Spurious correlation #3,069 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Wind power generated in New Caledonia and the second variable is Wipro's stock price (WIT). The chart goes from 2002 to 2021, 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 Wind power generated in New Caledonia and the second variable is Wipro's stock price (WIT). The chart goes from 2002 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The strong gusts of wind carried whispers of Wipro's success across the seas, leading to a surge in investor confidence and a delightful whirlwind of stock price growth.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of modern wind turbines standing elegantly against the stunning backdrop of New Caledonia’s coastline. The turbines' sleek structures catch the eye as their blades spin gracefully in the strong ocean breeze. Meanwhile, a digital stock market ticker prominently displays Wipro's stock price (WIT), indicating a significant upward trend due to the surge in demand for the company's wind turbine division spurred by the increased wind power generation in New Caledonia. The image combines the serene beauty of nature with the cutting-edge advancements in green energy, creating a visually compelling scene with a vaporwave aesthetic. 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: Wind power generated in New Caledonia and Wipro's stock price (WIT). 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: Vaporwave Hyper-realistic Data cyber art a Polaroid photo Cutsy graphics
ChatGPT: Wind power generated in New Caledonia: Vaporwave

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 Wind power generated in New Caledonia and Wipro's stock price (WIT), in the following situation: Because the increased wind power in New Caledonia led to a surge in demand for wind turbines, causing Wipro's stock price to soar due to their lucrative wind turbine division.. Keep the description simple.
ChatGPT: A group of sleek, modern wind turbines stand tall and proud against the beautiful backdrop of New Caledonia's coastline, their blades spinning gracefully in the strong ocean breeze. Meanwhile, on a digital stock market ticker, Wipro's stock price (WIT) is displayed prominently, showing a significant upward trend, indicating a surge in demand for the company's wind turbine division due to the increased wind power generation in New Caledonia.

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: [ Wind power generated in New Caledonia: Vaporwave ] and depicting this scene: A group of sleek, modern wind turbines stand tall and proud against the beautiful backdrop of New Caledonia's coastline, their blades spinning gracefully in the strong ocean breeze. Meanwhile, on a digital stock market ticker, Wipro's stock price (WIT) is displayed prominently, showing a significant upward trend, indicating a surge in demand for the company's wind turbine division due to the increased wind power generation in New Caledonia. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of modern wind turbines standing elegantly against the stunning backdrop of New Caledonia’s coastline. The turbines' sleek structures catch the eye as their blades spin gracefully in the strong ocean breeze. Meanwhile, a digital stock market ticker prominently displays Wipro's stock price (WIT), indicating a significant upward trend due to the surge in demand for the company's wind turbine division spurred by the increased wind power generation in New Caledonia. The image combines the serene beauty of nature with the cutting-edge advancements in green energy, creating a visually compelling scene with a vaporwave aesthetic.

*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 Wind power generated in New Caledonia caused Wipro's stock price (WIT) to increase.

AI academic paper

(Because p < 0.01)

Blowin’ in the Wind: A Breezy Connection Between Wind Power in New Caledonia and Wipro's Stock Price

Journal of Renewable Energy Economics and Financial Analysis

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Wind power generated in New Caledonia and Wipro's stock price (WIT). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
Blowin’ in the Wind: A Breezy Connection Between Wind Power in New Caledonia and Wipro's Stock Price

[[ABSTRACT]]
In this study, we set out to investigate the relationship between the wind power generated in the beautiful New Caledonia and the stock price of Wipro (WIT). It's no surprise that we found ourselves blown away by the potential impact of wind power on the stock market!

Utilizing data from the Energy Information Administration and LSEG Analytics (Refinitiv), we embarked on this breezy journey. Our research team uncovered a rather impressive correlation coefficient of 0.8430493 and a statistically significant p-value of less than 0.01 for the period spanning from 2002 to 2021. This correlation was practically whooshing us off our feet!

As we delved deeper into the data, we couldn't help but notice how the wind power generation in New Caledonia seemed to be in synch with the fluctuations in Wipro's stock price. It's as if the wind was whispering stock market secrets to us, or perhaps it was just blowing hot air - it's hard to say for sure.

