Extra Quiz 1 questions from 2008.
Answer the next six questions for the following problem:
The call center of a phone ordering company has two operators, each can handle 50
customers order per hour. The order picking team has five workers and each worker
ISMT 161 Operations Management
Quiz 1, Spring 2005
Instructor: Shu Ming Ng
Policy
This is a close book exam. Students are not allowed to consult books, solutions to problems or notes
during the exam. However, a piece of A4 size with handwritten notes on
ISMT 162 Introduction to Operations Management
Quiz 1
Time: 9:00am 9:50am
(9 Questions, 20 Points)
Note: Each question has 5 choices. There is only ONE correct answer for each question.
You are required to write down the reason or the procedure to find yo
ISMT 162 Introduction to Operations Management
Quiz 1
Time: 9:00am 9:50am
(9 Questions, 20 Points)
Note: Each question has 5 choices. There is only ONE correct answer for each question.
You are required to write down the reason or the procedure to find yo
ISMT 162 Introduction to Operations Management
Quiz 2
Time: 9:00am 9:50am
(15 Questions, 20 Points)
Note: Each question has 5 choices. There is only ONE correct answer for each question.
Name:
Student No.:
Question 1. (1 point) Which is NOT a cost of qual
ISMT 162 Introduction to Operations Management
Quiz 2
Time: 9:00am 9:50am
(15 Questions, 20 Points)
Note: Each question has 5 choices. There is only ONE correct answer for each question.
Name:
Student No.:
Question 1. (1 point) Which is NOT a cost of qual
ISMT 111 BUSINESS STATISTICS TUTORIAL 8
Simple Linear Regression Model Aim: Use X (Independent Variable, or Predictor Variable) to predict Y (Dependent Variable, or Response Variable) after drawing n pairs of observations, (x1 , y 1 ),., (xn , y n
Topic 1 Descriptive Statistics
1.1 Frequency Distribution: a grouping of data into different categories showing the number of observations in each class. Four steps: Decide on the number of classes. Determine the class interval or width. Set the i
Topic 0 Basic Concepts of Statistics
0.1 Population :The complete collection of Individuals that are of interest in the study. Sample: A portion, or part, of the population of interest.
0.2 Random sample: A random sample is a sample selected from a
Topic 2 Probability
2.1 Probability A probability is a measure of the likelihood that an event in the future will happen. Denote event by A , the probability of the event A by P(A) ,
0 P ( A) 1 , when P(A)=0 , we say A is an impossible event, P(A)=
ISMT 111 L1 BUSINESS STATISTICS TUTORIAL 7
Definition Null Hypothesis ( H 0 )
created by Andrew Yam
 a hypothesis we assume to be TRUE, e.g. H 0 : = 0  assumption we wish to test Alternative Hypothesis ( H a or H 1 )  a hypothesis we wish to
Topic 3 Discrete Probability Distributions Part A
3.1 A random variable is a numerical description of the outcome of an experiment. A random variable can be classified as being either discrete or continuous depending on the numerical values it assume
ISMT 111 BUSINESS STATISTICS TUTORIAL 6
Confidence Interval Estimation for Population Mean, For large sample size n, if is unknown, use s instead For small sample size with normal population and known A (1 )100% Confidence Interval for is
c
ISMT 111 BUSINESS STATISTICS TUTORIAL 5
Sampling Distribution of Sample Statistics The sampling distribution of a statistic is the probability distribution of all the possible values of this statistic which are computed from random samples with sam
Topic 3 Discrete Probability Distributions Part B 3.7 Combination: the number of ways to choose r objects from a group of n objects without regard to order.
n
Cr =
n! r! (n r)!
3.8 Binomial Distribution 3.8.1 The setup for Binomial Distribution
Topic 5A Sampling Distribution 5.1 Sampling variation: Since the sample is a random subset of the population, the sample mean and population mean will not be the same. Different samples will have different sample means. Sample mean is random variable
Topic 4 Distribution of Continuous Random Variable 4.1 Uniform distribution: If c and d are numbers on the real line (c < d), the probability curve describing the uniform distribution on [c, d] is
f ( x )= 1 d c for c x d
The probability that x is
Topic 5B Sampling Distribution 5.5 Sample Proportion v.s. Population proportion: 5.6 Distribution of sample proportion: Approximated by a normal distribution if
p = p
np 5, n(1 p) 5
p =
p(1 p) n
5.7 Distribution of difference between two samp
Topic 6A Confidence Interval One sample case 6.0 Basic Concepts: Confidence level, Sampling error, Standard Error, Controlling of Sampling Error,
6.1 Confidence Interval for Population mean
6.2 Confidence Interval for population proportion
p Z/2
Topic 6B Confidence Interval Two sample cases 6.4 Confidence Interval for Difference of Population mean
Point Estimate (Critical Value)(Standard Error) known, normal population or large sample
1 , 2
X1 X 2
z / 2
12
n1
+
2 2
n2
1 = 2
unk
Topic 7B Hypothesis Testing Two samples case 7.5
7.6
7.7
7.8
Testing of proportions difference
H 0 : p1 p2 = 0 H a : p1 p 2 0
case 1
n p +n p p= 1 1 2 2 n1 + n2
Z=
p1 p2 p (1 p ) p (1 p ) + n1 n2
case 2:
H 0 : p1 p2 = d H a : p1
Topic 7A Hypothesis Testing One sample case 7.1
7.2
7.3
7.4 Errors in Making Decisions Type I Error Reject a true null hypothesis, The probability of Type I Error is Type II Error Fail to reject a false null hypothesis, The probability of Type II
Topic 8A Linear Regression Basic Concepts 8.1 Linear Regression Model , prediction equation
yi=0 + 1 xi + i Y  X = 0 + 1X i Y =b +b X
i i
i
0
1
i
8.2 Estimation of parameters:
S XY = (X i X )(Yi Y ) = X iYi
X Y
i
i
n
S XX = ( X
Topic 8b Linear Regression Measures of Variation 8.3 Assumptions of Linear Regession Model: Linearity (X and mean value of Y have linear relationship) Indepedence of Error (1, 2are independent) Normality of Error (1, 2are normal) Equal variance (
Topic 8c Linear Regression Testing linearity, CI for mean response, PI for response variable 8.6 Testing of linearity
H 0 : 1 = 0 H a : 1 0
Test statistic
b t = 1 Sb1
, where
S b1 =
s S XX
8.7 Confidence Interval for the mean response
[y t
' , qB . . . .o ch . . B.' . , B' , C
r
t3 4 t z qhe l^

N
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i3
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Fh 

ch 
o N
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N N
N
u N
N
N
h N
N
ch N
zJ .
o z g
zi o e . .
c u :z s Z VZR s g R G z g t23 1 z
ISMT 111 BUSINESS STATISTICS TUTORIAL 1
Types of Data Qualitative/Categorical data a) Nominal Data  no natural order between the categories, e.g. gender b) Ordinal Data  order exists, e.g. size (S,M,L) Quantitative/Numerical data a) Discrete da
ISMT 111 BUSINESS STATISTICS TUTORIAL 3
Two Independent Variables Let X and Y be two independent discrete random variables, while a is a constant.
created by Andrew Yam
Var(aX ) = a2Var(X )
E(aX ) = aE(X )
Var(X Y ) = Var( X ) + Var(Y )
E(X
ISMT 111 BUSINESS STATISTICS TUTORIAL 2
Terminology Experiment: obtaining one observation Sample Space (S): the set of all possible outcomes of an experiment Simple Event: an element of the sample space Event: a subset of the sample space Gener