Introduction to Analysis Variance Flashcards
It is a hypothesis-testing procedure that is used to evaluate mean differences between two or more treatments or populations.
Analysis of Variance (ANOVA)
The variable that designates the groups being compared.
Factor
The individual conditions that make up a factor.
Levels of the Factor
A study with two combine factors.
Two-factor design/Factorial Design
It is the risk of a Type I error, or alpha level, for an individual hypothesis test.
Testwise Alpha Level
It is the total probability of a Type I error that is accumulated from all of the individual tests in the experiment.
Experimentwise Alpha Level
It simply measures how much difference exists between the treatment conditions.
Between-treatments Variance
It provides a measure of how big the differences are when the null hypothesis is true.
Within-treatments Variance
The denominator of the F-ratio that provides a measure of the variance caused by random, unsystematic differences.
Error Term
Symbol for the number of levels of the factor.
k
Symbol the number of score in each treatment.
n
Symbol of the total number of scores in the entire study.
N
Symbol for the sum of all scores in the research study.
G
It is used to organize the results of the analysis in one table.
ANOVA SUmmary Table
It is accounted for by the treatment effect that is usually called in the Greek letter as eta squared.
Percentage of Variance
An alternative statistical analysis that is used if one assumptions for the independent-measures of ANOVA is suspected to be violated and it is designed specifically for ordinal data.
Kruskal-Wallis Test
These are additional hypothesis tests that are done after an ANOVA to determine exactly which mean difference are significant and which are not.
Post Hoc Test/Posttests
It is the commonly used test in psychological research that allows you to compute a single value that determines the minimum difference between treatment where it means that is necessary for significance.
Tukey’s Honestly Significant Difference (HSD) Test
The value that is then used to compare any two treatment conditions.
Honestly Significant Difference (HSD)
It has distinction of being one of the safest of all possible post hoc tests which is the smallest risk of Type I error.
Scheffe Test
