4.67 would be a rounded answer. Really it's 4.666666666666666666 (the 6 go on forever) but we can't write that out.
The first two negatives cancel out and you're left with positive 4. Now go inside the square root and do the exponent. -4*-4 = 16. Then do the -4*3*1 = -12. Do 16-12 = 4. now the square root of 4 = 2. at the dominator is 2*3 = 6. right now they problem should look like 4+- 2/ 6. from there you split the problem in two. so you have 4+2/6 & 4-2/6 then you solve both problems.
6/6 2/6
1 1/3
1 & 1/3 are your answers. I hope this helped!
Http://lbcsd.innersync.com/sites/jhayes/documents/U1M3Gr6pg.49-502015JHayes.pdf
Answer:
Hence the adjusted R-squared value for this model is 0.7205.
Step-by-step explanation:
Given n= sample size=20
Total Sum of square (SST) =1000
Model sum of square(SSR) =750
Residual Sum of Square (SSE)=250
The value of R ^2 for this model is,
R^2 = \frac{SSR}{SST}
R^2 = 750/1000 =0.75
Adjusted
:
Where k= number of regressors in the model.
