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NeTakaya
2 years ago
9

Lenovo uses the​ zx-81 chip in some of its laptop computers. the prices for the chip during the last 12 months were as​ follows:

                                                                                                             month price per chip month price per chip january ​$1.901.90 july ​$1.801.80 february ​$1.611.61 august ​$1.821.82 march ​$1.601.60 september ​$1.601.60 april ​$1.851.85 october ​$1.571.57 may ​$1.901.90 november ​$1.621.62 june ​$1.951.95 december ​$1.751.75 this exercise contains only part
d. with alphaα ​= 0.1 and the initial forecast for october of ​$1.831.83​, using exponential​ smoothing, the forecast for periods 11 and 12 is ​(round your responses to two decimal​ places): month oct nov dec forecast ​$1.831.83 1.801.80 1.791.79 with alphaα ​= 0.3 and the initial forecast for october of ​$1.761.76​, using exponential​ smoothing, the forecast for periods 11 and 12 is ​(round your responses to two decimal​ places): month oct nov dec forecast ​$1.761.76 1.701.70 1.681.68 with alphaα ​= 0.5 and the initial forecast for october of ​$1.721.72​, using exponential​ smoothing, the forecast for periods 11 and 12 is ​(round your responses to two decimal​ places): month oct nov dec forecast ​$1.721.72 1.651.65 1.631.63 based on the months of​ october, november, and​ december, the mean absolute deviation using exponential smoothing where alphaα ​= 0.1 and the initial forecast for octoberequals=​$1.831.83 is ​$ . 160.160 ​(round your response to three decimal​ places). based on the months of​ october, november, and​ december, the mean absolute deviation using exponential smoothing where alphaα ​= 0.3 and the initial forecast for octoberequals=​$1.761.76 is ​$ 0.1130.113 ​(round your response to three decimal​ places). based on the months of​ october, november, and​ december, the mean absolute deviation using exponential smoothing where alphaα ​= 0.5 and the initial forecast for octoberequals=​$1.721.72 is ​$ nothing ​(round your response to three decimal​ places).
Mathematics
1 answer:
Stella [2.4K]2 years ago
5 0
Given the table below of the prices for the Lenovo zx-81 chip during the last 12 months

\begin{tabular}
{|c|c|c|c|}
Month&Price per Chip&Month&Price per Chip\\[1ex]
January&\$1.90&July&\$1.80\\
February&\$1.61&August&\$1.83\\
March&\$1.60&September&\$1.60\\
April&\$1.85&October&\$1.57\\
May&\$1.90&November&\$1.62\\
June&\$1.95&December&\$1.75
\end{tabular}

The forcast for a period F_{t+1} is given by the formular

F_{t+1}=\alpha A_t+(1-\alpha)F_t

where A_t is the actual value for the preceding period and F_t is the forcast for the preceding period.

Part 1A:
Given <span>α ​= 0.1 and the initial forecast for october of ​$1.83, the actual value for october is $1.57.

Thus, the forecast for period 11 is given by:

F_{11}=\alpha A_{10}+(1-\alpha)F_{10} \\  \\ =0.1(1.57)+(1-0.1)(1.83) \\  \\ =0.157+0.9(1.83)=0.157+1.647 \\  \\ =1.804

Therefore, the foreast for period 11 is $1.80


Part 1B:

</span>Given <span>α ​= 0.1 and the forecast for november of ​$1.80, the actual value for november is $1.62

Thus, the forecast for period 12 is given by:

F_{12}=\alpha&#10; A_{11}+(1-\alpha)F_{11} \\  \\ =0.1(1.62)+(1-0.1)(1.80) \\  \\ &#10;=0.162+0.9(1.80)=0.162+1.62 \\  \\ =1.782

Therefore, the foreast for period 12 is $1.78</span>



Part 2A:

Given <span>α ​= 0.3 and the initial forecast for october of ​$1.76, the actual value for October is $1.57.

