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Probability, Statistics & Linear Programming Laboratory (BS202)

Room F-501                

  • Lab Incharge                  –   Dr. Nishi Deepa Palo 
  • Lab Assistant               —   Mr. Vijay
  • Subjects                         –  Probability Statistics and LPP Lab 

The Probability, Statistics and Linear Programming (LPP) Laboratory is part of the Applied Science Department and is offered to students in the Fourth Semester of the academic program. The laboratory is designed to provide practical exposure to statistical analysis, probability modeling, and optimization techniques.

The lab is equipped with 20 well-configured computer systems installed with updated software to support computational experiments, simulations, and problem-solving activities. It also features a smart board facility for interactive teaching and live demonstrations, ensuring technology-enabled learning. The modern infrastructure helps students perform data analysis, visualization, and linear programming applications effectively, thereby connecting theoretical concepts with real-world practice.

The laboratory provides a modern and conducive learning atmosphere that enhances analytical thinking, computational skills, and industry-relevant problem-solving abilities among students.

Objectives

(i) To enable students to understand and apply probability distributions, statistical inference, and optimization techniques through computational experiments.

(ii) To provide hands-on training using updated statistical and mathematical software for real-time data analysis and modeling.

(iii) To bridge the gap between theoretical concepts and practical implementation through simulations, case studies, and problem-solving sessions.

(iv) To enhance students’ logical reasoning, analytical abilities, and decision-making skills relevant to industry and research.

  • 4th Semester – 10 experiments

List of Experiments

  1. Introduction to MATLAB Environment and Basic Programming Constructs.
  2. Fitting of Binomial Distribution using MATLAB.
  3. Fitting of Poisson Distribution using MATLAB.
  4. Fitting of Normal Distribution using MATLAB.
  5. Linear Regression Analysis and Goodness of Fit.
  6. Multiple Linear Regression using MATLAB.
  7. Solution of Transportation Problem using North-West Corner Method.
  8. Solution of Assignment Problem using MATLAB.
  9. Solution of Transportation Problem using Least Cost Method.
  10. Solution of Linear Programming Problem using Simplex Method.