Sampling Definitions

Definitions fro sampling

Population

A whole set of items that are of interest

Census

Observes or measures every member of a population

Sample

A subset of the population from which data is collected

Advantage of a census

Should give completely accurate results

3 disadvantages of a census

• Time consuming

• Cannot be used when the testing process destroys the item

• Hard to process a large quantity of data

3 advantages of a sample compared to a census

• Less time consuming and expensive than a census

• Fewer people have to respond

• Less data to process than in a census

2 disadvantages of a sample

Data may not be accurate enough, Sample may not be large enough to give information about small sub-groups of the population

Sample units

Individual units of a population

Samping frame

A list of sample units

What is a simple random sample of size n?

A sample where every sample of size n has an equal chance of being selected

In stratified sampling

Population is divided into mutually exclusive strata and a random sample is taken from each

In systematic sampling

Required elements are chosen at regular intervals form an ordered list

3 advantages of simple random sampling

Free of bias, Easy and cheap to implement for small populations and samples, Each sampling unit has known and equal chance of selection

2 disadvantages of simple random sampling

Not suitable when the population size or the sample size is large, A sampling frame is needed

2 advantages of systematic sampling

• Simple and quick to use

• Suitable for large samples and large populations

2 disadvantages of systematic sampling

A sampling frame is needed, It can introduce bias if the sampling frame is not random

2 advantages of stratified sampling

• Sample accurately reflects the population

• Guarantees proportional representation of groups within a population

2 disadvantages of stratified sampling

• Population must be clearly classified into distinct strata

• Selection within each stratum suffers from the same disadvantages as a simple random sampling

An example of a simple random sampling is

A jury

An example of a systematic sampling is

Every house number ending in 1

An example of stratified sampling is

Bhasvic asking 50 first years and 40 second years. (Bhasvic has 1500 first years and 1200 second years)

In quota sampling

An interviewer selects a sample that reflects the characteristics of the population

Opportunity sampling

Taking the sample from people who are available at the time the study is carried out and who fit the criteria you are looking for

4 advantages of quota sampling

Allows a small sample to still be representative of the the population, No sampling frame required, Quick, Allows for easy comparison between different groups within a population

4 disadvantages of quota sampling

Non-random sampling can introduce bias, Population must be divided into groups, Increasing scope of study increases number of groups, Non-responses are not recorded as such

2 advantages of oppurtunity/convenience sampling

Easy to carry out, Inexpensive

2 Disadvantages of oppurtunity sampling are

• Unlikely to provide a representative sample

• Highly dependent on the individual researcher

An example of quota sampling is

For maths

An example of oppurtunity samping

Asking women aged between 19 and 25 outside Paddington train station between 10am and 11am

Quantitative variables

Variables with numerical observations

Quantative data

Data with numerical observations

Qualatitive variables

Variables with non-numerical observations

Qualitative data

Data with non-numeric observations

Continuous variable

Can take any value in a given range

Discrete variable

Can take only specific values in a given range