Variable Selection, Model Validation, Nonlinear Regression

Variable Selection, Model Validation, Nonlinear Regression

本课程是 Advanced Statistical Techniques for Data Science 专项课程的一部分

位教师：Kiah Ong

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4个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

4个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将获得的技能

要了解的详细信息

可分享的证书

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作业

10 项作业

授课语言：英语（English）

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本课程是 Advanced Statistical Techniques for Data Science 专项课程专项课程的一部分

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该课程共有4个模块

If you have a technical background in mathematics/statistics/computer science/engineering and or are pursuing a career change to jobs or industries that are data-driven, this course is for you. Those industries might be finance, retail, tech, healthcare, government, or many others. The opportunity is endless.

This course will focus on getting you acquainted with the generalized linear model (GLM) through the examples of logistic and Poisson regression. You will also see how simple and multiple linear regression relates to GLM using the link function. We will also study a regression technique that is robust to having outliers in the data. Finally, we will learn how to perform model validation involving GLM. After this course, students will be able to: - Determine which regression models to use based on the nature of the response variable. - Use regression technique which is robust to the presence of outliers. - Perform generalized linear regression using R by identifying the correct link function. - Interpret and draw conclusions on the regression model. - Use R to perform statistical inference based on the regression models.

In this module, you will learn the differences between logistic regression and ordinary linear regression, how to obtain the regression parameters using the maximum likelihood method, and use R to compute the estimators of a linear regression model and give a probabilistic prediction of Y=1 given X=x’s. There is a lot to read, watch, and consume in this module so, let’s get started!

涵盖的内容

7个视频4篇阅读材料3个作业1个讨论话题

7个视频总计33分钟

Course Welcome 2分钟
Module 1 Introduction 1分钟
Lesson 1 Introduction 1分钟
Logistic Regression - Part 1 11分钟
Lesson 2 Introduction 1分钟
Logistic Regression Part II - Part 1 10分钟
Logistic Regression Part II - Part 2 8分钟

4篇阅读材料总计80分钟

Syllabus 10分钟
Video 22 Slides - Introduction to Logistic Regression Part I (pdf) 30分钟
Video 23 Slides - Introduction to Logistic Regression Part II (pdf) 30分钟
Module 1 Summary 10分钟

3个作业总计240分钟

Module 1 Summative Assessment 180分钟
Introduction to Logistic Regression Part I 30分钟
Intro to Logistic Regression Part II 30分钟

1个讨论话题总计10分钟

Meet and Greet Discussion 10分钟

In this module, you will learn the difference between Poisson regression and ordinary linear regression, how to obtain the regression parameters using the maximum likelihood method, use R to compute the estimators of a Poisson regression model and the generalized linear model, and the similarities between the linear, logistic, and Poisson regressions. There is a lot to read, watch, and consume in this module so, let’s get started!

涵盖的内容

6个视频3篇阅读材料3个作业

6个视频总计26分钟

Module 2 Introduction 1分钟
Lesson 3 Introduction 1分钟
Poisson Regression - Part 1 9分钟
Poisson Regression - Part 2 4分钟
Lesson 4 Introduction 1分钟
GLM 10分钟

3篇阅读材料总计70分钟

Video 24 Slides - Poisson Regression (pdf) 30分钟
Video 25 Slides - Generalized Linear Models (pdf) 30分钟
Module 2 Summary 10分钟

3个作业总计240分钟

Module 2 Summative Assessment 180分钟
Poisson Regression 30分钟
Generalized Linear Models 30分钟

In this module, you will learn how to modify the ordinary least squares method to make the regression model more robust to the effect of outliers and use R to compute the robust regression parameters using different M-estimators and perform model validations involving logistic regression. There is a lot to read, watch, and consume in this module so, let’s get started!

涵盖的内容

7个视频4篇阅读材料3个作业

7个视频总计45分钟

Module 3 Introduction 1分钟
Lesson 5 Introduction 1分钟
Robust Regression - Part 1 10分钟
Robust Regression - Part 2 12分钟
Lesson 6 Introduction 1分钟
Model Validations - Part 1 11分钟
Model Validations - Part 2 10分钟

4篇阅读材料总计80分钟

Video 26 Slides - Robust Regression (pdf) 30分钟
Video 27 Slides - Variable Selection and Model Validation (pdf) 30分钟
Module 3 Summary 10分钟
Insights from an Industry Leader: Learn More About Our Program 10分钟

3个作业总计240分钟

Module 3 Summative Assessment 180分钟
Robust Regression 30分钟
Variable Selection and Model Validation 30分钟

This module contains the summative course assessment that has been designed to evaluate your understanding of the course material and assess your ability to apply the knowledge you have acquired throughout the course.