"The earliest use of statistics came from rulers and governments, who wanted information (data), such as the number of people, resources (e.g. food, gold, land) in order to set taxes, fund infrastructure (building projects), raise and maintain armies and go to war (Appendix 1). To make accurate decisions, ideally you would want to collect all the information or data available about a defined group or category. This is called the Population (the entire group of individuals or observations). The modern equivalent of this, is called a census or survey of the population (usually every 10 years) of a country, which collects information such as the total number of people, ethnicity, age and gender. The data obtained is called the population data. Some examples include, those with a disease or condition (e.gs diabetes or hypertension), smoking, animals or plants. However, it is not practical or possible to get the population data most of the time, so we take a random sample which can be representative of the population. The sample is a defined group of individuals or observations such as smoking habits taken from an identified and specific population. The sample should be representative of the population and is chosen by setting inclusion and exclusion criteria. The inclusion and exclusion criteria define the characteristics or features of the sample. For example, inclusion criteria could be healthy, males, aged 20-30; whilst exclusion criteria participants (or subjects) not suitable for selection might be smokers, not on any medication or have a medical condition"-- Provided by publisher
