine predators. These studies demonstrate the unforeseen alliances that can emerge within the realm of consumer preferences and economic phenomena.

In "The Economics of Energy Markets" by Brown and White (2018), the authors elucidate the multifaceted nature of energy consumption patterns, highlighting the complex interplay between environmental factors and consumer behavior. Drawing on empirical evidence, the book posits that the dynamics of gasoline consumption extend beyond straightforward supply and demand models, echoing the nuanced complexities that underpin our investigation.

In a departure from the traditional economic literature, the fictional works of "The Great Gatsby" by F. Scott Fitzgerald and "Confessions of a Shopaholic" by Sophie Kinsella offer nuanced glimpses into the world of luxury, desire, and unexpected encounters. While these texts may not directly address Eritrean gasoline consumption or customer satisfaction at Macy's, they speak to the underlying themes of consumer experience and the uncanny convergence of disparate elements.

Furthermore, popular internet memes such as "Distracted Boyfriend" and "Woman Yelling at a Cat" ironically encapsulate the unpredictability of human behavior and the serendipitous nature of interwoven narratives - a sentiment resonant with the unanticipated correlation under investigation. These cultural artifacts serve as tongue-in-cheek reminders of the inexplicable connections that permeate the fabric of consumer preferences and market dynamics.

As the literature on unconventional correlations and consumer behavior unfolds, our study seeks to contribute to this tapestry of unexpected revelations, shedding light on the underlying mechanisms that link Eritrean gasoline consumption to customer satisfaction at Macy's.

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 Gasoline pumped in Eritrea and Customer satisfaction with Macy's. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and American Customer Satisfaction Index . You used data from 2005 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]]
"Fueling Satisfaction: Examining the Unlikely Relationship Between Gasoline Pumped in Eritrea and Customer Contentment at Macy's"

[[ABSTRACT]]
This study explores the unexpected correlation between the volume of gasoline pumped in Eritrea and customer satisfaction levels at the renowned retail establishment, Macy's. Drawing on data from the Energy Information Administration and the American Customer Satisfaction Index, our research team conducted a robust analysis spanning the years 2005 to 2020. The analysis revealed a striking correlation coefficient of 0.7797306 and a statistically significant p-value of less than 0.01, highlighting a compelling relationship between these seemingly disparate variables. While conventional wisdom may suggest a lack of connection between Eritrean gasoline consumption and the shopping experience at a popular American department store, our findings challenge these assumptions. The implications of this study extend beyond the realm of retail and energy economics, opening novel avenues for interdisciplinary inquiry and underscoring the unpredictable nature of consumer behavior and market dynamics.

[[INTRODUCTION]]
The world of consumer behavior and market dynamics is a vast and complex tapestry, woven with countless threads of interconnected variables. From the price of tea in China to the yield of wheat in Kansas, the global marketplace is a web of hidden connections and unexpected correlations. In this vein, our research embarks on an unconventional exploration of the relationship between the seemingly disparate realms of gasoline consumption in Eritrea and customer satisfaction at the esteemed emporium known as Macy's.
While the link between these two variables may appear as incongruous as mismatched socks, our study endeavors to unravel the enigmatic bond that binds them. Drawing on data from the Energy Information Administration and the American Customer Satisfaction Index, our research spans a fifteen-year period from 2005 to 2020. Our curiosity was piqued by the initial observation of a potential association, and thus began our journey into the labyrinth of data analysis and statistical inference.
The unexpected nature of our findings compels us to reevaluate preconceived notions regarding consumer behavior and economic interplay. As we venture into uncharted territory, it becomes clear that the world of retail and energy economics is not as straightforward as a well-organized retail display or a precisely calibrated fuel pump. The intersection of these seemingly dissimilar worlds beckons us to delve deeper into the intricate mechanisms that shape consumer preferences and market dynamics.
Our investigation has yielded a striking correlation coefficient of 0.7797306 and a statistically significant p-value of less than 0.01, cementing the validity of the connection between Eritrean gasoline consumption and the satisfaction of patrons at Macy's. This unexpected revelation challenges conventional wisdom and beckons us to embrace the unpredictable nature of consumer behavior.
As we navigate through the underexplored terrain of these remarkable findings, our study not only contributes to the literature on retail and energy economics but also unveils hitherto undiscovered avenues for interdisciplinary inquiry. The implications of this research stretch far beyond the confines of the department store and the gas pump, calling for a reevaluation of traditional paradigms and prompting an appreciation of the capricious dance of market forces.
In essence, the unanticipated correlation between Eritrean gasoline consumption and customer contentment at Macy's serves as a testament to the unfathomable intricacies of the marketplace, reminding us that beneath the surface of apparent randomness, patterns may emerge, and surprises may abound. Our endeavor is not merely an exploration of statistical relationships but an ode to the unpredictability and fascination that underpin the world of consumer behavior and economic phenomena.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the mysterious relationship between the quantity of gasoline pumped in Eritrea and the levels of customer satisfaction at Macy's, a comprehensive research approach was adopted. The data utilized in this study were primarily derived from the Energy Information Administration (EIA) and the American Customer Satisfaction Index (ACSI), covering the extensive timeframe from 2005 to 2020. The utilization of these primary sources ensured the integrity and reliability of the information under scrutiny.

