**100% money back guarantee**read our guarantees

- September 13, 2020
- By menge

I need help with only problem 3 in 1 hour. Please i will give very very good review from my side.

`1DATA-DRIVEN DECISION MAKING I

ISE 4553/5553

Assignment 6

Where applicable, always provide hypotheses and respond to the assumptions of ANOVA (you

can use R to produce these plots or perform statistical tests). For ?by hand? calculations, you

may use Excel for calculations, but implement the equations yourself. For each ?by hand?

problem, provide the standard ANOVA table (e.g., Table 4.2 in [Montgomery 2013]). As with all

homework this semester, spend time to be neat and organized. You are encouraged to type out

homework submissions and use an equation editor function, integrating into your typed

document any R output. Any disorganized submissions are subject to a zero grade.

Problem 1

Problem 4.53 in [Montgomery 2013], as written.

Problem 2

Show the development of Equation 4.21 from a general set of = observations. Assume a

single missing value in treatment and block , and, like the book, call this missing observation

. In showing Equation 4.21, you must show how Equation 4.20 is derived from the equation

just before it.

Problem 3

As an industrial and systems engineer, you?re testing four different shop floor layouts by

measuring the construction time (in minutes) to construct a subassembly for six different work

crews. You?re not interested in the speed of individual work crews (you hope to fix that later

with improved work design and training), but you do want to account for the variability

associated with the work crew. Test at the 0.02 level of significance whether the four layouts

produce different assembly times. As someone making a recommendation as to the layout,

what do you do?

Crew

A

B

C

D

E

F Layout 1

49.2

49.5

52.7

55.1

49.1

58.4 Layout 2

53.1

52.9

56.8

50.6

51.8

57.2 Layout 3

51.2

51.0

49.9

51.4

51.3

61.8 Layout 4

57.5

56.4

57.8

56.5

52.3

61.7 Problem 4

Reconsider Problem 3, but treating the experiment as a complete randomized design, ignoring

potential differences among work crews. Reanalyze the experiment under this new assumption.

What difference would ignoring blocking have on the results and conclusions? Why is this

important?

Problem 5 (ISE 4553 STUDENTS ONLY)

Problem 4.10 in [Montgomery 2013], as written.

Problem 5 (ISE 5553 STUDENTS ONLY)

Problem 4.23 in [Montgomery 2013], as written.