Our findings suggest a compelling relationship between wind power generation in New Caledonia and the movement of Wipro's stock price. This research sheds light on the potential impact of renewable energy sources on the financial market, proving that even the gentle breeze can have a noticeable effect on stock prices. One might say that this relationship really puts the "wind" in Wipro's sales!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of renewable energy and financial markets has always been a topic of great interest, and in recent years, the growing focus on sustainability has amplified the significance of this intersection. In this paper, we aim to explore the intriguing relationship between wind power generated in the picturesque New Caledonia and the stock price of Wipro (WIT).
Now, you might be wondering, "What's the connection between wind power and stock prices? Do they blow hot and cold, or are they just full of hot air?" These are exactly the questions that sparked our curiosity and led us to embark on this research journey. As the saying goes, with great puns comes great responsibility!
First and foremost, it's important to note that New Caledonia’s natural beauty and wind power potential provide the perfect backdrop for our study. The gentle breezes and refreshing gusts of wind not only attract kite surfers but also hold immense potential for renewable energy production. It's safe to say that New Caledonia isn't just a pretty place – it also has the power to make a big impact on the energy landscape.
As for Wipro, the India-based tech giant has always been a strong contender in the stock market. Its presence is as constant as the wind, and it's clear that investors are always "blown away" by its potential. Our investigation into the connection between wind power and Wipro's stock price aims to uncover whether there's more to this relationship than meets the "eye of the storm."
To conduct our analysis, we delved into data from the Energy Information Administration for wind power generation and tapped into the insights provided by LSEG Analytics (Refinitiv) for Wipro's stock price movements. Using statistical tools and methodologies, we set out to untangle the winds of correlation and causation, aiming to breeze through the complex web of data. After all, in the world of research, there's no such thing as "too much wind data" – it's always a breath of fresh air!
The findings of our study uncovered a remarkable correlation coefficient and a statistically significant p-value, providing evidence of a tangible link between wind power generation in New Caledonia and the stock performance of Wipro. It's as if the winds were whispering to the stock market, imparting their wisdom like the ancient wind spirits of lore. Or perhaps it's just a case of "wind manipulation" in the stock market – either way, the findings are nothing short of breezy intrigue!
In the following sections, we will delve further into the methodology employed, the intricacies of the data analysis, and the implications of our findings. So hold on to your hats and keep an eye on the wind, because we're about to take a gusty ride through the world of renewable energy and stock market surprises! After all, when it comes to research, the sky's the limit – especially when the wind is at our backs!

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The relationship between renewable energy sources and financial markets has been a subject of growing interest in academic and practitioner circles. Smith et al. (2018) highlighted the potential implications of wind power generation for stock market movements, shedding light on the tangible impact of natural forces on financial dynamics. However, as we probed deeper into this topic, we couldn't help but wonder - are these findings just full of hot air, or is there a breath of truth to this connection?

Doe (2020) delved into the intricate dance between renewable energy and financial markets, emphasizing the significance of incorporating sustainable energy sources into investment considerations. As we skimmed through Doe’s work, it became clear that the winds of change were indeed blowing across the financial landscape. Now, one might say that renewable energy and stock prices go together like the wind and a windmill – a perfect match that’s simply “fan-tastic!”

Moving away from purely academic literature, let's consider some popular non-fiction books that complement our study. "The Wonders of Wind Power" by John Green provides an accessible yet informative exploration of wind energy and its potential impact on various sectors, including finance. Meanwhile, "Blowing Away the Stock Market: The Wind Power Effect" by Jane Smith offers a captivating narrative on the intertwined nature of renewable energy and stock price movements. These titles not only offer valuable insights but also blow a breath of fresh air into the sometimes-dry world of research literature.

Now, let’s take a whimsical turn into the realm of fiction, where the fusion of wind power and stock markets takes on a whole new level of imagination. "The Wind in the Sales," a novel by A. Windstrom, takes readers on a wild ride through the turbulent world of renewable energy investments, blending adventure and finance in a gusty tale of intrigue. On a lighter note, "Gone with the Windmill" by Margaret Mitchell whimsically weaves a story of romance and stock market shenanigans amidst the backdrop of renewable energy developments. These imaginative titles add a touch of whimsy to our exploration, reminding us that the wind's influence can be as playful as it is powerful.

Now, for a delightful detour into the realm of internet memes, let's not forget the infamous "Invisible Windmill" meme, which humorously juxtaposes the invisibility of wind power with its palpable impact. This lighthearted take on wind energy reminds us that even in the midst of serious research, there's always room for a good ol’ fashioned chuckle.

As we weave through the scholarly, fictional, and playful representations of our research topic, it becomes increasingly apparent that the connection between wind power in New Caledonia and Wipro's stock price is not just a passing breeze. Our findings add another gust of evidence to this blooming field, showing that even the gentlest zephyr can sway the tides of the stock market. So, buckle up and brace yourselves – we're about to weather the winds of statistical analysis and financial whimsy in the upcoming sections!

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Wind power generated in New Caledonia and Wipro's stock price (WIT). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and LSEG Analytics (Refinitiv) . You used data from 2002 to 2021

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]]
Blowin’ in the Wind: A Breezy Connection Between Wind Power in New Caledonia and Wipro's Stock Price

[[ABSTRACT]]
In this study, we set out to investigate the relationship between the wind power generated in the beautiful New Caledonia and the stock price of Wipro (WIT). It's no surprise that we found ourselves blown away by the potential impact of wind power on the stock market!

Utilizing data from the Energy Information Administration and LSEG Analytics (Refinitiv), we embarked on this breezy journey. Our research team uncovered a rather impressive correlation coefficient of 0.8430493 and a statistically significant p-value of less than 0.01 for the period spanning from 2002 to 2021. This correlation was practically whooshing us off our feet!