The first step in our data collection process involved perusing the voluminous databases of the EIA and ACSI. As we waded through the sea of statistical records, we utilized a proverbial sieve to capture the pertinent variables related to gasoline consumption in Eritrea and customer satisfaction metrics associated with Macy's. The selection criteria were as rigorous as a fastidious shopper inspecting each watermelon in search of the perfect one - only the most pertinent and meticulously detailed data points made the cut.

Following the extraction of the relevant data, an intricate dance of statistical analyses commenced. The quantitative investigation was akin to a meticulous choreography, with each step carefully calibrated to ensure the accuracy and robustness of the findings. The data underwent a series of rigorous tests, including correlation analysis, regression modeling, and exploratory factor analysis. Through these analytical maneuvers, we sought to unearth any semblance of a connection between Eritrean gasoline consumption and customer satisfaction at Macy's, embracing the imperative of statistical significance with fervent dedication.

In addressing potential confounding factors and spurious correlations, sensitivity analyses were performed. This rigorous examination aimed to discern whether the observed relationship between Eritrean gasoline consumption and customer satisfaction at Macy's withstood the scrutiny of alternative model specifications and control variables. The meticulous calibration of these sensitivity analyses ensured that our findings remained steadfast in the face of potential extraneous influences, akin to a resilient ship navigating uncharted waters.

Furthermore, to mitigate the potential for publication bias and spurious correlations, efforts were made to triangulate our findings with existing literature. A comprehensive review of academic journals, industry reports, and scholarly publications pertaining to retail economics and consumer behavior was conducted. This meticulous exploration of the academic landscape served as a compass, guiding our study through the labyrinth of prior research and anchoring our findings in the context of existing knowledge.

In summary, the research methodology employed in this study integrated a coherent blend of data extraction, statistical analyses, sensitivity assessments, and literature review. Through the intricate orchestration of these methodological components, our research sought to unearth the enigmatic association between Eritrean gasoline consumption and customer satisfaction at Macy's, shedding light on an unsuspected interconnection amidst the intricate tapestry of consumer behavior and market dynamics.

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 Gasoline pumped in Eritrea and Customer satisfaction with Macy's. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and American Customer Satisfaction Index .

For the time period 2005 to 2020, you found a correlation 0.7797306, r-squared of 0.6079797, 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]]
"Fueling Satisfaction: Examining the Unlikely Relationship Between Gasoline Pumped in Eritrea and Customer Contentment at Macy's"

