Data Analysis 2: Foundations of Statistics

Term: 
Fall
Credits: 
2.0
Course Description: 

Type: core

Timing: Full time, part time: Friday afternoon

 

Business analytics and data science are built on classic statistics. This introductory course discusses

distributions, histograms, kernel densities, summary statistics, introduces distributions like Bernoulli, binomial, normal (Gaussian), uniform along their means and standard deviations. In terms of understanding patterns, we will look at frequency tables, joint probabilities, marginal probabilities, conditional probabilities and discuss the meaning and implication of key theories such as the Bayes' theorem or the Central Limit Theorem. Sampling methods will be introduced along with some advanced methods such as bootstrapping.  

Learning Outcomes: 

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Assessment: 

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Prerequisites: 

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