Subject

Applied Statistical Analysis

Course Title

Applied Statistical Analysis
Applied statistical analysis

Code

m23_w_023

Study Programme

Data statistics and analytics

Organizer of the study programme (unit, institute, department or division)

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

Second cycle

Academic year / semester

9 / Winter

Number of ECTS credits

Teacher

Bojan Ilijoski, Ilinka Ivanoska, Marija Mihova

Prerequisites for enrolling in the course

—

10.

Objectives of the course programme (competences)

The main goal is for students to gain knowledge and experience in using statistics with a real-world perspective and to understand what their solutions could be. Additionally, the objectives of this course include building students' foundation in applied statistics, enhancing practical skills and promoting corporate practices, developing statistical consulting and data-mining skills, and providing experience in preparing oral and written reports, etc. Students will learn to use open-source software packages for data analysis and processing, commercial software for statistical data processing, and will also be introduced to the fundamentals of statistical programming.

11.

Course content

Principles of applied statistics, statistical computation, statistical modeling, applications of statistics, description, interpretation, and exploratory analysis of data using graphical and other tools, statistical tools, analysis of ready-made data with SPSS (or Stata or SAS), work in Excel, and fundamentals of programming in R and/or Python.

12.

Learning methods

Lectures. Preparation of a seminar paper and a project.

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of available time

60 + 0 + 30 + 60 + 30 = 180 hours

15.

Forms of teaching activities

15.1.	Lectures - theoretical instruction	60 hours
15.2.	Exercises (laboratory, auditory), seminars, teamwork	0 hours

16.

Other forms of activities

16.1.	Project assignments	60 hours
16.2.	Independent assignments	30 hours
16.3.	Home study	30 hours

17.

Assessment method

17.1.	Tests	10 points
17.2.	Seminar paper / project (presentation: written and oral)	60 points
17.3.	Activities and learning	10 points
17.4.	Final exam	0 points

18.

Grading criteria (points / grade)

up to 50 points	5 (five) (F)
from 51 to 60 points	6 (six) (E)
from 61 to 70 points	7 (seven) (D)
from 71 to 80 points	8 (eight) (C)
from 81 to 90 points	9 (nine) (B)
from 91 to 100 points	10 (ten) (A)

19.

Requirement for obtaining a signature and taking the final exam

Prepared project and seminar papers

20.

Language of instruction

Macedonian

21.

Method for monitoring the quality of teaching

Questionnaires and interviews with students.

22.

Literature

22.1.

Required literature

22.2.

Additional literature

No. Author Title Publisher Year