Stat Vocab.

Front 1

Population

Back 1

(Collection of all) individuals or items under consideration.

Front 2

Sample

Back 2

(That Part) of the (population)

Front 3

Descriptive Stats.

Back 3

(Methods) for (organizing & summerizing) info.

Front 4

Inferential Stats.

Back 4

Methods for (drawing) & (measuring) the reliability of (conclusions) about a population based on info obtained from a sample ofthe poulation.

Front 5

Observational study

Back 5

Observe characteristics & take measurements.

Front 6

Designed Experiments

Back 6

Imposed treatments & controls

Front 7

Simple Random sampling

Back 7

sampling for which ea. possible sample of (a given size is (equally likely to be the one obtained)

Front 8

Simple Random Sample

Back 8

Sample obtained by simple random sampling.

Front 9

Representative Sample

Back 9

Reflect as closely as possible the relevant characteristics of the population.

Front 10

Simple Random Sampling (with replacement)

Back 10

A member of the population can be slected more than once.

Front 11

Simple Random Sampling (without replacement)

Back 11

A memember of the population can be selected (at most once) or ARE NOT PUT BACK IN THE SAMPLE.

Front 12

Systematic Random Sampling

Back 12

STEP 1 (Divide) the (population size) by (sample size) & Round the results DOWN to the nearest whole number)

STEP 2 Use a random number table or a simular device to obtain a number k, between l & m.

STEP 3 Select for the sample those members of the population that are numbered k,k+m, k+2m.....

Front 13

Cluster Sampling

Back 13

Cluster sampling is esp. useful when the members of the population are (widely scattered)


STEP 1 DIVIDE the POPULATION into groups of (clusters).

STEP 2 Obtain a simple random sample random sample of (clusters).

STEP 3 (Use ALL the members) of the clusters obtained in step 2 as the sample.

Front 14

Homogeneous

Back 14

Composed of parts or elements that are of the same kind.

Front 15

Stratified Sampling

Back 15

Population is divided into (subpopulations) called strata and then sampling is done from ea. stratum.

Front 16

Stratified Random Sampling with Proportional Allocation.

Back 16

Step 1 Divide the population into subpopulations (strata).

Step 2. From ea. stratum obtain a simple random sample of size proportional to the size of the stratum: that is, the sample size for a stratum equales the (total sample size) times the stratum size (divided) by the population size.

STEP 3 Use (All) the memebers obtained in STEP 2 as the sample.

Front 17

Multistage Sampling

Back 17

Is frequently used frequently by (pollsters and government) agencies.

Front 18

Experimental Units; Subjects

Back 18

In a designed experiment, the individuals or items on which the experiment is preformed are called (experimental units). When the experimental units are humans,the term (subject) is often used in place of experimental unit.

Front 19

Prinicipals of Experimental Design.

CONTROL

Back 19

Two or more treatments should be compared.

Front 20

Prinicipals of Experimental Design.

RANDOMIZATION: Root word (Random)

Back 20

The experimental units should be randomly divided into groups to avoid (unintentional selection) bias in constituting the groups.

Front 21

Prinicipals of Experimental Design.

Repications: (Repeat)

Back 21

A sufficient number of experimental units should be used to ensure that randomization creates groups that that resemble each other closely & increase the chances of detecting any differences among the treatments.