Let the probability of getting a tail in the biased coin be x.
∴ P (T) = x
⇒ P (H) = 3x
For a biased coin, P (T) + P (H) = 1
x+3x=1
⇒ 4x=\(\frac{1}{4}\)
∴\(P(T)=\frac{1}{4} and P(H)=\frac{3}{4}\)
When the coin is tossed twice, the sample space is {HH, TT, HT, TH}.
Let X be the random variable representing the number of tails.
∴ P (X = 0) = P (no tail) = P (H) × P (H) =\(\frac{3}{4}X\frac{3}{4}=\frac{9}{16}\)
P (X = 1) = P (one tail) = P (HT) + P (TH)
=\(\frac{3}{4}.\frac{1}{4}+\frac{1}{4}.\frac{3}{4}\)
=\(\frac{3}{16}+\frac{3}{16}\)
=\(\frac{3}{8}\)
P (X = 2) = P (two tails) = P (TT) =\(\frac{1}{4}X\frac{1}{4}=\frac{1}{16}\)
Therefore, the required probability distribution is as follows.
| X | 0 | 1 | 2 |
| P(X) | \(\frac{9}{16}\) | \(\frac{3}{8}\) | \(\frac{1}{16}\) |
A shop selling electronic items sells smartphones of only three reputed companies A, B, and C because chances of their manufacturing a defective smartphone are only 5%, 4%, and 2% respectively. In his inventory, he has 25% smartphones from company A, 35% smartphones from company B, and 40% smartphones from company C.
A person buys a smartphone from this shop
(i) Find the probability that it was defective.
“One of these days you’re going to talk yourself into a load of trouble,” her father said aggressively. What do you learn about Sophie’s father from these lines? (Going Places)


A random variable is a variable whose value is unknown or a function that assigns values to each of an experiment's results. Random variables are often deputed by letters and can be classified as discrete, which are variables that have particular values, or continuous, which are variables that can have any values within a continuous range.
Random variables are often used in econometric or regression analysis to ascertain statistical relationships among one another.
There are two types of random variables, such as: