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:
- A basic understanding of linear algebra and multivariate calculus.
- A basic understanding of statistics and regression models.
- At least a little familiarity with proof based mathematics.
- Basic knowledge of the R programming language.
After taking this course, students will have a firm foundation in a linear algebraic treatment of regression modeling. This will greatly augment applied data scientists' general understanding of regression models.
教学大纲 - 您将从这门课程中学到什么
周
1Background
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.
7 个视频 （总计 28 分钟）, 4 个阅读材料, 1 个测验
7 个视频
Introduction2分钟
Matrix derivatives5分钟
Coding example2分钟
Centering by matrix multiplication6分钟
Coding example2分钟
Variance via matrix multiplication6分钟
Coding example2分钟
4 个阅读材料
Welcome to the class10分钟
Course textbook10分钟
Grading10分钟
In this module10分钟
1 个练习
Background Quiz12分钟
周
2One 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.
6 个视频 （总计 29 分钟）, 2 个阅读材料, 1 个测验
6 个视频
Centering first8分钟
Coding example1分钟
Connection with linear regression7分钟
Coding example1分钟
Fitted values and residuals4分钟
2 个阅读材料
Before you begin10分钟
Before you begin10分钟
1 个练习
One Parameter Regression Quiz10分钟
周
3Linear regression
In this lecture, we focus on linear regression, the most standard technique for investigating unconfounded linear relationships.
8 个视频 （总计 23 分钟）, 2 个阅读材料, 1 个测验
8 个视频
Coding example1分钟
Prediction2分钟
Coding example2分钟
Residuals2分钟
Coding example1分钟
Generalizations6分钟
Generalizations example2分钟
2 个阅读材料
Before you begin10分钟
Generalizations10分钟
1 个练习
Linear Regression Quiz12分钟
周
4General least squares
We now move on to general least squares where an arbitrary full rank design matrix is fit to a vector outcome.
6 个视频 （总计 39 分钟）, 1 个阅读材料, 1 个测验
6 个视频
Coding example3分钟
Second derivation of least squares4分钟
Projections9分钟
Third derivation of least squares12分钟
Coding example4分钟
1 个阅读材料
Before you begin10分钟
1 个练习
General Least Squares Quiz20分钟
4.4
21 个审阅热门审阅
创建者 DL•Jun 8th 2016
We need more advanced, theoretical courses on Coursera, like this one, in order to deeply understand the more general courses like Regression Models and Linear Models.
创建者 SP•Apr 30th 2017
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.
讲师
Brian Caffo, PhD
Professor, BiostatisticsBloomberg School of Public Health
关于 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.
常见问题
我什么时候能够访问课程视频和作业？
注册以便获得证书后，您将有权访问所有视频、测验和编程作业（如果适用）。只有在您的班次开课之后，才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程，可能无法访问某些作业。
我购买证书后会得到什么？
您购买证书后，将有权访问所有课程材料，包括评分作业。完成课程后，您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
退款政策是如何规定的？
有助学金吗？
还有其他问题吗？请访问 学生帮助中心。
