Design 2 Spring 2017
Prof Robert Steele
Prof of Advanced Technology
[email protected]
Intro
Questions?
Time-Line Charts
Also called Gantt charts
Example (from Pressman):
Process and Project Metrics
The only rational way to improve any process
is to m
Design 2 Spring 2017
Feb 14 2017
Prof Robert Steele
[email protected]
Quality Management
Quality Concepts
DeMarco:
A products quality is a function of how much it
changes the world for the better.
Robert Glass contends:
user satisfaction = compliant pr
Design 2 Spring 2017
Jan 31 2017
Prof Robert Steele
Prof of Advanced Technology
[email protected]
Risk Management
Reactive vs Proactive
With proactive, potential risks are identified
and ranked by importance
Software Risks
Project risks affect schedul
Design 2 Spring 2017
Feb 21 2017
Prof Robert Steele
[email protected]
Admin
Mid-semester deliverable
A recorded demo of your work-to-date
Make sure you are liaising with your industry
sponsor/ faculty advisor
Review Meeting
At end of FTR, must be dec
Design 2 Spring 2017
Prof Robert Steele
Prof of Advanced Technology
[email protected]
Intro
Key emphases for this course
Deliver a quality project that impresses your
industry partner (or faculty advisor )
Review syllabus
Project Management
Consider
Design 2 Spring 2017
Feb 28 2017
Prof Robert Steele
[email protected]
Admin
Mid-semester deliverable
Please see specification document and rubric
Make sure you are liaising with your industry
sponsor/ faculty advisor
make sure they are happy with wha
Design 2 Spring 2017
Feb 7 2017
Prof Robert Steele
[email protected]
Characteristics of Effective Software
Engineers
Software engineer has a sense of individual
responsibility
Brutally honest willing to point our flaws in
the software (constructively)
Class Examples: Chapter 9
SECTION 9.1
a. correctly stated
b. not correct; the inequality is in H0; equality in HA
c. no, symbols used are statistics, not population parameters
d. no, the same value must appear in H0, HA; also both H0, HA contain equal sta
Class Examples: Chapter 8, sections 1 to 3
NOTE: THE DATASETS FOR SOME PROBLEMS CAN BE FOUND IN THE DATASETS MODULE IN MyCourses
or ON THIS WEBSITE: www.wiley.com/college/montgomery
SECTION 8.1
a. the mean is in the middle of the confidence interval: (37.
Chapter 7 Class Examples
SECTION 7.2
Excel: Use NORM.DIST. You must calculate the std dev for sample = 3.5/6 = 1.429
This is P(X < 75.75); we want P(X > 75.75) so subtract from 1:
P(X > 75.75) = 1 P(X < 75.75) = 1 0.5694 = 0.4306
TI83/84: use Distr, Norma
Chapter 11 Class Examples
SECTION 11.2
Part a. Using excel, data analysis, regression; estimate of 2 = 8.767753
b. y-hat = 13.32018 + 3.324371(7.50) = 38.253
c. y-hat = 13.32018 + 3.324371(5.8980) = 32.9273
in the data set, y = 30.9 when x = 5.8980
residu
Chapter 6 Class Examples
Section 6.1
n
sample mean x
x
i 1
n
i
748.0
83.11 drag counts
9
2
n
xi
n
i 1
748.02
2
x
62572
i
n
9
sample variance s 2 i 1
n 1
9 1
404.89
50.61 drag counts 2
8
sample standard deviation
s 50.61 7.11 drag counts
Dot Diag
Simpsons Paradox
Solution:
The overall success rate depends on the success rates for each stone size group, but also the probability
of the groups. It is the weighted average of the group success rate weighted by the group size as
follows:
P(Overall succe
Chapter 3 Class Examples
Section 3.1
For each of the following exercises, determine the range (possible values) of the random
variable.
Section 3.2
Chapter 3 Class Examples
Section 3.3
Section 3.4
Section 3.5
Chapter 3 Class Examples
Section 3.6
Section 3
Chapter 4 Class Examples
Section 4.2
Section 4.3
Chapter 4 Class Examples
Determine the probability density function for the following cumulative distribution function.
Problem 4-30
Section 4.4
Section 4.5
Chapter 4 Class Examples
Section 4.6
Chapter 4 Cl
. Caper 4 Cassampls
Section 4.6
(we Aggiime than Z has a standard Henna] dixtt‘ibuiion.
USE: Appendix Tﬂbfﬁ ill :0 Lietermine the. value for .3 that wives
sash of the feliowjng:
{a} P —23 "~11 Z411: 2:} = (195 Us). 1’ {—3, e: 3. ~11 .3} x {3.99
(1) P"
Chapter 6 quiz
Question 1 (1 point)
The sample mean is analogous to the center of mass in mechanics.
Question 1 options:
A) True
B) False
Save
Question 2 (1 point)
The mode of a sample is the most frequently occurring value in the sample.
Question 2 optio
Chapter 5 Quiz
Question 1 (1 point)
A conditional probability distribution does not depend on the values of any other random
variables.
Question 1 options:
A) True
B) False
Question 2 (1 point)
A marginal probability distribution is the individual probabi
Quiz
Note: It is recommended that you save your response as you complete each question.
Chapter 3 Quiz
Question 1 (1 point)
Discrete random variables take on values across a continuum.
Question 1 options:
A) True
B) False
Save
Question 2 (1 point)
The cum
CHAPTER 8
1.
The statistical interval that contains a stated proportion of the values of a probability
distribution is called a confidence interval.
A) False
B) True
2.
In a 95% confidence interval the quantity 0.95 = 1 0.05 is called the confidence
coeff
Chapter 1 Quiz
Question 1 (1 point)
Statistical reasoning is also called statistical inference.
Question 1 options:
A) True
B) False
Save
Question 2 (1 point)
A time series plot shows the data values along the x-axis and the time variable along the y-axis
Chapter 4 Quiz
Question 1 (1 point)
The probability density function of a continuous random variable is a simple
description of the probabilities associated with the random variable.
Question 1 options:
A) True
B)
Fals
e
Question 2 (1 point)
For a continu
Chapter 11 Quiz
Question 1 (1 point)
A scatter diagram is a convenient way to display graphically the relationship between two quantitative
variables.
Question 1 options:
A) True
B) False
Save
Question 2 (1 point)
Regression analysis can be used to establ
Stats for Engineers QUIZ Chapter 2
Chapter 2 Quiz
Question 1 (1 point)
An experiment that can be repeated many times under identical conditions yet have different outcomes is
called a random experiment.
Question 1 options:
A) True
B) False
Save
Question 2
Chapter 13 Quiz
Question 1 (1 point)
The analysis of variance (ANOVA) can be used for comparing the equality of more than two treatment
means.
Question 1 options:
A) True
B) False
Save
Question 2 (1 point)
In a fixed-effects experiment the treatments or f