week 10: variance + inferential statistics

Question 1

what does an experiment ask?

Answer 1

does variation in the IV cause variation in the DV

Question 2

how do we combat sources of variability?

Answer 2

isolating the effects of the IV

Question 3

example of isolating effects of independent variable

Answer 3

when measuring the effect of diversity training on implicit racial bias, we do not care about effect of being younger vs older or scale of caring.

Question 4

what are sources of variability in this example?

Answer 4

different values of diversity
differences in age
differences in mood
differences in SES
chance factors

Question 5

what is systematic variance?

Answer 5

variability caused by manipulating the IV (anti-bias diversity training)

Question 6

what is error variance?

Answer 6

variability caused by everything else

Question 7

what are examples of error variance?

Answer 7

• individual differences
  -random factors
  -misunderstood instructions
  -unexpected events
  -experimenter/equipment errors

Question 8

what makes up inferential statistics?

Answer 8

systematic variance + error variance = total variance

Question 9

what is total variance?

Answer 9

total variability in the DV caused by all factors

Question 10

what are ways of dealing with potential confounds?

Answer 10

avoid them !!
turn it into a control variable

Question 11

what is a control variable?

Answer 11

a factor that is fixed throughout the experiment

Question 12

if it cant vary then it cant introduce variability in the DV

Question 13

what is a control variable that be use in the diversity experiment?

Answer 13

age group, comparing 40+ and less than 40

Question 14

what is a drawback of too much control?

Answer 14

limited generalizability if the findings

Question 15

make the potential confound a…

Answer 15

random variable

Question 16

what is a random variable?

Answer 16

a factor that varies randomly and unsystematically throughout

Question 17

if we can ensure that it varies randomly, it will contribute to….

Answer 17

error variance

Question 18

inferential statistics asks

Answer 18

are differences “significantly different”

Question 19

what determines statistical significance?

Answer 19

1. magnitude of difference, that is due to systematic difference
2. variability within groups

Question 20

statistical significance increases with ……..
and decreases with ……….

Answer 20

1. mean difference
2. variability

Question 21

what are methods to measure statistical significance and what does it measure?

Answer 21

t test, measures if there is a significant difference between the means of 2 groups and how they are related

Question 22

I t I > 1.96 ->

Answer 22

statistically significant

Question 23

determining statistical significance is a probabilistic judgment

Question 24

what is the significance p= .05

Answer 24

alpha criterion, normal threshold in psychology.
if p value is less than .05 than mean difference is statistically significant

Question 25

what is type I error?

Answer 25

false positive

Question 26

replication is important

Question 27

what is type II error

Answer 27

false negative

Question 28

IV with two “levels”

1. Anti-bias diversity training condition
   2.No training condition (control condition)

Question 29

what is the yerkes-dodson curve

Answer 29

it proposes that you reach your peak level of performance with an intermediate level of stress, or arousal

Question 30

what is a ceiling effect?

Answer 30

extreme high values

Question 31

what is floor effect

Answer 31

extremely low values

Question 32

how to avoid ceiling and floor effects?

Answer 32

• pilot studies
• multiple IV levels
• noticeable difference in IV levels