explain all and show with excel formula and working for calculation Assuming a linear relationship, use the least squares method to determine the intercept b0 and slope b1. (0.5 point)

c. Interpret the meaning of the intercept and the slope.

d. Predict the mean ROE for a bank with a leverage ratio of 9 %.

e. What is the nature of the relationship between ROE and leverage ratio?

f. Determine the coefficient of determination (r^2) squared and interpret its meaning in this data. (1 point)

g. Determine the standard error of the estimate and evaluate whether this number is a good value for this data. (1 point)

h. How useful do you think this regression model is for ROE? (1 point - How you reached your decision is point and the decision, if correct is )

i. Perform a residual analysis for these data. Based on your results, evaluate whether the assumptions of regression have been seriously violated.

j. At the 0.05 level of significance, is there evidence of a linear relationship between leverage ratio and ROE? - How you reached your decision and the decision, if correct

k. Construct a 95% confidence interval estimate of the population slope (b1)

Question 2 Fill in the rest of the following ANOVA table, if the number of observations is 30 and there is one independent variable.

ANOVA
	df	SS	MS	F	Significance F
Regression	a	1445.1719	f	g	h
Residual	b	d	46.0962
Total	c	e

i) What are the values of a, b, c, d, e, f and g in the table? - a, b, d, f & g ; c & e are ; and h

ii) What is the coefficient of determination (r^2) of this regression? Show your calculation. EXPLAIN ALL SHOW value WITH EXCEL FORMULA only AND FOLLOW GIVEN VALUE

Regression Statistics
Multiple R	0.211812508
R Square	0.044864539
Adjusted R Square	0.00333691
Standard Error	2.188469336
Observations	25
ANOVA
	df	SS	MS	F	Significance F
Regression	1	5.174245188	5.174245188	1.080353971	0.309422363
Residual	23	110.1561548	4.789398035
Total	24	115.3304
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%
Intercept	12.88293068	2.496744924	5.159890606	3.14024E-05	7.718020293	18.04784107	7.718020293
Leverage Ratio (%)	-0.268713787	0.258527599	-1.039400775	0.309422363	-0.803518871	0.266091298	-0.803518871
RESIDUAL OUTPUT					PROBABILITY OUTPUT
Observation	Predicted ROE (%)	Residuals	Standard Residuals		Percentile	ROE (%)
1	10.33014971	3.46985029	1.619615685		2	4.6
2	10.94819142	4.551808581	2.124639382		6	7.7
3	9.873336273	0.726663727	0.339183501		10	8.2
4	10.67947763	0.720522367	0.33631691		14	8.5
5	11.16316245	-1.163162449	-0.542927213		18	8.7
6	10.33014971	0.76985029	0.359341614		22	8.7
7	10.89444866	-1.294448662	-0.604207439		26	8.8
8	10.65260625	-0.452606254	-0.211262195		30	9.1
9	10.35702109	1.342978911	0.626859815		34	9.2
10	10.49137798	0.308622018	0.144054936		38	9.6
11	10.00769317	2.792306834	1.303359963		42	10
12	10.24953557	-1.149535574	-0.536566622		46	10.2
13	10.5988635	1.901136503	0.887390015		50	10.6
14	10.54512074	-1.84512074	-0.861243639		54	10.8
15	10.49137798	-2.291377982	-1.069542318		58	10.8
16	9.927079031	-5.327079031	-2.486510954		62	11.1
17	10.06143592	-2.361435924	-1.102243135		66	11.2
18	9.228423186	-0.728423186	-0.340004761		70	11.2
19	10.14205006	0.65794994	0.307110093		74	11.4
20	9.873336273	-1.173336273	-0.54767603		78	11.5
21	10.11517868	1.384821319	0.646390519		82	11.7
22	9.443394215	1.756605785	0.819927676		86	12.5
23	10.89444866	-2.094448662	-0.977621978		90	12.8
24	10.14205006	1.05794994	0.493817362		94	13.8
25	10.76009177	-1.560091769	-0.728201187		98	15.5