Applied Statistics

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Mathematics

Synopsis:

Basic notions and terminology, random variable, descriptive and inferential statistics. Discrete and continuous random variables, normal distribution, log-normal distribution. Statistical methods, theory of estimation, hypotheses testing, simple linear regression.

Requirements:

none

Syllabus of lectures:

Subject can be adapted according to students demands.

1. Difference between descriptive and inferential statistics.

2. Probability. Conditional probability. Independence of random events.

3. Discrete random variables, probability distribution, expectation, variance, examples of discrete distributions.

4. Continuous distribution. Density. Distribution function. Quantiles.

5. Normal distribution.

6. Log-normal distribution.

7. two-dimensional distribution. Marginal distribution. Independence. Correlation.

8. Central limit theorem.

9. Parameters estimation. Confidence intervals.

10. Hypotheses testing. One and two-samples tests.

11. Linear regression. Method of least squares.

12. Linear regression. Estimation of parameters. Prediction.

Syllabus of tutorials:

1. Descriptive statistics in Excel.

2. Normal distribution in Excel.

3. Theory of estimation. Confidence intervals.

4. Two-sample problems.

5. Monte Carlo methods.

Study Objective:

Students know probability models and statistical methods of data analyses.

Study materials:

Jarušková D.: Matematická statistika, ČVUT Praha, 1997. Jarušková D., Hála M.: Pravděpodobnost a matematická statistika 12 - Příklady, ČVUT Praha, 2000.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Stavební inženýrství, specializace Pozemní stavby (compulsory elective course)
• Stavební inženýrství, specializace Pozemní stavby (compulsory elective course)