Population & Sampling (Edexcel IGCSE Maths)
Population & sampling
What are the different types of data?
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Primary data is data that has been collected by the person carrying out the research
- This could be through questionnaires, surveys, experiments etc
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Secondary data is data that has been collected previously
- This could be found on the internet or through other research sources
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Qualitative data is data that is usually given in words (not numbers) to describe something
- For example: the colour of a teacher's car
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Quantitative data is data that is given using numbers which usually count or measure something
- For example: the number of pets that a student has
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Discrete data is quantitative data that takes specific numerical values
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These may or may not be integers
- For example: number of pets, shoe sizes, ...
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The values could go on forever
- For example: the number of times a coin is flipped until a ‘tails’ is obtained
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Continuous data is quantitative data that needs to be measured
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Continuous data can take any value within an interval
- For example: the height of a student
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Continuous data is often presented as rounded values
- to the level of precision of whatever measured them
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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
What is grouped data?
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Discrete data can be grouped into class intervals
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This is more convenient than stating every single data value
- E.g. For house prices, you may be more interested in how many houses sold for "£200k to £250k" than exactly how many houses sold for £238k, £225k, and so on
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Continuous data can be grouped into class intervals
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The class intervals must have no gaps between them
- The class intervals (group widths) do not necessarily need to be equal
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You can use a combination of to achieve this
- E.g. for height, cm, the intervals could be , ,
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With discrete data the class intervals may have gaps between them, as the data can only take specific separate values
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You still need to make it clear which group a value would go into
- They cannot overlap
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E.g. for "number of siblings" the groups may be "0 to 1" and "2 to 3" etc
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Each class interval represents a small range of whole-number values, and no values exist in between them
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What is a population?
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A population refers to the whole set of things which you are interested in
- e.g. if a teacher wanted to know how long pupils in year 11 at their school spent revising each week then the population would be all the year 11 pupils at the school
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Population does not necessarily refer to a number of people
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e.g. if an IT expert wanted to investigate the speed of mobile phones in the UK
- The population is all the phones in the UK
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What is a sample?
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A sample refers to a selected part (called a subset) of the population which is used to collect data from
- e.g. for the teacher investigating year 11 revision times a sample would be a certain number of pupils from year 11
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The larger the sample, the more reliable the conclusions drawn from it will be
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A random sample is where every item in the population has an equal chance of being selected
- e.g. every pupil in year 11 would have the same chance of being selected for the teacher's sample
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A biased sample is where the sample is not random
- e.g. the teacher asks pupils from just one class
What are the advantages and disadvantages of using a population?
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You may see or hear the word census - this is when data is collected from every member of the whole population
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The advantages of using a population
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Accurate results - as every member/item of the population is used
- In reality it would be close to every member for practical reasons
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All options/opinions/responses will be included in the results
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The disadvantages of using a population
- Time consuming to collect the data
- Expensive due to the large numbers involved
- Large amounts of data to organise and analyse
What are the advantages and disadvantages of using a sample?
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The advantages of using a sample
- Quicker to collect the data
- Cheaper as not so much work involved
- Less data to organise and analyse
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The disadvantages of using a sample
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A small sample size can lead to unreliable results
- Sampling methods can usually be improved by taking a larger sample size
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A sample can introduce bias
- particularly if the sample is not random
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A sample might not be representative of the population
- Only a selection of options/opinions/responses might be accounted for
- The members/items used in the sample may all have similar responses e.g. even with a random sample it may be possible the teacher happens to select pupils for his sample who all happen to do very little revision
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It is important to recognise that different samples (from the same population) may produce different results
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The larger the sample, the more reliable the conclusions drawn from it will be
Worked Example Mike is a biologist studying mice and has access to 600 mice that live in an enclosure.
Mike wants to sample some of the mice for a study into their response to a new drug.
He decides to sample 10 mice, selecting those nearest to the enclosure's entrance.
(a) State the population in this situation.
Answer:
Final answer: The population is the 600 mice living in the enclosure
(b) State two possible issues with the sample method Mike intends using.
Answer:
Final answer: The sample size is very small - just 10 mice The mice are not being selected at random - those nearest the entrance have a greater chance of being selected
(c) Suggest one way in which Mike could improve the reliability of the results from his sample.
Answer:
Final answer: Mike should increase the sample size to increase the reliability of the results
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