Explain the difference between a stratified sample and a cluster sample. (Select all that apply.)

(1) In a cluster sample, every sample of size n has an equal chance of being included.

(2) In a stratified sample, every sample of size n has an equal chance of being included.

(3) In a stratified sample, the clusters to be included are selected at random and then all members of each selected cluster are included.

(4) In a cluster sample, random samples from each strata are included.

(5) In a cluster sample, the clusters to be included are selected at random and then all members of each selected cluster are included.

(6) In a cluster sample, the only samples possible are those including every kth item from the random starting position.

(7) In a stratified sample, random samples from each strata are included.

(8) In a stratified sample, the only samples possible are those including every kth item from the random starting position.

Explain the difference between a stratified sample and a cluster sample. (Select all that apply.)

(1) In a cluster sample, every sample of size n has an equal chance of being included.

(2) In a stratified sample, every sample of size n has an equal chance of being included.

(3) In a stratified sample, the clusters to be included are selected at random and then all members of each selected cluster are included.

(4) In a cluster sample, random samples from each strata are included.

(5) In a cluster sample, the clusters to be included are selected at random and then all members of each selected cluster are included.

(6) In a cluster sample, the only samples possible are those including every kth item from the random starting position.

(7) In a stratified sample, random samples from each strata are included.

(8) In a stratified sample, the only samples possible are those including every kth item from the random starting position.