課程信息
4.7
25 ratings
2 reviews
Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. 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....
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100% 在線課程

立即開始,按照自己的計劃學習。
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Advanced Level

高級

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建議:6 weeks of study, 1-2 hours/week

完成時間大約為9 小時
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English

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Globe

100% 在線課程

立即開始,按照自己的計劃學習。
Calendar

可靈活調整截止日期

根據您的日程表重置截止日期。
Advanced Level

高級

Clock

建議:6 weeks of study, 1-2 hours/week

完成時間大約為9 小時
Comment Dots

English

字幕:English

教學大綱 - 您將從這門課程中學到什麼

1

章節
Clock
完成時間為 2 小時

Introduction and expected values

In this module, we cover the basics of the course as well as the prerequisites. We then cover the basics of expected values for multivariate vectors. We conclude with the moment properties of the ordinary least squares estimates. ...
Reading
7 個視頻(共 38 分鐘), 3 個閱讀材料, 1 個測驗
Video7 個視頻
Multivariate expected values, the basics4分鐘
Expected values, matrix operations2分鐘
Multivariate variances and covariances5分鐘
Multivariate covariance and variance matrix operations5分鐘
Expected values of quadratic forms3分鐘
Expected value properties of least squares estimates13分鐘
Reading3 個閱讀材料
Welcome to the class10分鐘
Course textbook10分鐘
Introduction to expected values10分鐘
Quiz1 個練習
Expected Values30分鐘

2

章節
Clock
完成時間為 1 小時

The multivariate normal distribution

In this module, we build up the multivariate and singular normal distribution by starting with iid normals....
Reading
4 個視頻(共 31 分鐘), 2 個閱讀材料, 1 個測驗
Video4 個視頻
The singular normal distribution7分鐘
Normal likelihoods5分鐘
Normal conditional distributions8分鐘
Reading2 個閱讀材料
Introduction to the multivariate normal10分鐘
A note on the last quiz question.10分鐘
Quiz1 個練習
the multivariate normal20分鐘

3

章節
Clock
完成時間為 1 小時

Distributional results

In this module, we build the basic distributional results that we see in multivariable regression....
Reading
8 個視頻(共 60 分鐘), 1 個閱讀材料, 1 個測驗
Video8 個視頻
Confidence intervals for regression coefficients6分鐘
F distribution4分鐘
Coding example7分鐘
Prediction intervals11分鐘
Coding example5分鐘
Confidence ellipsoids7分鐘
Coding example6分鐘
Reading1 個閱讀材料
Distributional results10分鐘
Quiz1 個練習
Distributional results20分鐘

4

章節
Clock
完成時間為 1 小時

Residuals

In this module we will revisit residuals and consider their distributional results. We also consider the so-called PRESS residuals and show how they can be calculated without re-fitting the model....
Reading
4 個視頻(共 32 分鐘), 2 個閱讀材料, 1 個測驗
Video4 個視頻
Code demonstration3分鐘
Leave one out residuals8分鐘
Press residuals14分鐘
Reading2 個閱讀材料
Residuals10分鐘
Thanks for taking the course10分鐘
Quiz1 個練習
Residuals14分鐘
4.7

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創建者 MLJan 31st 2017

Good course on applied linear statistical modeling.

講師

Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

關於 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....

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  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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