SPSS

SPSS

Courses Info

Course Objective

Managers play an important role in organizational decision making. To be effective in this role, Managers need to be enabled to conceive and execute business research using theoretical inputs on research methodology if the research is manageable at their level. Knowledge of SPSS is all the more important for interacting with Consultants should their help be needed for the organization. It is also necessary to enable managers on software like SPSS to facilitate statistical analysis of data to support the research. With this capability, managers would be able to handle many routine business research problems at their levels. This course aims at equipping you on these.

Detailed Syllabus

  • MEASUREMENT AND SCALING
  • Measurements – Types of Measurement Scales – Attitude
  • Measurement – Classification of Scales – Single vs Multiple, Comparative vs Non-comparative
  • Types of Errors in Measurement – Criteria for good measurement – Reliability – Validity – Sensitivity.
  • Measurement and Scaling, Primary Scales of Measurement. Nominal Scale, Ordinal Scale, Interval Scale, Ratio Scale.
  • Comparative Scaling Techniques – Paired Comparison, Rank Order Scaling, Constant Sum Scaling, Q-Sort and Other Procedures.
  • Verbal Protocols, International Marketing Research and Ethics in Marketing Research

 

  • QUESTIONNAIRE DESIGN
  • Objectives of a Questionnaire, Criteria for Questionnaire Designing, Questionnaire Designing Procedure, Types of Questions to ask and intricacies in them.

 

  • DATA PREPARATION
  • Data Coding, Data Cleaning, Identification Outlier, Handling Missing Values (all using SPSS)
  • The Data Preparation Process , Questionnaire Checking, Editing, Treatment of Unsatisfactory Responses, Coding, Coding Questions, Code-book, Coding Questionnaires

 

  • EXPLORATORY RESEARCH
  • Pre-Experimental Design, True-Experimental Design
  • Quasi-Experimental Design

 

  • TWO-WAY ANOVA
  • Applications of two-way ANOVA as an analysis tool for complex experimental designs complex experimental designs

 

  • FACTOR ANALYSIS
  • Basics with Real time example

 

  • REGRESSION

                                                     

  • Simple   Regression   –   Linear   regression,   Regression Analysis and Real time Interpretation.
  • Multiple Regression – Assumptions & Basics, SPSS Output Interpretation, Transforming Dependent & Independent Variables
  • Multiple Regression – Dealing with Multi-co linearity, idea of Autocorrelation, Regression with Dummy Variables

 

  • DISCRIMINANT ANALYSIS
  • Discriminant Analysis – Basics with Real time example Interpretation.
  • Discriminant Analysis – Two Group Case
  • Discriminant Analysis – Multiple Group Case

 

  • CLUSTER ANALYSIS
  • Cluster Analysis – Basics with Real time example Interpretation.
  • Hierarchical Clustering
  • K-Means Clustering

 

  • Conjoint Analysis
  • Report Writing
  • Parametric And Non-Parametric Test
  • Sign Test, Mann – Whitney Test, Spearman Test, Kruscal –Wallis Test, Friedman Test.
  • Hypothesis Test, Level Of Significance, Significance Interval, Type I and Type Ii Error Occurrence.
  • Correlation, Types Of Correlation And Correlation Coefficient With Real Time Example
  • Types of Statistical Test and Situation Wise Explanation.
  • T-test, F-Test, Chi square test, Z – Test.
  • Experimental Design – Pre – Experimental Design, True Experimental Design, Quasi – Experimental Design.
  • Real Time Data Collection, Code Book preparation, Project Report preparation and their Analysis.
  • Real Time Project Walkthrough, Interview material Discussion and Data Analysis Resume Preparation
  • Communication Management – Communication: Introduction, Email Communication, Teleconference and Meetings, Assertiveness and Scenarios