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HS 3801 > week 9 > Flashcards

week 9 Flashcards

independent group anova

1
Q

ANOVA tests the difference between

A

more than two groups

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2
Q

what is multiple comparison bias

A

every time you carry out a t-test within the same set of data you increase chance of making type 1 error (inflating alpha)

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3
Q

f-ratio allows us to

A

determine if two variances are equal

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4
Q

if treatment and error are equal f-ratio will be

A

1

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5
Q

as treatment variance gets larger in relation to error variance what happens to f-ratio

A

it exceeds 1 (gets larger)

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6
Q

t/f: the larger the f-ratio, the more statistically significant effect

A

true

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7
Q

the f-ratio is an

A

omnibus test

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8
Q

characteristics of single-factor independent group ANOVA

A
  1. one independent variable
  2. one dependent variable
  3. subjects are randomly assigned
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9
Q

treatment variance is variability due to action of our

A

independent variable

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10
Q

assumptions of independent ANOVA

A
  1. independent random sampling
  2. normality
  3. homogenity of variance
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11
Q

anova is based on the assumption that

A

errors will be normally distributed

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12
Q

when is the grand mean equal to the average of group means

A

when group sizes are equal

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13
Q

what does no variability within groups suggest

A

no measurement error within the study

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14
Q

total df formula

A

N-1 (participants - 1)

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15
Q

treatment effect df formula

A

k-1 (number of groups -1)

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16
Q

error df formula

A

N-K or df total - df treatment

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17
Q

f distribution in an anova is

A

never split

18
Q

eta square (n^2)

A

proportion of variance accounted for

19
Q

how to conduct a pairwise comparison

A

post hoc test

20
Q

tukeys HSD

A

post hoc test that computes multiple t-tests while controlling for the inflation of type 1 error that results from multiple comparissons

21
Q

what do the letters in q(kv) represent

A

k= number of treatment groups
v= error DF
look up on table

22
Q

what does anova allow for

A

Allows us to partition the total variability of our data into “explained variance” and “unexplained variance”

23
Q

what kind of ratio is the test statistic anova

A

f-ratio

24
Q

bonferroni correction

A

It is the idea that the inflation of type 1 error is only a problem if the experiment-wise alpha is larger than our tolerance for error
- adjusts the per-comparison alpha so that the “inflates alpha” is not acceptably high
- if you know how many comparisons your making you can just adjust the per-comparison alpha to a value that when multiplied by your number of calculations is not acceptably high
- this is not something we will use

25
Q

bonferroni leads to a

A

substantial reduction in your power

26
Q

variance partitioning

A

splitting total variance into treatment and error variance

27
Q

anova null hypothesis

A

that all means are equal to eachother

28
Q

what are the characteristics of single anova

A
  1. one independent variable (IV)
    - the IV must have multiple levels
  2. one dependent variable (DV)
  3. subjects are randomly assigned to the levels of the IV or random representations of the levels of the IV
    - a subject can be a member of only one group or level (ie. groups are independent)
29
Q

anova is based on the fact that your errors will be

A

normally distributed

30
Q

homogeniety of variances

A

variances are equal to eachother

31
Q

k =

A

number of groups

32
Q

What is the sum of squares for the error effect equal to

A

The weighted sum of the variances for each treatment group
- weighted by the n-sizes of each treatment group

33
Q

what is included in anova summary table

A
  1. source (column that defines source of variance)
  2. SS (sums of squares, columns that lists the variance numerators)
  3. df (column that lists the variance denominators)
  4. MS (mean squares, the variance estimates, when you divide the SS for a variance component by it’s df you get a mean square)
  5. F
34
Q

three sources of variance

A

treatment, error, total

35
Q

how to calculate ms

A

ss/df

36
Q

how is f ratio in anova calculated

A

MStreatment/MSerror

37
Q

when looking up critical values of F the alpha is never

A

split

38
Q

what effect size estimate is not useful for independent ANOVA

A

cohens d

39
Q

what effects size is useful for anova

A

eta square (proportion of variance in dependent variable predicted by the independent variable

40
Q

what kind of analysis is anova

A

regression analysis

41
Q

anova predicts interval or ratio data using

A

categorical (nominal or ordinal) independent variable

42
Q

when is anova robust to the assumtion of homogeneity of varience

A

when n sizes are equal

HS 3801 (4 decks)

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