ECO 351 Exam 2

In a regression analysis, if SSE = 200 and SSR = 300, then the coefficient of determination is _____.

600

The standardized residual is provided by dividing each residual by its _____.

standard deviation

A procedure used for finding the equation of a straight line that provides the best approximation for the relationship between the independent and dependent variables is ______.

the least squares method

In regression analysis, the independent variable is typically plotted on the _____.

x-axis of a scatter diagram

It is possible for the coefficient of determination to be _____.

less than 1

Regression analysis was applied between sales data (in $1000s) and advertising data (in $100s), and the following information was obtained. ŷ = 12 + 1.8x n = 17 SSR = 225 SSE = 75 Sb1 = 0.2683 Refer to Exhibit 14-3. Based on the above estimated regression equation, if advertising is $3,000, then the point estimate for sales (in dollars) is _____.

$66,000

Regression analysis was applied between sales (in $1000s) and advertising (in $100s), and the following regression function was obtained.ŷ = 500 + 4xBased on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is _____.

$900,000

A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). n = 10 Σx = 55 Σy = 55 Σx2 = 385 Σy2 = 385 Σxy = 220 Refer to Exhibit 14-1. The least squares estimate of b1 equals _____.

-1

The following information regarding a dependent variable (y) and an independent variable (x) is provided. x y 2 4 1 3 4 4 3 6 5 8 SSE = 6 SST = 16 Refer to Exhibit 14-4. The coefficient of determination is _____.

.625

A regression analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). n = 10 Σx = 55 Σy = 55 Σx2 = 385 Σy2 = 385 Σxy = 220 Refer to Exhibit 14-1. The coefficient of determination equals _____.

1

The following information regarding a dependent variable (y) and an independent variable (x) is provided. x y 2 4 1 3 4 4 3 6 5 8 SSE = 6 SST = 16 Refer to Exhibit 14-4. The MSE is _____.

2

Regression analysis was applied between sales data (in $1000s) and advertising data (in $100s), and the following information was obtained. ŷ = 12 + 1.8x n = 17 SSR = 225 SSE = 75 Sb1 = 0.2683 Refer to Exhibit 14-3. Using α = .05, the critical t value for testing the significance of the slope is _____.

2.131

Regression analysis was applied between sales data (in $1000s) and advertising data (in $100s), and the following information was obtained. ŷ = 12 + 1.8x n = 17 SSR = 225 SSE = 75 Sb1 = 0.2683 Refer to Exhibit 14-3. The t statistic for testing the significance of the slope is _____.

6.709

The proportion of the variation in the dependent variable y that is explained by the estimated regression equation is measured by the _____.

Coefficient of determination

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

Residual

The equation that describes how the dependent variable (y) is related to the independent variable (x) is called _____.

The regression model

The numerical value of the coefficient of determination ______.

can be larger or smaller than the coefficient of correlation

In simple linear regression, r2 is the _____.

coefficient of determination

In regression and correlation analysis, if SSE and SST are known, then with this information the _____.

coefficient of determination can be computed

A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation:ŷ = 9 − 3xThe above equation implies that if the price is increased by $1, the demand is expected to _____.

decrease by 3,000 units

Data points having high leverage are often _____.

influential

An observation that has a strong effect on the regression results is called a(n) _____.

influential observation

If the coefficient of correlation is .4, the percentage of variation in the dependent variable explained by the estimated regression equation _____.

is 16%

In a regression analysis, the variable that is used to predict the dependent variable ______.

is the independent variable

The least squares criterion is _____.

min Σ(yi - ŷi)2

Regression analysis is a statistical procedure for developing a mathematical equation that describes how _____.

one dependent and one or more independent variables are related

A data point (observation) that does not fit the trend shown by the remaining data is called a(n) _____.

outlier

The primary tool or measure for determining whether the assumed regression model is appropriate is _____.

residual analysis