Students can download 12th Business Maths Chapter 8 Sampling Techniques and Statistical Inference Ex 8.3 Questions and Answers, Samacheer Kalvi 12th Business Maths Book Solutions Guide Pdf helps you to revise the complete Tamilnadu State Board New Syllabus and score more marks in your examinations.

## Tamilnadu Samacheer Kalvi 12th Business Maths Solutions Chapter 8 Sampling Techniques and Statistical Inference Ex 8.3

Question 1.
A ______ may be finite or infinite according to as the number of observations or items in it is finite or infinite.
(a) Population
(b) census
(c) parameter
(d) none of these
(a) Population

Question 2.
A _______ of statistical individuals in a population is called a sample.
(a) Infinite set
(b) finite subset
(c) finite set
(d) entire set
(b) finite subset

Question 3.
A finite subset of statistical individuals in a population is called ________
(a) a sample
(b) a population
(c) universe
(d) census
(a) a sample

Question 4.
Any statistical measure computed from sample data is known as _______
(a) parameter
(b) statistic
(c) infinite measure
(d) uncountable measure
(b) statistic

Question 5.
A ______ is one where each item in the universe has an equal chance of known opportunity of being selected.
(a) Parameter
(b) random sample
(c) statistic
(d) entire data
(b) random sample

Question 6.
A random sample is a sample selected in such a way that every item in the population has an equal chance of being included ______
(a) Harper
(b) Fisher
(c) Karl Pearson
(d) Dr. Yates
(a) Harper

Question 7.
Which one of the following is probability sampling?
(a) purposive sampling
(b) judgement sampling
(c) simple random sampling
(d) Convenience sampling
(c) simple random sampling

Question 8.
In simple random sampling from a population of units, the probability of drawing any unit at the first draw is ______
(a) $$\frac{n}{\mathrm{N}}$$
(b) $$\frac{1}{\mathrm{N}}$$
(c) $$\frac{N}{\mathrm{n}}$$
(d) 1
(b) $$\frac{1}{\mathrm{N}}$$

Question 9.
In _______ the heterogeneous groups are divided into homogeneous groups.
(a) Non-probability sample
(b) a simple random sample
(c) a stratified random sample
(d) systematic random sample
(c) a stratified random sample

Question 10.
Errors in sampling are of ______
(a) Two types
(b) three types
(c) four types
(d) five types
(a) Two types

Question 11.
The method of obtaining the most likely value of the population parameter using statistic is called ________
(a) estimation
(b) estimator
(c) biased estimate
(d) standard error
(a) estimation

Question 12.
An estimator is a sample statistic used to estimate a ______
(a) population parameter
(b) biased estimate
(c) sample size
(d) census
(a) population parameter

Question 13.
________ is a relative property, which states that one estimator is efficient relative to another.
(a) efficiency
(b) sufficiency
(c) unbiased
(d) consistency
(a) efficiency

Question 14.
If probability P[|$$\bar{\theta}$$ – θ| < ε] → 1µ as n → ∞ for any positive ε then $$\bar{\theta}$$ is said to ______ estimator of θ.
(a) efficient
(b) sufficient
(c) unbiased
(d) consistent
(d) consistent

Question 15.
An estimator is said to be _______ if it contains all the information in the data about the
parameter it estimates.
(a) efficient
(b) sufficient
(c) unbiased
(d) consistent
(b) sufficient

Question 16.
An estimate of a population parameter given by two numbers between which the parameter would be expected to lie is called an _______ interval estimate of the parameter.
(a) point estimate
(b) interval estimation
(c) standard error
(d) confidence
(b) interval estimation

Question 17.
A ________ is a statement or an assertion about the population parameter.
(a) hypothesis
(b) statistic
(c) sample
(d) census
(a) hypothesis

Question 18.
Type I error is ______
(a) Accept H0 when it is true
(b) Accept H0 when it is false
(c) Reject H0 when it is true
(d) Reject H0 when it is false
(c) Reject H0 when it is true

Question 19.
Type II error is ______
(a) Accept H0 when it is wrong
(b) Accept H0 when it is true
(c) Reject H0 when it is true
(d) Reject H0 when it is false
(a) $$\frac{\sigma}{\sqrt{2 n}}$$
(b) $$\frac{\sigma}{n}$$
(c) $$\frac{\sigma}{\sqrt{n}}$$
(d) $$\frac{\sigma^{2}}{\sqrt{n}}$$
(c) $$\frac{\sigma}{\sqrt{n}}$$