Distinguish between a meta analysis and a case study Distinguish between

# Distinguish between a meta analysis and a case study

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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.

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• Fall '18
• F. TAILOKA
• researcher, observational studies