Deck 9: Forecasting Techniques

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Question
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
What is the forecasted value for the 7th week?

A) 53 phones
B) 82 phones
C) 71 phones
D) 49 phones
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Question
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
What is the formula used to calculate the value of at in the linear trend equation Ft+k = at + btk while using double exponential smoothing?

A) at = βbt - bt-1) + 1 -β)bt-1
B) at = αFt-1 + 1 - α)at +1 + bt+1)
C) at = αFt + 1 - α)at -1 + bt-1)
D) at = βbt + bt-1) + 1 + γ)bt-1
Question
Use the data given below to answer the following questions).
The table provided below gives the sales details of the number of android smart phones at an electronic retail store for the past 6 weeks. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2.  Week  Units sold 188244354465572685\begin{array} { | c | c | } \hline \text { Week } & \text { Units sold } \\\hline 1 & 88 \\\hline 2 & 44 \\\hline 3 & 54 \\\hline 4 & 65 \\\hline 5 & 72 \\\hline 6 & 85 \\\hline\end{array}

-For the given data, what is the value of the simple moving average mean square error?

A) 0.21
B) 20.12
C) 14.25
D) 207.13
Question
What is a stream of historical data known as?

A) a time series
B) an index
C) a complex number
D) an orthopole
Question
Before launching a new line of toys, Toys Inc. used the method of historical analogy to obtain a forecast. In this scenario, Toys Inc.:

A) noted the behavior of its current customers while they use their products.
B) used a panel of experts, whose identities were kept confidential from one another, to respond to a sequence of questionnaires.
C) noted the consumer response to similar previous products to marketing campaigns and used the responses as a basis to predict how the new marketing campaign might fare.
D) used a brainstorming session among a group of experts to draw new ideas.
Question
Use the data given below to answer the following questions).
The table provided below gives the sales details of the number of android smart phones at an electronic retail store for the past 6 weeks. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2.  Week  Units sold 188244354465572685\begin{array} { | c | c | } \hline \text { Week } & \text { Units sold } \\\hline 1 & 88 \\\hline 2 & 44 \\\hline 3 & 54 \\\hline 4 & 65 \\\hline 5 & 72 \\\hline 6 & 85 \\\hline\end{array}

-For the given data, calculate the value of the simple moving average mean absolute percentage error.

A) 20.90
B) 23.45
C) 14.39
D) 25.56
Question
What is the formula used to calculate the value of bt in the linear trend equation Ft+k = at + btk while using double exponential smoothing?

A) bt = βbt - bt-1) + 1 -β)bt-1
B) bt = αFt-1 + 1 - α)at +1 + bt+1)
C) bt = αFt + 1 - α)at -1 + bt-1)
D) bt = βat - at-1) + 1 -β)bt-1
Question
The Delphi method used for forecasting:

A) obtains forecasts through a comparative analysis with a previous situation.
B) uses measures that are believed to influence the behavior of a variable that the researcher wishes to forecast.
C) uses a single measure that weights multiple indicators and provides a measure of overall expectation.
D) uses a panel of experts, whose identities are typically kept confidential from one another, to respond to a sequence of questionnaires.
Question
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2 and
? = 0.15 Hint: Use XLMiner)  Year  Units sold in  thousands 198188819829001983100019841200198511001986130019871250198811501989110019901200\begin{array} { | c | c| } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1981 & 888 \\\hline 1982 & 900 \\\hline 1983 & 1000 \\\hline 1984 & 1200 \\\hline 1985 & 1100 \\\hline 1986 & 1300 \\\hline 1987 & 1250 \\\hline 1988 & 1150 \\\hline 1989 & 1100 \\\hline 1990 & 1200 \\\hline\end{array}

-Calculate the value of the mean absolute percentage error using double exponential smoothing for the given data.

A) 1.80
B) 8.10
C) 91.27
D) 11976.17
Question
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
In the linear trend equation, Ft+k = at + btk, at is known as the .

A) level
B) trend
C) slope
D) forecast
Question
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
In the linear trend equation Ft+k = at + btk, identify the term that signifies the trend.

A) bt
B) k
C) at
D) Ft + k
Question
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
Which of the following is the value of the root mean square error for the given data?

A) 11.56
B) 21.77
C) 13.87
D) 20.13
Question
In forecasting, what is an index?

A) It is a single measure that weights multiple indicators and provides a measure of overall expectation.
B) It is a stream of historical data, such as weekly sales.
C) It is a time series that does not have trend, seasonal, or cyclical effects but is relatively constant and only exhibits random behavior.
D) It is a measure that provides a complete forecast.
Question
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
What is the forecasted value for the 3rd week?

A) 53 phones
B) 64 phones
C) 71 phones
D) 49 phones
Question
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
Calculate the value of the mean absolute percentage error for the given data.

A) 20.90
B) 16.60
C) 21.72
D) 29.97
Question
The data for the number of hand-held gaming devices sold for the past 5 weeks are 15 units, 20 units, 25 units, 30 units, and 17 units respectively. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects; thus, a moving average model would be appropriate. Setting k = 3 the three-period moving average forecast for week 6 is .

