Introduction to Statistical Concepts with SAS Essentials

Understanding the foundational concepts of statistics is essential for anyone looking to analyze and interpret data effectively. The Introduction to Statistical Concepts course offers a comprehensive 6-hour exploration of core statistical principles that form the basis for more advanced statistical studies. This course is geared toward Base SAS and SAS Enterprise Guide users, but it is suitable for anyone interested in gaining a solid statistical grounding. By covering both descriptive and inferential statistics, participants learn to examine data distributions, obtain and interpret sample statistics, and apply statistical methods to real-world scenarios.

Participants are introduced to a wide range of key concepts, including populations and samples, types of variables (quantitative, categorical), and different scales of measurement such as nominal, ordinal, interval, and ratio. The course emphasizes understanding and utilizing measures of location, percentiles, and measures of variability to describe data comprehensively.

Visualizing data effectively is another critical aspect of the course. Participants learn to create and interpret graphical displays such as histograms, normal distributions, box plots, and more using SAS procedures like UNIVARIATE and SGPLOT. This ability to picture data helps in assessing normality, understanding data shape through measures like skewness and kurtosis, and comparing distributions effectively.

The course also covers confidence intervals for the mean, providing insight into interval estimators, point estimators, variability, and the central limit theorem. Moreover, hypothesis testing is discussed in depth, highlighting steps in the decision-making process, types of errors, statistical tests, and the use of p-values and effect sizes.

For anyone interested in acquiring essential statistical skills or building a foundation for further statistical education, this course provides practical knowledge and a clear path for understanding statistical data analysis.