统计学（双学位与大学博洛尼亚）学士

第三学年Year 3 (level 4 in Glasgow)

• Flexible Regression - 10 credits / 5 ECTS
• Advanced Bayesian Methods - 10 credits / 5 ECTS
• Stochastic Processes - 10 credits / 5 ECTS
• Advanced Data Analysis - 10 credits / 5 ECTS
• Statistics Project - 30 credits / 15 ECTS
• Data Management and Analytics using SAS - 10 credits / 5 ECTS
• Statistical Programming in R and Python - 10 credits / 5 ECTS
• Spatial Statistics - 10 credits / 5 ECTS
• Theoretical Foundations of Machine Learning and Deep Learning – 20 credits / 10 ECTS
• Statistical Genetics – 5 ECTS
• Functional Data Analysis – 5 ECTS
• Environmental and Ecological Statistics – 10 credits / 5 ECTS
• Multivariate Statistics and Machine Learning 2 - 10 credits / 5 ECTS
• Deep Learning - 10 credits / 5 ECTS

第二学年Year 2

• 统计学2R:概率Statistics 2R: Probability

  STATS2002

• 统计学2S:统计方法模型与计算机Statistics 2S: Statistical Methods, Models and Computing 1

  STATS2003

• Mathematics 2A: Multivariable Calculus

  MATHS2001

• Mathematics 2B: Linear Algebra

  MATHS2004

• 统计学2X:概率二Statistics 2X: Probability II

  STATS2005

• 统计学2Y:统计方法模型与计算机Statistics 2Y: Statistical Methods, Models and Computing 2

  STATS2006

• 数学2D:数学方法与建模Mathematics 2D: Mathematical Methods and Modelling

  MATHS2033

第三学年Year 3 (Year 2 in Bologna)

• 概率二Probability II
• 分析数据Analysis of Data
• Inference
• 数学二Mathematics II
• 生物统计Biostatistics
• Mutivariate Analysis
• Time Series
• 计量经济学Econometrics
• Survey Sampling
• 统计模型Statistical Models