Hypothesis Testing
Normal Curve & Z-Scores
Significance & Errors
t-Tests
ANOVA, df & Research
100

This represents no difference or effect

Null hypothesis

100

Shape of a normal distribution

Bell-shaped

100

Probability result occurred by chance

p-value

100

Test used for two different groups

Independent samples t-test

100

Test used for three or more groups

One-way ANOVA

200

This predicts a difference exists

Alternative (research) hypothesis

200

Mean, median, and mode relationship in normal distribution

Equal

200

Standard alpha level

.05

200

Test used for same group measured twice

Dependent (paired) samples t-test

200

Test statistic for ANOVA

F-value

300

This hypothesis specifies direction (e.g., higher/lower)

Directional hypothesis

300

Percent of data within ±2 SD

About 95%

300

Decision when p < .05

Reject the null hypothesis

300

Key assumption for independent t-test

Two independent groups

300

Two types of ANOVA degrees of freedom

Between-groups and within-groups

400

This hypothesis does not specify direction

Nondirectional hypothesis

400

Meaning of a positive z-score

Above the mean

400

This type of error rejects a true null hypothesis

Type I error

400

“t” represents this in output

Test statistic

400

Section of a paper that reports statistical findings

Results

500

This is written first in hypothesis testing

Null hypothesis

500

What a z-score indicates

Number of standard deviations from the mean

500

This type of error fails to reject a false null hypothesis

Type II error

500

df formula for independent t-test

n₁ + n₂ − 2

500

Required elements in APA statistical reporting

Test statistic, degrees of freedom, p-value, descriptive statistics