Professor Anvari

Taught manufacturing and industrial systems engineering courses at the University of Michigan for five years where he received his three engineering degrees, and as an adjunct professor he teaches project and cost management at local universities in the Washington DC area. 

In his early career he worked at General Motors as a production engineer and later as an operations research and systems analyst at the cost and economic analysis center in Washington DC.

Mort is currently the ASA (FM&C) Lean Six Sigma (LSS) deployment director and is responsible for cost and economics programs and strategy where he oversees process improvement initiatives, economic studies validation, cost benefit analysis, and risk & uncertainty analysis in support of major defense programs.

Mort is Defense Acquisition University Level III Certified in Business, Cost Estimating, and Financial Management (BCEFM) and has won the 2006 DoD modeling and simulation award.

In his public lectures, Mort stimulates cost culture debates among government and industry leaders and managers. Professor Anvari has repeatedly appeared on live television programs analyzing the political economy of the Middle East.

Text Box: The course materials listed in this web site are copy rights © by the subject book publishers and are intended only for the classroom teaching of the subject books. Copy and redistribution of these contents are prohibited by the US copyright law.
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Anvari.Net

 

 

 

 

 

 

 

 

Probability & Statistics for Engineers & Scientists

 

 

1

Introduction to Statistics and Data Analysis

10

One and Two-Sample Tests of Hypotheses

 

 

2

Probability

11

Simple Linear Regression and Correlation

 

 

3

Random Variables and Probability Distributions

12

Multiple Linear Regression & Nonlinear Models

 

 

4

Mathematical Expectation

13

One-Factor Experiments: General

 

 

5

Some Discrete Probability Distributions

14

Factorial Experiments (Two or More Factors)

 

 

6

Some Continuous Probability Distributions

15

2k Factorial Experiments and Fractions

 

 

7

Functions of Random Variables

16

Nonparametric Statistics

 

 

8

Sampling, Distributions Data Descriptions

17

Statistical Quality Control

 

 

9

One and Two-Sample Estimation Problems

18

Bayesian Statistics

 

 

 

Regression Analysis (2nd Course in Statistics)

 

 

1

A Review of Basic Concepts

7

Some Regression Pitfalls

 

 

2

Introduction to Regression Analysis

8

Residual Analysis

 

 

3

Simple Linear Regression

9

Special Topics in Regression

 

 

4

Multiple Regression Models

10

Time Series Modeling and Forecasting

 

 

5

Principles of Model Building

11

Principles of Experimental Design

 

 

6

Variable Screening Methods

12

Analysis of Variance for Designed Experiments

 

 

 

Regression Analysis Case Studies

 

 

1

Legal Advertising- Does it Pay?

5

 Factors Affecting Sale Price at Public Auction

 

 

2

Modeling the Sale Prices of Properties

6

Modeling Daily Peak Electricity Demands

 

 

3

Deregulation of the Intrastate Trucking Industry

7

Reluctance to Transmit Bad News: MUM Effect

 

 

4

An Analysis of Rain Levels in California

 

 

 

 

 

Statistics for Business Decision Making & Analysis

 

 

1

Introduction

14

Sampling Variation and Quality

 

 

2

Data

15

Confidence Intervals

 

 

3

Describing Categorical Data

16

Statistical Tests

 

 

4

Describing Numerical Data

17

Alternative Approaches to Inference

 

 

5

Association between Categorical Variables

18

Comparison

 

 

6

Association between Quantitative Variables

19

Linear Patterns

 

 

7

Probability

20

Curved Patterns

 

 

8

Conditional Probability

21

The Simple Regression Model

 

 

9

Random Variables

22

Regression Diagnostics

 

 

10

Association between Random Variables

23

Multiple Regression

 

 

11

Probability Models for Counts

24

Building Regression Models

 

 

12

The Normal Probability Model

25

Categorical Explanatory Variables

 

 

13

Samples and Surveys

26

Analysis of Variance

 

 

 

 

27

Time Series

 

 

 

Statistics for Business and Economics

 

 

1

Describing Data: Graphical

2

Describing Data: Numerical

 

 

3

Probability

4

Random Variable, Probability Distributions

 

 

5

Continuous Variables and Distributions

6

Sampling & Sampling Distributions

 

 

7

Estimation: Single Population

8

Estimation

 

 

9

Hypothesis Testing

10

More on Hypothesis Testing

 

 

11

Simple Regression

12

Multiple Regression

 

 

13

More on Regression Analysis

14

Analysis of Categorical Data

 

 

15

Analysis of Variance

16

Time-Series Analysis and Forecasting

 

 

17

Additional Topics in Sampling

18

Statistical Decision Theory

 

Calculus

 

 

 

1.3  Exponential Functions

 

3.1  Derivatives

1.4  Parametric Equations

 

3.2_Differentiability

1.5  Functions and Logarithms

 

3.3  Rules for Differentiation

1.6  Trig Functions

 

3.4   Velocity, Speed, and Rates of Change

2.1  Rates of Change and Limits

 

3.5  Derivatives of Trig Functions

2.1.2  Step Functions

 

3.6  The Chain Rule

2.2  Limits Involving Infinity

 

3.7  Implicit Differentiation

2.3_Continuity

 

3.8_Derivatives of Inverse Trig Functions

2.4_Rates of Change and Tangent Lines

 

3.9  Derivatives of Exponential and Logarithmic Functions

Calculus for Scientist and Engineers

1. Functions

 

8. Sequences and Infinite Series

2. Limits

 

9. Power Series

3. Introducing the Derivative

 

10. Parametric and Polar Curves

4. Applications of the Derivative

 

11. Vectors and Vector-Valued Functions

5. Integration

 

12. Functions of Several Variables

6. Applications of Integration

 

13. Multiple Integration

7. Integration Techniques

 

14. Vector Calculus