DETERMINING SAMPLE DESIGN

What is Sample Design…..?

• A sample design is a definite plan for obtaining a sample from a given population. It refers

to the technique or the procedure the researcher would adopt in selecting items for the

sample.

Steps in Sample Design:

• Type of Universe

• Sampling Unit

• Sampling Frame

• Size of Sample

• Budgetary Constraints

• Sampling Procedure

CharacteristicsOf A Good Sample Design

• Sample design must result in a truly representative sample

• Sample design must be such which results in a small sampling error

• Sample design must be viable in the context of funds available for the

research study

• Sample design must be such so that systematic bias can be controlled in a

better way

• Sample should be such that the results of the sample study can be applied,

in general, for the universe with a reasonable level of confidence

Types of Sample Design

• Probability Sampling Design

• Each element/respondent has a known probability of being included in the sample.

• Non-probability Sampling Design

• Each element/respondent in the population is not given equal chance of selection.

Probability Sampling Designs:

• Simple Random Sampling

• Each and every element/respondent in the population is given equal chance of selection.

• Systematic Sampling

• The selection of sample starts by picking some random point in the list and then every nth element

is selected until the desired number is secured.

• Stratified Random Sampling

• The population is stratified into a number of non-overlapping subpopulations or strata and sample

items are selected from each stratum.

• Cluster Sampling and Area Sampling

• It involves grouping the population and then selecting the groups or the clusters rather than

individual elements for inclusion in the same.

• Area Sampling : Total geographical area is divided into a number of smaller non-overlapping areas,

generally called geographical clusters, then a number of these smaller areas randomly selected and

all elements in these small areas are included in the sample.

• Multi-stage Sampling

• This is further development of the idea of Cluster sampling. The first stage in this technique

may include to select large primary sampling unit then next smaller sampling unit and so on

and technique of random-sampling is applied to all stages. Ex: Country-State-District-City-

Families.

• Sequential Sampling

• This is somewhat a complex sample design where the ultimate size of the sample is not fixed

in advance but is determined according to mathematical decision on the basis of information

yielded as survey progresses.

Non Probability Sampling Designs: (Deliberate or Purposive Sampling)

• Convenience Sampling

• When elements/respondents in the population/universe are selected for inclusion in the sample

based on the ease of the access.It is called Convenience sampling.

• Judgment Sampling

• The researcher’s judgment is used for selecting items which he/she considers as

representative of the population. This sampling is used quite frequently in

Qualitative Research where the desire happens to be to develop hypotheses

rather than to generalise to larger population.

• Quota Sampling

• When The researcher or interviewer are simply given quota to be filled from

different strata, rather then selecting elements from each stratum based on simple

random is known as Quota sampling. The size of the quota for each stratum is

generally proportionate to the size of the stratum in the population. It generally

happens to be judgment sampling rather than random sampling.

COLLECTION OF DATA

TYPES OF DATA

• Depending on the source, statistical data are classified under two categories:

❑Primary Data

When the data used in a statistical study was collected under the control and

supervision of the investigator, such type of data is referred to as primary data.

❑Secondary Data

When the data was not collected by the investigator, but is derived from other

sources then such data is referred to as secondary data.

6. COLLECTING THE DATA

Primary data can be collected either through experiment or survey. Following are ways

to collect Primary data through survey:

• By Observation

• Through Personal Interview

• Through Telephone Interview

• By Mailing of Questionnaire

• Through Schedule

METHODS OF COLLECTING PRIMARY DATA

• Primary data may either be collected through any of following methods:

❑ Observation Method

❑ Questionnaire Method

➢ Personal Interview

➢ Mail

➢ Telephone

➢ e- contact

DESIGNING A QUESTIONNAIRE

• Covering Letter

• Personal detail of respondents should either be in start or at end of the questionnaire

• Number of questions should be kept to minimum

• Questions should be short and simple to understand

• Ambiguous questions ought to be avoided

• Questions should be arranged logically

• Questions of sensitive or personal nature should be avoided

• Questions requiring calculations should be avoided

TYPE OF QUESTIONS TO BE USED IN QUESTIONNAIRE

• Open Ended Questions

• Closed Ended Questions

• Multiple Choice Questions

PRE TESTING THE QUESTIONNAIRE (PILOT SURVEY)

• Pre-testing allows rectification of problems, inconsistencies, repetitions etc.

• If changes are required, the necessary modifications can be made before administering

questionnaire.

• Pre-testing must be done with utmost care, otherwise unnecessary and unwanted

changes may be introduced.

• If time and resources permit, a second pre-testing can also be done to ensure greater

reliability of results.

EDITING PRIMARY DATA

• Editing of primary data is necessary to ensure following:

➢ Completeness

➢ Consistency

➢ Accuracy

➢ Homogeneity

SOURCES OF SECONDARY DATA

• The sources of secondary data can broadly be classified under two heads:

➢Published Sources

➢Unpublished Sources

PUBLISHED SOURCES

• Reports and official publications of –

▪ International bodies such as:

➢ United Nations Organisation (UNO)

➢ World Health Organisation (WHO)

➢ International Labour Organisation ( ILO)

➢ International Monetary Fund (IMF)

➢ World Bank

▪ Central & State Govt. Agencies such as:

➢ Central Statistical Organisation (CSO)

➢ National Sample Survey Organisation (NSSO)

➢ Federation of Indian Chambers of Commerce and Industry (FICCI)

➢ Indian Council of Agriculture Research (ICAR)

• Semi-official publications of various local bodies such as Municipal Corporation and

District Boards

• Publications of autonomous and private Institutes

UNPUBLISHED SOURCES

• A major source of statistical data produced by Govt., semi-govt., private and public

organisations is based on the data drawn from internal records.

• This data based on internal records provides authentic statistical data and is much

cheaper as compared to primary data.

• Some examples of the internal records include employees’ payroll, the amount of raw

materials, cash receipts and cash book etc.

EDITING OF SECONDARY DATA

• The investigator must scrutinize and edit published data before using, keeping in mind the

following:

➢ Suitability of data

➢Reliability of data

➢Adequacy of data