1. Unit 2 Review

2. Developing a Thesis A thesis is a question or statement that the research will answer When writing a thesis, ask: Is it specific? Are the main variables identified? How will they be measured? Is there enough data to make an interesting analysis? Is the topic manageable? A hypothesis is a prediction of what you expect to find

3. Collecting data Different types of data: Quantitative Qualitative Time series

4. Sampling Poor data collection methods lead to bias in the data A biased sample does not represent the population Can be due to intentional or unintentional influences Choosing the sample randomly avoids bias A conclusion drawn from sample data is called an inference The larger the sample size, the better the results

5. Types of studies Cross sectional (snapshot of a situation) Longitudinal (studies same individuals over time)

6. Types of random sampling Simple Systematic Choose a random starting point, then sample every n th individual (n = population size / sample size) Stratified Divide population into groups called strata Use simple random sample on each strata Cluster Order population into groups Choose random groups to sample, and sample all members of chosen group Multistage Groups are randomly chosen from population Subgroups are randomly chosen from groups Individuals are randomly chosen from subgroups

7. Survey questions Bad questions lead to bad data Good questions may lead to good data, but is not guaranteed Question types: Open questions Closed questions Information Checklist Ranking Rating

8. Characteristics of good questions Be simple, relevant, specific, readable Be written without jargon/slang, abbreviations, acronyms, etc. Not lead the respondents Allow for all possible responses on closed Qs Be sensitive to the respondents

9. Bias When a sample is not representative of the population, it is biased Types of bias: Sampling bias (chosen sample does not accurately represent population) Non-response bias (data is not collected from potential respondents) Household bias (types of respondent are over- or under- represented because groups of different sizes are polled equally) Response bias (factors of sampling method bias the results)