Chapter 8 Flashcards

1
Q

How are all other variables controlled in experimental method

A

Experiment control

Randomization

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2
Q

Confounding variable

A

Variable that varies along with the independent variable

It occurs when efffects of independent variable and an uncontrolled variable are intertwined so you cannot determine which of the variables is responsible for the observed effect

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3
Q

When the results of an experiment can confidently be attributed to the effect of the independent variable, the experiment is said to have…

A

Internal validity

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4
Q

How does one achieve good internal validity?

A

Researcher myst design and conduct the experiment so that only the independent variable can be the cause of the results

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5
Q

A researcher using a Posttest only design must..:

A

Obtain two equivalent groups of participants

Introduce the independent variable
Measure the effect of the independent variable on the dependent variable

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6
Q

Why must pisttest only design use two EQUIVALENT groups?

A

To eliminate any selectional differences

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7
Q

Selection differences

A

Differences in the type of subjects who make up each group in an experimental design

This situation occurs when participants elect which group they are to be assigned to

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8
Q

Difference between pretext only design and pretext post test

A

In protest post test, a pretext is given before the experimental manipulation is introduced

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9
Q

Why in pretext posttest, is pretext given before manipulation

A

Makes it possible to ascertain that groups were infact equivalent from the beginning

It is not always needed in a large sample of participants that has random assignment

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10
Q

drop out factor is caused

A

Attrition or mortality

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11
Q

Fallbacks of a pretest

A

It can sensitize participants to what you are studying, enabling them to figure out what you are studying and why

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12
Q

Solomon design

A

Half of participants receive only the post test and half receive both the pre test and the post test

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13
Q

Independent group design (also known as between subjects design)

A

When participants are randomly assigned to the various conditions so that the each participated in only ONE group

Comparisons are made between different groups of participants

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14
Q

Repeated measure design

A

Participants receive all conditions

When each participant is measured after receiving each level of the independent variable.

(Also called within subject design)

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15
Q

Random assignment

A

Decision to assign an individual to a particular condition is completely random and beyond the control of the researcher

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16
Q

Advantages of repeated measure design

A

Fewer research participants are needed because each individual participated in all conditions

They are extremely sensitive to finding statistical significant differences between group.

17
Q

Two ways to assign participants to a group

A

Indenpendent group design (only participated in one )

repeated measure design (participated in all)

18
Q

Advantages of pretest post test

A

Ensure consistency (aka experimental control)

Can help with subject selection criteria

Can determine change between pretest and post test

Can determine if attrition (aka mortality) affected results

19
Q

Pre test post test disadvantages

A

Demand characteristics (like filler ideas)

Time, money, effort, etc

20
Q

How to ensure equivalency between two groups

A

Random assignment

21
Q

Repeated measures design (ak within subjects) advantages

A

Fewer Ss needegreater statistical “sensitivity” by deducting random error

22
Q

Disadvantages of experimental design

A

Order effects

Counterbalancing

23
Q

Threats to internal validity highlighted by quasi experiment designs

A
History 
Maturation 
Testing 
Instrument decay 
Progression toward the mean 
Attrition or drop out
24
Q

Order effect

A

The order of presenting the treatments effect the dependent variable

25
Order effect and repeated measure design
A problem with repeated measure design stems from the fact that different conditions must be presented in a particular sequence Greater recall in the high meaningful condition can be attributed to the fact that the high meaningful task came second
26
Practice effect
Performance in the second task might improve merely because of practice gained on the first task
27
Fatigue effect
When research participant becomes tired, bored or distracted
28
Disadvantages of repeated measure design
Order effect Practice effect Fatigue effect Carryover effect
29
Carryover effect
When effect of first treatment carries over to influence the response of the second treatment Ex-after reading about less sever crime, the more severe crime might seem worse to participants than it normally would
30
Counterbalancing
When all possible orders of presentation is included in the experiment This helps with order effect
31
How to deal with order effect
Counterbalancing or Latin square Time interval between treatments
32
Latin actuate
A technique to control for order effects without having all possible orders Each condition appears at each ordinal position Each condition prefers and follows each condition one time
33
How to counteract fatigue effect
A rest period/time in between treatments
34
Repeated measure design over independent group advantages
A reduction in the number of participants is required to complete the experiment Greater control over participant differences and thus greater ability to detect an effect of tha independent variable
35
When can you not use repeated measure design
An experimental procedure that produces a realistically permanent change in an individual Ex-psychotherapy treatment or surgical procedure
36
Matched pair designs
Instead of randomly assigning participants to groups, people get matched on participant variable such as age or personality trait The variable will be strongly related to the dependent variable
37
What does a matched pair design ensure
That groups are equivalent prior to introduction of independent variable
38
When is matching most likely used
When there’s only a few participants available or there is a strong relationship between dependent measure and the matching variable