Regression Modeling Fundamentals

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Regression Modeling Fundamentals

本课程是 SAS Statistical Business Analyst 专业证书的一部分

位教师：Jordan Bakerman

8,384 人已注册

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5个模块

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5个模块

深入了解一个主题并学习基础知识。

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作业

33 项作业

授课语言：英语（English）

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积累 Data Analysis 领域的专业知识

本课程是 SAS Statistical Business Analyst 专业证书专项课程的一部分

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该课程共有5个模块

This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on t tests, ANOVA, and linear regression, and includes a brief introduction to logistic regression.

In this module you learn about the course and the data you analyze in this course. Then you set up the data you need to do the practices in the course.

涵盖的内容

2个视频6篇阅读材料

2个视频总计13分钟

Welcome and Meet the Instructor 2分钟
Demo: Exploring Ames Housing Data 11分钟

6篇阅读材料总计66分钟

Learner Prerequisites 1分钟
Access SAS Software for this Course 10分钟
Follow These Instructions to Set Up Data for This Course 30分钟
Completing Demos and Practices 10分钟
Using Forums and Getting Help 5分钟
Frequently Asked Questions 10分钟

In this module you explore several tools for model selection. These tools help limit the number of candidate models so that you can choose an appropriate model that's based on your expertise and research priorities.

涵盖的内容

11个视频3篇阅读材料4个作业

11个视频总计28分钟

Overview 1分钟
Scenario 1分钟
Approaches to Selecting Models 2分钟
The All-Possible Regressions Approach to Model Building 1分钟
The Stepwise Selection Approach to Model Building 3分钟
Interpreting p-Values and Parameter Estimates 2分钟
Demo: Performing Stepwise Regression Using PROC GLMSELECT 8分钟
Scenario 1分钟
Information Criteria 2分钟
Adjusted R-Square and Mallows' Cp 1分钟
Demo: Performing Model Selection Using PROC GLMSELECT 6分钟

3篇阅读材料总计20分钟

Activity - Optional Stepwise Selection Method Code 10分钟
Information Criteria Penalty Components 10分钟
All-Possible Selection 0分钟

4个作业总计65分钟

Question 4.01 5分钟
Practice - Using PROC GLMSELECT to Perform Stepwise Selection 20分钟
Practice - Using PROC GLMSELECT to Perform Other Model Selection Techniques 20分钟
Model Building and Effect Selection 20分钟

In this module you learn to verify the assumptions of the model and diagnose problems that you encounter in linear regression. You learn to examine residuals, identify outliers that are numerically distant from the bulk of the data, and identify influential observations that unduly affect the regression model. Finally, you learn to diagnose collinearity to avoid inflated standard errors and parameter instability in the model.

涵盖的内容

18个视频7个作业

18个视频总计46分钟

Overview 1分钟
Scenario 1分钟
Assumptions for Regression 2分钟
Verifying Assumptions Using Residual Plots 3分钟
Demo: Examining Residual Plots Using PROC REG 5分钟
Scenario 1分钟
Identifying Influential Observations 1分钟
Checking for Outliers with STUDENT Residuals 1分钟
Checking for Influential Observations 3分钟
Detecting Influential Observations with DFBETAS 1分钟
Demo: Looking for Influential Observations Using PROC GLMSELECT and PROC REG 5分钟
Demo: Examining the Influential Observations Using PROC PRINT 7分钟
Handling Influential Observations 2分钟
Scenario 1分钟
Exploring Collinearity 2分钟
Visualizing Collinearity 2分钟
Demo: Calculating Collinearity Diagnostics Using PROC REG 5分钟
Using an Effective Modeling Cycle 2分钟

7个作业总计105分钟

Practice: Using PROC REG to Examine Residuals 20分钟
Question 5.01 5分钟
Practice: Using PROC REG to Generate Potential Outliers 20分钟
Question 5.02 5分钟
Question 5.03 5分钟
Practice: Using PROC REG to Assess Collinearity 20分钟
Model Post-Fitting for Inference 30分钟

In this module you learn how to transition from inferential statistics to predictive modeling. Instead of using p-values, you learn about assessing models using honest assessment. After you choose the best performing model, you learn about ways to deploy the model to predict new data.

