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80 Cards in this Set
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Experimental designs in which only one independent variable is manipulated

OneWay Designs.


This is the simplest oneway design, in which there are only two levels of the independent variable.

TwoGroup Experimental Design


A between subjects design in which participants are randomly assigned to one of two or more conditions.

Randominzed Groups Design


Participants are matched into blocks on the basis of a variable the researcher believes relevant to the experiment.

MatchedSubjects Design


Each participant serves in all experimental conditions.

Repeated Measures Design


The dependent variable is only measured after the experimental manipulation has occured

Posttest Only Design


Measure the dependent variable twicebefore and after the independent variable is manipulated.

PretestPosttest Design.


One drawback of using pretests.

Pretest Sensitization


3 basic oneway designs.

1) Randomized Groups Design
2) MatchedSubjects Design 3) Repeated Measures Design 

An experimental design in which 2 or more independent variables are manipulated.

Factorial Design


Often, the independent variables are referred to as:

Factors


A twoway factorial design has how many independent variables?

2


A 2x2x2 design has how many independent variables and how many levels?

3 independent variables and 2 levels.


Participants are assigned randomly to one of the possible combinations of the independent variables.

Randomized Groups Factorial Design.


In this design, first participants are matched into blocks on the basis of some variable that correlates with the dependent variable.

MatchedSubjects Factorial Design.


There will be as many participants in each matched block as there are:

Experimental Conditions


Requires all participants to participate in every experimental condition.

Repeated Measures Design


A design that combines one or more betweensubjects variables with one or more withinsubjects variables is called:

Mixed Factorial Design, BetweenWithin Design, or SplitPlot Factorial Design.


Primary advantage of factorial designs over oneway.

Provide information not only about the separate effects of each independent variable but also about the effects of the independent variables combined.


The effect of a single independent variable in factorial design.

Main effect.


This is present when the effect of one independent variable differs across the levels of other independent variables.

Interaction


Researchers seldom design studies with more than:

Three or Four independent variables.


Age, sex, intelligence, ability, personality and attitudes are examples of:

Subject Variables.


Called by the author...refers to design in which independent variables are manipulated and features of correlational designs in which subject variables are measured.

Expericorr Factorial Designs.


Procedure in which the researcher identifies the median of the distribution of participants' scores on the variable of interest.

MedianSplit Procedure.


Selecting participants for the experiment whose pretest scores are unusually low or high on the variable of interest.

Extreme Groups Procedure.
(often criticized and rarely used). 

The subject variable's effect on the independent variable is known as the

Moderator Variable
(not causal, but moderating) 

Researchers use this to determine whether the observed differences between the means of the experimental conditions are greater than expected on the basis of error variance alone.

Inferential Statistics.


States that the independant variable did not have an effect on the dependent variable.

Null Hypothesis.


States the independent variable did have an effect.

Experimental (or Research) Hypothesis.


Means that the researcher will conclude that the independent variable did indeed have an effect.

Rejecting The Null Hypothesis


Means that the researcher will conclude that the independent variable had no effect.

Failing to reject the null hypothesis.


Occurs when a researcher erroneously concludes that the null hypothesis is false, and thus rejects it.

Type I error.


The probablility of making a Type I error.

Alpha Level.


When we reject the null hypothesis with a low probability of making a Type I error we refer to the difference between the means as

Statistically Significant.


Mistakenly fail to reject the null hypothesis when it is in fact false.

Type II (incorrectly assuming the ind. variable has no effect when it actually does)


The probability that a study will correctly reject the null hypothesis when the null hypothesis is false.

Power.


This is used to determine the number of participants that is needed in order to detect the effect of a particular independent variable.

Power Analysis.


The proportion of variability in the dependent variable that is due to the independent variable.

Effect Size.


Two statistical tests used most often to analyze data collected in experimental research.

tTests and FTests


States which of the two condition means is expected to be larger.

