Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

YEAR 2 Stats > Independent one-way ANOVA > Flashcards

Independent one-way ANOVA Flashcards

1
Q

Used when we have 1 IV with more than 2 levels

A

One-way ANOVA

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Used when we have 1 IV with more than 2 levels, between subjects

A

One-way independent ANOVA

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Used when we have 1 IV with more than 2 levels, within subjects

A

One-way repeated measures ANOVA

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What does one-way ANOVA estimate?

A

Estimates whether the population means under the different levels of the IV are different

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Estimates whether the population means under the different levels of the IV are different

This is known as…?

A

One-way ANOVA

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

One-way ANOVA estimates whether the population means under the different levels of the IV are different

What are the estimates based on?

A

The difference between the
measured sample means

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Why use ANOVA and not stick to t-tests for studies with more than 2 IVs?

List 3 points

A
  1. With each IV levels, we’d have to run different t-tests

e.g. With 3 IV levels, we’d have to run 3 t-tests

  1. For each of these t-tests there would be a 5% chance of making a Type 1 error
  2. But the overall Type 1 error rate (across all t-tests) would be higher
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Explain the sock drawer analogy in 3 points

A
  1. Sock drawer contents:
    - 19 pairs of black socks
    - 1 pair white socks
  2. If you randomly pick out one pair:
    - 1 in 20 chance of picking out the white socks (5%)
  3. If you repeatedly go back and randomly pick out socks (returning those previously picked to the drawer)
    - Chance of eventually picking out the white socks increases (>5%)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

The probability that at least one of a ‘family’ of comparisons, run on the same data, will result in a
Type I error

This is known as…?

A

Familywise Error Rate

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Describe Familywise Error Rate

A

The probability that at least one of a ‘family’ of comparisons, run on the same data, will result in a Type I error

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

The probability that at least one of a ‘family’ of comparisons, run on the same data, will result in a…?

a. Type I error
b. Type II error

A

a. Type I error

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What is the formula for familywise error rate?

A

a’ = 1 - (1 - a)^c

or

Error rate for family of comparisons = 1 - (1 - Level of confidence we’re working to for each comparison (.95 if α=.05)^Number of comparisons

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

This study had 3 IV levels (A, B & C)

a. What is the familywise error rate?

b. What is the chance of Type I error?

A

A - B
A - C
B - C
= 3 comparisons

a.
a = 1 - (1 - 0.05)^3
a = .143

b. 14%

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

This study had 5 IV levels (A, B, C, D & E)

a. What is the familywise error rate?

b. What is the chance of Type I error?

A

A - B
A - C
A - D
A - E
B - C
B - D
B - E
C - D
C - E
D -E
= 10 comparisons

a.
a = 1 - (1 - 0.05)^10
a = .401

b. 40%

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

How many d.p. do we report Familywise error rate in?

A

3 d.p.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Do we include a 0 in front of the decimal point when reporting familywise error rate?

A

No

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

What tests control for the familywise error rate?

A

Omnibus tests (e.g. ANOVA)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Omnibus tests (e.g. ANOVA) control for…?

A

Familywise error rate

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

What is the formula for the F ratio in one-way ANOVA?

A

F = variance between IV levels / variance within IV levels

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Is the variance between IV
levels relative to within IV levels small or large when the F value is close to 0?

A

Small

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Is the variance between IV
levels relative to within IV levels small or large when the F value is further from 0?

A

Large

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

The variance between IV
levels relative to within IV levels is small when the F value is…?

a. Far from 0
b. Close to 0

A

b. Close to 0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

The variance between IV
levels relative to within IV levels is large when the F value is…?

a. Far from 0
b. Close to 0

A

a. Far from 0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

What contributes to variance between IV levels in independent designs?

List 3 things

A
  1. Manipulation of IV (treatment effects)
  2. Individual differences
  3. Experimental error (Random error, Constant error)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

What contributes to variance within IV levels in independent designs?