涵盖的内容

11个视频1篇阅读材料4个作业

11个视频总计27分钟

Overview 2分钟
Scenario 0分钟
Predictive Modeling Terminology 2分钟
Model Complexity 1分钟
Building a Predictive Model 3分钟
Model Assessment and Selection 2分钟
Demo: Building a Predictive Model Using PROC GLMSELECT 11分钟
Scenario 0分钟
Preparing for Scoring 1分钟
Methods of Scoring 1分钟
Demo: Scoring Data Using PROC PLM 4分钟

1篇阅读材料总计10分钟

Partitioning a Data Set Using PROC GLMSELECT 10分钟

4个作业总计75分钟

Question 6.01 5分钟
Practice: Building a Predictive Model Using PROC GLMSELECT 20分钟
Practice: Scoring Using the SCORE Statement in PROC GLMSELECT 20分钟
Model Building for Scoring and Prediction 30分钟

In this module you look for associations between predictors and a binary response using hypothesis tests. Then you build a logistic regression model and learn about how to characterize the relationship between the response and predictors. Finally, you learn how to use logistic regression to build a model, or classifier, to predict unknown cases.

涵盖的内容

25个视频18个作业

25个视频总计73分钟

Overview 2分钟
Scenario 1分钟
Associations between Categorical Variables 2分钟
Demo: Examining the Distribution of Categorical Variables Using PROC FREQ and PROC UNIVARIATE 6分钟
Scenario 1分钟
The Pearson Chi-Square Test 3分钟
Odds Ratios 4分钟
Demo: Performing a Pearson Chi-Square Test of Association Using PROC FREQ 5分钟
Scenario 0分钟
The Mantel-Haenszel Chi-Square Test 1分钟
The Spearman Correlation Statistic 1分钟
Demo: Detecting Ordinal Associations Using PROC FREQ 2分钟
Scenario 1分钟
Modeling a Binary Response 4分钟
Demo: Fitting a Binary Logistic Regression Model Using PROC LOGISTIC 7分钟
Interpreting the Odds Ratio 3分钟
Comparing Pairs to Assess the Fit of a Logistic Regression Model 5分钟
Scenario 1分钟
Specifying a Parameterization Method 5分钟
Demo: Fitting a Multiple Logistic Regression Model with Categorical Predictors Using PROC LOGISTIC 7分钟
Scenario 1分钟
Interactions between Variables 2分钟
Demo: Fitting a Multiple Logistic Regression Model with Interactions Using PROC LOGISTIC 4分钟
Demo: Fitting a Multiple Logistic Regression Model with All Odds Ratios Using PROC LOGISTIC 3分钟
Demo: Generating Predictions Using PROC PLM 2分钟

18个作业总计190分钟

Question 7.01 5分钟
Question 7.02 5分钟
Practice: Using PROC FREQ to Examine Distributions 20分钟
Question 7.03 5分钟
Question 7.04 5分钟
Question 7.05 5分钟
Question 7.06 5分钟
Practice: Using PROC FREQ to Perform Tests and Measures of Association 20分钟
Question 7.07 5分钟
Question 7.08 5分钟
Practice: Using PROC LOGISTIC to Perform a Binary Logistic Regression Analysis 20分钟
Question 7.09 5分钟
Question 7.10 5分钟
Practice: Using PROC LOGISTIC to Perform a Multiple Logistic Regression Analysis with Categorical Variables 20分钟
Question 7.11 5分钟
Question 7.12 5分钟
Practice: Using PROC LOGISTIC to Perform Backward Elimination and PROC PLM to Generate Predictions 20分钟
Categorical Data Analysis 30分钟

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位教师

授课教师评分

(11个评价)

Jordan Bakerman

SAS

4 门课程 61,148 名学生

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学生评论

5 stars
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4 stars
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3 stars
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2 stars
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1 star
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已于 Jun 14, 2021审阅

Thanks so much to our instructor, Jordan Bakerman for teaching this course!

已于 Feb 13, 2021审阅

Great Study material & Ease of understanding of the concepts.

已于 Jan 25, 2021审阅

Must have taken the prior Course. In the Specialization.

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