Course
BUSN 6110 Operations and Project Management
Term
Spring II, 2013. March 18 May 17
Catalog
Description
Prerequisites
This is a course that focuses on the major managerial issues in manufacturing management
and the tools that can be used to manage th
Probabilities Calculations
PHStat2
Sample Space
Event A
Event B
A
A'
Totals
B
50
80
130
B'
10
70
80
Totals
60
150
210
Simple Probabilities
P(A)
0.286
P(A')
P(B)
P(B')
0.714 (a)
0.619
0.381
p = f/n = 60/100 = 0.60
P(A and B)
P(A and B')
P(A' and B)
0.238 (
(A) Region
Iran
Saudi Arabia
Other OPEC countries
Non-OPEC countries
Total
(B) More than half the oil produced is from non-OPEC countries.
More than 22% is produced by OPEC countries other than Iran and Saudi Arabia.
Region
Iran
Saudi Arabia
Other OPEC co
a)
b)
c)
d)
e)
Categorical, nominal scale.
Numerical, continuous, ratio scale.
Categorical, nominal scale
Numerical, discrete, ratio scale
Categorical, nominal scale.
a)
b)
c)
d)
numerical, continuous, ratio scale *
numerical, discrete, ratio scale
numeri
Chapter 2 Presenting
Data
in Tables and Charts
Organizing Numerical Data
Tables and Charts for Numerical Data
Graphing Bivariate Numerical Data
Tables and Charts for Categorical Data
Tabulating and Graphing Bivariate
Categorical Data
Graphical Excellence
Chapter 1
Introduction and
Data Collection
Why a Manager Needs to Know About
Statistics
The Growth and Development of Modern
Statistics
Why are Data Needed?
Sources of Data
Types of Data
Types of Sampling Methods
Evaluating Survey Worthiness
What We Need
Probabilities Calculations
PHStat2
Sample Space
Event A
Event B
A
A'
Totals
B
10
25
35
B'
30
35
65
Totals
40
60
100
Simple Probabilities
P(A)
0.400
P(A')
P(B)
P(B')
0.600 (a)
0.350
0.650
p = f/n = 60/100 = 0.60
P(A and B)
P(A and B')
P(A' and B)
0.100 (b)
Chapters 4 & 5 Basic
Probability and Discrete
Probability Distributions
Basic Probability Concepts
Conditional Probability
The Probability Distribution
for a
Discrete Random
Variable
Binomial Distribution
Basic Laws of Probability
Simple probability P = f
Time Series
Forecasting
Time Series Components and
Models
Time Series Regression: Basic
Models
Moving Average
Time Series Components
and Models
Trend Long-run growth or decline.
Cycle Long-run up and down fluctuation around the trend level.
Seasonal Regul
Multiple Regression
Chapter 14
Basic
Multiple Regression
The Linear Regression Model
Model Utility: R2 and Adjusted R2
Testing Significance of an Independent
Variable
The Quadratic Regression Model
Interaction
Dummy Variables to Model Qualitative
Variabl
Hypothesis
Pooled-Variance t Test for the Difference Between Two Means
(assumes equal population variances)
Data
Hypothesized Difference
0
Level of Significance
0.01
Population 1 Sample
Sample Size
8
Sample Mean
42
Sample Standard Deviation
1.30274
Popula
Chapter 2 Presenting
Data
in Tables and Charts
Organizing Numerical Data
Tables and Charts for Numerical
Data
Graphing Bivariate Numerical Data
Tables and Charts for Categorical
Data
Tabulating and Graphing Bivariate
Categorical Data
1
Graphical Excellenc
Chapter 10 Two -Sample
Hypothesis Tests with
Numerical Data
Comparing Two Independent Samples: z and tTests for Differences Between Two Population
Means
F-test for Differences Between Two Population
Variances
Rule-of-2
Comparing Two Related (Dependent) Sa
Chapters 4 & 5 Basic
Probability and Discrete
Probability Distributions
Basic Probability Concepts
Conditional Probability
The Probability Distribution
for a
Discrete Random
Variable
Binomial Distribution
1
Basic Laws of Probability
Simple probability P =
Chapter 12 Hypothesis
Testing of More Than Two
Proportions Chi-squared (2)
GOALS
List the characteristics of the chisquare distribution.
Conduct a test of hypothesis
comparing an observed set of
frequencies to an expected
distribution.
Conduct a test of h
Chapter 1 Introduction
and
Data Collection
Why a Manager Needs to Know About
Statistics
The Growth and Development of Modern
Statistics
Why are Data Needed?
Sources of Data
Types of Data
Types of Sampling Methods
Evaluating Survey Worthiness
1
What We Nee
Chapter 13 Simple
Linear Regression
Types of Regression Models
Determining the Simple Linear
Regression Equation y = b0 + b1x
Measures of Variation
Residuals
Inferences about the Population
Slope,
Inferences about the Correlation
Coefficient, r
Linear Re
Chapter 9 - Fundamentals of
Hypothesis
Testing: One-Sample Tests
Hypothesis Testing Methodology
Z-Test of Hypothesis for the Mean
( Known)
One -Tail Tests
t-Test of Hypothesis for the Mean
( Unknown)
Z-Test of Hypothesis for the
Proportion (always Z-test)
Chapter 8 Confidence
Interval Estimation and
Sample Size
Confidence Interval Estimation of
the Population Mean, , ( Known)
Confidence Interval Estimation of
the Population Mean, , (
Unknown)
Confidence Interval Estimation for
the Population Proportion,
D
Chapter 11 - ANOVA
What if we have more than two sets
of data?
ANOVA (ANalysis Of VAriance) has
three assumptions:
1. Data is random and independent
2. Data is normal (in each data set)
3. The variances are equal (Levernes
test for homogeneity of variance
Chapter 3 Numerical
Descriptive Measures
Exploring Numerical Data and Their
Properties
Measures of Central Tendency, Variation
and Shape
Exploratory Data Analysis
Obtaining Descriptive Summary
Measures from a Population
The Coefficient of Correlation, r
P
Chapter 6 and 7 The
Normal Distribution and
Sampling Distribution
The Normal Distribution
Evaluating the Normality
Assumption
Introduction to Sampling
Distribution
Sampling Distribution of the
Mean
1
The Normal Distribution
Properties of the normal distr
Suppose that you want to create a portfolio that consists of a corporate bond fund, X, and a
common stock fund, Y. For a $1,000 investment, the expected return for X is
$ 80
and the expected return for Y is
$ 94.
The variance for X is
1 comma 575
and the
Chapter 6 and 7 The
Normal Distribution and
Sampling Distribution
The Normal Distribution
Evaluating the Normality Assumption
Introduction to Sampling Distribution
Sampling Distribution of the Mean
Sampling Distribution of the
Proportion
Roland E. Sprague