A) 20 units
B) 24 units
C) 30 units
D) 17 units
Question
Use the data given below to answer the following questions).
The table provided below gives the sales details of the number of android smart phones at an electronic retail store for the past 6 weeks. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2.  Week  Units sold 188244354465572685\begin{array} { | c | c | } \hline \text { Week } & \text { Units sold } \\\hline 1 & 88 \\\hline 2 & 44 \\\hline 3 & 54 \\\hline 4 & 65 \\\hline 5 & 72 \\\hline 6 & 85 \\\hline\end{array}

-Using the data, determine the value of the simple moving average root mean square error.

A) 0.21
B) 14.39
C) 20.12
D) 207.13
Question
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
What is the difference between the forecasted and the actual value for the 3rd week?

A) 1 phones
B) 6 phones
C) 4 phones
D) 3 phones
Question
Time-series models may exhibit seasonal effects or cyclical effects. A seasonal effect differs from a cyclical effect in that a seasonal effect:

A) has no trend, is relatively constant, and only exhibits random behavior.
B) describes ups and downs over a time frame such as several years.
C) is one that repeats at fixed intervals of time, typically a year, month, week, or day.
D) is based on analysis of historical time-series data and are predicated on the assumption that the future is an extrapolation of the past.
Question
Use the data given below to answer the following questions).
The table provided below gives the sales details of the number of android smart phones at an electronic retail store for the past 6 weeks. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2.  Week  Units sold 188244354465572685\begin{array} { | c | c | } \hline \text { Week } & \text { Units sold } \\\hline 1 & 88 \\\hline 2 & 44 \\\hline 3 & 54 \\\hline 4 & 65 \\\hline 5 & 72 \\\hline 6 & 85 \\\hline\end{array}

-For the given data, the simple moving average mean absolute deviation is .

A) 0.21
B) 20.12
C) 14.25
D) 207.13
Question
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-Which of the following is the forecast value for the 6th year?

A) 1256.06
B) 1328.04
C) 1321.31
D) 1327.24
Question
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-If the given time series has a trend and no seasonality, the most appropriate forecasting model to determine the forecast of the time series is the model.

A) single exponential smoothing
B) Holt-Winters no trend smoothing
C) double exponential smoothing
D) Holt-Winters additive
Question
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2 and
? = 0.15 Hint: Use XLMiner)  Year  Units sold in  thousands 198188819829001983100019841200198511001986130019871250198811501989110019901200\begin{array} { | c | c| } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1981 & 888 \\\hline 1982 & 900 \\\hline 1983 & 1000 \\\hline 1984 & 1200 \\\hline 1985 & 1100 \\\hline 1986 & 1300 \\\hline 1987 & 1250 \\\hline 1988 & 1150 \\\hline 1989 & 1100 \\\hline 1990 & 1200 \\\hline\end{array}

-Identify the value of the mean square error using double exponential smoothing for the given set of data.

A) 8.10
B) 1.80
C) 91.27
D) 11976.17
Question
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-If the given time series has no trend and no seasonality, the most appropriate forecasting model to determine the forecast of the time series is the model.

A) single moving average
B) Holt-Winters no-trend smoothing
C) double exponential smoothing
D) Holt-Winters additive
Question
A cyclical effect is one that repeats at fixed intervals of time, typically a year, month, week, or day.
Question
Use the data given below to answer the following questions).
The table below provides the sales data for JD Inc. for the year 1998. Given: ? = 0.2, ? = 0.15, and ? = 0.05 Hint: Use an additive Holt-Winters model.)  Umbrella Sales of JD Inc.  Year  Month  Units 1 Jan 39801 Feb 40001 Mar 47401 April 47201 May 49201 Jul 51401 July 46401 Aug 45201 Sep 44801 Oct 46901 Nov 42101 Dec 44182 Jan 43802 Feb 44002 Mar 51402 April 51202 May 53202 JuI 55402 July 50402 Aug 49202 sep 48802 Oct 50902 Nov 46102 Dec 4818\begin{array}{l}\text { Umbrella Sales of JD Inc. }\\\begin{array} { | c | c | c| } \hline \text { Year } & \text { Month } & \text { Units } \\\hline 1 & \text { Jan } & 3980 \\\hline 1 & \text { Feb } & 4000 \\\hline 1 & \text { Mar } & 4740 \\\hline 1 & \text { April } & 4720 \\\hline 1 & \text { May } & 4920 \\\hline 1 & \text { Jul } & 5140 \\\hline 1 & \text { July } & 4640 \\\hline 1 & \text { Aug } & 4520 \\\hline 1 & \text { Sep } & 4480 \\\hline 1 & \text { Oct } & 4690 \\\hline 1 & \text { Nov } & 4210 \\\hline 1 & \text { Dec } & 4418 \\\hline 2 & \text { Jan } & 4380 \\\hline 2 & \text { Feb } & 4400 \\\hline 2 & \text { Mar } & 5140 \\\hline 2 & \text { April } & 5120 \\\hline 2 & \text { May } & 5320 \\\hline 2 & \text { JuI } & 5540 \\\hline 2 & \text { July } & 5040 \\\hline 2 & \text { Aug } & 4920 \\\hline 2 & \text { sep } & 4880 \\\hline 2 & \text { Oct } & 5090 \\\hline 2 & \text { Nov } & 4610 \\\hline 2 & \text { Dec } & 4818 \\\hline\end{array}\end{array}

-Using an appropriate Holt-Winters trend model, calculate the value of the mean absolute percentage error for the given data.

