• Admission prerequisites

    The year 2016 call for applications has been published on 23 May 2016 here.
    Deadline for the applications: noon of 22 June 2016.

    Students aspiring to apply for the Statistics curriculum of the the PhD must have a good preparation in Mathematical Analysis and be familiar with the following statistical concepts:

    • Frequency distributions
    • Measures of location, variability and shape
    • Correlation and regression
    • Population and sample
    • Parametric and nonparametric statistical models
    • Point estimation: estimation methods and sample distribution of an estimator
    • Confidence intervals and regions
    • Hypothsis testing: test statistic, p-value, power function
    • Likelihood function and related quantities
    • Estimation, tests and confidence intervals based in the lokelihood function
    • Standard examples: inference on normal parameters (including linear regression), binomial models, multinomial models.

    The level of knowledge of the above concepts should be at least that of
    Mood A.M., Graybill F.A., Boes D.C., Introduction to the Theory of Statistics, 3rd ed., 2006, McGraw Hill.

    The level of knowledge of Mathematical Analysis should be at least that of
    Rudin  W., Principles of Mathematical Analysis, McGraw-Hill Education.