Answer:
a) Binomial.
b) n=20, p=0.01, k≥2
The probability hat a package sold will be refunded is P=0.0169.
Step-by-step explanation:
a) We know that
- the defective probability is constant and independent.
- the sample size is bigger than one subject.
The most appropiate distribution to represent this random variable is the binomial.
b) The parameters are:
- Sample size (amount of clips in the package): n=20
- Probability of defective clips: p=0.01.
- number of defective clips that trigger the money-back guarantee: k≥2
The probability of the package being refunded can be calculated as:

Step-by-step explanation:

Part A)
![\bf \qquad \qquad \textit{Future Value of an ordinary annuity}\\ \left. \qquad \qquad \right.(\textit{payments at the end of the period}) \\\\ A=pymnt\left[ \cfrac{\left( 1+\frac{r}{n} \right)^{nt}-1}{\frac{r}{n}} \right]](https://tex.z-dn.net/?f=%5Cbf%20%5Cqquad%20%5Cqquad%20%5Ctextit%7BFuture%20Value%20of%20an%20ordinary%20annuity%7D%5C%5C%0A%5Cleft.%20%5Cqquad%20%5Cqquad%20%5Cright.%28%5Ctextit%7Bpayments%20at%20the%20end%20of%20the%20period%7D%29%0A%5C%5C%5C%5C%0AA%3Dpymnt%5Cleft%5B%20%5Ccfrac%7B%5Cleft%28%201%2B%5Cfrac%7Br%7D%7Bn%7D%20%5Cright%29%5E%7Bnt%7D-1%7D%7B%5Cfrac%7Br%7D%7Bn%7D%7D%20%5Cright%5D)

![\bf A=1200\left[ \cfrac{\left( 1+\frac{0.05}{1} \right)^{1\cdot 12}-1}{\frac{0.05}{1}} \right]\implies A\approx 19100.55](https://tex.z-dn.net/?f=%5Cbf%20A%3D1200%5Cleft%5B%20%5Ccfrac%7B%5Cleft%28%201%2B%5Cfrac%7B0.05%7D%7B1%7D%20%5Cright%29%5E%7B1%5Ccdot%20%2012%7D-1%7D%7B%5Cfrac%7B0.05%7D%7B1%7D%7D%20%5Cright%5D%5Cimplies%20A%5Capprox%2019100.55)
part B)
so, for the next 11 years, she didn't make any deposits on it and simple let it sit and collect interest, compounded annually at 5%.

part C)
well, for 12 years she deposited 1200 bucks, that means 12 * 1200, or 14,400.
now, here she is, 12+11, or 23 years later, and she's got 32,668.42 bucks?
all that came out of her pocket was 14,400, so 32,668.42 - 14,400, is how much she earned in interest.
Answer:
1
Step-by-step explanation:
When you take the log of ...
b = b^1
you get ...

Answer:
A . About 95% of all random samples of 50 students from this population would result in a 95% confidence interval that covered the population mean number of hours of sleep per day.
Step-by-step explanation:
x% confidence interval:
A confidence interval is built from a sample, has bounds a and b, and has a confidence level of x%. It means that we are x% confident that the population mean is between a and b.
In this question:
95% CI from a sample of 50 students is (6.73, 7.67).
This means that we are 95% sure that the population mean is in this interval, that is, about 95% samples of 50 would contain the population mean, which is given by option A.