Thus, the forecast for period 11 is given by:

F_{11}=\alpha&#10; A_{10}+(1-\alpha)F_{10} \\  \\ =0.3(1.57)+(1-0.3)(1.76) \\  \\ &#10;=0.471+0.7(1.76)=0.471+1.232 \\  \\ =1.703

Therefore, the foreast for period 11 is $1.70

</span>
<span><span>Part 2B:

</span>Given <span>α ​= 0.3 and the forecast for November of ​$1.70, the actual value for november is $1.62

Thus, the forecast for period 12 is given by:

F_{12}=\alpha&#10; A_{11}+(1-\alpha)F_{11} \\  \\ =0.3(1.62)+(1-0.3)(1.70) \\  \\ &#10;=0.486+0.7(1.70)=0.486+1.19 \\  \\ =1.676

Therefore, the foreast for period 12 is $1.68



</span></span>
<span>Part 3A:

Given <span>α ​= 0.5 and the initial forecast for october of ​$1.72, the actual value for October is $1.57.

Thus, the forecast for period 11 is given by:

F_{11}=\alpha&#10; A_{10}+(1-\alpha)F_{10} \\  \\ =0.5(1.57)+(1-0.5)(1.72) \\  \\ &#10;=0.785+0.5(1.72)=0.785+0.86 \\  \\ =1.645

Therefore, the forecast for period 11 is $1.65

</span>
<span><span>Part 3B:

</span>Given <span>α ​= 0.5 and the forecast for November of ​$1.65, the actual value for November is $1.62

Thus, the forecast for period 12 is given by:

F_{12}=\alpha&#10; A_{11}+(1-\alpha)F_{11} \\  \\ =0.5(1.62)+(1-0.5)(1.65) \\  \\ &#10;=0.81+0.5(1.65)=0.81+0.825 \\  \\ =1.635

Therefore, the forecast for period 12 is $1.64



Part 4:

The mean absolute deviation of a forecast is given by the summation of the absolute values of the actual values minus the forecasted values all divided by the number of items.

Thus, given that the actual values of october, november and december are: $1.57, $1.62, $1.75

using </span></span></span><span>α = 0.3, we obtained that the forcasted values of october, november and december are: $1.83, $1.80, $1.78

Thus, the mean absolute deviation is given by:

\frac{|1.57-1.83|+|1.62-1.80|+|1.75-1.78|}{3} = \frac{|-0.26|+|-0.18|+|-0.03|}{3}  \\  \\ = \frac{0.26+0.18+0.03}{3} = \frac{0.47}{3} \approx0.16

Therefore, the mean absolute deviation </span><span>using exponential smoothing where α ​= 0.1 of October, November and December is given by: 0.157



</span><span><span>Part 5:

The mean absolute deviation of a forecast is given by the summation of the absolute values of the actual values minus the forecasted values all divided by the number of items.

Thus, given that the actual values of october, november and december are: $1.57, $1.62, $1.75

using </span><span>α = 0.3, we obtained that the forcasted values of october, november and december are: $1.76, $1.70, $1.68

Thus, the mean absolute deviation is given by:

&#10; \frac{|1.57-1.76|+|1.62-1.70|+|1.75-1.68|}{3} = &#10;\frac{|-0.17|+|-0.08|+|-0.07|}{3}  \\  \\ = \frac{0.17+0.08+0.07}{3} = &#10;\frac{0.32}{3} \approx0.107

Therefore, the mean absolute deviation </span><span>using exponential smoothing where α ​= 0.3 of October, November and December is given by: 0.107



</span></span>
<span><span>Part 6:

The mean absolute deviation of a forecast is given by the summation of the absolute values of the actual values minus the forecasted values all divided by the number of items.

Thus, given that the actual values of october, november and december are: $1.57, $1.62, $1.75

using </span><span>α = 0.5, we obtained that the forcasted values of october, november and december are: $1.72, $1.65, $1.64

Thus, the mean absolute deviation is given by:

&#10; \frac{|1.57-1.72|+|1.62-1.65|+|1.75-1.64|}{3} = &#10;\frac{|-0.15|+|-0.03|+|0.11|}{3}  \\  \\ = \frac{0.15+0.03+0.11}{3} = &#10;\frac{29}{3} \approx0.097

Therefore, the mean absolute deviation </span><span>using exponential smoothing where α ​= 0.5 of October, November and December is given by: 0.097</span></span>
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On this graph, 4:00 p.m. occurs at 16 hours after midnight, and 6:00 p.m. occurs at 18 hours after midnight. Which statements ar
KatRina [158]

Answer:

TRUE OPTIONS ARE:

