FULLY SOLVED BOOK LASY 5 YEARS PAPERS SOLVED PLUS GUESS
Module 1
Descriptive Statistics: Measures of central tendency - Problems on measures of ispersion –Karl Pearson correlation, Spearman’s Rank correlation, simple and multiple regression (problems on simple regression only) 19
Module 2
Probability Distribution: Concept and definition - Rules of probability – Random ariables –Concept of probability distribution – Theoretical probability distributions: Binomial, Poisson, Normal and Exponential – Baye’s theorem (No derivation) (Problems only on Binomial, Poisson and Normal)
Module 3
Decision Theory: Introduction – Steps of decision-making process – types of decision-making environments – Decision-making under uncertainty – Decision-making under Risk – Decision tree analysis (only theory). Design of Experiments: Introduction – Simple comparative experiments – Single factor experiments – Introduction to factorial designs
Module 4 (only theory)
Cluster Analysis: Introduction – Visualization techniques – Principal components – Multidimensional scaling – Hierarchical clustering – Optimization techniques Factor Analysis: Introduction – Exploratory factor analysis – Confirmatory factor analysis Discriminant Analysis: Introduction – Linear discriminant analysis
Module 5
Foundations of Analytics: Introduction – Evolution – Scope – Data for Analytics – Decision models – Descriptive, Predictive, Prescriptive – Introduction to data arehousing – Dashboards and reporting – Master data management(only theory)
Module 6
Linear Programming: structure, advantages, disadvantages, formulation of LPP, solution using graphical method. Transportation problem: Basic feasible solution using NWCM, LCM and VAM, optimisation using MODI method. Assignment Model: Hungarian method – Multiple solution problems – Maximization case – Unbalanced – Restricted.
Module 7
Project Management: Introduction – Basic difference between PERT & CPM – Network components and precedence relationships – Critical path analysis – Project scheduling – Project time-cost trade off – Resource allocation Instruction: Equal weightage is given for both theory and problems in the ratio of 60:40 Practical Component:
• Students are expected to have a basic excel classes
• Students should be able to categorize the data and find out the basic statistical values
