Month: December 2021

OPTIONS Need to collect lesser samples Process shifts detected easily Additional sensitivity by averages charts not justified Process drifts detected easily ANSWER Additional sensitivity by averages charts not justified EXPLANATION Individuals charts are not sensitive to special causes, so THE THIRD OPTION is correct.

OPTIONS The Average charts are not sensitive to non-normality The Average charts provide tighter controls Average charts best indicate within and between subgroup variation Average charts show mean shift ANSWER The Average charts provide tighter controls EXPLANATION The reason why Xbar charts are chosen over...

OPTIONS When you can collect only one observation per day When it is not feasible to use averages chart for process control When within-subgroup variation is to small relative to batch-batch variation All of the above ANSWER All of the above EXPLANATION Conditions mentioned in...

OPTIONS Xbar S P chart EWMA Chart ANSWER EWMA Chart EXPLANATION An EWMA chart has exponentially varying control limits.

OPTIONS The change effort has yielded some results The change effort needs to be re-checked The change effort has not yielded positive results The change effort has not changed anything ANSWER The change effort has not changed anything EXPLANATION If p-value is 0.420, it is...

OPTIONS Blocks in a Split Plot design serve as experimental units Split plots are the same as completely randomized designs Split plots are randomized twice The randomization in split plots ensure split plot errors are independently distributed ANSWER Split plots are the same as completely...

SELECT THE CORRECT ANSWER Effect C is the most significant for the model Effect D is the least significant for the model Effect A and B can be ignored Any conclusion can only be made after looking at the p-values for the effects ANSWER Any...

OPTIONS Quarter Fractional Factorial Design Screening Design Half fractional Factorial Design Resolution IV design ANSWER HALF FRACTIONAL FACTORIAL DESIGN EXPLANATION For 8 factors and 2 levels, full factorial experiment would have resulted in 256 runs, so here with 128 runs, Half fractional Factorial Design is...

OPTIONS Curvature effects are not estimated The variable response doesn’t follow linearity The model may be exposed to noise Extraneous factors may go undetected ANSWER The model may be exposed to noise EXPLANATION Full factorials on one replicate are very good experiments for interaction, but...