2. OUT LINES
• Definition of sample
• Classification of sampling techniques
• Probability sampling
• Non-probability sampling
• Characteristics of probability sampling
DEFINITION OF SAMPLE
• A small group of people taken from a large group and used to represent
The large group is called sample.
4. PROBABILITY SAMPLING
• a probability sampling is one that have been selected in such away
that every element choose has a known probability of being included.
Characteristics of probability sampling
• It refers from the sample as well as the population.
• Every individual of the population has an equal probability to be taken into the sample.
• It may be representative of the population.
5. SIMPLE RANDOM SAMPLING
• Simple random sampling is a method of probability sampling in which
every unit has a equal non zero chance of being selected for the sample.
Methods of selecting random sample:
• Lottery method
• Tables of random numbers
CLUSTER SAMPLING
• The process of randomly selecting intact groups , not individuals
within the define population sharing similar characteristics.
• Defined population is divided into numbers of mutually exclusive and
collectively and collectively exhaustive sub groups .
• Select an independent simple random sample of clusters.
6. STRATIFIED RANDOM SAMPLING
• Stratified random sampling is a method of probability sampling in which the population
Is divided into different subgroups and samples are selected from each of them.
STEPS:
• All units of population are divided into different stratas in accordance with
Their characteristics.
• Using random sampling sample items are selected from each stratum.
SYSTEMATIC RANDOM SAMPLING
• Systematic random sampling is a method of probability sampling in which the
defined target population is ordered and the 1st unit of sample is selected at
Random and rest of the sample is selected according to position a skip interval.
K=N/n
Where ,k= sampling
N=population size
n= Sample size