A) 8.10
B) 330.01
C) 384.83
D) 7.21
Question
The indexes in the forecasting indicators provide a complete forecast.
Question
Indicators are measures that are believed to influence the behavior of a variable an individual wishes to forecast.
Question
Using double exponential smoothing, find the value of the root mean square error for the given data.

A) 8.10
B) 91.27
C) 11976.17
D) 109.44
Question
Use the data given below to answer the following questions).
The table below provides the sales data for JD Inc. for the year 1998. Given: ? = 0.2, ? = 0.15, and ? = 0.05 Hint: Use an additive Holt-Winters model.)  Umbrella Sales of JD Inc.  Year  Month  Units 1 Jan 39801 Feb 40001 Mar 47401 April 47201 May 49201 Jul 51401 July 46401 Aug 45201 Sep 44801 Oct 46901 Nov 42101 Dec 44182 Jan 43802 Feb 44002 Mar 51402 April 51202 May 53202 JuI 55402 July 50402 Aug 49202 sep 48802 Oct 50902 Nov 46102 Dec 4818\begin{array}{l}\text { Umbrella Sales of JD Inc. }\\\begin{array} { | c | c | c| } \hline \text { Year } & \text { Month } & \text { Units } \\\hline 1 & \text { Jan } & 3980 \\\hline 1 & \text { Feb } & 4000 \\\hline 1 & \text { Mar } & 4740 \\\hline 1 & \text { April } & 4720 \\\hline 1 & \text { May } & 4920 \\\hline 1 & \text { Jul } & 5140 \\\hline 1 & \text { July } & 4640 \\\hline 1 & \text { Aug } & 4520 \\\hline 1 & \text { Sep } & 4480 \\\hline 1 & \text { Oct } & 4690 \\\hline 1 & \text { Nov } & 4210 \\\hline 1 & \text { Dec } & 4418 \\\hline 2 & \text { Jan } & 4380 \\\hline 2 & \text { Feb } & 4400 \\\hline 2 & \text { Mar } & 5140 \\\hline 2 & \text { April } & 5120 \\\hline 2 & \text { May } & 5320 \\\hline 2 & \text { JuI } & 5540 \\\hline 2 & \text { July } & 5040 \\\hline 2 & \text { Aug } & 4920 \\\hline 2 & \text { sep } & 4880 \\\hline 2 & \text { Oct } & 5090 \\\hline 2 & \text { Nov } & 4610 \\\hline 2 & \text { Dec } & 4818 \\\hline\end{array}\end{array}

-What will be the predicted sales for umbrellas for the month of February of year 2?

A) 4530.19
B) 4648.21
C) 4883.76
D) 4818.07
Question
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-Determine the value of the mean absolute deviation using the Holt-Winters no-trend model for the given data.

A) 367.35
B) 18.39
C) 21.70
D) 252.55
Question
For the given data, what is the sales forecast for the year 1992 in thousands)?

A) 1256.87
B) 1317.91
C) 1285.74
D) 1350.08
Question
Use the data shown below to answer the following questions).
The table below is the data set of the Shiller Real Home Price Index for the years 1946-1956. Use the data shown below to answer the following questions). The table below is the data set of the Shiller Real Home Price Index for the years 1946-1956.   Setting k = 3, determine the simple moving average forecast for the year 1950.<div style=padding-top: 35px>
Setting k = 3, determine the simple moving average forecast for the year 1950.
Question
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-Which of the following is the value of the root mean square error for the given data?

A) 252.55
B) 367.35
C) 21.70
D) 109.76
Question
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-Calculate the value of the mean absolute percentage error using the Holt-Winters no-trend model for the given data.

A) 8.10
B) 18.39
C) 21.70
D) 10.97
Question
Use the data given below to answer the following questions).
The table below provides the sales data for JD Inc. for the year 1998. Given: ? = 0.2, ? = 0.15, and ? = 0.05 Hint: Use an additive Holt-Winters model.)  Umbrella Sales of JD Inc.  Year  Month  Units 1 Jan 39801 Feb 40001 Mar 47401 April 47201 May 49201 Jul 51401 July 46401 Aug 45201 Sep 44801 Oct 46901 Nov 42101 Dec 44182 Jan 43802 Feb 44002 Mar 51402 April 51202 May 53202 JuI 55402 July 50402 Aug 49202 sep 48802 Oct 50902 Nov 46102 Dec 4818\begin{array}{l}\text { Umbrella Sales of JD Inc. }\\\begin{array} { | c | c | c| } \hline \text { Year } & \text { Month } & \text { Units } \\\hline 1 & \text { Jan } & 3980 \\\hline 1 & \text { Feb } & 4000 \\\hline 1 & \text { Mar } & 4740 \\\hline 1 & \text { April } & 4720 \\\hline 1 & \text { May } & 4920 \\\hline 1 & \text { Jul } & 5140 \\\hline 1 & \text { July } & 4640 \\\hline 1 & \text { Aug } & 4520 \\\hline 1 & \text { Sep } & 4480 \\\hline 1 & \text { Oct } & 4690 \\\hline 1 & \text { Nov } & 4210 \\\hline 1 & \text { Dec } & 4418 \\\hline 2 & \text { Jan } & 4380 \\\hline 2 & \text { Feb } & 4400 \\\hline 2 & \text { Mar } & 5140 \\\hline 2 & \text { April } & 5120 \\\hline 2 & \text { May } & 5320 \\\hline 2 & \text { JuI } & 5540 \\\hline 2 & \text { July } & 5040 \\\hline 2 & \text { Aug } & 4920 \\\hline 2 & \text { sep } & 4880 \\\hline 2 & \text { Oct } & 5090 \\\hline 2 & \text { Nov } & 4610 \\\hline 2 & \text { Dec } & 4818 \\\hline\end{array}\end{array}

