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fall B 2024 > research stats midterm > Flashcards

research stats midterm Flashcards

1
Q

what is biostatistics?

A

the statistics of medicine, health sciences and public health

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2
Q

define target population

A

larger population to which results will need to be generalized

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3
Q

define accessible population

A

actual population of subjects available

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4
Q

define sample

A

subgroup of accessible population which allows results to be generalized

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5
Q

define parameter

A

statistical characteristic of population

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6
Q

define statistic

A

statistical characteristic of sample

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7
Q

define descriptive statistic

A

describes sample shape, central tendency, variability

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8
Q

define inferential satistic

A

used to make inferences about a population

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9
Q

define central tendency

A

the central value
best representative value of target population
single value

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10
Q

define variability

A

spread of the data

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11
Q

define frequency distribution

A

the pattern of frequencies of a variable

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12
Q

3 measures of central tendency

A

mean - average
median - two equal halves
mode - most frequent score

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13
Q

describe skewed to the right

A

tail faces right
positive skew
mean > median/mode

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14
Q

describe skewed to the left

A

tail faces left
negative skew
mean < median/mode

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15
Q

when is mean best to use?

A

numeric, symmetric data

not good for skewed

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16
Q

when is median best to use?

A

skewed data
not effected by extremes

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17
Q

when is mode best to use?

A

nominal or ordinal
common in surveys

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18
Q

advantages to mean

A

easy to calculate and interpret
dont need to arrange values
all values represented
all algebraic formulas possible

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19
Q

disadvantages to mean

A

cant be used with categorical data
cant calculate if data missing
affected by extremes

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20
Q

advantages to median

A

easy to calculate
not affected by extremes
can be used with ranked data

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21
Q

disadvantages to median

A

tedious in large data set
problematic with even number of observations
doesnt account for all values

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22
Q

advantages of mode

A

easy to understand and fine
not affected by extremes
easy to ID in data set and in frequency distribution
mode is useful for categorical data

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23
Q

disadvantages of mode

A

not defined if no repeats
not based on all values
unstable when data has small number of values
sometimes could have 2+ or no modes

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24
Q

when would you choose median over mode?

A

distribution is skewed
researcher is using ordinal data

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25
Q

define range, percentiles, quartiles

A

R - max-min
P - divides into 100 parts
Q - four parts

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26
Q

define interquartile range

A

difference between 25th and 75th percentile
used with median

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27
Q

describe box plot

A

min
1st quartile
median
3rd quartile
max

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28
Q

define standard deviation

A

reported same units as raw scores
mean +/- SD

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29
Q

define variance

A

square of SD

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30
Q

coefficient of variation

A

used for interval and ratio data only
expressed as percentage
unitless so good for comparing scales

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31
Q

constant and predictable characteristics

A

68% +/- 1SD
95% +/- 2 SD
99% +/- 3 SD

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32
Q

define a z-score

A

standardized score based on normal distribution
z = SD units

z = score - mean / SD

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33
Q

define sampling error

A

sample mean will not equal the population mean. the difference is called sampling error
how well does the sample represent the population?

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34
Q

z scores for CI calculations

A

90% = z 1.65
95% = z 1.96
99% = z 2.58

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35
Q

central limit theorem

A

will approach mean is N increases

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36
Q

define point estimate

A

single value the is best estimate

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37
Q

define confidence interval

A

range of values that we are confident contains parameter

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38
Q

how would you increase precision (narrow) in CI?

A

larger sample size
less variance (lower SD)
lower selected level of confidence to 90%

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39
Q

CI equation

A

CI = mean +/- (z) SEM

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40
Q

define null hypothesis

A

no difference or relationship

will with reject or fail to reject

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41
Q

define alternative hypothesis

A

is a difference or relationship

42
Q

error: liar or blind

A

type 1: liar, p value
type 2: blind

43
Q

if p value is less than or equal to alpha,

A

reject the null

44
Q

if p value is greater than alpha,

A

fail to reject the null

45
Q

what happens if we fail to reject the null?

A

attribute any observed difference to sampling error only

46
Q

what p value and CI are analogous to each other?

A

95% CI
.05 p value

47
Q

significance of type 1 error

A

mistakenly finding difference
p value tells probability

48
Q

significance of type 2 error

A

mistakenly finding no difference
statistical power = 1-B
power is probability of rejection

49
Q

critical values for two tailed test

A

2.5% of critical region on each side of non critical
nondirectional hypothesis

50
Q

critical values of one tailed test

A

all 5% of critical region on the side hypothesis supports
directional hypothesis

51
Q

which (one or two tailed) is more powerful

A

on tailed

52
Q

define statsical power

A

probability of finding a statistically significant difference if such difference exists in the real world

53
Q

what are the four powers of power?

