Using R,
1. Create a linear model to represent the coefficients for the objects fw2 and fwe data. Use the Summary command to show the results of the simple regression analysis.
2. Obtain the confidence intervals for the linear models created in step 3 for the for the fw2 and fwe data.
3. Use the fitted() command to extract the model fitted values for the linear models created in step 3 for the for the fw2 and fwe data.
4. Using the resid() command, obtain the residuals for the linear models created in step 3 for the for the fw2 and fwe data.
Using R,
1. Create a linear model to represent the coefficients for the objects fw2 and fwe data. Use the Summary command to show the results of the simple regression analysis.
2. Obtain the confidence intervals for the linear models created in step 3 for the for the fw2 and fwe data.
3. Use the fitted() command to extract the model fitted values for the linear models created in step 3 for the for the fw2 and fwe data.
4. Using the resid() command, obtain the residuals for the linear models created in step 3 for the for the fw2 and fwe data.
| abund | flow | |
| Taw | 11 | 3 |
| Torridge | 28 | 3 |
| Ouse | 20 | 10 |
| Exe | 4 | 11 |
| Lyn | 15 | 16 |
| Brook | 24 | 24 |
| Ditch | 24 | 27 |
| Fal | 50 | 34 |
fwe
| speed | sfly | |
| Taw | 2 | 9 |
| Torridge | 3 | 25 |
| Ouse | 5 | 15 |
| Exe | 9 | 2 |
| Lyn | 14 | 14 |
| Brook | 24 | 25 |
| Ditch | 29 | 24 |
| Fal | 34 | 47 |
2
