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Introduction to Econometrics
Okay. So what exactly is Econometrics? At its core, Econometrics refers to the application of data science to primarily economic data. Econometricians (as they are often called) use methods like quantitative models, statistical tests, and even machine learning as a way to help uncover the stories that their data may hold. In Econometrics, you learn things about your data, and when you do, the hope is that you can use what you learn today to predict what you may learn tomorrow. Confused yet? No worries. In this course, we'll take everything step by step.
Things You Are Going To Need For This Video:
Article On Linear Interpolations
We recommend taking a look at primarily the first section of this article, which provides a solid explanation of exactly how linear interpolations work. The rest of the article is information that we did not cover, but if you want to learn more, maybe look into that as well!
Article On Cubic Spline Interpolations
This article provides an alternative explanation of what Cubic Spline Interpolations are. However, note that this article is also a bit more mathematically sophisticated, as Cubic Spline Interpolations is considered a more complex concept than Linear Interpolations. If you find yourself still confused after this article, try searching for videos or other articles along the lines of "Cubic Spline Interpolations Simply Explained." The article provided above also shows you how to perform Cubic Spline Interpolations in Python, which is something we recommend that you definitely look at when you have time to; in our videos, we performed Cubic Spline Interpolations only in R.
Code To Follow Along
(Make Sure You Follow the Comments In the Code to Correctly Export Your Data)
Kaggle Dataset
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