Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following:
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Advanced Statistics for Data Science
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Über diesen Kurs
Kompetenzen, die Sie erwerben
- Statistics
- Linear Regression
- R Programming
- Linear Algebra
von

Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Lehrplan - Was Sie in diesem Kurs lernen werden
Background
We cover some basic matrix algebra results that we will need throughout the class. This includes some basic vector derivatives. In addition, we cover some some basic uses of matrices to create summary statistics from data. This includes calculating and subtracting means from observations (centering) as well as calculating the variance.
One and two parameter regression
In this module, we cover the basics of regression through the origin and linear regression. Regression through the origin is an interesting case, as one can build up all of multivariate regression with it.
Linear regression
In this lecture, we focus on linear regression, the most standard technique for investigating unconfounded linear relationships.
General least squares
We now move on to general least squares where an arbitrary full rank design matrix is fit to a vector outcome.
Bewertungen
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Top-Bewertungen von ADVANCED LINEAR MODELS FOR DATA SCIENCE 1: LEAST SQUARES
Good course. Quite hard. Linear algebra should be your second language as it is assumed to be mastered. Exams should include some personal work.
Great refresher of linear algebra understood many things about linear models that I just knew superficially from its cores
Excellent experience. I have learnt a lot in different aspect of linear models as well as the coding skills from this course. Thank you.
Hard Topic, You must take all the basics in multivariate statistical analysis first.
Über den Spezialisierung Advanced Statistics for Data Science
Fundamental concepts in probability, statistics and linear models are primary building blocks for data science work. Learners aspiring to become biostatisticians and data scientists will benefit from the foundational knowledge being offered in this specialization. It will enable the learner to understand the behind-the-scenes mechanism of key modeling tools in data science, like least squares and linear regression.

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