What is the syllabus for M.Sc statistics and computing in BHU?

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 Kolmogorovs approach to probability Sample Space - Discrete sample space, Continuous sample space Event - Operation of Event, Independent Events, Mutually Exclusive Events Random Experiment Trial Bayes theorem and its application Random Variables Moment generating functions Probability generating functions Chesbyshevs 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 Spearmans and Kendalls 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 Fishers 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

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LPU offers M.Sc. Statistics that aims at brewing the scientist by provoking the doing by yourself approach using various statistical tools and techniques. The learner has to do project work keeping in mind the research centricity, for which the programme has been chosen. The M.Sc. Data Analytics programme at LPU is what it aims at equipping the student with - DISTRIBUTION THEORY, FUNDAMENTALS OF RESEARCH, INTRODUCTION TO DATA MANAGEMENT, LINEAR Algebra REAL ANALYSIS, SURVEY SAMPLING, DATA Science TOOLBOX : R PROGRAMMING, INFERENCE-I, LINEAR MODELS AND REGRESSION ANALYSIS, LINEAR MODELS AND REGRESSION ANALYSIS LAB, PATHWAY ELECTIVE 1, Probability RESEARCH METHODS AND DESIGN, DATA VISUALIZATION, DESIGN AND ANALYSIS OF EXPERIMENTS, DESIGN AND ANALYSIS OF EXPERIMENTS LAB, MULTIVARIATE ANALYSIS etc. However, you will get the detailed syllabus in the beginning of the session once you join LPU however, if you want to have the syllabus in advance you can either visit the website or write to LPU for the same on its official email id given on the website. Good Luck.

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