Probability and Queuing Theory detailed syllabus scheme for B.Tech Information Technology (IT), 2019-20 onwards has been taken from the DBATU official website and presented for the Bachelor of Technology students. For Subject Code, Course Title, Lecutres, Tutorials, Practice, Credits, and other information, do visit full semester subjects post given below.
For all other DBATU Syllabus for Information Technology 5th Sem 2019-20, do visit IT 5th Sem 2019-20 Onwards Scheme. The detailed syllabus scheme for probability and queuing theory is as follows.
Probability and Queuing Theory Syllabus for Information Technology (IT) 3rd Year 5th Sem 2019-20 DBATU
Prerequisites:
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Course Objectives:
- Be through with probability concepts.
- To acquire knowledge on Probability Distributions.
- Get exposed to the testing of hypothesis using distributions.
- Gain strong knowledge inn principles of Queuing theory.
- Get exposed to Discrete time Markov chain.
Course Outcomes:
- To acquire analytical ability in solving mathematical problems as applied to the respective branches of engineering.
UNIT I
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UNIT II
Theoretical Distributions: Discrete Probability distribution: Binomial distribution – MGF, Mean, Variance, Applications of Binomial distribution, Fitting a Binomial distribution, Poisson distribution – MGF, Mean, Variance, Applications of Poisson distribution, Fitting a Poisson distribution, Geometric distribution – MGF, Mean, Variance, Memoryless Property , Applications of Geometric distribution, Continuous Probability Distributions: Uniform distribution – MGF, Mean, Variance & Applications, Exponential Distribution – MGF, Mean, Variance, Memoryless Property Applications of Exponential distribution, Normal distribution – Mean, Variance, Standard Normal distribution and Applications of Normal distribution
UNIT III
Testing of Hypothesis: Introduction to Sampling Distributions, Population and Sample, Null Hypothesis and Alternative Hypothesis, Single and Two Tailed Test. Testing of Hypothesis, Level of Significance, Critical Region, Procedure for Testing of Hypothesis Large Sample Test- Test for Single Proportion, Two Sample Proportions. Large Sample Test- Test for Single Mean, Two Sample Means. Small Sample Tests – t Test For a Single Mean t” Test For The Difference Of Means, Paired t” Test F Test – Test of Significance of the Difference between Two Population Variances. Chi Square Test for Goodness of Fit, Independence of Attributes.
UNIT IV
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UNIT V
Markov Chains: Introduction to Stochastic process, Markov process, Markov chain one step & n-step Transition Probability, TPM and Applications, Chapman Kolmogorov theorem (Statement only), Applications on Chapman Kolmogorov theorem.
UNIT VI
MARKOV CHAINS: Transition probability- Applications, Classification of states of a Markov chain, Classification of states of a Markov chain – Applications.
Text Books:
- Veerarajan T., Probability, Statistics and Random Processes, Tata McGraw Hill, 1st Reprint 2004.
- S.C. Gupta and V.K. Kapoor, Fundamentals of Mathematical Statistics, Sultan Chand & Sons, 9th extensively revised Eition,1999
Reference Books:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
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For detail syllabus of all other subjects of Information Technology (IT) 5th Sem 2019-20 regulation, visit IT 5th Sem Subjects syllabus for 2019-20 regulation.