Exploring Populations

1. Exploring Populations How can I best understand and represent a population? O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

2. Understanding the Process • We don’t often speak to everyone we wish to speak about - so understanding populations often involves: • sampling • investigating • concluding • and attempting to argue the broader applicability of our findings O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

3. The Sampling Process • The process of sample selection involves: • naming your population • determining sample size • and employing appropriate sampling strategies O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

4. Naming your Population • Populations are commonly made up of individuals, but can be made up of households, workplaces, or events • Populations are then narrowed through defining characteristics such as geographic range. Additional defining characteristics include age, class, gender, and/ or race – or in the case of an organization, number of employees, years of operation, type of business, etc. O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

5. Determining Sample Size • Sample size very much depends on the nature of your research and the shape and form of the data you intend to collect • The best way to come up with a figure is to consider: • your goals (transferability or generalizability) • the parameters of your population (size and how easy it is to identify and find its elements) • and the type of data you plan to collect O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

6. Random Sampling • Random sampling refers to sampling strategies that give every element of a population an equal chance of selection. Strategies include: • simple random sampling • systematic sampling • stratified random sampling • and cluster sampling O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

7.                                         Simple Random Sampling In simple random sampling all elements of a population have an equal chance of inclusion. It is considered ‘fair’, but rarely used in practice because the process demands: identification of all elements of the population; lists of all those elements; and finally a way of randomly selecting from this list. O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

8.                                         Systematic Sampling Systematic sampling involves selecting every nth case within a defined population. It may involve going to every 10th house or selecting every 20th person on a list. It is easier to do than devising methods for random selection, and offers a close approximation of random sampling as long as the elements are randomly ordered. O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

9.                                         Stratified Random Sampling Stratified random sampling involves dividing your population into various subgroups and then taking a simple random (or systematic) sample within each one. O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

10.                               Cluster Sampling Cluster sampling involves surveying whole clusters of the population selected through a defined random sampling strategy. The thinking here is that the best way to find high school students is through high schools; or the best way to find church goers is through churches. O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

11. Non-Random Sampling • Non-random sampling refers to strategic requests for ‘volunteers’; the use of informants that ‘snowball’; or ‘hand picking’ respondents • Keep in mind that selecting a sample on the basis of convenience alone can threaten a study's credibility O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

12.         Handpicked Sampling Handpicked sampling involves selecting cases that meet particular criteria; are considered typical; show wide variance; represent ‘expertise’; or cover a range of possibilities. Other options include the selection of critical, extreme, deviant, or politically important cases. O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

13.              Snowball Sampling Snowball sampling is often used for populations that are not easily identified or accessed; and involves building a sample through referrals, i.e.) you identify someone from your population willing to be in your study. You then ask them to identify others who meet the study criteria. Each of those individuals is then asked for further recommendations. O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

14.       Volunteer Sampling Volunteer sampling simply refers to the process of selecting a sample by asking for volunteers. This may involve putting an ad in the newspaper or going to local organizations such as churches, schools, or community groups. O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight

15. Methods of Data Collection and Analysis • Traditionally, population studies involved the use of survey questionnaires, quantitative data, random samples, and statistical analysis • However, a variety of methods, data types, modes of analysis, and the use of non-random samples have broadened possibilities for understanding populations O'Leary, Z. (2004) The Essential Guide to Doing Research. London: Sage Chapter Eight