Answer:
0.0177 = 1.77% probability that the first defect is caused by the seventh component tested.
The expected number of components tested before a defective component is found is 50, with a variance of 0.0208.
Step-by-step explanation:
Assume that the probability of a defective computer component is 0.02. Components are randomly selected. Find the probability that the first defect is caused by the seventh component tested.
First six not defective, each with 0.98 probability.
7th defective, with 0.02 probability. So
0.0177 = 1.77% probability that the first defect is caused by the seventh component tested.
Find the expected number and variance of the number of components tested before a defective component is found.
Inverse binomial distribution, with
Expected number before 1 defective(n = 1). So
Variance is:
The expected number of components tested before a defective component is found is 50, with a variance of 0.0208.
Answer: (0,0)
Step-by-step explanation:
got it correct
Answer:
The ordered pair is not a solution as both sides of the equation do not equal each other.
Step-by-step explanation:
(3,2); x + 6y = 13
(3) + 6(2) = 13
3 + 12 = 13
15 = 13
Step-by-step explanation:
Substitute X for the amount Annie spent
4x-$64 = 100
4x = $164
x = $164/4
x = $41
Mean: $620, Mode: $600
Let's sort the rank stats.
First quartile: $580
Median: $610
Third quartile: $645
85th percentile: $685
OK, we're ready. What happened to a and b?
c. $645 is the third quartile, 75th percentile. That means 25% of the salaries are higher.
Answer: 25%
d. $685 is the 85th percentile, 15% greater.
Answer: 15%
e. The mean is the sum of all the salaries divided by the count.
Mean = Sum / Count
So the sum is the count times the mean,
Sum = Count × Mean = 100 × $620 = $62,000
Big payroll.
Answer: $62,000