STATISTICS:
A set of methods and rules for organizing, summarizing, and interpreting
information.
POPULATION:
A set of all the individuals of interest in a particular study.
SAMPLE:
A set of individuals selected from the population, as representative of
the population in a particular study.
PARAMETER:
Usually a numeric value that describes a population.
STATISTIC:
Usually a numeric value that describes a sample.
DATA:
Measurements of observation (singular: datum).
A
data set is a collection of measurements or observation.
A datum is a single measurement (also called score, or raw
score)
Statistical
procedures used to summarize, organize, and simplify data.
Techniques
that allow us to use sample data to make statements about the population.
The
discrepancy (error) that exists between sample data (a sample statistic) and the
properties of the population (parameters)
A
scale that has no numeric properties. The categories or values on the scale
differ by name only (e.g. male-female, red, black, blonde hair color)
ORDINAL
SCALE
Values
on the scale are meaningful in terms of a rank order of some quantity (e.g.
high, medium, low, in popularity)
INTERVAL
SCALE
The
values on the scale reflect intervals that are equal in terms of size (e.g.
temperature). There is no absolute
zero point on the scale (where the zero indicates absence of the attribute
measured)
RATIO
SCALE
Has
equal intervals and a true zero point (e.g. the number of errors on a
proofreading task during a 10-minute period).
The
type of measurement scale determines the appropriate statistic used when
analyzing data.
FACTORS
AFFECTING YOUR CHOICE OF A SCALE OF MEASUREMENT
A nominal scale yields the least information. An
ordinal scale adds some crude information. Interval and ratio scales yield the
most information.
The statistical tests available for nominal and
ordinal data (nonparametric) are less powerful (sensitive) than those available
for interval and ratio data (parametric).