Psychology 2810 Lecture Notes - Lecture 11: Point Estimation, Bias Of An Estimator, Standard Deviation
30 Dec 2016
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Review session: dec. 14th, wednesday, 11-2, room 8440 ssc. ***review questions for christmas exam on owl. Sometimes you have hypothesis, and sample stats and all that, but not parameters. In the real world, you don"t get sigma (ie. standard deviation of a population) The bigger n is, the more close s is to sigma (sample sd to pop sd) So nothing changes in calculation if you have a big n, but if you have a small n, you would recognize that you cannot work with the z tables. It"s a dif. kind of statistic- a t statistic, not z statistic. T distribution characteristics: 1. mean = 0 (like z, 2. symmetric (like z, 3. larger variance than z- more probability of being extreme from the mean, more spread out. probability of getting bigger numbers higher. You get a bigger tail because you get smaller denominator in the equation: 4. unlike z, t depends on n.
