Stfm 121
STFM121 - Inferential Statistics and Introductory to Operations Research Lecture-3
Dr. S. Thomas
Department of Statistics, North-West University, Mafikeng Campus,
August 8, 2013
UNIT 2: SAMPLING
POPULATION
A population consists of all the possible observations of the random variable under study. A census involves the gathering of data on a random variable from every member of the target population A sample is a subset of all members of a target population. Sampling is the process of selecting a representative subset of observations from a population to determine the characteristics of the random variable under study.
SAMPLING METHODS
Two methods of sampling are:
1 2
probability sampling methods non-probability sampling methods
PROBABILITY SAMPLING
In probability sampling (random-based sampling) every member of the target population has a chance of being selected for the sample. Sampling units are selected from the target population on a random basis. There are four probability-based sampling methods:
1 2 3 4
simple random sampling systematic random sampling stratified random sampling cluster random sampling.
PROBABILITY SAMPLING
Simple random sampling: Each member in the entire population has an equal chance of being selected. Systematic random sampling: Sampling begins by randomly selecting the first sampling unit from the sampling frame (database of population members). Thereafter, subsequent sampling units are selected at a uniform interval relative to the first sampling unit. Stratified random sampling: This method is used when the population is heterogeneous with respect to the random variable under study. The entire population can be divided into segments (or strata) where the sampling units in each stratum are relatively homogeneous. Thereafter, random samples are selected from each stratum.
PROBABILITY SAMPLING:
Cluster random sampling: The entire population is divided into clusters, and a random sample of
Dr. S. Thomas
Department of Statistics, North-West University, Mafikeng Campus,
August 8, 2013
UNIT 2: SAMPLING
POPULATION
A population consists of all the possible observations of the random variable under study. A census involves the gathering of data on a random variable from every member of the target population A sample is a subset of all members of a target population. Sampling is the process of selecting a representative subset of observations from a population to determine the characteristics of the random variable under study.
SAMPLING METHODS
Two methods of sampling are:
1 2
probability sampling methods non-probability sampling methods
PROBABILITY SAMPLING
In probability sampling (random-based sampling) every member of the target population has a chance of being selected for the sample. Sampling units are selected from the target population on a random basis. There are four probability-based sampling methods:
1 2 3 4
simple random sampling systematic random sampling stratified random sampling cluster random sampling.
PROBABILITY SAMPLING
Simple random sampling: Each member in the entire population has an equal chance of being selected. Systematic random sampling: Sampling begins by randomly selecting the first sampling unit from the sampling frame (database of population members). Thereafter, subsequent sampling units are selected at a uniform interval relative to the first sampling unit. Stratified random sampling: This method is used when the population is heterogeneous with respect to the random variable under study. The entire population can be divided into segments (or strata) where the sampling units in each stratum are relatively homogeneous. Thereafter, random samples are selected from each stratum.
PROBABILITY SAMPLING:
Cluster random sampling: The entire population is divided into clusters, and a random sample of