ISEN 314 Quiz 1
Solutions
Please try to finish the following questions. The full mark is one (1) point.
(a) [one word per blank] The six-sigma framework DMAIC stands for Define, Measure, Analyze, Improve, and Control.
(b) [one multi-word phrase per blank]

INEN314 Homework #9
(Due 11/14)
The following problems are related to your experiments in Lab#8. You need to use the data collected
from the Lab to finish this homework.
1. Use the data from Step 4 in your Lab #8, construct a control chart (x-bar chart an

March 9, 2011
Gustavo Espinoza
Natalia Siman
UIN:518000677
UIN: 919001336
ISEN 314
Lab 6 HW
2.Let X denote a random variable having a binomial distribution with p=0.4
and n=20. Use table 2 of the Appendix to evaluate:
a. P(X6)
b. P(X12)
c. P(X=8)
4. A com

Maria Fernanda Alvarez
1
ISEN 314 Lab Exercise 1 January 25, 2012
Objective of Lab: Learn about DMAIC and the DMAIC procedure(s)
1.0 Read Chapter 1 and 2 in Montgomery, 6th Edition
2.0 Define the following terms in your own words (5 Points apiece) Critica

INEN314 Homework #5
(Due 10/10)
Problems 1-2 are related to your experiments in Lab#5. You need to use the data collected from the
Lab to finish this homework.
1. [10 pts] (Part 1 from in Lab #5).
1a) What do you think would be the most appropriate distri

February 3, 2011
Gustavo Espinoza UIN: 518000677
Natalia Siman
UIN: 919001336
ISEN 314
Lab 2
2.1 Discuss the similarities between the Shewhart cycle and DMAIC.
Both systems look for ways to improve quality and processes . The Shewhart cycle is
known as th

February 17, 2011
Gustavo Espinoza UIN: 518000677
Natalia Siman
UIN: 919001336
ISEN 314
Lab 3
1. What is the advantage of stem-and-leaf plots over frequency histograms?
With frequency histograms, the identities of the individual observations are lost in t

ISEN 314
Natalia Siman
Gustavo Espinoza
Lab Exercise # 1
1.1 Why is it difficult to define quality?
Quality is difficult to define because it is a very subjective term, people have their own
definition. Also, each person may look for different desirable c

March 2, 2011
UIN:518000677
Gustavo Espinoza
Natalia Siman
UIN:
919001336
ISEN 314
Lab 5 HW
3.7 Construct a histogram for the data provide, comment on the shape of the
histogram. Does it resemble any of the distributions that we have discussed in
this cha

ISEN 314 Statistical Quality Control
Lab Exercise: 1
The following table contains observed data for service times at a local hamburger place. These
times include placing an order, paying and then getting a hamburger.
0.02
1.39
5.02
3.04
3.45
1.85
0.83
4.3

February 24, 2011
Gustavo Espinoza UIN: 518000677
Natalia Siman
UIN: 919001336
ISEN 314
Lab 4
1. Calculate estimates of the Mean, Variance and Standard deviation of this data by hand. For the
variance, use both (a) the second moment about the mean method

Rodrigo Landivar
Jonovan Rogers
Lab 5 HW
ISEN 314
3.7 Construct a histogram for the data provided. Does it resemble any of the distributions that
we have discussed in this chapter?
The distribution for this histogram is beta.
3.20. Consider the data in Ex

Lecture of Jan 31
From last class - Modeling and describing variation - Probability distribution, and their different from the empirical ones.
1
Important Distributions 1. Discrete Probability Distribution
Hypergeometric distribution Binomial distributi

February 10, 2011
Gustavo Espinoza UIN: 518000677
Natalia Siman
UIN: 919001336
ISEN 314
Lab 3
Discuss the seven step method used for problem solving and process improvement
The Seven Step Method is used for improving problem solving and processes. It is d

February 8, 2011
Gustavo Espinoza UIN: 518000677
Natalia Siman
UIN: 919001336
ISEN 314
Lab 2
2.3 One of the objectives of the control plan in DMAIC is to hold the gain What
that this mean?
By "hold the gains" it is meant to make sure that the gains are of

Hypergeomtric Distribution
- D
DN
x n - x
p( x ) =
x = 0,1, 2, ., min( n, D)
N
n
The mean and variance
nD D N - n
nD
2
=
1 -
& =
N
N N N - 1
Probability model for selecting a random sample of n items without replacement from a lot of N items of whic

