Ch10

Question 1

control variable

Answer 1

Control variable: any variable that an experimenter holds constant

Question 2

how does an experiment establish covariance, how is it indicated?

Answer 2

Indicated by difference in group means

-If independent variables don’t have different levels, then covariance can’t be established

-Covariance is also related to the outcome variable- if conditions are the same, the study will find no covariance, because the outcome didn’t vary based on the level

Question 3

Comparison group (comparison condition)

Answer 3

provides a comparison for the outcome of interest,
- If independent variables don’t have different levels, then covariance can’t be established

Question 4

control group

Answer 4

Control group (no treatment condition): the neutral group, level of the independent variable that doesn’t receive any treatment

Question 5

treatment group

Answer 5

receive treatment condition/ manipulation

Question 6

Placebo group (placebo control group, expectancy condition):

Answer 6

Placebo group (placebo control group, expectancy condition): If control group is given an inert treatment

Question 7

design confounds

Answer 7

Design confounds: when a second variable varies systematically along with the intended independent variable, acts as alt info for the results

Question 8

systematic variability

Answer 8

Systematic variability: when the second variable effects only one group
- confound

Question 9

Unsystematic variability

Answer 9

random or haphazard, effects both groups, not a confound

• Can make it difficult to detect differences in your dependent variable

Question 10

selection effects

Answer 10

Selection effects: occurs when kinds of participants in one level of the independent variable are systematically different from the participants in the other level(s)

• Can happen when experimenters let participants choose level (self-selected)

-Or if experimenters assign one type of person to a particular condition

Question 11

Matched groups (matching, matched subjects design):

Answer 11

first measure participants on a variable that may affect the dependent variable, then match participants in pairs, then randomly assign one of them to each condition

-Prevents selection effects

Question 12

Independent-groups design (between-subjects design, between-groups design):

Answer 12

different groups of participants placed into different levels of the independent variable

Question 13

types of Ind-groups design

Answer 13

• Posttest-only design
• pretest/posttest design

Question 14

Posttest-only design (equivalent groups posttest design)

Answer 14

participants are randomly assigned to independent variable groups thus rendering the groups equivalent, and are tested on the dependent variable once, after the manipulation occurs

Question 15

pretest/posttest design (equivalent groups pretest/posttest design)

Answer 15

pretest/posttest design (equivalent groups pretest/posttest design): participants are randomly assigned, are tested on dependent variable twice- before and after exposure to independent variable

Question 16

which kindof ind. groups design can show if there aren’t selection effects

Answer 16

pre/post Shows there’s no selection effect if the pretest results are equal/similar

Question 17

Within groups design (within-subjects design, repeated measures design):

Answer 17

only one group of participants, each person presented with all levels of the independent variable

Question 18

Types of within-group design

Answer 18

• Concurrent measures design
• repeated measures design

Question 19

Concurrent measures design

Answer 19

type of w/in groups where participants exposed to all levels of independent variable at same time and a single preference is the dependent variable

Question 20

Repeated measures design

Answer 20

type of w/in groups where participants are measured on a dependent variable after exposure to each level of the independent variable

Question 21

pros of w/in groups

Answer 21

• participant “acts as their own control”
• Gives researchers more power to notice differences between conditions
• fewer participants

Question 22

power

Answer 22

probability that a study will show statistically significant result when an independent variable truly has an effect in the population

• Reduces unsystematic variability (noise) that may obscure the actual effect.

Question 23

order effects

Answer 23

being exposed to one condition effects how participants respond to other conditions
- threat to w/in groups design

Question 24

types of order effects

Answer 24

• Practice effects (fatigue effects): long sequence may lead participants to get better at a task, or tired/bored
• Carryover effects: contamination from one condition/level to next

Question 25

counterbalancing

Answer 25

randomly assign order of experiencing the different levels

• helps avoid order effects

Question 26

types of counterbalancing

Answer 26

• Full counterbalancing: all possible condition orders are represented
• Partial counterbalancing: only some condition orders are represented,
  • latin square

Question 27

Demand characteristics

Answer 27

Demand characteristics (experimental design): participants pick up on cues that lead them to guess an experiment’s hypothesis

Question 28

Manipulation check:

Answer 28

an extra dependent variable that researchers insert to determine if the experimental manipulation worked

• Used often when intention is to make participants think or feel some way (ex: making jokes to manipulate amusement, + a rating on how funny the jokes were)

Question 29

pilot study

Answer 29

Pilot study: simple study using separate group completed either before or sometimes after conducting primary interest study

Question 30

pro of experimenting on homogenous group

Answer 30

Running an experiment on a non-diverse (homogenous) sample lessens the chance of unsystematic variability from obscuring the results of the independent variable

Question 31

coen’s d + what does it show

Answer 31

used in experiments instead of r

• d shows the groups differences of the results on the dependent variable
• Shows difference in groups means AND how much the scores overlap (std. deviation)

-Strengths of d
0.20 = small/weak
0.50 = medium/moderate
0.80 = large/strong

Question 32

threats

Answer 32

• Any (design) confounds? Did another variable accidentally covary?
• in an independent-groups design: control for selection effects using random assignment or matching
• In within-groups design: control for order effects using counterbalancing