-Calculate the value of the mean square error using an appropriate Holt-Winters trend model for the given data.

A) 8.10
B) 346.26
C) 140942.78
D) 7.62
Question
Which of the following equations is the trend line equation for the given data? Note: the fitted model assumes that the years are numbered 1 through 10, not the actual dates.)

A) 60.123x + 481.56
B) 48.16x + 481.86
C) 32.17x + 931.87
D) 57.15x + 503.81
Question
Use the data given below to answer the following questions).
The table below provides the sales data for JD Inc. for the year 1998. Given: ? = 0.2, ? = 0.15, and ? = 0.05 Hint: Use an additive Holt-Winters model.)  Umbrella Sales of JD Inc.  Year  Month  Units 1 Jan 39801 Feb 40001 Mar 47401 April 47201 May 49201 Jul 51401 July 46401 Aug 45201 Sep 44801 Oct 46901 Nov 42101 Dec 44182 Jan 43802 Feb 44002 Mar 51402 April 51202 May 53202 JuI 55402 July 50402 Aug 49202 sep 48802 Oct 50902 Nov 46102 Dec 4818\begin{array}{l}\text { Umbrella Sales of JD Inc. }\\\begin{array} { | c | c | c| } \hline \text { Year } & \text { Month } & \text { Units } \\\hline 1 & \text { Jan } & 3980 \\\hline 1 & \text { Feb } & 4000 \\\hline 1 & \text { Mar } & 4740 \\\hline 1 & \text { April } & 4720 \\\hline 1 & \text { May } & 4920 \\\hline 1 & \text { Jul } & 5140 \\\hline 1 & \text { July } & 4640 \\\hline 1 & \text { Aug } & 4520 \\\hline 1 & \text { Sep } & 4480 \\\hline 1 & \text { Oct } & 4690 \\\hline 1 & \text { Nov } & 4210 \\\hline 1 & \text { Dec } & 4418 \\\hline 2 & \text { Jan } & 4380 \\\hline 2 & \text { Feb } & 4400 \\\hline 2 & \text { Mar } & 5140 \\\hline 2 & \text { April } & 5120 \\\hline 2 & \text { May } & 5320 \\\hline 2 & \text { JuI } & 5540 \\\hline 2 & \text { July } & 5040 \\\hline 2 & \text { Aug } & 4920 \\\hline 2 & \text { sep } & 4880 \\\hline 2 & \text { Oct } & 5090 \\\hline 2 & \text { Nov } & 4610 \\\hline 2 & \text { Dec } & 4818 \\\hline\end{array}\end{array}

-What is the value of the mean absolute deviation for the given data?

A) 8.10
B) 340.73
C) 14.82
D) 7.62
Question
Use the data shown below to answer the following questions).
The table below is the data set of the Shiller Real Home Price Index for the years 1946-1956. Use the data shown below to answer the following questions). The table below is the data set of the Shiller Real Home Price Index for the years 1946-1956.   Setting k = 5, calculate the simple moving average forecast for the year 1951.<div style=padding-top: 35px>
Setting k = 5, calculate the simple moving average forecast for the year 1951.
Question
Using double exponential smoothing, calculate the value of the mean absolute deviation for the given data.

A) 8.10
B) 1.80
C) 91.27
D) 11976.17
Question
If a time series has seasonality but no trend, the most appropriate model used for forecasting is the Holt-Winters multiplicative model.
Question
Explain the different types of Holt-Winters models used in forecasting.
Question
Explain econometric models used in forecasting with examples.
Question
Write a short note on indicators and indexes used in forecasting.
Question
Explain the significance of using double moving average and double exponential smoothing models.
Question
The Holt-Winters additive model applies to time series whose amplitude increases or decreases over time.
Question
What is simple exponential smoothing?
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Deck 9: Forecasting Techniques
1
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
What is the forecasted value for the 7th week?

A) 53 phones
B) 82 phones
C) 71 phones
D) 49 phones
82 phones
2
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
What is the formula used to calculate the value of at in the linear trend equation Ft+k = at + btk while using double exponential smoothing?

