UNIT III: INTERPOLATION AND EXTRAPOLATION
1. Write any two assumptions of interpolation.
Ans The following assumptions are made:
(i) There are no Sudden Jumps in the values of the independent variable from one period to another
(ii) The rate of changes in figures from one period to another is uniform
2. What are the conditions on which Binomial Expansion methods od Interpolation are applied?
Ans: : (i) There are no sudden jumps from one period to another period
(ii) There is a sort of uniformity in the rise or fall of the value of variables
(iii)There is a definite and stable relationship Between the two Variables.
UNIT IV: SAMPLING AND SAMPLING DISTRIBUTION
1. Distinguish between parameter and statistic.
ANS: Any Statistical Measure computed from population data is known as a parameter.
Any statistical measure computed from sample data is called a statistic.
2. What are the methods of sampling?
Ans: The methods of sampling are:
(i) Probability or random sampling
(ii) Non-Probability or non-random
3, What is Simple random sampling?
Ans: Simple random sampling refers to the sampling technique in which every unit of the population has ab equal opportunity of being selected in the sample.
Section of item in just a matter of chance
4. What is stratified random sampling?
Ans: Stratified random sampling is one of the random methods which, by using the available information concerning the population, attempts to design a more efficient sample obtained by simple random procedure. the population is subdivided into the homogenous group and a random sample is drawn from stratum.
5. What is snowball Sampling?
Ans: Snowball sampling is a technique of building up a list or sample of the special population by using an initial set of its members as informants.
6. Define stage sampling or multi-stage sampling.
Ans: Under these methods, Random selection is made of primary, intermediate and final unites from the given population.
7. What is the sampling distributions?
Ans: The probability of a sample statistic is called its sampling distribution. A sampling distribution is the probability of given statistics based on a random sample. It is created by the sample means on the rules of probability.