Unit-4
Probability and Probability Distribution
Question-1: A box contains 4 white and 2 black balls and a second box contains three balls of each colour. Now a bag is selected at random and a ball is drawn randomly from the chosen box. Then what will be the probability that the ball is white?
Sol.
Here we have two mutually exclusive cases-
1. The first bag is chosen
2. The second bag is chosen
The chance of choosing the first bag is 1/2. And if this bag is chosen then the probability of drawing a white ball is 4/6.
So that the probability of drawing a white ball from the first bag is-
And the probability of drawing a white ball from the second bag is-
Here the events are mutually exclusive, then the required probability is-
Question-2: A die is rolled. If the outcome is a number greater than three. What is the probability that it is a prime number?
Sol.
The sample space is- S = {1, 2, 3, 4, 5, 6}
Let A be the event that an outcome is a number that is greater than three and B be the event that it is a prime.
So that-
A = {4, 5, 6} and B = {2, 3, 5} and hence
P(A) = 3/6, P(B) = 3/6 and
Now the required probability-
Question-3: Two male and female candidates appear in an interview for two positions in the same post. The probability that the male candidate is selected is 1/7 and the female candidate selected is 1/5.
What is the probability that-
1. Both of them will be selected
2. Only one of them will be selected
3. None of them will be selected.
Sol.
Here, P (male’s selection) = 1/7
And
P (female’s selection) = 1/5
Then-
1.
2.
3.
Question-4: A factory has two machines A and B making 60% and 40% respectively of the total production. Machine A produces 3% defective items, and B produces 5% defective items. Find the probability that a given defective part came from A.
SOLUTION:We consider the following events:
A: Selected item comes from A.
B: Selected item comes from B.
D: Selected item is defective.
We are looking for a . We know:
Now,
So we need
Since D is the union of the mutually exclusive events and (the entire sample space is the union of the mutually exclusive events A and B)
Question-5: Three urns contain 6 red, 4 black; 4 red, 6 black; 5 red, 5 black balls respectively. One of the urns is selected at random and a ball is drawn from it. If the ball is drawn is red find the probability that it is drawn from the first urn.
Solution:
:The ball is drawn from urnI.
: The ball is drawn from urnII.
: The ball is drawn from urnIII.
R:The ball is red.
We have to find
Since the three urns are equally likely to be selected
Also,
From (i), we have
Question-6: Three urn contains 6 red, 4 black; 4 red, 6 black; 5 red, 5 black balls respectively. One of the urn is selected randomly and a ball is drawn from it.
If the ball drawn is red then find the probability that it is drawn from the first urn.
Sol.
Let,
Now we have to find-
By using Bayes theorem-
=
Here three urns equally likely to be selected-
So that-
And-
So that-
=
Hence the required probability is 2/5.
Question-7: ln a bolt factory machines and manufacturerespectively 25%, 35% and 40% of the total. lf their output 5, 4, and 2 percent are defective bolts. A bolt is drawn at random from theproduct and is found to be defective. What is the probability that it was manufactured by machine B.?
Solution: bolt is manufactured by machine
: bolt is manufactured by machine
: bolt is manufactured by machine
The probability of drawing a defective bolt manufactured by machine is (D/A)
Similarly, (D/B) and (D/C)
By Baye’s theorem
Question-8: If a random variable X has the following probability distribution in the tabular form then what will be the expected value of X.
X | 0 | 1 | 2 |
P(x) | 1/4 | 1/2 | 1/4 |
Sol.
We know that-
So that-
Question-9: In a lottery, m tickets are drawn at a time out of a ticket numbered from 1 to n. Find the expected value of the sum of the numbers on the tickets drawn.
Solution. Let be the variables representing the numbers on the first, second,…nth ticket. The probability of drawing a ticket out of n ticket spelling in each case 1/n, we have
Therefore the expected value of the sum of the numbers on the tickets drawn
Question-10: The probability density function of a variable X is
X | 0 | 1 | 2 | 3 | 4 | 5 | 6 |
P(X) | k | 3k | 5k | 7k | 9k | 11k | 13k |
(i) Find
(ii) What will be e minimum value of k so that
Solution. (i) If X is a random variable then
(ii)Thus minimum value of k=1/30.
Question-11: The overall percentage of failures in a certain examination is 20. If six candidates appear in the examination, what is the probability that at least five pass the examination?
Solution:
Probability of failures
Probability
Probability of at least five passes P(5 or 6)
Question-12: Assuming that 20% of the population of a city are literate, so that the chance of an individual being literate is and assuming that 100 investigators each take 10 individuals to see whether they are literate, how many investigators would you expect 3 or less were literate.
Solution
P (3 or less) = P (0 or 1 or 2 or 3 )
Required number of investigators
approximately
Question-13: In a certain factory producing cycle tyres there is a small chance of 1 in 500 tyres to be defective. The tyres are supplied in lots of 10. Using Poisson distribution calculate the approximate number of lots containing no defective, one defective, and two defective tyres, respectively, in a consignment of 10000 lots.
Solution:
S.No | Probability of defective | Number of lots containing defective |
1 |
| |
2 |
| |
3 |
|
Question-14: The mean inside diameter of a sample of 200 washers produced by a machine is 0.0502 cm and the standard derivation is 0.005 cm. The purpose for which these washers are intended allows a maximum tolerance in the diameter of 0.496 to 0.508 cm, otherwise, the washers are considered defective. Determine the percentage of defective washers produced by the machine, assuming the diameters are normally distributed
Solution:
Area for non-defective washersArea between and
= 2 Area between and
Percentage of defective washers
Question-15: A manufacturer knows from experience that the resistance of resistors he produces is normal with mean and standard deviation What percentage of resistors will have resistance between 98 ohms and 102 ohms?
