Engineering (scientific) method
1 2
Develop a (clear) description (of the problem). Identify the important factors (that affect this problem or that may play a role in its solution). Propose a tentative model (based on scientific or engineering knowledge

2/16/2009
7-1 Introduction
The field of statistical inference consists of those methods used to make decisions or to draw conclusions about a population. These methods utilize the information contained in a sample from the population in drawing conclusio

3/23/2009
8-1 Introduction
In the previous chapter we illustrated how a parameter can be estimated from sample data. However, it is important to understand how good is the estimate obtained. Bounds that represent an interval of plausible values for a par

8-1 Introduction
In the previous chapter we illustrated how a parameter can be estimated from sample data data. However, it is important to understand how good is the estimate obtained obtained. Bounds that represent an interval of plausible values for a

3/23/2009
9-1 Hypothesis Testing
9-1.1 Statistical Hypotheses Statistical hypothesis testing and confidence interval estimation of parameters are the fundamental methods used at the data analysis stage of a comparative experiment, experiment in which the

9-1 Hypothesis Testing 9 1H th i T ti
9-1.1 Statistical Hypotheses yp Statistical hypothesis testing and confidence interval estimation of parameters are the fundamental methods used at the data analysis stage of a comparative experiment, experiment in wh

3/23/2009
10-1 Introduction
10-2 Inference for a Difference in Means of Two Normal Distributions, Variances Known
10-2 Inference for a Difference in Means of Two Normal Distributions, Variances Known
Assumptions
Figure 10-1 Two independent populations.
1

10-1 Introduction 10 1 I t d ti
10-2 Inference for a Difference in Means of Two N f T Normal Distributions, Variances l Di t ib ti V i Known
Figure 10-1 Two independent populations.
10-2 Inference for a Difference in Means of Two N f T Normal Distribution

Stat-315 Applied Probability and Statistics
Midterm 1 (Fall 2009) Name: Score:
Students are required to finish the exam in class within two hours independently. Cheating is NOT allowed. Any forms of cheating or attempt to cheat is a serious offense which

Stat-315 Applied Probability and Statistics
Midterm 2 (Fall 2009) Name: Score:
Students are required to finish the exam in class within two hours independently. Cheating is NOT allowed. Any forms of cheating or attempt to cheat is a serious offense which

6-1 Numerical Summaries
Definition: Sample Mean
6-1 Numerical Summaries
Example 6-1
6-1 Numerical Summaries
Figure 6-1 The sample mean as a balance point for a system of weights.
6-1 Numerical Summaries
Population Mean For a finite population with N measu

9/22/2007
6-1 Numerical Summaries
Definition: Sample Mean
6-1 Numerical Summaries
Example 6-1
6-1 Numerical Summaries
Figure 6-1 The sample mean as a balance point for a system of weights.
6-1 Numerical Summaries
Population Mean For a finite population wi

Chapter 1: The Role of Statistics in Engineering
Bin Wang bwang@jaguar1.usouthal.edu
Department of Mathematics and Statistics University of South Alabama
Montgomery&Runger E4; first created on 08/15/08
Compiled on January 13, 2009by Dr. Bin WANG
1/3
Engin

2-1 Sample Spaces and Events
Chapter 2: Probability
Bin Wang bwang@jaguar1.usouthal.edu
1 2
What is random experiment? An experiment that results in different outcomes. What is sample space? The set of all possible outcomes of a random experiment is calle

Chapter 2: Probability
Bin Wang bwang@jaguar1.usouthal.edu
Department of Mathematics and Statistics University of South Alabama
Montgomery&Runger E4; first created on 08/15/08
Compiled on January 15, 2009by Dr. Bin WANG
1/18
2-1 Sample Spaces and Events
1

3.1 Discrete Random Variables
Chapter 3: Discrete Random Variables and Probability Distributions
Bin Wang bwang@jaguar1.usouthal.edu
1 2
Random variable; Discrete random variable;
Department of Mathematics and Statistics University of South Alabama
Montgo

Chapter 3: Discrete Random Variables and Probability Distributions
Bin Wang bwang@jaguar1.usouthal.edu
Department of Mathematics and Statistics University of South Alabama
Montgomery&Runger E4; first created on 08/15/08
Compiled on January 20, 2009by Dr.

4.1 Continuous Random Variables
Chapter 4: Continous Random Variables and Probability Distributions
Bin Wang bwang@jaguar1.usouthal.edu Definition (Continuous Random Variable) A random variable that can assume any value in one or more intervals.
Departmen

Chapter 4: Continous Random Variables and Probability Distributions
Bin Wang bwang@jaguar1.usouthal.edu
Department of Mathematics and Statistics University of South Alabama
Montgomery&Runger E4; first created on 08/15/08
Compiled on January 22, 2009by Dr.

9/8/2007
5-1 Two Discrete Random Variables
5-1.1 Joint Probability Distributions
5-1 Two Discrete Random Variables
5-1.2 Marginal Probability Distributions
The individual probability distribution of a random variable is referred to as its marginal probab

5-1 Two Discrete Random Variables
5-1.1 Joint Probability Distributions
5-1 Two Discrete Random Variables
5-1.2 Marginal Probability Distributions
The individual probability distribution of a random variable is referred to as its marginal probability dis