STAT213
Tutorial sheet #4 Solutions
Question 1
Each probability is between 0 and 1 and they sum to 1.
Question 2
m = 1(0.691) + 2(0.178) + 3(0.049) = 1.194
E(X2)
= 1(0.691) + 4(0.178) + 9(0.049) = 1.844; s2 = 1.844 – 1.1942 = 0.418364; s = sqrt(0.418364) = 0.6468
Question 3
We need m-2s = 1.194 – 2(0.6468) = -0.1 as well
as m+2s = 2.5. The only values of the
distribution that lie between these limits are 0, 1 and 2. P(0)
+ P(1) +P(2) = 8.2% + 69.1% + 17.8% = 95.1% which is well above the threshold
of 75% under Chebyshev’s Theorem.
Question 4
Using
Minitab, since we want P(2), we choose the probability
radio button in the binomial dialogue box. The number of trials is 20, the
probability of success is 0.05 and the input constant is 2. P(2)
= 0.1887 = 18.87%
Question 5
Using Minitab, since we want P(no more than 1), we choose the cumulative
probability radio button and the input constant is 1. P(no
more than 1) = 0.7359 = 73.59%
Question 6
P(at
least 2) = 100% - P(no more than 1) = 100% - 73.59% = 26.41%
Question 7
The number
of trials = n = 5x20 = 100. Then m = 100(0.05) = 5; s = sqrt(5(0.95)) = 2.18; m + 3s = 11.54 which rounds to 12. The
maximum commission is 12 x $450 = $5400.
Question 8
m = 500(1/5000) = 0.1. Using Minitab,
since we want P(0), we choose the probability radio
button in the Poisson dialogue box. The mean is 0.1 and the input constant is
zero. P(0) = 0.9048 = 90.48%
Question 9
If m = 0.1 for one shift, then m = 0.3 for three shifts. Note that P(at least 1) = 1 – P(0). Using Minitab as with the previous
question (except with the mean equal to 0.3), P(0) =
0.7408 = 74.08%. So, P(at least 1) = 100% - 74.08% =
25.92%
Question 10
If m = 0.3 for one day, then m = 2.1 for seven days. Using Minitab, since we
want P(no more than 6), we choose the cumulative
probability radio button, the mean is 2.1 and the input constant is 6. P(no more than 6) = 0.9942 = 99.42% which is the probability
of having no more than 6 scrap gears in a 7-day period. This appears to be a
realistic expectation.
Question 11
As mentioned in the previous question, m = 2.1. Then s = sqrt(2.1) = 1.45; m + 3s = 6.45 which we can round to 6.
As we see
in the previous question, the probability of having no more than 6 scrap gears
in a 7-day period is 99.42%. This is clearly higher than the 88.9% probability
under Chebyshev’s theorem.
Question 12
m = 0.5. Then P(0)
= 60.65%
Question 13
m = 3; P(at
least 2) = 100% - P(fewer than 2) = 100% - P(no more than 1) = 100% - 19.91% =
80.09%
Question 14
m = 6. Then s = sqrt(6) = 2.45; m + 3s = 13.35 which we can round to 13. P(no more than 13) = 99.64%
Question 15
The first thing is to construct a crosstab letting cell phone = x and blackberry = y:
|
x | y |
0 |
1 |
Total |
|
0 |
0.02 |
0.03 |
0.05 |
|
1 |
0.09 |
0.86 |
0.95 |
|
Total |
0.11 |
0.89 |
1.0 |
mx = 0.95; E(X2) = 0.95; sx2 = 0.95 – 0.952 = 0.0475
my = 0.89; E(Y2)
= 0.89; sy2 = 0.89 – 0.892 = 0.0979
E(XY) =
0.86; Cov(X,Y) = 0.86 – (0.95)(0.89) = 0.0145
So mx + my = 0.95 + 0.89 = 1.84;
Var(X+Y)
= 0.0475 + 0.0979 + 2(0.0145) = 0.1744; Stdev(X+Y) = sqrt(0.1744)
= 0.4176;
r2
= 0.01452/[(0.0475)(0.0979)] = 4.52%