Paper I, Semester I · 4 credits · 4 instruction hours per week
Source document. This page reproduces the syllabus this course was written to, as published — its semesters, credits and paper numbers are that document’s, not this site’s. The course itself is studied on its own, in any order.
This page reproduces the prescribed outline for the paper, so that the teaching
pages can be checked against it line by line. It is the syllabus, not a summary of it. Nothing
about marks, duration or examination pattern appears on this site.
Course Objectives
Able to understand the Theoretical Probability and Distributions and Statistical Inference
which are based on Advanced concepts of Real Analysis, Complex Analysis.
Able to understand the concepts of Limits, continuity, completeness of set, supremum,
infimum, sequence and series, Convergences, R-S Integrations, Multiple integrations, etc.
Course Outcomes
Able to understand the basic concepts of real analysis.
Strong foundations in understanding Probability & Distribution concepts.
Able to understand convergence of sequence and series of real valued function.
Understand existence of integral and their evaluation.
Understand change of multiple integral and Lebesgue integral.
Unit I
AS PRESCRIBED
Metric spaces — Compact sets — Perfect sets — Connected sets. Limits of
functions — Continuous functions — Continuity and compactness, Continuity and
connectedness, Discontinuities — Monotonic functions, Differentiation.
Integrators of Bounded variations. Statements of necessary and sufficient conditions of
Riemann–Stieltjes integral. Differentiation under the integral sign. Interchanging the
order of integration.
Sequences and Series of Functions: Uniform convergence — Uniform convergence and
continuity — Uniform convergence and integration — Uniform convergence and
differentiation — The Stone–Weierstrass theorem.