Stats Final

Front 1

Data

Back 1

collections of observations (such as measurements, genders, survey responses)

Front 2

Statistics

Back 2

the science of planning studies and experiments, obtaining data, and then organizing,
summarizing, presenting, analyzing, interpreting, and drawing conclusions based on data

Front 3

Population

Back 3

the complete collection of all individuals (scores, people, measurements, and so
on) to be studied

Front 4

census

Back 4

the collection of data from every member of the population

Front 5

sample

Back 5

a subcollection of members selected from a population

Front 6

parameter

Back 6

a numerical measurement describing some characteristic of a population

Front 7

statistic

Back 7

a numerical measurement describing some characteristic of a sample

Front 8

Quantitative (or numerical) data

Back 8

consists of numbers representing counts of measurements

Front 9

Categorical (or qualitative or attribute) data

Back 9

consist of names or labels that are not numbers
representing counts or measurements

Front 10

Discrete data

Back 10

when the number of possible values is either a nite number of a "countable"
number

Front 11

Continuous (numerical) data

Back 11

innitely many possible values that correspond to some
continuous scale that covers a range of values without gaps, interruptions, or jumps

Front 12

voluntary response sample

Back 12

when the respondents themselves decide to be included or not

Front 13

correlation

Back 13

when two variables have a relationship towards each other (do not assume causality)

Front 14

self-interest study

Back 14

when a company finances a study in favor for their own benefit

Front 15

observational study

Back 15

observe the study but do nothing to test it

Front 16

Continuous (numerical) data

Back 16

innitely many possible values that correspond to some
continuous scale that covers a range of values without gaps, interruptions, or jumps

Front 17

voluntary response sample

Back 17

when the respondents themselves decide to be included or not

Front 18

correlation

Back 18

when two variables have a relationship towards each other (do not assume causality)

Front 19

experiment

Back 19

apply some treatment and then proceed to observe its eects on the subjects

Front 20

self-interest study

Back 20

when a company finances a study in favor for their own benefit

Front 21

simple random sample

Back 21

n subjects is selected in such a way that every possible sample of the same size has the same chance of being chosen

Front 22

observational study

Back 22

observe the study but do nothing to test it

Front 23

random sample

Back 23

members from the population are selected in such a way that each individual member in the population has an equal chance of being selected

Front 24

experiment

Back 24

apply some treatment and then proceed to observe its eects on the subjects

Front 25

simple random sample

Back 25

n subjects is selected in such a way that every possible sample of the same size has the same chance of being chosen

Front 26

probability sample

Back 26

selecting members from a population in such a way that each member of the population has a known (but not necessarily the same) chance of being selected

Front 27

random sample

Back 27

members from the population are selected in such a way that each individual member in the population has an equal chance of being selected

Front 28

systematic sampling

Back 28

select some starting point and then select every kth (such as every 50th) element in the population

Front 29

probability sample

Back 29

selecting members from a population in such a way that each member of the population has a known (but not necessarily the same) chance of being selected

Front 30

systematic sampling

Back 30

select some starting point and then select every kth (such as every 50th) element in the population

Front 31

stratified sampling

Back 31

subdivide the population into at least two dierent subgroups (or
strata) so that subjects within the same subgroup share the same characteristics (such as gender or age bracket), then we draw a sample from each subgroup (or stratum)

Front 32

cluster sampling

Back 32

First divide the population area into sections (or clusters), then randomly selected some of those clusters, and then choose all the members from those selected clusters