COURSE OBJECTIVES

The realm of statistical modeling makes mathematical evaluation for the application to get authenticated against the observed data.  There are different types of statistical models known as tests that can be used to analyze data. The objective behind this course is to describe and predict information, observe the characteristics and pattern behind the data, validate and test the data model, evaluate the data model with mathematical inference and representation, use a limited sample to make intelligent and accurate conclusions about a greater population.

COURSE DURATION: 4 Weeks
COURSE OUTCOMES:

By the end of this course, the learners will be able to
    • Practice t-tools and permutation-based alternatives including bootstrapping, multiple-group comparisons, analysis of variance, linear regression, model checking, and refinement.
    • Model Statistical computing and simulation-based emphasis as well as basic programming in the SPSS, Rapid miner statistical package.
    • Develop tools for real-life applications by evaluating assumptions
    • Predict real word data with mathematical models and statistical assumptions.
    
COURSE CONTENTS:

Module 1: Introduction to Analytics:
Overview - Data and its processing platforms - Analytics Process Model - Analytics Model Requirements-Types of Analytics - Predictive analytics - Descriptive Analytics - Text Analytics - Social Media Analytics -Survival Analytics

Module 2: Introduction to Statistics:
Introduction to statistical modeling – Exploratory data analysis – Probability and Distributions - Properties of random variables - Bayesian and frequentist approaches to statistical inference

Module 3: Descriptive Statistics:
Univariate descriptive statistics – Sampling and estimation - Hypothesis testing– Multivariate descriptive statistics – Normal distributions– inference

Module 4: Statistical Modeling:
ANOVA – MANOVA – Regression – Estimation of model accuracy and testing – Principal Component Analysis - Factor Analysis

COURSE INSTRUCTORS:

    1. Mrs.R.Parkavi , rpit@tce.edu
    2. Mrs.C.Santhiya, csit@tce.edu