Applied Data Analysis and Modeling for Energy Engineers and Scientists

1. Mathematical Models and Data Analysis
T. Agami Reddy

2. Probability Concepts and Probability Distributions
T. Agami Reddy

3. Data Collection and Preliminary Data Analysis
T. Agami Reddy

4. Making Statistical Inferences from Samples
T. Agami Reddy

5. Estimation of Linear Model Parameters Using Least Squares
T. Agami Reddy

6. Design of Experiments
T. Agami Reddy

7. Optimization Methods
T. Agami Reddy

8. Classification and Clustering Methods
T. Agami Reddy

9. Analysis of Time Series Data
T. Agami Reddy

10. Parameter Estimation Methods
T. Agami Reddy

11. Inverse Methods
T. Agami Reddy

12. Risk Analysis and Decision-Making
T. Agami Reddy

Keywords: Energy, Energy Efficiency (incl. Buildings), Engineering Thermodynamics, Heat and Mass Transfer, Probability Theory and Stochastic Processes, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences