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EBP > Statistics I & II > Flashcards

Statistics I & II Flashcards

1
Q

Parameter

A

describes the whole population

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2
Q

Is a parameter fixed or does it vary? Why?

A

fixed because you know data about everyone in the population

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3
Q

Statistic

A

describes a sample of the population

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4
Q

Is a statistic fixed or does it vary? Why?

A

varies because you can take different samples from the same population

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5
Q

Is a parameter or a statistic more reliable?

A

parameter

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6
Q

What is the issue with using a parameter instead of a statistic?

A

if the population you are testing is large, the testing requires more time and resources

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7
Q

What are descriptive statistics used to describe?

A

central tendency, variability, & shape of data

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8
Q

Central tendency

A

where the middle of the data lies

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9
Q

What is the “king” measurement for central tendency - mean, median or mode? Why?

A

mean because you can do the most stats w/it

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10
Q

What is the mean affected by?

A

Outliers

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11
Q

If your data has outliers, which measurement is used instead of mean?

A

Median

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12
Q

Median

A

the middle most number in a set of scores

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13
Q

Mode

A

the most frequently occurring score(s) in a distribution

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14
Q

Mean (average)

A

the sum of the scores divided by the number of scores

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15
Q

Variability

A

the spread or dispersion of a set of research data or distribution

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16
Q

If you have test scores that are all over the place (10’s, 35’s, and 100’s), yet most scored in the 80’s, would you have a lower or higher variability?

A

higher variability

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17
Q

Range

A

the difference between the highest and lowest scores in a distribution

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18
Q

Percentiles

A

describes a score’s position within a distribution compared to others on a scale of 0-100%

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19
Q

If you are in the 75th percentile, you scored ___________ than ________ of others.

A

75%
higher

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20
Q

Quartiles

A

divide distributions into four equal parts

Q1 = 25th percentile
Q2 = 50th percentile
Q3 = 75th percentile
Q4 = 100th percentile

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21
Q

Interquartile range

A

The difference between the upper and lower quartiles.

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22
Q

Standard deviation

A

represents the spread/dispersion/variability of scores relative to the mean

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23
Q

Coefficient of variation compares what?

A

compares 2 SD’s

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24
Q

What is the “king” measurement for variability?

A

standard deviation

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25
Q

Which type of measurement is used to describe nominal data?

A

mode

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26
Q

Which type of measurement is used to describe ordinal data?

A

median & interquartile range or mode

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27
Q

Which type of measurement is used to describe interval and ratio data?

A

mean & standard deviation or mode & interquartile range

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28
Q

What is a bell curve used to describe?

A

shape

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29
Q

How much data lies between -1SD and 1SD of the mean?

A

68.3

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30
Q

How much data lies between -2SD and 2SD of the mean?

A

95.5%

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31
Q

How much data lies between -3SD and 3SD of the mean?

A

99.7%

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32
Q

In a bell curve with a positive skewed distribution, the mean gets pulled to the ___________ creating a tail to the __________. Why?

A

right, right

the mean is heavily affected by outliers, so it gets pulled further toward the right

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33
Q

In a bell curve with a negative skewed distribution, the mean gets pulled to the __________ creating a tail to the ___________. Why?

A

left, left

the mean is heavily affected by outliers, so it gets pulled further toward the left

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34
Q

When the data is skewed in a bell curve, the __________ is often used to describe the central tendency. Why?

A

median because it is not as impacted by outliers as the mean is

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35
Q

Inferential statistics

A

allow us to estimate unknown population traits from using a sample

When you have collected data from a sample, you can use inferential statistics to understand the larger population from which the sample is taken.

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36
Q

Probability

A

likelihood that an event will occur given all possible outcomes

it is what SHOULD happen, not what WILL happen

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37
Q

What is probability used for?

A

used to determine if observed effects are likely to have occurred by chance

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38
Q

Probability is described as _______ and is in ________ form.

A

“p”, decimal

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39
Q

Simply put, what is sampling error accounting for?

A

our sample will never fully reflect the entire population

40
Q

Will a larger or smaller sample be more representative of the entire population?

A

larger

41
Q

Null hypothesis

A

the observed difference (or effect) occurred by chance

42
Q

Example of a null hypothesis

A

There will be NO STATISTICAL DIFFERENCES in strength between open and closed chain exercises.

43
Q

Statistical tests will always test the ________ hypothesis.

A

null

44
Q

Example of an alternative hypothesis

A

There will be SIGNIFICANT DIFFERENCES in strength between open and closed chain exercises.

45
Q

Alternative hypothesis

A

the observed difference (or effect) could not occur by chance

46
Q

When we run a statistical test, we either ____________ the null hypothesis or do not _________ the null hypothesis.

A

reject

47
Q

Type I error

A

false-positive findings which means that the research found a difference when there isn’t really a difference

48
Q

Type II error

A

false-negative findings which means that research did not find a difference when there is a difference present

49
Q

In a small sample size, which type of error is more likely?

A

type II

50
Q

In a large sample size, which type of error is more likely?