List 2 things

A
  1. Individual differences
  2. Experimental error (Random error)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

Variance between IV levels includes…?

A
  1. The variance caused by the manipulation of the IV
  2. Error variance
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

Variance within IV levels includes…?

A
  1. Only error variance
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

Total variance is the sum of…?

A

Variance between IV levels
(incl. variance explained by our model and error variance, aka ‘model’ variance) and Variance within IV levels (only error variance, aka ‘residual’ variance)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

Residual variance is known as…?

A

Variance within IV levels

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

Model variance is known as…?

A

Variance between IV levels

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
31
Q

Variance between IV levels is also known as…?

A

Model variance

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
32
Q

Variance within IV levels is also known as…?

A

Residual variance

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
33
Q

How do we partition the variance?

List 4 points

A
  1. Calculates the means for each IV level
  2. Calculates the grand mean
  • Sum of IV level means, divided by the number of IV levels
  1. Calculates the within IV levels variance
  • Sum of squared differences between individual values and the corresponding IV level mean
  1. Calculates the between IV levels variance
  • Sum of squared differences between each IV level
    mean and the grand mean
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
34
Q

An investigator wants to determine whether participants recall more items in a verbal short term memory task if they have been instructed to use a mnemonic strategy.

He recruits 60 participants and randomly assigns them to one of 3 groups: no mnemonic, mnemonic 1 or mnemonic 2. He records how many items they can recall for a list of 20 words

What are the:

a. IVs
b. IV levels
c. DV
d. Subjects design
e. Type of test

A

a. Mnemonic strategy
b. 3 (No mnemonic, mnemonic 1, mnemonic 2)
c. Items/words recalled
d. Between subjects
e. One-way independent ANOVA

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
35
Q

What are the 4 assumptions for independent one-way ANOVA?

A
  1. Normality
  2. Homogeneity of variance
  3. Equivalent sample size
  4. Independence of observations
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
36
Q

What is the normality assumption for independent one-way ANOVA?

A

The DV should be normally distributed, under each level of the IV

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
37
Q

What is the homogeneity of variance assumption for independent one-way ANOVA?

A

The variance in the DV, under
each level of the IV, should be (reasonably) equivalent

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
38
Q

How do we check homogeneity of variance on SPSS?

A

Levene’s test

If p < 0.05, we reject the null, data is not homogenous

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
39
Q

What can correct for homogeneity of variance for independent one-way ANOVA?

A

Welch F statistic

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
40
Q

Welch F statistic can correct for…?

A

Homogeneity of variance

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
41
Q

Levene’s test checks for…?

A

Homogeneity of variance

42
Q

What is the equivalent sample size assumption for independent one-way ANOVA?

A

Sample size under each level of the IV should be roughly equal

43
Q

What is the independence of observations assumption for independent one-way ANOVA?

A

Scores under each level
of the IV should be independent

44
Q

What is the non parametric equivalent for the independent one-way ANOVA?

A

Kruskal WallisTest

45
Q

Kruskal WallisTest is a non parametric equivalent for…?

A

Independent one-way ANOVA

46
Q

What is the H0 for Levene’s hypothesis?

A

There is no difference between the variance under each level of the IV (i.e. homogeneity)

47
Q

If p < .05 on the Levene’s test, we reject null hypothesis which means…?

A

The data is heterogenous

48
Q

Where do we find Levene’s statistic on SPSS?

A

The ‘Based on Mean’ row on the ‘Test of Homogeneity of Variances’ table

49
Q

How do you present the SPSS output of independent one-way ANOVA?

A

F(dfm,dfr) = F-value, p = p-value

or

F(Between Groups Sum of Squares, Within Groups Sum of Squares) = F, Sig.

50
Q

Where the assumption of homogeneity of variance has been violated (i.e. a significant Levene’s result), we should report the result of …?

A

Welch’s F test

51
Q

How do we report the results on SPSS of Welch’s F test?

