Stats

Question 1

statistics

Answer 1

the science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions. Stats also provides a measure of confidence in conclusions

Question 2

population

Answer 2

the entire group being studied

Question 3

individual

Answer 3

a member of the population

Question 4

sample

Answer 4

a subset of the population (a group of individuals)

Question 5

statistic

Answer 5

numerical characteristic (summary) of a sample

Question 6

inferential statistics

Answer 6

uses the sample to draw conclusions about the population

Question 7

parameter

Answer 7

numerical characteristic (summary) of the population

Question 8

Process of statistics

Answer 8

1. Identify the research objective
2. Collect data to meet the objective/answer the question
3. describe/analyze data
4. perform inference

Question 9

Types of variables

Answer 9

qualitative and quantitative

Question 10

quantitative

Answer 10

numerical (discrete or continuous)

Question 11

qualitative

Answer 11

categorical

Question 12

discrete

Answer 12

finish # of values, usually a count

Question 13

continuous

Answer 13

infinite # of values over an interval, usually as measurement

Question 14

nominal

Answer 14

naming only, no ranking (QL)

Question 15

ordinal

Answer 15

nominal and order (ranking, QL)

Question 16

Interval

Answer 16

ordinal and subtraction meaningful (QN)

Question 17

Ratio

Answer 17

interval and division meaningful (QN)

Question 18

Observational study

Answer 18

observation ONLY. No attempt to influence or change the explanatory or response variables. No causation can be established; association is the strongest possible statement

Question 19

lurking variable

Answer 19

an unmonitored variable that affects the response variable and may be related to the explanatory variable

Question 20

confounding variable

Answer 20

a monitored variable that affects the response so that the effect (change in response) can’t be solely attributed to the explanatory variable

Question 21

designed experiment

Answer 21

treatment is actively imposed. Explanatory variable value is intentionally changed to see if the response variable is also changed. Causation can be established

Question 22

cross-sectional

Answer 22

observational study; data from a point in time

Question 23

case-control

Answer 23

retrospective - looking back at what happened/recorded data in the past. can be inaccurate

Question 24

cohort

Answer 24

identify group, observe over a long period of time

Question 25

prospective

Answer 25

into the future

Question 26

census

Answer 26

all individuals in the population with data

Question 27

random sample

Answer 27

a sample of the population obtained using a chance process

Question 28

convenience sample

Answer 28

using readily available individuals of the population for the sample. Worthless, because a convenience sample will never represent the population accurately

Question 29

simple random sample (SRS)

Answer 29

every sample of size n from a population of size N has an equally likely probability of being selected

Question 30

frame

Answer 30

a list of all the individuals in the population

Question 31

SRS order

Answer 31

1. assign a number ___1 to N to each individual in the population 2. use the random number table (RNT) or StatCrunch to obtain values 3. provide the SRS in context

Question 32

stratified random

Answer 32

all individuals in a strata share 1 common characteristc. Separate the population subjectively by strata, then take an SRS from each strata. Combine the SRS's for the stratified random sample

Question 33

systematic random

Answer 33

select every kth individual from the population (k=pop. size/sample size=N/n, round down, randomly selects an integer between 1 and k; call it p. The systematic random sample is p, p+k, p+2k..., p+(n-1)k

Question 34

cluster sample

Answer 34

generally, each cluster is similar to the population. Randomly selects 1 cluster. The individuals in that cluster are the sample

Question 35

bias

Answer 35

systematic over-representation of response/groups

Question 36

bias in sampling

Answer 36

over-representation of a group, convenience, undercover age(incomplete frame)

Question 37

bias in nonresponse

Answer 37

individuals selected for the sample don't respond or cant be contacted

Question 38

bias in response

Answer 38

inaccurate answers from individuals in the sample (interviewer error, misrepresentation, wording of questions leading or too vague, ordering of questions/words, type of question, data entry error)

Question 39

nonsampling error

Answer 39

result from under coverage, nonresponse bias, response bias, or data-entry error

Question 40

sampling error

Answer 40

using a sample (statistic) to estimate a population (parameter)

Question 41

experiment

Answer 41

controlled study with actively imposed treatment. Modify explanatory variable(s) values and look for a change in response variable values

Question 42

experimental unit

Answer 42

gets treatment (subjects if people)

Question 43

control group

Answer 43

gets no treatment or the placebo. used for comparison to treatment groups

Question 44

single-blind

Answer 44

subject does not know what treatment they are getting

Question 45

double-blind

Answer 45

single blind and researchers in contact with subject don't know what treatment the subject is getting

Question 46

completely randomized experimental design

Answer 46

experimental units are randomly assigned to treatment groups. Random assignment removes bias, ensures the equivalence of the groups before treatment, and is necessary for establishing cause and effect

Question 47

matched pairs

Answer 47

think twins/ordered pairs, only 2 treatments