As we delved deeper into the data, we couldn't help but notice how the wind power generation in New Caledonia seemed to be in synch with the fluctuations in Wipro's stock price. It's as if the wind was whispering stock market secrets to us, or perhaps it was just blowing hot air - it's hard to say for sure.

Our findings suggest a compelling relationship between wind power generation in New Caledonia and the movement of Wipro's stock price. This research sheds light on the potential impact of renewable energy sources on the financial market, proving that even the gentle breeze can have a noticeable effect on stock prices. One might say that this relationship really puts the "wind" in Wipro's sales!

[[INTRODUCTION]]
The intersection of renewable energy and financial markets has always been a topic of great interest, and in recent years, the growing focus on sustainability has amplified the significance of this intersection. In this paper, we aim to explore the intriguing relationship between wind power generated in the picturesque New Caledonia and the stock price of Wipro (WIT).
Now, you might be wondering, "What's the connection between wind power and stock prices? Do they blow hot and cold, or are they just full of hot air?" These are exactly the questions that sparked our curiosity and led us to embark on this research journey. As the saying goes, with great puns comes great responsibility!
First and foremost, it's important to note that New Caledonia’s natural beauty and wind power potential provide the perfect backdrop for our study. The gentle breezes and refreshing gusts of wind not only attract kite surfers but also hold immense potential for renewable energy production. It's safe to say that New Caledonia isn't just a pretty place – it also has the power to make a big impact on the energy landscape.
As for Wipro, the India-based tech giant has always been a strong contender in the stock market. Its presence is as constant as the wind, and it's clear that investors are always "blown away" by its potential. Our investigation into the connection between wind power and Wipro's stock price aims to uncover whether there's more to this relationship than meets the "eye of the storm."
To conduct our analysis, we delved into data from the Energy Information Administration for wind power generation and tapped into the insights provided by LSEG Analytics (Refinitiv) for Wipro's stock price movements. Using statistical tools and methodologies, we set out to untangle the winds of correlation and causation, aiming to breeze through the complex web of data. After all, in the world of research, there's no such thing as "too much wind data" – it's always a breath of fresh air!
The findings of our study uncovered a remarkable correlation coefficient and a statistically significant p-value, providing evidence of a tangible link between wind power generation in New Caledonia and the stock performance of Wipro. It's as if the winds were whispering to the stock market, imparting their wisdom like the ancient wind spirits of lore. Or perhaps it's just a case of "wind manipulation" in the stock market – either way, the findings are nothing short of breezy intrigue!
In the following sections, we will delve further into the methodology employed, the intricacies of the data analysis, and the implications of our findings. So hold on to your hats and keep an eye on the wind, because we're about to take a gusty ride through the world of renewable energy and stock market surprises! After all, when it comes to research, the sky's the limit – especially when the wind is at our backs!

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To capture the elusive dance of wind power and stock prices, we employed a series of rigorous yet whimsical research methods. Like a ship sailing through the wind-swept seas of data, our approach navigated the gusts and gales of information to uncover the hidden treasures of correlation and causation. We aimed to avoid getting "blown off course" and stay firmly anchored in the realm of scientific inquiry. We promise, despite the air of informality, this is not just a "breeze" through the methodological landscape.

First and foremost, our data collection process resembled a gentle, yet persistent, breeze. We harnessed the winds of the internet and collected data from various sources, with a predominant reliance on the Energy Information Administration and LSEG Analytics (Refinitiv). Our research team scoured through the virtual winds, sifting through the digital air currents to gather wind power generation data from the serene shores of New Caledonia and Wipro's stock price movements from 2002 to 2021. It was a bit like chasing after the wind, but with a whiff of statistical significance at the end of the chase!

Once we had hoisted the sails of data collection, we set our compass to navigate the choppy seas of statistical analysis. Our toolkit included the trusty correlation coefficient, a stalwart companion in the turbulent seas of data relationships. We also employed the gusty winds of regression analysis, allowing us to chart the course of wind power's influence on Wipro's stock price. We might say we were "blown away" by the statistical significance, but really, it was a more measured and scholarly reaction.

The statistical landscape was not without its storm clouds, of course. To ensure the robustness of our findings, we took into account not just the direction of the wind, but also the strength of its influence. Through various tests of significance and sensitivity analyses, we weathered the statistical tempests and emerged with results that could stand strong against the strongest of winds. It's a good thing we didn't rely on "volatile" statistics!

In tandem with the statistical analyses, we engaged in a qualitative assessment of the data, uncovering the nuances and subtleties of the relationship between wind power in New Caledonia and Wipro's stock price. This qualitative component was like the gentle rustle of leaves in the wind, adding depth and texture to our understanding of the breezy connection we sought to explore. After all, behind every correlation, there's a story waiting to be told - or in this case, whispered by the wind!

