Understanding and Generalizing Results

1
Understanding and Generalizing Results

• Chapters 13 14

2
Inferential Statistics

• Use to determine if our results are due to a true
  treatment effect
• Orif they are due to random error

3
Hypotheses

• Null hypothesis
• H0 There is no difference between the treatment
  group and the control group
• Research Hypothesis
• H1 There is a difference between the treatment
  group and the control group
• Remember, we test the Null hypothesis

4
t-tests

• Use to test the differences between group means
• IV categorical, with only 2 levels
• DV continuous

5
F-tests

• Use to test the differences between group means
• IV categorical, with 3 or more levels
• DV continuous

6
Type I Error

• Reject the Null hypothesis when it is true
• We set the probability that this will occur at
  alpha (our p value)
• Usually set at .05, or a 5 chance

7
Type II Error

• Retain the Null hypothesis when it is false
• Probability of making a type II error (beta) is
  influenced by three factors
• alpha
• Sample size
• Effect size

8

• Decision H0 True H0 False
• Reject H0 Type I Error Correct
  Decision
  p ? p 1 - ?
  Power
• Fail to Correct Decision Type II
  Error
• Reject H0 p 1 - ? p ?

9
Generalizing Results

• College students
• Volunteers
• Gender considerations
• Locale
• Test using a statistical interaction

10
Generalizability Issues

• Pre-testing
• Mundane Experimental realism
• Replication
• Exact
• Conceptual