Chapter 5: Variables in Research Flashcards
How are variables related to theoretical concepts? Provide an example.
Distinguish between independent variables and dependent variables. Give examples.
dependent variables are meant to alter when the independent variable is altered
Why is it not accurate to say that the independent variable is the cause and the dependent variable is the effect? Provide an example.
Because you do not always know which is the cause and which one is the effect, it is more accurate to discuss their (relevance??)
Violent video games
What are the levels of an independent variable?
A level is a different value of an independent variable such as placebo or non-placebo
What are the considerations when choosing the levels of an independent variable?
Distinguish between quantitive and categorical variables. Give examples.
quantitive-altered by amount
categorical-altered by kind or type
Giving different amounts of water to a plant is quantitive, choosing which fertalizer to give to the plant is categorical
What is the difference between continuous and discreet variables?
discreet variables cannot have intermediate measurements like a person cannot commit 1.3 crimes. A continuous variable can have intermediate measurements such as someone lifting 101.675 pounds.
Define: measurement
the process of assigning numbers to events or objects according to rules
List the four types of measurement scales.
Describe the four types of measurement scales. What are their properties? Give examples.
Nominal Scale
Ordinal Scale
What is a nominal scale? Provide an example.
a measure that simply divides objects or events into categories according to their similarities or differences (p125)
The nominal scale gives information only about whether two events are the same or different. (127)
What is an ordinal scale? Provide an example.
a measure that both assigns objects or events a name and arranges them in order of their magnitude (p125)
The ordinal scale does that too, but also gives us a ranking on some variable.
What is an interval scale? Provide an example.
a measure in which the differences between numbers are meaningful; includes both nominal and ordinal information
The interval scale conveys nominal and ordinal information, and also allows us to make quantitative statements about the magnitude of the differences between events.
Why does Nico’s mother know more about his liking for vegetables than Jessica’s mother does about Jessica’s vegetable preferences. (126) [Difference between ordinal and interval scale]
Nico’s scale was more specific. Jessica rated her least to most favorite simply by rank while Nico rated his through a numerical value that illustrates the interval gap between favoirites
ex 5,4,3,2,1-Jessica
ex 5, 3.3, 2.4, 1.6-Nico
What is a ratio scale. Provide an example of a meaningful and meaningless zero.
a measure having a meaningful zero point as well as all of the nominal, ordinal, and interval properties
A meaningless zero is like rate your preference fomr 0-10 where it just adds to your bottom end of the same measurment. If 0 meant neutral or nothing it has a meaning as a separate measurment
The ratio scale contains all the information of the other three scales, as well as conveying information about ratios of magnitudes.
Is a person with an IQ of 120 “twice” as smart as someone with an IQ of 60? Why or why not?
Provide an alternate example from the textbook that explains the difference between reliability and validity. Give an example that is valid but nor reliable and the reverse.
Define reliability of a test measure. What are the types of reliability of measures? Give an example of each.
Test-retest reliability and internal consistency reliability
1-take the same test and get the same results
2-split the test questions in half and see if the person scores evenly on both tests (ie see if they are measuring the same thing)
List each type of validity in relation to tests and measurement and provide an example of each
(1) construct validity,
(2) face validity,
(3) content validity
(4) criterion validity
Define construct validity
a test that the mea- surements actually mea- sure the constructs they are designed to measure, but no others (131)
*it can readily make predictions about what it tests!
Define face validity
idea that a test should appear superficially to test what it is supposed to test (131)
ie can the layman see the validity
Define content validity
idea that a test should sample the range of behavior represented by the theoretical concept being tested (132)
ie it measures all that is chiefly relevant and not just one aspect of a thing (intelligence tests)
Define criterion validity
idea that a test should correlate with other measures of the same theoretical construct (132)
ie an intelligence test will measure things people and research commonly agree requires intelligence
Using a bathroom scale as an example, explain how a measurement can be both reliable and invalid.
Distinguish between real and apparent limits. Why are they relevant to independent variables?
Real limits are the rounded number to the next interval. A person may be 5’87645 tall but we would say 5’8 whereas the apparent limit is the specific number
Define variable of interest
a variable of interest is when it is unclear which variable is the cause and which is the effect
Define subject variable
variables that the researcher does not manipulate. Examples could include status of wealth of the subject or IQ
Define confounded variable
A confounded variable is one that varies with the independent variable (122)
In other words, you cannot tell what is actually impacting the dependent variable.
Define error variance
variability in the depen- dent variable that is not associated with the inde- pendent variable
What is the difference between concurrent and predicted validity?
Concurrent-measures what is
predicted-measures what will be
Define random error
This variability could be called random error (or error variance) because it is not associated with any known independent variable. (132)
ie slight unpredictable errors in the measuring tool
Define systematic or constant error. When is it less of a problem and when is it more? Provide examples of each.
-measurement error that is associated with consistent bias
-It is less problematic if the error impacts the variables consistently and evenly
-It is more problematic when it confounds the independent variable
