GDBA 530
D. Morin
Chapter 11
Analysis of variance
And design of Experiments
Learning Objectives
Describe an experimental design and its elements, including
independent variables both treatment and classification and
dependent variables.
Test a completel
GDBA 530
D. Morin
Chapter 13
Multiple Regression Analysis
Learning Objectives
Explain how, by extending the simple regression model to a
multiple regression model with two independent variables, it is
possible to determine the multiple regression equatio
GDBA 530
D. Morin
Chapter 12
Correlation and Simple Regression
Analysis
Learning Objectives
Calculate the Pearson product-moment correlation coefficient to
determine if there is a correlation between two variables.
Explain what regression analysis is an
Department of Supply Chain and Business Technology Management
DMORIN
GDBA 530 Winter 2016
Review questions
1) University C claims its students study only 20% of the day during term time. To test this
claim, a random sample of 400 students were surveyed wi
Department of Supply Chain and Business Technology Management
GDBA 530 Winter 2016
Assignment 3
Due March 28, 2016
Question 1:
A chair manufacturing company knows that the average number of chairs a worker can assemble in one
hour is 15, with a standard d
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School of Business
Department of Supply Chain and Business Technology Management
DttIORIN
GDBA 530 at; as fZEs: ass :as
Review questions f 51
1) University C claims its students study only 20% of the day during term time
Department of Supply Chain and Business Technology Management
GDBA 530 Winter 2016
Assignment 4
Due April 11, 2016
Question 1
The marketing director of a large supermarket chain would like to use shelf space to predict the
sales of pet food. A random samp
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Concordia University
School of Business
Department of Supply Chain and Business Technology Management
GDBA 530
Midterm Exam
March 5, 2016
D. Morin
Last Name: First Name M
Student ID. No.:
INSTRUCTIONS
1. This is an OPEN BOOK examination. You are a
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john Molsen @5 559a;
Scheoi of Business
Department of Supply Chain and Business Technology Management
GDBA 530 Winter 2016
Assignment 2
Due February 29, 2016
l) The heights of a group of athletes are modeled by a norm
TEST FOR THE MEAN
H 0 : =0
H 1 : 0
Test Statistic
Normal population
known
Z=
t=
Normal Population
unknown
X
0
n
X
0
S
~
n
Reject
H 0 if:
H 0 : 0
H 1 : < 0
Reject
H 0 if:
H 0 : 0
H 1 :> 0
Reject
Confidence Interval
H 0 if:
Z <Z
Z > Z
X Z
2 n
t<t n1,
t
Review session 1
Dr Morin
1) Purchasing Survey asked purchasing professionals what sales traits impressed them most in
a sales representative. Seventy-eight percent selected thoroughness. Forty percent
responded knowledge of your own product. The purchasi
GDBA 530
D. Morin
Chapter 9
Statistical Inference:
HypothesisTesting: One Population
Learning Objectives
Develop both one- and two-tailed null and alternative
hypotheses that can be tested in a business setting by examining
the rejection and non-rejectio
Department of Supply Chain and Business Technology Management
GDBA 530 Winter 2016
Assignment1
Due February 5, 2016
1) The following table represent the distribution of drivers and percentage of fatal crashes according
to the age groups for the population
GDBA 530
DMorin
Chapter 2
Charts and Graphs
Learning Objectives
Explain the difference between grouped and un- grouped data
and construct a frequency distribution from a set of data and
explain what the distribution represents.
Describe and construct di
Prep101
Economics103StudySheet
BasicConceptandModels
Opportunity cost refers to the value of the nextbest alternative that you give up when
you make a choice. Opportunity cost arises because resources are scarce and choosing
moreofonethingmeanschoosingles
Prep101
Comm215MTSolutions
2. Numerical Descriptive Techniques
Problems
Q1.
Solution: a
Arithmetic mean: X
SD =
n
(Xi X ) n
i 1
1n
Xi
n i 1
1n
( X i X )
n i 1
1n
1
X i n nX ]
n i 1
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= n [
Q2.
Solution: c
Think of Normal distribution as a
CHAPTER 3: Probability
3.1
ExperimentAny process of observation that has an uncertain outcome.
EventA set of sample space outcomes.
ProbabilityThe probability of an event is the sum of the probabilities of the sample space
outcomes or the long-run relativ
CHAPTER 4: Discrete Random Variables
4.2
The values of a discrete random variable can be counted, or listed; the values of a continuous
random variable cannot be counted, or listed.
4.3
a.
b.
c.
d.
e.
f.
g.
4.4
See page 119 in text.
4.8
a.
Valid
b.
Not va
Students Solutions Manual and Study Guide: Chapter 1
Page 1
Chapter 1
Introduction to Statistics
LEARNING OBJECTIVES
The primary objective of Chapter 1 is to introduce you to the world of statistics.
We would like to answer the following questions:
1. Wha
Lesson 6 Sampling Distributon
At Home Problem Solutions
PROBLEM # 6.7
a) P(! > 1,050)
X
P( X > 1050) = P
/ n
>
1050 1000
= P(Z > 1.00) = 1 P(Z < 1.00) = 1 .8413 =.1587
200 / 16
b) P(! < 960)
X
Basics of
Probabilities
How to
represent
data
ResearchHypothesis Testing
REST OF THE SEMESTER
Simple Linear
Regression
Goodness of Fit
and
Independence
Test
Multiple Linear
Regression
Hypothesis
Testing
LESSON 6
IN A NUTSHELL
Normal Probability Distributi
COMM 215 Midterm
Chapter 1
Data mining: application of statistical techniques and algorithms to the analysis of large data sets
Business intelligence: application of tools/technologies for gathering, storing, retrieving, and
analyzing data that businesses
GDBA 530
DMorin
Chapter 1
Introduction to Statistics
Learning Objectives
Define statistics and list example applications of statistics
in business.
Define important statistical terms, including population,
sample, and parameter, as they relate to descri
jghMgiga
Schooi of Business
Department of Supply Chain and Business Technology Management
GDBA 530 Winter 2016
Assignment 4
Due April 113 2016
Questien it
The marketing director of a large supermarket chain would like to use shelf space to predict the