Question

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.818616296
R Square	0.67013264
Adjusted R Square	0.658351663
Standard Error	9.16867179
Observations	30
ANOVA
	df	SS	MS	F	Significance F
Regression	1	4781.80995	4781.80995	56.8826	3.2455E-08
Residual	28	2353.807187	84.06454239
Total	29	7135.617137
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	28.21496731	3.739591617	7.544932763	3.22E-08	20.55476114	35.87517349
Dividend	2.367177613	0.313863719	7.542055589	3.25E-08	1.724256931	3.010098296

c. You run a regression analysis using Data Analysis to answer the following question: Is stock selling price a function of annual dividend?

The Regression output table is to the right. Is the overall model statistically significant? State how you made your decision.

g. Interpret the coefficient of determination (r2)

e. What are the regression coefficients for the independent variable and the constant from the table?
	b0:
	b1:

f.   Interpret the regression coefficients.
	b0:
	b1:

g. Write the regression equation using the regression coefficient and constant.

h.   What is the predicted price per share of a stock for a company that gives an annual dividend of $18?

Answer 1

c) To check whether overall model is statistically significant we perform F test

Test statistic , F = 56.8826

The P value for F with (1,28) df is less than 0.0001 (the significance F )

Since P value is very small , we can conclude that the overall model is significant

d) Coefficient of determination , r² = 0.6701

That means 67.01% variation in stock selling price can be explained the model .

e) b0 = 28.21497 (constant /y- intercept )

b1= 2.36718 (coefficient of independent variable, dividend / slope )

f) b0 , which is the y intercept , is the value of y when x=0 . In the context of the problem $28.21  is the stock selling price when annual dividend is zero.

y intercept may not have any practical meaning most of the time , but it has mathematical significance.

b1: the slope , for each unit increase in independent variable (annual dividend) , the independent variable increases by $2.37 on an average .

g) The equation of line of regression is

Stock selling price = 28.21 + 2.37 * Annual dividend

h) Predicted price per share of a stock = 28.21 + 2.37* 18

= $70.87

g)

W