INFO Midterm

Suppose a residual plot of x verses the residuals, , shows a nonconstant variance. In particular, as the values of x increase, suppose that the value of the residuals also increase. This means that as the values of x get larger, the ability to predict y becomes less accurate. as the values of x get larger, the error term, , becomes smaller. as the values of x get larger, the values of y become larger. as the values of x get larger, the standard deviation of the residuals becomes smaller.

as the values of x get larger, the ability to predict y becomes less accurate.

Which of the following options is NOT an iterative variable selection procedure? backward elimination. best subsets regression. forward selection. stepwise regression.

best subsets regression

Two variables have a positive linear correlation. As the dependent variable increases, the independent variable will increase. decrease. remain constant. vary normally about its mean.

increase

The study of how a dependent variable y is related to two or more independent variables is called least significant difference analysis. linear regression analysis. multiple linear regression. factorial design analysis.

multiple linear regression

A time-series graph shows that annual sales data have decreased gradually over the past several years. Given this, if a linear trend model is used to forecast future years' sales, the value of the regression slope coefficient will be positive negative approaching zero difficult to determine

negative

The tests of significance in regression analysis are based on assumptions about the error term ε. One such assumption is that the error term ε follows a ________ distribution for all values of x. binomial exponential normal uniform

normal

A _____ is used to visualize sample data graphically and to draw preliminary conclusions about the possible relationship between the variables. contingency table scatter chart bar chart pie chart

scatter chart

Which graphical display is useful in determining which forecasting model to select? box plot a normal distribution bar chart scatter chart

scatter chart

An annual time series cannot exhibit a seasonal component trend component forecast random component

seasonal component

The component of the time series that shows a periodic pattern lasting one year or less is a(n) seasonal pattern. linear trend pattern. exponential trend pattern. cyclical pattern.

seasonal pattern

Regression analysis involving one independent variable and one dependent variable is referred to as factor analysis. time series analysis. simple linear regression. data mining.

simple linear regression

In the simple linear regression equation, the parameter B1 is the _______ of the true regression line. slope x-intercept y-intercept end-point

slope

The average of all the historical data will always provide the best results when the underlying time series is increasing. decreasing. stationary. cyclical.

stationary

A time series whose statistical properties are independent of time is called a(n) forecast. least squares trend line. adjusted model. stationary time series.

stationary time series

The process of making estimates and drawing conclusions about one or more characteristics of a population through analysis of sample data drawn from the population is known as inductive inference. deductive inference. statistical inference. Bayesian inference.

statistical inference

When determining the best estimated regression equation to model a set of data, the procedure that uses an iterative variable selection procedure that considers adding an independent variable and removing an independent variable at each step is called backward elimination. the best subsets procedure. forward selection. stepwise selection.

stepwise selection

The _____ is a measure of the error that results from using the estimated regression equation to predict the values of the dependent variable in a sample. sum of squares due to regression (SSR) error term sum of squares due to error (SSE) residual

sum of squares due to error (SSE)

The procedure of using sample data to find the estimated regression equation is better known as point estimation. interval estimation. the least squares method. extrapolation.

the least squares method

In the simple linear regression equation, the parameter Bo represents the _____ of the true regression line. slope x-intercept y-intercept end-point

y-intercept

When the mean value of the response variable is independent of variation in the predictor variable, the slope of the regression line is positive. zero. negative. infinite.

zero

The tests of significance in regression analysis are based on assumptions about the error term ε. One such assumption is that the error term ε is a random variable with a mean or expected value of 0. 1. x y

0

__________ is a statistical procedure used to develop an equation showing how two variables are related. Regression analysis Data mining Time series analysis Factor analysis

Regression analysis

Suppose an estimated regression equation has a coefficient of determination (r2) of 0.866. Interpret this value. The estimated regression equation explains approximately 86.6% of the variation in the dependent variable. The estimated regression equation explains approximately 75.0% of the variation in the dependent variable. The estimated regression equation explains approximately 93.1% of the variation in the dependent variable. The estimated regression equation explains approximately 13.4% of the variation in the dependent variable.

The estimated regression equation explains approximately 86.6% of the variation in the dependent variable.

