Question 1

The biggest challenge of regression is:&#10;A)&#160;differentiating the independent variable(s) from the dependent variable(s)&#160;&#10;B)&#160;determining which independent variable(s) to include&#160;&#10;C)&#160;collecting accurate data&#160;&#10;D)&#160;properly coding the variables

Accepted Answer

Determining which independent variable(s) to include is often the biggest challenge in regression. This involves identifying which variables have the most significant impact on the dependent variable and which ones do not contribute significantly. It requires careful analysis of the data, considering possible confounding factors, and selecting the most relevant variables to the model.

Question 2

A useful graph in almost any regression analysis is a scatterplot of residuals (on the vertical axis)versus fitted values (on the horizontal axis),where a &#34;good&#34; fit not only has small residuals,but it has residuals scattered randomly around zero with no apparent pattern.

Accepted Answer

This statement is true. A scatterplot of residuals versus fitted values is a useful tool for evaluating the goodness of fit of a regression model. Ideally, we want the residuals to be small and randomly scattered around zero with no discernible pattern, indicating that the model is a good fit for the data.

Question 3

In regression analysis,the variable we are trying to explain or predict is called the&#10;A)&#160;independent variable&#160;&#10;B)&#160;dependent variable&#160;&#10;C)&#160;regression variable&#160;&#10;D)&#160;statistical variable

Accepted Answer

The dependent variable is the variable that is being explained or predicted by the independent variables in a regression analysis.

Question 4

The smoothing constant used in simple exponential smoothing is analogous to the span in moving averages.

Accepted Answer

The smoothing constant in simple exponential smoothing and the span in moving averages both determine the degree of weight given to past observations in forecasting future values.

Question 5

A &#34;fan&#34; shape in a scatterplot indicates:&#10;A)&#160;nonconstant error variance&#160;&#10;B)&#160;a nonlinear relationship&#160;&#10;C)&#160;the absence of outliers&#160;&#10;D)&#160;sampling error

Accepted Answer

A "fan" shape in a scatterplot indicates a nonconstant error variance, where the variance in the response variable differs across values of the predictor variable. This violation of the constant variance assumption can lead to biased and inefficient regression parameter estimates.

Question 6

The adjusted R2 adjusts R2 for:&#10;A)&#160;non-linearity&#160;&#10;B)&#160;outliers&#160;&#10;C)&#160;low correlation&#160;&#10;D)&#160;the number of explanatory variables in a multiple regression model

Accepted Answer

The adjusted R² accounts for the number of explanatory variables in a model, preventing overestimation of the model's explanatory power when more variables are added.

Question 7

Which of the following is not one of the commonly used summary measures for forecast errors&#10;A)&#160;MAE (mean absolute error)&#160;&#10;B)&#160;MFE (mean forecast error)&#160;&#10;C)&#160;RMSE (root mean square error)&#160;&#10;D)&#160;MAPE (mean absolute percentage error)

Accepted Answer

MAE, RMSE, and MAPE are commonly used summary measures for forecast errors, but MFE is not. MFE is simply the average difference between the forecast and the actual value, without taking into account the direction of the error (whether the forecast was too high or too low). Therefore, it is not as informative as other measures that do take direction into account.

Question 8

The term autocorrelation refers to:&#10;A)&#160;the analyzed data refers to itself&#160;&#10;B)&#160;the sample is related too closely to the population&#160;&#10;C)&#160;the data are in a loop (values repeat themselves)&#160;&#10;D)&#160;time series variables are usually related to their own past values

Accepted Answer

Autocorrelation refers to the correlation of a variable with its own past values in a time series data. It measures the degree of similarity between observations of a variable that is separated by time. So, option D is correct. Option A and C are partially correct but not complete as they do not represent the broader definition of autocorrelation. Option B is incorrect as it does not relate to the concept of autocorrelation.

Question 9

In reference to the equation ,the value 0.10 is the expected change in Y per unit change in X.

Accepted Answer

The coefficient 0.10 is the slope of the regression line, indicating the expected change in Y for a one-unit change in X. Therefore, the statement is true.

