Your Name: Your Email:  ### Course Length:

This is a four-day course.

### Description

This course is ideally suited to someone with prior statistical knowledge who undertakes statistical analysis in the language of SAS. This course provides an introduction to the application of statistical techniques such as Analysis of Variance, Regression and Logistic Regression.

### An introduction to Statistical Procedures

• Background statistical concepts
• Generating random samples using PROC SURVEYSELECT
• Generating descriptive statistics using PROC MEANS and PROC UNIVARIATE
• Examining the distribution of a dataset
• Producing confidence intervals
• Performing hypothesis tests
• Compare the mean statistic of two populations using PROC TTEST

### Analysis of Variance (ANOVA)

• Use PROC GLM to compare the mean statistic of two populations using a One-Way ANOVA
• Use PROC GLM to compare the mean statistics of multiple populations using a One-Way ANOVA
• Use PROC GLM to compare the mean statistics of multiple populations using a Two-Way ANOVA
• Learn how to deal with interactions in a Two-Way ANOVA.
• Understand the impact of a blocking factor in ANOVA.

### Regression I

• Examine the relationship between continuous variables using scatter plots
• Use PROC CORR to identify the magnitude of linearity between continuous variables
• Use PROC REG to perform Simple Linear Regression (SLR)
• Use PROC REG to perform Multiple Linear Regression (MLR)
• Understand the impact of Collinearity in Multiple Linear Regression
• Learn methods of building Multiple Logistic Regression Models
• Learn how to interpret different models

### Regression II

• Use Scatter plots to examine the residual statistics in a  given model
• Learn methods of detecting outliers and influential observations
• Learn methods of detecting Collinearity

### An introduction to Logistic Regression/Categorical Data Analysis

• Use PROC FREQ to generate frequency tables
• Learn how to detect associations between variables using the FREQ procedure
• Use PROC CORR to obtain correlation statistics
• Use PROC LOGISTIC to perform a Logistic Regression Analysis
• Use PROC LOGISTIC to perform Multiple Logistic Regression
• Compare the explanatory and predictive ability of Multiple Logistic Regression Models

### What you should already know:

• A knowledge of p-values, hypothesis testing, Analysis of Variance and Regression is essential.
• Experience of running a program in the Language of SAS, creating a dataset, applying formats and running basic Statistical Procedures. This knowledge can be gained on our Foundations - The Language of SAS Course.

### Don't Delay - Book Today!

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