Answer:
The other two angles are 75° and 125°.
Step-by-step explanation:
Let three angles are 2x, 3x and 5x.
The smallest angle is 50.
It means,
2x = 50
x = 25
So,
3x = 3(25) = 75°
5x = 5(25) = 125°
So, the other two angles are 75° and 125°.
6............................................
A) Demand function
price (x) demand (D(x))
4 540
3.50 810
D - 540 810 - 540
----------- = -----------------
x - 4 3.50 - 4
D - 540
----------- = - 540
x - 4
D - 540 = - 540(x - 4)
D = -540x + 2160 + 540
D = 2700 - 540x
D(x) = 2700 - 540x
Revenue function, R(x)
R(x) = price * demand = x * D(x)
R(x) = x* (2700 - 540x) = 2700x - 540x^2
b) Profit, P(x)
profit = revenue - cost
P(x) = R(x) - 30
P(x) = [2700x - 540x^2] - 30
P(x) = 2700x - 540x^2 - 30
Largest possible profit => vertex of the parabola
vertex of 2700x - 540x^2 - 30
When you calculate the vertex you find x = 5 /2
=> P(x) = 3345
Answer: you should charge a log-on fee of $2.5 to have the largest profit, which is $3345.
I’m a little confused by the question and the problem, is there a picture of the problem you could add?
This question is incomplete, the complete question is;
Suppose John is a high school statistics teacher who believes that watching many hours of TV leads to lower test scores. Immediately after giving the most recent test, he surveyed each of the 24 students in his class and asked them how many hours of TV they watched that week. He then matched each student's test grade with his or her survey response. After compiling the data, he used hours of TV watched to predict each student's test score. He found the least-squares regression line to be y" = -1.5x + 85.
He also calculated that the value of r, the correlation, was -0.61.
what is the correct value of the coefficient of determination R² and give a correct interpretation of its meaning
Answer:
Interpretation of coefficient of determination R² = 0.3721
R² = 0.3721, meaning 37.21% of the total variation in test scores can be explained by the least square regression line
Step-by-step explanation:
Given the data in the question;
the least square regression line is;
y" = -1.5x + 85
the correlation coefficient r = -0.61
Now, the coefficient of determination R² is square of correlation coefficient r
R² = -61²
R² = 0.3721
