SOC202H1 Lecture Notes - Lecture 6: Standard Deviation, Standard Score, Falsifiability
Document Summary
Introduction to quantitative methods lecture 6: statistic vs parameter: a statistic is something calculated based on a sample, and a parameter a quantity that relates to a population, statistical analyses including significance testing: We use data from a sample to learn something about the population. Every sample will yield somewhat different results. There is a level of uncertainty about how well the sample represents the characteristics of the population. We use significance tests to gauge whether we found the results based on our sample by pure chance a lone or due to sampling variability or whether they are likely to be present in the population. Significant= very unlikely to be caused by random chance a lone. Level of measurement of variables: formulate hypotheses: Must be falsifiable: counter example of the hypothesis must be tautological statement (statement that is always true) Possible to empirically observe whether or not the evidence supports the hypothesis: null hypothesis:
