# ISS (Statistical Services) Statistics Paper II (New 2016 MCQ Pattern): Questions 239 - 243 of 253

Access detailed explanations (illustrated with images and videos) to 253 questions. Access all new questions- tracking exam pattern and syllabus. View the complete topic-wise distribution of questions. Unlimited Access, Unlimited Time, on Unlimited Devices!

View Sample Explanation or View Features.

Rs. 200.00 -OR-

How to register? Already Subscribed?

## Question 239

### Question

MCQ▾

The denominator in the Cramer-Rao inequality is known as

### Choices

Choice (4)Response

a.

Information Limit

b.

Upper bound of the Variance

c.

Lower Bound of the variance

d.

All of the above

## Question 240

### Question

MCQ▾

Suppose we want to find out the mean milk yield of the cows in India, a survey of 66831 cows was made and the mean milk yield was 12.5 liter with a standard deviation of 4.3 liter. Then the 95 % confidence interval for the average milk yield is

### Choices

Choice (4)Response

a.

b.

c.

d.

## Question 241

### Question

MCQ▾

For a normal population , the variance of the sample mean and sample variance are given by and . Then which of the following is true?

### Choices

Choice (4)Response

a.

Sample mean is more efficient estimator for than the sample median

b.

Sample median is more efficient estimator for than the sample mean

c.

Sample mean and Sample median are efficient

d.

All of the above

## Question 242

### Question

MCQ▾

A Statistical Hypothesis, which does not specifies the population completely, is known as

### Choices

Choice (4)Response

a.

Composite Hypothesis

b.

Simple Hypothesis

c.

Null Hypothesis

d.

Alternative Hypothesis

## Question 243

### Question

MCQ▾

Which of the definition is true for Sufficiency of an estimator?

### Choices

Choice (4)Response

a.

If is a estimator of parameter based on a sample of size n from the population with density such that the conditional distribution of given T is independent of then T is sufficient estimator of .

b.

An estimator is said to be sufficient for if it provides all the information contained in the sample about the parametric function

c.

A statistic is sufficient estimator of parameter if and only if the likelihood function (joint p. d. f. of the sample) can be expressed as where is the p. d. f. of statistic and is a function of sample observations only independent of

d.

All a., b. and c. are correct