Many inferential procedures assume that variable(s) under study follow a normal distribution in the population. In this module we will study properties of this distribution and learn how to calculate important measures that would be useful later in inference.

Learning Objectives:

• Understand the properties of a normal distribution, the graph of its density function, interpret areas enclosed by a normal curve over an interval, percentiles
• Learn and apply 68-95-99.7 Empirical Rule
• Standard normal distribution, z-scores and standard normal table
• Compute areas under the normal curve and interpret the results
• Compute percentiles and interpret the results
• Calculate cut-off values of the variable to cover middle p% of the distribution
• How normal is a population distribution - Learn how to infer that the population distribution of the variable is normal – set up hypothesis, use normal probability plot, Anderson-Darling normality test, interpret p-value of the test

Chapter 6 – Normal Distribution – Pages 361 - 375

Suggested Exercises – Chapter 6 – Odds 60 through 80