Expectation and Variance
| Institution | Jomo Kenyatta University of Science and Technology |
| Course | Information Technol... |
| Year | 2nd Year |
| Semester | Unknown |
| Posted By | Jeff Odhiambo |
| File Type | |
| Pages | 30 Pages |
| File Size | 233.95 KB |
| Views | 3431 |
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Description
Expectation and Variance are fundamental concepts in probability and statistics. The expectation (or expected value) of a random variable represents its theoretical average over an infinite number of trials, essentially summarizing the central tendency of its probability distribution. It is calculated as the weighted sum of all possible values of the variable, where the weights are their respective probabilities. Variance, on the other hand, measures the dispersion or spread of the random variable around its expectation. It quantifies how much the values deviate, on average, from the mean, and is calculated as the expected value of the squared differences between the variable and its mean. Together, expectation and variance provide a comprehensive understanding of a random variable’s behavior, highlighting both its central value and the variability around it.
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SMA 2371: Partial Differential Equations (Complete Notes, Examples & Solutions) – JKUAT Biostatistics Year 2 Semester 2
These are comprehensive and well-organized lecture notes for SMA 2371: Partial Differential Equations (PDE) offered to BSc. Biostatistics Year 2 Semester 2 students at JKUAT. The notes are neatly arranged from lecture one to the final topics, making them ideal for class learning, revision, CAT preparation, and final examinations.
The notes include detailed explanations, worked examples, step-by-step mathematical derivations, solved exercises, and applications of Partial Differential Equations. Topics covered include:
• Review of basic concepts and partial derivatives
• Jacobians, surfaces and curves in three dimensions
• Simultaneous first-order differential equations
• Methods of solving symmetric differential equations
• Orthogonal trajectories
• Pfaffian differential equations
• Linear first-order partial differential equations
• Formation of PDEs
• Elimination of arbitrary constants and arbitrary functions
• Heat, Wave, Laplace and Poisson equations
• Separation of variables
• Fourier and Laplace Transform methods
• Numerous worked examples, tutorial questions and examination-style problems with solutions.
These notes are suitable for JKUAT students and other university students studying Mathematics, Statistics, Biostatistics, Engineering, Applied Mathematics or related courses. They are an excellent revision resource for CATs and final examinations.
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