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Statistics and Basic Measurements

Code: 63125
ECTS: 5.0
Lecturers in charge: izv. prof. dr. sc. Mihael Makek
Lecturers: doc. dr. sc. Maja Novak - Laboratory exercises
dr. sc. Pavla Šenjug - Laboratory exercises

doc. dr. sc. Maja Novak - Exercises
Take exam: Studomat
Load:

1. komponenta

Lecture typeTotal
Lectures 30
Exercises 20
Laboratory exercises 25
* Load is given in academic hour (1 academic hour = 45 minutes)
Description:
COURSE GOALS: To acquire theoretical knowledge of the probability and statistics, gaining operational knowledge of methods of data analysis and achieving skills for collecting and analysis of data during laboratory experimental work.

LEARNING OUTCOMES AT THE LEVEL OF THE PROGRAMME:
1. KNOWLEDGE AND UNDERSTANDING
1.3 demonstrate a thorough knowledge of the most important physics theories (logical and mathematical structure, experimental support, described physical phenomena)
2. APPLYING KNOWLEDGE AND UNDERSTANDING
2.6 perform experiments independently using standard techniques, as well as to describe, analyze and critically evaluate experimental data
4. COMMUNICATION SKILLS
4.2 present one's own research or literature search results to professional as well as to lay audiences

LEARNING OUTCOMES SPECIFIC FOR THE COURSE:
By finishing this course, student will:
- know and understand probability theory, and understand need for the axiomatic approach
- know limit theorems(s) and law of large numbers
- be able to connect axiomatic theory with random processes in real life
- know main statistical concepts (expectation, variance, moments, uncertainties ...)
- be able to conduct simple physical experiments and calculate all relevant statistical parameters
COURSE DESCRIPTION:
Basic formulae for data analysis, graphical presentation of the measurements, basic combinatory, axiomatic probability theory (Kolmogorov axioms), Bayes theorem, random variable, expectation and variance, moments, several discrete distributions, Gauss distribution with central limit theorem, multidimensional random variables, law of large numbers, basic statistics concepts, estimators, (un)biased estimation, Gamma function, three laboratory exercises
REQUIREMENTS FOR STUDENTS:
Knowledge of basic set theory, and basic differential and integral analysis.
GRADING AND ASSESSING THE WORK OF STUDENTS:
The final exam consists of written and oral examinations, final score is the average value of grades obtained on each of them. Additional points are achieved by successful work in laboratory. Written exam can be replaced by a successful solving of three colloquiums.
Literature:
  1. predavanja su dostupna na Internetu
  2. A. M. Mood, F. A. Graybill, D. C. Boes, Introduction to the theory of statistics, McGraw Hill 1974
  3. J. L. Devore, Probability and statistics for engineering and the sciences, Duxbury, Thomson Learning, 2000
  4. Ž. Pauše, Uvod u matematičku statistiku, Školska knjiga, Zagreb, 1993.
2. semester
Mandatory course - Regular study - Physics
Consultations schedule: