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MATLAB Introduction

Guide to using MATLAB for data analytics at UML

MATLAB Learning Objectives

  1. Use of MATLAB and MathWorks Statistics and Machine Learning Toolbox.
  2. Create and troubleshoot basic m scripts.
  3. Import datasets for analysis.
  4. Plot datasets.
  5. 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

Data Analysis Learning Objectives

  1. Describe, analyze and model CPH-NEW or other research datasets.
  2. Use descriptive statistics and plots for exploratory data analysis (EDA).
  3. Fit probability distributions to data.
  4. Perform hypothesis testing.
  5. Apply basic regression and classification algorithms.
  6. 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.