ENME392 Fall 2011
Homework 9 Solutions
Total number of points: 100
Assignment:
1.
The following data were collected for the number of M&Ms of each color in 17 small
bags of candies.
(20 pts)
a) What i
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ENGINEERING SERVICES
INDUSTRY ANALYSIS
Kevin Yuan
UNIVERSITY OF MARYLANDCOLLEGE PARK, MD
1
Engineering Services Industry Analysis
What knowledge do you possess that can contribute to ser
SAMPLING CONFIDENCE INTERVALS
1. WHAT IS THE CENTRAL LIMIT THEOREM? (IN YOUR OWN WORDS) WHAT
ARE THE RULES FOR IT? EXPLAIN WHY YOU THINK IT WORKS. IN OTHER
WORDS HOW IS IT POSSIBLE THAT YOU CAN HAVE A
Statistical Process Control
1
Statistical Process Control (SPC)
A process must be checked to see if it meets specification limits
Statistical process control means that the process must also be
cons
Estimation and Sampling
Understanding the basic principles behind the
use of samples to understand populations
1
Overview
Definitions: Population, Sample, Statistic, Point
Sample mean &
Estimation,
Joint Probability Distributions
Calculating and working with joint probabilities
and systems with more than one random
variable
1
Recap(itulation)
How to count
Sample spaces, Permutations, Combinati
Two-Factor ANOVA
1
Two-Factor ANOVA
In the previous slides, the 2nd factor was not of interest. What if it is?
What if you want to study the effect of two parameters (factors) at several levels
on an
Discrete Random Variables and
Discrete Probability Distributions
Understand how discrete probability distributions are
developed and how they are used/analyzed
1
Recap(itulation)
How to count
Sample
ENME392 Fall 2010
Homework 8 Solutions
Total number of points: 48
1.
Chapter 9: 9.36
(3pts)
nA = 50, nB = 50, xA = 78.3, xB = 87.2, A = 5.6, and B = 6.3. It is known that z0.025 =
1.96. So, a 95% conf
ENME392 Fall 2011
Homework 13 Solutions
Total number of points: 100
1. Chapter 13: 13.28 (Edition 8) / 13.26 (Edition 9)
(10 pts)
The hypotheses are
H0 : 1 = 2 = 3 = 0, no differences in the varieties
ENME392 Spring 2011
Homework 11 Solutions
Total number of points: 60
1. Chapter 12: 12.3
PLUS, compare to the results obtained by doing each X separately. Discuss.
(10 pts)
Time
6.40
15.05
18.75
30.25
ENME392 Fall 2011
Homework 1 Solutions
Assignment:
1) (49pts) Using the dataset of exercise 1.1 in Walpole:
3.4, 2.5, 4.8, 2.9, 3.6, 2.8, 3.3, 5.6, 3.7, 2.8, 4.4, 4.0, 5.2, 3.0, 4.8
a) (7pts) What is
ENME392 Fall 2011
Homework 4 Solutions
Total number of points: 100
1.
Chapter 3: 3.39 (leave as a formula)
(4 pts)
sack of fruit with 3 oranges X, 2 apples Y, 3 bananas B
8 total fruit, take 4 pieces
ENME392 Fall 2011
Homework 5 Solutions
Total number of points: 100
Assignment:
1.
Chapter 8: 8.22
(5 pts)
(a) the mean and standard deviation of the sampling distribution
cm
cm
(b) The number of sampl
ENME392 Fall 2011
Homework 6 Solutions
For this problem, you may work in groups of up to 4. Obtain a box or box lid of
approximately 9 x 13. Draw a square on the bottom of it that is 3.5 on each side;
ENME392 Fall 2011
Homework 7 Solutions
Total number of points: 100
The questions are a follow-up to last-weeks assignment: (80 pts)
a) Group your number-of-heads data into 25 groups of 4 points by tak
ENME392 Fall 2011
Homework 8
Total number of points: 100
The question is a follow-up to last-weeks assignment:
a) What is the 95% prediction interval for a future number of heads?
(8pts)
Textbook prob
ENME392 Fall 2011
Homework 11 Solutions
Total number of points: 100
1. Chapter 10: 10.84 (Edition 8) / 10.82 (Edition 9)
(10 pts)
The hypotheses are
H0 : Data follows the hypergeometric distribution h
ENME392 Fall 2011
Homework 12 Solutions
Total number of points: 100
1. Chapter 11: 11.1
(10 pts)
i) Plot the data.
120
Dynamic Lift
100
80
60
40
20
0
0
20
40
Arm Strength
60
i =1
xi
yi
17.3
19.3
19.5
Continuous Random Variables and
Continuous Probability Distributions
Understand how continuous probability distributions
are developed and how they are used/analyzed
1
Recap(itulation)
Last time:
Di
Statistical Inference Techniques
- Two samples (Parametric)
- Nonparametric testing
1
Overview
Other kinds of useful two-sample tests using chi-squared
Goodness of Fit
Independence
Homogeneity
Ot