 When every unit of the population is examined. This is known as Census method.  On the other hand when a small group selected as representatives of the population is examined. ___ It is known as Sampling method

 Sampling is a process of inferring something about a large group of elements by studying only a part of it OR  It is a process of selecting relatively a small group of people representing the population.

 It is a miniature / replica of the entire group from which it has been selected  It is selected part which is used to ascertain the characteristics of the large group.  It is small/ cross section of larger whole

 The larger whole from which the sample has been taken is known as population.  It may consists of persons, objects, attributes, qualities, animals etc who have atleast one common characteristic,for example all graduates.

 The measures of samples are known as statistics.  The measures of population are known as parameters.

 Technically,sample is drawn from Sampling Frame i.e. a complete, accurate and up-to-date list of all the units in the population.  This frame is either constructed by the researcher for the purpose of his study OR may use some existing list of frame (Telephone Directories,List of schools/colleges in a state)

 The basic requirements of a scientific or ‘good’ sample are: 1) Representativeness 2) Adequate and, 3) Accurate

Size of the sample will depend upon the nature of the population. So the size of the sample is determined on the basis of 1) Variability in the population 2) The degree of precision required 3) The level of confidence at which the results are to be required.

Sampling Methods Probability Sampling Non-Probability Sampling

Probability Sampling Each unit of the population has equal chance of being included in the sample. Statistical theory is applicable. It leads to representative and adequate sample Non Probability Sampling Neither each unit has equal chance nor the chance of its being included in the sample are known. It is not possible in this It is left to the chance or luck.

 Probability sampling is technique where units /elements of population are not selected at the discretion of the researcher rather by means of certain procedures which ensure that every unit of a population has one fixed probability chance of being included in the sample.

Probability sampling Simple random sampling Stratified random sampling Systematic sampling Cluster sampling

 It is method of selecting a sample from a finite population.  Random sample is selected in such a way that every unit of the population has an equal and independent chance of being included.  Define the population  Listing of the population  Deciding the size of the sample  Selection of the sample by use of a) Lottery method b) Table of random numbers.

Random Sampling Steps Listing Population From 1 to N Deciding Size of Sample Selection of Sample Defining Population

 A random sample thus selected will have the following points to its credits : i. There will be no consistent bias. ii. On the average the sample will be representatives. iii. The degree of discrepancy can be calculated by using appropriate SE formula which is applicable to random sample.

___n ____n

 It involves the listing of the population units in a systematic manner.  Steps : 1) Listing of the units of population in some order –either alphabetically/ seniority wise etc 2) Determined the Sampling Fraction and also the number of K th unit i.e. K = N/n. 3) Choose a random number between 1 to K, both inclusive, 4) Select every K th unit from the list.

 It is useful when the units in the population are not available.  In this stratification of the Main Population is done into a number of sub-population on the basis of some stratification criteria each of which is homogeneous w.r.t. one or more characteristics  Steps: 1) Decide upon the relevant stratification criteria.___ It may be sex, age, SES, Geographical region etc 2) Divide the entire population into sub population based on Stratification Criteria. 3) List up the units separately in each sub- population 4) Select the requisite number of units from each sub – population by using random technique. 5) All the sub- samples representing sub- population make the main sample

 It is used when the population is infinite, where a list of units of population does not exist, where the geographic distribution is scattered and when sampling of individual units is not convenient for administrative reasons Steps: 1) It involves division of population of elementary units into groups/clusters that serve as primary sampling units 2) Selection of clusters is then made up to make the sample instead of individual member because here cluster is the sampling unit.

 It is used in large scale survey where the researcher has to select a sample a 2, 3, 4 stages.  For example in Survey type studies at the National level.

 Simple Random Sampling is used when the population is finite.  Stratified Sampling is used when list of units of individual in a population are not available.  Cluster Sampling is used when the population under study is infinite.  Multistage Sampling is used in large scale service for a more comprehensive investigation.

 In this sampling the units of sampling are selected at the discretion of the researcher. Guiding Factors in the Non-probability Sampling are a) Convenience of the researcher b) Experience of the researcher c) Availability of the subjects

Non- Probability Sampling IncidentalPurposiveQuota

 It is generally used with those groups which are selected because of the easy availability of the sampling units.  It is based on the assumption that a good researcher has a good judgment.  A quota sample involves the selection of the sample units within each stratum or quotas on the basis of the judgment of the researcher rather than on calculable chance of being included in it.