Probability, Sampling, Sample Surveys, Linear Programming, Time Series analysis, Regression and Correlation are the main topics covered under M.Sc in Statistics Entrance Exam. Sample Space, Events, Measures of central tendency, etc are the other topics covered in the test.

Detailed Syllabus of M.Sc in Statistics Entrance Exam

Probability

• Conditional Probability
• Unconditional Probability
• Approaches to probability - Classical approach to probability, Relative frequency approach to probability, Richard Von Mises approach to probability, Cramer and Kolmogorov’s approach to probability
• Sample Space - Discrete sample space, Continuous sample space
• Event - Operation of Event, Independent Events, Mutually Exclusive Events
• Random Experiment
• Trial
• Baye’s theorem and its application
• Random Variables
• Moment generating functions
• Probability generating functions
• Chesbyshev’s inequality and its application

Distributions

• Uniform Distribution
• Binomial Distribution
• Poisson distribution
• Geometric Distribution
• Hyper-geometric Distribution
• Continuous univariate distributions
• Normal Distribution
• Exponential Distribution
• Gamma and Beta Distribution

Types of Data

• Qualitative and quantitative Data
• Discrete and Continuous data
• Primary and Secondary data
• Presentation of Data
• Construction
• Diagrammatic
• Graphical representation
• Bar diagram
• Ogive diagram
• Histogram
• Frequency Polygon
• Measures of central tendency
• Dispersion
• Relative Dispersion
• Absolute Dispersion
• Bivariate Data
• Scatter diagram
• Correlation coefficient
• Rank correlation
• Spearman’s and Kendall’s measures
• Multivariate Data
• Multiple correlations in three variables
• Partial correlation in three variables
• Regression lines
• Regression coefficient
• Principal of least squares
• Analysis of Categorical Data

Sampling

• Random sample
• Point estimate of a parameter
• Concept of bias and standard error of an estimate
• Tests of significance based on Chi- square
• Testing for the mean and variance of Univarite
• Sample tests
• Use of central limit theorem for testing and interval estimation
• Fisher’s Z transformation
• Non- Parametric tests
• Wilcoxon- Mann- Whitney test
• Run- test
• Median- test

Sample Surveys

• Concept of population and sampling
• Census and sample survey
• Sample selection
• Sample size
• Non-Sampling error
• Simple random sampling
• Stratified random sampling
• Systematic sampling

Linear programming

• Elementary theory of convex sets
• General linear programming problems (LPP)
• Graphical and simplex method of solving LPP
• Transportation Problems
• Assignment problems

Introduction to computers

• Basic set of an electronic computer
• CPU
• Input devices
• Output devices
• Need of computers in statistics
• Binary number system
• Machine
• Language
• Basic commands to operate a computer
• Ms- Office Tools

Demographic Methods

• Sources of demographic data
• Measurement of mortality
• Measurement of fertility
• Economic statistics
• Index number
• Simple aggregative methods
• Weighted average methods
• Lasperey’s, Passche’s and Fisher’s index numbers

Time series Analysis

• Economic time series
• General theory of control charts
• Process control chars for variables (X, R and S Charts)
• Control chart for attributes (np, p and c charts)
• Hypothesis
• Statistical hypothesis
• Simple and composite hypothesis
• Statistical hypothesis
• Null and alternative hypothesis
• Parameter models
• Parameter space
• Point Estimation
• Interval estimation
• Concepts of confidence interval and confidence coefficient

The exam pattern may vary slightly for each University that conducts the test but, the topics covered for the entrance test will be similar as discussed above to a great extent.