This course introduces the basics of data communication and networking. Students will develop an understanding of the general principles of data communication and networking as used in networks. It also includes an activity of setting up a small local area network. The goal of this course is that the student will develop an understanding of the structure of network, its elements and how these elements operate and communicate with each other.
Collecting Data, Kinds of Data, Frequency Distribution of a Variable, Graphical Representation of Frequency Distribution, Summarisation of Data, Measures of Central Tendency, Measures of Dispersion or Variability
Unit 2 : Probability ConceptsPreliminaries, Trials, Sample Space, Events, Algebra of Events, Probability Concepts, Probability of an Event, Probability of Compound Events, Conditional Probability and Independent Events
Unit 3 : Probability DistributionsRandom Variable, Discrete Random Variable, Continuous Random Variable, Binomial Distribution, Poisson Distribution, Uniform Distribution, Normal Distribution
Population and Samples, What is a Sampling Distribution, t-distribution, Chi-Square distribution F-distribution
Unit 5 : EstimationPoint Estimation, Criteria For a Good Estimator, Interval Estimation, Confidence Interval for Mean with Known Variance, Confidence Interval for Mean with Known Variance, Confidence Interval for Proportion
Unit 6 : Tests of SignificanceSome Basic Concepts, Tests About the Mean, Difference in the Means of Two Populations Test About the Variance
Unit 7 : Applications of Chi-Square in Problems with Categorical DataGoodness-of-fit, Test of Independence
Analysis of Variance: Basic Concepts, Source of Variance, One-Way Classification Model for One-Way Classification, Test Procedure, Sums of Squares, Preparation of ANOVA Table, Pairwise Comparisons, Unbalanced Data, Random Effects Model
Unit 9 : Regression AnalysisSimple Linear Regression, Measures of Goodness of Fit, Multiple Linear Regression, Preliminaries, Regression with Two Independent Variables
Unit 10 : Forecasting and Time Series AnalysisForecasting, Time Series and Their Components ,Long-term Trend, Seasonal Variations, Cyclic Variations, Random Variations/Irregular Fluctuations, Forecasting Models, The Additive Model, The Multiplicative Model, Forecasting Long-term Trends, The Methods of Least Squares, The Methods of Moving Averages, Exponential Smoothing.
Unit 11 : Statistical Quality ControlConcept of Quality, Nature of Quality Control, Statistical Process Control, Concepts of Variation, Control Charts, Control Charts For Variables, Process Capability Analysis, Control Charts For Attributes, Acceptance Sampling, Sampling Plan Concepts, Single Sampling Plans.
Sampling- What and Why? Preliminaries, Simple Random Sampling, Estimation of Population Parameters Systematic Sampling, Linear Systematic Sampling, Circular Systematic Sampling, Advantages and, Limitations of Systematic Sampling
Unit 13 : Stratified SamplingStratified Sampling, Preliminaries, Advantages, Estimation of population parameters, Allocation of sample size, Construction of strata, Post-Stratification
Unit 14 : Cluster Sampling and Multistage SamplingCluster Sampling, Preliminaries, Estimation of population mean, Efficiency of cluster sampling Multistage sampling, Preliminaries, Estimation of mean in two stage sampling
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