<em>"The temperature increased until 4:00 p.m. "</em>

<em>"The temperature decreased after 6:00 p.m. "</em>

<em>"The temperature increased more quickly between 12:00 p.m. and 4:00 p.m. than before 12:00 p.m."</em>

Step-by-step explanation:

<em>graph attached and complete question below:</em>

<em>Which statements are true about the temperatures Luis  recorded on the graph? Check all that apply. </em>

  • <em>The temperature increased until 4:00 p.m. </em>
  • <em>The temperature was not recorded between 4:00 p.m.  and 6:00 p.m. </em>
  • <em>The temperature decreased after 6:00 p.m. </em>
  • <em>The temperature increased and then decreased before  holding constant. </em>
  • <em>The temperature increased more quickly between 12:00 p.m. and 4:00 p.m. than before 12:00 p.m.</em>

<em />

Until 1600 hours, the graph increases, so we can say temperature increased until 4.00 pm (FIRST OPTION TRUE).

From 1600 to 1800 hours (4 - 6pm), the temperature stayed same (horizontal line). This doesn't mean the temperature wasn't recorded. (2nd OPTION FALSE).

After 1800 hours (6pm), the line goes downward, so temperature decreased after 6 pm. (3rd OPTION TRUE).

If you look at the temperature graph, we can see temperature increased, then increased more, then constant, then decreased. Thus the 4th option isnt true. (4th OPTION FALSE).

Before 12, the increase isn't as sharp as after 12. After 12 temperature increase has more slope, so this increase is more. (5th OPTION TRUE).

7 0
2 years ago
Read 2 more answers
A study of long-distance phone calls made from General Electric Corporate Headquarters in Fairfield, Connecticut, revealed the l
Katena32 [7]

Answer:

(a) The fraction of the calls last between 4.50 and 5.30 minutes is 0.3729.

(b) The fraction of the calls last more than 5.30 minutes is 0.1271.

(c) The fraction of the calls last between 5.30 and 6.00 minutes is 0.1109.

(d) The fraction of the calls last between 4.00 and 6.00 minutes is 0.745.

(e) The time is 5.65 minutes.

Step-by-step explanation:

We are given that the mean length of time per call was 4.5 minutes and the standard deviation was 0.70 minutes.

Let X = <u><em>the length of the calls, in minutes.</em></u>

So, X ~ Normal(\mu=4.5,\sigma^{2} =0.70^{2})

The z-score probability distribution for the normal distribution is given by;

                           Z  =  \frac{X-\mu}{\sigma}  ~ N(0,1)

where, \mu = population mean time = 4.5 minutes

           \sigma = standard deviation = 0.7 minutes

(a) The fraction of the calls last between 4.50 and 5.30 minutes is given by = P(4.50 min < X < 5.30 min) = P(X < 5.30 min) - P(X \leq 4.50 min)

    P(X < 5.30 min) = P( \frac{X-\mu}{\sigma} < \frac{5.30-4.5}{0.7} ) = P(Z < 1.14) = 0.8729

    P(X \leq 4.50 min) = P( \frac{X-\mu}{\sigma} \leq \frac{4.5-4.5}{0.7} ) = P(Z \leq 0) = 0.50

The above probability is calculated by looking at the value of x = 1.14 and x = 0 in the z table which has an area of 0.8729 and 0.50 respectively.

Therefore, P(4.50 min < X < 5.30 min) = 0.8729 - 0.50 = <u>0.3729</u>.

(b) The fraction of the calls last more than 5.30 minutes is given by = P(X > 5.30 minutes)

    P(X > 5.30 min) = P( \frac{X-\mu}{\sigma} > \frac{5.30-4.5}{0.7} ) = P(Z > 1.14) = 1 - P(Z \leq 1.14)

                                                              = 1 - 0.8729 = <u>0.1271</u>

The above probability is calculated by looking at the value of x = 1.14 in the z table which has an area of 0.8729.

(c) The fraction of the calls last between 5.30 and 6.00 minutes is given by = P(5.30 min < X < 6.00 min) = P(X < 6.00 min) - P(X \leq 5.30 min)

    P(X < 6.00 min) = P( \frac{X-\mu}{\sigma} < \frac{6-4.5}{0.7} ) = P(Z < 2.14) = 0.9838

    P(X \leq 5.30 min) = P( \frac{X-\mu}{\sigma} \leq \frac{5.30-4.5}{0.7} ) = P(Z \leq 1.14) = 0.8729

The above probability is calculated by looking at the value of x = 2.14 and x = 1.14 in the z table which has an area of 0.9838 and 0.8729 respectively.

