# data handling notes

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- Created by: louisepardoe
- Created on: 05-04-16 14:57

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**Sampling and bias**

- sample data must be representative
- the population is the whole group you want to find out about
- often you can't survey the whole population
- a sample is a small group from the population
- for a sample to be representative it needs to be: a random sample (every member has an equal chance of being in it) and big enough for the size of the population
- to spot bias you need to think about when, where and how the sample is taken and how many members are in it
- if certain groups are excluded, the sample isn't random and that can lead to bias from things like age, gender and different interests
- if the sample is too small, it's also likely to be biased

**Sampling methods**

random sampling

- assign a number to every member of the population
- create a list of random numbers
- match the random numbers to members of the population

stratified sampling

- find the proportion…

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