# STA301 Solved MCQs For Final Term 2024

Students if you are looking for STA301 Solved MCQs For Final Term if yes? then you reach the right place where you can easily find the MCQs for the final term exams where students can easily complete their final term STA301 exams preparation.

Students you know these are Statistics and Probability MCQs for the virtual university students who have this book STA301 and their students looking for the Final term MCQs.

## STA301 Solved MCQs For Final Term

1: A failing student is passed by an examiner. It is an example of:

No information regarding student exams
Type I error
Type II error
Correct decision

2: A confidence interval has a specified probability_ of containing the true value of the parameter.

α
1-a
1+a
a/2

3: Which of the following relationship exist between the sampling distribution of samples mean and the sampling distribution samples median?

Both of these
Var(mean)<Var(median)
None of these
Var(median)< Var(median)

4: An estimator is always a:

Random variable
Statistic and Random variable
Statistic
Parameter

5: To test the hypothesis about the difference of means for large samples, what test statistic will be used?

F
T
Z
Chi-square

6: If a significance level of 5% is used rather than 1%, the r II hypothesis is:

None of these
Just as likely to be rejected
Less likely to be rejected
More likely to be rejected

7: The test statistic to test the U1 = U2 (U represents the mean of the population)for a normal population when n>30

T-Test
F-Test
All of Above
Z-Test

8: The total no. of possible samples of size 2 (without replacement) from the population of size 6, will be:

10
18
20
15

9: ……………are equivalent.

Type-II error and Level of confidence
Type-I error and Level of significance
Type-I error and Level of confidence
Type-II error and Level of significance

10: The test statistic is used to decide whether to hull the hypothesis.

None of these
Reject
Accept or Reject
Accept

11: An estimator is said to be efficient if it has

None of these
Unbiased estimate
Both (a) & (b)
Smallest Variance

12: In general, the estimators obtained by the method of moments are…………

Inefficient
All the above
Biased
Inconsistent

13: A statistic whose standard deviation decreases with an increase in sample size will be called:

Sufficient
Unbiased
Efficient
Consistent

14: For a particular hypothesis test, Alpha=0.09 and |Beta=0.03, what is the value of Type I error?

0.91
0.09
0.03
0.97

15: From which of the following methods we can obtain a point estimate of the population parameters?

Maximum Likelihood Method
All of the above
Method of Moments
Method of Least Squares

16: A random sample of n=25 values gives a sample mean of 83. Can this sample be regarded as drawn from a normal population with μ= 80 and s= 7? In this question the alternative hypothesis will be:

H1: μ = 80
H1: μ> 80
H1: μ 80
H1: μ <80

17: Consider a large population with a mean of 160 and a standard deviation of 20. A random sample of size 64 is taken from this population. What is the standard deviation of the sample mean?

2.500
3.125
1.654
3.568

18: The standard deviation of the sampling distribution of proportion is:

n/p
P
q/n
✓(pq/n)

19: For a particular hypothesis test, Alpha=0.07 and Beta=0.05. What is the level of significance?

0.05
0.93
0.07
0.95

20: The relative efficiency of T1 compared to T2 where:

T1 is an unbiased estimator
T2 is an unbiased estimator
both T1 and T2 are unbiased estimators
both T1 and T2 are biased estimators

21: If we are testing HO: mean = 50 against H1: mean < 50 then the rejection region will be

on both sides
on the right side of the mean
in the center
on the left side of the mean

22: Conventionally, the probability of making a type-l error is denoted by which of the following symbols?

a (alpha)
s (sigma)
B (beta)
? (theta)

23: How can we interpret the 90% confidence interval for the mean of the normal population?

There are 10% chance of falling true value of the O parameter
There are 100% chances of falling true value of the O parameter
There is a 90% chance of falling the true parameter
There are 90% chance of falling true value of the O parameter

24: Ideally, the width of the confidence interval should be

98
100
0
1

25: Total no. of possible samples of size 3 (with replacement from the population of size 6, will be:

196
256
216
325

26: Interval estimation and confidence interval are:

Same
Independent
Different
Opposite

27: If a significance level of 10 % is used rather than 5%, the ll hypothesis is:

None of these
More likely to be rejected
Just as likely to be rejected
Less likely to be rejected

28: A quantity obtained by applying the Cestnin rule or formal is known as a

Estimate
Parameter
Estimator
Proportion

29: From which of the following methods we can obtain an estimate of the population parameters?

Method of Least Squares
All of the above
Method of Moments
Maximum Likelihood Method

30: A standard deviation obtained from the sampling distribution of sample statistics is known as

Universal error
Standard error
Minimum error
Sampling error