A) at = βbt - bt-1) + 1 -β)bt-1
B) at = αFt-1 + 1 - α)at +1 + bt+1)
C) at = αFt + 1 - α)at -1 + bt-1)
D) at = βbt + bt-1) + 1 + γ)bt-1
at = αFt + 1 - α)at -1 + bt-1)
3
Use the data given below to answer the following questions).
The table provided below gives the sales details of the number of android smart phones at an electronic retail store for the past 6 weeks. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2.  Week  Units sold 188244354465572685\begin{array} { | c | c | } \hline \text { Week } & \text { Units sold } \\\hline 1 & 88 \\\hline 2 & 44 \\\hline 3 & 54 \\\hline 4 & 65 \\\hline 5 & 72 \\\hline 6 & 85 \\\hline\end{array}

-For the given data, what is the value of the simple moving average mean square error?

A) 0.21
B) 20.12
C) 14.25
D) 207.13
207.13
4
What is a stream of historical data known as?

A) a time series
B) an index
C) a complex number
D) an orthopole
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5
Before launching a new line of toys, Toys Inc. used the method of historical analogy to obtain a forecast. In this scenario, Toys Inc.:

A) noted the behavior of its current customers while they use their products.
B) used a panel of experts, whose identities were kept confidential from one another, to respond to a sequence of questionnaires.
C) noted the consumer response to similar previous products to marketing campaigns and used the responses as a basis to predict how the new marketing campaign might fare.
D) used a brainstorming session among a group of experts to draw new ideas.
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6
Use the data given below to answer the following questions).
The table provided below gives the sales details of the number of android smart phones at an electronic retail store for the past 6 weeks. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2.  Week  Units sold 188244354465572685\begin{array} { | c | c | } \hline \text { Week } & \text { Units sold } \\\hline 1 & 88 \\\hline 2 & 44 \\\hline 3 & 54 \\\hline 4 & 65 \\\hline 5 & 72 \\\hline 6 & 85 \\\hline\end{array}

-For the given data, calculate the value of the simple moving average mean absolute percentage error.

A) 20.90
B) 23.45
C) 14.39
D) 25.56
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7
What is the formula used to calculate the value of bt in the linear trend equation Ft+k = at + btk while using double exponential smoothing?

A) bt = βbt - bt-1) + 1 -β)bt-1
B) bt = αFt-1 + 1 - α)at +1 + bt+1)
C) bt = αFt + 1 - α)at -1 + bt-1)
D) bt = βat - at-1) + 1 -β)bt-1
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8
The Delphi method used for forecasting:

A) obtains forecasts through a comparative analysis with a previous situation.
B) uses measures that are believed to influence the behavior of a variable that the researcher wishes to forecast.
C) uses a single measure that weights multiple indicators and provides a measure of overall expectation.
D) uses a panel of experts, whose identities are typically kept confidential from one another, to respond to a sequence of questionnaires.
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9
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2 and
? = 0.15 Hint: Use XLMiner)  Year  Units sold in  thousands 198188819829001983100019841200198511001986130019871250198811501989110019901200\begin{array} { | c | c| } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1981 & 888 \\\hline 1982 & 900 \\\hline 1983 & 1000 \\\hline 1984 & 1200 \\\hline 1985 & 1100 \\\hline 1986 & 1300 \\\hline 1987 & 1250 \\\hline 1988 & 1150 \\\hline 1989 & 1100 \\\hline 1990 & 1200 \\\hline\end{array}

-Calculate the value of the mean absolute percentage error using double exponential smoothing for the given data.

A) 1.80
B) 8.10
C) 91.27
D) 11976.17
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10
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
In the linear trend equation, Ft+k = at + btk, at is known as the .

A) level
B) trend
C) slope
D) forecast
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11
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
In the linear trend equation Ft+k = at + btk, identify the term that signifies the trend.

A) bt
B) k
C) at
D) Ft + k
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12
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
Which of the following is the value of the root mean square error for the given data?

A) 11.56
B) 21.77
C) 13.87
D) 20.13
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13
In forecasting, what is an index?

A) It is a single measure that weights multiple indicators and provides a measure of overall expectation.
B) It is a stream of historical data, such as weekly sales.
C) It is a time series that does not have trend, seasonal, or cyclical effects but is relatively constant and only exhibits random behavior.
D) It is a measure that provides a complete forecast.
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14
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
What is the forecasted value for the 3rd week?

A) 53 phones
B) 64 phones
C) 71 phones
D) 49 phones
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15
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
Calculate the value of the mean absolute percentage error for the given data.

A) 20.90
B) 16.60
C) 21.72
D) 29.97
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16
The data for the number of hand-held gaming devices sold for the past 5 weeks are 15 units, 20 units, 25 units, 30 units, and 17 units respectively. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects; thus, a moving average model would be appropriate. Setting k = 3 the three-period moving average forecast for week 6 is .

A) 20 units
B) 24 units
C) 30 units
D) 17 units
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17
Use the data given below to answer the following questions).
The table provided below gives the sales details of the number of android smart phones at an electronic retail store for the past 6 weeks. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2.  Week  Units sold 188244354465572685\begin{array} { | c | c | } \hline \text { Week } & \text { Units sold } \\\hline 1 & 88 \\\hline 2 & 44 \\\hline 3 & 54 \\\hline 4 & 65 \\\hline 5 & 72 \\\hline 6 & 85 \\\hline\end{array}

-Using the data, determine the value of the simple moving average root mean square error.

