Statistics- Data Collection (1)

Question 1

Population

Answer 1

Whole set of items that are of interest

Question 2

Census

Answer 2

Observes/measures each member of a population

Question 3

Sample

Answer 3

Selection of observations taken from a subset of the population, used to find information about the whole population

Question 4

Census Advantages

Answer 4

Completely accurate

Question 5

Census Disadvantages

Answer 5

• Time consuming and expensive
• Cannot be used if the testing process destroys the item
• Hard (or impossible) to process large quantities of data

Question 6

Sample Advantages

Answer 6

• Less time consuming and less expensive than a census
• Fewer responses needed
• Less data to process

Question 7

Sample Disadvantages

Answer 7

• Data may not be accurate

- Sample may not be large enough to reflect all subsets

Question 8

Sampling units

Answer 8

Individual units of a population

Question 9

Sampling frame

Answer 9

List of individually numbered or named sampling units

Question 10

3 main random sampling methods

Answer 10

• Simple random
• Systematic
• Stratified

Question 11

Simple random sampling

Answer 11

Sample is chosen randomly using a random number generator

-requires a sampling frame to be set up

Question 12

Systematic sampling

Answer 12

Every nth member of the population is chosen from an ordered list where

• n=population size/sample size
• first element should be a random number between 1 and n

Question 13

Stratified sampling

Answer 13

Population is divided into mutually exclusive strata and a random sample is taken from each
-proportion of each strata should be the same

Question 14

Stratified sampling formula

Answer 14

Number sampled in a stratum= (number in stratum/ number in population)*overall sample size

Question 15

Simple random sampling ADV

Answer 15

• Free of bias
• Easy and cheap to implement for small populations and samples
• Each sampling unit has a knows and equal chance of selection

Question 16

Simple random sampling DISADV

Answer 16

• Not suitable when there is a large population or sample size
• A sampling frame is needed

Question 17

Systematic sampling ADV

Answer 17

• Simple and quick

- Suitable for large samples and populations

Question 18

Systematic sampling DISADV

Answer 18

• A sampling frame is needed

- Can introduce bias if the sampling frame is not random (two people together are unlikely to be selected)

Question 19

Stratified sampling ADV

Answer 19

• Accurately reflects population structure

- Guarantees proportional representation of groups in the population

Question 20

Stratified sampling DISADV

Answer 20

• Population must be clearly classified into distinct strata

- Selection within each stratum suffers the same disadvantages as simple random sampling

Question 21

2 main non-random sampling methods

Answer 21

• Quota

- Opportunity

Question 22

Quota Sampling

Answer 22

An interviewer or researcher selects a sample that reflects the characteristics of the whole population

Question 23

Opportunity Sampling

Answer 23

Sampling the people who are available whilst the study is carried out and fit criteria

Question 24

Quota sampling ADV

Answer 24

• Allows a small sample to represent the whole population
• No sampling frame needed
• Quick, easy, inexpensive
• Allows for easy comparison between different groups

Question 25

Quota sampling DISADV

Answer 25

- Non random= bias - Population must be divided into groups - Increasing scope of study increases the number of groups, take time and money - Non-responses aren't recorded as such

Question 26

Opportunity sampling ADV

Answer 26

- Easy to carry out | - Inexpensive

Question 27

Opportunity sampling DISADV

Answer 27

- Unlikely to provide a representative sample | - Dependent on individual researcher

Question 28

Quantitative variable

Answer 28

Data associated with numerical observations

Question 29

Qualitative variable

Answer 29

Data associated with non-numerical observations

Question 30

Continuous variable

Answer 30

A variable that can take any value in a given range

Question 31

Discrete variable

Answer 31

A variable that can only take specific values in a given range

Question 32

Class

Answer 32

The groups data is presented in in a grouped frequency table

Question 33

Class boundaries

Answer 33

Max and min values in each class

Question 34

Midpoint

Answer 34

Average of the class boundaries

Question 35

Class width

Answer 35

Difference between upper and lower boundaries