Biostatistics Flashcards

1
Q

Discrete variable

A

Can take only a limited number of values within a given range

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1
Q

Nominal

A

Discrete Variable that is classified into groups in an unordered manner

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2
Q

What kind of variable is “disease presence [yes or no]”

A

Nominal variable

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3
Q

Ordinal variable

A

ranked in a specific order but with no consistent magnitude of difference between rankes

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4
Q

What kind of variable is “NYHA functional class”

A

Ordinal variable

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5
Q

What is the most common error type in data with discrete variables?

A

Measure of central tendency- in most cases means and standard deviations should not be reported with ordinal data

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6
Q

Continuous variables

A

can take on any value within a given range

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7
Q

What kind of variable is interval

A

Continuous variable with data ranked in a specific order with a consistent change in magnitude between variables

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8
Q

What kind of data is degrees Fahrenheit?

A

Interval variable

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9
Q

What kind of variable is ratio data?

A

Like “interval” but with absolute zero

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10
Q

What kind of data is heart rate or blood pressure

A

Ratio (continuous variable)

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11
Q

Arithmetic mean (average)
-Definition
-What data should be used
-Weaknesses

A

-Sum of all values divided by the total number of values
-continuous and normally distributed data
-very sensitive to outliers and tend toward the tail

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12
Q

Median
-Definition
-What data should be used
-weaknesses

A

-midpoint of the values when placed in order from highest to lowest
-ordinal or continuous data
-insensitive to outliers

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13
Q

Mode
-Definition
-What data should be used
-weaknesses

A

-Most common value in a distribution
-nominal, ordinal, or continuous data
-does not describe meaningful distributions with large range of values, each of which occurs infrequently

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14
Q

Standard deviation
-Definition
-How to find (mathmatically)

A

-measure of variability about the mean (spread of data)
-square root of the variance (average squared difference of each obs from the mean)

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15
Q

Range
-Definition
-Weakness

A

-Difference between the smallest and largest values in a data set
-Very sensitive to outliers

16
Q

Percentiles
-Definition
-Example

A

-The point (value) in a distribution in which a value is larger than some percentage of the other values in the sample. Can be calculated by ranking all data in a data set
-The 75th percentile lies at a point at which 75% of the other values are smaller

17
Q

Inferential Statistics
-Definition

A

Conclusions or generalizations made about a population (large group) from the study of a sample of that population

18
Q
A

the wider the CI –> the more likely it is to encompass the true population

19
Q

What test will compare the mean of the study sample with the population mean (or two independent samples)?

A

Student-t test

20
Q

What kind of test will compare matched samples

A

paired student t-test

21
Q

What does ANOVA stand for?

A

analysis of variance

22
Q

What kind of test can be used to compare more han two groups?

23
Q

What does ANCOVA stand for?

A

Analysis of covariance

24
What kind of test explains the influence of one variable on another while statistically controlling for other variables?
ANCOVA
25
What kind of tests should be used when you dont have discrete data or data is not normally distributed?
Nonparametric tests
26