8.605
This number is bigger than 6.604 and it is smaller than 8.643
:)
Answer:
<u>Fred.</u>
Started hang gliding at a height of 700 ft and descends 15 feet every seconds
<u>Gene</u>
Started hang gliding at a height of 575 ft and descends 10 feet every seconds
Step-by-step explanation:
The function that models Fred's hang gliding is 
The initial value is 700 feet. This Fred was 700 feet above see level before he starts descending.
The rate of descent is -15 ft/s. This means Fred descends 15 feet in one second.
From the table the initial height is 575 ft. This means Gene was 575 feet above sea-level at the beginning of the hang gliding.
The rate of descent is
ft/s.
This means that in every seconds, Gene descends 10 feet.
Answer:
The 95% confidence interval estimate of the population mean rating for Miami is (6.0, 7.5).
Step-by-step explanation:
The (1 - <em>α</em>)% confidence interval for the population mean, when the population standard deviation is not provided is:

The sample selected is of size, <em>n</em> = 50.
The critical value of <em>t</em> for 95% confidence level and (<em>n</em> - 1) = 49 degrees of freedom is:

*Use a <em>t</em>-table.
Compute the sample mean and sample standard deviation as follows:
![\bar x=\frac{1}{n}\sum X=\frac{1}{50}\times [1+5+6+...+10]=6.76\\\\s=\sqrt{\frac{1}{n-1}\sum (x-\bar x)^{2}}=\sqrt{\frac{1}{49}\times 31.12}=2.552](https://tex.z-dn.net/?f=%5Cbar%20x%3D%5Cfrac%7B1%7D%7Bn%7D%5Csum%20X%3D%5Cfrac%7B1%7D%7B50%7D%5Ctimes%20%5B1%2B5%2B6%2B...%2B10%5D%3D6.76%5C%5C%5C%5Cs%3D%5Csqrt%7B%5Cfrac%7B1%7D%7Bn-1%7D%5Csum%20%28x-%5Cbar%20x%29%5E%7B2%7D%7D%3D%5Csqrt%7B%5Cfrac%7B1%7D%7B49%7D%5Ctimes%2031.12%7D%3D2.552)
Compute the 95% confidence interval estimate of the population mean rating for Miami as follows:


Thus, the 95% confidence interval estimate of the population mean rating for Miami is (6.0, 7.5).
Answer:
1 = Input G
2 = Input F
3 = Input H
Step-by-step explanation:
Answer:
The probability that exactly 19 of them are strikes is 0.1504
Step-by-step explanation:
The binomial probability parameters given are;
The probability that the pitcher throwing a strike, p = 0.675
The probability that the pitcher throwing a ball. q = 0.325
The binomial probability is given as follows;

Where:
x = Required probability
Therefore, the probability that the pitcher throws 19 strikes out of 29 pitches is found as follows;
The probability that exactly 19 of them are strikes is given as follows;
Hence the probability that exactly 19 of them are strikes = 0.1504