Solution:
Area between and
(Area between and )+(Area between and )
(Area between and )=20.3413=0.6826
Percentage of resistors having resistance between 98 ohms and 102 ohms =68.26
Question-16: If a random variable X is normally distributed with mean 80 and standard deviation 5, then find-
1. P[X > 95]
2. P[X < 72]
3. P [85 < X <97]
[Note- use the table- area under the normal curve]
Sol.
The standard normal variate is –
Now-
1. X = 95,
So that-
2. X = 72,
So that-
3. X = 85,
X = 97,
So that-
Question-17: The life of electric bulbs is normally distributed with a mean of 8 months and a standard deviation of 2 months.
If 5000 electric bulbs are issued how many bulbs should be expected to need replacement after 12 months?
[Given that P (z ≥ 2) = 0. 0228]
Sol.
Here mean (μ) = 8 and standard deviation = 2
Number of bulbs = 5000
Total months (X) = 12
We know that-
Area (z ≥ 2) = 0.0228
Number of electric bulbs whose life is more than 12 months ( Z> 12)
= 5000 × 0.0228 = 114
Therefore replacement after 12 months = 5000 – 114 = 4886 electric bulbs.
Question-18: A manufacturer of electric bulbs claims that a certain pen manufactured by him has a mean life of at least 460 days. A purchasing officer selects a sample of 100 bulbs and put them on the test. The mean life of the sample found 453 days with a standard deviation of 25 days. Should the purchasing officer reject the manufacturer’s claim at a 1% level of significance?
Sol.
Here the population mean =
Sample size = n = 100
Sample mean =
Sample standard deviation = S = 25
The null and alternative hypotheses will be-
Here alternative hypothesis is left tailed so that the test is left tailed test-
Here population standard deviation is unknown so that we should use a t-test if the life of the bulbs follows a normal distribution.
But it is not the case. Here sample size is 100 which is large.
Note- a sample size of more than 30 is considered a large sample.
So here we use Z-test-
The critical value of Z statistic at a 1% level of significance is = -2.33
Since the calculated value of the test statistic is less than the critical value that means the test statistic lies in the rejection region.
Therefore we reject the null hypothesis.
So that we reject the manufacturer’s claim at a 1% level of significance.
Question-19: A set of five similar coins is tossed 320 times and the result is
Number of heads | 0 | 1 | 2 | 3 | 4 | 5 |
Frequency | 6 | 27 | 72 | 112 | 71 | 32 |
Solution. For v = 5, we have
P, probability of getting a head=1/2;q, probability of getting a tail=1/2.
Hence the theoretical frequencies of getting 0,1,2,3,4,5 heads are the successive terms of the binomial expansion
Thus the theoretical frequencies are 10, 50, 100, 100, 50, 10.
Hence,
Since the calculated value of is much greater than the hypothesis that the data follow the binomial law is rejected.
Question-20: In experiments of pea breeding, the following frequencies of seeds were obtained
Round and yellow | Wrinkled and yellow | Round and green | Wrinkled and green | Total |
316 | 101 | 108 | 32 | 556 |
Theory predicts that the frequencies should be in proportions 9:3:3:1. Examine the correspondence between theory and experiment.
Solution. The corresponding frequencies are
Hence,
For v = 3, we have
Since the calculated value of is much less than there is a very high degree of agreement between theory and experiment.
Question-21: A mechanism is making engine parts with an axle diameter of 0.7 inches. A random sample of 10 parts shows a means diameter of 0.742 inches with a standard deviation of 0.04 inches. Based on this sample would you say that the work is inferior?
Solution. Here we have,
Taking the hypothesis that the product is not inferior that is there is no significant difference between and μ.
Degree of freedom = 10-1=9
For we get from table IV,
As the calculated value of the value of t is significant at a 5% level of significance. This implies that differs significantly from μ and the hypothesis is rejected. Hence the work is inferior. The work is inferior even at a 2% level of significance.
Question-22: One type of aircraft is found to develop engine trouble in 5 flights out of a total of hundred and another type in 7 flights out of a total of 200 flights. is there a significant difference in the two types of aircraft so as far as engine defects are concerned.
Solution. number of troubled flights =5
200 flights, number of troubled flights
e=0.0254
z<1, the difference is not significant.
Question-23: From a random sample of 10 pigs fed on diet A. The increase in weight in a certain period were 10, 6, 16, 17, 13, 12, 8, 14, 15, 9 lbs. For another random sample of 12 pig’s fat on diet B, the increases in the same period were 7, 13, 22, 15, 12, 14, 18, 8, 21, 23, 10, 17 lbs. Test whether diets A and B differ significantly as regards their effects on weight increases?
Solution. We calculate the means and standard deviation of the samples as follows
| Diet A |
|
| Diet B |
|
10 | -2 | 4 | 7 | -8 | 64 |
6 | -6 | 36 | 18 | -2 | 4 |
16 | 4 | 16 | 22 | 7 | 49 |
17 | 5 | 25 | 15 | 0 | 0 |
13 | 1 | 1 | 12 | -3 | 9 |
12 | 0 | 0 | 14 | -1 | 1 |
8 | -4 | 16 | 18 | 3 | 9 |
14 | 2 | 4 | 8 | -7 | 49 |
15 | 3 | 9 | 21 | 6 | 36 |
9 | -3 | 9 | 23 | 8 | 64 |
|
|
| 10 | -5 | 25 |
|
|
| 23 | 2 | 4 |
120 | 0 | 120 | 10 | 0 | 314 |
Assuming that the samples do not differ in weight so far as two diets are concerned i.e.
Hence,
Here,
For
The calculated value of
Hence the difference between the sample means is not significant that is the two diets do not differ significantly as regards their effects on the increase in weight.