In: Finance
X 2 3 1 1 4
Y 3 3 -1 0 6
a) calculate the slope and y-intercept for these data.
Y= ( )+ ( )X (Round to four decimal places).
b) Calculate the total sum of squares (SST)
SST= (Round to one decimal places)
c) Partition the sum of squares into the SSR and SSE
SSE= (Round to three decimal places)
SSR= (Round to three decimal places)
Note: the problem is solved thru data analysis module of Excel and please find the output below for all the details :
Equation Y = --2.2647 + 2.0294(x)
Output
Regression Statistics | ||||||||
Multiple R | 0.953562738 | |||||||
R Square | 0.909281895 | |||||||
Adjusted R Square | 0.879042526 | |||||||
Standard Error | 0.965076447 | |||||||
Observations | 5 | |||||||
ANOVA | ||||||||
df | Sum Square | MS | F | Significance F | ||||
Regression | 1 | 28.00588235 | 28.00588235 | 30.06947368 | 0.011928486 | |||
Residual | 3 | 2.794117647 | 0.931372549 | |||||
Total | 4 | 30.8 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | -2.264705882 | 0.921516477 | -2.457585879 | 0.091062739 | -5.197382591 | 0.667970827 | -5.197382591 | 0.667970827 |
X Variable 1 | 2.029411765 | 0.370089923 | 5.483563958 | 0.011928486 | 0.851620456 | 3.207203074 | 0.851620456 | 3.207203074 |
RESIDUAL OUTPUT | ||||||||
Observation | Predicted Y | Residuals | Standard Residuals | |||||
1 | 1.794117647 | 1.205882353 | 1.442821453 | |||||
2 | 3.823529412 | -0.823529412 | -0.98534148 | |||||
3 | -0.235294118 | -0.764705882 | -0.914959946 | |||||
4 | -0.235294118 | 0.235294118 | 0.281526137 | |||||
5 | 5.852941176 | 0.147058824 | 0.175953836 |