5. Measurement is a process of assigning values
to variables based on rules
Measurement results from an interaction
among an instrument, the subject being
measured, and the measurement
environment
6. Type Level Example
Nominal Unordered categories Gender is either male or
female
Ordinal Ordered
categories
Size is small, medium or, large
Interval No true zero, but equal
intervals
% items correct on
achievement test as an
indicator of ability
Ratio True zero and equal intervals % items correct on
achievement test
7. Discrete –
• Well-defined finite set of possible values (which are
called states of the discrete variable).
• Commonly have 9 or fewer categories with numeric
values, but can have more (e.g., country names)
Continuous –
• Take on any value between any other two values.
• Any real-values number along a number line.
• Usually even variables with discrete values are treated
as continuous if they have >9 values.
8. Measurement Levels
Nominal Ordinal Interval Ratio
TypesofVariables
Discrete
X X
Maybe, but
treated as
continuous
Maybe, but
treated as
continuous
Continuous Never Never
X X
10. Population versus sample
Parameter versus statistic
Inference of population parameters from
sample statistics
11. Population
• Any complete group with at least one characteristic in
common
• Not just people, but any entity
• Might consist of, but not limited to, people, animals,
businesses, buildings, motor vehicles, farms, objects, or
events
Sample
• A group of units selected from a larger group (the
population)
• Generally selected for study because the population is too
large to study in its entirety
• Good samples represent the population
12. Parameter
• Information about a population
• Characteristic of a population
• A population value
• The “truth”
Statistic
• Information about a sample
• An estimate of a population value
20. Data usually are available from a sample, not a
population
That is, sample statistics are available, not population
parameters
We wish to infer (or estimate) parameters from
statistics
Because data are available from a sample, not the
population, error occurs when inferring (or estimating)
population parameters from sample statistics
Statistical techniques help us make decisions under
error and uncertainty
22. Are composed of propositions that explain the
empirical, observable world. A proposition is an
“if–then” statement
Are networks showing relationship and causality
among propositions
Must have“empirical import”
23. The foundation of theory-building
Statements of testable scientific propositions
The focus for empirical work
24. Examine propositions in theory that require
verification.
Are specific.
Are testable.
25. The term "nomological" is derived from Greek
and means "lawful”
A nomological network is a "lawful network,” a
network of propositions that describe how
things work
26.
27.
28.
29.
30. Hypotheses are“tested”
Hypotheses are never“proved”
Hypotheses only are“rejected”
Theories are built and verified by testing hypotheses