課程信息

13,440 次近期查看

學生職業成果

29%

完成這些課程後已開始新的職業生涯

29%

通過此課程獲得實實在在的工作福利
可分享的證書
完成後獲得證書
100% 在線
立即開始,按照自己的計劃學習。
第 3 門課程(共 5 門)
可靈活調整截止日期
根據您的日程表重置截止日期。
完成時間大約為15 小時
英語(English)
字幕:英語(English)

您將獲得的技能

Logistic RegressionData AnalysisPython ProgrammingRegression Analysis

學生職業成果

29%

完成這些課程後已開始新的職業生涯

29%

通過此課程獲得實實在在的工作福利
可分享的證書
完成後獲得證書
100% 在線
立即開始,按照自己的計劃學習。
第 3 門課程(共 5 門)
可靈活調整截止日期
根據您的日程表重置截止日期。
完成時間大約為15 小時
英語(English)
字幕:英語(English)

提供方

卫斯连大学 徽標

卫斯连大学

教學大綱 - 您將從這門課程中學到什麼

內容評分Thumbs Up93%(1,000 個評分)Info
1

1

完成時間為 3 小時

Introduction to Regression

完成時間為 3 小時
4 個視頻 (總計 25 分鐘), 5 個閱讀材料, 1 個測驗
4 個視頻
Lesson 2: Experimental Data6分鐘
Lesson 3: Confounding Variables8分鐘
Lesson 4: Introduction to Multivariate Methods6分鐘
5 個閱讀材料
Some Guidance for Learners New to the Specialization10分鐘
Getting Set up for Assignments10分鐘
Tumblr Instructions10分鐘
How to Write About Data10分鐘
Writing About Your Data: Example Assignment10分鐘
2

2

完成時間為 4 小時

Basics of Linear Regression

完成時間為 4 小時
8 個視頻 (總計 53 分鐘), 9 個閱讀材料, 1 個測驗
8 個視頻
SAS Lesson 2: Testing a Basic Linear Regression Mode6分鐘
SAS Lesson 3: Categorical Explanatory Variables5分鐘
Python Lesson 1: More on Confounding Variables6分鐘
Python Lesson 2: Testing a Basic Linear Regression Model8分鐘
Python Lesson 3: Categorical Explanatory Variables4分鐘
Lesson 4: Linear Regression Assumptions12分鐘
Lesson 5: Centering Explanatory Variables3分鐘
9 個閱讀材料
SAS or Python - Which to Choose?10分鐘
Getting Started with SAS10分鐘
Getting Started with Python10分鐘
Course Codebooks10分鐘
Course Data Sets10分鐘
Uploading Your Own Data to SAS10分鐘
SAS Program Code for Video Examples10分鐘
Python Program Code for Video Examples10分鐘
Outlier Decision Tree10分鐘
3

3

完成時間為 3 小時

Multiple Regression

完成時間為 3 小時
10 個視頻 (總計 68 分鐘), 2 個閱讀材料, 1 個測驗
10 個視頻
SAS Lesson 2: Confidence Intervals3分鐘
SAS Lesson 3: Polynomial Regression8分鐘
SAS Lesson 4: Evaluating Model Fit, pt. 15分鐘
SAS Lesson 5: Evaluating Model Fit, pt. 29分鐘
Python Lesson 1: Multiple Regression6分鐘
Python Lesson 2: Confidence Intervals3分鐘
Python Lesson 3: Polynomial Regression9分鐘
Python Lesson 4: Evaluating Model Fit, pt. 15分鐘
Python Lesson 5: Evaluating Model Fit, pt. 210分鐘
2 個閱讀材料
SAS Program Code for Video Examples10分鐘
Python Program Code for Video Examples10分鐘
4

4

完成時間為 4 小時

Logistic Regression

完成時間為 4 小時
7 個視頻 (總計 38 分鐘), 6 個閱讀材料, 1 個測驗
7 個視頻
Python Lesson 1: Categorical Explanatory Variables with More Than Two Categories6分鐘
Lesson 2: A Few Things to Keep in Mind2分鐘
SAS Lesson 3: Logistic Regression for a Binary Response Variable, pt 17分鐘
SAS Lesson 4: Logistic Regression for a Binary Response Variable, pt. 24分鐘
Python Lesson 3: Logistic Regression for a Binary Response Variable, pt. 17分鐘
Python Lesson 4: Logistic Regression for a Binary Response Variable, pt. 23分鐘
6 個閱讀材料
SAS Program Code for Video Examples10分鐘
Python Program Code for Video Examples10分鐘
Week 1 Video Credits10分鐘
Week 2 Video Credits10分鐘
Week 3 Video Credits10分鐘
Week 4 Video Credits10分鐘

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關於 数据分析和解释 專項課程

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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