A) 0.21
B) 14.39
C) 20.12
D) 207.13
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18
Answer the following questions) using exponential smoothing after having optimized α at 0.1 increments.
What is the difference between the forecasted and the actual value for the 3rd week?

A) 1 phones
B) 6 phones
C) 4 phones
D) 3 phones
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19
Time-series models may exhibit seasonal effects or cyclical effects. A seasonal effect differs from a cyclical effect in that a seasonal effect:

A) has no trend, is relatively constant, and only exhibits random behavior.
B) describes ups and downs over a time frame such as several years.
C) is one that repeats at fixed intervals of time, typically a year, month, week, or day.
D) is based on analysis of historical time-series data and are predicated on the assumption that the future is an extrapolation of the past.
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20
Use the data given below to answer the following questions).
The table provided below gives the sales details of the number of android smart phones at an electronic retail store for the past 6 weeks. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2.  Week  Units sold 188244354465572685\begin{array} { | c | c | } \hline \text { Week } & \text { Units sold } \\\hline 1 & 88 \\\hline 2 & 44 \\\hline 3 & 54 \\\hline 4 & 65 \\\hline 5 & 72 \\\hline 6 & 85 \\\hline\end{array}

-For the given data, the simple moving average mean absolute deviation is .

A) 0.21
B) 20.12
C) 14.25
D) 207.13
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21
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-Which of the following is the forecast value for the 6th year?

A) 1256.06
B) 1328.04
C) 1321.31
D) 1327.24
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22
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-If the given time series has a trend and no seasonality, the most appropriate forecasting model to determine the forecast of the time series is the model.

A) single exponential smoothing
B) Holt-Winters no trend smoothing
C) double exponential smoothing
D) Holt-Winters additive
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23
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2 and
? = 0.15 Hint: Use XLMiner)  Year  Units sold in  thousands 198188819829001983100019841200198511001986130019871250198811501989110019901200\begin{array} { | c | c| } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1981 & 888 \\\hline 1982 & 900 \\\hline 1983 & 1000 \\\hline 1984 & 1200 \\\hline 1985 & 1100 \\\hline 1986 & 1300 \\\hline 1987 & 1250 \\\hline 1988 & 1150 \\\hline 1989 & 1100 \\\hline 1990 & 1200 \\\hline\end{array}

-Identify the value of the mean square error using double exponential smoothing for the given set of data.

A) 8.10
B) 1.80
C) 91.27
D) 11976.17
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24
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-If the given time series has no trend and no seasonality, the most appropriate forecasting model to determine the forecast of the time series is the model.

A) single moving average
B) Holt-Winters no-trend smoothing
C) double exponential smoothing
D) Holt-Winters additive
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25
A cyclical effect is one that repeats at fixed intervals of time, typically a year, month, week, or day.
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26
Use the data given below to answer the following questions).
The table below provides the sales data for JD Inc. for the year 1998. Given: ? = 0.2, ? = 0.15, and ? = 0.05 Hint: Use an additive Holt-Winters model.)  Umbrella Sales of JD Inc.  Year  Month  Units 1 Jan 39801 Feb 40001 Mar 47401 April 47201 May 49201 Jul 51401 July 46401 Aug 45201 Sep 44801 Oct 46901 Nov 42101 Dec 44182 Jan 43802 Feb 44002 Mar 51402 April 51202 May 53202 JuI 55402 July 50402 Aug 49202 sep 48802 Oct 50902 Nov 46102 Dec 4818\begin{array}{l}\text { Umbrella Sales of JD Inc. }\\\begin{array} { | c | c | c| } \hline \text { Year } & \text { Month } & \text { Units } \\\hline 1 & \text { Jan } & 3980 \\\hline 1 & \text { Feb } & 4000 \\\hline 1 & \text { Mar } & 4740 \\\hline 1 & \text { April } & 4720 \\\hline 1 & \text { May } & 4920 \\\hline 1 & \text { Jul } & 5140 \\\hline 1 & \text { July } & 4640 \\\hline 1 & \text { Aug } & 4520 \\\hline 1 & \text { Sep } & 4480 \\\hline 1 & \text { Oct } & 4690 \\\hline 1 & \text { Nov } & 4210 \\\hline 1 & \text { Dec } & 4418 \\\hline 2 & \text { Jan } & 4380 \\\hline 2 & \text { Feb } & 4400 \\\hline 2 & \text { Mar } & 5140 \\\hline 2 & \text { April } & 5120 \\\hline 2 & \text { May } & 5320 \\\hline 2 & \text { JuI } & 5540 \\\hline 2 & \text { July } & 5040 \\\hline 2 & \text { Aug } & 4920 \\\hline 2 & \text { sep } & 4880 \\\hline 2 & \text { Oct } & 5090 \\\hline 2 & \text { Nov } & 4610 \\\hline 2 & \text { Dec } & 4818 \\\hline\end{array}\end{array}

-Using an appropriate Holt-Winters trend model, calculate the value of the mean absolute percentage error for the given data.

