• Distinguish between a meta-analysis and a case study. • Distinguish between observational studies and experimental studies. • Learn the basic techniques for choosing a sample.
40 Process of a Study
41 Observational Studies • An observational study observes data that already exists. • No manipulation of the sample is performed by the researchers. • No cause-effect relationships can be determined between variables. – For example, if we collect data on SAT scores and the GPA of freshmen college students, we might find a relationship between the variables, but it would be inappropriate to conclude a cause and effect relationship.
42 Observational Studies • A researcher collects data from a sample of the population . • A representative sample is one that as the relevant characteristics as the population and does not favor one group of the population over the other. • In choosing a sample, we need a sampling frame which is list of all members of the population from which a sample can be drawn.
43 Observational Studies • There are several basic methods of choosing a sample from a population . • If the goal is to collect information from a representative sample, the best one we could find is the entire population. • Gathering data from every member of the population is called a census .
44 Observational Studies • A census is impractical because of the following reasons: – It can be too time consuming. – It can be too expensive. – Also, the data collection could be destructive in nature.
45 Random Sampling • A random sample is one in which every member of the population has an equal chance of being selected. • Random sampling can be performed using the following methods: – Writing names on pieces paper, put the pieces of paper in hat and drawing names at random from the hat. – Assigning numbers to names and using a random number table or a random number generator to select the sample.
46 Random Sampling
47 Stratified Sampling • A stratified sample is one in which members of the population are divided into two or more subgroups, called strata , that share similar characteristics like age, gender, or ethnicity.
48 Stratified Sampling • The separate samples from the different strata do not need to be the same size. • The total sample could be drawn so that the proportion from each strata reflects the composition of the population.
49 Cluster Sampling • A cluster sample is one chosen by dividing the population into groups, called clusters , that are each similar to the entire population. The reseacher then randomly selects some of the clusters. • The sample consists of the data collected from every member of each cluster selected.
50 Systematic Sampling • A systematic sample is one chosen by selecting every n th member of the population.
- Fall '18
- F. TAILOKA
- researcher, observational studies