Course overview
The foundation of data analytics is based on statistics. This course will cover the concepts of random sampling and bias, experimental design, regression statistics and outliers, classification techniques, and unsupervised 'machine' learning. The course will use R as its core programming environments using real example data sets.
Course learning outcomes
- Understand fundamentals of data statistics and inference
- Understand the difference between supervised and unsupervised machine learning
- Interpret data sets from different disciplines
- Program using R
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