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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 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 and Outcomes

  1. Use various data types, loop statements, OOPs concepts, Exemptions, string operations etc for a specified problem.
  2. Design, implement, debug a given problem using Python.
  3. Execute the programs using derived and user defined data types.
  4. Implement programs using modular approach and file I/O.
  5. Writing Python code for any statistical methods for the given data data set.

Both Theoretical and Practical Concepts to be Covered

AS PRESCRIBED

Introduction to Python Programming, Input, Processing and Output, Displaying Output with the Print Function, Comments, Variables, Reading Input from the Keyboard, Performing Calculations Operators. Type conversions, Expressions, More about Data Output. Decision Structures and Boolean Logic: if, if-else, if-elif-else Statements, Nested Decision Structures, Comparing Strings, Logical Operators, Boolean Variables. Repetition Structures: recursion and non-recursion, while loop, for loop, Calculating a Running Total, Input Validation Loops, Nested Loops. python-syntax, statements, functions, Built-in-functions and Methods, Modules in python, Exception Handling. Functions: Defining and Calling a Void Function, designing a Program to Use Functions, Local Variables, Passing Arguments to Functions, Global Variables and Global Constants, Value-Returning Functions, Generating Random Numbers, Writing Our Own Value-Returning Functions, The math Module, Storing Functions in Modules. File and Exceptions: Introduction to File Input and Output, Using Loops to Process Files, Processing Records, Exceptions. Finding Items in Lists with in-Operator, List Methods and Useful Built-in Functions, Copying Lists, Processing Lists, Two-Dimensional Lists, Tuples. Strings: Basic String Operations, String Slicing, Testing, Searching, and Manipulating Strings.

Covered by Python Programming and Data Structures, Units 1 to 5.

List of Practicals to be Implemented

AS PRESCRIBED

Note: Must able to write Programs with all possibilities like usage of functions, Loops, OOP concepts, methods, built in functions etc. wherever it is possible. Without usage of Python Packages for statistical tools.

  1. Program to find the sum and product of two matrices.
  2. Program to find the Determinant and Inverse of the given matrix.
  3. Program to sort the given set of numbers using bubble sort, Quicksort, Merge sort, insertion sort. Program for linear search, binary search.
  4. Program to find the Median, Mode for the given of array of elements.
  5. Program for preparation of frequency tables, Computation of mean, median, mode, variance and standard deviation to the given data set.
  6. Program to compute first four Central & Non-central moments, Skewness and Kurtosis to the given data set.
  7. Program to generate random numbers from Uniform, Binomial, Poisson, Normal and Exponential distributions using algorithms.
  8. Program to Fit Binomial, Poisson & Negative Binomial distributions for the given data set and testing their goodness of fit and drawing the curve plots.
  9. Program to Fit Normal, Exponential & Cauchy distributions for given data set.
  10. Program for finding Correlation and regression lines for the given data set.
  11. Program for testing means, variances, correlations.
  12. Program for carryout the analysis of variance for one way and two way.

→ All twelve, written and run