STAT 517 Advanced Statistical Models
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Using R/Studio, students will gain working knowledge about data preparation and processing, descriptive statistics, supervised statistical learning, and unsupervised statistical learning of various data (numbers, classifications, texts and images). You will be able to conduct statistical learning research, develop feasible models, and apply them to predictive models. The interpretability and predictive accuracy of statistical models will be used in context. You will learn how to use R to solve problems in the right way and write repeatable reports. The focus will be on concept and implementation, that is, developing a clear understanding of the method, knowing the method to be used, assumptions and limitations, and actual implementation to solve the problem. The coverage is roughly divided into two main areas:
- Supervised learning: classification and regression
- Unsupervised learning: clustering, association and serialization
Learning result:
- Students will be able to access and manipulate data from various formats, sizes and visualizations to understand data structure.
- Students will be able to work competently and analyze data to match the model and draw wise conclusions and conclusions based on the model.
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