A Concise Introduction to Business Research Methods: Concepts and Tools using SPSS
Purchasing Options
Features
- Offers a step-by-step description of the application of the SPSS for data analysis
- Includes SPSS screenshots
- Covers different forms of experimental design
- Presents descriptive questions, multiple-choice questions, T/F statements, and data exercise sets
Summary
Introductory in its approach, this text covers essential aspects of research methods. The author emphasizes major topics, such as experimental design, scale construction techniques, testing reliability and validity, as well as the application of univariate, bivariate, and multivariate tools in data analysis. Step-by-step details of the application of the SPSS, along with screenshots, are included to illustrate the application of tools to analyze and interpret research data. The book covers pre-, quasi-, true-, and complex experimental design forms. Each chapter contains descriptive questions, multiple-choice questions, true/false statements, and exercises.
Table of Contents
Research - Introduction
Significance of Research
Types of Research
Basic Concepts: Hypothesis, Constructs, Variables
Research Process
Management Problem vs. Research Problem
Factor Considered in Formulating Research Problem
Preparing an Academic Research Proposal
Research Design
Meaning and Concepts
Types: Exploratory, Descriptive and Experimental
Methods of Exploratory Design
Methods of Descriptive Design: Mail, Personal, Telephone, On-line Surveys
Methods of Experimental Designs (pre, quasi, true and complex designs)
Threats in Establishing Internal and External Validity
Measurement and Scaling
Types of Measurement
Scale Construction Techniques
Comparative vs. Non-comparative Scales
Constructing Scales for Attitudinal Measurement: Thurstone, Guttman and Likert Scales
Criteria for Good Measurement
Testing Reliability and Validity of a Scale
Sampling
Sampling Concepts
Sampling Process
Sampling Techniques (Probability and Non-probability)
Constructing Questionnaires
Questionnaire vs. Schedule
Guidelines in Constructing the Questionnaire
Errors in Measurement
Data Preparation and Analysis
Concepts of Editing and Coding
Data Analysis Concepts: Univariate, Bivariate and Multivariate
Univariate Data Analysis
One-Sample TTest
One-Sample Goodness-of-fit Test
Kolmogorov-Smirnov One-sample Test
One-way Analysis of Variance (ANOVA)
Kruskal-Wallis One-way ANOVA
Tukey Multiple Comparison of Means Test
Bivariate Data Analysis
T-Test
Paired-T test
Pearson Correlation
Spearman Rank Correlation
Partial and Part Correlation
Chi-square Test
Kruskall Gamma, Lambda Tests
Cohen's Kappa
Regression Analysis Using a Continuous Independent Variable
Regression Analysis Using a Categorical (Dummy) Independent variable
Multivariate Analysis
Two-way Anova
Two-way Anova with Interaction
Ancova
Multiple Regression
Factor Analysis
Introduction to Structural Equation Modeling (SEM)
Appendix:Statistical Tables
Glossary
Index
References
Author Bio(s)
D. Israel is a professor in the School of Business and Human Resources at XLRI Jamshedpur.
