Question 1

A cyclical effect is one that repeats at fixed intervals of time, typically a year, month, week, or day.

Accepted Answer

A) True 
 B)False  False

Question 2

Use the data given below to answer the following question(s).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: α = 0.2, γ = 0.05, and season length = 1. (Hint: Use XLMiner). $$\begin{array} { | c | c | } 
\hline \text { Year } & \begin{array} { c } 
\text { Units sold in } \
\text { thousands }
\end{array} \
\hline 1 & 750 \
\hline 2 & 823 \
\hline 3 & 1034 \
\hline 4 & 1945 \
\hline 5 & 1556 \
\hline 6 & 1300 \
\hline 7 & 1346 \
\hline 8 & 1150 \
\hline 9 & 967 \
\hline 10 & 1200 \
\hline
\end{array}$$
-Which of the following is the forecast value for the 6th year?

Accepted Answer

A)  1256.06 
B)  1328.04 
C)  1321.31 
D)  1327.24 
A)  1256.06 
B)  1328.04 
C)  1321.31 
D)  1327.24 B

Question 3

Use the data given below to answer the following question(s).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: α = 0.2, γ = 0.05, and season length = 1. (Hint: Use XLMiner). $$\begin{array} { | c | c | } 
\hline \text { Year } & \begin{array} { c } 
\text { Units sold in } \
\text { thousands }
\end{array} \
\hline 1 & 750 \
\hline 2 & 823 \
\hline 3 & 1034 \
\hline 4 & 1945 \
\hline 5 & 1556 \
\hline 6 & 1300 \
\hline 7 & 1346 \
\hline 8 & 1150 \
\hline 9 & 967 \
\hline 10 & 1200 \
\hline
\end{array}$$
-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.

Accepted Answer

A)  single moving average 
B)  Holt-Winters no-trend smoothing 
C)  double exponential smoothing 
D)  Holt-Winters additive 
A)  single moving average 
B)  Holt-Winters no-trend smoothing 
C)  double exponential smoothing 
D)  Holt-Winters additive A

Question 4

If the actual value of a time series at time t and the forecast value for time t is denoted by At and Ft respectively, then the formula for the mean absolute deviation over a range of forecasted values is .

Accepted Answer

A)  $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left|A_{t}-F_{t}\right|}{n} $ 
B)  $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left(A_{t}-F_{t} \mid\right)^{2}}{n} $ 
C)  $ \mathrm{MAD}=\frac{\sum_{t=1}^{n} \sqrt{\left|A_{t}-F\right|}}{n} $ 
D)  $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left|\frac{A_{t}-F_{t}}{2}\right|}{n} $ 
A)  $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left|A_{t}-F_{t}\right|}{n} $ 
B)  $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left(A_{t}-F_{t} \mid\right)^{2}}{n} $ 
C)  $ \mathrm{MAD}=\frac{\sum_{t=1}^{n} \sqrt{\left|A_{t}-F\right|}}{n} $ 
D)  $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left|\frac{A_{t}-F_{t}}{2}\right|}{n} $

Question 5

Use the data given below to answer the following question(s).
The details of the clock sales at a supermarket for the past 6 weeks are shown in the table below. 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. $$\begin{array} { | c | c | } 
\hline \text { Week } & \text { Units sold } \
\hline 1 & 88 \
\hline 2 & 44 \
\hline 3 & 54 \
\hline 4 & 65 \
\hline 5 & 72 \
\hline 6 & 85 \
\hline
\end{array}$$
-For the given data, what is the value of the simple moving average mean square error?

Accepted Answer

A)  0.21 
B)  20.12 
C)  14.25 
D)  207.13 
A)  0.21 
B)  20.12 
C)  14.25 
D)  207.13

Question 6

If a time series has seasonality but no trend, the most appropriate model used for forecasting is the Holt-Winters multiplicative model.

Accepted Answer

A) True 
 B)False

Question 7

Use the data given below to answer the following question(s).
The details of the clock sales at a supermarket for the past 6 weeks are shown in the table below. 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. $$\begin{array} { | c | c | } 
\hline \text { Week } & \text { Units sold } \
\hline 1 & 88 \
\hline 2 & 44 \
\hline 3 & 54 \
\hline 4 & 65 \
\hline 5 & 72 \
\hline 6 & 85 \
\hline
\end{array}$$
-For the given data, calculate the value of the simple moving average mean absolute percentage error.

Accepted Answer

A)  20.90 
B)  23.45 
C)  14.39 
D)  25.56 
A)  20.90 
B)  23.45 
C)  14.39 
D)  25.56

Question 8

Time-series models may exhibit seasonal effects or cyclical effects. A seasonal effect differs from a cyclical effect in that a seasonal effect:

Accepted Answer

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. 
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 9

Write a short note on indicators and indexes used in forecasting.

