Question 1

For the following time series, you are given the moving average forecast.   ​ The mean squared error equals

Accepted Answer

A)  42.5. 
B)  20.25. 
C)  170. 
D)  0. 
A)  42.5. 
B)  20.25. 
C)  170. 
D)  0.

Question 2

The time series component that exhibits a repeating pattern over successive periods, often one-year intervals is called a(n) _____ component.

Accepted Answer

A)  trend 
B)  seasonal 
C)  cyclical 
D)  irregular 
A)  trend 
B)  seasonal 
C)  cyclical 
D)  irregular

Question 3

The time series pattern that exists when the data fluctuate around a constant mean is the _____ pattern.

Accepted Answer

A)  horizontal 
B)  trend 
C)  seasonal 
D)  cyclical 
A)  horizontal 
B)  trend 
C)  seasonal 
D)  cyclical

Question 4

You are given the following information on the seasonal-irregular component values for a quarterly time series:   ​ The seasonal index for Quarter 1 is

Accepted Answer

A)  .997. 
B)  1.2. 
C)  4. 
D)  3. 
A)  .997. 
B)  1.2. 
C)  4. 
D)  3.

Question 5

Which of the following is not present in a time series?

Accepted Answer

A)  seasonality 
B)  cross-sectional pattern 
C)  trend 
D)  cyclical pattern 
A)  seasonality 
B)  cross-sectional pattern 
C)  trend 
D)  cyclical pattern

Question 6

Below you are given some values of a time series consisting of 27 time periods.   ​ The estimated quadratic regression equation for these data is
Tt = 14.25 + .45t + .21t2
The forecasted value for time period 28 is

Accepted Answer

A)  32.73. 
B)  100.7. 
C)  109.5. 
D)  191.49. 
A)  32.73. 
B)  100.7. 
C)  109.5. 
D)  191.49.

Question 7

Given an actual demand of 50, its forecast of 53, and an α of .2, what would be the forecast for the next period using exponential smoothing?

Accepted Answer

A)  52.4 
B)  58.9 
C)  61.0 
D)  50.6 
A)  52.4 
B)  58.9 
C)  61.0 
D)  50.6

Question 8

Which of the following forecasting methods puts the least weight on the most recent time series value?

Accepted Answer

A)  exponential smoothing with α = .3 
B)  exponential smoothing with α = .2 
C)  moving average using the most recent 4 periods 
D)  moving average using the most recent 3 periods 
A)  exponential smoothing with α = .3 
B)  exponential smoothing with α = .2 
C)  moving average using the most recent 4 periods 
D)  moving average using the most recent 3 periods

Question 9

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?

Accepted Answer

A)  0 
B)  .1 
C)  .5 
D)  1.0 
A)  0 
B)  .1 
C)  .5 
D)  1.0

Question 10

The actual demand and the forecast for a product are shown below. Calculate MAE and MSE. Show all of your computations.

Accepted Answer

The answer of The actual demand and the forecast for...

Question 11

A sequence of observations on a variable measured at successive periods of time is known as a(n)

Accepted Answer

A)  trend component. 
B)  time series. 
C)  forecast. 
D)  additive time series model. 
A)  trend component. 
B)  time series. 
C)  forecast. 
D)  additive time series model.

For the following time series, you are given the moving average forecast. The mean squared error equals

The time series component that exhibits a repeating pattern over successive periods, often one-year intervals is called a(n) _____ component.

The time series pattern that exists when the data fluctuate around a constant mean is the _____ pattern.

You are given the following information on the seasonal-irregular component values for a quarterly time series: The seasonal index for Quarter 1 is

Which of the following is not present in a time series?

Below you are given some values of a time series consisting of 27 time periods. The estimated quadratic regression equation for these data is T_t = 14.25 + .45t + .21t² The forecasted value for time period 28 is

Given an actual demand of 50, its forecast of 53, and an α of .2, what would be the forecast for the next period using exponential smoothing?

Which of the following forecasting methods puts the least weight on the most recent time series value?

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?

The actual demand and the forecast for a product are shown below. Calculate MAE and MSE. Show all of your computations.

A sequence of observations on a variable measured at successive periods of time is known as a(n)

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Tests of Independence and Goodness of Fit

Experimental Design and Analysis of Variance

Simple Linear Regression

Multiple Regression

Regression Analysis: Model Building

Nonparametric Methods

Decision Analysis

Index Numbers

Statistical Methods for Quality Control

Sample Survey

Filters

Exam 17: Time Series Analysis and Forecasting

For the following time series, you are given the moving average forecast. ​ The mean squared error equals

The time series component that exhibits a repeating pattern over successive periods, often one-year intervals is called a(n) _____ component.

The time series pattern that exists when the data fluctuate around a constant mean is the _____ pattern.

You are given the following information on the seasonal-irregular component values for a quarterly time series: ​ The seasonal index for Quarter 1 is

Which of the following is not present in a time series?

Below you are given some values of a time series consisting of 27 time periods. ​ The estimated quadratic regression equation for these data is Tt = 14.25 + .45t + .21t2 The forecasted value for time period 28 is

Given an actual demand of 50, its forecast of 53, and an α of .2, what would be the forecast for the next period using exponential smoothing?

Which of the following forecasting methods puts the least weight on the most recent time series value?

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?

The actual demand and the forecast for a product are shown below. Calculate MAE and MSE. Show all of your computations.

A sequence of observations on a variable measured at successive periods of time is known as a(n)

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Tests of Independence and Goodness of Fit

Experimental Design and Analysis of Variance

Simple Linear Regression

Multiple Regression

Regression Analysis: Model Building

Nonparametric Methods

Decision Analysis

Index Numbers

Statistical Methods for Quality Control

Sample Survey

Filters

For the following time series, you are given the moving average forecast. The mean squared error equals

You are given the following information on the seasonal-irregular component values for a quarterly time series: The seasonal index for Quarter 1 is

Below you are given some values of a time series consisting of 27 time periods. The estimated quadratic regression equation for these data is T_t = 14.25 + .45t + .21t² The forecasted value for time period 28 is