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Stats > Exam > Flashcards

Exam Flashcards

1
Q

To work out F statistic

A

MS / MSerror

Between groups MS/ Within groups MS

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2
Q

If means are the same is there a significant difference?

A

No

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3
Q

How is something significant?

A

Below .05 or Below .01

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4
Q

How do you work out how many participants?

A

Df of within sample / number of groups

+1

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5
Q

What are priori contrasts used for?

A

Experimenter can make predictions about means

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6
Q

In a between groups two way ANOVA how many error terms are there?

A

1

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7
Q

MS axs

A

Within subjects error term for main effect of variable A

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8
Q

MS a

A

Within subjects main effect of variable A

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9
Q

MS s

A

Within subjects subjects of variable A

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10
Q

Familywise and per comparison equation

A

afw = c (apc)

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11
Q

What is a family wise error?

A

Multiple tests that increase type 1 error

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12
Q

What is per comparison error?

A

Single test that increases type 1 error

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13
Q

What is ANCOVA

A

Statistical control of error variability

When experimental control of error not possible

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14
Q

Ancova assumptions

A

Homoscedasticity- equal scatter
Heterogeneity of regression coefficients
Multicollinearity

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15
Q

ANOVA assumptions

A 
Normal distributions 
Independent 
DV ratio / interval scale 
IV categorical 
Homogeneity of variance
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16
Q

Test reliability is a precursor of

A

Validity

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17
Q

Vectors set to 90 degrees have what rotatation?

A

Orthogonal

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18
Q

Rotations converged in 3 iterations are

A

Orthogonal

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19
Q

Types of Orthogonal roatation

A

Varmiax
Equamax
Quartimax

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20
Q

Types of oblique rotation

A

Direct oblimin

Promax

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21
Q

Which regression has a priori sequence of entry?

A

Hierarchical regression

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22
Q

What is a scree plot?

A

Eigenvalues on Y axis

Factors on X axis

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23
Q

What is a cross loading

A

Any loading greater than .4

And has difference if more than .2

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24
Q

What does KR-20 measure?

A

Internal reliability for measures with dichotomous choices (Yes/No)
Values up to +1.00

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25
Q

What does KR-20 stand for?

A

Kuder- Richardson

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26
Q

What is good internal reliability in regards to KR-20

A

Anything greater than .7

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27
Q

Three kinds of factorial design

A

Completely randomised factorial design ( 1 treatment condition / between groups)
Randomised block factorial design ( all treatments in randomised order within group)
Mixed factorial design

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28
Q

Criteria for different populations

A

At least some of the rules are different

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29
Q

Mean square equation of error

A

MSs/ab = SSs/ab / dfs/ab

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30
Q

What is a?

A

Sig

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31
Q

When is it more important to allow type 1 errors?

A

When important to find new facts

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32
Q

When is it important to allow type 2 errors?

A

When not clogging up literature

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33
Q

What is probability (p)

A

Probability of observed effect

Having assumed null hypothesis true

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34
Q

The normal distribution

A 
Mathematical function 
2 population parameters 
Distribution of scores 
u = mean 
o = SD
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35
Q

Different normal distributions are generated whenever

A

The pop mean or pop SD are different

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36
Q

What is normal distribution used for?

A

In order to make standardised comparisons

Across different populations and treatments

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37
Q

If shared area of normal distribution large

A

Populations similar

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38
Q

If shared area of normal distribution small

A

Populations different

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39
Q

In terms of normal distribution It is mathematically impossible for the shared area to

A

Ever equal zero

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40
Q

What is chi square distribution used for?

A

Testing sample and population variance are same / different

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41
Q

F distribution based on

A

Different distribution

42
Q

If 2 populations are the same then F ratio will be

A

1

43
Q

If two populations are different then F ratio will be

A

More than 1

44
Q

The f ratio will further increase with

A

Further the difference

45
Q

The F ratio depends on knowing the

A

Variances for two samples

Degrees of freedom associated with each sample, based on sample sizes

46
Q

Chi squared and F distribution used for…

A

More statistical approach
( not normal distribution)
Looking at treatment populations

