Stats Definitions (CH. 1) Types of sampling

Frame

a list of the individuals in the population being studied. If the population of interest is all the students at a​ school, the frame would be a list of all the students currently attending that school.

Simple random Sampling

is the basic sampling technique where we select a group of subjects (a sample) for study from a larger group (a population). Each individual is chosen entirely by chance and each member of the population has an equal chance of being included in the sample.

Convenience Sampling

one of the main types of non-probability sampling methods. Made up of people who are easy to reach for example calling for volunteers.

Cluster sampling

a sampling technique used when "natural" but relatively heterogeneous groupings are evident in a statistical population. It is often used in marketing research. In this technique, the total population is divided into these groups (or clusters) and a simple random sample of the groups is selected is obtained by dividing the population into groups and selecting all individuals from within a random sample of the groups. To determine customer opinion of their musical variety, Sony randomly selects 60 concerts during a certain week and surveys all concert goers.

Systematic Sampling

a type of probability sampling method in which sample members from a larger population are selected according to a random starting point and a fixed periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size. Does not require a frame. Example: selecting every 14th laptop that comes out of the machine to form a sample.

Stratified Sampling

the researcher divides the population into separate groups, called strata. Then, a probability sample (often a simple random sample ) is drawn from each group. obtained by dividing the population into homogeneous groups and randomly selecting individuals from each group. obtained by separating the population into nonoverlapping groups called strata and then obtaining a simple random sample from each stratum. The individuals within each stratum should be homogeneous​ (or similar) in some way. In order for the stratified sample to be representative of the​ population, the number of individuals sampled from each stratum should be proportional to the size of the strata in the population. For​ example, if one wanted take a stratified sample of 100 individuals from a population that is​ 53% female and​ 47% male, then 53 females and 47 males should be sampled.