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Sampling

Need of Sampling
Probability Sampling
Nonprobability Sampling
Method of Sampling

Home >> Data Analysis >> Sampling
Data Sampling
Sampling is very important task in data analysis. If you are unaware about the sample size, sample need, sample methods you can never get the accurate results in the end.

Sample Size and Considration

Need of Sampling

In real life situation it is impossible to study whole population due to many reason depends upon different situations in which population occurs. Cost and time are two very important factor that makes study of population impossible.

Cost: Suppose your company send food container from your country to other countries. Due to some reason your manager thinks, the food boxes that had been packed already have some problem in it. Your taks is to make sure every thing is correct. If you open a box and examine it then repack it, it costs you $120. So if you have 1000 boxes and you check each individual box that will costs you 1000*120=$120000. So it is not practical to open all the boxes.

Time:The second important factor is time. Suppose your manager is interested to get feed back about new product(launched last month). You have assigned a limited geographical area (25km). If you going to cover the whole area that will take approximately 1 month. So its better to select some areas from that range so that you can finish your job with 2-4 days.

NOTE: There may be many other reasons that makes population study impossible. Each such reason come into picture due to different situation in which population occurs.

All sampling methods can be divided into two categories. First is probability sampling and second is non-probability sampling.

Probability Sampling

Nonprobability Sampling

Methods of Sampling
Random Sampling
Systematic Sampling
Stratified Sampling
Convenience Sampling

Judgment Sampling
Quota Sampling
Snowball Sampling
Cluster (Area) Random Sampling
Multi Stage Sampling