47
Q

Chi squared 2 assumptions

A

Population normally distributed

Measure taken on interval / ratio scale

48
Q

F ratio further 2 assumptions

A

Homogeneity of variances

Independent measures

49
Q

The F equation

A

F = Xsquared a / sa-1

/ Xsquared b / sb- 1

50
Q

Chi squared equation

A

X squared = (s-1) o squared s

/ o squared p

51
Q

The F ratio is the ratio of

A

Two sample based variances

52
Q

F value observed and critical value meaning

A

If Observed F value greater than critical F value then significant

53
Q

The general problems of rejecting null hypothesis

A

Can always attribute some portion of difference to chance factors / error

54
Q

What is the name of uncontrolled sources of variability in experiment

A

Experimental errors

55
Q

Two types of error

A

Individual differences error

Experimental error

56
Q

Experimental error is show by

A

Within group variability

57
Q

Two estimates of experimental error are

A

Independent from eachother

But both reflect same value of experimental error

58
Q

A systematic source of variability comes from the

A

Treatment effect

59
Q

Unsystematic source of variability comes from

A

Experimental error of subjects and measurement

60
Q

When population means are not equal this is the result of the …

A

Treatment effects

61
Q

When population means are equal reflects

A

Experimental error alone

62
Q

Sum of squares equation

A

SStotal = SSwithin + SSbetween

63
Q

Basic ratio of variance

A

Score and sum squared divided by the number of items that contribute to the score and sum

64
Q

For the purpose of ANOVA, variance is defined as

A

variance = SS / df

65
Q

SSt is the

A

Total sum of squares

66
Q

SSa is the

A

Between group sum of squares

67
Q

SSs/a is the

A

Within group sum of squares

68
Q

If null hypothesis true, ratio of between groups and within groups variability equal to

A

1

69
Q

Partitioning the variability means

A

Subdividing total deviation

70
Q

Total deviation equation

A

AS - T

71
Q

Between groups deviation equation

A

A - T

72
Q

Within groups deviation equation

A

AS - A

73
Q

What do the parts of the deviation equation mean?

A 
T = grand mean 
AS = total deviation 
AS = within group 
A = between group
74
Q

Transforming the data reduces the chances of making which error?

A

Type 2 error

75
Q

If ANOVA assumption broken it fails gracefully, eg

A

Miss real effects (Type 2 error)

But does not increase chances of making Type 1 error

76
Q

Transformation of positive and negative skews

Moderate Substantial Severe

A

Moderate - square root
Substantial - logarithm
Severe / reciprocal

77
Q

Designs which include multiple IVs are called

A

Factorial designs

78
Q

For 2 way between groups design

F ratio is calculated for :

A

Main effects if IV 1
Main effect of IV 2
Interaction effect of IV 1 and 2

79
Q

F ratio for main effect A

A

MSa / MSs/ab

80
Q

F ratio for main effect of variable B

A

MSb / MSs/ab

81
Q

F ratio for main interaction

A

MSab / MSs/ab

82
Q

Mean square equation for main effect A

A

MSa =

SSa / dfa

83
Q

Mean square equation for main effect B

A

MSb = SSb / dfb

84
Q

Within groups

F ratio for main effect

A

Fa = MSa / MSaxs

85
Q

Within subjects

F ratio for subject variables

A

Fs MSs / MSaxs

86
Q

A significant main effect of subject variable is a problem when

A

Specific predictions are made about performance

When there is a hidden altitude treatment interaction

87
Q

Within subjects additional assumptions

A

Sphericity
Homogeneity of treatment different variances
Compound symmetry

88
Q

No need to test for sphericity of IV if it only has

A

2 levels

89
Q

What do we want from Mauchleys test of sphericity

A

For value to be non significant

Homogeneity of variance

90
Q

With mixed designs, what is there no such thing of?

A

One factor mixed design

91
Q

What test for homogeneity of variance is used for split plot?

A

Box’s M

92
Q

What test is used to test for normality?

A

Box’s M

93
Q

How do we control in experimentation

A

Randomisation

94
Q

Mean square equation for interaction

A

MSAB = SSAB / DFAB

95
Q

Each sum of squares is calculated by combining two quantities called

A

Basic ratios

96
Q

Degrees of freedom are the

A

Number of observations that are free to vary

When we already know something about those observations

97
Q

Actual variance estimates are called

A

Mean squares

98
Q

If means are the same there is no

A

Significant difference

99
Q

If only 2 levels of a factor then

A

No analytical comparisons are required

T- tests can be performed instead

100
Q

Definition of interaction effect

A

Means of the IVs differ with respect to the levels of the other IV

Stats (19 decks)

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