Question 1

A higher value of the smoothing constant α makes the forecast less responsive to recent data.

Accepted Answer

A) True 
 B)False

Question 2

A computer analysis reveals that the best-fitting trend model is yt = 4.12e0.987t. The trend was fitted using year-end common stock prices for Melodic Kortholt Outlet for the last six years. The R2 is 0.8571. Which conclusion is not supportable?

Accepted Answer

A) The absolute annual growth (in dollars per share) is increasing. 
B) Few investments could match the astounding growth rate. 
C) At the end of year 3 the stock price would be nearly $80. 
D) The exponential model is inappropriate for financial data. 
A) The absolute annual growth (in dollars per share) is increasing. 
B) Few investments could match the astounding growth rate. 
C) At the end of year 3 the stock price would be nearly $80. 
D) The exponential model is inappropriate for financial data.

Question 3

The shape of the fitted quadratic model yt = 248 - 84t + 2.4t2 is declining, then rising.

Accepted Answer

A) True 
 B)False

Question 4

Which statement is correct regarding forecasting using an exponential smoothing model?

Accepted Answer

A) A model with low α is more responsive to new data than a model with high α. 
B) Increasing α will typically increase the forecast accuracy. 
C) As α increases, more weight is put on recent data. 
D) When data have an upward trend, the forecasts will have an upward bias. 
A) A model with low α is more responsive to new data than a model with high α. 
B) Increasing α will typically increase the forecast accuracy. 
C) As α increases, more weight is put on recent data. 
D) When data have an upward trend, the forecasts will have an upward bias.

Question 5

Use the estimated regression equation yt = 448 + 12t + 18 Qtr1 - 26 Qtr2 + 3 Qtr3 to make a forecast for period 13. The regression model has three quarterly binaries (0 or 1). The model was fitted to 12 periods of quarterly data, starting with the first quarter.

Accepted Answer

A) 588 
B) 476 
C) 622 
D) No forecast is possible without knowing R2. 
A) 588 
B) 476 
C) 622 
D) No forecast is possible without knowing R2.

Question 6

If yt = 256e-0.07t, then the forecast for period 6 is approximately:

Accepted Answer

A) 390. 
B) 203. 
C) 179. 
D) 168. 
A) 390. 
B) 203. 
C) 179. 
D) 168.

Question 7

A firm's income statement contains data measured over a period of time, as opposed to being measured at a point in time.

Accepted Answer

A) True 
 B)False

Question 8

Which trend would you choose to forecast the 2013 value of Bob's beer can collection?

Accepted Answer

A) Linear model. 
B) Exponential model. 
C) They are equivalent. 
A) Linear model. 
B) Exponential model. 
C) They are equivalent.

Question 9

What is the approximate slope of a linear trend for the value of Bob's beer can collection?

Accepted Answer

A) -25 
B) -50 
C) -15 
D) -10 
A) -25 
B) -50 
C) -15 
D) -10

Question 10

Using exponential smoothing, if Ft = 33, yt = 41, and α = .20, what is the new forecast Ft+1?

Accepted Answer

A) 34.6 
B) 36.2 
C) 38.1 
D) 40.2 
A) 34.6 
B) 36.2 
C) 38.1 
D) 40.2

Question 11

The smoothing constant α indicates the weight assigned to the most recent forecast.

Accepted Answer

A) True 
 B)False

Question 12

In the model yt = 516 - 42t + 3t2 the turning point:

Accepted Answer

A) is a peak. 
B) is a trough. 
C) could be either a peak or a trough. 
D) is neither a peak nor a trough. 
A) is a peak. 
B) is a trough. 
C) could be either a peak or a trough. 
D) is neither a peak nor a trough.

Question 13

A multiplicative time-series model Y = T × C × S × I becomes an additive model if we take the logarithm of each side of the equation.

Accepted Answer

A) True 
 B)False

Question 14

Suppose you fit a (linear or nonlinear) trend regression to a monthly time series and discover that the R2 is only 18 percent. The best conclusion is that:

Accepted Answer

A) adding seasonal factors might make things worse. 
B) fitting a seasonal component could raise the R2. 
C) there is no seasonality in the time series. 
D) the overall trend is probably negative. 
A) adding seasonal factors might make things worse. 
B) fitting a seasonal component could raise the R2. 
C) there is no seasonality in the time series. 
D) the overall trend is probably negative.

