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Examination in progress. Last date: Tuesday 27th of June at 12:30.Course outline
- Introduction to statistics. Data preprocessing
- Exploratory data analysis (descriptive statistics, data visualization)
- Brief review of probability theory
- Probability distributions. Central limit theorem
- Point estimates (maximum likelihood method, method of moments)
- Confidence intervals, testing of statistical hypotheses
- Model selection. Normality testing
- Testing of statistical hypotheses II (two sample tests)
- ANOVA, tests of independence, contingency tables
- Nonparametric tests
- Linear regression model (revision and generalization)
- Modern methods - Monte Carlo simulations, bootstrap
- Revision
Prerequisities
- Basic knowledge of mathematical analysis: functions, limits of sequences and functions, derivations and integral for real and multidimensional functions.
- Basic knowledge of linear algebra: matrices and determinants, eigenvalues and eigenvectors.
- Basic knowledge of probability theory: probability, random variables and vectors, limit theorems.
- Basic knowledge of linear regression models.
Review (self study) of probability theory
- Sigma algebra, probability measure and its properties, Kolmogorov definition of probability, conditional probability, independent events.
- Random variables and vectors, their distributions, properties and connections. Discrete and continuous random variables and random vectors, their distributions. Numerical characteristics of random variables and random vectors. Independent random variables.
- Law of large numbers, central limit theorem.
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Assessment methods
- 3 homework assignments (you can get together up to 40 points).
- Final written exam - open notes (you can get up to 60 points).
Type of Completion:
- Fulfilling requirements (Zápočet, Z) - need to get at least 50 points in total.
- Examination (Zkouška, Zk) - grading:
100-90 | A |
89-80 | B |
79-70 | C |
69-60 | D |
59-50 | E |
49-0 | F |
The final exam
- The exam type: written with open notes.
- Time for the exam: 100 minutes.
- During the exam, you will be asked to prove your identity (showing your ID).
- If anybody has recorded disability in Information System and needs special treatment, let me know before the exam (in advance). Subsequent demands will not be taken into account.
- The exam language is English.
- The exam will be written. You will write down your solution on separate sheets of paper.
- You may use any materials available, but communication with others is prohibited.
- You may use R for computations, but all the relevant results state in your solution (you will not submit your R-code).
- Google or Wikipedia solutions will not be accepted.
- The use of ChatBots is strictly forbidden.
- In case of suspicious solutions and results, you might be subject to an additional oralexam.
- Unreadable solutions will be ignored.
- Sample exam:
Error: The referenced object does not exist or you do not have the right to read.https://is.muni.cz/el/fi/jaro2023/MV013/um/MV013-sample-exam2023.pdf
Seminars
- The first week (February 14 - 15) optional exercise classes will take place to get familiar with statistical software R and RStudio.
- Regural exercise classes (seminars) start the second week.
- Attendance at the seminars is obligatory (two unexcused absences will be tolerated).
- Only proper excuses will be accepted uploaded into Information System on time).
- All the students must be assigned to a seminar group (otherwise, you get an "X").
- There
are 2 groups for students who cannot bring their own laptops and 4 groups for
students with their own laptops.
Homework assignments
- The assignment will be published centrally on Wednesday afternoon/evening (3 times a semester, not regularly).
- Deadline: the next Wednesday 23:59 (midnight).
- Solution (pdf and source code) upload to "Homework vaults" in the Information system.
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