Therefore, P(4.50 min < X < 5.30 min) = 0.9838 - 0.8729 = <u>0.1109</u>.

(d) The fraction of the calls last between 4.00 and 6.00 minutes is given by = P(4.00 min < X < 6.00 min) = P(X < 6.00 min) - P(X \leq 4.00 min)

    P(X < 6.00 min) = P( \frac{X-\mu}{\sigma} < \frac{6-4.5}{0.7} ) = P(Z < 2.14) = 0.9838

    P(X \leq 4.00 min) = P( \frac{X-\mu}{\sigma} \leq \frac{4.0-4.5}{0.7} ) = P(Z \leq -0.71) = 1 - P(Z < 0.71)

                                                              = 1 - 0.7612 = 0.2388

The above probability is calculated by looking at the value of x = 2.14 and x = 0.71 in the z table which has an area of 0.9838 and 0.7612 respectively.

Therefore, P(4.50 min < X < 5.30 min) = 0.9838 - 0.2388 = <u>0.745</u>.

(e) We have to find the time that represents the length of the longest (in duration) 5 percent of the calls, that means;

            P(X > x) = 0.05            {where x is the required time}

            P( \frac{X-\mu}{\sigma} > \frac{x-4.5}{0.7} ) = 0.05

            P(Z > \frac{x-4.5}{0.7} ) = 0.05

Now, in the z table the critical value of x which represents the top 5% of the area is given as 1.645, that is;

                      \frac{x-4.5}{0.7}=1.645

                      {x-4.5}{}=1.645 \times 0.7

                       x = 4.5 + 1.15 = 5.65 minutes.

SO, the time is 5.65 minutes.

7 0
2 years ago
Blanche bought a 5-year cd for $7100 with an apr of 2.8%, compounded quarterly, but she wants to take all her money out 9 months
katrin2010 [14]
The formula for getting the accumulated amount(compounded) is;
A =P(1+r%)∧n
Where A = Acumulated amount 
            P = principle (deposit)
            r = interest rate and
            n = period
Since the interst is compounded quartly, 
period = (5×4)-3 = 17

A = 7100(1+2.8/100)∧17
   = 7100×1.028∧17
   = 11,353.80

The money she will end up earning in interest on the cd = $11,353.80
4 0
2 years ago
Complete the table of inputs and outputs for the given function g(x)=3-8x.
Andreas93 [3]

Answer:

The answers to your questions are given below.

Step-by-step explanation:

From the question given above,

g(x) = 3 – 8x

Thus, we can complete the table given in question above as follow:

1. Determination of x

g(x) = 0

x =?

g(x) = 3 – 8x

0 = 3 – 8x

Collect like terms

0 – 3 = – 8x

– 3 = – 8x

Divide both side by –8

x = – 3 / –8

x = 3/8

2. Determination of g(x)

x = 0

g(x) =.?

g(x) = 3 – 8x

g(x) = 3 – 8(0)

g(x) = 3 – 0

g(x) = 3

3. Determination of x

g(x) = – 5

x =?

g(x) = 3 – 8x

– 5 = 3 – 8x

Collect like terms

– 5 – 3 = – 8x

– 8 = – 8x

Divide both side by – 8

x = – 8 / – 8

x = 1

4. Determination of g(x)

x = 3

g(x) =.?

g(x) = 3 – 8x

g(x) = 3 – 8(3)

g(x) = 3 – 24

g(x) = – 21

Summary

x >>>>>>>>>>>>>>> g(x)

3/8 >>>>>>>>>>>>> 0

0 >>>>>>>>>>>>>>> 3

1 >>>>>>>>>>>>>>>> – 5

3 >>>>>>>>>>>>>>> – 21

6 0
2 years ago
Alex is x years old. Addison is y years younger. Find their combined age in 10 years’ time.
stira [4]

Answer:

x+10-y

Step-by-step explanation:

i'm not 100% sure about this response, but i'd assume the answer is like this for the following reasons:

alex is x years old, and 10 years have passed, meaning 10 years are added onto his age (x+10). addison is still the same amount of years apart from him in age, so you subtract y from that (x+10-y).

4 0
2 years ago
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