Random, systematic, convenient, cluster, and stratified sampling are the five types of sampling.
Simple random sampling.
Systematic sampling.
Stratified sampling.
Clustered sampling.
Convenience sampling.
Quota sampling.
Judgement (or Purposive) Sampling.
Snowball sampling.
A sampling strategy in which each sample has an equal chance of being chosen is known as random sampling. A sample drawn at random is supposed to be a fair reflection of the entire population.
The random sampling approach is one in which every item in the population has an equal probability of being chosen for the sample. As a result, this method is also known as the chance sampling method.
In a statistical study, sampling procedures refer to how members of the population are chosen to participate in the research. If a sample isn't chosen at random, it'll almost certainly be prejudiced in some way, and the results won't be representative of the entire population.
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1.easy to understand all topic
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plz provides all notes
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please provide notes also in pdf
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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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