Chapter 12 business stat and opt

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The F-value to test the overall significance of a regression model is computed by dividing the sum of squares regression (SSreg) by the sum of squares error (SSerr).

False

The proportion of variability of the dependent variable (y) accounted for or explained by the independent variable (x) is called the coefficient of correlation.

False

The range of admissible values for the coefficient of determination is −1 to +1.

False

The slope of the regression line, y = 21 − 5x, is 21.

False

The slope of the regression line, y = 21 − 5x, is 5.

False

The standard error of the estimate, denoted se, is the square root of the sum of the squares of the vertical distances between the actual Y values and the predicted values of Y.

False

The strength of a linear relationship in simple linear regression change if the units of the data are converted, say from feet to inches.

False

One of the major uses of residual analysis is to test some of the assumptions underlying regression.

True

Regression output from Excel software includes an ANOVA table.

True

Data points that lie apart from the rest of the points are called deviants.

False

If the correlation coefficient between two variables is -1, it means that the two variables are not related.

False

In a simple regression the coefficient of correlation is the square root of the coefficient of determination.

False

In regression, the predictor variable is called the dependent variable.

False

In regression, the variable that is being predicted is usually referred to as the independent variable.

False

In the simple regression model, y = 21 − 5x, if the coefficient of determination is 0.81, we can say that the coefficient of correlation between y and x is 0.90.

False

One of the assumptions of simple regression analysis is that the error terms are exponentially distributed

False

Prediction intervals get narrower as we extrapolate outside the range of the data.

False

Regression output from Excel software directly shows the regression equation.

False

In simple regression analysis the error terms are assumed to be independent and normally distributed with zero mean and constant variance.

True

A t-test is used to determine whether the coefficients of the regression model are significantly different from zero.

True

Correlation is a measure of the degree of linear relationship between two variables.

True

For the regression line, y = 21 − 5x, 21 is the y-intercept of the line.

True

Given x, a 95% prediction interval for a single value of y is always wider than a 95% confidence interval for the average value of y.

True

The coefficient of determination is the proportion of variability of the dependent variable (y) accounted for or explained by the independent variable (x).

True

The difference between the actual y value and the predicted y value found using a regression equation is called the residual.

True

The process of constructing a mathematical model or function that can be used to predict or determine one variable by another variable is called regression analysis.

True

To determine whether the overall regression model is significant, the F-test is used.

True


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