Answer:
The probability distribution of X is:
![P(x=0)=0.0625\\\\P(x=1)=0.25\\\\P(x=2)=0.375\\\\P(x=3)=0.25\\\\P(x=4)=0.0625\\\\](https://tex.z-dn.net/?f=P%28x%3D0%29%3D0.0625%5C%5C%5C%5CP%28x%3D1%29%3D0.25%5C%5C%5C%5CP%28x%3D2%29%3D0.375%5C%5C%5C%5CP%28x%3D3%29%3D0.25%5C%5C%5C%5CP%28x%3D4%29%3D0.0625%5C%5C%5C%5C)
Step-by-step explanation:
"Tossing a coin and getting H" can be modelled as a Bernoulli random variable. The variable X is a sum of 4 of this Bernoulli variables, we can model X as a binomial random variable, with p=0.5 and n=4.
The values X can take are: 0, 1, 2, 3 and 4.
The values of this probability are calculated as:
![P(x=0) = \binom{4}{0} p^{0}q^{4}=1*1*0.0625=0.0625\\\\P(x=1) = \binom{4}{1} p^{1}q^{3}=4*0.5*0.125=0.25\\\\P(x=2) = \binom{4}{2} p^{2}q^{2}=6*0.25*0.25=0.375\\\\P(x=3) = \binom{4}{3} p^{3}q^{1}=4*0.125*0.5=0.25\\\\P(x=4) = \binom{4}{4} p^{4}q^{0}=1*0.0625*1=0.0625\\\\](https://tex.z-dn.net/?f=P%28x%3D0%29%20%3D%20%5Cbinom%7B4%7D%7B0%7D%20p%5E%7B0%7Dq%5E%7B4%7D%3D1%2A1%2A0.0625%3D0.0625%5C%5C%5C%5CP%28x%3D1%29%20%3D%20%5Cbinom%7B4%7D%7B1%7D%20p%5E%7B1%7Dq%5E%7B3%7D%3D4%2A0.5%2A0.125%3D0.25%5C%5C%5C%5CP%28x%3D2%29%20%3D%20%5Cbinom%7B4%7D%7B2%7D%20p%5E%7B2%7Dq%5E%7B2%7D%3D6%2A0.25%2A0.25%3D0.375%5C%5C%5C%5CP%28x%3D3%29%20%3D%20%5Cbinom%7B4%7D%7B3%7D%20p%5E%7B3%7Dq%5E%7B1%7D%3D4%2A0.125%2A0.5%3D0.25%5C%5C%5C%5CP%28x%3D4%29%20%3D%20%5Cbinom%7B4%7D%7B4%7D%20p%5E%7B4%7Dq%5E%7B0%7D%3D1%2A0.0625%2A1%3D0.0625%5C%5C%5C%5C)
Where
p: is the probability of tossing a coin and getting a Heads
q: is the probability of tossing a coin and not getting a Heads.
The binomial number is a way to calculate the possible combinations of getting a certain amount of heads.
For example, in 4 tosses, there are 6 ways or combinations of getting 2 heads and 2 tails:
![\binom{4}{2}=\frac{4!}{2!(4-2)!}=\frac{24}{2*2}=6](https://tex.z-dn.net/?f=%5Cbinom%7B4%7D%7B2%7D%3D%5Cfrac%7B4%21%7D%7B2%21%284-2%29%21%7D%3D%5Cfrac%7B24%7D%7B2%2A2%7D%3D6)