Ans. is 'b' i.e., Systematic random Simple random samplingo Simple random sampling, also, known as 4unrestricted random samplingis applicable for small, homogenous, readily available population and is used in clinical trials,o In simple random sampling each individual is chosen randomly and entirely by chance,o So, each individual has the same probability of being chosen at any stage during the sampling process.For example : -o Let us assume you had a school with 1000 students, divided equally into boys and girls, and you wanted to select 100 of them for further study.o You might put all their names in a bucket and then pull 100 names out.o Not only does each person have an equal chance of being selected, we can also easily calculate the probaility of a given person being chosen, since we know the sample size (n) and population (N) and it becomes a simple matterof division - n/N or 100/1000 = 0.10 (10%).o This means that even' student in the school has a 10% or 1 in 10 chance of being selected using this method.Methods of simple random sampling.Lottery methodRandom number tableComputer sofware - Computer technique.Systematic random samplingo In order to do systematic random sampling, the individuals in a population are arranged in a certain way (for example, alphabetically).o A random starting point is selected and then every n,h (for example 10th or 15th) individual is selected for the sample.o That is, after arranging the individuals in certain pattern (e.g., alpabetically) a starting point is chosen at random, and choices thereafter at regular interv als,o For example, suppose you want to sample 8 houses from a street of 120 houses.o 120/8 = 15, So every' 15th house is chosen after a random starting point between 1 and 15.o If the random starting point is 11, then the houses selected are - 11, 26, 41, 56, 71, 86, 101, and 116.o In contrast to simple random sampling, some houses have a larger selection probabily e.g., in this question 11, 26,41,56, 71, 86, 100 and 116.o While the remaining number can not be selected.Stratified random samplingo When sub-populations vary considerably, it is advantageous to sample each subpopulation (stratum) independently,o Stratification is the process of grouping members of the population into relative hemogenous subgroups before sampling.o The strata should be mutually exclusive, every element in the population must be assigned to only one stratum,o Then systematic random sampling method is applied within each stratum.Population - Stratification - Systematic random sampling - Sample.o This often improves the representativeness of the sample by reducing sampling error.o For example, suppose in a population of 1000, sample of 100 is to be drawn for Hb estimation, first convert the population into homogenous striata (e.g., 700 males and 300 females), then draw 70 males and 30 females by doing systematic random sampling.