M.Sc in Statistics

Master

In Jabalpur

Price on request

Description

  • Type

    Master

  • Location

    Jabalpur

Facilities

Location

Start date

Jabalpur (Madhya Pradesh)
See map
Saraswati Vihar, Pachpedi, Jabalpur (M.P.), 482001

Start date

On request

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Course programme




Course Structure

Unit -1 Multivariate normal distribution and it’s properties, Random Sampling from a
multivariate normal distribution. Maximum likelihood estimators of parameters.
Distribution of Sample mean Vector,
Unit-2 Hotelling’s T2 - distribution and its application, Null distribution of a sample
correlation coefficient. Null distribution of Partial and Multiple correlation coefficient.
Unit-3 Classification and discrimination procedures for discrimination between two
multivariate normal populations. Principal components & Canonical variable.
Unit-4 Introduction to Design of Experiments, CRD, RBD, LSD; Graeco Latin Square
Design. Missing Plot Technique – general theory and applications. Analysis of Covariance.
Split Plot Design.
Unit-5 General Block Design, Information metric ‘C’ and it’s properties. Concept of
connectedness, orthogonality, balance. Analysis of block designs.
Unit -1 Meaning and scope of SQC, Shewhart control charts for X , R, np p, C etc. and their
uses. OC and ARL of control charts, uses of runs and related pattern of points.
Cusum charts, Use of V-mask, Derivation of ARL.
Unit-2 Sampling inspection plans – Classification and general properties. Sampling plans by
variables, Estimation of lot defective and plan parameter determination in known and
unknown cases.
Unit-3 Gauss – Makov Setup – Estimability, Best point estimates and interval estimates of
estimable linear parametric function. Normal equation and least square estimates.
Unit-4 Error and estimation spaces, Variances and covariance’s of least square estimates.
Estimation of error variance, Estimations with correlated observations. Least squares
estimates with restriction on parameters, Simultaneous estimates of linear parametric
functions.
Unit-5 Tests of hypothesis for one and more than one linear parametric function. Confidence
interval and regions, Power of F-test, Multiple comparison test due to Tukey and
Scheffe, Simultaneous confidence intervals
Unit -1 Definition and Scope of O.R. Phases inO.R. Linear Programming problems- Methods
of solution, Artificial variable techniques. Degeneracy and Methods for resolving it.
Unit-2 Revised simplex Algorithm in standard from I. Duality in linear Programming
problems, Duality Theorems – Basic Duality Theorem, Fundamental Duality Theorem.
Unit-3 Transportation and assignment problems with proofs of relevant results and methods of
solutions. Goal Programming – Concept, Goal Programming as an extension of LP,
Single Goal models.
Unit-4 Integer Liner Programming – Def. importance and need of integer programming.
Gomory’s cutting plane method. Geometric interpretation of Gomory’s cutting plane
method. Branch and bound methods. Geometrical interpretation of Branch & Bound
method. Application of Integer Programming.
Unit-5 Non Linear Programming problem – Def. practical situation, Formulation of non linear
programming problems. Canonical form of non-linear programming problem.
Graphical solution and verification of Kuhn – Tucker Conditions.

M.Sc in Statistics

Price on request