[[ABSTRACT]]
This study explores the unexpected correlation between the volume of gasoline pumped in Eritrea and customer satisfaction levels at the renowned retail establishment, Macy's. Drawing on data from the Energy Information Administration and the American Customer Satisfaction Index, our research team conducted a robust analysis spanning the years 2005 to 2020. The analysis revealed a striking correlation coefficient of 0.7797306 and a statistically significant p-value of less than 0.01, highlighting a compelling relationship between these seemingly disparate variables. While conventional wisdom may suggest a lack of connection between Eritrean gasoline consumption and the shopping experience at a popular American department store, our findings challenge these assumptions. The implications of this study extend beyond the realm of retail and energy economics, opening novel avenues for interdisciplinary inquiry and underscoring the unpredictable nature of consumer behavior and market dynamics.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The world of consumer behavior and market dynamics is a vast and complex tapestry, woven with countless threads of interconnected variables. From the price of tea in China to the yield of wheat in Kansas, the global marketplace is a web of hidden connections and unexpected correlations. In this vein, our research embarks on an unconventional exploration of the relationship between the seemingly disparate realms of gasoline consumption in Eritrea and customer satisfaction at the esteemed emporium known as Macy's.
While the link between these two variables may appear as incongruous as mismatched socks, our study endeavors to unravel the enigmatic bond that binds them. Drawing on data from the Energy Information Administration and the American Customer Satisfaction Index, our research spans a fifteen-year period from 2005 to 2020. Our curiosity was piqued by the initial observation of a potential association, and thus began our journey into the labyrinth of data analysis and statistical inference.
The unexpected nature of our findings compels us to reevaluate preconceived notions regarding consumer behavior and economic interplay. As we venture into uncharted territory, it becomes clear that the world of retail and energy economics is not as straightforward as a well-organized retail display or a precisely calibrated fuel pump. The intersection of these seemingly dissimilar worlds beckons us to delve deeper into the intricate mechanisms that shape consumer preferences and market dynamics.
Our investigation has yielded a striking correlation coefficient of 0.7797306 and a statistically significant p-value of less than 0.01, cementing the validity of the connection between Eritrean gasoline consumption and the satisfaction of patrons at Macy's. This unexpected revelation challenges conventional wisdom and beckons us to embrace the unpredictable nature of consumer behavior.
As we navigate through the underexplored terrain of these remarkable findings, our study not only contributes to the literature on retail and energy economics but also unveils hitherto undiscovered avenues for interdisciplinary inquiry. The implications of this research stretch far beyond the confines of the department store and the gas pump, calling for a reevaluation of traditional paradigms and prompting an appreciation of the capricious dance of market forces.
In essence, the unanticipated correlation between Eritrean gasoline consumption and customer contentment at Macy's serves as a testament to the unfathomable intricacies of the marketplace, reminding us that beneath the surface of apparent randomness, patterns may emerge, and surprises may abound. Our endeavor is not merely an exploration of statistical relationships but an ode to the unpredictability and fascination that underpin the world of consumer behavior and economic phenomena.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of the data revealed a notable correlation coefficient of 0.7797306 between the volume of gasoline pumped in Eritrea and customer satisfaction levels at Macy's, suggesting a stronger-than-expected relationship between these ostensibly unrelated variables. The r-squared value of 0.6079797 indicates that approximately 61% of the variation in customer satisfaction at Macy's can be explained by changes in gasoline consumption in Eritrea. Furthermore, the p-value of less than 0.01 attests to the statistical significance of this unexpected association, lending additional weight to the observed correlation.

The scatterplot in Figure 1 vividly illustrates the robust correlation between Eritrean gasoline consumption and customer satisfaction at Macy's, providing visual confirmation of the surprising connection. Each data point on the scatterplot serves as a poignant reminder that in the intricate dance of market forces, seemingly unrelated factors may perform a harmonious duet that defies conventional expectations.

The implications of these findings extend beyond the immediate scope of retail and energy economics, challenging established dogmas and inviting a reevaluation of the interconnectedness of seemingly disparate phenomena. The striking correlation uncovered in this study serves as a testament to the complexity inherent in consumer behavior and market dynamics, reminding us that beneath the seemingly ordinary lies a treasure trove of unexpected relationships and unforeseen patterns.

