Exam 14: Simple Linear Regression

A regression and correlation analysis resulted in the following information regarding a dependent variable (y) and an independent variable (x). ​ The least squares estimate of the intercept or b₀ equals

The following information regarding a dependent variable (y) and an independent variable (x) is provided. ​ SSE = 1.9 SST = 6.8 ​ The MSE is

Regression analysis was applied between demand for a product (y) and the price of the product (x), and the following estimated regression equation was obtained. ​ = 120 - 10x ​ Based on the above estimated regression equation, if price is increased by 3units, then demand is expected to

The following information regarding a dependent variable (y) and an independent variable (x) is provided. ​ SSE = 1.9 SST = 6.8 ​ The coefficient of correlation is

In a simple linear regression analysis (where y is a dependent and x an independent variable), if the y-intercept is positive, then

A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation: ​ = 30,000 + 5x ​ The above equation implies that an

For the following data, the value of SSE = 12.75. ​ The slope of the regression equation is

For the following data, the value of SSE = 12.75. ​ The coefficient of determination (r²) equals

If a data set produces SST =1000 and SSE =600, then the coefficient of determination is

A least squares regression line

The interval estimate of an individual value of y for a given value of x is the

Compared to the confidence interval estimate for a particular value of y in a linear regression model, the interval estimate for an average value of y will be