Electricity, Magnetism: Electrical Charge, Coulomb’s law, electric field, dipole and flux of electric field and flux density, Gauss’s law, electric potential, potential energy. Magnetic field, Magnetic flux and flux density, Ampere’s law, Biot Savart’s law, Faraday’s law of Induction, Inductance, Energy in the Magnetic field. Optics: Defects of images, spherical aberration, astigmatism, coma, distortion, curvature, chromatic aberration. Light, interference of light, Young’s experiment, Fresnel prism, interference. Newton’s rings, interferometers, Diffraction, resolving power of optical instruments, diffraction grating; Polarization and polarized light. Brewster’s law, polarization by double refraction, Nicol prism, optical activity and Polarimeters. The course includes lab works based on theory taught.

# Course Catalogue

Statistics:

Introduction to Statistics: what is statistics, statistical data, statistical methods, scope and limitation of statistics, Populations and Samples, collection and presentation of data, Grouped Data and Histograms, Some Graphical Methods: bar charts, time plots, Pie charts, scatter plots, box and Whisker plots, Measure of Central Tendency: mean , median and mode, Measure of Variations, Measure of Skewness, Moments and Kurtosis, difference between Variation and Skewness, Correlation and Regression Analysis: significance of the study of correlation, types of correlation, difference between correlation and regression Analysis, Sampling and Sampling Distributions, Survey Sampling Methods.

Probability:

Probability: meaning of probability, classical definition of probability, statistical probability, some theorems in probability, distribution function, probability distributions:

Binomial, normal and exponential distributions.

Operations Management (OM) is concerned with the management of resources and activities that produce and deliver goods and services for customers. In addition to explaining the concept of Operations as a Competitive Weapon, Operations Strategy and Process Management some of the major tools of Operations Management to be covered are: Total Quality Control, Statistical Process Control, Location, Layout, Capacity, Supply-Chain Management and Inventory Management, Resource Planning and Scheduling.

Introduction. Sets and probability. Random variable and its probability distribution. Treatment of grouped sampled data. Some discrete probability distribution. Normal distribution. Sampling theory. Estimation theory. Tests of hypothesis. Regression and correlation. Analysis of variance.

Statistics:

Introduction to Statistics: what is statistics, statistical data, statistical methods, scope and limitation of statistics, Populations and Samples, collection and presentation of data, Grouped Data and Histograms, Some Graphical Methods: bar charts, time plots, Pie charts, scatter plots, box and Whisker plots, Measure of Central Tendency: mean , median and mode, Measure of Variations, Measure of Skewness, Moments and Kurtosis, difference between Variation and Skewness, Correlation and Regression Analysis: significance of the study of correlation, types of correlation, difference between correlation and regression Analysis, Sampling and Sampling Distributions, Survey Sampling Methods.

Probability:

Probability: meaning of probability, classical definition of probability, statistical probability, some theorems in probability, distribution function, probability distributions:

Binomial, normal and exponential distributions.