The area of a rectangle is equal L x W
4 cm longer than it is wide L = 4 + <span>W
</span>
L x W = 117 we replace L here
(4 + <span>W ) x W = 117
</span>
4W + W ^2 = 117
<span>4W + W ^2 -117 = 0
</span>W ^2 +4 W -117 = 0
W² + 4W - 117 = 0
<span>
THEN u want to use the </span>use the quadratic formula
OR Factoring gives us
(W + 13)(W - 9) = 0
W = -13 or 9
But it can't be negative, so
W = 9 and L= 9+4 = 13
Well we set the perimeter to 120 feet.
This means that 2x+2y=120
Now we know the area of a rectangle is xy so we have to solve for both x and y in the perimeter equation.
2x=120-2y
x=60-y
2y=120-2x
y=60-x
Now we plug these values into our area equation A=xy to get:
A=(60-y)(60-x)
A. The mean and standard deviation.
The mean of a sampling distribution is approximately equal to the mean of the population. Given that the mean of the population is equal to 174.5, the mean of the sampling distribution is also this value.
The standard deviation of a sample distribution is equal to,
u(m) = u/sqrt n
Substituting the known values,
u(m) = 6.9 / sqrt 25 = 1.38
b. Get the z-score of both items,
z-score = (data point - mean) / standard deviation
z-score of 172.5
z-score = (172.5 - 174.5) / 1.38 = -1.49
This translates to 0.068.
z-score of 175.8
z-score = (175.8 - 174.5) / 1.38 = 0.94
This translates to 0.83.
The difference between the two z-scores is 0.762.
The number of samples with this height is 0.762(200) which is equal to approximately 152.
c. z-score of 172 centimeters
z-score = (172 - 174.5) / 1.38
z-score = -1.81
This translates to 0.03.
The number of people with this height from the sample is (0.03)(200) = 6
Answer:
His 95% confidence interval is (0.065, 0.155).
Step-by-step explanation:
In a sample with a number n of people surveyed with a probability of a success of 
, and a confidence level of 
, we have the following confidence interval of proportions.
In which
z is the zscore that has a pvalue of 
.
For this problem, we have that:
95% confidence level
So 
, z is the value of Z that has a pvalue of 
, so 
.
The lower limit of this interval is:
The upper limit of this interval is:
His 95% confidence interval is (0.065, 0.155).
