Introduction to Analysis Variance Flashcards

1
Q

It is a hypothesis-testing procedure that is used to evaluate mean differences between two or more treatments or populations.

A

Analysis of Variance (ANOVA)

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2
Q

The variable that designates the groups being compared.

A

Factor

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3
Q

The individual conditions that make up a factor.

A

Levels of the Factor

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4
Q

A study with two combine factors.

A

Two-factor design/Factorial Design

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5
Q

It is the risk of a Type I error, or alpha level, for an individual hypothesis test.

A

Testwise Alpha Level

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6
Q

It is the total probability of a Type I error that is accumulated from all of the individual tests in the experiment.

A

Experimentwise Alpha Level

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7
Q

It simply measures how much difference exists between the treatment conditions.

A

Between-treatments Variance

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8
Q

It provides a measure of how big the differences are when the null hypothesis is true.

A

Within-treatments Variance

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9
Q

The denominator of the F-ratio that provides a measure of the variance caused by random, unsystematic differences.

A

Error Term

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10
Q

Symbol for the number of levels of the factor.

A

k

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11
Q

Symbol the number of score in each treatment.

A

n

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12
Q

Symbol of the total number of scores in the entire study.

A

N

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13
Q

Symbol for the sum of all scores in the research study.

A

G

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14
Q

It is used to organize the results of the analysis in one table.

A

ANOVA SUmmary Table

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15
Q

It is accounted for by the treatment effect that is usually called in the Greek letter as eta squared.

A

Percentage of Variance

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16
Q

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.

A

Kruskal-Wallis Test

17
Q

These are additional hypothesis tests that are done after an ANOVA to determine exactly which mean difference are significant and which are not.

A

Post Hoc Test/Posttests

18
Q

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.

A

Tukey’s Honestly Significant Difference (HSD) Test

19
Q

The value that is then used to compare any two treatment conditions.

A

Honestly Significant Difference (HSD)

20
Q

It has distinction of being one of the safest of all possible post hoc tests which is the smallest risk of Type I error.

A

Scheffe Test