Question 15

An exponential trend can have a turning point (peak or trough).

Accepted Answer

A) True 
 B)False

Question 16

If a fitted trend equation is yt = 220 - 40t + 2.5t2, then the forecast for period 6 is:

Accepted Answer

A) 225. 
B) 70. 
C) 304. 
D)  110. 
A) 225. 
B) 70. 
C) 304. 
D)  110.

Question 17

Using exponential smoothing, if Ft = 12, yt = 15, and α = .10, what is the new forecast Ft+1?

Accepted Answer

A) 14.1 
B) 12.6 
C) 12.3 
D) 13.7 
A) 14.1 
B) 12.6 
C) 12.3 
D) 13.7

Question 18

The shape of the fitted quadratic model yt = 823 + 72t - 5.1t2 is rising, then declining.

Accepted Answer

A) True 
 B)False

Question 19

Which of the following measures of fit is expressed in the same units as yt?

Accepted Answer

A) SE (standard error) 
B) MAPE (mean absolute percent error) 
C) MSD (mean squared error) 
D) R2 (coefficient of determination) 
A) SE (standard error) 
B) MAPE (mean absolute percent error) 
C) MSD (mean squared error) 
D) R2 (coefficient of determination)

Question 20

For these data, what is the three-period trailing moving average for period 6? $$\begin{array} { | c | c | c | c | c | c | c | c | c | c | } 
\hline t & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 \
\hline y _ { t } & 22 & 33 & 27 & 34 & 38 & 26 & 28 & 35 & 41 \
\hline
\end{array}$$

Accepted Answer

A) 32.67 
B) 31.33 
C) 33.00 
D) 34.67 
A) 32.67 
B) 31.33 
C) 33.00 
D) 34.67

A higher value of the smoothing constant α makes the forecast less responsive to recent data.

A computer analysis reveals that the best-fitting trend model is y_t = 4.12e^0.987^t. The trend was fitted using year-end common stock prices for Melodic Kortholt Outlet for the last six years. The R² is 0.8571. Which conclusion is not supportable?

The shape of the fitted quadratic model y_t = 248 - 84t + 2.4t² is declining, then rising.

Which statement is correct regarding forecasting using an exponential smoothing model?

Use the estimated regression equation y_t = 448 + 12t + 18 Qtr1 - 26 Qtr2 + 3 Qtr3 to make a forecast for period 13. The regression model has three quarterly binaries (0 or 1). The model was fitted to 12 periods of quarterly data, starting with the first quarter.

If y_t = 256e^-0.07^t, then the forecast for period 6 is approximately:

A firm's income statement contains data measured over a period of time, as opposed to being measured at a point in time.

Which trend would you choose to forecast the 2013 value of Bob's beer can collection?

What is the approximate slope of a linear trend for the value of Bob's beer can collection?

Using exponential smoothing, if F_t = 33, y_t = 41, and α = .20, what is the new forecast F_t₊₁?

The smoothing constant α indicates the weight assigned to the most recent forecast.

In the model y_t = 516 - 42t + 3t² the turning point:

A multiplicative time-series model Y = T × C × S × I becomes an additive model if we take the logarithm of each side of the equation.

Suppose you fit a (linear or nonlinear) trend regression to a monthly time series and discover that the R² is only 18 percent. The best conclusion is that:

An exponential trend can have a turning point (peak or trough).

If a fitted trend equation is y_t = 220 - 40t + 2.5t², then the forecast for period 6 is:

Using exponential smoothing, if F_t = 12, y_t = 15, and α = .10, what is the new forecast F_t₊₁?

The shape of the fitted quadratic model y_t = 823 + 72t - 5.1t² is rising, then declining.

Which of the following measures of fit is expressed in the same units as y_t?