Accepted Answer

Indicators are measures that are believe

Question 10

Use the data given below to answer the following question(s).
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. (Hint: Optimize α value in 0.1 increments) $$\begin{array} { | c | c | } 
\hline \text { Week } & \text { Units sold } \
\hline 1 & 88 \
\hline 2 & 44 \
\hline 3 & 54 \
\hline 4 & 65 \
\hline 5 & 72 \
\hline 6 & 85 \
\hline
\end{array}$$
-Calculate the value of the mean absolute percentage error for the given data.

Accepted Answer

A)  20.90 
B)  16.60 
C)  21.72 
D)  29.97 
A)  20.90 
B)  16.60 
C)  21.72 
D)  29.97

Question 11

Identify the components of simple linear regression models and discuss their applications Use the data given below to answer the following question(s).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: α = 0.2 and β
= 0.15 (Hint: Use XLMiner) $$\begin{array} { | c | c | } 
\hline \text { Year } & \begin{array} { c } 
\text { Units sold in } \
\text { thousands }
\end{array} \
\hline 1981 & 888 \
\hline 1982 & 900 \
\hline 1983 & 1000 \
\hline 1984 & 1200 \
\hline 1985 & 1100 \
\hline 1986 & 1300 \
\hline 1987 & 1250 \
\hline 1988 & 1150 \
\hline 1989 & 1100 \
\hline 1990 & 1200 \
\hline
\end{array}$$
-Calculate the value of the mean absolute percentage error using double exponential smoothing for the given data.

Accepted Answer

A)  1.80 
B)  8.10 
C)  91.27 
D)  11976.17 
A)  1.80 
B)  8.10 
C)  91.27 
D)  11976.17

Question 12

Identify the components of simple linear regression models and discuss their applications Use the data given below to answer the following question(s).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: α = 0.2 and β
= 0.15 (Hint: Use XLMiner) $$\begin{array} { | c | c | } 
\hline \text { Year } & \begin{array} { c } 
\text { Units sold in } \
\text { thousands }
\end{array} \
\hline 1981 & 888 \
\hline 1982 & 900 \
\hline 1983 & 1000 \
\hline 1984 & 1200 \
\hline 1985 & 1100 \
\hline 1986 & 1300 \
\hline 1987 & 1250 \
\hline 1988 & 1150 \
\hline 1989 & 1100 \
\hline 1990 & 1200 \
\hline
\end{array}$$
-Identify the value of the mean square error using double exponential smoothing for the given set of data.

Accepted Answer

A)  8.10 
B)  1.80 
C)  91.27 
D)  11976.17 
A)  8.10 
B)  1.80 
C)  91.27 
D)  11976.17

Question 13

Use the data given below to answer the following question(s).
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. (Hint: Optimize α value in 0.1 increments) $$\begin{array} { | c | c | } 
\hline \text { Week } & \text { Units sold } \
\hline 1 & 88 \
\hline 2 & 44 \
\hline 3 & 54 \
\hline 4 & 65 \
\hline 5 & 72 \
\hline 6 & 85 \
\hline
\end{array}$$
-In the linear trend equation Ft+k = at + btk, identify the term that signifies the trend.

Accepted Answer

A)  bt 
B)  k 
C)  at 
D)  Ft + k 
A)  bt 
B)  k 
C)  at 
D)  Ft + k

Question 14

Use the data given below to answer the following question(s).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: α = 0.2, γ = 0.05, and season length = 1. (Hint: Use XLMiner). $$\begin{array} { | c | c | } 
\hline \text { Year } & \begin{array} { c } 
\text { Units sold in } \
\text { thousands }
\end{array} \
\hline 1 & 750 \
\hline 2 & 823 \
\hline 3 & 1034 \
\hline 4 & 1945 \
\hline 5 & 1556 \
\hline 6 & 1300 \
\hline 7 & 1346 \
\hline 8 & 1150 \
\hline 9 & 967 \
\hline 10 & 1200 \
\hline
\end{array}$$
-Calculate the value of the mean absolute percentage error using the Holt-Winters no-trend model for the given data.

Accepted Answer

A)  8.10 
B)  18.39 
C)  21.70 
D)  10.97 
A)  8.10 
B)  18.39 
C)  21.70 
D)  10.97

Question 15

What is a stream of historical data known as?

Accepted Answer

A)  a time series 
B)  an index 
C)  a complex number 
D)  an orthopole 
A)  a time series 
B)  an index 
C)  a complex number 
D)  an orthopole

Question 16

Identify the components of simple linear regression models and discuss their applications Use the data given below to answer the following question(s).
The worldwide sales of cars from 1981-1990 are shown in the table below. Given: α = 0.2 and β
= 0.15 (Hint: Use XLMiner) $$\begin{array} { | c | c | } 
\hline \text { Year } & \begin{array} { c } 
\text { Units sold in } \
\text { thousands }
\end{array} \
\hline 1981 & 888 \
\hline 1982 & 900 \
\hline 1983 & 1000 \
\hline 1984 & 1200 \
\hline 1985 & 1100 \
\hline 1986 & 1300 \
\hline 1987 & 1250 \
\hline 1988 & 1150 \
\hline 1989 & 1100 \
\hline 1990 & 1200 \
\hline
\end{array}$$
-Using the double exponential smoothing, calculate the value of the mean absolute deviation for the given data.

