Probability Sampling

Sampling techniques can be divided into two categories: probability and non-probability. In probability sampling, each population member has a known, non-zero chance of participating in the study. Randomization or chance is the core of probability sampling techniques. If you are using this type of sampling you need to specify this in research methodology chapter of your dissertation briefly mentioning its advantages and disadvantages as discussed below.

In non-probability sampling, on the other hand, sample group members are selected non-randomly, therefore, in non-probability sampling only certain members of the population has a chance to participate in the study.

Probability sampling comprises the following sampling techniques:

Application of Probability Sampling: an Example

Let’s suppose, your dissertation topic is ‘A study into employee motivation of ABC Company and the ways of increasing it’. You chose survey primary data collection method to achieve research objectives. ABC Company has 400 employees and you decided that the sample size of 60 employees should be sufficient for the purposes of the research.

In this case, simple random sampling, the most basic form of probability sampling technique can be applied via using a table of randomly generated numbers.  Websites such as Generate Data, Graph Pad, Mockaroo and many others can be used to do this task easily and quickly.

Now, all you have to do is to choose a starting point in the table (a row and column number) and look at the random numbers that appear there. In this case, since the data run into three digits, the random numbers would need to contain three digits as well. You need to ignore all the random numbers after 400, since your target population has only 400 members. Also, choose a specific number only once and if a number recurs, simply skip it and move to the next number. In this way, the first 60 different numbers between 001 and 400 that represent 60 employees of ABC Company constitute your sample group.

Advantages of Probability Sampling

  1. The absence of systematic and sampling bias
  2. Higher level of reliability of research findings
  3. Increased accuracy of sampling error estimation
  4. The possibility to make inferences about the population

Disadvantages of Probability Sampling

  1. Higher complexity compared to non-probability sampling
  2. More time consuming
  3. Usually more expensive than non-probability sampling

My e-book, The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step approach contains a detailed, yet simple explanation of sampling methods. The e-book explains all stages of the research process starting from the selection of the research area to writing personal reflection. Important elements of dissertations such as research philosophy, research approach, research design, methods of data collection and data analysis are explained in this e-book in simple words. John Dudovskiy

Probability Sampling