January 14
th
a
Lecture 1
e
Measurement: process of assigning a symbol (usually a numeral)
according to a set of rules to reflect the amount of a characteristic
something (usually a person or animal) possesses
e
May involve categorizing events (qualitative)
e
May involve using numbers to characterize the size of event (quantitative)
e
Data: the result of measurement
e
Data = a plural word.
. think of it as “facts”
e
Evaluation: higher order word than measurement
e
Judging …measurement up against a standard
e
Accuracy of measurement
o
Validity – whether or not a measurement or a process measures
what it is supposed to actually measure.
o
Reliability – can you reproduce the same number/data
•
Objectivity – kind of reliability …has to do w/ who
administers the test.
Different people measure one
thing but get different numbers… that’s NOT
objective!!
•
You want a test to be objective if you want numerous
ppl to take the test
e
e
January 16
th
a
Lecture 1
e
Statistics: mathematical technique by which data are organized, treated,
and presented for interpretation and evaluation
o
A fact about a sample
e
Evaluation: philosophical process of determining worth of data7
e
The process of measurement
o
Four steps:
1. Identification and definition of object to be measured
2. Identification and definition of standard to which object will
be compared
3. comparison between object and standard
4. Quantitative statement is made of the relationship
between the object and standard
5. English system of measurement compared to metric
system
e
Lecture 2
e
A fact about a population is called a parameter
e
Ordinal is the level of measurement involved in ranking
e
‘There will be no difference between the performance of group A and B’ is
an example of the null hypothesis
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View Full DocumentA study for which there is good evidence that the treatment is the only
things that could have caused the dependent variable to change is high in
internal validity
e
Variable: characteristic of a person, place, or thing that can assume more
than one value
e
Constant: characteristic that can assume only one value
o
In a particular study, only 10 yr old children are included (age is
constant)
o
Number of players on a regulation baseball team
e
Types of variables
o
Continuous variables: theoretically can assume any value and any
level of subdivision
Weight, height…
o
Discrete variable: limited to certain numbers, usually whole
numbers or integers
Apples, computers
e
Levels of measurement
o
Nominal scale: scale which groups subjects into mutually exclusive
categories
Example: occupation
•
Sales, teacher, lawyer, doctor, other
Frequency data: grouping and counting of categories
•
12 sales people, 10 teachers, 5 lawyers, 3 doctors, 6
other
o
Ordinal scale (rank order scale): provides quantitative order to the
variables, but does not indicate how much better one score is than
another
Example: small, medium, and large drinks at a restaurant
o
Interval scale: scale has equal units of measurement but without an
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 Spring '08
 DECKER,MIK
 Normal Distribution, Standard Deviation, Standard Error, Null hypothesis

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