In conclusion, the bond between Eritrean gasoline consumption and customer contentment at Macy's showcases the enchanting unpredictability of the marketplace, inviting further exploration into the labyrinthine world of consumer behavior and economic interactions. This unexpected correlation testifies to the capricious nature of market forces, emphasizing the need for a nuanced understanding of the intricate web of connections that underpin the global marketplace.

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 Gasoline pumped in Eritrea and Customer satisfaction with Macy's. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
"Fueling Satisfaction: Examining the Unlikely Relationship Between Gasoline Pumped in Eritrea and Customer Contentment at Macy's"

[[ABSTRACT]]
This study explores the unexpected correlation between the volume of gasoline pumped in Eritrea and customer satisfaction levels at the renowned retail establishment, Macy's. Drawing on data from the Energy Information Administration and the American Customer Satisfaction Index, our research team conducted a robust analysis spanning the years 2005 to 2020. The analysis revealed a striking correlation coefficient of 0.7797306 and a statistically significant p-value of less than 0.01, highlighting a compelling relationship between these seemingly disparate variables. While conventional wisdom may suggest a lack of connection between Eritrean gasoline consumption and the shopping experience at a popular American department store, our findings challenge these assumptions. The implications of this study extend beyond the realm of retail and energy economics, opening novel avenues for interdisciplinary inquiry and underscoring the unpredictable nature of consumer behavior and market dynamics.

[[LITERATURE REVIEW]]
Previous studies have delved into the relationship between seemingly incongruent variables, uncovering surprising connections in the labyrinth of consumer behavior and market dynamics. Smith et al. (2010) examined the correlation between national coffee consumption and the sales of lawnmowers, showcasing the intricate web of interdependence within the marketplace. Similarly, Doe and Jones (2015) conducted a comprehensive analysis of ice cream sales and the frequency of shark sightings at various coastal regions, shedding light on the enigmatic ties between summer treats and marine predators. These studies demonstrate the unforeseen alliances that can emerge within the realm of consumer preferences and economic phenomena.
In "The Economics of Energy Markets" by Brown and White (2018), the authors elucidate the multifaceted nature of energy consumption patterns, highlighting the complex interplay between environmental factors and consumer behavior. Drawing on empirical evidence, the book posits that the dynamics of gasoline consumption extend beyond straightforward supply and demand models, echoing the nuanced complexities that underpin our investigation.
In a departure from the traditional economic literature, the fictional works of "The Great Gatsby" by F. Scott Fitzgerald and "Confessions of a Shopaholic" by Sophie Kinsella offer nuanced glimpses into the world of luxury, desire, and unexpected encounters. While these texts may not directly address Eritrean gasoline consumption or customer satisfaction at Macy's, they speak to the underlying themes of consumer experience and the uncanny convergence of disparate elements.
Furthermore, popular internet memes such as "Distracted Boyfriend" and "Woman Yelling at a Cat" ironically encapsulate the unpredictability of human behavior and the serendipitous nature of interwoven narratives - a sentiment resonant with the unanticipated correlation under investigation. These cultural artifacts serve as tongue-in-cheek reminders of the inexplicable connections that permeate the fabric of consumer preferences and market dynamics.
As the literature on unconventional correlations and consumer behavior unfolds, our study seeks to contribute to this tapestry of unexpected revelations, shedding light on the underlying mechanisms that link Eritrean gasoline consumption to customer satisfaction at Macy's.

[[RESULTS]]
The analysis of the data revealed a notable correlation coefficient of 0.7797306 between the volume of gasoline pumped in Eritrea and customer satisfaction levels at Macy's, suggesting a stronger-than-expected relationship between these ostensibly unrelated variables. The r-squared value of 0.6079797 indicates that approximately 61% of the variation in customer satisfaction at Macy's can be explained by changes in gasoline consumption in Eritrea. Furthermore, the p-value of less than 0.01 attests to the statistical significance of this unexpected association, lending additional weight to the observed correlation.
The scatterplot in Figure 1 vividly illustrates the robust correlation between Eritrean gasoline consumption and customer satisfaction at Macy's, providing visual confirmation of the surprising connection. Each data point on the scatterplot serves as a poignant reminder that in the intricate dance of market forces, seemingly unrelated factors may perform a harmonious duet that defies conventional expectations.
The implications of these findings extend beyond the immediate scope of retail and energy economics, challenging established dogmas and inviting a reevaluation of the interconnectedness of seemingly disparate phenomena. The striking correlation uncovered in this study serves as a testament to the complexity inherent in consumer behavior and market dynamics, reminding us that beneath the seemingly ordinary lies a treasure trove of unexpected relationships and unforeseen patterns.
In conclusion, the bond between Eritrean gasoline consumption and customer contentment at Macy's showcases the enchanting unpredictability of the marketplace, inviting further exploration into the labyrinthine world of consumer behavior and economic interactions. This unexpected correlation testifies to the capricious nature of market forces, emphasizing the need for a nuanced understanding of the intricate web of connections that underpin the global marketplace.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

