Task 8: Someone like you.

Question 1

What are the three basic types of experimental design?

Answer 1

1. Between-subjects design (different group randomly assigned to the levels of the ind. var.)
2. Within-subjects design ( a single group + all levels of treatment)
3. Single-subject design (similar to within subjects design, except you don’t average data across subjects)

Question 2

Error variance is the

Answer 2

variability among scores caused by variables other than your independent variables.

Question 3

Sources of error variance can be:

Answer 3

subject differences
environmental conditions
even the same subject cannot be exactly the same from moment to moment.

Question 4

Steps for reducing error variance:

Answer 4

• hold extraneous variables constant by treating subjects similarly
• same procedures for all subjects
• subjects matched on characteristics
• random assignments.

Question 5

With statistical analysis one can

Answer 5

estimate the probability with which error variance alone would produce differences between group. You can do this using inferential statistics.

Question 6

Inferential statistics is the process of

Answer 6

making predictions about the population based on a sample.

Question 7

If the probability (due to statistical analysis) of the effects of error variance is low enough, your results are said to be

Answer 7

statistically significant, from which you can conclude that your results are mostly due to manipulation of the independent variable and not error variance.

Question 8

The types of between-subjects designs are:

Answer 8

• Randomised two-group design
• Randomised multi-group design
• Matched-group design
• Matched pairs design
• Matched-multigroup design

Question 9

Randomised two-group design:

Answer 9

• two groups => expose them to different levels of treatment ;
• compare the two means => determine whether they differ ;
• simple statistical analysis ;
• assed the reliability of any difference.

also

• no pretesting necessary
• provides a limited amount of information about the effect of the independent variable.

Question 10

The randomised multi-group design:

Answer 10

• add as many levels of the independent variable as needed to test you hypothesis ;
• is used to expand the randomised two-group design
• multiple control group design => 2 or more experimental groups, does not have a control group.

Question 11

Parametric design =

Answer 11

manipulating your independent variable quantitively (mean)

Question 12

Nonparametric design =

Answer 12

manipulating your independent variable qualitatively (median), using a rather small sample.

Question 13

Matched-group design:

Answer 13

matched sets of subjects are distributed at random, one per group, into the groups of experiment => group the subjects whose characteristics match and distribute them randomly.

Question 14

Because of the matched-group design..

Answer 14

the effect of the characteristic on which the subjects were matched gets distributed evenly across the treatments => effect of the error variance has been minimised.

Question 15

Characteristics of matched group designs:

Answer 15

1. Control over subject variables ;
2. Simple to carry out (only two levels of your independent variable) ;
3. Requires pretesting ;
4. If the matched characteristic has a large effect = > more sensitive experiment ;
5. Larger subject pool.

Question 16

The matched-multigroup design involves

Answer 16

multiple levels of a single factor or multiple factors.

Question 17

In an experiment, a factor is the

Answer 17

independent variable (explanatory). Each factor can have multiple levels.

e.g. Dosage of Vitamin C = factor
0 mg - level 1
40 mg - level 2
100 mg - level 3

Question 18

Combinations of levels are called

Answer 18

treatments.

Question 19

Characteristics of within-subjects design

Answer 19

1. One group ;
2. Each subject is exposed to all levels of treatment ;
3. The researcher looks at changes in performance within each participant across treatments ;
4. Because the behaviour is measured independently => also called a repeated-measures design ;
5. No error variance ;
6. Fewer subjects ;
7. Demanding on subjects ;
8. Subject attrition (drop out)
9. Carryover effects.

Question 20

A carryover effect occurs when

Answer 20

the first treatment alters the behaviour observed in the subsequent treatment = effect that “carries over” from one experimental condition to another.

Question 21

Carryover effects can arise from:

Answer 21

1. Learning - subjects learn the treatment => better performance in a similar task ;
2. Fatigue - performance deteriorates ;
3. Habituation - stimuli more familiar => reduced responsiveness ;
4. Sensitisation - exposure to one stimulus => responds more strongly to another stimulus ;
5. Contrast - exposure to one condition => altered response in another ;
6. Adaptation - 1st result simply differs from last result.

Question 22

You can deal with carryover effects in three ways:

Answer 22

1- Counterbalancing
2- Taking steps to minimise carryover
3- Separate carryover effects from treatment effects.

Question 23

Counterbalancing happens when

Answer 23

you assign the various treatments of the experiments in different order for different subjects.

Question 24

Characteristics of complete counterbalancing:

Answer 24

1- provides every possible ordering of treatments ;
2- the minimum number of subjects = number of different orderings ;
3- small number of participants.

Question 25

Partial counterbalancing:

Answer 25

1- includes only some of the possible treatment orders ; 2- order is chosen randomly ; 3- each treatment appear equally in each position ; 4- Latin square design ensures that each treatment appears an equal number of times in each ordinal position.

Question 26

Counterbalancing may be ineffective when

Answer 26

we discover differential carryover effects (the magnitude of the carryover effects differs for orders of treatment presentation).

Question 27

Taking steps to minimise carryover:

Answer 27

- minimising carryover effects => reduced error variance + stronger design ; - not all sources can be minimised ; - in case of learning => retrain subjects before your experiment ; - adaptation and habituation => before introducing the treatment, allow subjects to adapt or habituate; - habituation, adaptation, fatigue => breaks between treatments.

Question 28

You can separate the carryover effect from the effect of your experimental treatment using..

Answer 28

factorial design.

Question 29

Using factorial design =>

Answer 29

two or more independent variables with two or more levels of treatment should affect the dependent variable separately.

Question 30

In a 3x4 factorial design we have:

Answer 30

two factors, where the first factor has three levels the second factor has 4 levels

Question 31

How many groups do we have in a 2x2 factorial design?

Answer 31

4

Question 32

Characteristics of factorial design:

Answer 32

- you can measure the size of any carryover effect ; - the result is a complex, demanding experiment ; - only practical with a small number of treatments.

Question 33

The single-factor two-level design:

Answer 33

- simplest form of within-subjects design ; - two levels of a single independent variable ; - all subjects receive both levels of the variable ; - half of the subjects = one order ; - other half of the subjects = opposite order ; - the scores within each treatment are averaged ; - the two means are compared.

Question 34

Single-factor multilevel design:

Answer 34

a single group of subjects is exposed to three or more levels of a single independent variable.