COMM3710 - Fall 2011 - Section 001 - Lecture Notes - 09/20

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Logic of significance testing is the logic of the negative. What is actually tested for a hypothesis is the null hypothesis. The null hypothesis always says no difference or no relationship. So the null hypothesis is what is always tested not the research hypothesis. So if something is really different then you reject the null and retained the alternative or the working hypothesis. If there is a normal distribution with no real significance then you fail to reject the null. Then decide on the probability level which for social scientist is 5%. So alpha ยต is 0.05.

Every time you do an experiment there are four possible outcomes.
Your Decision
Null is True
Alternative is true
Reject null
Type I Error; Alpha
Correct decision
Fail to reject the null
Correct decision
Type II error

You can control the type I error. You just change your alpha. In society we always concentrate on type I errors and almost never type II errors.