Certified Lean Six Sigma Master Black Belt (LSSMBB): LSSMBB

In analyzing some data, you first try multiple linear regression with all the factors and with interactions

(example: Factor A times Factor B is interaction AB)

You obtain a multiple regression equation of the form:

Response = 15 + .13 A - .30 B - .02 C - .00001 AB + .0000004 AC - .00000013 BC +.000000 ABC.

The p-values for most of the factors and interactions are between 0 and .05, except interactions BC and

ABC, which have p-values between .4 and .9.

Which of the following approaches might be appropriate to simplify the equation?

A. Drop all factors with negative coefficients.

B. Drop factors BC and ABC and rerun the multiple linear regression.

C. Drop factors B and C and rerun the multiple linear regression.

D. Drop factors B and C and rerun the multiple linear regression.

A. Are downtime issues easily noted?

B. Can extra inventory be seen easily?

C. Are unneeded tools or supplies easily noted?

D. Are setups optimized for lower scrap levels?

Sally and Sara sell flower pots at their garage sale. Martha motivates Rose mentioning that they will sell a minimum of 16 pots per day if the outside temperature exceeds 60o F. From a sample, whose population is assumed to follow a Normal Distribution, taken for 30 days at 60 degrees or more an average of 15.2 pots per day were sold with a Standard Deviation of 0.6 pots. What is the Z value for this sales process?

A. 0.67

B. 1.13

C. 1.33

D. 2.66