The document discusses different types of sampling methods used in statistical surveys. It defines key terms like population, sample, parameter, and sampling. It then describes various sampling techniques including simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. Simple random sampling involves each member of the population having an equal chance of selection, while systematic sampling selects units at regular intervals from a complete list. Stratified sampling divides the population into subgroups first before sampling, and cluster sampling selects intact groups of individuals.

1. RELATED TO DESIGN OF SAMPLING SURVEY
-chandana priya
* RANDAM SAMPLING

2. *TERMINOLOGY
*POPULATION
*SAMPLE
*SIZE OF SAMPLE
*PARAMETER
*SAMPLING

3. POPULATION/UNIVERSE
• Population in statistics means the whole of the information
Which comes under the preview of statistical information.
(or)
• A population is the pool of individuals from which a statistical
sample is drawn for a study.
• Ex: marks obtained by students in a class
 Population is divided into 2 types:
• Finite Population:
The population is said to be finite when the number of items
in the population can be expressed as a definite quantity
Ex: The population of weights of students in class 10th
• Infinite population:
The population is said to be infinite when the number of
items in the population cannot be expressed as a definite quanty
Ex :water drop in a ocean or stars in the sky

4. SAMPLE
• A selection of a group of individuals or items from a
population in such a way that the group represents the popln is
called a sample.
• Sample size should be always smaller than the population size.
• Ex: we will check whether rice is cooked or not.
SIZE OF SAMPLE:
• The number of individuals or items include in a finite sample is
called the size of the sample.
PARAMETER:
• Any statistical measure computed from population data is
known as parameter
• Ex: population mean(µ) population parameter(θ)
SAMPLING:
• It is the process od selecting a sample from a population is
called sampling

6. Simple Randam sample
• It is the method of selection of a sample in such a way that
Each and every member of population has an equal chance of
probability

7. SYSTEMATIC SAMPLING
• It is commonly used in the complete and up-to-date list of the
sampling units is available
• This consists in selecting only the first unit at radam, and the
rest being automatically selected according to some pattern
involving regular spacing in units
• N=nk =>k=(n/n)
• Where k=sampling interval ;n=size2
• Ex: suppose a supermarket study the buying habits of a
customer then we choose 10th or 15th customers

8. STRATIFIED SAMPLING
• In stratified sampling popn of N units is first divided into
sub-populations of N1,N2,N3,…..NL
• These sub-populations are non-overlapping

9. CLUSTER OR AREA SMPLING:
• Subdivide the popln into sub groups is called clusters
• Units are belongs to the sample
• And these smallest cluster sampling called as area sampling
• It may be one-stage or multi-stage
• Ex: agriculture goverment agencies

10. MULTI STAGE SAMPLING
• IN this sampling method sample of elementary units is selected
in stages.
• Firstly a sample of cluster is selected and form among them a
groups of elementary units is selected.