Statistic data processing of agricultur machinery

ID: 3574
Course type: scientific and vocational
Course coordinator: Simonović D. Vojislav
Lecturers: Simonović D. Vojislav
Contact: Simonović D. Vojislav
Level of studies: Ph.D. (Doctoral) studies – Mechanical Engineering
ECTS: 5
Final exam type: written

Lectures

Goal

Consideration of statistical methods for data processing in engineering of engineering systems and their application in solving specific problems.

Outcome

Ability to prepare data, perform preliminary statistical considerations or descriptive statistics, select the correct statistical method to apply to the appropriate data set, process statistical data and interpret the results.

Theoretical teaching

Mathematical settings of certain statistical methods.

Practical teaching

Data analysis in SPSS Statistics software package.

Attendance requirement

Regulated by the program of study.

Resources

SPSS Statistics software package.

Assigned hours

Total assigned hours: 65

Active teaching (theoretical)

New material: 40
Elaboration and examples (recapitulation): 10

Active teaching (practical)

Auditory exercises: 0
Laboratory exercises: 0
Calculation tasks: 0
Seminar paper: 0
Project: 0
Consultations: 0
Discussion/workshop: 0
Research study work: 0

Knowledge test

Review and grading of calculation tasks: 0
Review and grading of lab reports: 0
Review and grading of seminar papers: 0
Review and grading of the project: 0
Test: 0
Test: 0
Final exam: 15

Knowledge test (100 points total)

Activity during lectures: 70
Test/test: 0
Laboratory practice: 0
Calculation tasks: 0
Seminar paper: 0
Project: 0
Final exam: 30
Requirement for taking the exam (required number of points): 0

Literature

Tabachnick, B.G., Fidell, L.S. (2007). Using multivariate statistics (5th edn). Boston: Pearson Education.; Еllis, Paul D. (2010). The Essential Guide to Effect Sizes: An Introduction to Statistical Power, Meta-Analysis and the Interpretation of Research Results. United Kingdom: Cambridge University Press.; Garson, G. D. (2012). Significance Testing: Parametric & Nonparametric. Asheboro, NC: Statistical Associates Publishers., 91-95.