The results of this study provide compelling evidence of a significant and robust correlation between Eritrean gasoline consumption and customer satisfaction at Macy's. The unexpected strength of this relationship, as evidenced by the correlation coefficient of 0.7797306 and the statistically significant p-value of less than 0.01, challenges conventional assumptions about the disparate nature of these variables. This finding supports previous research that has unearthed surprising connections between unrelated phenomena, such as the link between national coffee consumption and lawnmower sales, and the correlation between ice cream sales and shark sightings at coastal regions.

The presence of such a strong correlation prompts a reconsideration of the intricacies of consumer behavior and market dynamics. It underscores the capricious nature of market forces and serves as a reminder of the serendipitous interwoven narratives that characterize the global marketplace.

The unexpected alliance between Eritrean gasoline consumption and customer satisfaction at Macy's may initially appear perplexing, akin to the baffling outcomes of internet memes such as "Distracted Boyfriend" and "Woman Yelling at a Cat." However, just as these cultural artifacts humorously encapsulate the unpredictability of human behavior, this correlation defies rigid expectations and calls for a deeper inquiry into the multifaceted tapestry of consumer preferences and economic phenomena.

The observed correlation extends beyond mere statistical significance to denote a larger narrative of intertwined fates and interdependent variables. The scatterplot visualization vividly illustrates the striking coherence between these ostensibly incongruous factors, prompting contemplation on the perplexing dance of market forces and the enigmatic ties that bind disparate elements.

In conclusion, the unexpected relationship between Eritrean gasoline consumption and customer contentment at Macy's asserts the unpredictable nature of market dynamics. It reinforces the need for a holistic understanding of the complex web of connections that underpin consumer behavior and economic interactions, underscoring the whimsicality inherent in the global marketplace.

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 Gasoline pumped in Eritrea and Customer satisfaction with Macy's. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
"Fueling Satisfaction: Examining the Unlikely Relationship Between Gasoline Pumped in Eritrea and Customer Contentment at Macy's"

[[ABSTRACT]]
This study explores the unexpected correlation between the volume of gasoline pumped in Eritrea and customer satisfaction levels at the renowned retail establishment, Macy's. Drawing on data from the Energy Information Administration and the American Customer Satisfaction Index, our research team conducted a robust analysis spanning the years 2005 to 2020. The analysis revealed a striking correlation coefficient of 0.7797306 and a statistically significant p-value of less than 0.01, highlighting a compelling relationship between these seemingly disparate variables. While conventional wisdom may suggest a lack of connection between Eritrean gasoline consumption and the shopping experience at a popular American department store, our findings challenge these assumptions. The implications of this study extend beyond the realm of retail and energy economics, opening novel avenues for interdisciplinary inquiry and underscoring the unpredictable nature of consumer behavior and market dynamics.

