Statistical Sciences 2244A/B Midterm: midterm 1 Review

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tanwolf659

6 Mar 2017

School

Western University

Department

Statistical Sciences

Course

Statistical Sciences 2244A/B

Professor

Jennifer Waugh

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Document Summary

Difference between sample statistic and true population parameter. Not a problem/mistake it"s predictable because no bias. Each member of the population has an equal chance of being selected. Simple random sample: each possible sample of a required size (n) has an equal chance at being selected. Strati ed sampling: population split into 2+ strata (based on pre-existing knowledge) then random sample from that, this is only random if strata are sampled proportionately. Cluster sampling: population is divided into regions, then random sample of regions (multiple clusters chosen, when a cluster is chosen, everyone in that cluster is therefore chosen, each cluster has the same chance of being selected. Systematic sampling: a starting point is randomly selected, and then units are sampled at a constant interval. Under-coverage: when some people are left out of the population (ex. they don"t have a telephone) Non-response: couldn"t be contacted or refused to answer.

Related Questions

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.

redrabbit701

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

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

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

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

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

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

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

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

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

grayotter535

Statistical Sciences 2244A/B Midterm: midterm 1 Review

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