Lecture 1 - Introduction to Marketing Research
Lecture 2 - Defining Research Problem
Lecture 3 - Developing Research Approach and Developing Research Design: Non-Conclusive
Lecture 4 - Research Design: Conclusive
Lecture 5 - Qualitative Research: Nature and Approaches
Lecture 6 - Qualitative Research: Depth Interview, Focus Group Discussion
Lecture 7 - Projective Technique, Case Study
Lecture 8 - Case Study, Descriptive Research Design and Research Errors
Lecture 9 - Primary and Secondary Data, Research Error
Lecture 10 - Measurement and Scaling: Comparative and Non-comparative Scaling
Lecture 11 - Scale Development Process
Lecture 12 - Questionnaire and Form Design
Lecture 13 - Causal Research and Types
Lecture 14 - Experimental Design and Sampling
Lecture 15 - Sampling Design and Procedure
Lecture 16 - Sampling and Sample Size Determination
Lecture 17 - Hypothesis Development: Null and Alternate, Type I and Type II Errors
Lecture 18 - Data Preparation
Lecture 19 - Hypothesis Testing: T-Test, Z-Test
Lecture 20 - T, Z and F Test
Lecture 21 - Hypothesis Testing: Anova and Manova
Lecture 22 - Cross Tabulation and Chi Square Test
Lecture 23 - Correlation and Regression
Lecture 24 - Regression
Lecture 25 - Factor Analysis
Lecture 26 - Factor Analysis
Lecture 27 - SEM and CFA - 1
Lecture 28 - SEM and CFA - 2
Lecture 29 - SEM and CFA - 3
Lecture 30 - Cluster Analysis - I
Lecture 31 - Cluster Analysis - II
Lecture 32 - Discriminant Analysis
Lecture 33 - Discriminant Analysis - 1
Lecture 34 - Researching Rural Market
Lecture 35 - International Marketing Research
Lecture 36 - Ethics in Marketing Research
Lecture 37 - Ethics in Marketing Research - 1
Lecture 38 - Report Preparation and Presentation
Lecture 39 - Multi Dimentional Scaling
Lecture 40 - Conjoint Analysis
Lecture 41 - Introduction to Text Analysis
Lecture 42 - Text Analysis Process
Lecture 43 - Importance and Application of Text Analysis
Lecture 44 - Tools and Techniques of Text Analysis
Lecture 45 - Text Preprocessing and Text Representation
Lecture 46 - Text Representation (Continued...)
Lecture 47 - Hands-on – Methodology for Analyzing YouTube Comments on Sustainable Development Goals
Lecture 48 - Data Preprocessing and Cleaning with Python
Lecture 49 - Data Preprocessing and Cleaning with Python (Continued...)
Lecture 50 - Sentiment Analysis
Lecture 51 - Introduction to NRC Lexicon
Lecture 52 - Application of NRC Lexicon using Python
Lecture 53 - Sentiment Analysis: Machine Learning and Deep Learning Algorithms
Lecture 54 - Introduction to Topic Modeling
Lecture 55 - Topic Modeling Techniques
Lecture 56 - Hands-on Exercise: Topic Modeling using LDA
Lecture 57 - Hands-on Exercise: Topic Modeling using NMF
Lecture 58 - Part of Speech Tagging and Named Entity Recognition
Lecture 59 - Hands-on Exercise: Named Entity Recognition
Lecture 60 - Hands-on Exercise: Part of Speech Tagging
