A-level Maths Statistics Definitions

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Definitions fro sampling

35 Terms

1

Population

A whole set of items that are of interest

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2

Census

Observes or measures every member of a population

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3

Sample

A selection of observations taken from a subset

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4

Advantage of a census

Should give a completely accurate results

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5

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

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6

3 advantages of a sample

  • Less time consuming and expensive than a census

  • Fewer people have to respond

  • Less data to process than in a census

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7

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

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8

Sample units

Individual units of a population

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9

Samping frame

A list of sample units

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10

A simple random sample if size n

One where ever sample of size n has an equal chance of being selected

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11

In stratified sampling

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

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12

In systematic sampling

Required elements are chosen at regular intervals form an ordered list

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13

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

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14

2 disadvantages of simple random sampling

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

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15

2 advantages of systematic sampling

Simple and quick to use, Suitable for large samples and large populations

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16

2 disadvantages of systematic sampling

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

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17

2 advantages of stratified sampling

Sample accurately reflects the population, Guarantees proportional representation of groups within a population

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18

2 disadvantages of stratified sampling

Population must be clearly classified into district data, Selection within each stratum suffers from the same disadvantages as a simple random sampling

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19

An example of a simple random sampling is

A jury

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20

An example of a systematic sampling is

Every house number ending in 1

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21

An example of stratified sampling is

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

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22

In quota sampling

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

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23

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

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24

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

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25

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

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26

2 advantages of oppurtunity sampling

Easy to carry out, Inexpensive

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27

2 Disadvantages of oppurtunity sampling are

Unlikely to provide a representative sample, Highly dependent on individual researcher

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28

An example of quota sampling is

For maths

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29

An example of oppurtunity samping

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

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30

Quantatitve variables

Variables with numerical observations

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31

Quantative data

Data with numerical observations

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32

Qualatitive variables

Variables with non-numerical observations

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33

Qualatitive data

Data with non-numerical observations

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34

Continuous variable

Can take any value in a given range

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35

Discrete variable

Can take only specific values in a given range

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