Question

Consider the following data for two variables, X and Y

X	6	29	21	15	24
Y	10	30	22	14	25

a. Develop an estimated regression equation for the data of the form y-hat = b_o + b₁ x. Comment on the adequacy of this equation for predicting y . Enter negative value as negative number.

The regression equation is

Y = [          ] + [            ] X (to 2 decimals)

S = [       ] (to 3 decimals)         R^2 = [    ] % ( to 1 decimal ) R-sq adj [              ] % 9 to 1 decimal )

Analysis of Variance

SOURCE DF SS (to 2 decimals) MS (to 2 decimals) F (to 2 decimals) P-value (to 4 decimals) Regression           Residual Error           Total

Using a .05 significance level, the P-value indicates a [ Weak, Strong or No Relationship ] ; note that [    ] % (to 1 decimal) of the variability in y has been explained by x .

 

Answer 1

Using Minitab:

Click Stat > Regression > Regression... on the top menu, as shown below:

You will be presented with the following Regression dialogue box:

After transferring the variables, Click the OK button. The output that Minitab produces is shown below.

The regression equation is

Y = 3.08 + 0.901 X

R2 = [ 96.3 ] % (to 1 decimal ) R-sq adj = [ 95.1 ] % ( to 1 decimal)

Analysis of Variance SOURCE DF SS (to 3 decimals) MS (to 3 decimals) F (to 2 decimals) P-value (to 4 decimals) Regression 1 255.061 255.061 78.56 0.003 Residual Error 3 9.739 3.246     Total 4 264.800

Using a .05 significance level, the P-value indicates a Strong Relationship ] ; note that [ 96.3 ] % (to 1 decimal) of the variability in y has been explained by x .