qmb test 4

The range of the Durbin-Watson statistic is _____.

0 to 4

In a multiple regression analysis involving 15 independent variables and 200 observations, SST = 800 and SSE = 240. The coefficient of determination is ______.

0.700

For a multiple regression model, SSR = 600 and SSE = 200. The multiple coefficient of determination is _____.

0.75

Adjusted multiple coefficient of determination

A measure of the goodness of fit of the estimated multiple regression equation that adjusts for the number of independent variables in the model and thus avoids overestimating the impact of adding more independent variables.

Multiple coefficient of determination

A measure of the goodness of fit of the estimated multiple regression equation. It can be interpreted as the proportion of the variability in the dependent variable that is explained by the estimated regression equation.

Smoothing constant

A parameter of the exponential smoothing model that provides the weight given to the most recent time series value in the calculation of the forecast value.

Seasonal pattern

A seasonal pattern exists if the time series plot exhibits a repeating pattern over successive periods. The successive periods are often one-year intervals, which is where the name seasonal pattern comes from.

Time series

A sequence of observations on a variable measured at successive points in time or over successive periods of time.

Deseasonalized time series

A time series from which the effect of season has been removed by dividing each original time series observation by the corresponding seasonal index.

Time series decomposition

A time series method that is used to separate or decompose a time series into seasonal and trend components.

Stationary time series

A time series whose statistical properties are independent of time. For a stationary time series the process generating the data has a constant mean and the variability of the time series is constant over time.

Trend pattern

A trend pattern exists if the time series plot shows gradual shifts or movements to relatively higher or lower values over a longer period of time.

Dummy variable

A variable used to model the effect of categorical independent variables. A dummy variable may take only the value zero or one.

Which of the following tests is used to determine whether an additional variable makes a significant contribution to a multiple regression model?

an F test

The correlation in error terms that arises when the error terms at successive points in time are related is termed _____.

autocorrelation

In a multiple regression model, the error term ε is assumed to _____.

be normally distributed

The variable selection procedure that identifies the best regression equation, given a specified number of independent variables, is _____.

best-subsets regression

A variable such as z, whose value is z = x1x2 is added to a general linear model in order to account for potential effects of two variables x1and x2 acting together. This type of effect is _____.

called interaction

A component of the time series model that results in the multi-period above-trend and below-trend behavior of a time series is a(n) _____.

cyclical component

A variable that takes on the values of 0 or 1 and is used to incorporate the effect of qualitative variables in a regression model is called a(n) _____.

dummy variable

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

horizontal pattern

A multiple regression model has the form;

increase by 2 units

Refer to Exhibit 15-2. The coefficient of the unit price indicates that if the unit price is _____.

increased by $1 (holding advertising constant), sales are expected to decrease by $3000

The joint effect of two variables acting together is called _____.

interactino

The estimated regression equation is _____.

intercept + x1 + x2 (coefficient)

If a qualitative variable has k levels, the number of dummy variables required is _____.

k-1

When dealing with the problem of non-constant variance, the reciprocal transformation means using _____.

1/y as the dependent variable instead of y

A regression model involved 5 independent variables and 126 observations. The critical value of t for testing the significance of each of the independent variable's coefficients will have _____.

130 degrees of freedom

To test for the significance of a regression model involving 14 independent variables and 255 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are _____.

14 and 240

To test for the significance of a regression model involving 3 independent variables and 47 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are _____.

3 and 43

Cyclical pattern

A cyclical pattern exists if the time series plot shows an alternating sequence of points below and above the trend line lasting more than one year.

Weighted moving averages

A forecasting method that involves selecting a different weight for the most recent k data values values in the time series and then computing a weighted average of the values. The sum of the weights must equal one.

Exponential smoothing

A forecasting method that uses a weighted average of past time series values as the forecast; it is a special case of the weighted moving averages method in which we select only one weight—the weight for the most recent observation.

Moving averages

A forecasting method that uses the average of the most recent k data values in the time series as the forecast for the next period.

Time series plot

A graphical presentation of the relationship between time and the time series variable. Time is shown on the horizontal axis and the time series values are shown on the vertical axis.

Horizontal pattern

A horizontal pattern exists when the data fluctuate around a constant mean.

Categorical independent variable

An independent variable with categorical data.

the error terms at successive points in time are related.

Autocorrelation Correlation in the errors that arises when

A test to determine whether first-order autocorrelation is present.

