- Study programme and level: University degree programme Public sector governance 1st Cycle
- 1st year
- 8 ECTS
- Course type: Core
- Lectures: 60
- Tutorial: 30
- Other forms of study: 30
- Individual work: 120
- Lecturer: Lan Umek, PhD
1. Objectives and competences
- defines problem, asks empirical research questions, prepares, and processes statistical research,
- uses computational technology and statistical tools for gathering, analysing and presenting statistical data and results of empirical research
- uses descriptive statistical techniques for single variable analysis,
- prepares sampling process, calculates the values of sample parameters and estimates the values of population parameters,
- forms hypothesis, chooses and uses suitable hypothesis testing technique,
- analyses and reports relationships between variables, predicts and controls values of variables in relationship,
- relates the discovered statistical phenomena to the practical situation in public sector.
Student is qualified:
- to examine numerical data to grasp issues, draw conclusions, and solve problems;
- to use statistical techniques to analyse data and solve practical problems;
- to perceive, understand and resolve challenges, solvable with statistical approach;
- to identify, collect, and organize data for statistical research and value based decision-making;
- to use IT equipment and statistical tools to proceed statistical research and create reports and presentation;
- to grasp the meaning of statistical information, and apply it to situations at hand;
- to convey the results of statistical research using presentation of statistical information
Vital role of statistics in empirical research
- Problem solving, asking research questions, inductive, deductive researching
- Entities and their properties – variables
- How and where to acquire data for empirical researching, how to present statistical data
Analysis of relationships between variables
- Relationships between variables as a key to statistical prediction, how to detect and illustrate relationship between variables
- How to predict and control the values of variables
Techniques for studying relationships between variables
- An overview of the techniques for studying relationships between variables
- Techniques for illustrating relationships between variables
- The analysis of single variable
- Sampling and estimation
- Hypothesis testing
- Techniques for detecting relationships between variables
- Techniques for predicting and controlling the values of variables
- BENČINA, Jože, DEVJAK, Srečko (2010). Statistika v upravi. Fakulteta za upravo, Ljubljana: e-studij.fu.uni-lj.si/course/, 130 str.
- ROSENBERG, Kenneth .M. (2007). The Excel Statistics Companion. Thomson Higher Education, Belmont. Poglavja 1 - 7, 154 strani.
- SCHMULLER, Joseph (2009). Statistical Analysis with Excel for Dummies. Wiley Publishing, Inc., Indianapolis. Poglavja 1 – 16, 335 str.
- ARON Arthur, ARON Elaine N., COUPS Elliot (2008). Statistics for the Behavioral and Social Sciences, A Brief Course, 4th ed. Pearson Education, Inc., . New Jersey. Poglavja 1 – 10, 358 str.
- SELJAK, Janko (2000). Statistika v javni upravi. Visoka upravna šola, Ljubljana. 318 str.
4. Intended learning outcomes
- understand the vital role of statistics in public sector data analysis;
- be able: to detect problem situation, to define problem statement and ask research question; to formulate problem and define hypothesis in terms of statistics; to proceed basic hypothesis testing; understand some basic statistical techniques for processing statistical data; be able to identify and use appropriate statistical techniques for analysing relationships between variables;
- be able: to predict and control statistical phenomena; to interpret the results of statistical analysis in terms what the solution means for the problem at hand; develop commitment to the practical application of statistics in data analyses in public sector.
5. Learning and teaching methods
- practical work
- exam part:written or oral exam or 2 mid-term exams (80 %)
written part of the exam can be done by 2-mid term exams (both exceeding 50 %)
- active participation (e-learning): quizzes (20 %)
Student can get a positive grade if the combined result from the exam and quizzes (0.8*exam+0.2*quizzes) exceeds 50%.