This course covers basic statistical concepts that are critical for understanding and using statistical methods. This course explains what statistics is and why it is important to understand the characteristics of your data.

The information in this course is a prerequisite for many other statistical courses that SAS Education offers. The course is appropriate for Base SAS and SAS Enterprise Guide users. Data, practices, and a case study are included.

Learn how to

• examine data distributions
• obtain and interpret sample statistics using the UNIVARIATE and MEANS procedures
• examine data distributions graphically in the UNIVARIATE and SGPLOT procedures
• construct confidence intervals
• perform simple tests of hypothesis.

Who should attend

Anyone who wants to learn the basics of statistics

Formats available	Duration
e-Learning:	6 hours/180 day license	System Requirements

There are no formal prerequisites for this course.

This course addresses Base SAS, SAS Enterprise Guide, SAS/STAT software.

Basic Statistical Concepts

• descriptive and inferential statistics
• populations and samples
• parameters and statistics
• uses of variables: independent and dependent
• types of variables: quantitative and categorical
• scales of measurement (nominal, ordinal, interval, and ratio)
• statistical methods

Descriptive Statistics

• describing your data
• measures of location
• percentiles
• measures of variability

Picturing Your Data

• picturing your data: histogram
• normal distribution
• assessing normality
• measures of shape: skewness
• measures of shape: kurtosis
• normal probability plots
• box plots
• comparing distributions

Confidence Intervals for the Mean

• point estimators, variability, and standard error
• distribution of sample means
• interval estimators
• confidence intervals
• normality and the central limit theorem

Hypothesis Testing

• decision-making process
• steps in hypothesis testing
• types of errors and power
• the p-value, effect size, and sample size
• statistical hypothesis test
• the t statistic, t distribution, and two-sided t-test