Hypothesis testing framework
-State the null and alternative hypotheses.
-Calculate the value of the test statistic.
-Identify the reference distribution.
-Find the
P-value
for the observed test statistic
-Check the assumptions.
-State a conclusion.
One-sample
compares 1 mean ? fixed number (?1=?0).
One-sample Z-test
one mean, know ?
One-sample T-test
one mean, unknown ?
One-sample Proportion
one proportion. H0: p = p0
Two-sample
compares mean1 ? mean2 (?1=?2).
Two-sample T-test
Two means.
Confidence interval
We are 95% confident that, the population parameter will occur within the range of values.
Two-sample Proportion
Two proportions.
Paired-sample
compares subject with paired mean1 ? mean2 (?D=0). EX. [before-after] [left-right] [experimental-control]
Paired-sample T-test
Two measurements on each subject.
Chi-square
compares category1 ? category2 (C1-C2 = no association)
Chi-square test
Two categorical variables measured on each subject.
expected value
Linear Regression
R-squared: amount that DV is explained by the IV.
Linear regression test
Two quantitative random variables measured on each subject. SPSS: coefficients (t)-(sig).
ANOVA
compares 3+ independent (group) means. (H0: all ?'s are equal)
One-way ANOVA
3+ means. H0: group means are all equal.
Assumption checking
-What is the assumption?
-Where do you look to check the assumption?
-What do you expect to see if the assumption is valid?
-What do you see?
-What is your conclusion?
Normality-checking
Q-Q plot (close to line)
Linearity-checking
Residual-Predicted
linearity- (random scatter)
constant spread- even (left-right)
Independence
Random allocation etc.
All of Stats-table
Probability Rules
P(not A) = 1 -P(A)
P(A and-or B) = P(A)+P(B)-P(A&B)
P(A&B) indep = P(A)xP(B)
P(A&B) disjoint = 0