Biostatistics, Chapters I & II

Cluster

Sampling: dividing the population into groups by a category.

Ordinal Variable

: categorical variables but with a clear ordering (small /medium /large)

Outliers

are any points that lie outside of the LF and UF.

Population

: complete collection of all measurements or data that are being considered.

Categorical Variables

: two+ categories, but no intrinsic ordering (ex: blood type)

Discrete Variables

: a numeric variable for which we can list the possible values (think: integers)

numeric variable

Continuous Variable: a(n) that is measured on a continuous scale (temperature, height)

Outliers

are marked by small circles.

categorical variables

Bar Charts: frequency distribution for .

Population

complete collection of all measurements or data that are being considered

Sample

sub-collecion of members selected from a population

Simple Random Sample

each member of the population has the same change of being included, and samples are chosen independently

Cluster Sampling

dividing the population into groups by a category

Stratified Random Sampling

divide the population into groups (strata) based on one+ classification criteria

Sampling Bias

some members of the population have a higher chance to be selected than others

Ordinal Variable

categorical variables but with a clear ordering (small/medium/large)

Continuous Variable

a numeric variable that is measured on a continuous scale (temperature, height)

Bar Charts

frequency distribution for categorical variables

Histograms

frequency distribution but no spaces

Mean

The average of the observations

N is odd

(n + 1)th largest value

N is even

average of (n/2)th largest value and (n/(2) + 1)th

LF = Q1

h

h = 1.5(Q3

Q1)