Company Ticker	Years	Yield
GE	1	0.767
MS	1	1.816
WFC	1.25	0.797
TOTAL	1.75	1.378
TOTAL	3.25	1.748
GS	3.75	3.558
MS	4	4.413
JPM	4.25	2.31
C	4.75	3.332
RABOBK	4.75	2.805
TOTAL	5	2.069
MS	5	4.739
AXP	5	2.181
MTNA	5	4.366
BAC	5	3.699
VOD	5	1.855
SHBASS	5	2.861
AIG	5	3.452
HCN	7	4.184
MS	9.25	5.798
GS	9.25	5.365
GE	9.5	3.778
GS	9.75	5.367
C	9.75	4.414
BAC	9.75	4.949
RABOBK	9.75	4.203
WFC	10	3.682
TOTAL	10	3.27
MTNA	10	6.046
LNC	10	4.163
FCX	10	4.03
NEM	10	3.866
PAA	10.25	3.856
HSBC	12	4.079
GS	25.5	6.913
C	25.75	8.204
GE	26	5.13
GE	26.75	5.138
T	28.5	4.93
BAC	29.75	5.903

Using Excel:

Years to Maturity and Bond Yield. A sample containing years to maturity and (percent) yield for 40 corporate bonds is contained in the file CorporateBonds (Barron's, April 2, 2012). a. Develop a scatter chart of the data using years to maturity as the independent variable. Does a simple linear regression model appear to be appropriate? b. Develop an estimated quadratic regression equation with years to maturity and squared values of years to maturity as the independent variables. How much variation in the sample values of yield is explained by this regression model? Test the relationship between each of the independent variables and the dependent variable at a 0.05 level of significance. How would you interpret this model? c. Create a plot of the linear and quadratic regression lines overlaid on the scatter chart of years to maturity and yield. Does this help you better understand the difference in how the quadratic regression model and a simple linear regression model fit the sample data? Which model does this chart suggest provides a superior fit to the sample data? d. What other independent variables could you include in your regression model to explain