PSYC 3000 Lecture Notes - Lecture 6: Sampling Distribution, Chi-Squared Distribution, Level Of Measurement

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2 Aug 2016
Department
Course
PSYC 3000
Sept 24
Hypothesis Testing
-hypothesis are always made about the population
-use sample to test it.
-sampling distribution is the probability of different outcomes for this experiment
Test of the mean
-step 1: statistic chosen=mean
-make a hypothesis about nature of the mean in population
-measure the mean in the sample.
-every time you take a sample, you look at the sample of the mean. Eventually you will look at sampling
distribution of the mean.
-leptokurtic=thin and pointy
-platykurtic=flat distribution
-the way to create a sampling distribution is to take many samples from the same population. The mean
won’t be the same for every sample.
-after many samples have been taken the shape of the distribution will not move around much.
Test of the skew
-hypothesis a skew in a population (ex: 0)
-take many random sample and calculate the skew from each.
-end result is always conclusion about the population.
Test of the variance
-called the chi square test
-will always give a chi square distribution.
-because the variance can never be 0 your hypothesis can never a normal distribution but always a
positively skewed one.
Test of a proportion
-when testing nominal data you change it to proportions. You would estimate that a proportion of the
population
-when asking a “yes/no” question you must give yes and no a numeric value
Test of the mean
-a test of pairs of means could be carried out to find out if the difference is significant
-every time a test is listed in a paper it will have a p value.
P values
-different p values will yield different data
-whatever your alpha level is it exists independent of your data. Your alpha level is chosen before your
data is collected.
-p values arrive out of your data.
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