JNTUK R20 2-2 Complex Variables and Statistical Methods Material PDF Download

JNTUK R20 2-2 Complex Variables and Statistical Methods Material PDF Download

Students those who are studying JNTUK R20 Civil Branch, Can Download Unit wise R20 2-2 Complex Variables and Statistical Methods (CV&SM) Material/Notes PDFs below.

JNTUK R20 2-2 Complex Variables and Statistical Methods Material PDF Download

OBJECTIVES:

• To familiarize the complex variables.
• To make the student capable of evaluating the integrals in complex domains
• To make the student capable of expanding a given function as a series and finding the poles and residues
• To make the student capable of evaluating the integrals in complex domains using residue theorem
• To familiarize the students with the foundations of probability and statistical methods.
• To equip the students to solve application problems in their disciplines.

UNIT-1

Functions of a complex variable and Complex integration:

Introduction – Continuity – Differentiability – Analyticity –Cauchy-Riemann equations in Cartesian and polar coordinates – Harmonicand conjugate harmonic functions – Milne – Thompson method. Complex integration: Line integral – Cauchy’s integral theorem – Cauchy’s integral formula – Generalized integral formula (all without proofs) and problems on above theorems.

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UNIT-2

Series expansions and Residue Theorem: Radius of convergence – Expansion in Taylor’s series, Maclaurin’s series and Laurent series. Types of Singularities: Isolated – pole of order m – Essential – Residues – Residue theorem ( without proof) – Evaluation of real integral of the type f x dx

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UNIT-3

Probability and Distributions: Review of probability and Baye’s theorem – Random variables – Discrete and Continuous random variables – Distribution functions – Probability mass function, Probability density function and Cumulative distribution functions – Mathematical Expectation and Variance – Binomial, Poisson, Uniform and Normal distributions.

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UNIT-4:

Sampling Theory: Introduction – Population and Samples – Sampling distribution of Means and Variance (definition only) – Central limit theorem (without proof) – Representation of the normal theory distributions – Introduction to t, 2  and F-distributions – Point and Interval estimations – Maximum error of estimate.

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UNIT-5:

Tests of Hypothesis: Introduction – Hypothesis – Null and Alternative Hypothesis – Type I and Type II errors – Level of significance – One tail and two-tail tests – Tests concerning one mean and two means (Large and Small samples) – Tests on proportions.

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TEXT BOOKS:

1. B. S. Grewal, Higher Engineering Mathematics, 43rd Edition, Khanna Publishers.
2. Miller and Freund’s, Probability and Statistics for Engineers, 7/e, Pearson, 2008.

REFERENCES:

1. J. W. Brown and R. V. Churchill, Complex Variables and Applications, 9th edition, McGraw Hill, 2013
2. S. C. Gupta and V. K. Kapoor, Fundamentals of Mathematical Statistics, 11/e, Sultan Chand & Sons Publications, 2012.
3. Jay l. Devore, Probability and Statistics for Engineering and the Sciences, 8th Edition, Cengage.
4. Shron L. Myers, Keying Ye, Ronald E Walpole, Probability and Statistics Engineers and the Scientists, 8th Edition, Pearson 2007.
5. Sheldon, M. Ross, Introduction to probability and statistics Engineers and the Scientists, 4th Edition, Academic Foundation, 2011

OUTCOMES:

• apply Cauchy-Riemann equations to complex functions in order to determine whether a given continuous function is analytic (L3)
• find the differentiation and integration of complex functions used in engineering problems (L5)
• make use of the Cauchy residue theorem to evaluate certain integrals (L3)
• apply discrete and continuous probability distributions (L3)
• design the components of a classical hypothesis test (L6)
• infer the statistical inferential methods based on small and large sampling tests (L4)