In the following sections, we'll delve deeper into the data analysis process, unraveling the intricate knot of wind power and stock market dynamics. So, fasten your seatbelts and secure your hats, because we're about to embark on a wind-swept journey through the heart of our research methods. After all, every good research methodology needs a "tailwind" to push it forward!

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

Please make up the results section of an academic research paper presenting the findings of the connection between Wind power generated in New Caledonia and Wipro's stock price (WIT). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and LSEG Analytics (Refinitiv) .

For the time period 2002 to 2021, you found a correlation 0.8430493, r-squared of 0.7107322, 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]]
Blowin’ in the Wind: A Breezy Connection Between Wind Power in New Caledonia and Wipro's Stock Price

[[ABSTRACT]]
In this study, we set out to investigate the relationship between the wind power generated in the beautiful New Caledonia and the stock price of Wipro (WIT). It's no surprise that we found ourselves blown away by the potential impact of wind power on the stock market!

Utilizing data from the Energy Information Administration and LSEG Analytics (Refinitiv), we embarked on this breezy journey. Our research team uncovered a rather impressive correlation coefficient of 0.8430493 and a statistically significant p-value of less than 0.01 for the period spanning from 2002 to 2021. This correlation was practically whooshing us off our feet!

As we delved deeper into the data, we couldn't help but notice how the wind power generation in New Caledonia seemed to be in synch with the fluctuations in Wipro's stock price. It's as if the wind was whispering stock market secrets to us, or perhaps it was just blowing hot air - it's hard to say for sure.

Our findings suggest a compelling relationship between wind power generation in New Caledonia and the movement of Wipro's stock price. This research sheds light on the potential impact of renewable energy sources on the financial market, proving that even the gentle breeze can have a noticeable effect on stock prices. One might say that this relationship really puts the "wind" in Wipro's sales!

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intersection of renewable energy and financial markets has always been a topic of great interest, and in recent years, the growing focus on sustainability has amplified the significance of this intersection. In this paper, we aim to explore the intriguing relationship between wind power generated in the picturesque New Caledonia and the stock price of Wipro (WIT).
Now, you might be wondering, "What's the connection between wind power and stock prices? Do they blow hot and cold, or are they just full of hot air?" These are exactly the questions that sparked our curiosity and led us to embark on this research journey. As the saying goes, with great puns comes great responsibility!
First and foremost, it's important to note that New Caledonia’s natural beauty and wind power potential provide the perfect backdrop for our study. The gentle breezes and refreshing gusts of wind not only attract kite surfers but also hold immense potential for renewable energy production. It's safe to say that New Caledonia isn't just a pretty place – it also has the power to make a big impact on the energy landscape.
As for Wipro, the India-based tech giant has always been a strong contender in the stock market. Its presence is as constant as the wind, and it's clear that investors are always "blown away" by its potential. Our investigation into the connection between wind power and Wipro's stock price aims to uncover whether there's more to this relationship than meets the "eye of the storm."
To conduct our analysis, we delved into data from the Energy Information Administration for wind power generation and tapped into the insights provided by LSEG Analytics (Refinitiv) for Wipro's stock price movements. Using statistical tools and methodologies, we set out to untangle the winds of correlation and causation, aiming to breeze through the complex web of data. After all, in the world of research, there's no such thing as "too much wind data" – it's always a breath of fresh air!
The findings of our study uncovered a remarkable correlation coefficient and a statistically significant p-value, providing evidence of a tangible link between wind power generation in New Caledonia and the stock performance of Wipro. It's as if the winds were whispering to the stock market, imparting their wisdom like the ancient wind spirits of lore. Or perhaps it's just a case of "wind manipulation" in the stock market – either way, the findings are nothing short of breezy intrigue!
In the following sections, we will delve further into the methodology employed, the intricacies of the data analysis, and the implications of our findings. So hold on to your hats and keep an eye on the wind, because we're about to take a gusty ride through the world of renewable energy and stock market surprises! After all, when it comes to research, the sky's the limit – especially when the wind is at our backs!

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis revealed a strong positive correlation between wind power generation in New Caledonia and the stock price of Wipro (WIT) for the time period of 2002 to 2021. The correlation coefficient of 0.8430493 indicates a robust relationship between these variables. It seems that when the wind in New Caledonia picked up, so did Wipro's stock price, blowing away any doubts about their connection.

Now, it's a "breeze," they said. But jokes aside, the r-squared value of 0.7107322 suggests that approximately 71.07% of the variability in Wipro's stock price can be explained by the variance in wind power generation in New Caledonia. It's almost as if Wipro's stock price was dancing in harmony with the wind, like a graceful leaf caught in a gusty waltz.

The p-value of less than 0.01 further emphasizes the statistical significance of this relationship, indicating that the observed correlation is unlikely to be a mere coincidence. This finding packs quite the punch, doesn't it? It's almost as if the wind in New Caledonia was saying, "I'm not just blowing hot air; I've got some serious stock market influence up my sleeve."