A

type I

51
Q

You decide to get covid tested and your results came back positive. However, it turns out that you don’t actually have covid. What type of error is this?

A

type 1

52
Q

You decide to get covid tested and your results came back negative. However, it turns out that you do have covid. What type of error is this?

A

type II

53
Q

Level of significance (alpha)

A

determines how strict one is with rejecting the null hypothesis

maximal acceptable risk of making a type I error

Probability of a Type 1 error
Rejecting Null hypothesis when its true

54
Q

How would an individual reduce the chance of a type I error occurring?

A

reduce the level of significance (alpha)

55
Q

Beta

A

probability of making a type II error

56
Q

Statistical power (1-beta)

A

probability of finding statistically significant differences

57
Q

What does the statistical power depend on?

A

alpha, sample size, effect size

58
Q

How would an individual reduce the change of a type II error occurring?

A

lower beta or increase statistical power

59
Q

What does the p-value tell you?

A

probability that your results are due to chance when testing between and/or within groups

How likely ur data could have occurred under the null hypothesis.

60
Q

If p = 0.10 this means that

A

there is a 10% probability that your results are due to chance.

61
Q

If p < 0.05 this means that

A

there is less than a 5% probability that your results are due to chance.

62
Q

If p < 0.01 this means that

A

there is less than a 1% probability that your results are due to chance.

63
Q

The lower the p-value, the more confident you are that your results are _______ due to chance.

A

NOT

64
Q

If you have a p-value = 0.10, does this mean that there is a 90% chance that your results are accurate?

A

no -

there is 10% probability that your results are due to chance

BUT you cannot reverse this & assume the opposite is true

65
Q

What is the p-value dependent upon?

A

sample size

66
Q

What are alternative forms of measurement to a p-value?

A

confidence intervals & effect size

67
Q

Confidence Intervals (CI)

A

range of numbers for which you expect the true population to fall

68
Q

If you have a 95% CI = (a, b), what does this mean?

A

you are 95% confident that the true difference between groups is between a and b

69
Q

“Is there a difference?”

A

p-value

70
Q

“How big is the difference?”

A

effect size

71
Q

Larger effect size =

A

larger difference

72
Q

What is the first step when choosing a statistical test?

A

determine the purpose of analysis

what are you trying to do…?
- predict
- relationship
- significance of difference

73
Q

What is the second step when choosing a statistical test?

A

determine scale of dependent variable

is it…?
nominal, ordinal, interval or ratio

74
Q

What are the 3 assumptions of parametric data?

A
  1. normality: data follows normal distribution
  2. equal variances: same spread
  3. typically ratio or interval data & represented as mean
75
Q

What are the 3 assumptions of nonparametric data?

A
  1. no need for normality or equal variance
  2. ordinal or nominal data
  3. typically presented as median
76
Q

When you see the word predict, which test should we automatically think of?

A

regression

77
Q

What is R^2?

A

measure of how strong the prediction is.

total variance of y (dependent) that can be explained by x (independent)

78
Q

What are the 3 predicting factors?

A
  1. likelihood ratios (LR)
  2. relative risk (RR)
  3. odds ratio (OR)
79
Q

Sensitivity test

A

how often a test gives a positive result in people with a condition

  • lots of true positives
  • few false negatives
80
Q

Specificity test

A

how often a test gives a negative result in people without a condition

  • lots of true negatives
  • few false positives
81
Q

If a test has 92% sensitivity and you obtain a negative result, you can confidently rule ______ the condition.

A

out

82
Q

If a test has a 95% specificity and you obtain a positive result, you can confidently rule ______ the condition.

A

in

83
Q

What two clinical questions do likelihood ratios help answer?

A
  1. How sure am I that a person w/a positive test result actually has what I tested him/her for?
  2. How sure am I that a person w/a negative test result actually does not have what I tested him/her for?
84
Q

+ LR =

A

sensitivity / (1-specificity)

85
Q
  • LR =
A

(1-sensitivity)/specificity

86
Q

Relative Risk

A

compares one risk to another

87
Q

Relative risk = 1

A

the risk in the exposed group is the same as the risk in the unexposed group, so

no indication of benefit or harm

88
Q

Relative risk < 1

A

the exposure is associated w/a protective effect

89
Q

Relative risk > 1

A

exposed group has a greater risk of contracting the disease, so

exposure is associated w/harm

90
Q

If you have a RR of 0.5, what does this mean?

A

you are at a 50% lower risk than the average

91
Q

If you have a RR of 1.5, what does this mean?

A

you have a 50% higher risk than the average

92
Q

In order to put RR into context, what do you need to know?

A

the baseline risk for the disease

93
Q

Odds Ratio

A

compares whether the odds of a certain event happening is the same for two groups

94
Q

OR = 1

A

the event is equally likely in both groups

95
Q

OR > 1

A

event is less likely in the first group

96
Q

OR < 1

A

event is less likely in the first group

97
Q

What is the measure of choice in a case-control study?

A

odds ratio

EBP (12 decks)

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