Probability and Queueing Theory Syllabus for B.Tech 4th sem is covered here. This gives the details about credits, number of hours and other details along with reference books for the course.<\/p>\n
The detailed syllabus for Probability and Queueing Theory B.Tech (R13) fourthsem is as follows<\/p>\n
OBJECTIVES:<\/strong> UNIT I RANDOM VARIABLES \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/strong>(9+3 \u00a0 hours) UNIT II TWO – DIMENSIONAL RANDOM VARIABLES<\/strong> \u00a0\u00a0\u00a0 <\/strong>(9+3 \u00a0 hours) UNIT III RANDOM PROCESSES<\/strong> \u00a0 \u00a0\u00a0\u00a0 <\/strong>(9+3 \u00a0 hours) Download iStudy<\/a> Android<\/a> App for complete Anna University syllabus, results, timetables and all other updates. There are no ads and no pdfs and will make your life way easier.<\/a><\/strong><\/p>\n TOTAL (L:45+T:15): 60 PERIODS<\/strong><\/p>\n OUTCOMES:<\/strong><\/p>\n TEXT BOOKS:<\/strong><\/p>\n REFERENCES:<\/strong><\/p>\n
\nTo provide the required mathematical support in real life problems and develop probabilistic models which can be used in several areas of science and engineering.<\/p>\n
\nDiscrete and continuous random variables \u2013 Moments \u2013 Moment generating functions \u2013 Binomial, Poisson, Geometric, Uniform, Exponential, Gamma and Normal distributions.<\/p>\n
\nJoint distributions \u2013 Marginal and conditional distributions \u2013 Covariance \u2013 Correlation and Linear regression \u2013 Transformation of random variables.<\/p>\n
\nClassification \u2013 Stationary process \u2013 Markov process – Poisson process \u2013 Discrete parameter Markov chain \u2013 Chapman Kolmogorov equations \u2013 Limiting distributions.<\/p>\n\n
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