Chapter 2

-11
"A measure should have validity, describing what it is intended to measure and accurately reflecting the concept."
"It should also have reliability, being consistent in the sense that a subject will give the same response when asked again."
"Statistical methods help us determine the factors that explain variability among subjects.
Variable (VAR) - any characteristic we can measure for each subject, that can vary in value among subjects in a SAM or POP.
Measurement scale - the values the VAR can take


-12


Classification of VAR
-- whether the measurement scale consists of categories or numbers
-- number of levels in that scale


Quantitative (QUAN) VAR - measurement scale has numerical values
-- values represent different magnitudes of the VAR


Categorical (CAT) VAR - measurement scale is a set of categories
-- distinct categories differ in quality, not in numerical magnitude
-- often called Qualitative (QUAL)




Interval (INT) - the possible numerical values for a QUAN VAR
-- specific numerical distance between each pair of levels


CAT VAR -- unordered and ordered
Nominal scale - CAT VAR for which scale does not have a high or low end, no level is greater than or smaller than any other level, unlike values for QUAN VAR.


Ordinal (ORD) scale - CAT scales that have a natural ordering of values


"A third type of scale falls, in a sense, between nominal and interval.  It consists of categorical scales having a natural ordering of values.  The levels form an ordinal scale.  Examples are social class (upper, middle, lower), political philosophy (very liberal, slightly liberal, moderate, slightly conservative, very conservative) [...]."


-13


"The scales refer to the actual measurement and not to the phenomena themselves."

Chapter 1

-3
Statistics (STA) - body of methods for obtaining and analyzing(A) data(D)
Design - planning how to gather D for research studies
Description (DESC) - summarizing D
Inference (INF) - making predictions based on D.  
DESC STA - graphs, tables, numerical summaries
STA INF - predictions made using D
STA A -- DESC and INF


-4
Subjects - entities that a study observes
Population (POP) - total set of subjects of interest in a study
Sample (SAM) - subset of the POP on which the study collects D
DESC STA - summarize the information in a collection of D
INF STA - provide predictions about a POP based on D from SAM of POP


-5
Parameter - numerical summary of the POP
STA - numerical summary of the SAM D