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Semester 1: Real Analysis and Linear Algebra

  • Metric Space open, closed sets Intervals rectangles

    Metric Space, Open and Closed Sets, Intervals, Rectangles
    A metric space is a set equipped with a distance function that defines the distance between any two points in the set.
    • Non-negativity: Distance is always non-negative.

    • Identity: The distance between two points is zero if and only if the points are the same.

    • Symmetry: The distance from point A to point B is the same as from B to A.

    • Triangle inequality: The distance from A to C is less than or equal to the distance from A to B plus the distance from B to C.

    • Euclidean space: R^n with the standard distance metric.

    • Discrete metric space: A set with distance defined as 0 if points are the same, and 1 otherwise.

    An open set in a metric space is a set where, for every point within the set, there exists a radius such that the ball centered at that point is entirely contained in the set.
    • Any union of open sets is open.

    • Any finite intersection of open sets is open.

    • Open intervals (a, b) in R.

    • Open balls in R^n.

    A closed set contains all its boundary points, meaning it includes its limit points.
    • Any intersection of closed sets is closed.

    • Any finite union of closed sets is closed.

    • Closed intervals [a, b] in R.

    • The set of all limit points of a sequence in a metric space.

    An interval (a, b) where a and b are not included.
    An interval [a, b] where a and b are included.
    An interval [a, b) or (a, b] where one endpoint is included and the other is not.
    • Any closed interval is a closed set.

    • Any open interval is an open set.

    A rectangle in R^n can be defined as a Cartesian product of closed intervals.
    • Rectangles are closed sets in the standard Euclidean topology.

    • Open rectangles can be defined as the Cartesian product of open intervals.

    • In R^2, a rectangle can be defined as [a1, b1] x [a2, b2].

    • Open rectangles are of the form (a1, b1) x (a2, b2).

  • Real valued Continuous functions- Discontinuities - compact sets

    Real valued Continuous functions - Discontinuities - Compact sets
    • Definition of Continuous Functions

      A function f is continuous at a point c if for every epsilon greater than 0, there exists a delta greater than 0 such that whenever the distance between x and c is less than delta, the distance between f(x) and f(c) is less than epsilon.

    • Types of Discontinuities

      1. Removable Discontinuity: The limit of f(x) as x approaches c exists, but f(c) is not equal to this limit. 2. Jump Discontinuity: The left-hand limit and right-hand limit at c exist, but they are not equal. 3. Infinite Discontinuity: The function approaches infinity as x approaches c.

    • Compact Sets

      A set K in a metric space is compact if every open cover of K has a finite subcover. This is equivalent to saying that K is closed and bounded, according to the Heine-Borel theorem in Euclidean spaces.

    • Continuous Functions on Compact Sets

      If f is a continuous function on a compact set K, then f is uniformly continuous on K. Furthermore, f attains its maximum and minimum values on K.

    • Importance of Discontinuities in Analysis

      Discontinuities play a crucial role in understanding the behavior of functions. They affect integrability, differentiability, and the application of theorems such as the Intermediate Value Theorem.

    • Examples of Continuous and Discontinuous Functions

      1. Continuous Function: f(x) = x^2 is continuous everywhere. 2. Discontinuous Function: f(x) = 1/x for x!=0 and f(0) = 0 is discontinuous at x = 0.

  • Bolzano Weirstrass theorem, Heine Borel theorem

    Bolzano Weierstrass Theorem and Heine Borel Theorem
    • Bolzano Weierstrass Theorem

      The Bolzano Weierstrass theorem states that every bounded sequence in R^n has a convergent subsequence. This theorem is essential in real analysis as it guarantees the presence of limit points and underpins many fundamental concepts such as compactness and closure of sets.

    • Boundedness

      A set is considered bounded if there exists a real number M such that the distance between any two points in the set is less than M. This condition is crucial for the application of the Bolzano Weierstrass theorem.

    • Convergent Subsequences

      A subsequence of a sequence is derived by selecting certain elements while preserving the original order. A sequence is convergent if its terms approach a specific value as the index increases.

    • Heine Borel Theorem

      The Heine Borel theorem characterizes compact subsets of R^n. It states that a subset of R^n is compact if and only if it is closed and bounded. This theorem is fundamental for analyzing continuity and convergence in real analysis.

    • Closed Sets

      A set is closed if it contains all its limit points. Closed sets are crucial in determining compactness and are often utilized in limits and continuity.

    • Relation Between Both Theorems

      Both theorems emphasize important properties of sets in R^n, focusing on boundedness and convergence. The Bolzano Weierstrass theorem applies to sequences, while the Heine Borel theorem provides a criterion for compactness in terms of closure and boundedness.

  • Derivatives, maxima and minima, Riemann integral, Riemann Stieltjes integral

    Derivatives, Maxima and Minima, Riemann Integral, Riemann-Stieltjes Integral
    • Derivatives

    • Maxima and Minima

    • Riemann Integral

    • Riemann-Stieltjes Integral

Real Analysis and Linear Algebra

M.Sc. Statistics

Real Analysis and Linear Algebra

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Periyar University

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