1. Statistics for the Behavioral Sciences (5th ed.) Gravetter & Wallnau
Chapter 8 Introduction to Hypothesis Testing
University of Guelph Psychology 3320 — Dr. K. Hennig Winter 2003 Term

2. The logic
experience-> question (What is it? Why…?)-> insight (hypothesis)-> “Is it so?”
As text has it:
State your hypothesis (e.g., MIQ for voters is =110)
thus we would predict that our sample M = 110
Obtain a random sample from the population (e.g., n = 200 registered voters) and compute M
Compare M with predicted M
Intellig- ability
Intellig- ence

3. Fig. 8.2 Tx Tx Population a) actual research situation Treated Sample
b) pt. of view of hypothesis test
Population
Treated Sample Tx

4. Step 1: State the hypothesis
Question: does handling a infant have an effect on body weight?
null hypothesis stated: assume that in the general population there is no change, no effect, no difference (nothing happened)
H0: infants handled = 26 lbs. (even with handling)
the alternative hypothesis states there is a change, effect, difference
H1: infants handled <> 26 lbs. (handling makes a difference) - both ref. to popultns

5. Step 2: Set the criteria
If the Ho is true, sample means will be close to the null hypothesis
unlikely sample means will be very different from the null hypothesis (in the tails of the distribution)
criteria separating the likely from the unlikely sample
Alpha level ( or level of significance): p value used to define the unlikely sample
critical regions: very unlikely if the null hypothesis is true - if sample falls within, reject null hypothesis

6. Set the criteria (contd.)
 = .05 (boundaries separate the extreme 5% from the middle 95%)
see Column C (the tail) in the tail: z = 1.96 and z = -1.96
Similarly,  = .01, 99%: z =  2.58
Similiary,  = .001: z =  3/30

7. Step 3: Collect data
Select parents and randomly assign to training program of daily handling (= Tx)
Weigh after 2 years
summarize the data using the appropriate statistics (e.g., M)
Compare with the null hypothesis by transforming into z-score

8. Step 4: Make a decision (“It is/not so!”)
Calculate: M = 30 lbs. at age 2; sample size = n = 16, and  = 4

9. (contd.)
Why do we focus on the null hypothesis? Why assume there is no change?
negative thinking?
“innocent until proven guilty?” - burden of proof
“Is it so?” vs. “Is it not so?”
Logically, easier to falsify vs. verify (?)
E.g., All dogs have four legs!
E.g., state, the Tx works and then try and prove vs. the Tx has no effect and try to show false (conclude: insufficient evidence)