# Best sampling method

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I have learned a lot about sampling method from my school. Everything is fine to me but sometimes I cannot determine how I can choice best sampling method for my research. Is there any short-cut method?

### 1 comment to Best sampling method

• Jack

Actually, though it is frustrating, there is no shortcut method of choosing sampling method in SPSS research. Your statement of problem will guide you to choose the best sampling method. But I can give you an illustration so that you can do this task step by step.

1. First think clearly about your problem statement of your SPSS research. In your notebook, clearly mark that what you want to know from this statement.

2. Then find out the two main things. One is related to maximize precision and another one is budget.

3. As you already know the sampling method, just try to think what method will be fitted best to achieve your objective. Ask yourself several times. Should it be simple random sampling? Or stratified sampling? Or cluster one? If this will be a cluster one, then ask yourself- will it be one-stage or two-stage cluster sample? Should you consider sampling with replacement versus sampling without replacement? In this stage, your main task is to find out the all possible ways and put different types of questions from different angles.

4. After finishing the previous stage, you will find two or three method can be taken for your SPSS research. Now you need to think about budget. Look about the amount of money as well as time. Compare your methods regarding time and money. You will find the suitable method shortly.

You may think it a long process. Actually you are right in a sense that in first some SPSS researches, you will have to fight with yourself to determine the best sampling method. But it is also true that you will be familiar with that within a short time if you do this practice seriously. Achieving some experiences, you can identify the best sampling method later on. So, for the best sweets, you have to hard work for first few days.