A

F(df1,df2) = Statistic, Sig.

52
Q

Sum of squared differences between IV level means and grand mean (i.e. between IV level variance)

This is known as…?

A

Model Sum of Squares (SSM)

53
Q

What is Model Sum of Squares (SSM)?

A

Sum of squared differences between IV level means and grand mean (i.e. between IV level variance)

54
Q

Sum of squared differences between individual values and corresponding IV level mean (i.e. within IV level
variance)

This is known as…?

A

Residual Sum of Squares (SSR)

55
Q

What is Residual Sum of Squares (SSR)?

A

Sum of squared differences between individual values and corresponding IV level mean (i.e. within IV level
variance)

56
Q

What is the formula for Mean Square Between Groups (MSM)?

A

Sum of Squares Between Groups (SSM) / df Between Groups (dfM)

57
Q

What is the formula for Mean Square Within Groups (MSR)?

A

Sum of Squares Within Groups (SSR) / df Within Groups (dfR)

58
Q

What is the F value formula on SPSS?

A

F = Mean Square Between Groups (MSM) / Mean Square Within Groups (MSR)

59
Q

How many df values does independent one-way ANOVA have?

A

2

  • df model (between IV levels)
  • df residual (within IV levels
60
Q

How do you calculate the df model (between IV levels) for independent one-way ANOVA?

A

df model = k (number of IV levels) - 1

61
Q

How do you calculate the df residual (within IV levels) for independent one-way ANOVA?

A

df residual = N (sample size) - k (number of IV levels)

62
Q

Between IV level variance is known as…?

A

Model variance

63
Q

Within IV level variance is known as…?

A

Error/Residual variance

64
Q

N (sample size) - k (number of IV levels)

This is the formula to calculate the df for…?

A

Within IV levels or df residual

65
Q

This is the formula to calculate the df for…?

k (number of IV levels) - 1

A

Between IV levels or df model

66
Q

What are Post-hoc tests?

A

Secondary analyses used to assess which IV level mean
pairs differ

67
Q

Secondary analyses used to assess which IV level mean
pairs differ

This is known as…?

A

Post-hoc tests

68
Q

When are Post-hoc tests used?

A

When F-value is significant

69
Q

Post-hoc tests are run as t-test but include…?

A

Correction for multiple
comparisons

70
Q

What are the 3 types of Post-hoc tests?

A
  1. Bonferroni
  2. Least Significant Difference (LSD)
  3. Tukey Honestly Significant Difference (HSD)
71
Q

What is the Type I Error risk for Bonferroni?

a. Very high
b. High
c. Low
d. Very low

A

d. Very low

72
Q

What is the Type I Error risk for Least Significant Difference (LSD)?

a. Very high
b. High
c. Low
d. Very low

A

b. High

73
Q

What is the Type I Error risk for Tukey Honestly Significant Difference (HSD)?

a. Very high
b. High
c. Low
d. Very low

A

c. Low

74
Q

What is the Type II Error risk for Bonferroni?

a. Very high
b. High
c. Low
d. Very low

A

a. Very high

75
Q

What is the Type II Error risk for Least Significant Difference (LSD)?

a. Very high
b. High
c. Low
d. Very low

A

c. Low

76
Q

What is the Type II Error risk for Tukey Honestly
Significant Difference (HSD)?

a. Very high
b. High
c. Low
d. Very low

A

b. High

77
Q

What is the classification for Bonferroni?

A

“very conservative”

78
Q

What is the classification for Least Significant Difference (LSD)?

A

“liberal”

79
Q

What is the classification for Tukey Honestly Significant Difference (HSD)?