The regression model in which a regression relationship based on past time series values is used to predict the future time series values is a(n) causal model. linear regression model. autoregressive model. multiple regression model.

autoregressive model

The component of the time series that results in periodic above-trend and below-trend behavior of the time series lasting more than one year is known as a seasonal pattern linear trend pattern exponential trend pattern cyclical pattern

cyclical pattern

A variable used to model the effect of categorical independent variables is called a explanatory variable. categorical variable. dummy variable. quantitative variable.

dummy variable

We can model a time series with a seasonal pattern by treating the season as a dummy variable. smoothing constant. lagged variable. trend component.

dummy variable

In the simple linear regression model, the ________ accounts for the variability in the dependent variable that cannot be explained by the linear relationship between x and y. constant term error term model parameter residual

error term

The term in the multiple regression model that accounts for the variability in y that cannot be explained by the linear effect of the q independent variables is the error term, the leading coefficient, the coefficient of determination, r2 the response variable,

error term

The _____ is the range of values of the independent variables in the data used to estimate the regression model. confidence interval codomain experimental region validation set

experimental region

Simple linear regression refers to the type of regression analysis for which the relationship between the independent variable and dependent variable are approximated by a(n) exponential curve. straight line. normal curve. piecewise function.

exponential curve

What forecasting method 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? exponential smoothing moving averages weighted moving averages time series decomposition

exponential smoothing

Prediction of the value of the dependent variable outside the experimental region is called interpolation. forecasting. averaging. extrapolation.

extrapolation

A prediction of future values of a time series is called a(n) forecast. lagged value. least squares trend line. adjusted model.

forecast

The difference between the actual time series value and the forecast is the forecast error. absolute forecast error. percent error. lagged error.

forecast error

The process of making conjecture about the value of a population parameter, collecting sample data that can be used to assess this conjecture, measuring the strength of the evidence against the conjecture that is provided by the sample, and using these results to draw a conclusion about the conjecture is known as postulation. hypothesis testing. statistical inference. empirical research.

hypothesis testing

The coefficient of determination can be any positive number. is defined as SSR/SST. is used to measure the slope of the estimated regression line. is interpreted as the percent of the variation in the values of x that are explained by the estimated regression line.

is defined as SSR/SST

Autoregressive models typically violate the condition necessary for inference in time series analysis. least squares regression. forecast modeling. correlation analysis.

least squares regression

The graph of the simple linear regression equation is a(n) _____. ellipse hyperbola parabola line

line

Three of the following forecasting methods are appropriate for a time series with a horizontal pattern. Which one is not appropriate for a time series with a horizontal pattern? exponential smoothing. linear trend regression. moving averages. weighted moving averages.

linear trend regression

A measure of the accuracy of a forecasting method, the average of the absolute value of the errors as a percentage of the corresponding forecast values is the mean absolute error (MAE). mean squared error (MSE). mean absolute percentage error (MAPE). mean forecast error (MFE).

mean absolute percentage error (MAPE)

A measure of forecasting accuracy, the average of the squared differences between the forecast values and the actual time series values is the mean absolute error (MAE). mean squared error (MSE). mean absolute percentage error (MAPE). mean forecast error (MFE).

mean squared error (MSE)

If the historical data on which the model is being built consist of monthly data, the forecasting period would probably be daily weekly monthly annually

monthly

The method that uses the average of the most recent k data values in the time series as the forecast for the next period is called exponential smoothing. linear trend regression. moving averages. weighted moving averages.

moving averages

When there are many independent variables to consider, special procedures are sometimes employed to select the independent variables to include in the regression model. All of the following are examples of variable selection procedures except for backward elimination. forward selection. best subsets. overfitting.

overfitting

A(n) ________ refers to a measurable factor that defines a characteristic of a population, process, or system. random variable expectation parameter residual

parameter

When we use the estimated regression equation to develop an interval that can be used to predict the mean for a specific unit that meets a particular set of given criteria, that interval is called a confidence interval. prediction interval. estimation interval. population interval.

prediction interval

What type of regression model should be used when there is a nonlinear relationship between the independent and dependent variables which is fit by including the independent variable and the square of the independent variable? simple linear regression model multiple variable regression model quadratic regression model exponential regression model

quadratic regression model

While virtually all time series exhibit a __________________, not all time series exhibit other components. seasonal component trend component forecast random component

random component

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the constant term. error term. residual. model parameter.

residual

The tests of significance in regression analysis are based on assumptions about the error term ε. One such assumption is that the variance of ε, denoted by σ 2 , is greater as x increases. less as x increases. the same for all values of x. unrelated to the value of x.

the same for all values of x

The time-series component that implies a long-term upward or downward pattern is called the trend component the time component the exponential component the seasonal component

the trend component

A set of observations on a variable measured at successive points in time or over successive periods of time is referred to as a(n) time series. forecast. least squares trend line. adjusted model.

time series

In regression analysis, when using large data sets, splitting data into ____ will be useful in determining which model to use. training and validation sets sets with similar patterns and trends linear or nonlinear sets seasonal and non-seasonal sets

training and validation sets