Column coefficient

Assumed source concentrations C0 for four arbitrary elements (column 2), mineral 1-liquid and mineral 2-liquid partition coefficients (columns 3 and 4), residual solid-liquid bulk partition coefficients calculated from mineral abundances listed in Table 9.2. Concentration units are arbitrary. 

In order to decode the effects and interactions the full design matrix with all the contrast coefficients (columns) is needed. This is shown in Table 4. The T column contains the data of all the CRF values and is used to calculate the overall mean effect. 

In the Table A.l, the coefficients are multiplied by m (given in the first coefficients column), so as to get whole numbers. Only those approximations that are likely to be used are included. 

This algorithm takes min(m, n) stages. The total number of pivots accepted is the rank, r, of the equation system.The final array can be decoded by associating each coefficient column with the corresponding variable. Rearranging the array to place the pivotal rows and columns in the order of selection, one can write the results in the partitioned form... 

Section First stage Last stage Column internals Mass transfer coefficient Column diameter (m)... 

When you click on OK, the computer carries out the procedure and puts the output on the screen. A number of statistical parameters are exhibited. You can find the value of correlation coefficient and its square (in the R Square cell). At the bottom of the output are the parameters of the fit. There are columns labeled Coefficient, Standard Error, t Stat, P-Value, Lower 95%, and Upper 95%. There are two rows for the intercept and slope. The intercept row is labeled Intercept, and the slope row is labeled X Variable. The Coefficient column contains the parameter. The Standard Error column contains the error based on the standard deviation (about 68% confidence). The Lower 95% column contains the parameter decremented by the expected error at the 95% confidence level, and the Upper 95% column contains the parameter incremented by the expected error. To obtain the expected error, you will have to do a subtraction. You should look at the list of residuals to see it there is a systematic curvature in the data, which shows up with residuals having one sign at the ends of the fit and the other sign in the middle. 

C Input nbasis X nbasis matrix of transformation coefficients (columns define new orbitals). 

Combining Eqs. (4.10) and (4.11), we see that the function is an eigenfunction if the product of the D matrix with the column vector of the coefficients returns the coefficient column, multiplied by the eigenvalue k, i.e.,... 

Ic = Moment of inertia, column, in" k = End connection coefficient, columns Mq = Overturning moment, in-Lbs N = Number of columns... 

Heat-transfer coefficients —Column approach to flooding and entrainment —Column approach to dumping —Column tray efficiency —Column inverse response —Column-material and energy balances... 

---