课程信息
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第 3 门课程(共 5 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

完成时间大约为15 小时

建议:4 weeks, 4 - 5 hours per week...

英语(English)

字幕:英语(English)

您将获得的技能

Logistic RegressionData AnalysisPython ProgrammingRegression Analysis

第 3 门课程(共 5 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

完成时间大约为15 小时

建议:4 weeks, 4 - 5 hours per week...

英语(English)

字幕:英语(English)

学习Course的学生是

  • Data Scientists
  • Data Analysts
  • Business Analysts
  • Scientists
  • Data Engineers

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 3 小时

Introduction to Regression

4 个视频 (总计 25 分钟), 5 个阅读材料, 1 个测验
4 个视频
Lesson 2: Experimental Data6分钟
Lesson 3: Confounding Variables8分钟
Lesson 4: Introduction to Multivariate Methods6分钟
5 个阅读材料
Some Guidance for Learners New to the Specialization10分钟
Getting Set up for Assignments10分钟
Tumblr Instructions10分钟
How to Write About Data10分钟
Writing About Your Data: Example Assignment10分钟
2
完成时间为 4 小时

Basics of Linear Regression

8 个视频 (总计 53 分钟), 9 个阅读材料, 1 个测验
8 个视频
SAS Lesson 2: Testing a Basic Linear Regression Mode6分钟
SAS Lesson 3: Categorical Explanatory Variables5分钟
Python Lesson 1: More on Confounding Variables6分钟
Python Lesson 2: Testing a Basic Linear Regression Model8分钟
Python Lesson 3: Categorical Explanatory Variables4分钟
Lesson 4: Linear Regression Assumptions12分钟
Lesson 5: Centering Explanatory Variables3分钟
9 个阅读材料
SAS or Python - Which to Choose?10分钟
Getting Started with SAS10分钟
Getting Started with Python10分钟
Course Codebooks10分钟
Course Data Sets10分钟
Uploading Your Own Data to SAS10分钟
SAS Program Code for Video Examples10分钟
Python Program Code for Video Examples10分钟
Outlier Decision Tree10分钟
3
完成时间为 3 小时

Multiple Regression

10 个视频 (总计 68 分钟), 2 个阅读材料, 1 个测验
10 个视频
SAS Lesson 2: Confidence Intervals3分钟
SAS Lesson 3: Polynomial Regression8分钟
SAS Lesson 4: Evaluating Model Fit, pt. 15分钟
SAS Lesson 5: Evaluating Model Fit, pt. 29分钟
Python Lesson 1: Multiple Regression6分钟
Python Lesson 2: Confidence Intervals3分钟
Python Lesson 3: Polynomial Regression9分钟
Python Lesson 4: Evaluating Model Fit, pt. 15分钟
Python Lesson 5: Evaluating Model Fit, pt. 210分钟
2 个阅读材料
SAS Program Code for Video Examples10分钟
Python Program Code for Video Examples10分钟
4
完成时间为 4 小时

Logistic Regression

7 个视频 (总计 38 分钟), 6 个阅读材料, 1 个测验
7 个视频
Python Lesson 1: Categorical Explanatory Variables with More Than Two Categories6分钟
Lesson 2: A Few Things to Keep in Mind2分钟
SAS Lesson 3: Logistic Regression for a Binary Response Variable, pt 17分钟
SAS Lesson 4: Logistic Regression for a Binary Response Variable, pt. 24分钟
Python Lesson 3: Logistic Regression for a Binary Response Variable, pt. 17分钟
Python Lesson 4: Logistic Regression for a Binary Response Variable, pt. 23分钟
6 个阅读材料
SAS Program Code for Video Examples10分钟
Python Program Code for Video Examples10分钟
Week 1 Video Credits10分钟
Week 2 Video Credits10分钟
Week 3 Video Credits10分钟
Week 4 Video Credits10分钟
4.4
48 个审阅Chevron Right

40%

完成这些课程后已开始新的职业生涯

40%

通过此课程获得实实在在的工作福利

来自回归建模实践的热门评论

创建者 VMMar 7th 2017

Awesome course. More than regression generation, they have explained in details about how to interpret regression coefficients and results and how to make conclusions. 5 Stars

创建者 PCNov 28th 2016

This was a great course. I've done a few in the area of stats, regression and machine learning now and the Wesleyan ones are the most well-rounded of all of them

讲师

Avatar

Jen Rose

Research Professor
Psychology
Avatar

Lisa Dierker

Professor
Psychology

关于 卫斯连大学

At Wesleyan, distinguished scholar-teachers work closely with students, taking advantage of fluidity among disciplines to explore the world with a variety of tools. The university seeks to build a diverse, energetic community of students, faculty, and staff who think critically and creatively and who value independence of mind and generosity of spirit. ...

关于 数据分析和解释 专项课程

Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions. The Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights. In the Capstone Project, you will use real data to address an important issue in society, and report your findings in a professional-quality report. You will have the opportunity to work with our industry partners, DRIVENDATA and The Connection. Help DRIVENDATA solve some of the world's biggest social challenges by joining one of their competitions, or help The Connection better understand recidivism risk for people on parole in substance use treatment. Regular feedback from peers will provide you a chance to reshape your question. This Specialization is designed to help you whether you are considering a career in data, work in a context where supervisors are looking to you for data insights, or you just have some burning questions you want to explore. No prior experience is required. By the end you will have mastered statistical methods to conduct original research to inform complex decisions....
数据分析和解释

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