Fig. 1 displays a scatterplot illustrating the strong correlation between wind power generation in New Caledonia and Wipro's stock price. The points on the plot seem to form a pattern reminiscent of swirling winds, as if Mother Nature herself was giving us a subtle wink through the data.

In conclusion, our research findings provide compelling evidence of a notable association between wind power generation in New Caledonia and the stock performance of Wipro. This correlation highlights the potential impact of renewable energy sources on the financial market, demonstrating that sometimes, the winds of change can indeed blow in favor of stock prices.

As we wrap up this section, let me leave you with a thought: Renewable energy and stock prices may seem like a "breezy" match, but their interconnectedness is nothing to be taken lightly. After all, when it comes to the blend of science and finance, it's all about riding the winds of change – in both the data and the dad jokes!

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Wind power generated in New Caledonia and Wipro's stock price (WIT). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Blowin’ in the Wind: A Breezy Connection Between Wind Power in New Caledonia and Wipro's Stock Price

[[ABSTRACT]]
In this study, we set out to investigate the relationship between the wind power generated in the beautiful New Caledonia and the stock price of Wipro (WIT). It's no surprise that we found ourselves blown away by the potential impact of wind power on the stock market!

Utilizing data from the Energy Information Administration and LSEG Analytics (Refinitiv), we embarked on this breezy journey. Our research team uncovered a rather impressive correlation coefficient of 0.8430493 and a statistically significant p-value of less than 0.01 for the period spanning from 2002 to 2021. This correlation was practically whooshing us off our feet!

As we delved deeper into the data, we couldn't help but notice how the wind power generation in New Caledonia seemed to be in synch with the fluctuations in Wipro's stock price. It's as if the wind was whispering stock market secrets to us, or perhaps it was just blowing hot air - it's hard to say for sure.

Our findings suggest a compelling relationship between wind power generation in New Caledonia and the movement of Wipro's stock price. This research sheds light on the potential impact of renewable energy sources on the financial market, proving that even the gentle breeze can have a noticeable effect on stock prices. One might say that this relationship really puts the "wind" in Wipro's sales!

[[LITERATURE REVIEW]]
The relationship between renewable energy sources and financial markets has been a subject of growing interest in academic and practitioner circles. Smith et al. (2018) highlighted the potential implications of wind power generation for stock market movements, shedding light on the tangible impact of natural forces on financial dynamics. However, as we probed deeper into this topic, we couldn't help but wonder - are these findings just full of hot air, or is there a breath of truth to this connection?
Doe (2020) delved into the intricate dance between renewable energy and financial markets, emphasizing the significance of incorporating sustainable energy sources into investment considerations. As we skimmed through Doe’s work, it became clear that the winds of change were indeed blowing across the financial landscape. Now, one might say that renewable energy and stock prices go together like the wind and a windmill – a perfect match that’s simply “fan-tastic!”
Moving away from purely academic literature, let's consider some popular non-fiction books that complement our study. "The Wonders of Wind Power" by John Green provides an accessible yet informative exploration of wind energy and its potential impact on various sectors, including finance. Meanwhile, "Blowing Away the Stock Market: The Wind Power Effect" by Jane Smith offers a captivating narrative on the intertwined nature of renewable energy and stock price movements. These titles not only offer valuable insights but also blow a breath of fresh air into the sometimes-dry world of research literature.
Now, let’s take a whimsical turn into the realm of fiction, where the fusion of wind power and stock markets takes on a whole new level of imagination. "The Wind in the Sales," a novel by A. Windstrom, takes readers on a wild ride through the turbulent world of renewable energy investments, blending adventure and finance in a gusty tale of intrigue. On a lighter note, "Gone with the Windmill" by Margaret Mitchell whimsically weaves a story of romance and stock market shenanigans amidst the backdrop of renewable energy developments. These imaginative titles add a touch of whimsy to our exploration, reminding us that the wind's influence can be as playful as it is powerful.
Now, for a delightful detour into the realm of internet memes, let's not forget the infamous "Invisible Windmill" meme, which humorously juxtaposes the invisibility of wind power with its palpable impact. This lighthearted take on wind energy reminds us that even in the midst of serious research, there's always room for a good ol’ fashioned chuckle.
As we weave through the scholarly, fictional, and playful representations of our research topic, it becomes increasingly apparent that the connection between wind power in New Caledonia and Wipro's stock price is not just a passing breeze. Our findings add another gust of evidence to this blooming field, showing that even the gentlest zephyr can sway the tides of the stock market. So, buckle up and brace yourselves – we're about to weather the winds of statistical analysis and financial whimsy in the upcoming sections!

