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67 Cards in this Set

  • Front
  • Back
Indepentent Variable (IV)
affect or alter status on another V
Dependent Variable (DV)
depends on status from another V
Ptotocol Analysis
Content analysis of cognitive processes
Interval recording
observing a beh'r for a peroid of time
Event sampling
observing a beh'r each time occurs
Simple random sampling
Ea member of pop has equal chance of being selected
Stratefied random sampling
dividing pop into strata and randomly selecting subs
cluster sampling
selecting units of ind rather than inds and either including all inds or randomly selecting from units
extraneous Variable
source of systematic error.
irrelevant V
Techs to control effects of extraneous Variable
random assignment
holding ext v constant
matching subs on ext v
building ext into study (blocking)
statistical control- Ancova
internal validity
determine if a causal relat exists
extraneous V
biological or psychological change that occurs to sub during course of study as a function of time
external event which affects subs
when exposure to test alters subs performance
accuracy of measures or procedures
interaction betw selection and treatment
subs characteristics make them respond in a certain way that can't be generalized to pop
respond in a certain way when know observed
demand characteristics
Cues that inform subs of study purpose or what is expected
mutliple treatment interference
exposing subs to 2 or more levels on IV
counterbalance design
control treatment interference- sub receive levels in randon order
between groups designs
effects of dif levels of IV assessed by admin ea level to a dif grp of subs and then comparing the status
factorial design
2 or more IV
through info relat among V's
analysis the main effect of IV and interaction between them
main effect
effecton 1 IV onthe DV, disregardign effects of all other IV
effects of an IV differ at dif levels of another IV
within subs design
all levels of the IV are administered sequentailly to all subs
subs performance on post-tests is likely correlated to performance on pretests.
can inflate the value therey increasing chance of Type I error
mixed design
combo of between grp and within sub methologies
AB design
simple single sub
ABA, ABAB reversal designs
more than baseline and or more than one treatment
multiple baseline design
if reversal unethical
not require withdrawal of treatment
nominal scale
unordered cats
eg) sex
ordinal scale
divides into cats and gives info on order
eg ranks and Likert
interval scale
order, equal intervals
eg) IQ tests
ratio scale
order, equal intervals and absolute zero pt.
eg) Kelvin scale, no correct answers, reaction in seconds
postively skewed
negativley skewed
m, md, mo
subtract lowest score from highest
variance (meam square)
all of the scores
standard deviation
measure of variablity
sq root ss/n-1
central limit theorem
as sample size increases, samplling distribution of the mean approaches normal distribution
the mean of the sampling dist = pop mean
sd of the mean= pop SD divided by the sq rt of the sample size
standard error of the mean
sd of a sampling dist of the mean
size of rejection region
.05 or 5% = rejection; 95% is retention
rejection region always in tail
type I error
reject true null
equals alpha
type II error
retains a false null
equals beta
parametric tests
pop mean, variance, other parameters
interval or ratio scale.
when a study has more than 1 grp has homoscedasticity
and value of interest in normally dist. in pop.
nonparametric tests
analyze data collected on variables on a nominal or ordinal scale.
chi square
analyze frequency of observations of a nominal variable
mann-whitmey u test
ordinal data
study includes 2 independent grps and data on DV is reported in ranks
wilcoxon matched-pairs signed ranks test
two correlated (matched) grps and the dif between the DV scores of subs who have been matched in pairs are converted to ranks
kruskal-wallis test
sim to mann-whitney
study included 2 or more indepentdent grps and the data to be analyzewd are ranks
student t tes
eval dif between 2 means
analysis of variance
compare 2 or more means
factorial ANOVA
study has 2 or more IV
randomized block factorial ANOVA
blocking has been used to control ext V
repeated measures ANOVA
within sub design in wch dif levels of the IV or combo of the levels of 2 or > IV are sequentially given to ea sub
analysis of covariance (ANCOVA)
combo of anova and regression analysis.
control ext v by statistically removing the portion of variability in the DV caused by the ext V
mixed (split-polt) anova
mixed design.
at least one IV is a between-grp V and IV is a within-sub V
trend analysis
1 or > quantitative IV and eval form of relat between IV and DV
mutivariate analysis of variance (MANOVA)
1 or > IV and 2 or > DV that are ea measured on an interval or ratio scale.
correlation coefficient
sums the degree of association bet V with a single number Pearson r
mutlivaraite techs
assess degree of association among 3 or > V and make predications that involve at least 2 predicators and 1 criterion
mutliple regression
2 or > continuous or discrete preds will be used to predict status on a continous criterion
canonical correlation
extensionof multiple regression
discriminant function analysis
2 or > continuous preds will be used to predict or est a person's status on a single nominal criterion
logistic regression
predict status on a single discrete criterion using 2 or > cont or discrete preds.
path analysis
extension of multiple regression
translating a theory about the causal relationship among a set of variables into a path diagram
path analysis
used when a causal model includes recursive (1 way) and non-recursive (2 way)paths.
exams the relat between observed V and takes into account the latent traits those V are believed to measure and the effects of measurement error.