Answer:
Check the explanation
Explanation:
The odds are 4 to 1 against, so we can estimate the probability of success (p) as
![(p)/(q)=(p)/(1-p)=(1)/(4)\\\\4p=1-p\\\\5p=1\\\\p=0.2](https://img.qammunity.org/2021/formulas/mathematics/college/q6xabe9p2is7puojo7wr1pu9tnz5i4sbbn.png)
The expected pay for every success is 3 to 1, so we lose $1 for every lose and we gain $3 for every win.
The number of winnings in the 100 rounds to be even can be calculated as:
![W+L=100\\\\L=100-W\\\\\\Payoff=0=3*W-1*L=3W-1*(100-W)=3W+W-100\\\\0=4W-100\\\\W=25](https://img.qammunity.org/2021/formulas/mathematics/college/4hiaoqnqh6guqalxl4q62zrco7hszg2ydp.png)
We have to win at least 25 rounds to have a positive payoff.
As the number of rounds is big, we will approximate the binomial distribution to a normal distribution with parameters:
![\mu=np=100*0.2=20\\\\\ \sigma=โ(npq)=โ(100*0.2*0.8)=4](https://img.qammunity.org/2021/formulas/mathematics/college/17vamitt52xx591a05ju0vhvgzskhob04l.png)
The z-value for x=25 is
![z=(X-\mu)/(\sigma)=(25-20)/(4)=1.25](https://img.qammunity.org/2021/formulas/mathematics/college/g6defmgd58xk5p6xshjg6e86m6sju2767d.png)
The probability of z>1.25 is
P(X>25)=P(z>1.25)=0.10565
There is a 10.5% chance of having a positive payoff.
NOTE: if we do all the calculations for the binomial distribution, the chances of having a net payoff are 13.1%.