Chapter 8 Bivariate Correlational Research

Question 1

3 goals of the scientific approach!!!

Answer 1

describe
predict
explain

Question 2

3 big types of research designs

Answer 2

descriptive, correlational, experimental

Question 3

examples of descriptive studies

Answer 3

surveys, nat. obs., case studies

Question 4

examples of correlational studies

Answer 4

questionnaires, interviews, observational measures

Question 5

each research design is associated w/ which scientific goal?

Answer 5

descriptive/describe
correlational/predict
experimental/explain

Question 6

bivariate correlation

Answer 6

association involving exactly 2 variables

Question 7

main difference b/w quantitative and categorical variables

Answer 7

categorical numerical values are arbitrary, and quantitative numerical values are somewhat ordered (less to more, lower to higher, etc)

Question 8

2 types of quantitative variables

Answer 8

discrete: no decimals (ex: # of books)
continuous: unlimited number of values b/w adjacent values (ex: reaction time of 1.37 seconds)

Question 9

3 types of correlational coefficients and when they’re used

Answer 9

Pearson’s r: 2 variables at ratio/interval level
Spearman’s rank-order r: 2 variables at the ordinal level
Point-biserial r: 1 variable w/ 2 categories and 1 continuous variable

Question 10

what tools are useful when the IV is categorical and the DV is quantitative?

Answer 10

bar graphs, mean, t-test

Question 11

effect size

Answer 11

magnitude or strength of a relationship b/w 2 or more variables

Question 12

which effect size is usually more important, large or small?

Answer 12

large. more accurate predictions

Question 13

R-squared

Answer 13

proportion of variance shared by 2(+) variables

Question 14

what does a narrower CI indicate?

Answer 14

the more precise the point estimate may be

Question 15

sample size in terms of stability

Answer 15

a larger sample size gives a more stable estimate of effect size than a small sample size

Question 16

p-value

Answer 16

likelihood that the association is due/not due to chance

Question 17

p < 0.5

Answer 17

significant, unlikely that the association is due to chance

Question 18

p = 0.5 or p > 0.5

Answer 18

not significant, likely due to chance

Question 19

is a p value a correlation coefficient?

Answer 19

no

Question 20

when the 95% CI does not include zero

Answer 20

p<0.5 and the correlation in the sample is unlikely to have come from a population where the corr. is 0

Question 21

when the 95% CI includes zero

Answer 21

p>0.5 but we still can’t rule out that the true population corr is zero

Question 22

what effect size is more likely to be statistically significant?

Answer 22

larger/moderate

Question 23

a very small effect size might be statistically significant for what?

Answer 23

large sample

Question 24

what does replication test?

Answer 24

consistency

Question 25

define outlier

Answer 25

a score/point on the graph that is highly deviant from the rest of the data

Question 26

online vs offline outliers effect on correlation

Answer 26

online: inflate coefficient
offline: reduce coefficient

Question 27

which samples are the most affected by outliers?

Answer 27

small samples

Question 28

2 ways to detect outliers

Answer 28

1. 3 SDs away from the mean
2. median absolute deviation

Question 29

2 ways to handle outliers

Answer 29

1. remove from dataset before inferential statistical analysis
2. keep in dataset and recode w values equal to that of 3SDs from the mean

Question 30

restricted range

Answer 30

when the sample under the study doesn’t include the full range of variables

Question 31

what does it mean if a sample is homogenous?

Answer 31

the values of the sample are all pretty similar (creates a restricted range)

Question 32

curvilinear association

Answer 32

the relationship b/w 2 variables is not a straight line and r=0. U shaped curve

Question 33

3 criteria for causation

Answer 33

covariance
temporal precedence
internal validity

Question 34

the 3rd variable must be associated with what to be considered a potential alternative explanation?

Answer 34

both variables

Question 35

spurious association

Answer 35

the apparent correlation b/w X and Y is actually caused by Z

Question 36

moderation can address which validity?

Answer 36

external

Question 37

moderation

Answer 37

the strength/direction of an association b/w A and B differs depending on the level of C (moderator)