A

“reasonably
conservative”

80
Q

This post-hoc test is classified as “reasonably
conservative”

a. Bonferroni

b. Least Significant Difference (LSD)

c. Tukey Honestly Significant Difference (HSD)

A

c. Tukey Honestly Significant Difference (HSD)

81
Q

This post-hoc test is classified as “liberal”

a. Bonferroni

b. Least Significant Difference (LSD)

c. Tukey Honestly Significant Difference (HSD)

A

b. Least Significant Difference (LSD)

82
Q

This post-hoc test is classified as “very conservative”

a. Bonferroni

b. Least Significant Difference (LSD)

c. Tukey Honestly Significant Difference (HSD)

A

a. Bonferroni

83
Q

This post-hoc test has a very low Type I Error risk

a. Bonferroni

b. Least Significant Difference (LSD)

c. Tukey Honestly Significant Difference (HSD)

A

a. Bonferroni

84
Q

This post-hoc test has a high Type I Error risk

a. Bonferroni

b. Least Significant Difference (LSD)

c. Tukey Honestly Significant Difference (HSD)

A

b. Least Significant Difference (LSD)

85
Q

This post-hoc test has a low Type I Error risk

a. Bonferroni

b. Least Significant Difference (LSD)

c. Tukey Honestly Significant Difference (HSD)

A

c. Tukey Honestly Significant Difference (HSD)

86
Q

This post-hoc test has a low Type II Error risk

a. Bonferroni

b. Least Significant Difference (LSD)

c. Tukey Honestly Significant Difference (HSD)

A

b. Least Significant Difference (LSD)

87
Q

This post-hoc test has a high Type II Error risk

a. Bonferroni

b. Least Significant Difference (LSD)

c. Tukey Honestly Significant Difference (HSD)

A

c. Tukey Honestly Significant Difference (HSD)

88
Q

This post-hoc test has a very high Type II Error risk

a. Bonferroni

b. Least Significant Difference (LSD)

c. Tukey Honestly Significant Difference (HSD)

A

a. Bonferroni

89
Q

What are the 2 different effect sizes calculated for ANOVA?

A
  1. Partial n2
  2. Cohen’s d
90
Q

How much variance in the DV is explained by the manipulation of the IV overall

What effect size is this?

A

Partial n2

91
Q

The magnitude of the difference between pairs of IV level means, expressed in SD units

What effect size is this?

A

Cohen’s d

92
Q

What does partial n2 tell us?

A

How much variance in the DV is explained by the manipulation of the IV overall

93
Q

What does Cohen’s d tell us?

A

The magnitude of the difference between pairs of IV level means, expressed in SD units

94
Q

What is considered a small effect size of partial n2?

A

> .01

95
Q

What is considered a medium effect size of partial n2?

A

> .06

96
Q

What is considered a large effect size of partial n2?

A

> .14

97
Q

What proportion of the variance in the DV is accounted for by the manipulation of the IV?

This is known as…?

A

Partial eta^2

98
Q

What does partial eta^2 tell us?

A

What proportion of the variance in the DV is accounted for by the manipulation of the IV?

99
Q

What is the formula for partial eta^2?

A

Partial eta^2 = SSM / (SSM + SSR)

or

Partial eta^2 = Sum of Squares Between Groups / (Sum of Squares Between Groups + Sum of Squares Within Groups)

100
Q

How many d.p. do you report partial n^2 or partial eta^2?

A

3 d.p.

101
Q

Do you put a 0 in front of the decimal point when reporting partial n^2 or partial eta^2?

A

No

102
Q

Calculate the Cohen’s d for each pair of the IV level means

Data:

No Mnemonic
Mean = 8.40
SD = 1.82

Mnemonic 1
Mean = 9.85
SD = 1.53

Mnemonic 2
Mean = 10.40
SD = 1.76

A

NM & M1
d = 8.40 - 9.85 / (1.82 + 1.53 / 2)

d = (-) 0.87 (large effect size)

NM & M2
d = 8.40 - 10.40 / (1.82 + 1.76 / 2)

d = (-) 1.12 (large effect size)

M1 & M2
d = 9.85 - 10.40 / (1.53 + 1.76 / 2)

d = (-) 0.33 (small effect size)

YEAR 2 Stats (10 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions