1. komponenta

Lecture type	Total
Lectures	15
Seminar	30

* Load is given in academic hour (1 academic hour = 45 minutes)

COURSE OBJECTIVE:
Introduction to statistics, probability and numerical methods, and suitable programming tools.

COURSE IMPLEMENTATION PROGRAM:
1. and 2. Descriptive statistics
3. Probability
4. Conditional probability, independent events
5. Random variables (discrete and continuous)
6. Expected value and variance
7. Binomial and Poisson distribution
8. Normal distribution
9. Parameter estimation
10. Confidence interval
11. Tests of hypotheses, t-test, F-test
12. Hi-square test
13. Least squares method. Correlation coefficient
14. Interpolation (optional)
15. Numerical methods for nonlinear equations

DEVELOPMENT OF GENERAL AND SPECIFIC SKILLS BY STUDENTS:
Students should know the basic techniques of descriptive statistics, statistical estimation, probability calculation, numerical methods for solving equations and systems of equations, approximation, optimization and differential equations. Moreover, students should be able to use Excel.

STUDENTS OBLIGATIONS:
Class participation, solving given problems.

PREREQUISITES FOR COURSE ENROLLMENT.
- Mathematics 1

PREREQUISITES FOR ATTENDING THE COURSE EXAM:
Active class participation.

TEACHING METHODS
Lectures, computer demonstrations.

EXAMINATION METHODS
Two midterms exams or a final exam. Excel exam.

METHODS FOR MONITORING THE COURSE QUALITY
Student Survey

1. to apply descriptive statistics to data analysis
2. to sketch the axioms of probability
3. to apply the knowledge of discrete and continuous random variables
4. to apply the estimation and testing techniques when making decisions about the population based on a sample
5. to be able to use Excel procedures
6. to explain scientific principles important for materials science and engineering, especially in chemistry, physics, mathematics and chemical engineering
7. to use suitable computer databases, analytical and modelling software
8. to present results of their work in written and oral form

1. Uvod u teoriju vjerojatnosti i statistiku za inženjere, Skripta, I. Gusić, http://matematika.fkit.hr,
2. Uvod u statistiku, Ž. Pauše, Školska knjiga, 1993.
3. Numerička matematika, I. Ivanšić, Element, 1993.
4. Probability and Statistics for Engineering and the Sciences, J. Devore, Cengage Learning, 2015.

Enrollment :
Attended : Calculus I

Mandatory course - Regular studij - Materials Science and Engineering