Solved Probability Questions with Answers

This post is about some solved probability questions. These questions make use of (i) the Addition Law of Probabilities, and (ii) the Multiplication Law of Probabilities.

Solved Probability Questions

Question 1: Box A contains 5 Green and 7 Red balls. Box B contains 3 Green, 3 Red, and 6 Yellow balls. A box is selected at random, and a ball is drawn at random from it. What is the probability that the bill drawn is green?

Solution:

Box A

Total Balls: 5 + 7 = 12
Prob(Green) = $\frac{3}{12}$

Box B

Total Balls: 3 + 3 + 6 = 12
P(Green) = $\frac{3}{12} = \frac{1}{4}$

$$P(A+B) = P(A) + P(B) = \frac{5}{12} + \frac{3}{12} = \frac{8}{12} = \frac{2}{3}$$

Question 2: A pair of fair dice is thrown twice. What is the probability of getting a total of 5 or 11?

Solution:

\begin{align*}
P(X = 11 \,\, or X = 5) &= P(X=11) + P(X=15) – P(X=11\,\,and\,\, X=5)\\
P(X=11) &= \frac{2}{36}\\
P(X=5) &= \frac{4}{36}=\frac{1}{9}\\
P(X=11\,\, and X=5) &= 0
\end{align*}

Therefore,

\begin{align*}
P(X=11\,\, or X=5) &= P(X=11) + P(X=5) \\
&=\frac{2}{36} + \frac{1}{9} = \frac{1}{6}
\end{align*}

Note that $P(X=11\,\, and X=5) = 0$, because the sum of two dice cannot be at the same time 5 and 11.

Question 3: A marble is drawn at random from a box containing 10 red, 30 white, 20 blue, and 15 orange marbles. What is the probability that it is (i) orange or red (ii) not red or blue (iii) not blue, (iv) white, (v) red, white, or blue.

Solution:

Total number of balls = 10 + 30 + 20 + 15 = 75
Number of Orange balls = 15
Number of Blue balls = 20
Number of White balls = 30
Number of Red balls = 10

  1. P(a marble drawn is red or orange) = P(Red marble) + P(Orange marble)
    $$=\frac{10}{75} + \frac{15}{75} = \frac{1}{3}$$
  2. P(a marble drawn is not red or blue) = P(not Red) + P(Blue) – P(Blue and not Red)
    $$=\frac{65}{75} + \frac{20}{75} – \frac{20}{75} = \frac{65}{75}$$
  3. P(a ball drawn is not Blue) = $1 – P(Blue) = 1 – \frac{20}{75} = 0.733$
  4. P(a ball drawn is white) = $\frac{30}{75}$
  5. P(a ball drawn is Red, White, or Blue) = P(Red) + P(White) + P(Blue)
    $$=\frac{10}{75} + \frac{30}{75} + \frac{20}{75} = \frac{60}{75}$$

Question 4: If two dice are thrown what are the various total number of dots that may turn up? What are the probabilities of each of them? What is the probability that the number of dots will total at least four?

Solution:

When two dice are thrown together, the minimum total number of dots is 2 (1, 1), and the maximum dots possible are 12 (6, 6). Therefore

  • Probability of 2 dots (1, 1) = $\frac{1}{36}$
  • Probability of 3 dots {(2, 1), (1, 2)} = $\frac{2}{36} = \frac{1}{18}$
  • Probability of 4 dots {(2,2) (3,1) (1,3)} = $\frac{3}{36} = \frac{1}{12}$
  • Probability of 5 dots {(4,1) (1,4) (2,3) (3,2)} = $\frac{4}{36} = \frac{1}{9}$
  • {Probability of 6 dots {(3,3) (4,2) (2,4) (5,1) (5,1)} = $\frac{5}{36}$
  • Probability of 7 dots {(4,3) (3,4) (5,2) (2,5) (6,1) (1,6)} = $\frac{6}{36} = \frac{1}{6}$
  • Probability of 8 dots {(6,2) (2,6) (5,3) (3,5) (4,4)} = $\frac{5}{36}$
  • Probability of 9 {(5,4) (4,5) (6,3) (3,6)} dots = $\frac{4}{36} = \frac{1}{9}$
  • Probability of 10 dots {(5,5) (6,4) (4,6)} = $\frac{3}{36} = \frac{1}{2}$
  • Probability of 11 dots {(5,6) (6,5)} = \frac{2}{36} = \frac{1}{18}$
  • Probability of 12 dots {(6,6)} = $\frac{1}{36}$
  • Probability that the number of dots will total at least 4 = $\frac{33}{36}$

Question 5: A one card is selected at random from a deck of 52 playing cards. What is the probability that the card is a club or a face card or both?

