There are two types of probability distributions, each of which is utilised for different objectives and data creation processes.
The probability distribution is either normal or cumulative.
The probability distribution is either binomial or discrete.
A probability distribution for a given random variable is a function or table of values that translates the sample space's outcomes to their probabilities. For instance, in a coin tossing experiment, the sample space is. {HH, HT, TH, TT}.
The probability of an event is calculated using the following formula: P(A) = n(A)/n(S)
Chance distributions aid in the modelling of our environment by allowing us to estimate the probability of a specific event occurring or the variability of its occurrence. They're a frequent approach to express and possibly predict an event's likelihood.
Statisticians divide probability distributions into the following types: Discrete Probability Distributions. Continuous Probability Distributions.
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1.easy to understand all topic
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plz provides all notes
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plzz provide notes....
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please provide notes also in pdf
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please provide course notes
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Shashi Kumar
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great resource to learn data science in hindi. but in this particular video lecture there is a mistake....actually mutually exclusive event can never be independent event.
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it really amazing to study....and easily understand difficult concepts...i hope you make more video on like power bi and nueral network model....its really helpful....thank you for these
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