GLHLTH 371 Lecture Notes - Lecture 9: Standard Deviation, Null Hypothesis, Effect Size
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Published on 9 May 2016
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2/16/16
- Test will be mostly multiple choice, some calculations, and then interpreting a table
- Don’t need to memorize or know things from readings, they are just to understand the
applications of the research methods
I. Variance
a. Describes how much scores vary around the mean
a.i. Scores tightly clustered = small variance
b. Variance Calculation
b.i. Find the mean of all the values
b.ii. Find difference between each score and the mean
b.iii. Square each difference
b.iii.1. Makes sure there are no negative values
b.iii.2. Also just helps…?
b.iv. Find the sum of the squares
b.v. Divide by n if it is the whole population, divide by n-1 if it is a sample and not
the whole population; this yields the variance
b.vi. Then take the square root of this (the variance) to get the standard deviation
c. Be able to calculate:
c.i. Mode, median, and range
II. Power
a. The probability that you will reject the null hypothesis when you should (when there is a
true difference)
b. Probability of detecting a real effect if one exists
c. Power = 1-beta (where beta is probability of making a type two error)
d. Know how power depends on:
d.i. Alpha level: increasing alpha, increases power; increasing likelihood that you
would be able to reject the null-hypothesis
d.ii. Sample size: increasing sample size increases power since that gets a more
accurate
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