analytical chemistry - sampling and its techniques
1. B.C.S. GOVT. PG. COLLEGE
DHAMTARI
:: SUBMITTED TO ::
DEPARTMENT OF CHEMISTRY B.C.S GOVT. PG COLLEGE
DHAMTARI
TOPIC – SAMPLE AND SAMPLING TECHNIQUE
GUIDED BY PRESENTED BY
MISS. AAKANKSHA MARKAM TOKESHWAR SAHU, MSC (III)RD SEM
3. Introduction
• Sampling and sample preparation have a unique meaning and special
importance when applied to the field of analytical chemistry. In
analytical chemistry, analysis of any substance we are not use bulky
state of matter, we take just small part of material then we carried out
quantitative and qualitative analysis of matter.
• Analyte – constituent of the sample
• Matrix – matrix refers to the components of the sample other than analyte
• Sample = Analyte + Matrix
4. Sample
• Sample is carried out of the larger bulk
• Sample is part of anything taken or presence for inspection.
• Sample is a group of people, object or item that are taken from a larger
population for measurement.
• A sample refers to a smaller, manageable version of a larger group.
• The sample should be representative of the population.
Sampling
Frame
5. Probability Sampling
Every member of the population has a chance of being selected for study. It
is mainly used in quantitative research.
They are again classified following types :-
Sampling
The act, process or technique of selecting a suitable sampling from large
population.
There are two types of sampling I) Probability Sampling
II) Non-probability Sampling
6. Simple Random Sampling – Every member of the population has an equal
chance of selection. Sampling frame should include the whole population.
Example – Lottery method.
7. Stratified Random Sampling – The population is divided mutually
exclusive groups (such as group) and random sample are drawn from
each group.
divide the population subgroups called strata based on the
relevant characteristic eg. Gender, job role, age etc.
8. Systematic Sampling – The entire population is arrange in a particular order
ascending or a descending
first of all a sampling interval given by K =
𝑁
𝑛
,
where N the size of the population, n the size of the sample
9. Cluster Sample – The population is divided into mutually exclusive group these group
already existing group such as block, city, college etc. the cluster should be mutually
homogeneous but internally heterogeneous.
10. Non-Probability Sampling
Convenience Sampling – In this sampling method the researchers selects most
accessible member in population.
Judgement Sampling – The Researchers selects population members who are good
prospects for accurate information.
11. Quota Sampling – In this method
population is divided different groups or
class according to different
characteristic of the population and
some percentage of different groups in
total population is fixed.
Snowball Sampling – It is also
known as chain sampling or network
sampling. This sampling technique can
go on and on, just like a snowball
increasing in size (in this case the
sample size) till the time a researcher
has enough data to analyze. It formed
by participates via other participates.