1. Research Methodology IV Operationalisation & Sampling BTech IT Cape Peninsula University (CPUT) Faculty of Informatics & Design (FID) Lecturer: Nhlanhla Mlitwa

2. About Sampling Sampling is a significant aspect of operationalisation. It is equally applicable to both qualitative and quantitative paradigms of research… Data collection tools cannot be designed without first completing the sampling framework. Is that not important enough for you? Oh… Holy cow!!.. what is this sampling thing now? You ask …Good question, let’s discuss it on the next slide

3. …Sampling When you do research, you’re trying to understand the causality between variables. A perfect research would be that where you observe everything there is about a phenomenon. An example: when trying to understand how rapists & murderers engage in their acts (carry out their job), and your unit of analysis are rapists & Murderers, the perfect way is to find every murderer that exists on the planet – to observe/ analyze. But – how realistic is that (re- costs, time & accuracy)?

4. …Sampling Sampling is about selecting a workable sum of your units of observation, from the research population. The principle is that the sample should be representative of the population to enable generalizations about the population. Note: I have just mentioned “research population” and “Generalizations”…! What is a research Oh, and what’s a fuss about generalizations? ( You like asking strange questions, don’t you?) What is a research population? Oh, and what’s a fuss about generalizations? ( You like asking strange questions, don’t you?)

5. …Sampling If you are observing murderers and their actions, then your research population is everyone that rapes. But what if you’re interested only in good murders? Obviously, you exclude the bad ones An academic definition of a research population: “...it is that aggregation of elements from which a sample is actually selected”. A sampling unit is what we have defined as a “unit of analysis”. A sampling element is that unit about which information is needed, i.e. a good murderers.

6. Sampling Students! It seems odd that one may talk of something like a good & a bad murderer – doesn’t it? My point in this is that of conceptualisation. That is, you can only be accurate in identifying the population, if you’ve clarified your concepts, i.e. which murderers am I looking for?

7. …sampling Sampling & generalizability …you need to be able to know something about a research population. So, when you select the sample, you need to ensure that it is as inclusive of all the elements of the population as possible, so that you can make a valid generalization about that population. If all units being studied were the same (constants, & not variables), then there would be no need for sampling as one unit would be an adequate representation of the population. That’s never the case with variables.

8. … sampling Non-probability sampling: In the case of good or bad murderers, there is no exhaustive list of all existing murderers to select from, so random selection of participants (random sampling) will not work for you. Sampling in quantitative research, has a slightly different focus to that of qualitative sampling. There are two types of sampling: Probability & non-probability sampling. Probability sampling: - all elements have an equal probability of being selected into the sample, so you use random sampling. - all elements have an equal probability of being selected into the sample, so you use random sampling.

9. Probability sampling Includes: - Random Sampling - Random Sampling - Stratified sampling - Stratified sampling - Cluster Sampling - Cluster Sampling

10. Non-Probability Sampling Remember in probability sampling – that you have knowledge of your population. You know who, where and how many they are. Remember in probability sampling – that you have knowledge of your population. You know who, where and how many they are. Because of this, you are able to give them an equal probability through random selection, to get into the sample. Because of this, you are able to give them an equal probability through random selection, to get into the sample. Non-probability is a direct opposite. Non-probability is a direct opposite. You have limited knowledge about your research population, hence you cannot do random selection. You have limited knowledge about your research population, hence you cannot do random selection.

11. Non-probability sampling It refers to all non-mathematically random sample-selection methods. These methods include: Haphazard sampling Haphazard sampling Quota Sampling Quota Sampling Purposive sampling Purposive sampling Snowballing Snowballing Deviant case sampling Deviant case sampling Sequential sampling Sequential sampling Theoretical sampling Theoretical sampling

12. Non-Probability sampling Haphazard sampling – is where you select anyone you happen to come across. When would you use this method of sampling? When would you use this method of sampling? When researching problems of a very general nature, that they apply to anyone When researching problems of a very general nature, that they apply to anyone QUOTA SAMPLING: You first identify relevant categories of units that are relevant for your problem (question), then you decide on the numbers you need (p221)

13. Non-random sampling SNOWBALLING – it is about using referrals. SNOWBALLING – it is about using referrals. When do you use this? When do you use this? It is when you are researching cases that are not easily traceable and are hard to identify and locate. It is when you are researching cases that are not easily traceable and are hard to identify and locate. In this case you use the little sources that exist, and rely on them to direct you to others that they know – who in turn, will further refer you to their friends. In this case you use the little sources that exist, and rely on them to direct you to others that they know – who in turn, will further refer you to their friends.

14. Non-random sampling Deviant case: This is when you are studying something that differs from the usual. This is when you are studying something that differs from the usual. In this case, you will see many cases of a pattern that is known. You will ignore them, and when you see a different one, you will select that case. In this case, you will see many cases of a pattern that is known. You will ignore them, and when you see a different one, you will select that case. As your research object would have required, you will then analyze the features that distinguish them from the usual norms As your research object would have required, you will then analyze the features that distinguish them from the usual norms

15. Non-random sampling Sequential: This is often used in conjunction with other methods. This is often used in conjunction with other methods. It sort of addresses the question, when do I stop selecting the units of observation. It sort of addresses the question, when do I stop selecting the units of observation. In this case, you will continue to select your research subject, and continue to dig information out of the new cases until you find a situation where you are not getting anything new In this case, you will continue to select your research subject, and continue to dig information out of the new cases until you find a situation where you are not getting anything new

16. Non-random sampling Theoretical sampling: In this case you’re guided by a specific theoretical position. In this case you’re guided by a specific theoretical position. You select cases that reveal specific information that speaks to your theoretical presuppositions about a case in point. You select cases that reveal specific information that speaks to your theoretical presuppositions about a case in point.

17. In closing, we must discuss the FINAL exercise: - Research Proposal, - Due on 2 June, 2011 - Should be Printed, & hand delivered at 16h30 - All students should be present to carry out an exercise on this assignment at this time!. - You must only write your students number (not your name, please!) - We will be using the basement (close to the computer lab). - If you do not show up, you cannot participate in the exercise, and you cannot get the marks WE ARE TALKING 40% OF THE COURSE HERE thanks ! …Sampling