A) 8.10
B) 330.01
C) 384.83
D) 7.21
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27
The indexes in the forecasting indicators provide a complete forecast.
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28
Indicators are measures that are believed to influence the behavior of a variable an individual wishes to forecast.
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29
Using double exponential smoothing, find the value of the root mean square error for the given data.

A) 8.10
B) 91.27
C) 11976.17
D) 109.44
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30
Use the data given below to answer the following questions).
The table below provides the sales data for JD Inc. for the year 1998. Given: ? = 0.2, ? = 0.15, and ? = 0.05 Hint: Use an additive Holt-Winters model.)  Umbrella Sales of JD Inc.  Year  Month  Units 1 Jan 39801 Feb 40001 Mar 47401 April 47201 May 49201 Jul 51401 July 46401 Aug 45201 Sep 44801 Oct 46901 Nov 42101 Dec 44182 Jan 43802 Feb 44002 Mar 51402 April 51202 May 53202 JuI 55402 July 50402 Aug 49202 sep 48802 Oct 50902 Nov 46102 Dec 4818\begin{array}{l}\text { Umbrella Sales of JD Inc. }\\\begin{array} { | c | c | c| } \hline \text { Year } & \text { Month } & \text { Units } \\\hline 1 & \text { Jan } & 3980 \\\hline 1 & \text { Feb } & 4000 \\\hline 1 & \text { Mar } & 4740 \\\hline 1 & \text { April } & 4720 \\\hline 1 & \text { May } & 4920 \\\hline 1 & \text { Jul } & 5140 \\\hline 1 & \text { July } & 4640 \\\hline 1 & \text { Aug } & 4520 \\\hline 1 & \text { Sep } & 4480 \\\hline 1 & \text { Oct } & 4690 \\\hline 1 & \text { Nov } & 4210 \\\hline 1 & \text { Dec } & 4418 \\\hline 2 & \text { Jan } & 4380 \\\hline 2 & \text { Feb } & 4400 \\\hline 2 & \text { Mar } & 5140 \\\hline 2 & \text { April } & 5120 \\\hline 2 & \text { May } & 5320 \\\hline 2 & \text { JuI } & 5540 \\\hline 2 & \text { July } & 5040 \\\hline 2 & \text { Aug } & 4920 \\\hline 2 & \text { sep } & 4880 \\\hline 2 & \text { Oct } & 5090 \\\hline 2 & \text { Nov } & 4610 \\\hline 2 & \text { Dec } & 4818 \\\hline\end{array}\end{array}

-What will be the predicted sales for umbrellas for the month of February of year 2?

A) 4530.19
B) 4648.21
C) 4883.76
D) 4818.07
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31
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-Determine the value of the mean absolute deviation using the Holt-Winters no-trend model for the given data.

A) 367.35
B) 18.39
C) 21.70
D) 252.55
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32
For the given data, what is the sales forecast for the year 1992 in thousands)?

A) 1256.87
B) 1317.91
C) 1285.74
D) 1350.08
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33
Use the data shown below to answer the following questions).
The table below is the data set of the Shiller Real Home Price Index for the years 1946-1956. Use the data shown below to answer the following questions). The table below is the data set of the Shiller Real Home Price Index for the years 1946-1956.   Setting k = 3, determine the simple moving average forecast for the year 1950.
Setting k = 3, determine the simple moving average forecast for the year 1950.
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34
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-Which of the following is the value of the root mean square error for the given data?

A) 252.55
B) 367.35
C) 21.70
D) 109.76
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35
Use the data given below to answer the following questions).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: ? = 0.2, ? = 0.05, and season length = 1. Hint: Use XLMiner).  Year  Units sold in  thousands 175028233103441945515566130071346811509967101200\begin{array} { | c | c | } \hline \text { Year } & \begin{array} { c } \text { Units sold in } \\\text { thousands }\end{array} \\\hline 1 & 750 \\\hline 2 & 823 \\\hline 3 & 1034 \\\hline 4 & 1945 \\\hline 5 & 1556 \\\hline 6 & 1300 \\\hline 7 & 1346 \\\hline 8 & 1150 \\\hline 9 & 967 \\\hline 10 & 1200 \\\hline\end{array}

-Calculate the value of the mean absolute percentage error using the Holt-Winters no-trend model for the given data.

