In: Statistics and Probability
Consider the following set of ordered pairs.
x |
33 |
11 |
55 |
44 |
|
---|---|---|---|---|---|
y |
44 |
33 |
44 |
44 |
a) Calculate the slope and y-intercept for these data.
b) Calculate the total sum of squares (SST).
c) Partition the sum of squares into the SSR and SSE.
For the given data using Regression in Excel we get output as
SUMMARY OUTPUT | ||||||
Regression Statistics | ||||||
Multiple R | 0.878310066 | |||||
R Square | 0.771428571 | |||||
Adjusted R Square | 0.657142857 | |||||
Standard Error | 0.292770022 | |||||
Observations | 4 | |||||
ANOVA | ||||||
df | SS | MS | F | Significance F | ||
Regression | 1 | 0.578571429 | 0.578571 | 6.75 | 0.121689934 | |
Residual | 2 | 0.171428571 | 0.085714 | |||
Total | 3 | 0.75 | ||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | 2.914285714 | 0.353409054 | 8.246211 | 0.014389 | 1.393689285 | 4.43488214 |
x | 0.257142857 | 0.098974332 | 2.598076 | 0.12169 | -0.168709322 | 0.68299504 |
From the above output
( a )
Slope = 0.25714
Y intercept = 2.91429
( b )
total sum of squares (SST ) = 0.75
( c )
SSR = 0.578571429
SSE = 0.171428571
Partition the sum of squares into the SSR and SSE.