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Stats Flashcards

1
Q

Alpha

A

probability of rejecting the null when it is true

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2
Q

ANCOVA

A

statistically removes variablility in DV due to EV

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3
Q

Normal distribution

A

1SD = 68, 2SD = 95, 3SD = 99

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4
Q

Assumptions of Pearson r

A

linear, unrestricted range of scores, homosc (underest)

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5
Q

homoscedasticity

A

equal variablility of Y scores at all values of X

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6
Q

Canonical Correlation

A

cor of 2 linear combos of variables, predicts stat on criteria

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7
Q

Central limit theorem

A

samp dist of mean approach normal as sample size grows

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8
Q

cluster sampling

A

selecting groups from population: schools, hospitals

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9
Q

coefficient of determination

A

r2. Amount of var in Y accounted for by variability in X

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10
Q

correlation coefficient

A

relationship between two variables

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11
Q

counterbalanced design

A

administering different levels of IV in different orders

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12
Q

cross-sequential

A

combines sross-sectional and longitudnal

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13
Q

discriminant function analysis

A

2 or more continuous predictors, one discrete criterion

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14
Q

event sampling

A

rare behaviors or leave a permanent record

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15
Q

Internal validity

A

variability is due to the IV

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16
Q

interval recording

A

divide time into intervals, record if beh. Occurred

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17
Q

kurtosis

A

peakedness of distribution.

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18
Q

leptokurtic

A

tall distribution

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19
Q

platokurtic

A

flat distribution

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20
Q

Least squares criterion

A

stat used to locate reg. Line to reduce error

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21
Q

lisrel

A

verifies a predfined model or theory

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22
Q

Mann-Whitney U

A

non parametric, 2 independent groups

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23
Q

Mean squares between

A

numerator of F ratio, variability due to IV and error, MSB is larger,

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24
Q

Mean squares within

A

the denominator of the F ratio, variability due to error

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25
Q

Mulicollinearity

A

bad state for MV: predictors are highly correlated

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26
Q

Multiple baseline design

A

appying treatment to different behaviors, settings, groups.

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27
Q

Multiple correlation coefficient

A

R. Relat between 3 or more variables

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28
Q

Multiple regression

A

predicts score on continuous criterion

29
Q

ANOVA

A

one IV and one DV, each interval or ratio. Preferable to multiple t tests

30
Q

Path analysis

A

verify a predefined causal model or theory.

31
Q

Scheffe

A

post hoc, least risk of type I, pairwise and complex

32
Q

Tuckey

A

post hoc, least risk of type I, pairwise when equal size groups

33
Q

Fisher LSD

A

post hoc, least risk of type II, pairwise and complex

34
Q

Power

A

probability of rejecting a false null

35
Q

Protocal analysis

A

Have subject think outloud and analyze the record of verbalizations

36
Q

randomized block fact. anova

A

EV is treated as another IV, can analyze main and interaction effects of EV

37
Q

reactivity

A

effect of being aware of being in a study

38
Q

regression analysis

A

Predicts a score on a criterion based on a predictor

39
Q

rejection region

A

sample means that are unlikely to be the result of sampling error, = alpha

40
Q

reversal withdrawal design

41
Q

Solomon Four

A

Pretest is considered an IV

42
Q

effects of adding to raw score

A

+or - changes CT not SD, * or / changes CT and SD

43
Q

Statistical regression

A

scores moving toward mean when retested

44
Q

Latin square

A

each level of the IV appears the same number of times in each position

45
Q

Factorial design

A

two or more Ivs

46
Q

Sampling error

A

how sample differs from population

47
Q

maximize power

A

Increasing alpha, big sample, IV more intense

48
Q

Confidence

A

increases as alpha decreases

49
Q

single sample chi square

A

one variable, many categories

50
Q

multiple sample chi square

A

2 ore more variables, many categories

51
Q

assumption of chi square

A

observations are independent

52
Q

Wilcoxen matched pairs

A

2 correlated groups, alternative to t-test for correlated samples

53
Q

Man whitney U

A

2 independent groups, alternative to t-test for independent samples

54
Q

Kruskal wallace

A

2 + independent groups, alternative to one-way ANOVA

55
Q

Parametric

A

assumption: normal distribution, homoschedasticity

56
Q

t-test for single sample

A

compare sample mean to known mean

57
Q

t-test for correlated samples

A

two correlated groups (a single group is compared to itself)

58
Q

t-test for independent samples

A

two independent groups (experimental and control)

59
Q

One way Anova

A

1 IV , 1 DV, and 2+ independent groups

60
Q

Factorial Anova

A

2 or more IV (2 way = 2 Ivs). If sig, analyze main and interaction

61
Q

Manova

A

1 or more IV and 2 or more DV

62
Q

Pearson r

A

both variables are interval or ratio

63
Q

spearman rank order

A

both variables are rank ordered

64
Q

Phi

A

both variables are true dichotomies

65
Q

Tetrachoric

A

both are artificial dichotomies

66
Q

contingency

A

both are nominal

67
Q

Point biserial

A

one is true dichotomy and one is interval or ratio

68
Q

biserial

A

one is artificial dichotomy and one is interval or ratio

69
Q

Eta

A

assess non-linear relationships; both are interval or ratio

EPPP (7 decks)

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