Question 10

The adjusted R2 is used primarily to monitor whether extra explanatory variables really belong in a multiple regression model.

Accepted Answer

The adjusted R², also known as the adjusted R-squared, provides a measure of the proportion of variance in the dependent variable that is explained by the independent variables in a multiple regression model. It takes into account the number of variables in the model and adjusts the R-squared value accordingly. A higher adjusted R-squared value indicates that more of the variability in the dependent variable is explained by the independent variables, suggesting that these variables are useful in the model. Therefore, the adjusted R-squared can be used to assess the usefulness of additional explanatory variables in a multiple regression model.

Question 11

The percentage of variation explained R2 is the square of the correlation between the observed Y values and the fitted Y values.

Accepted Answer

The answer of The percentage of variation explained R2 is...

Question 12

The least squares line is the line that minimizes the sum of the residuals.

Accepted Answer

The answer of The least squares line is the line...

Question 13

Forecasting models can be divided into three groups.They are:&#10;A)&#160;time series, optimization, and simulation methods&#160;&#10;B)&#160;judgmental, regression, and extrapolation methods&#160;&#10;C)&#160;judgmental, random, and linear methods&#160;&#10;D)&#160;linear, non-linear, and extrapolation methods

Accepted Answer

The answer of Forecasting models can be divided into three...

Question 14

A time series can consist of four different components: trend,seasonal,cyclical,and random (or noise).

Accepted Answer

The answer of A time series can consist of four...

Question 15

Winter's method is an exponential smoothing method,which is appropriate for a series with trend but no seasonality.

Accepted Answer

The answer of Winter's method is an exponential smoothing method,which...

Question 16

In multiple regression,the regression coefficients reflect the expected change in:&#10;A)&#160;Y when the associated X value increases by one unit, holding the other variables constant&#160;&#10;B)&#160;X when the associated Y value increases by one unit, holding the other variables constant&#160;&#10;C)&#160;Y when the associated X value decreases by one unit, holding the other variables constant&#160;&#10;D)&#160;X when the associated Y value decreases by one unit, holding the other variables constant

Accepted Answer

The answer of In multiple regression,the regression coefficients reflect the...

Question 17

The residual is defined as the difference between the actual and predicted,or fitted values of the response variable.

Accepted Answer

The answer of The residual is defined as the difference...

Question 18

A model that uses temperature,season of the year (fall,winter,spring,summer),and whether or not it is a weekend,to predict the # of customers for the day would include how many independent variables&#10;A)&#160;3&#160;&#10;B)&#160;5&#160;&#10;C)&#160;6&#160;&#10;D)&#160;7

Accepted Answer

The answer of A model that uses temperature,season of the...

Question 19

In regression analysis,we can often use the standard error of estimate se to judge which of several potential regression equations is the most useful.

Accepted Answer

The answer of In regression analysis,we can often use the...

Question 20

When using the moving average method,you must select ____ which represent(s)the number of terms in the moving average.&#10;A)&#160;a smoothing constant&#160;&#10;B)&#160;the explanatory variables&#160;&#10;C)&#160;an alpha value&#160;&#10;D)&#160;a span

Accepted Answer

The answer of When using the moving average method,you must...

Question 21

Exhibit 13-2&#10;The station manager of a local television station is interested in predicting the amount of television (in hours) that people will watch in the viewing area. The explanatory variables are: X1 age (in years), X2 education (highest level obtained, in years) and X3 family size (number of family members in household). The multiple regression output is shown below:&#10;&#8203;  &#10;Refer to Exhibit 13-2.Use the information above to estimate the linear regression model.

Accepted Answer

The answer of Exhibit 13-2&#10;The station manager of a local...

Question 22

Exhibit 13-2&#10;The station manager of a local television station is interested in predicting the amount of television (in hours) that people will watch in the viewing area. The explanatory variables are: X1 age (in years), X2 education (highest level obtained, in years) and X3 family size (number of family members in household). The multiple regression output is shown below:&#10;&#8203;  &#10;Refer to Exhibit 13-2.Identify and interpret the percentage of variation explained (R2)for the model.

Accepted Answer

The answer of Exhibit 13-2&#10;The station manager of a local...

