You take an exam that contains 20 multiple-choice questions. Each question has 4 possible options. You know the answer to 10 questions, but you have no idea about the other 10 questions so you choose answers randomly. Your score X on the exam is the total number of correct answers. Find the p.m.f. of X. What is P(X > 15)?
Let's define the random variable Y as the number of your correct answers to the 10 questions you answer randomly. Then your total score will be X=Y+10. First, let's find the PMF of Y. For each question, your success probability is 1/4. Hence, you perform 10 independent Bernoulli 1/4 trials and Y is the number of successes. Thus, we conclude
"P_y=(y=(^{10}_{y})(1\/4)^y(3\/4)^{10-y}"
for y=0,1,2,3...10
"P_y=0" otherwise
Now we need to find the PMF of X=Y+10. First note that "R_x=\\{10,11,12...20\\}"
We can write
"P_x(10)=P(x=10)=P(y+10=10)=P(y=0)=(^{10}_{0})(1\/4)^0(3\/4)^{10-0}=(3\/4)^{10}\\\\P(x=11)=P(y+10=11)=P(y=1)=(^{10}{1})(1\/4)^1(3\/4)^{10-1}=10(1\/4)(3\/4)^9"
In general for
"k \\isin R_x=\\{10,11,12...20\\}"
"P_x(k)=P(x=k)=P(y+10=k)=P(y=k-10)=(^{10}_{k-10})(1\/4)^{k-10}(3\/4)^{20-k}"
For k={10,11,12...20}
"P_x(k)=0"
Otherwise
In order to calculate P(X>15), we know we should consider y=6,7,8,9,10
"P_y(y)=(^{10}_y)(1\/4)^y(3\/4)^{10-y}"
For y=6,7,8,9,10
Py(y)=0 otherwise
"P_x(k)=(^{10}_{k-10})(1\/4)^{k-10}(3\/4)^{20-k}"
For k=16,17,18,19,20
"P_x(k)=0" otherwise
"P(X>15)=P_x(16)+P_x(17)+P_x(18)+P_x(19)+P_x(20)=(^{10}_6)(1\/4)^6(3\/4)^4+(^{10}_7)(1\/4)^7(3\/4)^3+(^{10}_8)(1\/4)^8(3\/4)^2+(^{10}_9)(1\/4)^9(3\/4)^1+(^{10}_{10})(1\/4)^{10}(3\/4)^0=0.019727"
Comments
Leave a comment