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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, p-
                       values.
                 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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