PRESENTATION ON

SAMPLINGPrepaired By:

Rajni Devi

M.A,M.LIB.SC,PGDCA(UGC NET)

Dept of Library & Information science

Kurukshetra University, Kurukshetra

SAMPLING

Introduction

Sampling method refers to thecollection of data from a few element ofthe Population. Population refers to theaggregate of data source. Any aggregatefrom which data is collected is called apopulation. A sample is a subset ofpopulation.

Essential of Good Sampling

• Representative

• Adequacy

• Homogeneity

• Independent Ability

• Cost

Type of sampling

• Probability Sampling

• Non Probability Sampling

Type of sampling

Probability sampling

Simple random sampling

Systematic sampling

Stratified Random Sampling

Cluster Sampling

Sampling with probability proportional to size

Sequential Sampling

Non Probability sampling

Quota Sampling

Purposive or Judgement Sampling

Accidental Sampling

Snowball sampling

Probability Sampling

Probability sampling is also knownas random or chance sampling.Under this sampling design, everyitem of the population has an equalchance of inclusion in the sample.

Types of Probability Sampling

• Simple random sampling

• Systematic sampling

• Stratified Random Sampling

• Cluster Sampling

Simple Random Sample

• Every subset of a specified size n from the population has an equal chance of being selected

Systematic Sample

• Every nth member ( for example: every 10th person) is selected from a list of all population members.

Stratified Random Sample

• The population is divided into two or more groupscalled strata, according to some criterion, such asgeographic location, grade level, age, or income, andsubsamples are randomly selected from each strata.

Cluster Sample

• The population is divided into subgroups (clusters) like families. A simple random sample is taken of the subgroups and then all members of the cluster selected are surveyed.

Non Probability Sampling

Non probability sampling refers to thesampling process in which the samples areselected for a specific purpose with a pre-determined basis of selection. This type ofsampling is also required at times whenrandom selection may be possible.

Non Probability Sampling

• Convenient Sampling

• Quota Sampling

• Purposive or Judgment Sampling

• Snowball sampling

Convenient Sampling

The sampling procedure of obtaining theunits that are most conveniently available.

Quota Sampling

In Quota Sampling, population is firstsegmented into mutually exclusive sub-groups.Then judgment is used to select the subjects orunits from each segment based on a specifiedproportion.

Purposive or Judgment Sampling

Samples in which the selection criteria arebased on personal judgment that the elementis representative of the population understudy.

Snowball Sampling

Samples in which selection of additionalrespondents is based on referrals from theinitial respondents.