[[INTRDUCTION]]
The world of consumer behavior and market dynamics is a vast and complex tapestry, woven with countless threads of interconnected variables. From the price of tea in China to the yield of wheat in Kansas, the global marketplace is a web of hidden connections and unexpected correlations. In this vein, our research embarks on an unconventional exploration of the relationship between the seemingly disparate realms of gasoline consumption in Eritrea and customer satisfaction at the esteemed emporium known as Macy's.
While the link between these two variables may appear as incongruous as mismatched socks, our study endeavors to unravel the enigmatic bond that binds them. Drawing on data from the Energy Information Administration and the American Customer Satisfaction Index, our research spans a fifteen-year period from 2005 to 2020. Our curiosity was piqued by the initial observation of a potential association, and thus began our journey into the labyrinth of data analysis and statistical inference.
The unexpected nature of our findings compels us to reevaluate preconceived notions regarding consumer behavior and economic interplay. As we venture into uncharted territory, it becomes clear that the world of retail and energy economics is not as straightforward as a well-organized retail display or a precisely calibrated fuel pump. The intersection of these seemingly dissimilar worlds beckons us to delve deeper into the intricate mechanisms that shape consumer preferences and market dynamics.
Our investigation has yielded a striking correlation coefficient of 0.7797306 and a statistically significant p-value of less than 0.01, cementing the validity of the connection between Eritrean gasoline consumption and the satisfaction of patrons at Macy's. This unexpected revelation challenges conventional wisdom and beckons us to embrace the unpredictable nature of consumer behavior.
As we navigate through the underexplored terrain of these remarkable findings, our study not only contributes to the literature on retail and energy economics but also unveils hitherto undiscovered avenues for interdisciplinary inquiry. The implications of this research stretch far beyond the confines of the department store and the gas pump, calling for a reevaluation of traditional paradigms and prompting an appreciation of the capricious dance of market forces.
In essence, the unanticipated correlation between Eritrean gasoline consumption and customer contentment at Macy's serves as a testament to the unfathomable intricacies of the marketplace, reminding us that beneath the surface of apparent randomness, patterns may emerge, and surprises may abound. Our endeavor is not merely an exploration of statistical relationships but an ode to the unpredictability and fascination that underpin the world of consumer behavior and economic phenomena.

[[RESULTS]]
The analysis of the data revealed a notable correlation coefficient of 0.7797306 between the volume of gasoline pumped in Eritrea and customer satisfaction levels at Macy's, suggesting a stronger-than-expected relationship between these ostensibly unrelated variables. The r-squared value of 0.6079797 indicates that approximately 61% of the variation in customer satisfaction at Macy's can be explained by changes in gasoline consumption in Eritrea. Furthermore, the p-value of less than 0.01 attests to the statistical significance of this unexpected association, lending additional weight to the observed correlation.
The scatterplot in Figure 1 vividly illustrates the robust correlation between Eritrean gasoline consumption and customer satisfaction at Macy's, providing visual confirmation of the surprising connection. Each data point on the scatterplot serves as a poignant reminder that in the intricate dance of market forces, seemingly unrelated factors may perform a harmonious duet that defies conventional expectations.
The implications of these findings extend beyond the immediate scope of retail and energy economics, challenging established dogmas and inviting a reevaluation of the interconnectedness of seemingly disparate phenomena. The striking correlation uncovered in this study serves as a testament to the complexity inherent in consumer behavior and market dynamics, reminding us that beneath the seemingly ordinary lies a treasure trove of unexpected relationships and unforeseen patterns.
In conclusion, the bond between Eritrean gasoline consumption and customer contentment at Macy's showcases the enchanting unpredictability of the marketplace, inviting further exploration into the labyrinthine world of consumer behavior and economic interactions. This unexpected correlation testifies to the capricious nature of market forces, emphasizing the need for a nuanced understanding of the intricate web of connections that underpin the global marketplace.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In closing, the analysis of the connection between gasoline pumped in Eritrea and customer satisfaction at Macy's has unearthed an unexpected and compelling correlation, challenging conventional wisdom and underscoring the unpredictable nature of consumer behavior and market dynamics. The robust correlation coefficient of 0.7797306 and the statistically significant p-value of less than 0.01 defy the odds, much like stumbling upon a matching pair of socks in a dark laundry room.

The scatterplot in Figure 1 serves as a visual testament to the surprising synchrony between Eritrean gasoline consumption and customer contentment at Macy's, akin to an impromptu duet between distant acquaintances. These findings prompt a reconsideration of traditional paradigms and an appreciation of the kaleidoscopic dance of market forces, akin to stumbling upon unexpected treasures in the clearance section of a department store.

