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Hi, I'm Miss Davies.

In this lesson, we're going to be looking at data collection.

The most common method of data collection is a survey to a sample of people.

The sample size is the number of people that are asked a survey.

A bigger sample size would give a more accurate representation of the general population.

However, if it is too large, it would take far too long to collect the data.

Biassed data is taken from the same location at a similar time or from the same age group.

This means that you're going to be getting the same kind of people answering the questions, making it by it biassed.

Here is some questions for you to try, pause the video to complete your task and resume once you're finished.

Here are the answers, the population in this example is the 2000 students.

If you were to survey 2000 people, it would take a long time.

30 is a suitable sample size, five people wouldn't give a true representation of the population, and the other two, 1700 and 2000 people will take a long time to record the data and to analyse it.

Here is some questions for you to try, pause the video to complete your task and resume once you're finished.

Here are the answers, this would give biassed results, to improve it, Paul should ask people at a variety of different locations.

Here is a question for you to try, pause the video to complete your task and resume once you're finished.

Here is the answer, Maria could put all the people's names into a hat and randomly select 20 or more names, or she could allocate everybody a number at random then it produced a list of random numbers in order to select people.

That's all for this lesson, thanks for watching.