HW 1 Solutions Fall 2011
1) a) ANSWER: FTR Reason: Because the p-value = .072 > .05 = .
b) ANSWER: No Reason: The test statistic will not be in the rejection region because she FTR the null hypothesis in part a). Using p-values or rejection regions will a

ISEN 314 Topic Overview for Exam I
1. Quality Definition How do quality and variability relate to each other? 2. Quality control methods: Origin, concept, usage What are the major quality control methods? Who introduced them? How has their use varied thro

ISEN 314 Quiz 3
Solutions
Please indicate what the distribution of x is in the following scenarios. Distribution type should be chosen from either Hypergeometric or Binomial or Poisson. The full mark is two (2) points.
1. Accidents in a building are assum

ISEN 314 Quiz 2
Solutions
Please try to finish the following questions. The full mark is two (2) points.
At a Las Vegas casino, you will need to insert a $2 when playing a slot machine. The machine will give you back $4 (including you own $2) if you win,

Lecture of Feb 07
From Last Class - Relation between Hypergeometric and Binomial distributions; - Poisson distribution; Exam # 1 coming up, on Feb 15, in lab.
1
Poisson versus Binomial
In Binomial distribution, if we count the number of defective items

Rodrigo Landivar
Jonovan Rogers
ISEN 314 HW # 3
1. What is the advantage of stem-and-leaf plots over frequency histograms?
One advantage to the stem-and-leaf plot over the histogram is that the stem-and-leaf plot displays
not only the frequency for each i

Nominal: Categorical data and numbers that are simply used as identifiers or names represent a
nominal scale of measurement. Numbers on the back of a baseball jersey and your social security
number are examples of nominal data. If I conduct a study and I'

Last Lecture
Completed Six Sigma Introduction
Began Toyota Production System (TPS)
1
Toward One-Piece Lot Sizes
Traditional Manufacturing batches move
from one stage of production to the next. Often
results in large WIP and inventory levels.
High setu

Last Lecture
The Penny Fab
Littles Law:
WIP = Th x CT
1
Location: Central Tendency
Measures
Mode Most likely value
MedianMiddle of data (fiftieth percentile)
Sample Mean - Average of the data
n
1
x xi
n i 1
2
Location: Spread & Variation
Measures
Ran

Last Lecture
Lean Waste Reduction
Seven Mudas + 1
The 5 Ss
WIP, Throughput, Cycle Time
Littles Law
1
What time do we need?
2
Takt Time
Takt Time
When we speak of takt time were attempting to
understand the rate at which we need to produce
our product in

Geometric Distribution
In a series of Bernoulli trials, let x denote the r.v.
that denotes the number of trials until the first
success occurs. Then x is a geometric random
variable with parameter 0 < p < 1 and
f ( x) (1 p)
E ( x) p
x 1
and
p
x=1, 2, 3.

Last Lecture
Basic Quality pmfs
In-class examples
Today pdfs
The Normal Distribution and Quality
1
Continuous Distributions
Continuous Probability Distributions
Normal
Chi-Square
Student t
F distribution
Exponential
Gamma
Weibull
Log-normal
Others
2

Chapter 4
Inferences About Process Quality
1
Methods for Inferences
Three Important Types of Statistical Inference
- Point Estimate (P.E.): as an estimate of a population parameter,
such as the mean or the variance.
- Confidence Intervals (C.I.): a range

ISEN 314
Homework 2
1.
Let x have a pdf f(x) with mean and variance 2. If
x1,xn represents a random sample of size n then
(a) show that
n
y xi
i 1
has mean n and variance n2.
(b) Show that y/n (which is X ) has mean and
variance
X2
.
n
2. Show that the f

McDavid 1
Technical Report:
An Investigation in Manufacturing Quality
by
Jairus McDavid
Quality Manager
The Mouse Factory
March 8, 2017
McDavid 2
Introduction
The Mouse Factory is a corporation whose foundations are centered around
professionalism, ethica

Homework 4
5.1
Chance causes of variability include stable patterns of variation that is inevitable in any
particular process. These variabilities are beyond human control and should be accepted as part
of the process.
Assignable variation is the variatio