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, percentilesLearn and apply 68-95-99.7 Empirical RuleStandard normal distribution, z-scores and standard normal tableCompute areas under the normal curve and interpret the resultsCompute percentiles and interpret the resultsCalculate cut-off values of the variable to cover middle p% of the distributionHow 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 testChapter 6 – Normal Distribution – Pages 361 - 375Suggested Exercises – Chapter 6 – Odds 60 through 80
Statistics and Probability
Community College / Lower Division, College / Upper Division
Ohio Transfer Module Mathematics, Statistics, and Logic (TMM) Standards
Core TMM010 Outcome: Core skill demonstrated by students who successfully complete an Introductory Statistics Course
Standard: Compute the probability of compound events, independent events, and disjoint events, as well as
conditional probability. Compute probabilities using discrete and continuous distributions, especially applications of the normal distribution.