This textbook was designed to introduce individuals to the concepts and strategies of statistical analyses for problems in health-related disciplines. The primary learning objective of this textbook is to introduce the reader to a variety of statistical methods and basic analytical procedures associated with processing data in regard to healthcare research. It is intended that by working through the applications and practice problems, readers should be able to understand and apply some of the methods for developing, implementing and critically evaluating data within the various disciplines of health, health sciences, healthcare, and health services delivery. Secondary objectives of this textbook include the development of an understanding of the theoretical concepts of statistical applications, different strategies for evaluating research questions using statistical methods, and an ability to interpret and critically evaluate statistical analyses, which can be used in measurement and evaluation.

Primary Outcome Linked to Competencies

Working through the material in this textbook, the reader should be able to apply basic statistical methodologies to support decision making within the various disciplines of applied health, including but not limited to nursing, health sciences, healthcare, and health services delivery. Specifically, in this textbook, the reader will be introduced to examples that include the methods by which to:

• Distinguish between descriptive and inferential statistics
• Classify levels of measurement
• Develop and interpret data using frequency distributions
• Apply and interpret various graphing techniques – present data using graphing methods that include, but are not limited to line, bar, bubble and pie charts
• Generate measures of location and measures of dispersion
• Calculate and interpret percentiles
• Apply binomial probability distribution methods
• Calculate normal probabilities using the z-test
• Calculate normal probabilities using the t-test
• Describe methods to select a sample
• Distinguish between measurements for a sample and for a population
• Determine sample size under various scenarios
• Differentiate between a population parameter and a sample statistic
• Compute point estimates and confidence intervals
• Apply hypothesis-testing methodologies
• Apply the computation of confidence intervals to decision making
• Apply tools of non-parametric analyses to tests of hypotheses
• Evaluate the goodness of fit using the chi-squared test
• Evaluate a contingency table using the chi-squared test

A Note about the use of SAS

Throughout this textbook, SAS University Edition is used as the platform upon which to compute statistics, and as the environment in which students can actively engage and problem solve. The textbook begins with an introduction to SAS University Edition so that the very novice user of statistics, programming languages, and SAS will feel comfortable with the theory and the examples, as presented. Likewise, throughout this textbook, we will use the web as a destination to locate information and gain direct assistance in problem-solving and task resolution.