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Statistical & Numerical Methods using C++

This is the collection of Sikkim Manipal University (SMU) question and answers for Statistical & Numerical Methods using C++. It will help to prepare your examination. All question paper are classified as per semester, subject code and question type of Part A, Part B and Part C with multiple choice options as same as actual examination. SMU question papers includes year 2024, 2023, 2022 Sem I, II, III, IV, V, VI examinations of all subjects.

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Course Name        MCA (Master of Computer Application)

Subject Code       MC0074 (Statistical & Numerical Methods using C++)

Get Questions        PART - A    PART - B    PART - C

Statistical & Numerical Methods using C++ Syllabus.

Part 1: Probability
Introduction; Features of random experiment; Definition of some basic terms; Conditional probability; Baye‘s theorem.

Part 2: Random Variables
Introduction; One-dimensional random variable; Discrete and continuous random variable; Mathematical expectation and variance; Two-dimensional random variable; Marginal and conditional probability distribution; Correlation coefficient; Covariance.

Part 3 : Distribution
Introduction; Bernoulli trials; Poisson distribution; Normal distribution; Uniform distribution; Exponential distribution; Gamma distribution; Chi-square distribution.

Part 4: MGF, Sampling theory and estimation
Introduction; Moment generating function; Functions of random variable; Sampling theory; Point estimation.

Part 5: Statistics
Introduction; Graphical representation; Measures of central tendency; Moments; Skewness; Kurtosis; Curve fitting; Regression.

Part 6: Stochastic process, Marcov-chains
Introduction; Stochastic process; Classification of stochastic process; Bernoulli Poisson process; Markov chains.

Part 7: Errors in Numerical Calculations
Introduction; Accuracy and Significant digit; Rounding off numbers to significant digits; Errors and their computation; Absolute, relative and percentage errors.

Part 8: Matrices and Linear System of Equations
Introduction; Different type of matrices; Operations on matrices; Determinant of matrices; Rank of a matrix; Solution to a system of linear equations; Eigen values and Eigen vectors.

Part 9: Solution of Algebraic and Transcendental Equations
Introduction; Bisection method; Method of false position; Iteration method; Newton-Raphson method; Generalized Newton method.

Part 10: Interpolation
Introduction; Finite differences; Newton‘s forward and backward difference interpolation formulae; Lagrange‘s interpolation formula; Divided differences.

Part 11: Numerical Differentiation and Integration
Introduction; Numerical differentiation; Derivatives using Newton‘s forward and backward difference interpolation formulae; Numerical integration.

Part 12: Numerical Solution of Ordinary Differential Equation
Introduction; Initial value problem; Taylor‘s series method; Euler‘s method; Modified Euler‘s method; Runge-Kutta method of second and fourth order.

Part 13: Introduction to Mathematical Software used for Numerical Analysis
Introduction to MATLAB: Key Features of MATLAB, History of MATLAB, Syntax of MATLAB, Variables, Vectors/Matrices, Semicolon, Graphics, Limitations, Lab Exercise, Numerical Algorithms Group (NAG).
 

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