Which of these control charts is known to have varying Control limits all the time?
OPTIONS Xbar S P chart EWMA Chart ANSWER EWMA Chart EXPLANATION An EWMA chart has exponentially varying control limits.
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Tag: Lean Six Sigma Black Belt
Home » Posts tagged "Lean Six Sigma Black Belt" (Page 21)
On doing a Paired t test on Phase I pilot, the Black Belt finds that the p-value between treatment groups is 0.420. What should the Black Belt conclude?
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...
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Which of the following statements is NOT true for Split Plot designs?
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...
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The main effects for a 4 factor 2 level Half fractional factorial design are shown below A – 3.5 B – 2.7 C – 5.2 D – -4.3 What should the Black Belt conclude merely by looking at the main effects?
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...
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A fractional factorial experiment is designed at 2 levels for 8 factors with a maximum of only 128 runs possible. This could be a
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...
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What is the major limitation of running a full factorial experiment on one replicate?
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...
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When analysing the Designed experimental setup, the Black Belt notes that the p-value of the model is 0.82. This means
OPTIONS There is 82% chance the model is significant There is 82% chance the model is non-significant There is 64% chance the model is significant There is 64% chance the model is non-significant ANSWER There is 82% chance the model is non-significant EXPLANATION SECOND OPTION...
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A fractional factorial experiment is designed at 2 levels for 9 factors with a maximum of only 32 runs possible. This could be a
OPTIONS Quarter Fractional Factorial Design Screening Design Half fractional Factorial Design Resolution IV design ANSWER RESOLUTION IV DESIGNS EXPLANATION This type of an experimental setting gets classified as a Resolution IV design.
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If the Sum of Squares of treatments is 100, the group size is 25 and number of treatments is five, the Mean Squares of error is
OPTIONS 20 5 25 15 ANSWER 5 EXPLANATION Mean Squares = Sum Squares/Degrees of freedom, so 5 is correct.
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Which of the techniques below helps you to understand and distinguish between within runs variability and between runs variability?
OPTIONS Replication Randomization Coding Blocking ANSWER REPLICATION EXPLANATION Replication helps you to understand the difference between the different variances.
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