6.232219005 4.96884706
6.613369608 4.387174511
6.181807446 4.313496804
9.665824986 4.532324696
10.1207792 4.857142496
6.70989604 5.738544559
5.955607057 1.372891736
5.804289436 4.851473236
5.825796008 5.109552097
7.58361516 6.13784256
6.418141103 1.653975439
6.565613079 3.718583107
8.095047736 7.565811515
6.266192007 5.410496092
7.449414468 3.990631485
5.884781265 5.817375183
5.848578334 5.382940006
7.322494745 1.959915924
4.979822659 4.798226595
6.995607471 3.684112072
9.309947371 6.19894743
6.256844664 5.288980627
8.221401811 2.185232592
6.636983299 4.71776619
6.137480044 3.737240577
9.219266176 4.385323524
7.549078679 5.585258865
7.559128475 5.746055603
6.505517173 2.877240419
4.711736822 2.117368221
7.631920648 6.910730362
8.079840851 7.307294464
9.335665202 6.713304043
8.594437265 8.899870777
4.064385724 3.715085793
6.940746403 2.861196041
9.378046203 7.560924053
6.792001295 6.888018131
7.847572541 3.358733201
7.063549232 4.703238487
6.89254787 2.138218045
7.249765825 7.496487379
6.670470357 5.186584997
6.406281567 1.487941933
6.180073524 4.290955806
4.190020895 1.260188055
5.991209054 1.835717702
10.31955376 9.230182648
4.713792109 2.137921095
6.418259668 1.655635357
The numbers on above represent a sample of 50 data pairs in protein residue analysis. Within this case a presence of an antibody residue (the X-variable) was paired with the antigen residue (the Y-variable) in a try to find a good predictor of antigen.
Instructions: Employ regression analysis to contrast antibody residue to the antigen residue, and answer the following problems:
1) What is the p-value of regression?
2) Can you reject null hypothesis that there is no relationship among the variables at the 99% confidence level?
3) What is the regression line?
4) What percentage of the response variable is describeed by predictor variable?
5) If 10 antibodies were found, what would be the predicted number of antigens?