References

BOOKS:

  1. Engineering Statistics, Montgomery, D.C., G.C. Runger and N.F. Hubele, 5th edition, John Wiley & Sons, Inc., 2011.

  2. Applied Numerical Methods with MATLAB for Engineers and Scientists, Chapra, S.C., 3rd edition, 2011.

  3. Probability Concepts in Engineering, Ang, A. and W. Tang, 2nd edition, JohnWiley & Sons, Inc.

  4. Geographic Information Systems and Science, Longley, P., John Wiley & Sons, Inc.

  5. Statistical Inference and Estimation, STAT 504 of PennState Eberly College of Science


COURSES:

  1. Introduction to Computational Thinking and Data Science, MIT Open Courseware

  2. Essential Statistics for Data Analysis using Excel, DAT222x, by Microsoft

  3. Probability and Statistics in Data Science using Python, DSE210x, by UCSanDiegoX

  4. Think Stats: Exploratory Data Analysis in Python, Allen B. Downey (Professor of Computer Science at the Franklin W. Olin College of Engineering in Needham, MA), 2014

  5. Earth Analytics Python Course, Earth Lab at University of Colorado, 2019

  6. Introduction to Numerical Methods and Matlab Programming for Engineers, by Todd Young and Martin J. Mohlenkamp, Ohio University

  7. Inferential Statistics Walkthrough, The Learning Machine site


OTHER MATERIALS

1. MATLAB Statistics Toolbox, MathWorks Inc.

2. MATLAB Curve Fitting Toolbox, MathWorks Inc.

3. Moler, C., Numerical Computing with MATLAB

4. Math is Fun: Data

5. The Complete MATLAB Course: Beginner to Advanced

6. Water statistics

7. Coding the Matrix - Philip N. Klein.

8. Cody Coursework of MathWorks (Instructor Guide)

9. Octave Online

10. Data Analysis, Teaching Computation in the Sciences Using MATLAB