A

alpha
effect size
variance
sample size

54
Q

best way to increase power

A

increase sample size

55
Q

determinants of statistical power

A

p = power
a = alpha level
n = sample size
e = effect size

56
Q

what is A priori

A

before data collection

57
Q

what is Post hoc

A

after data collection
only an issue of you fail to reject null

58
Q

CI analysis

A

if upper boundary excludes important benefit of treatment, trial is definitively negative

if CI includes important benefit, treatment might still be worthwhile

59
Q

define parametric statistics

A

assumes that sample data comes from population that follows a probability distribution based on a fixed set of parameters

60
Q

what are the 4 assumptions of parametric tests?

A

scale data - ratio or interval
random sampling
equal variance - roughly equivalent before starting
normality - normal distribution

61
Q

what does a t-test do?

A

determines if the difference in sample represent a real difference in the population or is if just sampling error

62
Q

what are examples of two levels of one independent variable?

A

two different groups
one single group with two interventions
one single group with pre and posttest measurements

63
Q

conceptual bias of comparing means

A

sample means will be different
variance comes from two sources
~the IV and everything else

64
Q

conceptual bias with independent groups

A

t= difference between means / variability within groups

65
Q

conceptual bias with repeated measures

A

t = mean of differences between pairs / SD error of the difference scores

66
Q

what if t > 1?

A

you have a greater difference between groups

67
Q

what if t< 1?

A

you have more variability within groups

68
Q

what is the most simple t test equation?

A

t = treatment effect + error / error

69
Q

what are degrees of freedom?

A

the number of independent pieces of information that went into calculating the estimate

number of values that are free to vary

70
Q

independent (unpaired t-test)

A

numerator is difference between group means
denominator represents the variance within groups

71
Q

assumptions for unpaired t-tests

A

data from interval or ratio
samples are randomly drawn from populations
homogeneity of variance - equal variances
population is normally distributed

72
Q

are unequal variances an issue?

A

not a major issue when sample sizes are equal

73
Q

effect size for t-test

A

use cohen’s d

small d = 0.20
medium d = 0.50
large d = 0.80
extra large d = 1.0 or 1.1

74
Q

paire t-test

A

numerator is mean of paired difference scores
denominator is standard error of difference scores

75
Q

3 assumptions for paired t-test

A

data from ratio or interval
samples are randomly drawn from populations
population is normally distributed

76
Q

what is an inappropriate use of multiple t-tests

A

to compare more than 2 means within the same sample
“family wise error”
increase chance of type I error

77
Q

which t test is used for independent groups with one IV

A

independent

78
Q

which t test is used for repeated measures with one IV

A

paired

79
Q

levene’s test

A

for equal variances for independent groups
tests the null: no dig difference in variance between

80
Q

what statistic does the ANOVA use?

A

the F statistic

81
Q

(ANOVA) if variance between samples is small,

A

F will be small

82
Q

(ANOVA) if variance within samples is small,

A

F will be large

83
Q

what is an ANOVA for?

A

compare 3+ groups

84
Q

one way ANOVA

A

one IV with 3+ levels

85
Q

one way repeated measures ANOVA

A

one IV with 3+ levels

86
Q

comparison of group means in ANOVA

A

looks at distance of each group from the grand mean

87
Q

what is the F test called?

A

omnibus test
will tell that a difference exists, but not where

88
Q

what tells where a difference exists?

A

multiple comparison tests

89
Q

ANOVA effect size small

A

eta squared: .01
cohen’s f: .10

90
Q

ANOVA effect size medium

A

eta squared: .06
cohen’s f: .25

91
Q

ANOVA effect size large

A

eta squared: .14
cohen’s f: .40

92
Q

increased power in RM ANOVA

A

less variance

93
Q

define sphericity

A

homogeneity of variance of differences
test with mauchly’s test

94
Q

what is another name for multiple comparison tests?

A

pairwise comparisons

95
Q

describe post hoc MCT

A

performed after ANOVA
most common
test every difference

96
Q

describe planned comparisons MCT

A

instead of ANOVA
focused on specific comparisons

97
Q

what is the goal of MCT

A

decrease family wise error rate

98
Q

what is a solution of of family wise error?

A

bonferroni correction
divide alpha by the number of statistical tests

99
Q

describe fisher’s least significant difference

A

essentially unadjusted t-tests (LSD)
least conservative
most power

100
Q

describe tukey’s honestly significant difference

A

IG only
middle of the road in terms of risk
most common
best balance of type I and II error

101
Q

describe bonferroni t-test

A

divides alpha by # of comparisons
most conservative
high type II error

102
Q

describe sidak

A

RM
adjusted alpha
good balance of type I and II error
most common

fall B 2024 (19 decks)

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