LECTURE 5 one way anova Flashcards

1
Q

why use anova

A

test whether all group means are equal when there is more than two levels to your independent variable or more than one independent variable

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2
Q

why cant you use t tests to look at one factor with three levels

A

inflates change of getting a type 1 error (say sig but not)
anova allows change of 5% to remain at a 5% level -
in t test prob of type 1 error is 1-0.95xno.levels

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3
Q

what is an omnibus test

A

tests for an effect across all means but doesnt say where the difference lies

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4
Q

how does an anova work

A

takes the F ratio of variance of participants performance that is due to the systematic differences caused by the IV compared to variance due to chance

f= variance by systematic exp manipulation / variance expected by chance

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5
Q

what are the sources of variability

A

systematic differences/experimental effects
individual differences
experimental error

sources are additive to make up the total variance

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6
Q

define systematic difference variability

A

difference conditions cause differences between samples

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7
Q

define individual difference variability

A

differences in level of ability between the participants cause the difference in the samples

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8
Q

define experimental error variability

A

unpredicatble changes due to extraneous variables ie the device used to measure the data

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9
Q

sources of variability in between group (independent measure)

A

systematic differences
individual differences
experimental error

effect of the experiment SSm

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10
Q

sources of variability in within group (independent measure)

A

individual differences and experimental error
(NOT SYSTEMATIC DIFFERENCES AS NOT COMPARING AGAINST DIFF CONDITION BUT LOOK AT VARIANCE IN SAME CONDITION)
residual error SSr

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11
Q

f ratio in independent measures to account for all sources of variability

A

F RATIO =
sys. diff + indiv diff + exp error (SSM - between group variability)
/ indiv diff + exp error (SSr - within group variability)

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12
Q

how to calculate total sum of square SSt

A

SSm (group means from grand mean) + SSr (individual data from individual group means) - SSt (all data from grand mean)

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13
Q

how to calculate Mean squared error

A
MSm = SSm (group means from grand mean) / dfm
MSr = SSr (within group variability/individual data from individual group means)/ dfr
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14
Q

How to calculate F Ratio

A

F = MSm (SSm/dfm) / MSr (SSr/dfr)

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15
Q

what does homogeniety of variances test

A

that variance in each condition is equal - levene stat

if means not the same (sig diff) then run kruskal wallis

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16
Q

how is df worked out in between groups

A

df = k - 1 where k = no. conditions

17
Q

how is df worked out in within groups

A

df = n - k where n = no. subjects

18
Q

how to report one way anova

A

f (df between, df within) = __, p = __, MSE = ___, n2=___

19
Q

what is effect size

A

measure of magnitude of the observed effect independent of sample size - compare effects across studies ie meta analysis

degree null is believed to be false - indexed by discrepency between null and alt hyp (index own method for working out ie cohens d)

20
Q

what is cohens d effect size

A

diff between means of null and alt hyp / STDV

small 0.2, medium 0.5, large 0.8

21
Q

how can you estimate effect size

A

look at previous research
pilot study
estimate by reference to cohens d

22
Q

what is anova effect size

A
eta squares (n2) 
explained variability / total variability (sum of between and within group variability) 

effect size is the proportion of variance accounted for by between group variability

23
Q

what is power

A

the probability of accepting an effect when there is one ie occurance of type 1 (0.5) or type 2 (0.2) error

24
Q

what effects power

A

alpha
sample size
effect size

25
Q

use of power

A

decide sample size

look at power test has

26
Q

Need for one way between subjects anova

A

1 IV

3+ levels