Question 23

Exhibit 13-3&#10;The quarterly numbers of applications for home mortgage loans at a branch office of a large bank are recorded in the table below.&#10;  &#10;Refer to Exhibit 13-3.Use simple exponential smoothing to forecast these data,requesting 4 quarters of future forecasts.Use the default smoothing constant of 0.10.Is this better than the moving average model

Accepted Answer

The answer of Exhibit 13-3&#10;The quarterly numbers of applications for...

Question 24

Exhibit 13-3&#10;The quarterly numbers of applications for home mortgage loans at a branch office of a large bank are recorded in the table below.&#10;  &#10;Refer to Exhibit 13-3.Obtain a simple exponential smoothing forecast again,this time optimizing the smoothing constant.Does it make much of an improvement

Accepted Answer

The answer of Exhibit 13-3&#10;The quarterly numbers of applications for...

Question 25

Exhibit 13-3&#10;The quarterly numbers of applications for home mortgage loans at a branch office of a large bank are recorded in the table below.&#10;  &#10;Refer to Exhibit 13-3.Use a moving average model to forecast these data,requesting 4 quarters of future forecasts.Use a span of 4 quarters.

Accepted Answer

The answer of Exhibit 13-3&#10;The quarterly numbers of applications for...

Question 26

Exhibit 13-2&#10;The station manager of a local television station is interested in predicting the amount of television (in hours) that people will watch in the viewing area. The explanatory variables are: X1 age (in years), X2 education (highest level obtained, in years) and X3 family size (number of family members in household). The multiple regression output is shown below:&#10;&#8203;  &#10;Refer to Exhibit 13-2.Interpret each of the estimated regression coefficients of the regression model above.

Accepted Answer

The answer of Exhibit 13-2&#10;The station manager of a local...

Question 27

Exhibit 13-1&#10;An express delivery service company recently conducted a study to investigate the relationship between the cost of shipping a package (Y), the package weight in pounds (X1), and the distance shipped in miles (X2). Twenty packages were randomly selected from among the large number received for shipment, and a detailed analysis of the shipping cost was conducted for each package. The sample information is shown in the table below:&#10;  &#10;Refer to Exhibit 13-1.Add the second explanatory variable (distance shipped)to the regression model.Estimate and interpret the slopes of this expanded model.

Accepted Answer

The answer of Exhibit 13-1&#10;An express delivery service company recently...

Question 28

Exhibit 13-3&#10;The quarterly numbers of applications for home mortgage loans at a branch office of a large bank are recorded in the table below.&#10;  &#10;Refer to Exhibit 13-3.Obtain a time series chart.Which of the forecasting models (one or more)do you think should be used for forecasting based on this chart&#10; Why

Accepted Answer

The answer of Exhibit 13-3&#10;The quarterly numbers of applications for...

Question 29

Exhibit 13-1&#10;An express delivery service company recently conducted a study to investigate the relationship between the cost of shipping a package (Y), the package weight in pounds (X1), and the distance shipped in miles (X2). Twenty packages were randomly selected from among the large number received for shipment, and a detailed analysis of the shipping cost was conducted for each package. The sample information is shown in the table below:&#10;  &#10;Refer to Exhibit 13-1.Estimate a simple linear regression model involving shipping cost and package weight.Interpret the slope coefficient of the least squares line as well as R2.

Accepted Answer

The answer of Exhibit 13-1&#10;An express delivery service company recently...

Question 30

Exhibit 13-1&#10;An express delivery service company recently conducted a study to investigate the relationship between the cost of shipping a package (Y), the package weight in pounds (X1), and the distance shipped in miles (X2). Twenty packages were randomly selected from among the large number received for shipment, and a detailed analysis of the shipping cost was conducted for each package. The sample information is shown in the table below:&#10;  &#10;Refer to Exhibit 13-1.How does the R2 value for this multiple regression model compare to that of the simple regression model estimated above&#10; Interpret the adjusted R2 values for the two models.

Accepted Answer

The answer of Exhibit 13-1&#10;An express delivery service company recently...

Deck 13: Regression and Forecasting Models