U2: Foundations: Methods and Approaches

Question 1

experiment

Answer 1

investigation trying to understand relations of cause and effect

Question 2

independent variable

Answer 2

manipulated variable

Question 3

dependent variable

Answer 3

measured variable

Question 4

control variable

Answer 4

variable that is constant

Question 5

representativeness

Answer 5

degree which sample accurately reflects the population

Question 6

sampling bias

Answer 6

bias that occurs when choosing sample

types: bias of selection, self-selection bias, prescreening/advertising bias, healthy user bias

Question 7

bias of selection

Answer 7

unrepresentative selection, occurs when people are selected in a physical space

Question 8

self-selection bias

Answer 8

when subjects have some control over whether they participate

Question 9

pre-screening/advertising bias

Answer 9

how volunteers are screen/when advertising is placed skewing the sample (i.e. “stop smoking treatment” add, leads to you getting people who are motivated even without the treatment)

Question 10

healthy user bias

Answer 10

when study populations is in better shape than the general population

Question 11

single-blind design

Answer 11

subjects don’t know if they’re in experimental or control group

Question 12

double-blind design

Answer 12

neither subjects nor researchers know if the latter is in the experimental or control group

Question 13

placebo

Answer 13

sugar pill, used to trick control group to thinking they’re getting the treatment

Question 14

correlation research

Answer 14

assessing the degree of association between two or more variables

Question 15

confounding variable/third variable/extraneous variable

Answer 15

unknown factor that plays a role

Question 16

longitudinal study

Answer 16

correlation study, study over a long period of time with the same subjects

Question 17

cross-sectional study

Answer 17

correlational study, testing a wide variety of subjects from different backgrounds to increase generalizability

Question 18

case studies

Answer 18

clinical research, study of single individual to allow for general conclusions about other cases

Question 19

survey

Answer 19

used for correlation research, way to accumulate data through questionares/interviews

Question 20

conceptual definition

Answer 20

theory or issue being studied

Question 21

operational definition

Answer 21

the way a theory/issue will be directly observed/measured in the study, has to be internally and externally valid

Question 22

internal validity

Answer 22

certainty with which the result of an experiment can be attributed to manipulation of the independent variable and not other extraneous variables

Question 23

external validity

Answer 23

extent to which findings can be generalized to other contexts

Question 24

naturalistic observation

Answer 24

observation of subjects in natural setting, outside of a lab

Question 25

descriptive statistics

Answer 25

summarize data

Question 26

inferential statistics

Answer 26

testing hypotheses about data and determining how confident to be about inferences about the data

Question 27

central tendency

Answer 27

descriptive statistics, characterizes the typical value in a set of data

Question 28

positive skew

Answer 28

most values are on lower end, some are larger values

Question 29

negative skew

Answer 29

most values on higher end, some are lower values

Question 30

standard deviation

Answer 30

average dispersion of numbers around the mean

in typical distribution, 68% of all scores are within one standard deviation and 95% are within two standard deviations

Question 31

pearson correlation coefficient

Answer 31

describes the linear relationship between two attributed
scale of -1, 0, 1 
1 = perfect positive correlation 
-1 = perfect negative correlation
0 = attributes are not related

Question 32

positive correlation

Answer 32

as X increases, Y increases

Question 33

negative correlation

Answer 33

as X increases, Y decreases

Question 34

sample size

Answer 34

N or n
number of observations or individuals measured
the larger the sample size the more accurate it will be to the general population

Question 35

null hypothesis

Answer 35

a treatment had no effect in an experiment

inferential statistics will allow possibility of rejecting null hypothesis with known level of confidence

Question 36

alternative hypothesis

Answer 36

a treatment had an effect

Question 37

alpha

Answer 37

the accepted probability that a result of an experiment can be attributed to chance rather than manipulation of the independent variable
this is always possible so alpha is usually set to 0.05 – which means that experiment’s results are statistically significant if probability of the results happening by chance in less than 5%

Question 38

type I error

Answer 38

false positive, conclusion that a difference exists when it actually doesn’t

Question 39

type II error

Answer 39

false negative, conclusion that there is no difference when there actually is a difference

Question 40

p-value

Answer 40

probability of making a type I error, indicates that results are statistically significant (not only due to chance)

Question 41

deception

Answer 41

used only if informing participants of nature of experiment might bias results

Question 42

stanley milgram

Answer 42

obedience experiment, convinced people they were administering painful electric shock to other participants (who knew the true nature of the experiment)

Question 43

confederates

Answer 43

people who pretend to be participants but actually know the nature of the study

Question 44

institutional review boards (IRBs)

Answer 44

assess research plans before approval to make sure it meets ethical standards

Question 45

ethical standards

Answer 45

• informed consent: participants must give consent and can leave the study at any time
• debriefing: after study is done. participants must be told the exact purpose of their participation
• confidentiality