INFORMATION
  • Invitation Letter (old!)
  • Access map 1
  • Access map 2

  • MATERIALS
  • Handouts (zip)
  • Case Problems

  • Lecture 1
  • Lecture 2
  • Lecture 3
  • Practics (Excel)
  • Lecture 5
  • Lectures 6,7
  • Lectures 8
  • Lectures 9
  • Lectures 10
  • Lectures 11

  • DATA (all zipped)
  • cells.xls
  • beer.xls
  • chemline.xls
  • bloodpressure.xls
  • schoolbus.xls
  • bile.xls
  • children.xls
  • depression.xls
  • mice.xls
  • pancreatitis.xls
  • salaries.xls

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    27.11.2009
    The first course is finished now! Thank you for the participation and "satisfaction survey" :)!

    The information about the next sessions and conditions will be provided soon.


    9.11.2009
    New Timetable

    Week 1
    Tuesday 10.11.2009   9:00 - 12:00 (passed)
    Wednesday 11.11.2009 9:00 - 12:00 (passed)
    Thursday 12.11.2009  9:00 - 12:00 (passed)

    Week 2
    Tuesday 24.11.2009   9:00 - 12:00 (passed)
    Wednesday 25.11.2009 9:00 - 12:00 (passed)
    Thursday 26.11.2009 14:00 - 17:00(passed)

    The cource will take place at Sanger room, 1st floor of Edison building of CRP-Sante. Please see the acess maps: photo, scheme

    Abstract

    The course gives an overview of the basics of applied statistics for researchers, engineers and students. It is specifically dedicated to those, who having no special knowledge in statistics, use or would like to use statistical methods in their practice. The course is built in the way that even a person with no background in statistics is able to follow it. Special attention is given to understanding of the basic rules and objects of a statistical investigation and their application. For this purpose examples will be given throughout the lectures. The course is divided into 6 three-hour sections, each followed by a small test for a self control. Practical parts (conducted in Excel) are integrated into the lectures, allowing immediate application of the theory.


    Plan

     Section I. TUESDAY November 10
    Lecture 1. Data presentation and numerical measures
         Data and statistics
         Descriptive statistics: tabular and graphical presentation
         Descriptive statistics: numerical measures (mean, median, standard deviation,variance, correlation)
         z-score. Chebyshev's theorem. Detection of outliers
    Lecture 2. Introduction to probability
         Introduction to probability
         Calculation of probability
         Bayes' theorem

     Section II. WEDNESDAY November 11
    Lecture 3. Probability distributions
         Discrete probability distributions (uniform, binomial, Poisson, hypergeometric)
         Continues probability distributions (uniform, Gaussian, exponential)
    Lecture 4. Practical work with Excel
         Case problem. Usage of the information about distribution

     Section III. THURSDAY November 12
    Lecture 5. Sampling statistics
         Sampling and sampling distribution
         Central limit theorem
         Means of sum of two normal random variables.
    Lecture 6. Statistical inference about mean (part 1)
         Interval estimation for the means
         Hypothesis tests and decision making
         Statistical inference about means and proportions of two populations
         Case problem. Formulation and test of hypotheses

     Section IV. TUESDAY November 24
    Lecture 7. Statistical inference about mean (part 2)
         Nonparametric methods for the comparison of means
         Number of replicates
         Means of sum, product and ratio of two random variable
         Hypothesis test in the case of multiple experiments
    Lecture 8. Statistical inferences about variance
         Interval estimation for the variance
         Hypothesis test for the variances of two population
         Tests of goodness of fit and independenc

     Section V. WEDNESDAY November 25
    Lecture 9. Analysis of variance (ANOVA)
         One-way ANOVA
         Two-way ANOVA
    Lecture 10. Topics in applied data analysis
         Multi-factor ANOVA
         Experimental design
         Principle component analysis (PCA)

     Section VI. THURSDAY November 26
    Lecture 11. Regression
         Linear regression. Estimation of the parameters
         Nonlinear regression
         Quality control
         Forecasting
    Lecture 12. Final remarks
         Verification of the tests
         Questions




    For further information:

          Dr. Petr NAZAROV
             Microarray Center, CRP-Sante, Luxembourg
             Tel. (+352) 26 970 283
             petr.nazarov(at)crp-sante.lu
          Aurelia DERISCHEBOURG
             CRP-Sante, Luxembourg
             Tel. (+352) 26 970 893
             aurelia.derischebourg(at)crp-sante.lu

    In the case of mistakes or possible copyright violations, please, contact the webmaster. Last update 25-11-2009