Marketing Analytics using R Training Videos (22 hours)

Course Objective – Marketing Analytics using R

The main aim of this course is to help you learn R for Marketing Analytics. R offers unsurpassed capabilities for fitting statistical models. It is extensible and is able to process data from many different systems, in a variety of forms, for both small and large data sets. The course will be covering applied, real-world marketing analytics problems as well as a few advanced marketing topics.

All the topics in the course are handled in a manner that they show how an analyst might realistically conduct analyses where multiple models are compared for statistical strength and practical utility

Key Highlights of Training Videos

  • Get a good grip of using R and related packages to perform data analysis
  • Self explanatory Concise downloadable training videos for performing in depth marketing Analytics
  • Self paced Videos pre recorded without students and any repetitions of concepts.
  • Understand advanced concepts of marketing analytics easily from business perspective practically without getting into heavier mathematical aspects
  • One – One Support via phone, email or Skype

Pre-requisites

Simply that you are interested in R for Marketing, and are willing to engage in hands-on learning. Earlier experience in programming is not mandatory.

Veiw Demo Videos on Marketing Analytics using R

Training Videos Content

Sessions

Contents

Duration

Video 1

Introduction to R

19 Mins

Video 2

R Overview, Basic objects, Data Frames, R commands, Control Structures in R, Custom functions, Loading and saving data, Clean up

120 Mins

Video 3

Summarizing variables, Data frames Operations, Working with Discrete and continuous data, Data Inspection, apply()

49 Mins

Video 4

Single variable visualization, Histograms, Box Plots, QQ plot -  Normality, by() and aggregate()

52 Mins

Video 5

Relationships between continuous variables, Associations Between Variables, Scatterplots,  Scatterplot matrices, Combining plots, Correlation Coefficients, Association in survey responses

103 Mins

Video 6

Comparing groups, Tables and Visualization, Descriptives , Frequencies and Proportions, Visualization of continuous data

53 Mins

Video 7

Statistical Tests, Testing Group Means- t Test, Testing Multiple Group Means- ANOVA, Testing Group Frequencies – chi square test, Testing Observed Proportions – Binomial Test

89 Mins

Video 8

Simple Linear Regression, First steps, Bivariate Association, Output Interpretation, Model fitment

66 Mins

Video 9

Introduction to Multiple Regression Models, Using Model to predict, Standardizing Predictions, Comparing Models, Factors as Predictors, Linear Model fitting process, Over fitting, Interaction Terms

72 Mins

Video 10

Introduction to Principle Component Analysis, Data setting for PCA, Visualization, PCA Computation, PCA in R, Interpreting PCA Output, Perceptual Maps

69 Mins

Video 11

Exploratory Factor Analysis, Concepts, EFA Solution in R, Rotations, Visualizing EFA, Data Dimension Reduction, Factors to Interpret Factor Variables

77 Mins

Video 12

Introduction to Multidimensional Scaling, Metric and Non Metric MDS, Process and Limitations of MDS

29 Mins

Video 13

Collinearity, Limitations of Linear model, Visualization of Collinearity, Remediating Collinearity

40 Mins

Video 14

Logistic Regression Model, Binary Outcomes, Output Interpretation, Checking Coefficients, Statistical significance

44 Mins

Video 15

Hierarchical Linear Models, Concepts, Improvement over simple Linear Model, Simple Ratings based Conjoint Analysis, Simple Hierarchical linear models, Complete Hierarchical Linear Model

60 Mins

Video 16

Understanding Segmentation, Clustering vs. Classification

21 Mins

Video 17

Steps of Clustering, Hierarchical Clustering, Mean-Based Clustering-Kmeans(), Model-Based Clustering, Latent class Analysis, Cophenetic Correlation Coefficient, Comparing Cluster Solutions

109 Mins

Video 18

Steps in Classification, Naïve Bayes, Random Forest, Variable importance

81 Mins

Video 19

Association rules for Market Basket Analysis, Metrics for MB Analysis

27 Mins

Video 20

Market Basket Analysis using R, Performing Market Basket Analysis in depth, Finding Association rules, Visualizing Association rules, Output interpretation

40 Mins

Video 21

Choice Modelling, Concepts, Understanding Data, Choice-Based Conjoint Analysis, Fitting Choice Models, Interpreting the model, Reporting

70 Mins

Who Can Buy?

This course will be very much useful for practicing marketing researchers and analysts who want to learn R, Statisticians, Marketing Professors and students or researchers from other fields who want to review selected marketing topics in an R context. This course is designed to be approachable for practitioners and does not dwell on equations or mathematical details of statistical models

Want to conduct this training in-house?

If you want to conduct this training for your employees or for your clients at your place, you can save on time and money. Mail us at info@pacegurus.com or call us on +91-98480 12123 for a no-obligation proposal