The unpredictability of these observations underscores the need for further exploration into the intricate mechanisms that govern consumer preferences and market dynamics. However, the illumination of this curious relationship between Eritrean gasoline consumption and customer satisfaction at Macy's presents a compelling case for the closure of further research in this avenue, akin to stumbling upon the perfect parking spot at a bustling shopping center.

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 Fueling Satisfaction: Examining the Unlikely Relationship Between Gasoline Pumped in Eritrea and Customer Contentment at Macy's. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of Retail Petrology

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 Fueling Satisfaction: Examining the Unlikely Relationship Between Gasoline Pumped in Eritrea and Customer Contentment at Macy's. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Global Gasoline Studies

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 Fueling Satisfaction: Examining the Unlikely Relationship Between Gasoline Pumped in Eritrea and Customer Contentment at Macy's with an abstract of This study explores the unexpected correlation between the volume of gasoline pumped in Eritrea and customer satisfaction levels at the renowned retail establishment, Macy's. Drawing on data from the Energy Information Administration and the American Customer Satisfaction Index, our research team conducted a robust analysis spanning the years 2005 to 2020. The analysis revealed a striking correlation coefficient of 0.7797306 and a statistically significant p-value of less than 0.01, highlighting a compelling relationship between these seemingly disparate variables. While conventional wisdom may suggest a lack of connection between Eritrean gasoline consumption and the shopping experience at a popular American department store, our findings challenge these assumptions. The implications of this study extend beyond the realm of retail and energy economics, opening novel avenues for interdisciplinary inquiry and underscoring the unpredictable nature of consumer behavior and market dynamics.

ChatGPT:

Eritrea, gasoline consumption, customer satisfaction, Macy's, retail, Energy Information Administration, American Customer Satisfaction Index, correlation coefficient, p-value, market dynamics, consumer behavior, interdisciplinary inquiry

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

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Data details

Gasoline pumped in Eritrea
Detailed data title: Volume of gasoline pumped consumed in Eritrea in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Gasoline pumped in Eritrea

Customer satisfaction with Macy's
Source: American Customer Satisfaction Index
See what else correlates with Customer satisfaction with Macy's

Correlation r = 0.7797306 (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 = 0.6079797 (Coefficient of determination)
This means 60.8% of the change in the one variable (i.e., Customer satisfaction with Macy's) is predictable based on the change in the other (i.e., Gasoline pumped in Eritrea) over the 16 years from 2005 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00037.^Show 0.0003682741365795315700000000
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 0.78 in 0.037% of random cases. Said differently, if you correlated 2,715 random variables^Note Which I absolutely did.
with the same 15 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 15 because we have two variables measured over a period of 16 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.

[ 0.46, 0.92 ] 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.

	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Gasoline pumped in Eritrea (Million Barrels/Day)	0.163589	0.116849	0.186959	0.11653	0.163589	0.210329	0.210329	0.233699	0.233699	0.257068	0.233698	0.23306	0.233699	0.233699	0.257068	0.245491
Customer satisfaction with Macy's (Consumer Satisfaction)	74	71	75	74	71	76	77	78	76	79	73	79	77	77	78	77

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([0.163589,0.116849,0.186959,0.11653,0.163589,0.210329,0.210329,0.233699,0.233699,0.257068,0.233698,0.23306,0.233699,0.233699,0.257068,0.245491,])
array_2 = np.array([74,71,75,74,71,76,77,78,76,79,73,79,77,77,78,77,])
array_1_name = "Gasoline pumped in Eritrea"
array_2_name = "Customer satisfaction with Macy's"

# 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 Gasoline pumped in Eritrea
Line chart for only Customer satisfaction with Macy's
The spurious research paper: Fueling Satisfaction: Examining the Unlikely Relationship Between Gasoline Pumped in Eritrea and Customer Contentment at Macy's

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Correlation ID: 1246 · Black Variable ID: 24388 · Red Variable ID: 19848


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