Solution:

\begin{align*}
P(club\,\, or\,\, face\,\, or\,\, both) &= P(club) + P(face) – P(club\,\, and\,\, face)\\
&=\frac{13}{52} + \frac{12}{52} – \frac{3}{52} = \frac{11}{26}
\end{align*}

Question 6: A class contains 10 men and 20 women of which half men and half women have brown eyes. What is the probability that a person chosen at random is a man or has brown eyes?

Solution:

Let $A$ be the event that it is a man (10 out of 30)
Let $B$ be the event that the person has brown eyes (5 men and 10 women: 15 out of 30)

$P(A\cap B)$ is a man AND has brown eyes $\frac{5}{30}$

\begin{align*}
P(A \cup B) &= P(A) + P(B) – P(A \cap B)\\
&= \frac{10}{30} + \frac{15}{30} – \frac{5}{30} = \frac{2}{3}
\end{align*}

Question 7: A drawer contains 50 bolts and 150 nuts. Half of the bolts and half of the nuts are rested. If one item is chosen at random, what is the probability that it is rusted or is a bolt?

Solution:

Number of Bolts = 50
NUmber of Nuts = 150
Total number of Items = 50 + 150 = 200

Item chosen is rusted: $P(A) = \frac{100}{200} = \frac{1}{2}$
Item chosen is bolt: $P(B) = \frac{50}{200} = \frac{1}{4}$
Ite is Rusted and Bolt = $P(A\cap B) = P(A) \cdot P(B) = \frac{1}{2}\cdot \frac{1}{4} = \frac{1}{8}$

\begin{align*}
P(A \cup B) &= P(A) + P(B) – P(A\cap B) \\
&= \frac{1}{2} + \frac{1}{4} – \frac{1}{8} = \frac{5}{8}
\end{align*}

Solved Probability Questions with Answers

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MCQs Basic Statistics Quiz 18

This post is about the MCQs Basic Statistics Quiz with Answers. There are 20 multiple-choice questions about the Basics of Statistics, covering measures of central tendency (Mean, Median, Mode, Geometric Mean, and Harmonic Mean), Measures of Dispersion, Deviations, Relationships between different measures of central tendency, Coding Methods for computing Mean, etc. Let us start with the MCQs Basic Statistics Quiz.

Online MCQs about Basic Statistics

1. The coding method is used for calculating

 
 
 
 

2. The arithmetic mean of 5, 9, 12, 15 is

 
 
 
 

3. The appropriate average for calculating the average percentage increase in population is

 
 
 
 

4. The arithmetic mean is affected by

 
 
 
 

5. If 4 is added to all observations in the data then the mean increases by

 
 
 
 

6. The value obtained by dividing the sum of the values by their number is called

 
 
 
 

7. The sum of squares of deviations of the values is least when deviations are taken from

 
 
 
 

8. In the case of an Open-end frequency table, the average cannot be computed accurately

 
 
 
 

9. The coding method is used for calculating

 
 
 
 

10. If $\Sigma (x – 12) = 0$ then $x=$

 
 
 
 

11. The mean of the $n$ natural numbers is

 
 
 
 

12. If the mean is greater than the mode, the distribution is

 
 
 
 

13. One type of average is

 
 
 
 

14. One type of average is

 
 
 
 

15. The sum of absolute deviations of the values is least when deviations are taken from

 
 
 
 

16. The sum of deviations of the values from their means is

 
 
 
 

17. The Geometric Mean of $a$ and $b$ is

 
 
 
 

18. The most central value of an array is called

 
 
 
 

19. The relation between AM, GM, and HM is

 
 
 
 

20. The arithmetic mean of 112, 120, 135, 150, 157 is

 
 
 
 

