1. Psychology 202a Advanced Psychological Statistics October 20, 2015

2. Effect sizes Not necessarily standardized. Evil journal editors. Standardized effect sizes corresponding to one-sample tests. d = (M –    s Effect sizes for differences between means. ‏ d = (M 1 – M 2  s P What’s large? What’s small? It depends.

3. Confidence intervals Goal: to find a range of reasonable values for a parameter based on a statistic and its sampling distribution. Question: what null hypotheses would I not reject on the basis of these data? The 100 * (1-  ) % CI for the mean:

4. Things the 95% confidence interval doesn't mean There is a 95% probability that  is between (lower bound) and (upper bound). I am 95% certain (or confident) that  is between (lower bound) and (upper bound). There is a 95% chance that the interval (lower bound) to (upper bound) contains . If I conduct confidence intervals in this way, 95% of the time,  will be between (lower bound) and (upper bound)‏

5. Things the 95% confidence interval does mean There is a 95% chance that the confidence interval resulting from the sample I am about to take will contain  If I conduct intervals in this way, 95% of the time, whatever interval I get will contain . Therefore, it is reasonable to act as if this interval contains ......because if I do so, in the long run, I will act correctly 95% of the time. Confidence intervals and duck-hunting statisticians.