unit 2 lecture 2

Question 1

Case studies

Answer 1

in depth reports about specific cases

Question 2

in depth reports about specific cases

Answer 2

Case studies

Question 3

Naturalistic observations

Answer 3

observing participants in real world contexts and taking a record of their behaviour

Question 4

observing participants in real world contexts and taking a record of their behaviour

Answer 4

Naturalistic observations

Question 5

Surveys/questionnaires

Answer 5

involves having individuals provide answers to a series of questions

Question 6

involves having individuals provide answers to a series of questions

Answer 6

Surveys/questionnaires

Question 7

Correlational research

Answer 7

provides a measure of the degree of association between two variables

Question 8

Positive correlation

Answer 8

when higher values on one variable tend to co-occur with lower values on another
Positive correlations generate correlation co efficients of 0-1.00
Negative correlations generate correlation co efficients of 0- -1.00
Strong correlations between variables (whether positive or negative) do not mean that there is a causal relationship between the two variables

Question 9

Casual direction problem

Answer 9

example: does curly cause fun or fun cause curlier hair

Question 10

example: does curly cause fun or fun cause curlier hair

Answer 10

Casual direction problem

Question 11

The third variable problem

Answer 11

potential variable that causes both curlier hair and more fun

Question 12

potential variable that causes both curlier hair and more fun

Answer 12

The third variable problem

Question 13

Experiments

Answer 13

– uniquely designed to provide answers about the casual relationships between variables… they have this advantage because they involve direct manipulation of one or more variables

Question 14

Random assignment

Answer 14

to experimental conditions (curled vs not curled) helps to ensure that participants in the two groups are roughly equal on all other important characteristics

Question 15

Confounding variables

Answer 15

– variables that differ between experimental conditions other than the one that the experimenter seeks to manipulate (bad to have these in experiment)

Question 16

– variables that differ between experimental conditions other than the one that the experimenter seeks to manipulate (bad to have these in experiment)

Answer 16

Confounding variables

Question 17

Independent variables

Answer 17

variable(s) being manipulated in an experiment

Question 18

variable(s) being manipulated in an experiment

Answer 18

Independent variables

Question 19

Dependant variable(

Answer 19

being measured in an experiment

Question 20

being measured in an experiment

Answer 20

Dependant variable(

Question 21

Experimental conditions

Answer 21

the one involving some active treatment such as administration of a drug, providing some sort of therapy or curling their hair

Question 22

the one involving some active treatment such as administration of a drug, providing some sort of therapy or curling their hair

Answer 22

Experimental conditions

Question 23

Control condition –

Answer 23

the one involving no active treatment but that is used as a basis for comparison such as administration of a placebo, giving them some sham type of therapy or playing with their hair without curling it

Question 24

the one involving no active treatment but that is used as a basis for comparison such as administration of a placebo, giving them some sham type of therapy or playing with their hair without curling it

Answer 24

Control condition –

Question 25

Between-subjects design

Answer 25

when different people participate in different conditions of an experiment

Question 26

when different people participate in different conditions of an experiment

Answer 26

Between-subjects design

Question 27

Within-subjects design

Answer 27

when the same people each participate in all conditions of an experiment

Question 28

when the same people each participate in all conditions of an experiment

Answer 28

Within-subjects design

Question 29

Descriptive statistics

Answer 29

summarize data)

Question 30

inferential statistics

Answer 30

draw conclusions

Question 31

Mean

Answer 31

the arithmetic average a group of scores

Question 32

the arithmetic average a group of scores

Answer 32

Mean

Question 33

median

Answer 33

– the middle highest value in a group of scores

Question 34

– the middle highest value in a group of scores

Answer 34

median

Question 35

mode

Answer 35

most common value in a group of scores

Question 36

most common value in a group of scores

Answer 36

mode

Question 37

Standard deviation

Answer 37

higher standard deviations reflect scores that are more dispersed further away from the mean score

Question 38

higher standard deviations reflect scores that are more dispersed further away from the mean score

Answer 38

Standard deviation

Question 39

The main purpose of inferential statistics is

Answer 39

statistical hypothesis testing

Question 40

To be statistically significant

Answer 40

a difference between conditions or a correlation between variables must be substantially greater than the standard deviation of scores

The same difference in sores may or may not be statistically significant depending on the standard deviation