Random, systematic, convenient, cluster, and stratified sampling are the five types of sampling.
Simple random sampling.
Judgement (or Purposive) 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.
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.
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
please provide course notes
Prakash Suresh Lokhande
Great. please provide pdf notes
MD Mishkat Ahsan
plzz provide pdf notes also
Mujhe ye link Sanjeev Sir k ek vedio se mili.. & i am very happy to watch this vedio..
& my all doughts are clear..