Accepted Answer

A)  8.10 
B)  1.80 
C)  91.27 
D)  11976.17 
A)  8.10 
B)  1.80 
C)  91.27 
D)  11976.17

Question 17

Use the data given below to answer the following question(s).
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. (Hint: Optimize α value in 0.1 increments) $$\begin{array} { | c | c | } 
\hline \text { Week } & \text { Units sold } \
\hline 1 & 88 \
\hline 2 & 44 \
\hline 3 & 54 \
\hline 4 & 65 \
\hline 5 & 72 \
\hline 6 & 85 \
\hline
\end{array}$$
-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?

Accepted Answer

A)  bt = ?(bt - bt-1) + (1 -?)bt-1 
B)  bt = ?Ft-1 + (1 - ?)(at +1 + bt+1) 
C)  bt = ?Ft + (1 - ?)(at -1 + bt-1) 
D)  bt = ?(at - at-1) + (1 -?)bt-1 
A)  bt = ?(bt - bt-1) + (1 -?)bt-1 
B)  bt = ?Ft-1 + (1 - ?)(at +1 + bt+1) 
C)  bt = ?Ft + (1 - ?)(at -1 + bt-1) 
D)  bt = ?(at - at-1) + (1 -?)bt-1

Question 18

Use the data given below to answer the following question(s).
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. (Hint: Optimize α value in 0.1 increments) $$\begin{array} { | c | c | } 
\hline \text { Week } & \text { Units sold } \
\hline 1 & 88 \
\hline 2 & 44 \
\hline 3 & 54 \
\hline 4 & 65 \
\hline 5 & 72 \
\hline 6 & 85 \
\hline
\end{array}$$
-Which of the following is the value of the root mean square error for the given data?

Accepted Answer

A)  11.56 
B)  21.77 
C)  13.87 
D)  20.13 
A)  11.56 
B)  21.77 
C)  13.87 
D)  20.13

Question 19

The indexes in the forecasting indicators provide a complete forecast.

Accepted Answer

A) True 
 B)False

Question 20

Explain econometric models used in forecasting with examples.

Accepted Answer

Student examples may vary.
Explanatory/c

A cyclical effect is one that repeats at fixed intervals of time, typically a year, month, week, or day.

If the actual value of a time series at time t and the forecast value for time t is denoted by At and Ft respectively, then the formula for the mean absolute deviation over a range of forecasted values is .

If a time series has seasonality but no trend, the most appropriate model used for forecasting is the Holt-Winters multiplicative model.

Time-series models may exhibit seasonal effects or cyclical effects. A seasonal effect differs from a cyclical effect in that a seasonal effect:

Write a short note on indicators and indexes used in forecasting.

What is a stream of historical data known as?

The indexes in the forecasting indicators provide a complete forecast.

Explain econometric models used in forecasting with examples.

Business Analytics

Analytics on Spreadsheets

Visualizing and Exploring Data

Descriptive Statistical Measures

Probability Distributions and Data Modeling

Sampling and Estimation

Statistical Inference

Trendlines and Regression Analysis

Introduction to Data Mining

Spreadsheet Modeling and Analysis

Monte Carlo Simulation and Risk Analysis

Linear Optimization

Applications of Linear Optimization

Integer Optimization

Decision Analysis

Filters

Exam 9: Forecasting Techniques

A cyclical effect is one that repeats at fixed intervals of time, typically a year, month, week, or day.

If the actual value of a time series at time t and the forecast value for time t is denoted by At and Ft respectively, then the formula for the mean absolute deviation over a range of forecasted values is .

If a time series has seasonality but no trend, the most appropriate model used for forecasting is the Holt-Winters multiplicative model.

Time-series models may exhibit seasonal effects or cyclical effects. A seasonal effect differs from a cyclical effect in that a seasonal effect:

Write a short note on indicators and indexes used in forecasting.

What is a stream of historical data known as?

The indexes in the forecasting indicators provide a complete forecast.

Explain econometric models used in forecasting with examples.

Business Analytics

Analytics on Spreadsheets

Visualizing and Exploring Data

Descriptive Statistical Measures

Probability Distributions and Data Modeling

Sampling and Estimation

Statistical Inference

Trendlines and Regression Analysis

Introduction to Data Mining

Spreadsheet Modeling and Analysis

Monte Carlo Simulation and Risk Analysis

Linear Optimization

Applications of Linear Optimization

Integer Optimization

Decision Analysis

Filters