For a smoothing constant of 0.2
Time period – 1 2 3 4 5 6 7 8 9 10
Actual value – 46 55 39 42 63 54 55 61 52
Forecast – 58 55.6 55.48 52.18 50.15 52.72 52.97 53.38 54.90
Forecast error - -12 -.6 -16.48 – 10.12 12.85 1.28 2.03 7.62 -2.9
The mean square error is 84.12
The mean forecast for period 11 is 54.38
For a smoothing constant of 0.8
Time period – 1 2 3 4 5 6 7 8 9 10
Actual value – 46 55 39 42 63 54 55 61 52
Forecast – 58 48.40 53.68 41.94 41.99 58.80 54.96 54.99 59.80
Forecast error - -12 6.60 -14.68 0.06 21.01 -4.80 0.04 6.01 -7.80The mean square error is 107.17
The mean forecast for period 11 is 53.56
Based on the MSE, smoothing constant of .2 offers a better model since the mean forecast is much better compared to the 53.56 of the smoothing constant of 0.8.
Answer:
160 miles
Step-by-step explanation:
Company A form $130 a day plus $0.30 per mile
Company A = 130 + 0.30x
Company B charges $50 a day plus $0.80 per mile
Company B = 50 + 0.80x
Where,
x = number of miles
Equate the cost of company A and company B
130 + 0.30x = 50 + 0.80x
Collect like terms
130 - 50 = 0.80x - 0.30x
80 = 0.50x
Divide both sides by 0.50x
x = 80 / 0.50
= 160
x = 160 miles
The number of miles in a day at which the rental costs for Company A and Company B are the same is 160 miles
-4(8-(-3))+7
Remove the parentheses, negative with negative will equal a positive so the new equation will be -4(8+3)+7. So 8+3=11, -4(11)+7. -4(11)=-44 and then add -44+7 which will equal -37
Step-by-step explanation:
√3 x² - 2x - √3 = 0
√3 x² - 3x + x - √3 = 0
√3 x(x - √3) + 1(x - √3) = 0
(x - √3 ) (√3 x + 1) = 0
x - √3 = 0 , √3 x +1 = 0
x = √3 , x = -1/√3
Answer:
see explanation
Step-by-step explanation:
Using the rules of radicals/ exponents
× 
= 
⇔ ![\sqrt[n]{a^{m} }](https://tex.z-dn.net/?f=%5Csqrt%5Bn%5D%7Ba%5E%7Bm%7D%20%7D)
Simplifying each term
7
= 7
x
= x × 
× 
= x × 3 × 
= 3 × 
= 3
Subtracting the 2 simplified like terms, that is
7 - 3
= 4 ← return to radical form
= 4
