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