Chapter 14: Simple Linear Regression

In regression analysis, the variable that is being predicted is
1. the independent variable
2. the dependent variable
3. usually denoted by x
4. none of the above
In the regression equation y = b_o + b₁_x, b_ois the
1. slope of the line
2. independent variable
3. y intercept
4. none of the above
In the regression equation y = b_o + b₁_x, b₁ is
1. the slope of the line
2. an independent variable
3. the y intercept
4. none of the above
In regression analysis, the variable that is doing the predicting or explaining is
1. the independent variable
2. usually denoted by y
3. the dependent variable
4. none of the above
The coefficient of determination is
1. the square root of the correlation coefficient
2. usually less than zero
3. the correlation coefficient squared
4. none of the above
The value of the coefficient of determination ranges between
1. -1 to +1
2. -1 to 0
3. 1 to infinity
4. 0 to +1
The coefficient of correlation
1. is the coefficient of determination squared
2. is the square root of the coefficient of determination
3. can never be negative
4. none of the above
The range of the correlation coefficient is
1. 0 to +1
2. -1 to 0
3. -1 to 0
4. -1 to +1
If the slope of the regression equation y = b_o + b₁_xis positive, then
1. as x increases y decreases
2. as x increases so does y
3. Either a or b is correct
4. none of the above
The residual refers to
1. y bar_i - y hat_i
2. y_i - y hat_i
3. y hat_i- y bar_i
4. none of the above