Joint probability distribution for discrete random variable GOOD example(PART-1)

In this video explaining one problem of joint probability. This probability is discrete random variable. This topic helps in engineering and science students. The joint probability distribution for discrete random variables represents the probability of all possible combinations of outcomes of the random variables. It can be represented by a probability mass function (PMF) which gives the probability of each possible combination of outcomes.

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Joint Probability & Sampling Theory: 18MAT41 & 17MAT41

Probability Distributions: 18MAT41 & 17MAT41

Calculus of Complex Functions: 18MAT41 & 17MAT41

Curve fitting & Statistical Method 18MAT41 17MAT31

LAPLACE TRANSFORM : 18MAT31

Fourier Transforms,Z-transform : 18MAT31 & 17MAT31

Fourier Series: 18MAT31 & 17MAT31

Calculus of Variation & Numerical Methods 18MAT31

Numerical Methods ODE's: 18MAT31 & 17MAT41

COMPLEX NUMBER: 18MATDIP31

Differential Calculus:18MATDIP31

Ordinary differential equation 18MATDIP31,17MATDIP31

Integral Calculus 18MATDIP31,17MATDIP31

Vector differentiation 18MATDIP31,17MATDIP31

Differential Calculus & Partial Differential 18MATDIP31,17MATDIP31

18MATDIP41 Linear Algebra

18MATDIP41 Numerical Methods

18MATDIP41 Higher order ODEs

18MATDIP41 Partial Differential Equations

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[ravitegar]

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[James]

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[hassansaboor]

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[suhasgn]

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[akashnaikodi]

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[vishalir]

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[sushmithaswamy]

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[تلاوةالقرآنالكريم-جب]

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I from Jordan and I understand all what you said, God bless you

[parthadutta]

nice video sir
but what is the solution of h(x/y)=1
plz reply....plzz

[apobangpo]

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.I understood this video well...

[dikshagupta]

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[tapiwatamirepi]

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[swathireddy]

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[mufidsyed]

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[shivarai]

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[NayonR]

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[pavirenu]

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It was really very helpful 🤝