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62 Cards in this Set
 Front
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Pearson r is used to:

Assess the relationship between two variables that are measured with continuous data(age, exam score)


Partial correlation describes the:

Index of the relationship with the influence of a third variable removed.


ANOVA is used to:

Test hypotheses based on population values.


A Ttest is used to:

Analyze data from a study that has one independent variable (with only two levels) and one dependent variable.


In a negatively skewed distribution:

Most scores are very high, the mean is lower than the median, and the median is lower than the mode.


Counterbalancing is used in studies to:

Control for order effects by presenting multiple treatments to subjects in varying orders for different subgroups.


Maturation refers to:

any internal change (biological or psychological) that occurs in subjects while an experiment is in progress  and has a systematic effect on the DV  MAY be a threat to internal validity


Instrumentation:

Can be a threat to internal validity, when the measuring process changes between the pre and post tests (e.g. raters become better at rating with practice)


Path analysis is useful for:

As a causal modeling technique, it can be used for examining unidirectional causal relationships among a set of measured traits


To use trend analysis, you need:

a quantitative independent variable


Autocorrelation refers to:

Observations obtained close together in time from the same subjects tend to be highly correlated


Best control for practice effects in an experiment:

Counterbalancing (


Difference between external & internal validity:

External: concerned with generalizing study to real world
Internal: plausability regarding causal relationships between study variables 

Eigenvalue

Stat that indicates the degree to which a particular factor (in a factor analysis) is accounting for varaiability (so it really tells us the explanatory power of the factor)


Standard score

Type of normreferenced score that is interpreted in terms of how many SD units a score falls above or below the mean (such as zscores & Tscores)


Multiple baseline design

Singlesubject design in which a treatment is applied sequentailly across settings, behaviors, or subjects (baseline data is first collected in each setting)


Advantage of MANOVA over multiple ANOVA's is:

reduces the probability that a Type I error will be made


The standard errors of the mean, measurment, & estimate express error in terms of:

Standard deviation


Construct Validity

How weel does the test measure the theoretical construc (e.g. intelligence) that is attempting to measure


Range of the standard error of measurement:

0 to the standard deviation of the test


Range of the validity coefficient

1 to +1


Range of reliability coefficient

0 to +1


In terms of reliability & validity, increasing test length will:

affect reliability more than validity


Rejecting a false null hypothesis means:

Your study has power


If you go from a onetailed test to a twotailed test, you are..

Lees likely to correctly reject the null (as you are losing power)


History refers to:

A threat to internal validity when any EXTERNAL event that affects scores on theDV (besides the experimental treatment)


Statistical Regression:

Tendency for extreme scores to revert to the average upon retesting (batting average)
Can be a threat to internal validity 

Differential Mortality

Threat to internal validity, when people who drop out of one of the groups, differ in significant ways from people who remain in the study


Controlling threats to internal validity:

1)Random assignment  most powerful method
2)Matching  identifying subjects who are similar & pairing off (bestwhen sampl size is small) 3) Blocking  analyzing the statistical effects of an extraeous variable 4)Holding constant  only including subjects who are homogenous 5)ANCOVA  statisical strategy for removing the effects of extraneous variables 

THREATS to external validity

1)Int. btw Selection & Tx 
2)Int. btw. Hx & Tx can't generalize to other settings time/period 3)Int. btw. Testing & Tx  can't geberalize unless had a pretest 4)Demand Chracteristics  cues in setting allowed subjects to guess hypothesis 5)Hawthorne Effect 6)Order Effects  problem with repeated measures design 

Ways to increase External Validity

1)Random Selectionensuress equal representativeness
2)Naturalistic Research  controls for Hawthorne & demand characteristics 3)Single/Double Blind Researchsubjetcs/researchers don't know which treatment has been assigned 4)Counterbalancing  controls for order effects 

True vs. Quasi Experimental Research

True = investigator randomly assigns subjects to different groups
Quasi = random assignment is not possible 

Developmental Research

1)Longitudial Design = same people studied over time
2)CrossSectional = different groups, divided by age are studied at the same time 3)CrossSequential = representative samples of different ages groups are assessed on two or more occasions 

SingleSubject Designs

1)AB Design  single baseline foloowed by single tx
2)Reversal (Withdrawal) Design  baseline, treatment, return to baseline, (ABA, or ABAB) 3)Multiple Baseline  IV is sequentially administered across 2 or more subjects, behaviors, or settings 

ZScore

A measure of how many SD's a given score is from the mean


TScore

based on 10 point intervals, where T=50, as the mean, and every 10 points above or below is one SD


Stanine Scores

distribution of 9 equal intervals 19, mean = 5 and SD = 2


Standard Error of the Mean

expected error of a given sample mean. It is obtained by dividing the SD by the square root of N


Type I Error:

conclude there is a difference, when in fact there is not


Type II Error

concluding there is no difference, when in fact there is


Factors that affect Power

Sample size = increases
Alpha  increases Onetailed  increases Magnitude of Population Difference  increases 

TTest

(Parametric test used to test hypotheses about two means)
One Sample = comparing one sample to a population mean Independent Samples = comparing 2 means that are unrelated Correlated Samples = compares means that are matched or related to each other 

Post Hoc Tests

1)Schaffe = most conservative (least Type 1 error)
2)ukey is best for pairwise comparisons 

ANOVA

Oneway = 1 independed variable & more than 2 independent groups
Factorial (2way) = used when there are more than one independent variable 

MANOVA

used when a study has 2 or more dpendent variables and one or more independent variable


MannWhitney

nonparametric test used forrankordered data when there are more than 2 independent groups


Factors Affecting the Pearson r

1)Linearity  assumes the reationship is linear
2)Homoscedasticity  assumes dispersion of scores is equal 3)Range of Scores  assumes a wide range of scores 

Misc. Correlation Coefficients

PointBiserial =relates 1 continous variable & 1 dichotomous
Contingency = correlation btw. 2 nominal variables, that each have at least 3 categories 

Spearman's Rho

Used to correlate 2 variables that are ordinally ranked


Eta

used to measure continous data when the relationship is nonlinear


Canonical Correlation

used to relate 2 or more predictors to 2 or more criterion variables


Discriminant Function Analysis

scores on 2 or more variables are combined to determine whether they can be used to predict which criterion group a person belongs in (i.e. high or low achievement group)


Suppressor Variable

an extraneos variabel that results in a spuriously LOWER correlation (it suppresses the relationship)


Trend Analysis

statitical technique for looking at the pattern of change between two quantitative variables (include linear, quadratic, cubic, & quartic)


Rosenthal Effect

when the experimenter's expectancies influence subject's responses on a dependent variable in the direction predicted


Solomon 4 group design is used to

Evaluate the effects of testing


ANCOVA is used to

reduce error variance due to an extraneous variable


In regards to SD & Validity, the Standard Error of Estimate has:

a direct relationship with SD of the criterion & an indirect relationship with validity


Item Response Theory is based on the premis that:

when test content is of varying difficulty, uniform scales of measurement can be applied to persons of different ability level


In weighting variables in a multiple regression equation, we use:

line of best fit


Cluster analysis is used for the purpose of:

deriving several subgroups from a cluster of dependent variables


Advantage of ANOVA over multiple TTests is:

Reduces Type I error
