Module Components

• Overview

Topics

• Sampling Error and Variation
• The Normal Distribution
• Estimating Population Values from Samples

NRSG 795: BIOSTATISTICS FOR EVIDENCE-BASED PRACTICE

Module 3: Variation and the Normal Distribution

Overview

This module begins to introduce you to issues we need for inferential statistics -where inferences about populations are made from observations in samples. It begins with a review of the concept of sampling error and variation. Then, characteristics of the normal distribution and its variations are covered in detail since the normal distribution is key to understanding standardized scores (e.g., z-scores), standard errors, and determining probabilities. Up until now, the standard deviation has been described in terms of a sample; now the concept of standard error will be introduced to estimate the variation around a point estimate in a population. With an understanding of standard error, confidence intervals are explained in terms of how precisely a statistic estimates a parameter.

Objectives

At the conclusion of this module, the learner will be able to:

• Describe the normal distribution and its variations including skewness and kurtosis.
• Use the normal distribution and z-scores to determine the percentage of a population that lies between two scores.
• Calculate confidence intervals around a point estimate.
• Determine the standard error of the mean for two populations.

Directions

There are three subtopics with and videos assigned within the subtopics. Learning activities within the subtopics are designed to help you apply what you learned.