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Quantitative Techniques II

by Abhishek Apoorv
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Quantitative Techniques II by Abhishek Apoorv

Abhishek Apoorv
Abhishek Apoorv

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Quantitative Techniques-II DCOM209/DMGT209
Copyright © 2012 SN Murthy & U Bhojanna All rights reserved Produced & Printed by EXCEL BOOKS PRIVATE LIMITED A-45, Naraina, Phase-I, New Delhi-110028 for Lovely Professional University Phagwara
SYLLABUS Quantitative Techniques-II Objectives: To familiarize the students with different statistical techniques useful in conducting business research and then applying the same in their business strategies. Sr. No. Description 1. Quantitative techniques for managers : quantitative decision making & its overview, An introduction to research: meaning, definition and objectives, Goals, Strategy, Tactics, Internal and External Research Suppliers, Research Method Concept, Constructs, Definitions, Variables, Propositions and Hypotheses research process 2. Research problem: selection of problem, understanding problem, necessity of defined problem, Pilot Testing, Data Collection, Analysis and Interpretation, Reporting the Results. Review of literature in research 3. Research design: meaning, types – descriptive, diagnostic, exploratory and experimental 4. Sources and methods of data collection: primary and secondary sources, data collection methods, Questionnaire designing: construction, types, developing a good questionnaire, mailed questionnaire and schedule 5. Sampling design and techniques, Scaling techniques: meaning and types, sampling distribution, Data processing operations: editing, coding, classification, tabulation, 6. Partial Correlation: zero order, first order, second order Multiple Correlation, coefficient of Multiple correlation 7. Multiple Regression and Correlation Analysis: Least square regression plane, linear Multiple regression analysis, Coefficient of Multiple Determination 8. Hypothesis Testing: Statistical significance, the logic of hypothesis testing, statistical testing procedure, pvalues. 9. Test of significance: Types of tests, z-test, t-test, chi-square test, ANOVA 10. Factor Analysis, Cluster Analysis and Conjoint Analysis

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