MCQs Basic Statistics Quiz

  • One type of average is
  • The most central value of an array is called
  • In the case of an Open-end frequency table, the average cannot be computed accurately
  • One type of average is
  • The value obtained by dividing the sum of the values by their number is called
  • The arithmetic mean of 5, 9, 12, 15 is
  • The arithmetic mean of 112, 120, 135, 150, 157 is
  • The appropriate average for calculating the average percentage increase in population is
  • The arithmetic mean is affected by
  • The mean of the $n$ natural numbers is
  • The sum of deviations of the values from their means is
  • The sum of squares of deviations of the values is least when deviations are taken from
  • If the mean is greater than the mode, the distribution is
  • If $\Sigma (x – 12) = 0$ then $x=$
  • The Geometric Mean of $a$ and $b$ is
  • The sum of absolute deviations of the values is least when deviations are taken from
  • The coding method is used for calculating
  • The coding method is used for calculating
  • The relation between AM, GM, and HM is
  • If 4 is added to all observations in the data then the mean increases by
  • One type of average is
  • The most central value of an array is called
  • In the case of an Open-end frequency table, the average cannot be computed accurately
  • One type of average is
  • The value obtained by dividing the sum of the values by their number is called
  • The arithmetic mean of 5, 9, 12, 15 is
  • The arithmetic mean of 112, 120, 135, 150, 157 is
  • The appropriate average for calculating the average percentage increase in population is
  • The arithmetic mean is affected by
  • The mean of the $n$ natural numbers is
  • The sum of deviations of the values from their means is
  • The sum of squares of deviations of the values is least when deviations are taken from
  • If the mean is greater than the mode, the distribution is
  • If $\Sigma (x – 12) = 0$ then $x=$
  • The Geometric Mean of $a$ and $b$ is
  • The sum of absolute deviations of the values is least when deviations are taken from
  • The coding method is used for calculating
  • The coding method is used for calculating
  • The relation between AM, GM, and HM is
  • If 4 is added to all observations in the data then the mean increases by
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MCQs Discrete Probability Distributions 7

The post is about MCQs Discrete Probability Distributions. There are 20 multiple-choice questions about discrete probability distributions covering distributions such as Binomial Probability Distribution, Bernoulli Probability Distribution, Poisson Probability Distribution, Poisson Probability, Distribution, Geometric Probability Distribution, and Hypergeometric Probability Distribution. Let us start with the MCQs Discrete Probability Distributions Quiz.

Please go to MCQs Discrete Probability Distributions 7 to view the test

MCQs Discrete Probability Distributions

  • For a binomial distribution which of the following is true
  • The number of possible outcomes in a Bernoulli trial is
  • The mean and mode of the Binomial distribution are equal if
  • The hypergeometric random variable is a
  • The parameters of hypergeometric distribution are
  • The probability of success changes from trial to trial in
  • The probability of success does not change from trial to trial in
  • The successive trials are without replacement in
  • Which of the following could never be described by the Binomial distribution?
  • If $X$ is the number of trials for the negative binomial distribution with parameters $p$ and $k$ then its minimum value is
  • For a given binomial distribution with $n$ fixed if $p=0.5$ then
  • The necessary and sufficient condition of the hypergeometric distribution is
  • Which of the following is the most reasonable condition for the binomial approximation to the hypergeometric distribution?
  • Suppose, we have a Poisson distribution with $\lambda$ equal to 2 then the probability of having exactly 10 occurrences is
  • Which of the following is a characteristic of the probability distribution for any random variable
  • In what case would the Poisson distribution be a good approximation of the binomial distribution
  • The mode of the geometric distribution is
  • The binomial distribution may be approximated by a Poisson distribution if
  • In a Binomial distribution, if $n$ is the number of trials and $p$ is the probability of success, then the mean value is given by
  • In a binomial probability distribution, the sum of the probability of failure and the probability of success is always
MCQs Discrete Probability Distributions

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Quartile Deviation (2025)

Quartile deviation denoted by QD is the absolute measure of dispersion and it is defined as the half of the difference between the upper quartile ($Q_3$) and the lower quartile ($Q_1$).

