Statistics

Subject	Statistics
Semester	3rd semester (autumn)
Type	compulsory
ECTS	9 ECTS
Study programme:	Economics / 1st Bologna cycle
Primary language:	Slovene

Introduction
The course is delivered in Slovenian and is a compulsory course in accordance with the curriculum of the undergraduate study programme in Business Studies. The course comprises 8 modules.
 
Prerequisites
Students must understand basic arithmetical operations and basic mathematical techniques, namely probability calculus, integration and differentiation. Students must have a sufficient command of English to be able to use the material on the online portals listed above independently, which serve as an aid in studying the course.

Content (Syllabus outline) 1. Introductory lectures. Counting, sets.
2. The fundamentals of probability calculus, an introduction to R.
3. Conditional probability.
4. Discrete random variables, simulations in R.
5. Variance, continuous random variables.
6. The law of large numbers and the central limit theorem.
7. Joint distributions, covariance and correlation, working with R.
8. Computer module (the R programme).
Objectives and competences
1. To learn the terminology and the fundamental concepts of probability theory. 2. To understand the principles of statistical inference. 3. To assemble a basic toolkit for a beginner working with statistical tools, together with an understanding of its usefulness and its limits. 4. To use software and to run statistical simulations (R Studio). 5. To become an informed user of statistical information. 6. To prepare for the course Statistics for Business Decision-Making in the second year of study.

Intended learning outcomes
Competences The use of the fundamental techniques of combinatorics (the multiplication rule, combinations, permutations) to calculate probabilities. The use of R Studio to simulate probabilistic scenarios. Calculating conditional probabilities and applying Bayes' theorem, testing the independence of events. Preparation for working with discrete random variables (Bernoulli, binomial, geometric and Poisson distributions). Preparation for working with continuous random variables (uniform, normal and exponential distributions). Knowledge of expected values and variance. Understanding of the law of large numbers and the central limit theorem. Calculating the covariance and correlation between jointly distributed random variables. The use of the available sources (the internet, books, articles) to understand other distributions.

Learning and teaching methods

Forms of work

Frontal teaching

Independent and individual student work

Methods of work

• Explanation
• Conversation/debate
• computer module
• case studies
• solving tasks

Assessment

Assessment consists of three elements: 1) a written examination (70/100), 2) homework (10/100), 3) a computer seminar (20/100). The written examination may be replaced by two mid-term tests, scheduled at the midpoint (after modules 1-4) and at the end of the course (after modules 5-8).

Completing the computer seminar and the homework is not a precondition for taking the written examination. Points obtained in the seminar and the homework are awarded by the end of the current semester in which the course is delivered. Points for both can be obtained only within the semester in which the course is delivered.

Method of submitting the seminar: in print, by the day of mid-term test 2 in the current semester of delivery.

Method of submitting homework: in print, on an ongoing basis at each session for the previous module. Homework submitted late will not be taken into account. The last homework assignment is to be submitted by the day of mid-term test 2 in the current semester of delivery.

Readings

• Steinbacher, Mitja. 2019. Statistika [Elektronski vir]: skripta predavanj in vaj za 1. letnik univerzitetnega programa Poslovne vede.
• Spletni portal: https://ocw.mit.edu/courses/mathematics/18-05-introduction-to-probability-and-statistics-spring-2014/index.htm. Študentje so opozorjeni na pravila rabe gradiva na naslovu: https://ocw.mit.edu/terms.
• Prosojnice s predavanj in računalniških modulov s povzetki temeljnih vsebin ter dodatna gradiva za računske module ter drugi študijski materiali.

Office hours

• before and after lectures
• by arrangement