Biostatistics BCPS (Study Guide For Pharmacy Amb
Care Certification) – Qs & As
Discrete Variables ✔️Ans -Can only take a limited number of
values within a given range.
1. Nominal
2. Ordinal
Nominal Data ✔️Ans -Discrete Variable
Data of categories only, unordered, with no indication of relative severity.
Data cannot be arranged in an ordering scheme. (Gender, Race, Religion,
mortality, disease state)
Ordinal Data ✔️Ans -Discrete Variable
Placed in categories and rank ordered, distance between categories may
not be the same. Ex: pain is low, moderate, high
Continuos Variables ✔️Ans -Variable that can have unlimited
number of possible values; can take on any value within a given range. Ex.
1. Interval
2. Ratio
Interval Data ✔️Ans -Continuous Variable
Data are ranked in a specific order with a consistent change in magnitude
between units; zero point is arbitrary (degrees Fahrenheit)
Ratio Data ✔️Ans -Continuous Variable
Interval data with an absolute zero (degrees Kelvin, HR, BP, time, distance)
Mean ✔️Ans -The arithmetic average of a distribution, obtained
by adding the scores and then dividing by the number of scores. Should
only be used with Continuous and normally distributed data. Very sensitive
to outliers
Median ✔️Ans -A value found by ordering a group of data from
least to greatest and choosing the middle value of the group. Also called the
50th percentile. Can be used with Ordinal and Continuous data. Insensitive
to outliers.
, Mode ✔️Ans -The number that occurs most often in a set of
data
Standard Deviation ✔️Ans -A measure of variability that
indicates the average difference between the scores and their mean. Use
only for continuous data that are normally distributed. +/- 1 SD = 68% of
sample values, +/- 2 SD = 95% of sample values, +/- 3 SD = 99% of sample
values
Coefficient of Variation ✔️Ans -A measure of dispersion
calculated by dividing a distribution's standard deviation by its mean.
SD/meanX100%
Range ✔️Ans -The difference between the greatest and least
numbers in a set of data. Sensitive to outliers.
Percentiles ✔️Ans -The point value in a distribution in which a
value is larger than some percentage of the other values in the sample. The
75th percentile lies at a point at which 75% of the other values are smaller
IQR interquartile range ✔️Ans -The difference between the
25th and 75th percentiles; contains 50% of data
Normal Distribution ✔️Ans -Gaussian dist. Approximate
distribution of scores expected when a sample is taken from a large
population, drawn as a frequency polygon that often takes the form of a
bell-shaped curve, called the normal curve. The mean an the median will be
about equal
Parametric Data ✔️Ans -Data has a tendency to group together,
to have a common mean from which they individually vary. Normally
distributed data are termed parametric.
Standard Error of the Mean ✔️Ans -An estimation of the
unaccounted for error within a mean. If the mean is 10 and the standard
error of the mean is 2, then the true score is likely to fall somewhere
between 8 and 12 or 10 +/- 2. Can be estimated by dividing the SD by the
square root of n (sample size)
Care Certification) – Qs & As
Discrete Variables ✔️Ans -Can only take a limited number of
values within a given range.
1. Nominal
2. Ordinal
Nominal Data ✔️Ans -Discrete Variable
Data of categories only, unordered, with no indication of relative severity.
Data cannot be arranged in an ordering scheme. (Gender, Race, Religion,
mortality, disease state)
Ordinal Data ✔️Ans -Discrete Variable
Placed in categories and rank ordered, distance between categories may
not be the same. Ex: pain is low, moderate, high
Continuos Variables ✔️Ans -Variable that can have unlimited
number of possible values; can take on any value within a given range. Ex.
1. Interval
2. Ratio
Interval Data ✔️Ans -Continuous Variable
Data are ranked in a specific order with a consistent change in magnitude
between units; zero point is arbitrary (degrees Fahrenheit)
Ratio Data ✔️Ans -Continuous Variable
Interval data with an absolute zero (degrees Kelvin, HR, BP, time, distance)
Mean ✔️Ans -The arithmetic average of a distribution, obtained
by adding the scores and then dividing by the number of scores. Should
only be used with Continuous and normally distributed data. Very sensitive
to outliers
Median ✔️Ans -A value found by ordering a group of data from
least to greatest and choosing the middle value of the group. Also called the
50th percentile. Can be used with Ordinal and Continuous data. Insensitive
to outliers.
, Mode ✔️Ans -The number that occurs most often in a set of
data
Standard Deviation ✔️Ans -A measure of variability that
indicates the average difference between the scores and their mean. Use
only for continuous data that are normally distributed. +/- 1 SD = 68% of
sample values, +/- 2 SD = 95% of sample values, +/- 3 SD = 99% of sample
values
Coefficient of Variation ✔️Ans -A measure of dispersion
calculated by dividing a distribution's standard deviation by its mean.
SD/meanX100%
Range ✔️Ans -The difference between the greatest and least
numbers in a set of data. Sensitive to outliers.
Percentiles ✔️Ans -The point value in a distribution in which a
value is larger than some percentage of the other values in the sample. The
75th percentile lies at a point at which 75% of the other values are smaller
IQR interquartile range ✔️Ans -The difference between the
25th and 75th percentiles; contains 50% of data
Normal Distribution ✔️Ans -Gaussian dist. Approximate
distribution of scores expected when a sample is taken from a large
population, drawn as a frequency polygon that often takes the form of a
bell-shaped curve, called the normal curve. The mean an the median will be
about equal
Parametric Data ✔️Ans -Data has a tendency to group together,
to have a common mean from which they individually vary. Normally
distributed data are termed parametric.
Standard Error of the Mean ✔️Ans -An estimation of the
unaccounted for error within a mean. If the mean is 10 and the standard
error of the mean is 2, then the true score is likely to fall somewhere
between 8 and 12 or 10 +/- 2. Can be estimated by dividing the SD by the
square root of n (sample size)