[[RESULTS]]
The analysis revealed a strong positive correlation between wind power generation in New Caledonia and the stock price of Wipro (WIT) for the time period of 2002 to 2021. The correlation coefficient of 0.8430493 indicates a robust relationship between these variables. It seems that when the wind in New Caledonia picked up, so did Wipro's stock price, blowing away any doubts about their connection.
Now, it's a "breeze," they said. But jokes aside, the r-squared value of 0.7107322 suggests that approximately 71.07% of the variability in Wipro's stock price can be explained by the variance in wind power generation in New Caledonia. It's almost as if Wipro's stock price was dancing in harmony with the wind, like a graceful leaf caught in a gusty waltz.
The p-value of less than 0.01 further emphasizes the statistical significance of this relationship, indicating that the observed correlation is unlikely to be a mere coincidence. This finding packs quite the punch, doesn't it? It's almost as if the wind in New Caledonia was saying, "I'm not just blowing hot air; I've got some serious stock market influence up my sleeve."
Fig. 1 displays a scatterplot illustrating the strong correlation between wind power generation in New Caledonia and Wipro's stock price. The points on the plot seem to form a pattern reminiscent of swirling winds, as if Mother Nature herself was giving us a subtle wink through the data.
In conclusion, our research findings provide compelling evidence of a notable association between wind power generation in New Caledonia and the stock performance of Wipro. This correlation highlights the potential impact of renewable energy sources on the financial market, demonstrating that sometimes, the winds of change can indeed blow in favor of stock prices.
As we wrap up this section, let me leave you with a thought: Renewable energy and stock prices may seem like a "breezy" match, but their interconnectedness is nothing to be taken lightly. After all, when it comes to the blend of science and finance, it's all about riding the winds of change – in both the data and the dad jokes!

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our findings align with the prior research that has hinted at the intriguing relationship between renewable energy sources and stock market dynamics. Just like a well-harnessed gust of wind, our results firmly support the notion that wind power generation in New Caledonia is no mere zephyr when it comes to influencing Wipro's stock price. (Dad joke incoming) You could say that this correlation is as clear as the wind in a wind tunnel!

As we hunker down into the nitty-gritty of our statistical analysis, it's clear that the breeze of evidence is blowing strongly in favor of a significant connection. The wind power generation in New Caledonia has exhibited a striking synchronicity with the movements of Wipro's stock price, almost as if their fates were intertwined by a cosmic breeze. (Here comes a pun) It's no wonder that the statistical significance practically knocked us off our feet – it seems the winds of correlation were stronger than a Category 5 hurricane!

The r-squared value and p-value further cement the robustness of this relationship, demonstrating that the variability in Wipro's stock price can be predominantly explained by the variance in wind power generation - it's as if Wipro's stock price and wind power generation were performing a ballet together, twirling in perfect statistical harmony. (A little more pun) This strong connection is truly a breath of fresh air in the world of finance and renewable energy research!

Now, this discussion wouldn't be complete without acknowledging our friendly scatterplot, which seems to whimsically mimic the swirls of a gentle breeze. The data points dance across the plot much like leaves caught in a playful wind, reminding us that even in the realm of statistics, there's room for nature's whimsy. (Here's a dad joke) It's almost like the data itself was whispering, "I'm not just a scatterplot; I've got some serious visualization skills!"

Finally, as we consider the larger implications of our findings, it's vital to recognize that the winds of change in renewable energy are more than mere blustery affairs - they hold tangible sway over the stock market. This research shines a light on the potential impact of renewable energy sources on financial markets, showcasing that the gentlest zephyr can make a noticeable impact on stock prices. It's as if wind power and stock prices were engaging in a pas de deux, twirling through the market's ever-changing landscape. (And a final dad joke) After all, in the world of finance and science, it's all about harnessing the winds of change – both the data and the dad jokes!

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Wind power generated in New Caledonia and Wipro's stock price (WIT). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Blowin’ in the Wind: A Breezy Connection Between Wind Power in New Caledonia and Wipro's Stock Price

[[ABSTRACT]]
In this study, we set out to investigate the relationship between the wind power generated in the beautiful New Caledonia and the stock price of Wipro (WIT). It's no surprise that we found ourselves blown away by the potential impact of wind power on the stock market!

Utilizing data from the Energy Information Administration and LSEG Analytics (Refinitiv), we embarked on this breezy journey. Our research team uncovered a rather impressive correlation coefficient of 0.8430493 and a statistically significant p-value of less than 0.01 for the period spanning from 2002 to 2021. This correlation was practically whooshing us off our feet!

As we delved deeper into the data, we couldn't help but notice how the wind power generation in New Caledonia seemed to be in synch with the fluctuations in Wipro's stock price. It's as if the wind was whispering stock market secrets to us, or perhaps it was just blowing hot air - it's hard to say for sure.

Our findings suggest a compelling relationship between wind power generation in New Caledonia and the movement of Wipro's stock price. This research sheds light on the potential impact of renewable energy sources on the financial market, proving that even the gentle breeze can have a noticeable effect on stock prices. One might say that this relationship really puts the "wind" in Wipro's sales!

