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:
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課程信息
您將獲得的技能
- Statistics
- Linear Regression
- R Programming
- Linear Algebra
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约翰霍普金斯大学
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.
授課大綱 - 您將從這門課程中學到什麼
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.
審閱
- 5 stars60.35%
- 4 stars26.62%
- 3 stars8.28%
- 2 stars3.55%
- 1 star1.18%
來自ADVANCED LINEAR MODELS FOR DATA SCIENCE 1: LEAST SQUARES的熱門評論
As the name says it's an advanced course. Take the challenge though! In my opinion the content is a must if you want to perform competently in data science.
Hard Topic, You must take all the basics in multivariate statistical analysis first.
Very thorough and rigorous. A great review for me.
Good mathematical rigour for the analysis of linear models. Builds some good intuition for the geometry of least squares which helps in model result interpretation.
關於 Advanced Statistics for Data Science 專項課程
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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