# Computing

## Probability and Statistics

- Class 60
- Practice 21
- Independent work 99

### Course title

Probability and Statistics

### Lecture type

Obligatory

### Course code

183401

### Semester

3

### ECTS

6

### Lecturers and associates

### Course objectives

Probability; equally likely outcomes; geometric probability.

Conditional probability; independence; law of yotal probability; Bayes' rule.

Discrete random variables and random vectors; marginal distribution; conditional distribution.

Moments; characteristic function; generating functions.

Geometric Distribution; Binomial Distribution; Poisson Distribution.

Random variables; probability distributions; probablitiy densities; Functions of random variables.

Exponential distribution; normal distribution.

Midterm exam.

Random vectors; conditional probability distributions.

Functions of random vectors; Law of large numbers and central limit theorem.

Measures of central tendency (mean, median, mode); measures of dispersion (standard deviation, variance, quantile, and IQR); Unbiased point estimations; Maximal-likelihood estimation.

Interval estimations; confidence intervals; Confidence Intervals for parameters of normal distribution.

Hypothesis testing; type of errors; parametric hypothesis testing; sampling distributions.

Hypothesis testing; type of errors; parametric hypothesis testing; sampling distributions; Pearson's Chi-squared Test (Goodness-of-fit tests, tests of independence and homogeneity).

Final exam.

### Prerequisites for:

- Artificial Intelligence
- Mobile Communications
- Information Theory
- Digital Video
- Statistical Data Analysis

### Required reading

(2018.), N.Elezović: Vjerojatnost i statistika, Element, Zagreb

(1989.), Ž. Pauše, Uvod u matematičku statistiku, Školska knjiga, Zagreb

(1989.), Ž. Pauše, Riješeni primjeri zadaci iz vjerojatnosti i statistike, Školska knjiga, Zagreb

#### Online education during epidemiological measures

- Study program duration
- 6 semesters (3 years)
- Semester duration
- 15 weeks of active teaching + 5 examination weeks
- Total number of ECTS points
- 180
- Title
- Bacc.ing.comp (Bachelor of Science in Computing)

**Academic calendar**

#### Minimal learning outcomes

- Solve problems of evaluating probability of a given event
- Recognize specific discrete or continuous distribution
- Solve problems of evaluating expectation and variance of some distribution
- Analyze given data
- Solve problems of point and interval estimation
- Use statistical tests
- Demonstrate ability for mathematical modelling
- Use critical thinking