NON -PROBABILITY SAMPLING AMNA ALI

Sampling The process of obtaining information from a subset (sample) of a larger group (population) The results for the sample are then used to make estimates of the larger group Faster and cheaper than asking the entire population Two keys Selecting the right people Have to be selected scientifically so that they are representative of the population Selecting the right number of the right people To minimize sampling errors I.e. choosing the wrong people by chance

Classification of Sampling Techniques Nonprobability Sampling Techniques Probability Sampling Techniques Convenience Sampling Judgmental Quota Snowball Simple Random Sampling Other Sampling Techniques Systematic Sampling Stratified Sampling Cluster Sampling

Types of Sampling Probability sample – a method of sampling that uses of random selection so that all units/ cases in the population have an equal probability of being chosen. Non-probability sample – does not involve random selection and methods are not based on the rationale of probability theory. Click to add notes

Selecting a Sampling Design Non-probability sampling - - unequal chance of being included in the sample (non-random) convenience sampling purposive sampling (judgement sampling,quota sampling) snowball sampling

Types of Non-Probability Sampling 1. Convenience Sampling (at will) A researcher's convenience forms the basis for selecting a sample. data is collected from the most convenient source people in my classes Mall intercepts

2. PURPOSIVE (discretion) you actually choose whom to involve in a sample. In purposive sampling, we sample with a purpose in mind. We usually would have one or more specific predefined groups we are seeking. eg. females between 30-40 years old. They size up the people passing by and anyone who looks to be in that category they stop to ask if they will participate. One of the first things they're likely to do is verify that the respondent does in fact meet the criteria for being in the sample. Purposive sampling can be very useful for situations where you need to reach a targeted sample quickly and where sampling for proportionality is not the primary concern.

Judgement Sampling A researcher exerts some effort in selecting a sample that seems to be most appropriate for the study.Judgmental sampling design is usually used when a limited number of individuals possess the trait of interest. It is the only viable sampling technique in obtaining information from a very specific group of people. It is also possible to use judgmental sampling if the researcher knows a reliable professional or authority that he thinks is capable of assembling a representative sample.

Quota Sampling In quota sampling, you select people nonrandomly according to some fixed quota. The population is divided into cells on the basis of relevant control characteristics. 50 women, 50 men The problem here (as in much purposive sampling) is that you have to decide the specific characteristics on which you will base the quota. Will it be by gender, age, education race, religion, etc.?

3. Snowball Sampling In snowball sampling, you begin by identifying someone who meets the criteria for inclusion in your study. You then ask them to recommend others who they may know who also meet the criteria. Although this method would hardly lead to representative samples, there are times when it may be the best method available Selection of additional respondents is based on referrals from the initial respondents. friends of friends

eg. if you are studying the homeless, you are not likely to be able to find good lists of homeless people within a specific geographical area. However, if you go to that area and identify one or two, you may find that they know very well who the other homeless people in their vicinity are and how you can find them.

Choosing Nonprobability vs. Probability Sampling

Non-probability sampling: Advantages: This is more accurate because you are targeting a specific group, therefore your answers will be similar to what the rest of the population (of this group) will answer. Disadvantages: This is more biased, because the individuals chosen are not at random. They also might not represent what another population thinks