1. Institute of Professional Studies School of Research and Graduate Studies Selecting Samples and Negotiating Access Lecture Eight

2. Outline of Presentation  Introduction  The need to sample  Overview of sampling techniques  Deciding on a suitable sample size  Choosing the appropriate sampling technique  Checking the sample representativeness  Strategies to gain access 2

3. Introduction Whatever your research question(s) and objective(s), you will need to consider whether you need to use sampling or not. Sometimes it may be possible to analyse data from every possible case or group members (i.e. Census), but for other times, it may be impossible to either collect or analyse all the data available due to constraints of time, money and access. In In such instances sampling becomes your best bet. 3

4. What is Sampling Sampling refers to the techniques that enable you to reduce the amount of data you need to collect by considering only data from a subgroup rather than all possible cases or elements. Some research questions will require sample data to generalize about all the cases from which your sample has been selected, hence you will want your sample to be representative of the population from which it was drawn. 4

5. The need to sample Sampling provides a valid alternative census when: 1. It would be impracticable for you to survey the entire population 2. Your budget constraints prevent you from surveying the entire population 3. Your time constraints prevent you from surveying the entire population 4. You have collected all the data but need the results quicker than census analysis will allow 5

6. How to obtain a representative sample The steps to follow are: 6 1. Define the target population. 2. Choose the sampling frame. 3. Select the sampling method. 4. Determine the sample size. 5. Implement the sampling plan.

7. Defining Target population and sampling frame Target population is the complete group of objects or elements relevant to the research project. They are relevant because they possess the information the research project is designed to collect. Sampling frame is a complete list of all the elements in the population from which the sample is drawn 7

8. Overview of sampling techniques Sampling techniques can be divided into two: 1. Probability or representative sampling; 2. Non-probability sampling or judgmental sampling Probability: each element of the population has a known, but not necessarily equal, probability of being selected in a sample. Non-Probability: not every element of the target population has a chance of being selected because the inclusion or exclusion of elements in a sample is left to the discretion of the researcher. 8

9. Sampling methods/techniques ProbabilityNon-Probability 9 Simple Random Systematic Stratified Cluster Multi-Stage Convenience Judgment Snowball/Referral Quota

10. Probability sampling methods Simple random sampling is a sampling method in which each element of the population has an equal probability of being selected. Systematic sampling is a sampling process that involves randomly selecting an initial starting point on a list, and thereafter every n th element in the sampling frame.. Stratified sampling requires the researcher to partition the target population into relatively homogeneous subgroups that are distinct and non-overlapping. Proportionate: the number of elements chosen from each of the strata is proportionate to the size of a particular strata relative to the overall sample size. Disproportionate: the number of elements chosen from each of the strata is not based on the size of the stratum relative to the target population size, but rather is based either on the importance of a particular stratum or its variability. 10

11. Probability sampling methods Cont’d Cluster sampling is a form of probability sampling in which the relatively homogeneous individual clusters where sampling occurs are chosen randomly and not all clusters are sampled. Cluster sampling involves dividing the population into clusters and randomly selecting a pre-specified number of clusters and then either collecting information from all the elements in each cluster or a random sample. With multi- stage cluster sampling the same process is completed two or more times. 11

12. Non-probability sampling Methods Convenience sampling involves selecting sample elements that are most readily available to participate in the study and who can provide the required information. Judgmental sampling is a form of convenience sampling, sometimes referred to as a purposive sample, in which the researcher’s judgment is used to select the sample elements. Quota sampling is similar to proportionately stratified random sampling but the selection of the elements from the strata is done on a convenience basis. Snowball also called a referral sample, the initial respondents typically are chosen using probability methods and these respondents then identify others in the target population. 12

13. Factors to consider when determining the sample size  The variability of elements in the target population.  Time available.  Budget.  Required estimation precision.  Whether findings will be generalized. 13

14. Statistical Factors to consider 1. The degree of confidence (often 95%). 2. The specified level of precision (amount of acceptable error). 3. The amount of variability (population homogeneity). 14

15. Calculation of minimum sample size n=p%*q%*[z/e%]^2 Where n is the minimum sample sized required p% is proportion belonging to the specified category q% is proportion not belonging to the specified category Z is the z-value corresponding to the level of confidence required e% is the margin of error required 15

16. Calculating Minimum Sample Size Cont’d If the population is less than 10000 a smaller sample size can be used without affecting accuracy. This is called adjusted minimum sample n’=n/{1+(n/N)} Where: n’ is the adjusted minimum sample size n is the minimum sample size (as calculated) N is the total population 16

17. Negotiating access in research Your ability to obtain both primary data and secondary data will depend on you gaining access to an appropriate source, or sources where there is a choice. There are two level of access you need to negotiate: 1. Physical access: Can be difficult because: i. The organisation may not be willing to engage in additional activities ii. The request may fail to meet the interest of the organisation 2. Cognitive access 17

18. Strategies to gain access The following strategies can help you gain access: 1. Allow yourself sufficient time 2. Using existing and new contacts 3. Provide a clear account of purpose and type of access required 4. Overcome organisational concerns 5. Highlight possible benefits to the organisation 6. Use suitable language 7. Facilitate replies 8. Develop access incrementally 9. Establish credibility 18

19. Thank you 19