Chapter 22

Question 1

Element

Answer 1

Is the entity on which data Are collected

Question 2

Target population

Answer 2

The population we ideally want to make inferences about

Question 3

Sampled population

Answer 3

The population from which the sample is actually selected

Question 4

Sampling units

Answer 4

Before sampling, the population must be divided into sampling units. Could be the elements or groups of elements

Question 5

Frame

Answer 5

A list of the sampling units for a particularly study is called a frame

Question 6

Non probabilistic sampling

Answer 6

When the sampling method does not contain known probabilities for each possible sample

Question 7

Convenience sampling

Answer 7

The units included in the sample are chosen on the grounds of accessibility

Question 8

Judgment sampling

Answer 8

A person knowledgeable on the subject of the study select sampling units that feels representative

Question 9

Sampling error

Answer 9

The magnitude of the difference between a point estimate, calculated with the sample using an unbiased point estimator, and the population parameter being estimated. Occurs because not every element in the population is surveyed

Question 10

Non sampling error

Answer 10

Ex> measurement errors, interviewer error, processing error

Question 11

Simple random sampling

Answer 11

A simple random sample of size n from a finite population of size N is a sample selected such that every possible sample of size n has the same probability of being selected.
1. Construct a farm or list of all elements in the sampled population
2. Then a selection procedure, based on the use of random numbers, is used to ensure that each element in the sample population has the same probability of being selected,

Question 12

Stratified random sampling

Answer 12

1. The population divided into H groups, called strata
2. Then from stratum h a simple random sample size of nh is selected
3. The data from the H simple random samples are combined to develop an estimate of a population parameter such as the population mean, total or proportion

If the variability within each stratum is smaller than the variability between the strata, a stratified random sample can lead to greater precision.

Question 13

Cluster sampling

Answer 13

1. The population is divided into N groups of elements called clusters, such that each element in the population belongs to one and only one cluster
2. From the clusters a sample of size n is taken, if we collect all the data for this entire sample n we use a single stage cluster sampling
   If we select a simple random sample from the sample of size n we use a two stage cluster sampling.
   Differences cluster and stratified sampling ? Cluster sampling provides better results when the elements within the clusters are heterogeneous, not alike, whereas stratified works well when the elements within each stratum are homogenous, alike

Question 14

Systematic sampling

Answer 14

Often used as an alternative to simple random sampling when the populations are large, can be time consuming. There offers systematic an alternative to simple random sampling where ex sample size of 50 from a population containing 5000 elements we might sample one element for every 5000 dividerat med 50 which would give us a sample coataining the 100 th element, the next 100th element and so one