Week 7

Given below are Excel outputs for various estimated autoregressive models for a company's real operating revenues (in billions of dollars) from 1989 to 2012. From the data, you also know the real operating revenues for 2010, 2011, and 2012 are 11.7909, 11.7757 and 11.5537, respectively. Referring to the scenario above, if one decides to use the Third-Order Autoregressive model, what will the predicted real operating revenue for the company be in 2013?

$11.62 billion

Given below are Excel outputs for various estimated autoregressive models for a company's real operating revenues (in billions of dollars) from 1989 to 2012. From the data, you also know the real operating revenues for 2010, 2011, and 2012 are 11.7909, 11.7757 and 11.5537, respectively. Referring to the scenario above, if one decides to use the Third-Order Autoregressive model, what will the predicted real operating revenue for the company be in 2015?

$12.47 billion

Given below are Excel outputs for various estimated autoregressive models for a company's real operating revenues (in billions of dollars) from 1989 to 2012. From the data, you also know the real operating revenues for 2010, 2011, and 2012 are 11.7909, 11.7757 and 11.5537, respectively. Referring to the scenario above, if one decides to use the Third-Order Autoregressive model, what will the predicted real operating revenue for the company be in 2014?

$12.57 billion

What is the correlation between Y and the predicted-Y?

0.987

The following table contains the number of complaints received in a department store for the first 6 months of last year. JAN 36 FEB 45 MAR 81 APR 108 MAY 144 Referring to the above table, if a three-term moving average is used to smooth this series, what would be the third calculated term?

111

What is the slope for the independent variable Size and is it significant at an alpha of .05?

12.2, no

A local store developed... during the 5-year period from 2009 to 2013. The following is the resulting regression equation: log10Y = 6.102 + 0.012X - 0.129 Q1 - 0.054 Q2 + 0.098 Q3 Where Y is the estimated number of contracts in a quarter Referring to the scenario above, the estimated quarterly compound growth rate in revenues is around:

2.8%

Referring to Table 16-8, the fitted trend value (in millions of dollars) for 1985 is __________.

35.1

The following table contains the number of complaints received in a department store for the first 6 months of last year. Month/ Complaints table Referring to scenario above, if a three-month moving average is used to smooth this series, what would be the second calculated value?

72

A model that can be used to make predictions about long-term future values of a time series is

All of the selections

In selecting an appropriate forecasting model, the following approaches are suggested:

All of the selections

A real estate builder wishes to determine how house size (House) is influenced by family income (Income), family size (Size), and education of the head of household (School). House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is in years. The builder randomly selected 50 families and ran the multiple regression. The business literature involving human capital shows that education influences an individual's annual income. Combined, these may influence family size. With this in mind, what should the real estate builder be particularly concerned with when analyzing the multiple regression model?

Collinearity

Based on the following scatter plot, which of the time-series components is not present in this quarterly time series? (w/ stock returns quarter image- downward scatter plot)

Cyclical

Which of the following terms describes the up and down movements of a time series that vary both in length and intensity?

Cyclical component

Business closures in a city in the western U.S. from 2007 to 2012 were: 2007 10 2008 11 2009 13 2010 19 2011 24 2012 35 Microsoft Excel was used to fit both first-order and second-order autoregressive models, resulting in the following partial outputs: Referring to the scenario above, the values of the MAD for the two models indicate that the first-order model should be used for forecasting. T/F

False

Referring to Table 16-2, set up a scatter diagram (i.e., time-series plot) with months on the horizontal X-axis. True or False: Referring to Table 16-2, advertising expenditures appear to be increasing in a linear rather than curvilinear manner over time.

False

There is a significant intercation between Size and Cove at an alpha of .05.

False

True or False: Collinearity is present when there is not a high degree of correlation between any of the independent variables.

False

True or False: Given a data set with 9 yearly observations, there are eight 3-year moving averages.

False

True or False: The Variance Inflationary Factor (VIF) measures the correlation of one dependent variable with the other X variables.

