Chapter 15

The regression line may be referred to as
1. the line of best fit
2. the least squares line
3. the regression of y on x
4. all of the above
If the correlation coefficient is equal to +1 then
1. all points will lie on a line sloping upwards to the right
2. all points will lie on a line sloping downwards to the right
3. some points will lie on a line sloping upwards to the right
4. some points will lie on a line sloping downwards to the right
If the correlation coefficient is equal to -0.3 then we would expect to make
1. good predictions from a regression line sloping upwards to the right
2. good predictions from a regression line sloping downwards to the right
3. poor predictions from a regression line sloping upwards to the right
4. poor predictions from a regression line sloping downwards to the right
Which of the following equations best describe this data?
1. y = 8 + 12x
2. y = 12 + 8x
3. y = 8
4. y = 12
You have been given the following data for y and x:

Which of the following equations best describe this data?
1. y = 11 + 3x
2. y = 20 + 3x
3. y = 11 + 5x
4. y = 20 + 5x
You have been given the following data for y and x:

x 15 16 17 17 18
y 71 72 74 84 87

Which of the following regression lines do you think would best fit this data?
Hint: you should be helpful to draw the scatter diagram first
1. y = -12.42 - 5.42x
2. y = -12.42 + 5.42x
3. y = +12.42 + 5.42x
4. y = +12.42 - 5.42x
If the value we would predict for y given x = 9 is
1. 212.6
2. 212.8
3. 213.8
4. 214.6
If the value we would predict for y given x = -12 is
1. -117
2. 117
3. -87
4. 87
Extrapolation is
1. prediction outside the range of the data
2. any prediction
3. prediction within the range of the data
4. no prediction
A transformation to linearity
1. will allow regression analysis to be used
2. will reduce the correlation coefficient
3. limit further analysis
4. is unnecessary provided you have sufficient data

Chapter 15

Quiz