Probabilty Sampling

Probability sampling is also known as ‘random sampling’ or ‘chance

sampling’. Under this sampling design, every item of the universe has an equal chance of inclusion in

the sample. It is, so to say, a lottery method in which individual units are picked up from the whole

group not deliberately but by some mechanical process. Here it is blind chance alone that determines

whether one item or the other is selected. The results obtained from probability or random sampling

can be assured in terms of probability i.e., we can measure the errors of estimation or the significance

of results obtained from a random sample, and this fact brings out the superiority of random sampling

design over the deliberate sampling design. Random sampling ensures the law of Statistical Regularity

which states that if on an average the sample chosen is a random one, the sample will have the same

composition and characteristics as the universe. This is the reason why random sampling is considered

as the best technique of selecting a representative sample.

Random sampling from a finite population refers to that method of sample selection which gives

each possible sample combination an equal probability of being picked up and each item in the entire

population to have an equal chance of being included in the sample. This applies to sampling without

replacement i.e., once an item is selected for the sample, it cannot appear in the sample again

(Sampling with replacement is used less frequently in which procedure the element selected for the

sample is returned to the population before the next element is selected. In such a situation the same

element could appear twice in the same sample before the second element is chosen). In brief, the

implications of random sampling (or simple random sampling) are:

(a) It gives each element in the population an equal probability of getting into the sample; and

all choices are independent of one another.

(b) It gives each possible sample...