**Q.12.
Define the term cluster sampling.**

**Ans.** The total population is divided in some recognisable
sub-divisions which are termed as clustere and a simple random sample is drawn
from each cluster.

**Q.13.
What is meant by non-random sampling?**

**Ans.** Non-random sampling methods are those which do not provide every item in the universe with a knowing chance of being included in the sample.

**Q.14.
Write the two merits and demerits of quota sampling. **

**Ans.
Merits:** The two merits are:

1. Mixture of stratified and purposive sampling.

2. Quite reliable results.

**Demerits:** The two demerits are:

1. Usde fopre-determined r conclusions.

2. Problems of sampling error.

**Q.15.
What is the meaning of extensive sampling?**

**Ans.** This sampling is almost like a census and a large number
of items from universe are included in the sample. Only those units are left
about which it seems difficult or impossible to collect information.

**Q.16.
Define the term F-distribution.**

**Ans.** In order to test the equality of two population variance
and equality of several population mean, we use the F-test. Thus, it is
necessary to know F-distribution. The F-distribution is named after the English
statistician, Sir Ronald Fisher.

**Q.17.
Write the three assumptions of F-test. **

**Ans. **The three assumptions of F-test are:

1. The parent population is normal.

2. The samples are selected randomly and thus the observations are independent.

3. The variance ratio should be greater than or equal to one. This is the reason that larger variance is divided by the smaller variance.

**Q.18.
What do you mean by chi-square test?**

**Ans.** The test of significance concerning large samples and
small samples are based on the assumption that the sample are drawn from a
normally distributed population. Since, these tests are based on assumption
about the type of population or parameters therefore, these tests are known as
parametric tests. But there are many situations in which it is not possible to
make any assumption about the distribution of the population from which samples
are drawn. This has led to the development of non-parametric tests in which no
assumption is made regarding the population from which samples are drawn.

**Q.19.
Write the four characteristics of chi-square test. **

**Ans.** The four
characteristics of chi-square test are:

It is a non-parametric test which is based on observed and expected frequencies rather than parameters like mean and standard deviations.

2. Though x? distribution is essentially a cotribuinuous distribution but it can also be applied to discrete random variables whose frequecies edcan be counted and tabulated with or without grouping.

3. This test is used for testing the hypothesis and not for estimation.

4. The sum of the observed and expected frequencies is always zero

Symbolically,

EO- E) = 20 – EE = N-N=0

**Q.20.
What is the meaning of degrees of freedom?**

**Ans.** The degrees of freedom refers to the end whserved frequencies. In other words by degrees of freedom, the values can be assigned arbitrarily or without violating in Fefer to the number of independent constraints in a set of data.

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