Chapter 11- ANOVA

The type of ANOVA used to analyze data depends on:

1) the number of factors being tested. 2) how the participants are observed across each level of a factor

Eta-squared

Compute percentage of variance accounted for by the treatment conditions

______ is used to measure the percentage of variance accounted for by the treatment effect for ANOVA.

Eta squared

_______ are additional hypothesis tests that are done after ANOVA to determine exactly which mean differences are significant and which are not.

Post hoc tests

One-way between-subjects ANOVA

Research design in which we select independent samples, meaning that different participants are observed at each level of a factor

When an experiment contains more than two treatment conditions and the decision from the ANOVA is to reject the null hypothesis, it is necessary to continue the analysis with a post hoc test. True or False

True

There are four assumptions to compute the one-way between-subjects ANOVA:

1) Normality: assume that data in the population or populations being sampled from are normally distributed 2) Random Sampling: assume data measured were obtained from a sample that was selected using a random sampling procedure 3) Independence: assume that the probabilities of each measured outcome in a study are independent or equal 4) Homogeneity of Variance: assume that the variance in each population is equal to each other

Analysis of Variance (ANOVA)

Analysis of variance (or F test) is a hypothesis testing procedure used to evaluate the differences between more than 2 conditions.

Source of variation

Any variation that can be measured in a study. In the one-way between-subjects ANOVA, there are two sources of variation. Between groups variation- variance of group means. Within groups (error) variation-variation attributed to error.

As more and more separate tests are conducted, the risk of Type I error accumulates, which is known as the ______.

Experiment wise alpha level

_____ is an assumption for the one-way between-subjects ANOVA that states the populations from which the samples are selected must have equal variances.

Homogeneity of variance

One-way between-subjects ANOVA is the most basic type of ANOVA

In this type of ANOVA, different participants are observed at each level of one factor

Power of ANOVA

Power of ANOVA is affected by the same variables as the t analysis. Power varies with N; as N increases power increases. Power varies directly with the size of the real effect of the independent variable; the greater the real effect the greater the power of the analysis. Power varies inversely with sample variability. The larger the sample variability is, the lower the power is.

One-way within-subjects ANOVA

Research design in which the same participants are in each condition, meaning that the same participants are observed at each level of a factor. a statistical procedure used to test hypotheses for one factor with two or more levels concerning the variance among group means. This test is used when the same participants are observed at each level of a factor and the variance in any one population is unknown