# STA301-Statistics and Probability Quiz MCQs Lecture 23-45 Finalterm Objective Questions | SUPERSTARWEBTECH

STA301-Statistics and Probability Quiz  MCQS #Objective #Questions #Finalterm
1. Which of the following is the property of hypergeometric experiment?
• p remains constant from trial to trial
• successive trials are independent
• sampling is performed without replacement
• n is not fixed
2. If the first-moment ratio is less than 0, then the distribution will be:
• positively skewed
• symmetrical
• negatively skewed
• None
3. Poisson distribution can be used to approximate the hypergeometric distribution when:
• p>0.05
• p<0.05
• p>0.10
• p<0.10
4. ___ is used when we are dealing with proportions to find the probabilities:
• Normal distribution
• t-distribution
• Both Z & t distribution
• F distribution
5. Total no. of possible samples of size 3 (with replacement) from the population of size 6, will be:
• 256
• 196
• 216
• 325
6. In sampling from a large population with sigma=20, the standard error of the mean is found to be 2. The size of the sample used is:
• 100
• 40
• 10
• 20
7. In sampling from a large population with σ=60. The size of the sample used is 100, the value of the standard error will be:
• 4
• 42
• 15
• 6
8. The number of parameters in a normal distribution is(are):
• 1
• 2
• 3
• 4
9. In hypergeometric distribution probability of success always:
• is constant from trial to trial
• varies from trial to trial
• sometimes varies and sometimes is constant
• None
10. In hypergeometric distribution; experiment can be repeated a
• fixed number of times
• variable number of times
• depends upon the situation
• None
11. In a binomial experiment, the probability of success changes on
• Each trial
• Second trial
• 10th trial
• 30th trial
12. The range of the binomial distribution is:
• 0, 1, 2, … , 100
• 0, 1, 2, …, n
• 0, 1, 2, …, x
• 1, 2, …, n
13. The number of typing errors per page in a book follows.
• Normal Distribution
• Poisson process
• Binomial distribution
• Hypergeometric distribution
14. The central limit theorem states that the mean of the sampling distribution of the means is equal to the population
• Standard deviation
• Standard error
• Random error
• Mean