The Quartile Deviation also known as semi-interquartile range (Semi IQR), is a measure of dispersion that focuses on the middle 50% of the data. It is calculated as half the difference between the Third Quartile ($Q_3$) and the First Quartile ($Q_1$). One can write it mathematically as

$$QD = \frac{Q_3-Q_1}{2}$$

Note that the interquartile range is only the difference between the upper quartile ($Q_3$) and the lower quartile ($Q_1$), that is,

$$Interquartile\,\, Range = IRQ = Q_3 – Q_1$$

The Relative Measure of Quartile Deviation is the Coefficient of Quartile Deviation and is given as

$$Coefficient\,\,of\,\,QD = \frac{Q_3 – Q_1}{Q_3 + Q_1}\times 100$$

Quartile Deviation

When to Use QD

  • When dealing with skewed data or data with outliers.
  • When a quick and easy measure of dispersion is needed.

Interpretation QD

Spread: A larger quartile deviation indicates greater variability in the middle portion of the data.
Outliers: QD is less sensitive to extreme values (outliers) compared to the standard deviation.

Quartile Deviation for Ungrouped Data

222225253030303131333639
404042424848505152555759
818689899091919192939393
939494949596969697979898
999999100100100101101102102102102
102103103104104104105106106106107108
108108109109109110111112112113113113
113114115116116117117117118118119121

The above data is already sorted and there are a total of 96 observations. The first and third quartiles of the data can be computed as follows:

$Q_1 = \left(\frac{n}{4}\right)th$ value $= \left(\frac{96}{4}\right)th$ value $= 24th$ value. The 24th observation is 59, therefore, $Q_1=59$.

$Q_3 = \left(\frac{3n}{4}\right)th$ value $= \left(\frac{3\times 96}{4}\right)th$ value $= 72th$ value. The 72nd observation is 108, therefore, $Q_3=108$.

The quartile deviation will be

$$QD=\frac{Q_3 – Q_1}{2} = \frac{108-59}{2} = 24.5$$

The Interquartile Range $= IQR = Q_3 – Q_1 = 108 – 59 = 49$

The coefficient of Quantile Deviation will be

$$Coefficient\,\, of\,\, QD = \frac{Q_3 – Q_1}{Q_3 – Q_1}\times 100 = \frac{108-59}{108+59}\times 100 = 29.34\%$$

Quartile Deviation for Grouped Data

Consider the following example for grouped data to compute the quartile deviation.

ClassesFrequenciesClass BoundariesCF
11-14.91110.95-14.9511
15-20.91914.95-20.9530
21-24.92120.95-24.9551
25-30.93424.95-30.9585
31-34.91630.95-34.95101
35-40.9934.95-40.95110
41-44.9440.95-44.95114
Total114  

The first and third quartiles for the above-grouped data will be

\begin{align*}
Q_1 &= l + \frac{h}{f}\left(\frac{n}{4} – C\right)\\
&= 14.95 + \frac{6}{19}\left(\frac{114}{4} – 11\right)\\
&= 14.95 + \frac{6}{19}(28.5 – 11) = 20.48\\
Q_3 &= l + \frac{h}{f}\left(\frac{3\times 114}{4}-85\right)\\
&=30.95 + 0.187418 = 31.14
\end{align*}

The QD is

$$QD = \frac{Q_3 – Q_1}{2} = \frac{31.14 – 20.48}{2} = \frac{10.66}{2} = 5.33$$

The Interquartile Range will be

$$IQR = Q_3 – Q_1 = 31.14 – 20.48 = 10.66$$

The coefficient of quartile deviation is

$$Coefficient\,\,of\,\, QD = \frac{Q_3 – Q_1}{Q_3 + Q_1}\times 100 = \frac{31.14 – 20.48}{31.14+20.48}\times 100 = 20.65\%$$

  • Less affected by outliers: Makes it suitable for skewed data.
  • Easy to calculate: Relatively simple compared to standard deviation.

Disadvantages of QD

  • Ignores extreme values: This may not provide a complete picture of the data’s spread.
  • Less sensitive to changes in data: Compared to standard deviation.

In summary, Quartile deviation is a valuable and useful tool for understanding the spread of data, particularly when outliers are present. By focusing on the middle 50% of the data, it provides a robust measure of dispersion that is less sensitive to extreme values. However, it is important to consider its limitations, such as its insensitivity to outliers and changes in data.

Frequently Asked Questions about Quartile Deviation

  1. What is quartile deviation?
  2. What are the advantages of QD?
  3. What are the disadvantages of QD?
  4. What is IQR?
  5. What is Semi-IQR?
  6. How QD is interpreted?
  7. How QD is computed for grouped and ungrouped data?
  8. When QD should be used?

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