Accession Number : ADA132562

Title :   Human Factors Engineering. A Self-Paced Text, Lessons 31-35,

Corporate Author : HUMAN ENGINEERING LAB ABERDEEN PROVING GROUND MD

Personal Author(s) : Brogan,Ruth ; Hedge,Jerry ; McElroy,Kevin ; Katznelson,Judah

PDF Url : ADA132562

Report Date : Aug 1981

Pagination or Media Count : 105

Abstract : Lesson 31 and the next one (Lesson 32) will deal with experimental design. This lesson will teach about different ways to classify variables: Independent, dependent, relevant, and other classes. This lesson will also present different types of research methods. Lesson 32 will lead the trainee from a knowledge of how numerous variables affect experiments to a discussion of how to control these relevant variables. Then, once the trainee has a better understanding of how to control variables, and manipulate others, we'll look at some experimental designs and the conditions under which they are used. Finally, we'll spend some time dealing with kinds of inferences and generalizations that can be drawn from the experiment--technically called an experiment's internal and external validity. Lesson 33 will teach about statistical tools. These techniques will aid the trainee in making decisions about the human factors experiments conducted or supervised. You are not going to be given a mini-course in how to compute statistics. Lesson 34 is the second lesson on statistics. This lesson will discuss statistical methods which allow you to describe the relationship between variables as scores and statistical methods which enable you to make inferences or generalizations about the data you have. Lesson 35 is a review of Lessons 21-34.

Descriptors :   *Human factors engineering, *Textbooks, *Training, Instructional materials, Programmed instruction, Test methods, Experimental design, Performance(Human), Methodology, Classification, Variables, Control, Utilization, Validation, Statistics

Subject Categories : Information Science
      Humanities and History
      Human Factors Engineering & Man Machine System

Distribution Statement : APPROVED FOR PUBLIC RELEASE