A probability is a number that represents the possibility of an event occurring. Probabilities can be stated as percentages ranging from 0% to 100% or as proportions ranging from 0 to 1.
There are three kinds of conditional probabilities - mutually exclusive, exhaustive, and dependent. Mutual exclusivity means that there’s only one possible outcome for each outcome; Expansive means that all outcomes have been examined; Dependent means that the outcome is dependent on another event.
P(E) = [Number of favourable outcomes of E]/[total number of possible outcomes of E] is the probability of an occurrence E. 2. A sure occurrence or certain event has a probability of 1.
The addition, multiplication, and complement laws are the three basic rules of probability. The likelihood of event A or event B occurring is calculated using the addition rule, which is expressed as: P(A or B) = P(A) + P(B) - P(A and B)
Probability is a mathematical concept that describes the likelihood of something happening. Weather patterns, for example, are used by meteorologists to forecast the likelihood of rain. Probability theory is utilised in epidemiology to investigate the relationship between exposures and the risk of adverse health outcomes.
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Akash Sambhaji
5
plz provides all notes
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Jamil Akhtar
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plzz provide notes....
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Sunita Singhal
5
please provide notes also in pdf
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Montu Mali
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nice ☺️👍
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Abdul Samed
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please provide course notes
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Shashi Kumar
5
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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Nikhil Fapale
5
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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