For these data, what is the three-period trailing moving average for period 6? t 1 2 3 4 5 6 7 8 9 22 33 27 34 38 26 28 35 41

Overview of Statistics

Data Collection

Describing Data Visually

Descriptive Statistics

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions and Estimation

One-Sample Hypothesis Tests

Two-Sample Hypothesis Tests

Analysis of Variance

Simple Regression

Multiple Regression

Chi-Square Tests

Nonparametric Tests

Quality Management

Filters

Exam 14: Time Series Analysis

A higher value of the smoothing constant α makes the forecast less responsive to recent data.

A computer analysis reveals that the best-fitting trend model is yt = 4.12e0.987t. The trend was fitted using year-end common stock prices for Melodic Kortholt Outlet for the last six years. The R2 is 0.8571. Which conclusion is not supportable?

The shape of the fitted quadratic model yt = 248 - 84t + 2.4t2 is declining, then rising.

Which statement is correct regarding forecasting using an exponential smoothing model?

Use the estimated regression equation yt = 448 + 12t + 18 Qtr1 - 26 Qtr2 + 3 Qtr3 to make a forecast for period 13. The regression model has three quarterly binaries (0 or 1). The model was fitted to 12 periods of quarterly data, starting with the first quarter.

If yt = 256e-0.07t, then the forecast for period 6 is approximately:

A firm's income statement contains data measured over a period of time, as opposed to being measured at a point in time.

Which trend would you choose to forecast the 2013 value of Bob's beer can collection?

What is the approximate slope of a linear trend for the value of Bob's beer can collection?

Using exponential smoothing, if Ft = 33, yt = 41, and α = .20, what is the new forecast Ft+1?

The smoothing constant α indicates the weight assigned to the most recent forecast.

In the model yt = 516 - 42t + 3t2 the turning point:

A multiplicative time-series model Y = T × C × S × I becomes an additive model if we take the logarithm of each side of the equation.

Suppose you fit a (linear or nonlinear) trend regression to a monthly time series and discover that the R2 is only 18 percent. The best conclusion is that:

An exponential trend can have a turning point (peak or trough).

If a fitted trend equation is yt = 220 - 40t + 2.5t2, then the forecast for period 6 is:

Using exponential smoothing, if Ft = 12, yt = 15, and α = .10, what is the new forecast Ft+1?

The shape of the fitted quadratic model yt = 823 + 72t - 5.1t2 is rising, then declining.

Which of the following measures of fit is expressed in the same units as yt?

For these data, what is the three-period trailing moving average for period 6? t 1 2 3 4 5 6 7 8 9 22 33 27 34 38 26 28 35 41

Overview of Statistics

Data Collection

Describing Data Visually

Descriptive Statistics

Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Distributions and Estimation

One-Sample Hypothesis Tests

Two-Sample Hypothesis Tests

Analysis of Variance

Simple Regression

Multiple Regression

Chi-Square Tests

Nonparametric Tests

Quality Management

Filters

A computer analysis reveals that the best-fitting trend model is y_t = 4.12e^0.987^t. The trend was fitted using year-end common stock prices for Melodic Kortholt Outlet for the last six years. The R² is 0.8571. Which conclusion is not supportable?

The shape of the fitted quadratic model y_t = 248 - 84t + 2.4t² is declining, then rising.

Use the estimated regression equation y_t = 448 + 12t + 18 Qtr1 - 26 Qtr2 + 3 Qtr3 to make a forecast for period 13. The regression model has three quarterly binaries (0 or 1). The model was fitted to 12 periods of quarterly data, starting with the first quarter.

If y_t = 256e^-0.07^t, then the forecast for period 6 is approximately:

Using exponential smoothing, if F_t = 33, y_t = 41, and α = .20, what is the new forecast F_t₊₁?

In the model y_t = 516 - 42t + 3t² the turning point:

Suppose you fit a (linear or nonlinear) trend regression to a monthly time series and discover that the R² is only 18 percent. The best conclusion is that:

If a fitted trend equation is y_t = 220 - 40t + 2.5t², then the forecast for period 6 is:

Using exponential smoothing, if F_t = 12, y_t = 15, and α = .10, what is the new forecast F_t₊₁?

The shape of the fitted quadratic model y_t = 823 + 72t - 5.1t² is rising, then declining.

Which of the following measures of fit is expressed in the same units as y_t?