1. Suppose you are trying developed a model predict Expenditure y usingincome as a predictors and you have the regression equation

	coefficients	standard error
Intercept	542	180.66666666667
Income	0.88	0.12571428571429

What is the equation of the regression line

(Hint look at the coefficients)

a.There is not enough information to answer the question.

b.Expenditure =542.00 + 0.89 Income

c.Expenditure =542.00 + 0.88 Income

d.Expenditure =180.67 + 0.22 Income

e.=542.88

2. Consider the following regression output of height X and weight Y for 60 people

	coefficient	standard error
Intercept	51.4	10.1
height	1.4	0.1

so the regression line is y=51.4+1.4x

R square 0.68

What is the interpretation of the gradient (this is the slope)

a.0.68% of the variation of weight is explained by regression line

b.When height is 10 weight is 51.40

c.10% of the variation in Weight is explained by height

d.none of the options are correct

e.Increasing height by 1 will increase weight by 1.40

f.all of the options are correct

g.Increasing height by 51.40 will increase weight by 1.40

3 . Suppose you are testing that there is strong evidence there is a linear relationship between 2 quantitative variables and you find the p-value of the slope is 2.8E-4 and you are 95% confident the slope is between 10 and 12

a.Since the p-value is less than 0.05 there is strong evidence there is a linear relationship

b.Since the p-value is less than 0.05 there is not strong evidence there is a linear relationship between the variables

c.2.8E-4 is the same as 0.000280

d.2.8E-4 is the same as -1.20