Guide to using MATLAB for data analytics at UML

- Use of MATLAB and MathWorks Statistics and Machine Learning Toolbox.
- Create and troubleshoot basic m scripts.
- Import datasets for analysis.
- Plot datasets.
- Create publishable, reproducible analysis reports.

While the goal is not to focus on 'programming', participants should become capable to gain a working proficiency in the use of MATLAB in data analysis

- Describe, analyze and model CPH-NEW or other research datasets.
- Use descriptive statistics and plots for exploratory data analysis (EDA).
- Fit probability distributions to data.
- Perform hypothesis testing.
- Apply basic regression and classification algorithms.
- Have the basic understanding on how to explore Statistics and Machine Learning Toolbox advanced methods (i.e. feature selection, regularization and other dimensionality methods).

NOTE: The expectation is not that participants become experts in advanced tools mentioned above, but to enable them to work under the direction of a statistician such as one the CPH-NEW investigators.

- Last Updated: Jul 27, 2021 2:02 PM
- URL: https://libguides.uml.edu/MATLAB
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