Statistics I: Basic ANOVA, Regression and Logistic Regression

Duration: 3.0 days CEUs: 1.8

AUDIENCE
This course is designed for analysts and statisticians who need to learn how SAS® procedures are used to analyze data and create statistical output.

BENEFITS
Students will learn how SAS handles:

• Logistic and Multiple Linear Regression
• Categorical Data Analysis
• Analysis of Variance and Statistical Inference
• Graphs for data visualization
• Confidence intervals and Test hypotheses
• Categorical analyses
• Fit models

PREREQUISITES
Programming I: SAS Essentials and a basic course in statistics. You should understand hypothesis testing, frequency tables, chi-square analysis, regression analysis, analysis of variance and p-values.

COURSE TOPICS

Overview of Statistics
• Basic statistical concepts and theory
• Data distributions
• Simple tests of hypothesis
• Two sample t-tests
• Confidence intervals
• Descriptive statistics
• Proc MEANS and Proc UNIVARIATE

Creating Analysis of Variance
• Multiple comparisons
• Design of Experiments
• One-way analysis of variance
• Nonparametric analysis
• Proc ANOVA and Proc GLM

Creating Regressions
• Assumptions
• Determining influential observations
• Simple linear and Multiple linear regressions
• Using Stepwise techniques to fit multiple regression models
• The effects of multi co-linearity
• Use Proc REG and Proc CORR

Creating Categorical Data Analysis
• Understanding categorical data
• Frequency Analysis and Proc FREQ
• Tests for Linear Association
• Logistic Regressions

Advanced Regression Topics
• Understanding influence
• Understanding the role of co-linearity
• Examine residual values

Software Used: Base SAS®, SAS/STAT® and SAS/GRAPH® Software.