# Introduction to Statistics Using SAS Enterprise Guide 5.1: ANOVA, Linear Regression and Logistic Regression

Course code TPEGSTA71
Duration 3 Days

This three-day course is an excellent follow-on to the SAS Enterprise Guide 1: Querying and Reporting course for anyone using, or wanting to use, statistics in a business environment. It covers a range of introductory statistical topics including the best way to describe your data, statistical inference, analysis of variance, simple and multiple linear regression, categorical data analysis, and an introduction to binary logistic regression.

# Prerequisites

Before attending this course, you should: Be able to navigate around SAS Enterprise Guide and to be able to run tasks within Enterprise Guide. This knowledge can be gained by attending the SAS Enterprise Guide 1: Querying and Reporting course. No prior knowledge of statistics is necessary.

Who should attend?

Anyone who would like to learn or know more about using statistical tests within their work environment. This course is not industry specific and emphasis will be placed on using SAS to carry out data investigation, analyses and the interpretation of the results to answer business problems.

# Delegates will learn how to

• construct graphs to explore, summarise and interpret data,
• assess the precision of your statistics,
• examine ways of testing business questions,
• examine relationships between variables,
• produce predictions of continuous target variables by fitting simple and multiple linear regression models explain why categorised data are treated differently,
• know what to do if your target variable is binary (e.g. Yes/No, Default/Repay)

# Outline

• Understanding the purpose of statistics
• Calculating some simple summary statistics
• Interpreting output from the Summary Statistics and Distribution Analysis Tasks.
• Examining the variability of data, why can we never be sure?

• Introduction to terminology for testing questions
• What is a t-test and when is it used?
• How can I obtain and interpret a p-value?
• Interpreting output from the t-TEST task
• What is analysis of variance (ANOVA)

Linear Regression

• Exploring the relationship between two continuous variables
• Measuring a linear relationship using correlation
• Interpreting the output from the Correlations task
• Understanding the misuses of correlation.
• Using Simple Linear Regression.
• Is our target variable related to more than one variable?
• Can we get better predictions by using more variables (Multiple Linear Regression)?
• How can we select the 'best' variables?

Logistic Regression

• Examining categorised data with the One-Way frequency task
• Examining and testing for an association between two variables
• Calculating and interpreting the chi-square test for association
• Why do we need to do something different?
• What is logistic regression and how does it work?
• How can I interpret the results from the Logistic Regression Task?
• What is an odds ratio and why is it useful?

• Paired T-test
• Fishers exact p-values
• Selecting Simple Random Samples

# 3 Days

Duration

This is a QA approved partner course

# Trusted, awarded and accredited

Fully accredited to ensure we provide the highest possible standards in learning

All third party trademark rights acknowledged.