Answer:
Discrete probability distribution
X 0 1 2 3 4
P(X=x) 1/16 4/16 6/16 4/16 1/16
Step-by-step explanation:
<u>Discrete Random variable</u>:-
A random variable X which can take only a finite number of discrete values
In an interval domain is called a discrete random variable. In other words
a real valued function defined on a discrete sample space is called a
Discrete Random variable.
For example : X(s) = { s: s = 0, 1, 2} The random variable X is a discrete Random variable.
Given the number of heads in 4 tosses of a coin
The total number of possible events is n(S) = 2^4 = 16
<u>Discrete distribution</u><u>:</u>-
The random variable X is a discrete Random variable.
X(x) = { x: x = 0, 1, 2,3,4}
Here x=0 means → no heads that is the possible outcomes are only one
n(E) = {T,T,T,T} = 1
P(X=0) = 
Here x=1 means → one head and three tails that is the possible outcomes are '4'
n(E) ={( HTTT),(THTT),(TTHT),(TTTH)

Here x=2means → TWO head and TWO tails that is the possible outcomes are '6'
n(E) = {( HHTT),(THHT),(TTHH),(HTTH),(THTH),(HTHT)
n(E) = 6


Here x=3means → three head and one tails that is the possible outcomes are '4'
n(E) = { HHHT,HTHH,HHTH,THHH} =3

Here x=4 means → FOUR heads that is the possible outcomes are only one
n(E) = {HHHH} = 1

<u>Final answer:</u>-
Discrete probability distribution
X 0 1 2 3 4
P(X=x) 1/16 4/16 6/16 4/16 1/16