Home Business Research Methods : MBA 108

Business Research Methods : MBA 108

Lecture No.DescriptionLecture By
Lecture 1 Introduction to Business ResearchLecture by Dr. Sandeep Kumar,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 2 Type of ResearchLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 3 Process of ResearchLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 4 Formulation of the Research ProblemLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 5 Concept of Hypothesis, Development of the Research HypothesesLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 6 Types of HypothesesLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 7 Research Design-Definition, FunctionsLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 8 Types of Research Design-Exploratory, Descriptive & experimentalLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 9 Experimental Research Design – Pre-experimental, Quasi-experimentalLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 10 Experimental Research Design-True experimental, Statistical application of various Research DesignsLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 11 Validity of research instruments-face & contentLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 12 Construct Validity; Readability of Research InstrumentsLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 13 Internal Consistency ProceduresLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 14 Methods of Data collection-Primary & Secondary SourcesLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 15 Concept of AttitudeLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 16 Attitude Scales Likert, ThurstoneLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 17 Guttman ScalesLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 18 Concept of QuestionnaireLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 19 Types of QuestionnaireLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 20 Questionnaire DesigningLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 21 Concept of SamplingLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 22 Concept of Sampling DesignLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 23 Types of Sampling Design-Probability, Non-probabilityLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 24 Various Probability Sampling DesignLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 25 Various Non-Probability Sampling DesignLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 26 Mixed Sampling DesignsLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 27 Sampling FrameLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 28 Sample Size DeterminationLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 29 Data ProcessingLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 30 Data Editing, CodingLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 31 Use of Tabulation in Data ProcessingLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 32 Data analysis-Univariate, bivariateLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 33 Multivariate Data AnalysisLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 34 Hypothesis Testing-ConceptLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 35 Types of ErrorLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 36 Steps in hypothesis testingLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 37 Parametric TestsLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 38 Non-Parametric TestsLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 39 AnovaLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 40 Correlation Analysis, Regression AnalysisLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 41 Chi-Square TestLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 42 Non-Parametric Tests for NormalityLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 43 Runs TestLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 44 Advanced Data Analysis Techniques-Basic Concepts of Factor AnalysisLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
Lecture 45 Discriminate Analysis. Conjoint AnalysisLecture by A,    Lecture by B,    Lecture by C,    Lecture by D
[whatsapp]