[[INTRDUCTION]]
The intersection of renewable energy and financial markets has always been a topic of great interest, and in recent years, the growing focus on sustainability has amplified the significance of this intersection. In this paper, we aim to explore the intriguing relationship between wind power generated in the picturesque New Caledonia and the stock price of Wipro (WIT).
Now, you might be wondering, "What's the connection between wind power and stock prices? Do they blow hot and cold, or are they just full of hot air?" These are exactly the questions that sparked our curiosity and led us to embark on this research journey. As the saying goes, with great puns comes great responsibility!
First and foremost, it's important to note that New Caledonia’s natural beauty and wind power potential provide the perfect backdrop for our study. The gentle breezes and refreshing gusts of wind not only attract kite surfers but also hold immense potential for renewable energy production. It's safe to say that New Caledonia isn't just a pretty place – it also has the power to make a big impact on the energy landscape.
As for Wipro, the India-based tech giant has always been a strong contender in the stock market. Its presence is as constant as the wind, and it's clear that investors are always "blown away" by its potential. Our investigation into the connection between wind power and Wipro's stock price aims to uncover whether there's more to this relationship than meets the "eye of the storm."
To conduct our analysis, we delved into data from the Energy Information Administration for wind power generation and tapped into the insights provided by LSEG Analytics (Refinitiv) for Wipro's stock price movements. Using statistical tools and methodologies, we set out to untangle the winds of correlation and causation, aiming to breeze through the complex web of data. After all, in the world of research, there's no such thing as "too much wind data" – it's always a breath of fresh air!
The findings of our study uncovered a remarkable correlation coefficient and a statistically significant p-value, providing evidence of a tangible link between wind power generation in New Caledonia and the stock performance of Wipro. It's as if the winds were whispering to the stock market, imparting their wisdom like the ancient wind spirits of lore. Or perhaps it's just a case of "wind manipulation" in the stock market – either way, the findings are nothing short of breezy intrigue!
In the following sections, we will delve further into the methodology employed, the intricacies of the data analysis, and the implications of our findings. So hold on to your hats and keep an eye on the wind, because we're about to take a gusty ride through the world of renewable energy and stock market surprises! After all, when it comes to research, the sky's the limit – especially when the wind is at our backs!

[[RESULTS]]
The analysis revealed a strong positive correlation between wind power generation in New Caledonia and the stock price of Wipro (WIT) for the time period of 2002 to 2021. The correlation coefficient of 0.8430493 indicates a robust relationship between these variables. It seems that when the wind in New Caledonia picked up, so did Wipro's stock price, blowing away any doubts about their connection.
Now, it's a "breeze," they said. But jokes aside, the r-squared value of 0.7107322 suggests that approximately 71.07% of the variability in Wipro's stock price can be explained by the variance in wind power generation in New Caledonia. It's almost as if Wipro's stock price was dancing in harmony with the wind, like a graceful leaf caught in a gusty waltz.
The p-value of less than 0.01 further emphasizes the statistical significance of this relationship, indicating that the observed correlation is unlikely to be a mere coincidence. This finding packs quite the punch, doesn't it? It's almost as if the wind in New Caledonia was saying, "I'm not just blowing hot air; I've got some serious stock market influence up my sleeve."
Fig. 1 displays a scatterplot illustrating the strong correlation between wind power generation in New Caledonia and Wipro's stock price. The points on the plot seem to form a pattern reminiscent of swirling winds, as if Mother Nature herself was giving us a subtle wink through the data.
In conclusion, our research findings provide compelling evidence of a notable association between wind power generation in New Caledonia and the stock performance of Wipro. This correlation highlights the potential impact of renewable energy sources on the financial market, demonstrating that sometimes, the winds of change can indeed blow in favor of stock prices.
As we wrap up this section, let me leave you with a thought: Renewable energy and stock prices may seem like a "breezy" match, but their interconnectedness is nothing to be taken lightly. After all, when it comes to the blend of science and finance, it's all about riding the winds of change – in both the data and the dad jokes!

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In closing, it's crystal clear that the winds of New Caledonia are more than just a breath of fresh air - they've been whispering financial secrets to Wipro's stock price all along. This correlation is no fluke; it's as real as the wind blowing through the trees - or should I say, "through the WIT-ness stand" of the stock market? Oh, the winds of correlation, they're a-blowin' alright!

Our research has uncovered a connection between wind power and stock prices that is as strong as a gusty gale. It's almost as if the wind turbines are spinning a tale of stock market success, taking Wipro's stock price to new heights – and speaking of heights, have you heard about the crosswind tower that made wind energy profitable? It was really a high-flier!

With this comprehensive analysis, we can confidently say that there's no need to continue beating around the bush or blowing hot air. The evidence speaks for itself, and it's as compelling as a strong headwind. As the old saying goes, "When it comes to wind and Wipro, there's no need to reinvent the windmill." It's all right there in the data, folks!

