Producing Data

Question 1

observational study

Answer 1

observe individuals and measuring variables of interest but not attempting to influence the response

Question 2

experiment

Answer 2

deliberately imposing some treatment on individuals in order to observe their responses. An experiment can help eliminate (or at least try to minimize the effects of) lurking variables

Question 3

population

Answer 3

entire group of individuals we are interest in

Question 4

census

Answer 4

involves using every member of a population for an observational study

Question 5

sample

Answer 5

subgroup of population that is being studied

Question 6

sampling

Answer 6

studying a part in order to gain information about the whole

Question 7

sampling error/variability

Answer 7

natural variation one would expect to see in sample statistics from sample to sample

Question 8

voluntary response sample

Answer 8

people who choose to be part of a sample by responding to a general appeal (biased)

Question 9

convenience sample

Answer 9

choosing the most convenient individuals from the population for your sample (biased)

Question 10

Bias

Answer 10

occurs when the sampling method systematically favors certain outcomes

Question 11

simple random sample (srs)

Answer 11

a sample of size n is selected in such a way if every individual in the population has an equal chance of being selected and every subset of individuals has an equal chance of being selected for the sample (unbiased)

Question 12

stratified random sample

Answer 12

divide the population into groups of similar individuals called strata, choose a separate SRS from each stratum, and then combine all of those individuals chosen from all of the strata to make up the full sample (unbiased)

Question 13

cluster sample

Answer 13

divide the population into groups (or clusters), then randomly select some of these clusters (completely ignoring the others). All the individuals from chosen clusters are selected to be in the sample

Question 14

multistage sample design

Answer 14

select successively smaller groups within the population in stages, resulting in a sample consisting of clusters of individuals. Each stage may employ an SRS, or another type of sample

Question 15

systematic sample

Answer 15

sampling with a pattern (inspecting every fifth bag of potato chips coming off an assembly line)

Question 16

probability sample

Answer 16

each member of the population has a known chance (greater than zero) to be selected

Question 17

undercoverage

Answer 17

some groups in population are left out of process of choosing sample, population is not same group as sampling frame

Question 18

non response

Answer 18

an individual is chosen for the sample but cannot be contacted or refuses to cooperate

Question 19

response bias

Answer 19

individual in sample chooses an answer to a survey that they thinks is best rather than the answer that they truly believe

Question 20

wording of question

Answer 20

leading questions cause individual being questioned to choose one answer as opposed to another

Question 21

sampling frame

Answer 21

group from which sample is chosen

Question 22

what must you do before you trust a poll result?

Answer 22

insist on knowing the exact questions asked, the rate of nonresponse, and the date and method of survey

Question 23

are larger samples or smaller samples better? why?

Answer 23

larger random samples are better because they give more accurate results that smaller samples because they decrease variability

Question 24

experimental units

Answer 24

individuals on which the experiment is being done (if units are people they are called subjects)

Question 25

treatment

Answer 25

specific experimental condition applied to units. level of treatment is measured by explanatory variable and level of variable we're interested in is measured by response variable

Question 26

factors

Answer 26

the explanatory variables in an experiment (experiments may have several factors)

Question 27

3 basic principles of experimental design

Answer 27

control, randomization, replication (all three principles must be present to be considered a well-designed experiment)

Question 28

control

Answer 28

controlling the effect of lurking variables on the response variable

Question 29

control group

Answer 29

group in experiment not given treatment to compare to afterwards

Question 30

randomization

Answer 30

ensures that individuals are assigned to treatment groups by chance

Question 31

replication

Answer 31

each treatment applied to multiple experimental units (ensures that results are not just due to chance variation)

Question 32

randomized comparative experiment

Answer 32

an experiment with random assignment and a control/comparison group

Question 33

statistically significant

Answer 33

an observed effect too large to attribute plausibly to chance

Question 34

placebo effect

Answer 34

a subject receiving a placebo reacts favorably to it (even though there is no medicinal benefit in the pill, for example) this is a psychological response

Question 35

block

Answer 35

group of experimental units known before the experiment to be similar in some way that is expected to affect the response to treatments (homogeneous group)

Question 36

matched pairs design

Answer 36

special type of block design

Question 37

blind

Answer 37

subjects involved in study do not know which treatment they are receiving

Question 38

double-blind

Answer 38

neither the researchers (people measuring the response variable) or subjects know who is receiving which treatment but the experimenters (people running the experiment) are aware of who is given what

Question 39

lack of realism

Answer 39

most serious potential weakness of experiments

Question 40

quote about how to set up groups

Answer 40

"control what you can, block on what you can't control, and randomize the rest"

Question 41

matched pairs experiment

Answer 41

one of two set ups: 1. subjects matched with themselves and given two different treatments (in a random order). this is more commonly used form of matched pairs design 2. similar subjects matched and each assigned a different treatment