Chapter 4 Flashcards
Any factor or attribute that can be measured
variable
Variables that are an attribute and are descriptive
Categorical or qualitative variables
Variables that can be numerically measured
Quantitative variable
Variables that cannot have intermediate values. ex: 1, 2, 3…
Discrete variables
Variables that can have any possible value
continuous variables
The presumed cause in a cause-effect reaction
independent variable
the presumed effect in a cause-effect reaction
dependant variable
A characteristic that differs across environments or situations
situational variable
A personal characteristic that differs across individuals
characteristic variable
Can the same factor be independent or dependant?
yes
Can an experiment have multiple dependant variables?
yes
Can an experiment have multiple independent variables?
yes
Underlying characteristics or processes that are not directly observed, but are inferred from behaviours or outcomes
hypothetical constructs
A variable that provides a causal link for an independent and dependent variable
mediator variable
A factor that alters the strength or direction of the relation between an independent and dependent variable
moderator variable
Referring to defining a variable in a measurable or manipulatable way
operational definition
The process of systematically assigning values to represent something
measurement
rules for assigning scale values to measurements
scales of measurement
A scale of values that only represent qualitative differences i.e. differences in college major or type of anxiety disorder
nominal scale
Assumptions made about nominal scale
All values represent a categorical variable, all values are equal to each other, the numbers themselves are arbitrary when assigned to something (1=biology, 2=physics)
Advantages of a nomial scale
able to find differences within a catagory
Limitations of a nomial scale
Not compatible with statistics, no fixed scale
Scale values represent relative differences of some attribute i.e. rank =1 (least populator) to rank = 25 (most popular)
ordinal scale
Advantages of an ordinal scale
arrange groups, measure order of magnitude
limitations of an ordinal scale
Not compatible with statistics
A scale that has equal differences between values on the scale reflects equal differences in the attribute being measured i.e. temperature
interval scale
Advantages of an interval scale
find differences between categories, analyze scores
Limitations of interval scale
Not compatible with statistics
When equal distances between values on the scale reflect equal differences in the amount of attribute being measured and has a true zero point
ratio scales
Advantages of a ration scale
Has a true zero which represents the absence of an attribute, compatible with stats
Represents the degree to which the measure yields results that agree with a known standard
accuracy
A degree of constant error occurs with each measurement
systematic error
The consistency of a measure
reliability
Random fluctuations that occur during measurement and cause the obtained scores to deviate
random measurement error
What can cause random measurement errors?
participants’ characteristics, measurement setting or procedures, issues with measurement instruments, or mistakes in transcribing data
Determining reliability by administering the same measure two or more times
Test-retest
The degree to which the items on the test an interrelated
internal reliability
A test is divided in two, so one half is correlated with the other
split-half reliability
A statistic that reflects how strongly individual items on a test corrolate
Cronbach’s alpha
The degree to which independent observers show agreement in their observations
interobserver reliablity
How accurate is an inference. It should be based on sound reasoning
validity
The degree to which the items on a measure appear to be reasonable
face validity
represents the degree to which items on a measure adequately represent the entire range of the content
content validity
the degree to which the scores acurately measure the content
criterion validity
The degree to which the measures accurately measure the construct it’s supposed to
construct validity
