1. SAMPLING

2. EXTERNAL VALDITY The accuracy with which the result of an investigation maybe generalized to a different group from the one studied.

3. Terminologies to Define Population – a group of people with particular characteristics of interest Universe- a group on non-human elements with particular characteristics of interest Parameters- specific characteristic that must be present for an individual to fit that group

4. Terminologies to Define Census- approach use by researchers in collecting and studying all elements in the group Sample- subset of the population or universe thought to represent the entire group Sampling Error- the degree to which a sample’s parameters differ from parameters of population/universe from which it was selected

5. Factors Influencing Sampling Error 1.Size of the sample created 2.The homogeneity of the population or universe

6. Sampling Methods There are two main types of sampling namely: a.Probability Sampling b.Non-Probability Sampling

7. Probability Sampling  The selection of elements from a population or universe in accordance with some set of mathematical rules, thereby permitting calculation of the probability of sampling error  Is one in which every unit of the population has an equal probability of being selected for the sample. This remains the primary method for selecting large, representative samples for social science and business researches.

8. Types of Probability Sampling Simple- Random Sampling -Each element in the population or universe is afforded an equal opportunity of being selected to the sample.

9. Techniques of Simple-Random Sampling: Techniques: 1.Lottery – the researcher separates the elements from one another, mixes them in a container and selects one element at a time until the determined size is reached a.Lottery w/out Replacement – each selected element is kept out of the pool of elements, thereby reducing the entire pool by one b.Lottery with Replacement- elements are returned to the pool following their selection, thereby keeping the pool of elements equal in size throughout the selection process

10. Techniques of Simple-Random Sampling: Techniques: 2. Random Numbers – number generators or electronic devices are needed on this type, a range and the number needed for sample is given 3. Random Digit Dialing- widely use in USA for phone type of survey

11. Types of Probability Sampling Systematic Sampling -Every nth element is selected following a random start -It is randomly selecting the first respondent and then every nth person after that. The number ‘n’ is called the sampling interval.

12. Types of Probability Sampling Stratified Sampling - When the population is divided into different strata or sub- groups and sample units are taken in a simple random method from each group. The final sample contains sample units from all these strata.

13. Types of Probability Sampling Multi-stage Cluster Sampling - This sampling implies dividing population into clusters and drawing random sample either from all clusters or selected clusters. Initial clusters are called primary sampling units; clusters within the secondary clusters are called multi-stage clusters. For example, dividing one city into various wards, each ward into areas, each area into neighborhood and each neighborhood into lanes and so on.

14. Non-Probability Sampling  Mass media researchers frequently use non-probability sampling. This is the kind of sampling where all sampling units don’t have the equal chance of selection.  Non adherence to mathematical rules is very visible on this type of sampling method

15. Types of Non-Probability Sampling Convenience or Available Sampling -This is known as accidental or haphazard sampling. This is a collection of readily accessible subjects for study. -Easily accessible and in its pure form, without any consideration of mathematical rules

16. Types of Non-Probability Sampling Volunteer Sampling - Nonprobability technique, sample elements are selected based on their agreement to participate in a research

17. Types of Non-Probability Sampling Purposive Sampling -It is also known as judgmental sampling. It includes subjects or elements selected for specific characteristics or qualities and eliminates those who fail to meet those criteria. -Example: Often used in advertising studies where researchers select the subjects who use a particular type of product and ask them to compare it with a new product.

18. Types of Non-Probability Sampling Quota Sampling - Subjects are selected to a predetermined or known percentage/quota. - Elements are selected from the population or universe in proportion to the incidence of some characteristic of interest to the researcher

19. Types of Non-Probability Sampling Snowball-Sampling/ Network Sampling - In this technique, the researcher begins the research with a few respondents who are known and available to him. Subsequently, the respondents give other names who meet the criteria of research, who in turn give more names. This process is continued until adequate numbers of persons are interviewed or until no more respondents are discovered. - This method is employed when the target population is unknown or when it is difficult to approach the respondents in any other way.