Durbin-Watson test

A model of the form y = β0 + β1z1 + β2z2 + ··· + βpzp + ϵ, where each of the independent variables zj (j = 1, 2, ··· , p) is a function of x1, x2, ··· , xk, the variables for which data have been collected.

General linear model

Multiplicative decomposition model

In a multiplicative decomposition model the actual time series value at time period t is obtained by multiplying the values of a trend component, a seasonal component, and an irregular component.

Additive decomposition model

In an additive decomposition model the actual time series value at time period t is obtained by adding the values of a trend component, a seasonal component, and an irregular component.

The effect of two independent variables acting together.

Interaction

Which of the following statements about the backward elimination procedure is false?

It begins with the regression model found using the forward selection procedure.

the process of developing an estimated regression equation that describes the relationship between a dependent variable and one or more independent variables.

Model building

In a multiple regression analysis, SSR = 1,000 and SSE = 200. The F statistic for this model is _____.

Not enough information is provided to answer this question.

Multiple regression analysis

Regression analysis involving two or more independent variables.

The multiple coefficient of determination is _____.

SSR/SST

Same as autocorrelation.

Serial correlation

Mean absolute error (MAE)

The average of the absolute values of the forecast errors.

Mean absolute percentage error (MAPE)

The average of the absolute values of the percentage forecast errors.

Mean squared error (MSE)

The average of the sum of squared forecast errors.

Forecast error

The difference between the actual time series value and the forecast.

Estimated multiple regression equation

The estimate of the multiple regression equation based on sample data and the least squares method; it is ŷ = b0 + b1x1 + b2x2 + .·.·.· + bpxp.

Multiple regression equation

The mathematical equation relating the expected value or mean value of the dependent variable to the values of the independent variables; that is, E(y) = β0 + β1x1 + β2x2+ .·.·.· +βpxp.

Multiple regression model

The mathematical equation that describes how the dependent variable yis related to the independent variables x1, x2, ..., xp and an error term

Least squares method

The method used to develop the estimated regression equation. It minimizes the sum of squared residuals (the deviations between the observed values of the dependent variable, yi, and the estimated values of the dependent variable, ŷi).

Multicollinearity

The term used to describe the correlation among the independent variables.

Methods for selecting a subset of the independent variables for a regression model.

Variable selection procedures

The least squares criterion is _____.

min ∑(yi - i)2

A multiple regression model has _____.

more than one independent variable

In multiple regression analysis, the correlation among the independent variables is termed _____.

multicollinearity

A measure of goodness of fit for the estimated regression equation is the _____.

multiple coefficient of determination

The mathematical equation that explains how the dependent variable y is related to several independent variables x1, x2, ..., xp and the error term ε is a(n) _____.

multiple regression model

All the variables in a multiple regression analysis _____.

none of the answers above

The parameters of nonlinear models have exponents _____.

other than 1

A variable that cannot be measured in numerical terms is called a _____.

qualitative variable

A variable that cannot be measured in terms of how much or how many but instead is assigned values to represent categories is called a(n) _____.

qualitative variable

The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is the _____.

residual

In regression analysis, an outlier is an observation whose _____.

residual is much larger than the rest of the residual values

The following regression model y = β0 + β1x1 + β2x2 + ε is known as _____.

second-order model with one predictor variable

ŷ = 17 + 4x1 - 3x2 + 8x3 + 8x4; For this model, SSR = 700 and SSE = 100.;Refer to Exhibit 15-3. The conclusion is that the _____.

t the mdel is significant

A test to determine whether or not first-order autocorrelation is present is _____.

the Durbin-Watson test

The adjusted multiple coefficient of determination is adjusted for _____.

the number of independent variables

Serial correlation is_____.

the same as autocorrelation

In a multiple regression model, the variance of the error term ε is assumed to be _____.

the same for all values of the independent variable

As the goodness of fit for the estimated multiple regression equation increases, _____.

the value of the multiple coefficient of determination increases

A group of observations measured at successive time intervals is known as a(n) _____.

time series

Gradual shifting or movement of a time series to relatively higher or lower values over a longer period of time is called _____.

trend

Common types of data patterns that can be identified when examining a time series plot include all of the following EXCEPT ______.

vertical

Refer to Exhibit 15-4. Which equation gives the estimated regression line?

ŷ = b0 + b1 x1 + b2 x2

In multiple regression analysis, the word "linear" in the term "general linear model" refers to the fact that_____.

β0, β1, . . . βp, all have exponents of 1