False

Given below are Excel outputs for various estimated autoregressive models for a company's real operating revenues (in billions of dollars) from 1989 to 2012. From the data, you also know the real operating revenues for 2010, 2011, and 2012 are 11.7909, 11.7757 and 11.5537, respectively. Referring to the scenario above and using a 5% level of significance, what is the appropriate autoregessive model for the company's real operating revenue?

First-Order Autoregressive Model

Which of the following is not an advantage of exponential smoothing?

It enables us to perform more than one-period ahead forecasting.

Which of the following is not an advantage of exponential smoothing?

It enables you to perform more than one-period ahead forecasting

Which of the following statements about moving averages is not true?

It gives greater weight to more recent data

Which of the following statements about the method of exponential smoothing is not true?

It gives greater weight to the earlier observations in the series

Which of the following methods should not be used for short-term forecasts into the future?

Moving averages

After estimating a trend model for annual time-series data, you obtain the following residual plot against time, the problem with your model is that:

The cyclical component has not been accounted for

A local store... The following is the resulting regression equation: log10Y=6.102+0.012X-0.129 Q1- 0.054 Q2+ 0.098 Q3 where Y is the estimated number of contracts in a quarter. Referring to the scenario above, in testing the significance of the coefficient for Q1 in the regression equation (- 0.129) which has a p-value of 0.492. Which of the following is the best interpretation of this result?

The revenues in the first quarter of the year are not significantly different from the revenues in the fourth quarter (Math Formula = 0.05)

Which of the following terms describes the overall long-term tendency of a time series?

Trend

Each forecast using the method of exponential smoothing depends on all the previous observations in the time series. T/F

True

Given a data set with 15 yearly observations, there are only thirteen 3-year moving averages. T/F

True

The MAD is a measure of the mean of the absolute discrepancies between the actual and the fitted values in a given time series. T/F

True

True or False: Two simple regression models were used to predict a single dependent variable. Both models were highly significant, but when the two independent variables were placed in the same multiple regression model for the dependent variable, R2 did not increase substantially and the parameter estimates for the model were not significantly different from 0. This is probably an example of collinearity.

True

An independent variable Xj is not considered highly correlated with the other independent variables if

VIF < 5

A local store developed... during the 5-year period from 2009 to 2013. The following is the resulting regression equation: log10Y = 6.102 + 0.012X - 0.129 Q1 - 0.054 Q2 + 0.098 Q3 Where Y is the estimated number of contracts in a quarter Referring to the scenario above, to obtain the fitted value for the first quarter of 2013 using the model, which of the following sets of values should be used in the regression equation?

X = 16, Q1 = 1, Q2= 0, Q3 = 0

A contractor developed... using quarterly data on number of contracts during the 3-year period from 2011 to 2013. The following is the resulting regression equation: In Y=3.37 + 0.117 X - 0.083 Q1 + 1.28 Q2 + 0.617 Q3 Referring to the scenario above, to obtain a forecast for the first quarter of 2014 using the model, which of the following sets of values should be used in the regression equation?

X=12, Q1 = 1, Q2 = 0, Q3 = 0

A contractor developed... using quarterly data on number of contracts during the 3-year period from 2011 to 2013. The following is the resulting regression equation: In Y=3.37 + 0.117 X - 0.083 Q1 + 1.28 Q2 + 0.617 Q3 Referring to the scenario above, to obtain a forecast for the fourth quarter of 2014 using the model, which of the following sets of values should be used in the regression equation?

X=15, Q1 = 0, Q2 = 0, Q3 = 0

A local store... The following is the resulting regression equation: log10Y=6.102+0.012X-0.129 Q1- 0.054 Q2+ 0.098 Q3 where Y is the estimated number of contracts in a quarter. Referring to the scenario above, to obtain a forecast for the third quarter 2014 using the model, which of the followings sets of values should e used in the regression equation?

X=22, Q1= 0, Q2= 0, Q3= 1

A local store... The following is the resulting regression equation: log10Y=6.102+0.012X-0.129 Q1- 0.054 Q2+ 0.098 Q3 where Y is the estimated number of contracts in a quarter. Referring to the scenario above, to obtain a fitted value for the fourth quarter of 2010 using the model, which of the following sets of values should be used in the regression equation?

