Calculate K, Mean & Variance in Discrete Random Variable

Veröffentlicht am: 14 Februar 2020
auf dem Kanal: Perfect Computer Engineer

39,850

804

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Notes:
[I/II]MATHS- 4 Price: ( Rs.99 )
Topics covered are:
1. Eigenvalues & Eigenvectors
Cayley - Hamilton Theorem
Derogatory & Non - Derogatory Matrices
Function of Square Matrix
Eigenvalues & Eigenvectors
Diagonalizable Matrix
Theorems & Proofs
2. Probability
Probability & Mathematical Expectation
Some Standard Distributions
Binomial Distribution
Poisson Distribution
Normal Distribution
Bayes' Theorem
3. Complex Integration
Complex Integration
Cauchy's Theorem
Taylor's & Laurent's series
Residues
4. Sampling
Large Sample Test
Small Sample Test
Independence of Attributes
Goodness of Fitting
5. Non - Linear Programming
Type 1: Inequality with one subjected condition ( Kuhn - Tucker)
Type 2: Inequality with two subjected conditions ( Kuhn - Tucker )
Type 3: No subjected condition
Type 4: Equality with one subjected condition
Type 5: Equality with two subjected conditions
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[II/II]Module Name- Probability Price: ( Rs.49)
Topics Covered are:-
Probability & Mathematical Expectation (Discrete & Continues Random Variable, Moment Generating Function, Raw & Central Moment)
Binomial Distribution
Poisson Distribution
Normal Distribution
Bayes' Theorem
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