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2.2 Categorize/Sample Data

This is one of the easier topics in the syllabus. Questions are generally very straight-forward and most of it you can expect to occur in part 1 of the exam. Questions are also based on common sense and if you know basic data categorization and sampling you should be ok for most part.

Data Types:

Categorical: data that describes a characteristic and can be broken down into categories. It has further 2 types:

Nominal: type of categorical data for which categories can be named but cannot be ordered like eye color (blue, black, brown cannot be ranked)

Ordinal: categorical data that can be ordered into a ranking like scale of 1 to 10

Numerical/Quantitative: data that can be counted and measured. It also has 2 types:

Discrete: these have exact numerical values e.g. number of people (can’t be 0.2 or 0.1 people)

Continuous: these can take any numerical value within a certain range e.g. heights/weights of people

Data Sampling:

Census: involves collecting information about each and every member of the entire population. Members can be people or objects. Doing a census is an expensive activity and sometimes a portion of the population is selected to get an understanding of the entire population, this is called sample data.

Random sampling: this kind of sample is selected (as the name suggests) randomly indicating that each member in the population has an equal chance of getting selected.

Stratified sampling: population is divided into sub-groups based on any logical characteristic (age, gender etc.) and samples are taken out from each of these sub-groups. The size of each random sample is proportional to the relative size of the subgroup in the population.

Systematic sampling: as name suggests has a system involved in it e.g. selecting every 10th member of a population.

There are two broad types of questions you can expect in exam:

2.2.1 Exam Question Type 1

2.2.2 Exam Question Type 2

Study notes of this section and other resources can be accessed here:

– 2.2.3 Study Notes & Resources

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