Measurement of Variables

1) State the type of variable (nominal, ordinal and numerical) for the following:
a) tribes in India -- Nominal
b) height of children -- Numerical
c) number of books -- Numerical
d) accession number of books -- Nominal
e) subject codes -- Nominal

2) With an example explain the use of Likert scale.
Example of the use of Likert Scale: Show your agreement with the following:
Libraries will ever remain important for the advancement of the society
Strongly Agree; Agree; Undecided; Disagree; Strongly Disagree

3) What are the advantages of sampling over census?
Sampling is advantageous over statistic in that it saves cost and time to be devoted to the survey. It involves fewer personnel to be deployed and also results in more precision in the results.

4) Distinguish between sampling error and non-sampling error
Sampling error is due to the faulty sample selected. It may be due to non- probability sampling techniques adopted. Non- sampling errors are due to the errors in data measurement or analysis methods.

5) What are the important steps in carrying out a sample survey?
The steps to be followed in carrying out a sample survey are:
specification of objective, preparation of sampling frame, identification of sampling procedure, determination of sample size, and selection of sampling units.

6) Explain the procedure of drawing a stratified random sample.
The procedure of drawing a stratified random sample is:
Divide the population into strata based on some characteristic chosen by you (example, Post graduate/ Under graduate, Male/Female, etc.)
Decide the number of units to be taken from each stratum proportional to the relative size of the stratum and standard deviation of the characteristic within the stratum. If stratum size is then a large a sub-sample should be taken. Similarly if you find that variability among units is more in a stratum than other strata, then you should take a larger sub-sample from that.
Choose the sub-sample from each stratum using simple random sampling.

7) Explain the following concepts:
 a) Systematic random sampling
Systematic random sampling is a type of random sampling where the bias is minimised. Here the random sample is selected in a systematic way, e.g., in case a sample of 100 is to be selected from a population of 1000, and then  we may select the first member of the population and every subsequent 20th member.
b) Parameter and statistic
Parameter is a summary value of the population while statistic is that of the sample.
c) Multistage sampling
Multistage sampling is sampling done in two or more stages. In case we have to survey reading habits of users in public libraries, we may first take a random sample on the basis of geographical regions and then further take a sample on the basis of age groups. This is an example of multistage sampling.


Convenience Sampling : It refers to the method of obtaining a sample that is most conveniently available to the researcher.
Judgement Sampling : In this sampling procedure the selection of sample is based on the researcher’s judgement about some appropriate characteristics required of the sample units.
Multistage Sampling : The sample selection is done in a number of stages.
Parameter : It is a measure of some characteristic of the population.
Population : It is the entire collection of units of a specified type in a given place and at a particular point of time.
Quota Sampling : In this sampling procedure the samples are selected on the basis of some parameters such as age, gender, geographical region, education, income, religion, etc.
Sample : It is a sub-set of the population. Therefore, it is a collection of some units from the population.
Simple Random Sampling: This is the basic sampling procedure where all units in the population have an equal chance of being included in the sample.
Snowball Sampling : It relies on referrals from initial sampling units to generate additional sampling units.
Statistic : It is a function of the values of the units that are included in the sample. The basic purpose of a statistic is to estimate some parameter.
Stratified Random : In this sampling procedure the population is divided Sampling into groups called strata. Subsequently sub-samples are selected from each stratum using a random sampling method.
Systematic Sampling : In this procedure the units are selected from the population at uniform interval (in time, order or space).

Source:IGNOU Study Material

Related Posts