A) 8.10
B) 18.39
C) 21.70
D) 10.97
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36
Use the data given below to answer the following questions).
The table below provides the sales data for JD Inc. for the year 1998. Given: ? = 0.2, ? = 0.15, and ? = 0.05 Hint: Use an additive Holt-Winters model.)  Umbrella Sales of JD Inc.  Year  Month  Units 1 Jan 39801 Feb 40001 Mar 47401 April 47201 May 49201 Jul 51401 July 46401 Aug 45201 Sep 44801 Oct 46901 Nov 42101 Dec 44182 Jan 43802 Feb 44002 Mar 51402 April 51202 May 53202 JuI 55402 July 50402 Aug 49202 sep 48802 Oct 50902 Nov 46102 Dec 4818\begin{array}{l}\text { Umbrella Sales of JD Inc. }\\\begin{array} { | c | c | c| } \hline \text { Year } & \text { Month } & \text { Units } \\\hline 1 & \text { Jan } & 3980 \\\hline 1 & \text { Feb } & 4000 \\\hline 1 & \text { Mar } & 4740 \\\hline 1 & \text { April } & 4720 \\\hline 1 & \text { May } & 4920 \\\hline 1 & \text { Jul } & 5140 \\\hline 1 & \text { July } & 4640 \\\hline 1 & \text { Aug } & 4520 \\\hline 1 & \text { Sep } & 4480 \\\hline 1 & \text { Oct } & 4690 \\\hline 1 & \text { Nov } & 4210 \\\hline 1 & \text { Dec } & 4418 \\\hline 2 & \text { Jan } & 4380 \\\hline 2 & \text { Feb } & 4400 \\\hline 2 & \text { Mar } & 5140 \\\hline 2 & \text { April } & 5120 \\\hline 2 & \text { May } & 5320 \\\hline 2 & \text { JuI } & 5540 \\\hline 2 & \text { July } & 5040 \\\hline 2 & \text { Aug } & 4920 \\\hline 2 & \text { sep } & 4880 \\\hline 2 & \text { Oct } & 5090 \\\hline 2 & \text { Nov } & 4610 \\\hline 2 & \text { Dec } & 4818 \\\hline\end{array}\end{array}

-Calculate the value of the mean square error using an appropriate Holt-Winters trend model for the given data.

A) 8.10
B) 346.26
C) 140942.78
D) 7.62
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37
Which of the following equations is the trend line equation for the given data? Note: the fitted model assumes that the years are numbered 1 through 10, not the actual dates.)

A) 60.123x + 481.56
B) 48.16x + 481.86
C) 32.17x + 931.87
D) 57.15x + 503.81
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38
Use the data given below to answer the following questions).
The table below provides the sales data for JD Inc. for the year 1998. Given: ? = 0.2, ? = 0.15, and ? = 0.05 Hint: Use an additive Holt-Winters model.)  Umbrella Sales of JD Inc.  Year  Month  Units 1 Jan 39801 Feb 40001 Mar 47401 April 47201 May 49201 Jul 51401 July 46401 Aug 45201 Sep 44801 Oct 46901 Nov 42101 Dec 44182 Jan 43802 Feb 44002 Mar 51402 April 51202 May 53202 JuI 55402 July 50402 Aug 49202 sep 48802 Oct 50902 Nov 46102 Dec 4818\begin{array}{l}\text { Umbrella Sales of JD Inc. }\\\begin{array} { | c | c | c| } \hline \text { Year } & \text { Month } & \text { Units } \\\hline 1 & \text { Jan } & 3980 \\\hline 1 & \text { Feb } & 4000 \\\hline 1 & \text { Mar } & 4740 \\\hline 1 & \text { April } & 4720 \\\hline 1 & \text { May } & 4920 \\\hline 1 & \text { Jul } & 5140 \\\hline 1 & \text { July } & 4640 \\\hline 1 & \text { Aug } & 4520 \\\hline 1 & \text { Sep } & 4480 \\\hline 1 & \text { Oct } & 4690 \\\hline 1 & \text { Nov } & 4210 \\\hline 1 & \text { Dec } & 4418 \\\hline 2 & \text { Jan } & 4380 \\\hline 2 & \text { Feb } & 4400 \\\hline 2 & \text { Mar } & 5140 \\\hline 2 & \text { April } & 5120 \\\hline 2 & \text { May } & 5320 \\\hline 2 & \text { JuI } & 5540 \\\hline 2 & \text { July } & 5040 \\\hline 2 & \text { Aug } & 4920 \\\hline 2 & \text { sep } & 4880 \\\hline 2 & \text { Oct } & 5090 \\\hline 2 & \text { Nov } & 4610 \\\hline 2 & \text { Dec } & 4818 \\\hline\end{array}\end{array}

-What is the value of the mean absolute deviation for the given data?

A) 8.10
B) 340.73
C) 14.82
D) 7.62
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39
Use the data shown below to answer the following questions).
The table below is the data set of the Shiller Real Home Price Index for the years 1946-1956. Use the data shown below to answer the following questions). The table below is the data set of the Shiller Real Home Price Index for the years 1946-1956.   Setting k = 5, calculate the simple moving average forecast for the year 1951.
Setting k = 5, calculate the simple moving average forecast for the year 1951.
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40
Using double exponential smoothing, calculate the value of the mean absolute deviation for the given data.

A) 8.10
B) 1.80
C) 91.27
D) 11976.17
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41
If a time series has seasonality but no trend, the most appropriate model used for forecasting is the Holt-Winters multiplicative model.
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42
Explain the different types of Holt-Winters models used in forecasting.
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43
Explain econometric models used in forecasting with examples.
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44
Write a short note on indicators and indexes used in forecasting.
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45
Explain the significance of using double moving average and double exponential smoothing models.
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46
The Holt-Winters additive model applies to time series whose amplitude increases or decreases over time.
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47
What is simple exponential smoothing?
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