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there are two types of data collection: 1. complete/total sampling- all members of the population are measured 2. partial sampling- a proportion of members of the whole population is measured. total enumeration is preferred for certain types of data. it has a high level of accuracy and provides a complete statistical coverage over space and time.
It is called one-stage cluster sampling. If random samples are taken within the selected clusters then it is two-stage cluster sampling.
sampling time is the number of samples per second taken from a continuous signal to make it discrete and holding time is the time between two samples..
two types is: 1. Descriptive statistics. 2. Inferential statistics.
There are a number of benefits and drawbacks to stratified sampling. Two benefits are:You have a cross-section of the population, so this is more likely to be representative and thus easier to generalise.You are less likely to get a "freak" sample.Two drawbacks are:This is a very long and difficult form of sampling. It could be inconvenient or costly.You may not stratify the population by the relevant factors - what if their gender isn't important, but their economic bracket is?