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
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