Answer:
y = 6 or 8
Step-by-step explanation:
1. Subtract the constant:
y^2 -14y = -48
2. Add the square of half the y-coefficient:
y^2 -14y +49 = -48 +49
Write as a square, if you like:
(y -7)^2 = 1
3. Take the square root:
y -7 = ±√1 = ±1
4. Add the opposite of the constant on the left:
y = 7 ±1 = 6 or 8
The solution is y = 6 or y = 8.
Answer:
The sample size is
Step-by-step explanation:
From the we are told that
The population proportion is p = 0.90
The margin of error is E = 0.01
From the question we are told the confidence level is 95% , hence the level of significance is
=> 
Generally the sample size is mathematically represented as
![n =[ \frac{ Z_{\frac{\alpha }{2} } }{E} ]^2 * p(1-p)](https://tex.z-dn.net/?f=n%20%20%3D%5B%20%20%5Cfrac%7B%20Z_%7B%5Cfrac%7B%5Calpha%20%7D%7B2%7D%20%7D%20%20%7D%7BE%7D%20%5D%5E2%20%2A%20p%281-p%29)
=> ![n =[ \frac{ 1.96 }{0.01} ]^2 * 0.90(1-0.90)](https://tex.z-dn.net/?f=n%20%20%3D%5B%20%20%5Cfrac%7B%201.96%20%20%7D%7B0.01%7D%20%5D%5E2%20%2A%200.90%281-0.90%29)
=> 
Answer:
y = 3x + 1
The ? is 3
Enter the numbers into the equation:
Enter (0,1) --> 1 = 0 + 1 --> 1 = 1
Enter (3,10) --> 10 = 3 · 3 + 1 --> 10 = 9 + 1 --> 10 = 10
Answer:
<u>Mean:</u> 810.51
<u>Standard deviation:</u> 128.32
Step-by-step explanation:
First, we calculate the sample mean. We have 35 data samples, so we compute it as
.
In general, given a set of <em>n </em>samples
, we calculate the sample mean as
.
For the standard deviation
, we first begin by calculating it's square. It can be obtained from the formula

By taking square root after computing the right hand side, we attain the desired value.
The attached image shows the dot diagram of this sample. The bottom pink vertical line shows the mean, and the two horizontal pink lines have a lenght of
.
The standard deviation means "The average expected distance a new sample will be from the mean". That's why usually, data samples which are denser around the mean have smaller standard deviations (as opposed to distributions who have a lot of values far away from the mean, which will make the standard deviation grow bigger).