## Sunday, October 7, 2012

### MA 9316 PROBABILITY AND STATISTICAL METHODS SYLLABUS | ANNA UNIVERSITY M.TECH REMOTE SENSING 1ST SEM SYLLABUS REGULATION 2009 2011 2012-2013

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MA 9316 PROBABILITY AND STATISTICAL METHODS SYLLABUS | ANNA UNIVERSITY M.TECH REMOTE SENSING 1ST SEM SYLLABUS REGULATION 2009 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY FIRST SEMESTER M.TECH REMOTE SENSING DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,PREVIOUS YEAR QUESTION PAPERS,MODEL QUESTION PAPERS, CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI,TIRUNELVELI,COIMBATORE), 2009 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009

MA 9316 PROBABILITY AND STATISTICAL METHODS L T P C
3 1 0 4 OBJECTIVE:
 To teach about the probability and Random variable of the various functions. It
also helps to understand the various statistical methods including the Design of
experiments.
UNIT I ONE DIMENSIONAL RANDOM VARIABLES 9+3
Random variables - Probability function – moments – moment generating functions and
their properties – Binomial, Poisson, Geometric, Uniform, Exponential, Gamma and
Normal distributions – Functions of a Random Variable.
UNIT II TWO DIMENSIONAL RANDOM VARIABLES 9+3
Joint distributions – Marginal and Conditional distributions – Functions of two
dimensional random variables – Regression Curve – Correlation.
UNIT III ESTIMATION THEORY 9+3
Unbiased Estimators – Method of Moments – Maximum Likelihood Estimation - Curve
fitting by Principle of least squares – Regression Lines.
UNIT IV TESTING OF HYPOTHESES 9+3
Sampling distributions - Type I and Type II errors - Tests based on Normal, t, Chi-square
and F distributions for testing of mean, variance and proportions – Tests for
Independence of attributes and Goodness of fit.
UNIT V MULTIVARIATE ANALYSIS 9+3
Covariance matrix – Correlation Matrix – Multivariate Normal density function – Principal
components – Sample variation by principal components – Principal components by
graphing.
TOTAL (L:45 + T:15) : 60 PERIODS
REFERENCES :
1. Richard Johnson. ”Miller & Freund’s Probability and Statistics for Engineers”,
Prentice – Hall of India, Private Ltd., New Delhi, 7th Edition, 2007.
2. Richard A. Johnson and Dean W. Wichern, “Applied Multivariate Statistical
Analysis”, Pearson Education, Asia, 5th Edition, 2002.
3. Gupta, S.C. and Kapoor, V.K. ”Fundamentals of Mathematical Statistics”, Sultan
and Sons, New Delhi, 2001.
4. Jay L. Devore, “Probability and statistics for Engineering and the Sciences”,
Thomson and Duxbbury, Singapore, 2002.
5. Dallas E Johnson et al., “Applied multivariate methods for data analysis”,
Thomson and Duxbbury press, Singapore, 1998.