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.
教学大纲 - 您将从这门课程中学到什么
周
1完成时间为 1 小时
Course Overview and Data Setup
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.
2 个视频 （总计 13 分钟）, 5 个阅读材料
5 个阅读材料
Learner Prerequisites10分钟
Choosing and Setting Up SAS Software for this Course10分钟
Follow These Instructions to Set Up Data for This Course (REQUIRED)30分钟
Completing Demos and Practices10分钟
Using Forums and Getting Help10分钟
完成时间为 3 小时
Introduction and Review of Concepts
In this module you learn about the models required to analyze different types of data and the difference between explanatory vs predictive modeling. Then you review fundamental statistical concepts, such as the sampling distribution of a mean, hypothesis testing, p-values, and confidence intervals. After reviewing these concepts, you apply one-sample and two-sample t tests to data to confirm or reject preconceived hypotheses.
17 个视频 （总计 41 分钟）, 2 个阅读材料, 9 个测验
17 个视频
Overview1分钟
Explanatory versus Predictive Modeling1分钟
Population Parameters and Sample Statistics1分钟
Normal (Gaussian) Distribution2分钟
Standard Error of the Mean51
Confidence Intervals2分钟
Statistical Hypothesis Test4分钟
p-Value: Effect Size and Sample Size Influence3分钟
Scenario48
Performing a t Test4分钟
Demo: Performing a One-Sample t Test Using PROC TTEST3分钟
Scenario1分钟
Assumptions for the Two-Sample t Test2分钟
Testing for Equal and Unequal Variances2分钟
Demo: Performing a Two-Sample t Test Using PROC TTEST4分钟
2 个阅读材料
Parameters and Statistics10分钟
Normal Distribution10分钟
9 个练习
Question 1.015分钟
Question 1.025分钟
Question 1.035分钟
Question 1.045分钟
Question 1.055分钟
Practice - Using PROC TTEST to Perform a One-Sample t Test20分钟
Question 1.065分钟
Practice - Using PROC TTEST to Compare Groups20分钟
Introduction and Review of Concepts30分钟
周
2完成时间为 4 小时
ANOVA and Regression
In this module you learn to use graphical tools that can help determine which predictors are likely or unlikely to be useful. Then you learn to augment these graphical explorations with correlation analyses that describe linear relationships between potential predictors and our response variable. After you determine potential predictors, tools like ANOVA and regression help you assess the quality of the relationship between the response and predictors.
29 个视频 （总计 70 分钟）, 2 个阅读材料, 14 个测验
29 个视频
Overview1分钟
Scenario58
Demo: Exploring Associations Using PROC SGPLOT1分钟
Identifying Associations in Linear Regression with Scatter Plots1分钟
Demo: Exploring Associations Using PROC SGSCATTER2分钟
Scenario56
The ANOVA Hypothesis1分钟
Partitioning Variability in ANOVA2分钟
Coefficient of Determination1分钟
F Statistic and Critical Values1分钟
The ANOVA Model2分钟
Demo: Performing a One-Way ANOVA Using PROC GLM6分钟
Scenario49
Multiple Comparison Methods2分钟
Tukey's and Dunnett's Multiple Comparison Methods1分钟
Diffograms and Control Plots1分钟
Demo: Performing a Post Hoc Pairwise Comparison Using PROC GLM6分钟
Scenario53
Using Correlation to Measure Relationships between Continuous Variables1分钟
Hypothesis Testing for a Correlation1分钟
Avoiding Common Errors When Interpreting Correlations5分钟
Demo: Producing Correlation Statistics and Scatter Plots Using PROC CORR6分钟
Scenario45
The Simple Linear Regression Model1分钟
How SAS Performs Simple Linear Regression1分钟
Comparing the Regression Model to a Baseline Model2分钟
Hypothesis Testing and Assumptions for Linear Regression1分钟
Demo: Performing Simple Linear Regression Using PROC REG7分钟
2 个阅读材料
What Does a CLASS Statement Do?10分钟
Correlation Analysis and Model Building10分钟
14 个练习
Question 2.015分钟
Question 2.025分钟
Question 2.035分钟
Question 2.045分钟
Practice - Performing a One-Way ANOVA20分钟
Question 2.055分钟
Question 2.065分钟
Practice - Using PROC GLM to Perform Post Hoc Parwise Comparisons20分钟
Question 2.075分钟
Question 2.085分钟
Practice - Describing the Relationship between Continuous Variables20分钟
Question 2.095分钟
Practice - Using PROC REG to Fit a Simple Linear Regression Model20分钟
ANOVA and Regression30分钟
周
3完成时间为 2 小时
More Complex Linear Models
In this module you expand the one-way ANOVA model to a two-factor analysis of variance and then extend simple linear regression to multiple regression with two predictors. After you understand the concepts of two-way ANOVA and multiple linear regression with two predictors, you'll have the skills to fit and interpret models with many variables.
