Sampling and collecting data

Question 1

What is qualitative data?

Answer 1

Qualitative data is data that is usually given in words not numbers to describe something
For example: the colour of a teacher’s car

Question 2

What is quantitative data?

Answer 2

Quantitative data is data that is given using numbers which counts or measures something
For example: the number of pets that a student has

Question 3

What is discrete data?

Answer 3

Discrete data is quantitative data that needs to be counted
Discrete data can only take specific values from a set of (usually finite) values
For example: the number of times a coin is flipped until a tails is obtained

Question 4

What is continuous data?

Answer 4

Continuous data is quantitative data that needs to be measured
Continuous data can take any value within a range of infinite values
For example: the height of a student

Question 5

Is age discrete or continuous data?

Answer 5

Age can be discrete or continuous depending on the context or how it is defined
If you mean how many years old a person is then this is discrete
If you mean how long a person has been alive then this is continuous

Question 6

What is a population?

Answer 6

The population refers to the whole set of things which you are interested in
For example: if a vet wanted to know how long a typical French bulldog slept for in a day then the population would be all the French bulldogs in the world

Question 7

What is a sample?

Answer 7

A sample refers to a subset of the population which is used to collect data from
For example: the vet might take a sample of French bulldogs from different cities and record how long they sleep in a day

Question 8

What is a sampling frame?

Answer 8

A sampling frame is a list of all members of the population
For example: a list of employees’ names within a company

Question 9

What is a population parameter?

Answer 9

A population parameter is a numerical value which describes a characteristic of the population
These are usually unknown
For example: the mean height of all 16-year-olds in the UK

Question 10

What is a sample statistic?

Answer 10

A sample statistic is a value computed using data from the sample
These are used to estimate population parameters
For example: the mean height of 200 16-year-olds from randomly selected cities in the UK

Question 11

What is a census?

Answer 11

A census collects data about all the members of a population
For example: the Government in England does a national census every 10 years to collect data about every person living in England at the time

Question 12

What is the advantage of a census?

Answer 12

The main advantage of a census is that it gives fully accurate results

Question 13

What are the disadvantages of a census? (2)

Answer 13

The disadvantages of a census are:
It is time consuming and expensive to carry out
It can destroy or use up all the members of a population when they are consumables (imagine a company testing every single firework)

Question 14

What are the advantages of sampling? (2)

Answer 14

The advantages of sampling are:
It is quicker and cheaper than a census
It leads to less data needing to be analysed

Question 15

What are the disadvantages of sampling? (2)

Answer 15

The disadvantages of sampling are:
It might not represent the population accurately
It could introduce bias

Question 16

What is simple random sampling?

Answer 16

Simple random sampling: if a sample of size is taken then every group of members from the population has an equal probability of being selected for the sample

Question 17

How is simple random sampling carried out?

Answer 17

Simple random sampling is carried out by uniquely numbering every member of a population and randomly selecting n different numbers using a random number generator or a form of lottery (where numbers are selected randomly)

Question 18

What is systematic sampling?

Answer 18

Systematic sampling: a sample is formed by choosing members of a population at regular intervals using a list

Question 19

How is systematic sampling carried out?

Answer 19

To carry this out you would calculate the size of the interval k=size of population (N)/size of sample (n) and choose a starting point between 1 and then select every kth member after the first one

Question 20

What is stratified sampling?

Answer 20

Stratified sampling: the population is divided into disjoint groups (called strata) and then a random sample is taken from each group (stratum)

Question 21

How is stratified sampling carried out?

Answer 21

The proportion of a sample that belongs to a stratum is equal to the proportion of the population that belongs to the stratum

The number of members sampled from a stratum = size of sample (n)/size of population (N) x number of members in the stratum

The population could be split by age ranges, gender, etc

Question 22

What is quota sampling?

Answer 22

Quota sampling: the population is split into groups (like stratified sampling) and members of the population are selected until each quota is filled.

If a member does not want to be included then another member is chosen instead
The members do not have to be selected randomly

Question 23

What is opportunity sampling?

Answer 23

Opportunity (convenience) sampling: a sample is formed using available members of the population who fit the criteria

Question 24

When should simple random sampling be used?

Answer 24

Simple random sampling: this should be used when you want a random sample to avoid bias
Useful when you have a small population or want a small sample (such as children in a class)

Question 25

When should simple random sampling not be used?

Answer 25

This can not be used if it is not possible to number or list all the members of the population (such as fish in a lake)

Question 26

When should systematic sampling be used?

Answer 26

Systematic sampling: this should be used when you want a random sample from a large population
Useful when there is a natural order (such as a list of names or a conveyor belt of items)
In order for the sample to be random the sampling frame needs to be random

Question 27

When shouldnt systematic sampling be used?

Answer 27

It can not be used if it is not possible to number or list all the members of the population (such as penguins in Antarctica)

Question 28

When should be stratified sampling be used?

Answer 28

Stratified sampling: this should be used when the population can be split into obvious groups of members (where members within a group have a common characteristic)
Useful when there are very different groups of members within a population

The sample will be representative of the population structure
The members selected from each stratum are chosen randomly

Question 29

When should stratified sampling not be used?

Answer 29

It can not be used if the population can not be split into groups or if the groups overlap

Question 30

When should quote sampling be used?

Answer 30

Quota sampling: this should be used when a small sample is needed to be representative of the population structure
Useful when collecting data by asking people who walk past you in a public place or when a sampling frame is not available

Question 31

What is the problem with quota sampling?

Answer 31

It can introduce bias as some members of the population might choose not to be included in the sample

Question 32

When should opportunity sampling be used?

Answer 32

Opportunity (convenience) sampling: this should be used when a sample is needed quickly
Useful when a list of the population is not possible

Question 33

How can opportunity sampling not be usefuL?

Answer 33

It is unlikely to be representative of the population structure

Question 34

What are the main criticisms of sampling techniques? (3)

Answer 34

Most sampling techniques can be improved by taking a larger sample

Sampling can introduce bias - so you want to minimise the bias within a sample
To minimise bias the sample should be random

A sample only gives information about those members - Different samples may lead to different conclusions about the population