In summary, the winds of New Caledonia and Wipro's stock price have formed a strong alliance - an alliance that shows no signs of dissipating. Studying this relationship has been an absolute whirlwind, but hey, the tides of research wait for no one! And speaking of tides, did you hear about the statistician who got stuck in the ocean while collecting data? He really underestimated the fluid dynamics!

In conclusion, our findings support the notion that the wind power in New Caledonia can indeed influence Wipro's stock price. It's time to set sail with the winds of research and let this study be the guiding light – or should I say, the guiding "gust" – for future investigations in this field.

And, with that, we confidently assert that no more research is needed in this area. Until the winds blow us in a new direction, this study stands tall and proud – just like a wind turbine on a breezy day!

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 Blowin’ in the Wind: A Breezy Connection Between Wind Power in New Caledonia and Wipro's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Renewable Energy Economics and Financial Analysis

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 Blowin’ in the Wind: A Breezy Connection Between Wind Power in New Caledonia and Wipro's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Renewable Energy Economics and Financial Analysis

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Blowin’ in the Wind: A Breezy Connection Between Wind Power in New Caledonia and Wipro's Stock Price with an abstract of In this study, we set out to investigate the relationship between the wind power generated in the beautiful New Caledonia and the stock price of Wipro (WIT). It's no surprise that we found ourselves blown away by the potential impact of wind power on the stock market!
Utilizing data from the Energy Information Administration and LSEG Analytics (Refinitiv), we embarked on this breezy journey. Our research team uncovered a rather impressive correlation coefficient of 0.8430493 and a statistically significant p-value of less than 0.01 for the period spanning from 2002 to 2021. This correlation was practically whooshing us off our feet!
As we delved deeper into the data, we couldn't help but notice how the wind power generation in New Caledonia seemed to be in synch with the fluctuations in Wipro's stock price. It's as if the wind was whispering stock market secrets to us, or perhaps it was just blowing hot air - it's hard to say for sure.
Our findings suggest a compelling relationship between wind power generation in New Caledonia and the movement of Wipro's stock price. This research sheds light on the potential impact of renewable energy sources on the financial market, proving that even the gentle breeze can have a noticeable effect on stock prices. One might say that this relationship really puts the "wind" in Wipro's sales!

ChatGPT:

wind power, New Caledonia, Wipro stock price, correlation analysis, renewable energy, stock market impact, Energy Information Administration, LSEG Analytics, Refinitiv, correlation coefficient, statistical significance, wind power generation, financial market, renewable energy sources

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

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Data details

Wind power generated in New Caledonia
Detailed data title: Total wind power generated in New Caledonia in billion kWh
Source: Energy Information Administration
See what else correlates with Wind power generated in New Caledonia

Wipro's stock price (WIT)
Detailed data title: Opening price of Wipro (WIT) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: ^{See full details} Via Microsoft Excel Stockhistory function

See what else correlates with Wipro's stock price (WIT)

Correlation r = 0.8430493 (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 = 0.7107322 (Coefficient of determination)
This means 71.1% of the change in the one variable (i.e., Wipro's stock price (WIT)) is predictable based on the change in the other (i.e., Wind power generated in New Caledonia) over the 20 years from 2002 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.06E-6.^Show 0.0000030595387903368100000000
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 0.84 in 0.000306% of random cases. Said differently, if you correlated 326,847 random variables^Note You don't actually need 326 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 19 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.64, 0.94 ] 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.

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Wind power generated in New Caledonia (Billion kWh)	0.008	0.005	0.01	0.02	0.03	0.04	0.03	0.03	0.051	0.046	0.057	0.052	0.057	0.062	0.045	0.045	0.045	0.057	0.049	0.0557002
Wipro's stock price (WIT) (Stock price)	1.22	1.15	1.64	2.51	2.46	3.31	3.01	1.66	4.56	5.2	3.49	2.98	4.68	4.32	4.26	3.59	4.13	3.8	3.75	5.78

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.

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([0.008,0.005,0.01,0.02,0.03,0.04,0.03,0.03,0.051,0.046,0.057,0.052,0.057,0.062,0.045,0.045,0.045,0.057,0.049,0.0557002,])
array_2 = np.array([1.22,1.15,1.64,2.51,2.46,3.31,3.01,1.66,4.56,5.2,3.49,2.98,4.68,4.32,4.26,3.59,4.13,3.8,3.75,5.78,])
array_1_name = "Wind power generated in New Caledonia"
array_2_name = "Wipro's stock price (WIT)"

# 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 Wind power generated in New Caledonia
Line chart for only Wipro's stock price (WIT)
AI-generated correlation image
The spurious research paper: Blowin’ in the Wind: A Breezy Connection Between Wind Power in New Caledonia and Wipro's Stock Price

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Correlation ID: 3069 · Black Variable ID: 23853 · Red Variable ID: 1851


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