 (Worse) It is a fact that engineers select an appropriate variable and the transformed observations are treated as though they are normally distributed.

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 (Worse) It is a fact that engineers select an appropriate variable and the transformed observations are treated as though they are normally distributed with a constant variance.

 (Better) Engineers select an appropriate variable and treat the transformed observations as though they are normally distributed with a constant variance.

 Omit It is a fact that since it does not add to the sentence’s meaning.  Other examples of needless phrase ◦ It is well known that ◦ It goes without saying that ◦ It may be said that ◦ It is evident that ◦ It has been found that ◦ It has long been known that

 (Worse) Those methods neither require previous knowledge of how the variables are distributed nor are censored data stipulated to be available.

 (Better) Those methods neither require previous knowledge of how the variables are distributed nor stipulate availability of the censored data.

 (Worse) The procedure for analyzing singly censored data in a replicated experiment is as follows: ◦ Step 1: Distinguish the experimental results as the uncensored (complete) data and the censored (incomplete) data. ◦ Step 2: The relationship between the two values must be found by performing regression analysis. ◦ Step 3: Estimate the two variables. ◦ Step 4: The estimated censored data must be ranked.

◦ Step 5: Find the regression models for response average and standard deviation for each trial. ◦ Step 6: The factors that significantly affect the response average and standard derivation must be identified. ◦ Step 7: The optimal factor/level combination must be determined.

 (Batter) The procedure for analyzing singly censored data in a replicated experiment is as follows: ◦ Step 1: Distinguish the experimental results as the uncensored (complete) data and the censored (incomplete) data. ◦ Step 2: Find the relationship between the two values must by performing regression analysis. ◦ Step 3: Estimate the two variables.

◦ Step 4: Rank the estimated censored data. ◦ Step 5: Find the regression models for response average and standard deviation for each trial. ◦ Step 6: Identify the factors that significantly affect the response average and standard derivation. ◦ Step 7: Determine the optimal factor/level combination.

 Depending on the sentence’s context, obtain, derive, attain, identify or distinguish can be used as an alternatives to find.

 (Worse) The derived model provides an extension of an earlier concept [1] and helping industrial managers in determining a feasible number of replenishments.  (Better) The derived model extends an earlier concept [1] and helps industrial managers in determining a feasible number of replenishments.

 Depending on the sentence’s context, assist, facilitate, guide and direct can be used as an alternatives to help.

 (Worse) Experimental design is used in this method to arrange the design parameters and noise factors in the orthogonal arrays and computing the signal-to-noise (SN) ratio based on the quality loss for each experimental combination.

 (Better 1) Experimental design is used in this method to arrange the design parameters and noise factors in the orthogonal arrays and to compute the signal-to-noise (SN) ratio based on the quality loss for each experimental combination.

 (Better 2) Experimental design is used in this method for arranging the design parameters and noise factors in the orthogonal arrays and for computing the signal-to- noise (SN) ratio based on the quality loss for each experimental combination.

 (Worse) The relative importance of each response can be transformed into a fuzzy number through means of the establishment of a formal scale system that can be used to convert linguistic terms into their corresponding fuzzy numbers and to express the relative importance of each response by linguistic term.

 (Better) The relative importance of each response can be transformed into a fuzzy number by establishing a formal scale system that can convert linguistic terms into their corresponding fuzzy numbers and express the relative importance of each response by linguistic term.

 Avoid wordiness by saying by instead of through means of.

 (Worse) The Taguchi approach provides a combination of experimental design techniques with quality loss considerations and that the average quadratic loss is minimized.  (Better) The Taguchi approach combines experimental design techniques with quality loss considerations and minimizes the average quadratic loss.

 (Worse) The conventional approach happens to be cumbersome, complicated and wastes too much time.  (Better) The conventional approach is cumbersome, complicated and time consuming.

 Avoid wordiness by saying is instead of happens to be.

 (Worse) The two-step procedure not only identifies those factors that significantly affect the signal-to-noise (SN) ratio, but also the levels that maximize SN are found.  (Better) The two-step procedure not only identifies those factors that significantly affect the signal-to-noise (SN) ratio, but also finds the levels that maximize SN.

 (Worse) Logethetis (1988) proved that strong non- linearities exist and the B technique was also recommended for use by him.  (Better) Logethetis (1988) proved that strong non- linearities exist and also recommended using the B technique.

 Depending on the sentence’s context, demonstrated, verified or confirmed can be used as alternatives to proved.

 (Worse) This work not only proposes an effective procedure based on the rank transformation of responses and regression analysis, but also the singly censored data are discussed.  (Better) This work not only proposes an effective procedure based on the rank transformation of responses and regression analysis, but also discusses the singly censored data.

 Depending on the sentence’s context, presents or describes can be used as an alternatives to proposes.

 (Worse) The following steps describe the procedure ◦ Step 1: Calculate the normalized decision matrix. ◦ Step 2: The weighted normalized decision matrix is calculated. ◦ Step 3: The ideal and negative-ideal solution is determined. ◦ Step 4: Calculate the separation measures. ◦ Step 5: The relative closeness to the ideal solution is calculated. ◦ Step 6: The preference order is ranked.

 (Better) The following steps describe the procedure ◦ Step 1: Calculate the normalized decision matrix. ◦ Step 2: Calculate the weighted normalized decision matrix. ◦ Step 3: Determine the ideal and negative-ideal solution. ◦ Step 4: Calculate the separation measures. ◦ Step 5: Calculate the relative closeness to the ideal solution. ◦ Step 6: Rank the preference order.