1. S-005 Sampling

2. Some basic terminology Population –Larger group (the research population) –Sometimes can be quite small Sample –A subset of the population Probability samples –Let us generalize to the population / provide “unbiased estimates” Non-probability samples (be careful!) –For exploratory research / convenience Census –Information from everyone in the population Sample information –Information from a subset

3. Advantages and limitations of samples Advantages –Faster –Less expensive Time Resources –Only way to collect data –Can specify size And margins of error –Often (almost always) more accurate than census –Others? Limitations –Can get a “wild” or unrepresentative sample –May really need complete information Studying small populations or rare conditions –Limitations on generalizing –Others?

4. Sample sizes for surveys (not for intervention studies) Three important factors influence the size of sample that we need 1.Margin of error How close do we need to be? Or what is our “margin of error?” Often we decide this by looking at other studies 2.Level of confidence How confident should we be in our results? 95% is common (100% is not possible) 3.Variance in the population How variable is the group? More variability means we need a larger sample so we can capture the variability Less variability means we can get by with a smaller sample We need information from prior studies, or perhaps we need a pilot study For some studies we need an idea of the “percentage” e.g., the percentage “in favor” or “saying yes” For other studies we use the “standard deviation”

5. A formula for sample size Sample size (n) Level of confidence Margin of error Variance in population For estimating a percentage or proportion

6. A formula for sample size Sample size (n) Level of confidence Margin of error Variance in population For estimating a mean score for a group