X=7, Q1=0, Q2=0, Q3=0

Referring to Table 15-3, is the overall model statistically adequate at a 0.05 level of significance for predicting sale price (Y)?

Yes, since the p-value for the F-test is smaller than 0.05.

The annual multiplicative time-series model does not possess _______ component.

a seasonal

Model Building Goal is to develop a model with the best set of independent variablesEasier to interpret if unimportant variables are removedLower probability of collinearity

above statement is true

If a group of independent variables are not significant individually but are significant as a group at a specified level of significance, this is most likely due to

collinearity.

The Variance Inflationary Factor (VIF) measures the

correlation of the X variables with each other.

You need to decide whether you should invest in a particular stock. You would like to invest if the price is likely to rise in the long run. You have data on the daily average price of this stock over the past 12 months. Your best action is to

estimate a least square trend model

You need to decide whether you should invest in a particular stock. You would like to invest if the price is likely to rise in the long run. You have data on the daily mean price of this stock over the past 12 months. Your best action is to

estimate a least square trend model

When a time series appears to be increasing at an increasing rate, such that percentage difference from value to value is constant, the appropriate model to fit is the

exponential trend

The following is the list of MAD statistics for each of the models you have estimated from time-series data: Model MAD Linear Trend 2.38 Quadratic Trend 3.22 Exponential Trend 1.39 AR(2) 2.71 Based on the MAD criterion, the most appropriate model is

exponential trend.

When a time series appears to be increasing at an increasing rate, such that percentage differences from observation to observation is constant, the appropriate model to fit is the

exponential trend.

Which of the following is not used to find a "best" model?

inverse SSE

The effect of an unpredictable, rare event will be contained in the ___________ component.

irregular

The method of least squares is used on time-series data for

obtaining the trend equation

The cyclical component of a time series

represents periodic fluctuations which usually occur in 2 or more years.

The fairly regular fluctuations that occur within each year would be contained in the _________________ component.

seasonal

The overall upward or downward pattern of the data in an annual time series will be contained in the ____________ component.

seasonal

To assess the adequacy of a forecasting model, one measure that is often used is

the MAD

When using the exponentially weighted moving average for purposes of forecasting rather than smoothing,

the current smoothed value becomes the forecast.

A local store developed... during the 5-year period from 2009 to 2013. The following is the resulting regression equation: log10Y = 6.102 + 0.012X - 0.129 Q1 - 0.054 Q2 + 0.098 Q3 Where Y is the estimated number of contracts in a quarter Referring to the scenario above, the best interpretation of the constant 6.102 in the regression equation is:

the fitted value for the first quarter of 2009, prior to seasonal adjustment, is 10^6102

A contractor developed... using quarterly data on number of contracts during the 3-year period from 2011 to 2013. The following is the resulting regression equation: In Y=3.37 + 0.117 X - 0.083 Q1 + 1.28 Q2 + 0.617 Q3 Referring to the scenario above,the best interpretation of the coefficient of Q3 (0.617) in the regression equation is:

the number of contracts in the third quarter of a year is approximately 314% higher than it would be during the fourth quarter

A local store developed... during the 5-year period from 2009 to 2013. The following is the resulting regression equation: log10Y = 6.102 + 0.012X - 0.129 Q1 - 0.054 Q2 + 0.098 Q3 Where Y is the estimated number of contracts in a quarter Referring to the scenario above, the best interpretation of the coefficient of Q2( -0.054) in the regression equation is:

the revenues in the second quarter of a year is approximately 11.69% lower than it would be during the fourth quarter.

A local store developed... during the 5-year period from 2009 to 2013. The following is the resulting regression equation: log10Y = 6.102 + 0.012X - 0.129 Q1 - 0.054 Q2 + 0.098 Q3 Where Y is the estimated number of contracts in a quarter Referring to the scenario above, the best interpretation of the coefficient of Q3 (0.098) in the regression equation is:

the revenues in the third quarter of a year is approximately 25.31% higher than it would be during the fourth quarter.

A regression diagnostic tool used to study the possible effects of collinearity is

the variance inflationary factor.

The method of moving averages is used

to smooth a series