Minimally significant difference

The omnibus test statistic, X, follows a distribution with it — 1 df. If the omnibus test is rejected the pairs of groups can be evaluated using a Bonferroni-type approach. This requires the assumption that the ranks are normally distributed. As with the parametric one-way ANOVA, a minimally significant difference in ranks can be calculated for this purpose as ... 

The goal of an analytical separation is to remove either the analyte or the interferent from the sample matrix. To achieve a separation there must be at least one significant difference between the chemical or physical properties of the analyte and interferent. Relying on chemical or physical properties, however, presents a fundamental problem—a separation also requires selectivity. A separation that completely removes an interferent may result in the partial loss of analyte. Altering the separation to minimize the loss of analyte, however, may leave behind some of the interferent. 

Methods that produced results not significantly different from the method with the minimal MAE received rank 1, i.e. all methods with rank 1 had a similar best performance. After determination of this group, the remaining methods with results significantly better than those of MLOGP or AAM received rank 11 and 111, respectively. Methods that had an MAE non-significantly different from (or even worse than) AAM received rank IV. 

Another significant difference between large- and small-scale processing is dilution of the product samples with water. Food processing equipment for fluids often needs to be started with water, and the food needs to be flushed from the system with water before the process is shut down. When making small batch samples in this type of equipment, care must be taken to obtain a representative sample with a minimum of dilution. There will also be a difference in the weights of the sample into and out of the process due to water addition or sample loss to minimize dilution. 

The Surflex-Sim method operates significantly differently [104]. Each of the molecules is surrounded by a set of observer points that characterizes the local character of the surface and potential interactions. Two similar molecules will have a common subset of comparable observer points. A optimal alignment occurs when the differences in pharmacophore character and molecular surface inferred from the observer points are minimized between two molecules. To speed up the algorithm, large molecules can be fragmented into parts which are then compared, and then tested for consistency. This feature also makes the method capable of identifying alignments when one molecule is much smaller than the other. 

Because the reaction is driven by protonation of the carbonyl functionality, reacting species were expected to be localized on the bed of the acid catalyst subjected to microwave irradiation. Hexane was used as a nonpolar solvent to minimize solvent absorption and superheating. Elimination of catalyst superheating in a continuous-flow reactor was most probably the reason why no significant differences were observed between the reaction rates under the action of microwave and conventional heating. 

M) The canonical orbitals used are optimal minimal-basis-set molecular orbitals , as given by Ransil, B. J. Rev. Mod. Phys. 32, 239 (1960). The contours of exact SCF-AO s are not significantly different. 

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