Course objectives:
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Processing of combinatorial and statistical problems in the environment of the program Mathematica. The main emphasis is placed on the creation of statistical models and their treatment by means of the program (such as regression analysis, interval estimates of parameters, graphical methods) or the development of support aids (such as some non-traditional non-parametric tests).
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Requirements on student
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Processing term paper on a selected topic in the field of statistics. The student will use their own zpraacování cathedral environment Mathematica. The results will also be interpreted in either the environment or the environment webMathematica projects in Mathematica.
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Content
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Course contents for individual weeks
1st The week combinatorial and statistical concepts
2nd Week Graphic data processing. Interval estimates.
3rd Construction week interval estimates for normal and binomial distribution
4th Construction week interval estimates for other types of distribution. Interval estimate of the difference mean values
5th Week Interval estimates of mean values for large selections. Bootstrap method.
6th Week Regression
7th Week Correlation
8th Week Hypothesis Testing
9th The Week parametric tests
10th The Week parametric tests
11th Week Nonparametric Tests
12th Week Nonparametric Tests
13th Week Repetition and final test
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Activities
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Fields of study
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Guarantors and lecturers
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Literature
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Contact hours
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26
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Preparation for formative assessments (2-20)
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14
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Graduate study programme term essay (40-50)
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30
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Total
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70
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Prerequisites - other information about course preconditions |
Students should have basic knowledge of the theory of probability, at least at the KMT / PAS and knowledge of the program Mathematica 6.0 or higher at least at the course KMT / PMS. |
Competences acquired |
Student:
- Understands the basic combinatorial and statistical concepts
- Can process graphics data. Means the creation of interval estimates.
- Understands the creation of structures of interval estimates for normal and binomial distribution
-is able to carry out the construction of interval estimates for other types of distribution. Interval estimates of the difference mean values and interval estimates of mean values for large selections.
-is familiar with the basics of regression and correlation analysis
-Understands the nature of hypothesis testing
- Can take the basic parametric tests (mean, variance)
- Using non-parametric tests
Developed are primarily for learning skills, communication skills, problem-solving, work and partly civic and social skills. |
Teaching methods |
- Lecture with practical applications
- Individual study
- Practicum
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Assessment methods |
- Test
- Seminar work
- Individual presentation at a seminar
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