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## 12%

### 您將獲得的技能

StatisticsLinear RegressionR ProgrammingRegression Analysis

1

## About Linear Regression and Modeling

1 個視頻 （總計 2 分鐘）, 2 個閱讀材料
1 個視頻
2 個閱讀材料
More about Linear Regression and Modeling10分鐘

## Linear Regression

8 個視頻 （總計 47 分鐘）, 3 個閱讀材料, 2 個測驗
8 個視頻
Correlation9分鐘
Residuals1分鐘
Least Squares Line11分鐘
Prediction and Extrapolation3分鐘
Conditions for Linear Regression10分鐘
R Squared4分鐘
Regression with Categorical Explanatory Variables5分鐘
3 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Week 1 Suggested Readings and Practice10分鐘
2 個練習
Week 1 Practice Quiz8分鐘
Week 1 Quiz18分鐘
2

3 個視頻 （總計 24 分鐘）, 5 個閱讀材料, 3 個測驗
3 個視頻
Inference for Linear Regression11分鐘
Variability Partitioning5分鐘
5 個閱讀材料
Lesson Learning Objectives10分鐘
Week 2 Suggested Readings and Exercises10分鐘
Week 1 & 2 Lab Instructions (RStudio)10分鐘
Week 1 & 2 Lab Instructions (RStudio Cloud)10分鐘
3 個練習
Week 2 Practice Quiz6分鐘
Week 2 Quiz16分鐘
Week 1 & 2 Lab20分鐘
3

## Multiple Regression

7 個視頻 （總計 57 分鐘）, 5 個閱讀材料, 3 個測驗
7 個視頻
Multiple Predictors11分鐘
Collinearity and Parsimony3分鐘
Inference for MLR11分鐘
Model Selection11分鐘
Diagnostics for MLR7分鐘
5 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Week 3 Suggested Readings and Exercises10分鐘
Week 3 Lab Instructions (RStudio)10分鐘
Week 3 Lab Instructions (RStudio Cloud)10分鐘
3 個練習
Week 3 Practice Quiz16分鐘
Week 3 Quiz20分鐘
Week 3 Lab20分鐘
4

## Final Project

1 個閱讀材料, 1 個測驗
1 個閱讀材料
Project Files and Rubric10分鐘
4.7
189 條評論

### 來自Linear Regression and Modeling 的熱門評論

Very good course taught by Dr. Mine who is as always a very good teacher. The videos are very eloquent and easy to understand. Highly recommend it if you are looking for a basic refresher course.

I feel I'm running out of complement words for this course series. In conclusion, clear teaching, helpful project, and knowledgeable classmates that I can learn from through final project.

## 講師

#### Mine Çetinkaya-Rundel

Associate Professor of the Practice
Department of Statistical Science

## 關於 杜克大学

Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world....

## 關於 Statistics with R 專項課程

In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis. You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions....

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