Syllabus
Inverted Beta Distribution, Noncentral Beta Distribution, Beta Binomial Distribution, Cauchy Distribution, Noncentral Chi-Squared Distribution, Dirichlet Distribution, Empirical Distribution Function, Erlang Distribution, Error Distribution, Generalized Exponential Distributions, Noncentral F-distribution, Inverted Gamma Distribution, Normal Gamma Distribution, Generalized Gamma Distribution, Inverse Gaussian (Wald) Distribution, Lognormal Distribution, Pareto Distribution, Power Function Distribution, Power Series (Discrete) Distribution, Wishart (Central) Distribution.
Objectives and Outcomes
Course Outcomes:
CO1: To understand the basics of different beta distributions.
CO2: To understand the distribution like Empirical and Erlang.
CO3: Know the importance of inverse Gama distribution and generalized exponential distribution.
CO4: To understand the inverse Gaussian distribution and Lognormal distribution.
CO-PO Mapping:
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PO1
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PO2
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PO3
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PO4
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PO5
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PO5
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PO6
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PO7
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PO8
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PO9
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PO10
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PO11
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PO12
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CO1
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2
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3
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2
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2
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2
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2
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|
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2
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1
|
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CO2
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2
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2
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2
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2
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2
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2
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|
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2
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1
|
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CO3
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2
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2
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2
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2
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2
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3
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|
|
|
|
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2
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1
|
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CO4
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2
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2
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1
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2
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2
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2
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|
|
|
|
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2
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1
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Text Books / References
Text Books /Reference Books
- Catherine Forbes, Merran Evens, Nicholas Hastings and Brian Peacock. (2010). Statistical
Distributions, Fourth Edition, Wiley & Sons Publication, USA.
- Karl Bury (1999) : Statistical distributions in Engineering , Cambridge University Press.
3. Thomopoulos, Nick T (2017): Statistical Distributions: Applications and Parameter Estimates, Springer.
