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28 Cards in this Set
- Front
- Back
researchers manipulates _________ to create groups that differ _______________ in levels of that variable and then compares the groups in terms of ____________________ |
(1) the independent variable (2) in the levels of that variable (3) their scores on dependent variable |
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All other variables are kept constant by |
(1) direct experimental control (2) Random assignment |
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if the scores of the two groups are different |
Researcher can conclude that independent variable caused results |
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Confounding Variable |
varies along with the independent variable - occurs when effects of independent variable and an uncontrolled variable are intertwined - with confounding variable cannot determine which variable is responsible for the effect |
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Internal Validity |
When results of an experiment can confidently be attributed to the effect of the independent variable - to achieve must design and conduct experiment so that only independent variable can be cause of results |
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Simple experimental design = |
2 variables - independent variable - dependent variable |
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To make sure only difference between the 2 groups is manipulated variable (3 steps) |
(1) Obtain two equivalent groups of participants (2) Introduce the independent variable (3) Measure effect of the independent variable on the dependent variable ` |
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Steps for experiment (for high internal validity) |
(1) Choose participants and assign them to the levels of the independent variable (2) Operationally define the independent variable to create at least 2 levels (3) Determine a way to measure the effect of the independent variable by operationally defining the dependent variable |
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(1) Choose the participants and assign them to the levels of the independent variable |
- must achieve equivalent groups to eliminate selection differences |
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3 ways to assign participants to experimental conditions |
(1) independent groups design: groups are made equivalent by randomly assigning participants to experience only one condition of the independent variable (2) Repeated measures design: participants are assigned to participate in all levels of the independent variable (3) Matched pairs design: makes group equivalent by first selecting pairs of participants who score the same on some variable of interest |
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(3) Determine a way to measure the effect of the independent variable by operationally defining the dependent variable |
same measurement procedure is used for both groups so that comparison of the two groups is possible |
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Independent groups design |
different participants are assigned to each level of the independent variable - through random assignment - as # of participants in study increases, random assignment prevents any systematic biases - with sufficiently large sample of participants, random assignment will produce groups that are virtually identical in all respects |
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pretest |
given each group prior to introduction of the experimental manipulation - to ensure that groups are equivalent at the beginning of the experiment - usually not necessary if participants have been randomly assigned to the two groups |
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posttest - only design |
when no pretest is given |
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3 main reasons why researcher may add a pretest |
(1) sample size is small => increases the likelihood that groups actually will not be equal on all variables (2) to select the participants to include in the experiment (3) when there is a possibility that participants will drop out of the experiment |
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mortality |
dropout factor in an experiment |
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Disadvantages of a pretest (3) |
(1) time-consuming and awkward to administer (2) Can sensitizes participant to what is being studied thus creating demand characteristics (3) can reduce external validity |
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Solutions for pretest disadvantages (2) |
(1) pretest can be disguised using deception (2) Embed the pretest in a set of irrelevant measures |
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Solomon four-group design |
- possible to assess the impact of the pretest directly by treating the presence of a pretest as a 2nd independent variable - Participants randomly assigned to one of four possible combinations |
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Repeated Measures Design |
participants are repeatedly measured on the dependent variable after being in each condition of the experiment |
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Advantages of Repeated Measures Design |
-Fewer participants needed -Extremely sensitive to statistical differences - Error variance is reduced b/c people serve as their own control group |
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Disadvantages of Repeated Measures Design |
Order effect: the order of presenting the treatments may affect the dependent variable |
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3 types of order effect |
(1) Practice effect: improvement in performance as a result of repeated practice with a task (2) Fatigue Effect: deterioration in performance as the research participant becomes tired, bored or distracted (3) Contrast Effect: when the response to the 2nd condition in the experiment is altered b/c the 2 conditions are contrasted to one another |
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Complete Counterbalancing |
all possible orders of presentation are included in the experiment
- 2 conditions: 2 X 1 = 2 orders - 3 conditions: 3 X 2 X 1 = 6 orders |
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Partial Counterbalancing |
-Latin Square: limited set of orders constructed to ensure... (1) each condition appears at each ordinal pattern (2) each condition precedes and follows each condition one time |
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Time Interval between Treatments |
need to determine the time interval between presentation of treatments and possible activities between them |
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Matched Pairs Design |
more complicated method of assigning participants to conditions in an experiment - ensure groups are equivalent on the matching variable prior to the intro of the independent variable manipulation - can be costly and time-consuming |
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3 steps of Matched Pairs Design |
(1) Obtain measure of the matching variable from each individual (2) Form matched pairs that are approx. equal on the characteristics (3) One member from each pair is to participate in one of the two conditions in the experiment |