13 个视频 （总计 43 分钟）, 1 个阅读材料, 5 个测验
13 个视频
Overview1分钟
Scenario1分钟
Demo: Performing a Two-Way ANOVA Using PROC GLM7分钟
Interactions3分钟
Demo: Performing a Two-Way ANOVA With an Interaction Using PROC GLM5分钟
Demo: Performing Post-Processing Analysis Using PROC PLM4分钟
Scenario44
The Multiple Linear Regression Model2分钟
Hypothesis Testing for Multiple Regression1分钟
Multiple Linear Regression versus Simple Linear Regression2分钟
Adjusted R-Square1分钟
Demo: Fitting a Multiple Linear Regression Model Using PROC REG7分钟
1 个阅读材料
The STORE Statement10分钟
5 个练习
Question 3.015分钟
Practice - Performing a Two-Way ANOVA Using PROC GLM20分钟
Question 3.025分钟
Practice - Performing Multiple Regression Using PROC REG20分钟
More Complex Linear Models30分钟
完成时间为 2 小时
Model Building and Effect Selection
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.
11 个视频 （总计 28 分钟）, 3 个阅读材料, 4 个测验
11 个视频
Overview47
Scenario1分钟
The All-Possible Regressions Approach to Model Building1分钟
The Stepwise Selection Approach to Model Building3分钟
Interpreting p-Values and Parameter Estimates2分钟
Demo: Performing Stepwise Regression Using PROC GLMSELECT7分钟
Scenario37
Information Criteria2分钟
Adjusted R-Square and Mallows' Cp56
Demo: Performing Model Selection Using PROC GLMSELECT5分钟
3 个阅读材料
Activity - Optional Stepwise Selection Method Code10分钟
Information Criteria Penalty Components10分钟
All-Possible Selection
4 个练习
Question 4.015分钟
Practice - Using PROC GLMSELECT to Perform Stepwise Selection20分钟
Practice - Using PROC GLMSELECT to Perform Other Model Selection Techniques20分钟
Model Building and Effect Selection20分钟
周
4完成时间为 3 小时
Model Post-Fitting for Inference
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.
18 个视频 （总计 46 分钟）, 7 个测验
18 个视频
Overview1分钟
Scenario40
Verifying Assumptions Using Residual Plots3分钟
Demo: Examining Residual Plots Using PROC REG5分钟
Scenario47
Identifying Influential Observations1分钟
Checking for Outliers with STUDENT Residuals1分钟
Checking for Influential Observations2分钟
Detecting Influential Observations with DFBETAS1分钟
Demo: Looking for Influential Observations Using PROC GLMSELECT and PROC REG5分钟
Demo: Examining the Influential Observations Using PROC PRINT6分钟
Handling Influential Observations1分钟
Scenario38
Exploring Collinearity1分钟
Visualizing Collinearity2分钟
Demo: Calculating Collinearity Diagnostics Using PROC REG5分钟
Using an Effective Modeling Cycle1分钟
7 个练习
Practice: Using PROC REG to Examine Residuals20分钟
Question 5.015分钟
Practice: Using PROC REG to Generate Potential Outliers20分钟
Question 5.025分钟
Question 5.035分钟
Practice: Using PROC REG to Assess Collinearity20分钟
Model Post-Fitting for Inference30分钟
完成时间为 2 小时
Model Building for Scoring and Prediction
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.
11 个视频 （总计 27 分钟）, 1 个阅读材料, 4 个测验
1 个阅读材料
Partitioning a Data Set Using PROC GLMSELECT10分钟
4 个练习
Question 6.015分钟
Practice: Building a Predictive Model Using PROC GLMSELECT20分钟
Practice: Scoring Using the SCORE Statement in PROC GLMSELECT20分钟
Model Building for Scoring and Prediction30分钟
4.9
5 个审阅来自Statistics with SAS的热门评论
This course is really fantastic!\n\nI love SAS, and I love analysis\n\nHope this will help me in my Ph. D studying career
讲师
Jordan Bakerman
Analytical Training ConsultantEducation
关于 SAS
Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.
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