1. Chapter 2 Review MDM 4U Mr. Lieff

2. 2.2 – In Search of Good Data What are the variables in a study? The information that is collected What types of variables exist? Quantitative Continuous – decimals are possible Discrete – only whole numbers Qualitative - description Cross-Sectional – data is collected once Longitudinal Studies – the same data is collected in regular intervals

3. 2.3 Collecting Samples Why do we sample? Census is expensive and time consuming Valid inferences can be made from a representative sample Convenience sampling – not representative Clinical Studies Treatment – the active drug Treatment Group – gets the drug Control Group – gets a treatment with no value Placebo – a placeholder for the drug Double Blind Test – neither the participants nor the researchers know who gets the treatment

4. 2.4 Random Sampling Methods Simple – names in a hat; generate random numbers Systematic sampling interval n = (population size) ÷ (sample size) Generate a random starting point between 1 and n Start there and sample every n th member Stratified – grouped population; take a proportional simple random sample of each group Cluster – grouped population; randomly select groups and sample entire group Multistage – grouped population; randomly select groups and take a simple random sample of each group

5. 2.4 Destructive Sampling Destructive Sampling – element cannot be returned to the population batteries, lightbulbs, cars, standardized testing Ex: destructive simple random sample: pick 10 batteries out of a bin of 100 and test Ex: destructive systematic random sample: test every 10 th battery (10% sample)

6. 2.5 Types of Bias Sampling Bias – poorly chosen sample Non-Response Bias – selected respondents do not provide data Household Bias – groups are not represented proportionally Response Bias – problems with the survey or surveyor

7. Chapter 2 Review pp. 136-137 #1abd, 2, 4–6, 8 #7: Canada’s Population 35.16 million (2013)