# ISS (Statistical Services) Statistics Paper III: Questions 12 - 16 of 96

Get 1 year subscription: Access detailed explanations (illustrated with images and videos) to **96** questions. Access all new questions we will add tracking exam-pattern and syllabus changes. View Sample Explanation or View Features.

Rs. 300.00 or

## Question number: 12

» Sampling Techniques » Stratified Random Sampling

Appeared in Year: 2015

### Describe in Detail

What are the advantages of stratified sampling? Consider the allocation of sample size n _{i} of strata given by , where N _{i} is the stratum size, σ _{i} is the within stratum standard deviation of the ith stratum, (i = 1, 2, …, k) and δ real. Write down the expression for the where stands for the unbiased estimator of the population mean of the study variate y based on sample random sample without replacement in each stratum.

### Explanation

In this type of sampling method first the whole population is divided into homogeneous groups under certain criterion. There groups are termed as strata. Many advantage of stratified sampling can be summarized as follows.

(i) if the admissible error is given, small samples is needed which results into a cut

## Question number: 13

» Econometrics » Ordinary Least Squares (OLS)

Appeared in Year: 2015

### Describe in Detail

Describe in detail Indirect Least square method for estimating structural parameters. Is the estimator unbiased and/or consistent?

### Explanation

For a just or exactly identified structural equation, the method of obtaining the estimates of the structural coefficients from the OLS estimates of the reduced-form coefficients is known as the method of indirect least squares (ILS), and the estimates thus obtained are known as the indirect least squares estimates. ILS

## Question number: 14

» Econometrics » Auto-Correlation

Appeared in Year: 2015

### Describe in Detail

Describe exact and near multicollinearity in a regression model. Discuss, along with justification, the effect of these situations on (i) sampling variation and (ii) prediction.

### Explanation

Multicollinearity refers to the existence of a perfect or exact linear relationship among some or all explanatory variables of a regression model. So, there are two types of multicollinearity. They are

1. ** Exact Multicollinearity: ** If exist perfect linear relationship among the explanatory variables then it is treated as exact multicollinearity.

## Question number: 15

» Applied Statistics » Index Numbers » Link and Chain Relatives Composition of Index Numbers

Appeared in Year: 2009

### Write in Short

Explain the time reversal and factor-reversal tests for an ideal index number. Give an example

of index number which satisfies both of these tests.

## Question number: 16

» Applied Statistics » Index Numbers » Income Distribution-Pareto and Engel Curves

Appeared in Year: 2009

### Describe in Detail

State the probability density function of the Pareto distribution and give its cumulative form.

Interpret the constants involved.

### Explanation

**Probability Density Function of the Pareto distribution: **

Suppose that X has the Pareto distribution with shape parameter a∈ (0, ∞) and scale parameter b∈ (0, ∞) then X has probability density function f given by

where is the (necessarily positive) minimum possible value of X, and α is