Theory of Statistical Inference

After completed course, the students are expected to:

• Know the most common distributions and the exponential family.
• Be familiar with transformation of univariate and multivariate densities.
• Know the concept of covariance and conditional probability.
• Know the different notions of convergence i statistics like
  convergence in probability, almost sure convergence and convergence in distribution.
• Be familiar with the concept of sufficiency and the likelihood principle.
• Know the most important estimation methods like maximum likelihood, least square and the method
  of moments.
• Be able to handle a parametric hypothesis testing problem and to use the likelihood ratio method.
• Have some knowledge of asymptotic statistics.