CI - difference b/t groups

T tests =

comparing the means of two groups

independent T test

between subjects

Reject or fail to reject null hypothesis based on

alpha level

Z

T-test for b-endorphins in blood pre and post T, Which type of T test is this?

dependent

Males vs females in this class and yearly amount of money spent on movie tickets. Which type of T test is this?

independent

One-tailed test =

– Directional hypothesis test – If a true difference exists, one group mean is expected to be higher/lower

Two-tailed test

– Nondirectional hypothesis – If a true difference exists, no assurance about which group mean will be higher or lower

ANOVA stands for

ANalysis Of Variance

Factor =

what is being compared (weight loss)

Levels =

different elements of a factor (different diets)

F-Statistic

a ratio that compares the variance between group means to the variance within the groups, used in ANOVA to determine if there are significant differences between groups.

Post hoc testing

if we find a difference

Simple (One-Way) ANOVA involves

1 independent variable / more than 2 levels

Post-hoc Analysis protects

xperimentwise error rate (probability that one or more of the significance tests results in a Type I error)

At its simplest ANOVA tests the following hypotheses:

H0 / HA

H0:

The means of all the groups are equal.`

Ha:

Not all the means are equal

One-Way ANOVA =

ANOVA with one IV with 1+ levels and one DV

Factorial ANOVA =

ANOVA with 2+ IV’s and one DV

The number of numbers =

the number of IV’s

The numbers themselves =

the number of levels in each IV

Why use a factorial ANOVA? Why not just use multiple one-way ANOVA’s?

Factorial ANOVA allows researchers to examine the interactions between multiple independent variables (IVs) on a dependent variable (DV) simultaneously, providing a more comprehensive understanding of how these IVs may affect the DV, as opposed to using separate one-way ANOVAs that may overlook interactions.