Directional Hypothesis


Merely states that the two means are expected to differ, but no prediction made regarding which will be larger.

Nondirectional Hypothesis.


When a researcher's prediction is directional this is used.

Onetailed test.


Used when the experiment involves a matchedsubjects or withinsubjects design.

paired ttest


Why do we use ANOVA?

Because multiple ttests inflate Type I error.


Researchers sometimes use the ____________ in which they adjust their desired alpha level by the number of tests they plan to conduct.

Bonferroni Adjustment


A statistical procedure when researchers want to test differences among many means.

Analysis of Variances (ANOVA)


ANOVA is based on a statistical test called the ________.

FTest


This is the ratio of the variance among conditions to the variance within conditions.

FTest


This reflects the total amount of variability in a set of data.

Sum of Squares


In ANOVA, this is equal to the sum of the sums of squares for each of the experimental groups.

Sum of Squares Within Groups


SSwg reflects __________

Error Variance


What is the mean square within groups?

MSwg = SSwg/dfwg


dfwg = _________

(nk)


The mean of all the group means.

The Grand Mean


dfbg=

k1


SSbg/dfbg=

MSbg


F=

MSbg/MSwg


If our calculated F value exceeds the critical F value for our degrees of freedom we can then......

Reject the null hypothesis


To identify which means differ significantly researchers use ______

followup tests, (post hoc tests, multiple comparisons)


If an ____________ is significant, we know that the effects of one independent variable differ depending on the level of another independent variable.

Interaction


The effect of one independent variable at a particular level of another independent variable.

Simple Main Effect.


This tests the means between two different conditions

ttest


tests the differences among more than 2 conditions

ANOVA


Whereas an ANOVA tests differences among the means of two or more conditions on one dependent variable, a ____________, tests differences between the means of two or more conditions on two or more dependent variables simulaneously.

Multivariate analysis of variance
MANOVA 

Why use MANOVA?

1) researcher has measured several dependent variables, all which tap into the same construct.
2) To control Type I error 

What are the 3 advantages to a pretest posttest design?

can determine that participants did not differ with respect to the dependent variable intially
can determine how much the independent variable changed their behavior they are more powerful 

What is a betweenwithin factorial design?

A design that combines one or more between subjects variables with one or more withinsubjects variables.


Distinguish main effect and interaction.

Main effect is the effect of a single independent variable in a factorial design. Interaction is present when the effect of one independent variable differs across the levels of the other independent variables.


What is an expericorr factorial design?

A design that combine features of an experimental design and features of a correlational design in which subject variables are measured.


Why is it insufficient to simply inspect the condition means to det. whether or not the ind. variable affected scores on the dep. variable?

The means may differ due to simple error or confound variance. This is the need for inferential statistics.


What is Power?

Power is the probability that a study will correctly reject the null hypothesis when it is false.


Why do researchers desire high power?

Higher power has a higher chance of detecting an effect of an independent variable.


Define statistical significance.

When we can reject the null hypothesis with a low probability of making a Type i error we say that the means are statistically significant.


When would you use a paired ttest?

When the experiment involves a matchedsubjects design or a withinsubjects design.


When ANOVA is used to analyze data from experiments with one independent variable, the sum of squares is composed of what two parts?

SSbg and SSwg


When ANOVA is used to analyze data from experiments with two independent variables, the total sum of squares is composed of four parts. what are they?

1. Error Variance
2. Main effect of A 3. Main effect of B 4. A x B interaction 

When the calculated value of F is less than the critical value of F, what decision does the researcher make regarding the null hypythesis.

The researcher fails to reject the null hypothesis.


What is an interaction?

An interaction is present when the effect of one independent variable differs accross the levels of other independent variables.


When do researchers do posthoc tests?

If ANOVA reveals a difference among 3 levels the significant main effect indicates that a difference exists, but doesn't say which. Post hoc tests such as LSD, Tukey's, etc. reveals this.
