1. Statistics

2. Survey
A Survey is a way of finding information from people for a particular purpose. It involves - asking questions - recording what people say - presenting information in a way that makes it easy to understand.
Example: Companies ask customers to complete questionnaires to find ways in which they can improve the service they offer.

3. Planning a Survey Key information:
You have to know exactly what you need to find out.
Give simple and clear questions to avoid any confusion
Avoid asking personal questions
Don’t ask too many questions
How to collect the data (over the phone, interview, questionnaire (online, postal), etc…)

4. Questionnaires Key points:
Questions should be clear, short and easily understood.
Start with simple questions to encourage the person who is completing the questionnaire.
Avoid leading questions. These are questions that suggest a particular response.
Avoid personal questions.
Do you think that politicians are overpaid?

5. Types of Data Primary Data is data which you collect yourself.
Secondary Data is data you find in newpapers, books or online.

6. Sampling Population is the entire group e.g. School community
Sample is a group from this overall population e.g. 1st year students

7. Simple Random Sampling:
Each student has an equal chance of being selected. Results should be similar to the result if you selected all participants.
Note: If sample is too small, results may not be reliable. If sample is too large, it may take too long to collect the data.
If the sample is not random and does not fairly represent the whole population, the results may be Biased.

8. Numerical Data
Numerical Data is data that can be answered with numbers.
For example when you are asked how many students are in your class or how many bedrooms in your house.

9. Numerical data can be broken down into two different types:
Discrete numerical data is data that has a finite ending or can be counted. For example, the number of pencils in a box represents discrete data.
Continuous numerical data represents values with infinite possibilities. For example, the weight of an object or the measurement of rainfall. Could be an infinite number of decimals.

10. Categorical Data
Categorical data is data that cannot be answered with numbers.
For example when you are asked what colour are your eyes or what is your favourite soccer team.

11. Categorical data can be broken down into two different categories:
Ordinal categorical data can be ordered in some way. For example, your exam grades (A, B, C, D, E, F, NG) or your social class (Lower, Middles, Upper).
Nominal categorical data cannot be ordered. For example, your hair colour or your phone type.