Statistics Flashcards

(67 cards)

1
Q

What kind of data uses whole numbers that are mutually exclusive (e.g. infected vs. not infected)

A

Discrete

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2
Q

What kind of data contains information that can be measured on a continuum or scale, have numeric values between the minimum and maximum values and requires a process of measuring rather than counting?

A

Continuous

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3
Q

Simplest or crudest level of measurement. Categories are used to classify observations into mutually exclusive groups or classes

A

Nominal scale

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4
Q

observations are ranked so that each category is distinct and stands in some definite relationship to each of the other categories.

A

Ordinal scale

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5
Q

When data meet all the requirements for ordinal data and the exact distance between any two observations on the scale is known.

A

Interval Scale

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6
Q

sum of values / # of observations

A

mean

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7
Q

the point at which 50% of the values fall below a middle value and 50% of the values occur above the middle value

A

Median

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8
Q

middle value of an odd numbered set of values

A

median

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9
Q

(2 middle values) / 2 in an even numbered set of values

A

median

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10
Q

Observation that occurs most frequently in a set of data

A

mode

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11
Q

1 SD will contain ___% of the measurements

A

68%

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12
Q

2 SD will contain ___% of the measurements

A

95%

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13
Q

3 SD will contain __% of the measurements

A

> 99.7%

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14
Q

Positive Skew means

A

Mean > Median

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15
Q

Normal distribution means

A

mean, median and mode are equal

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16
Q

Negative skew means

A

Mean < Median

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17
Q

Mesokurtosis

A

Normal bell shape

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18
Q

Leptokurtosis

A

More peaked shape curve

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19
Q

Platykurtosis

A

flatter shaped curve

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20
Q

Basic formula for all rates

A

(X/Y) * K

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21
Q

Indicates the risk of disease in a population over a period of time

A

Incidence

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22
Q

K (constant used to transform equations into uniform quantity)

A

made so the smallest calculated rate is at least 1 number to the left of the decimal

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23
Q

Incidence Rate

A

Equals the number of new cases of a disease for a specified time period

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24
Q

Prevalence Rate

A

Equals the number of existing cases of disease from a specified interval or point in time

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25
The proportion of persons in a population with a particular disease or attribute at specific point in time.
Prevalence
26
summary measure that compares HAI rates over time among one or more groups of patients to that of a standard population
Standardized Infection Ratio (SIR)
27
Proportion of persons at risk who become infected over an entire period of exposure
Attack Rate
28
Attack Rate
of new cases / population at risk (for same time period) * 100
29
Measure of the frequency of death in a defined population, during a specified time (usually a year)
Mortality Rate
30
Mortality Rate
dead / estimated population * K ``` K = 1,000 for crude rates K = 100,000 for cause specific ```
31
Difference in rate of a condition between an exposed population and an unexposed population.
Attributable risk
32
Attributable Risk Formula
Incidence in exposed - incidence in unexposed
33
Odds ratio formula
Draw Table and (A*D)/(B*C)
34
Probability of not having a disease given a negative screening test result in the screened population
Negative predictive value
35
Probability of having the disease given a positive screening test result in the screened population
Positive predictive value
36
The higher prevalence of the disease, PPV____________ & NPV ________________
PPV increases, NPV decreases
37
Relative risk equation
Draw table | A/R1) / (C/R2
38
If R (relative risk) equals 1....
There is no significant association
39
If R < 1
There is a negative association
40
If R > 1...
There is a positive association
41
The probability of committing a Type I error is referred to as
Significance level
42
This type of error means rejecting the null hypothesis when it is true and attributing significance where there is none
type 1 (alpha)
43
This type of error means accepting the null hypothesis when it is false or not attributing significance when it exists
Type II (Beta)
44
You can reduce a Type I error by...
Decreasing the length of rejection area, keep alpha level very small (0.05, 0.01)
45
You can reduce Type II errors by
Increasing the sampling size
46
The p value in statistical test results indicates
The probability of having committed a Type 1 error
47
What parametric test type test that the means of two sample groups are not different for a sample size >30 with normal distribution?
Z test
48
What parametric test is used with the sample size is < 30?
T test
49
T/F: Non-parametric test (such as Chi-square) make no assumptions about distribution of population values.
True
50
The probability that a test correctly identifies patients without disease as negative
Specificity
51
The probability that a test correctly identifies as positive patients who have the disease
sensitivity
52
Sensitivity Equation
TN/(TN + FP)
53
Specificity Equation
TP/(TP+FN)
54
Chi-square Equation
(O-E)^2/E
55
This non-parametric type of test is used for medium to large samples and tests the association between two classifications of a set of counts or frequencies.
Chi-square
56
This non-parametric test is used in place of the chi-square when the sample size number is <20
Fisher's Exact
57
The _____ of a test is its ability of a test detect a specified difference (e.g. the probability of rejecting the null hypothesis when it is false)
Power
58
Power of a hypothesis is affected by these 3 factors
1. sample size: Bigger sample size=greater the power 2. Significance level: higher significance = higher the power 3. The greater the difference between the "true" value parameter and the value specified in the null hypothesis, greater the power of a test.
59
What kind of graph shows a frequency distribution with values of the variable on the x-axis & the number of observations on the y-axis; data points are plotted at the midpoints of the intervals and are connected with a straight line?
Frequency polygon
60
Difference in rate of a condition between an exposed population and an unexposed population
attributable risk
61
The proportion of cases attributable (and avoidable) to this exposure in relation to all cases.
Attributable Risk Percent (ARP)
62
Attributable Risk Percent Calculation
(relative risk - 1) + relative risk
63
Precision of the relative risk is related to...
the power of a study.
64
this type of chart uses calculated upper & lower limits over time
control charts
65
this type of chart is useful in IC because there can be more than one error per patient taken into account
U Charts
66
This type of chart provide a range of expected variation about a mean and the upper & lower limits beyond which the process is considered out of control
control charts
67
This type of chart is useful in conveying changes in rates over time & identifying points in time when rates are outside the expected range
control charts