1. SylabUZ
2. Wydział Nauk Ścisłych i Przyrodniczych
3. semestr zimowy 2024/2025
4. WMIiE - oferta ERASMUS - Program Erasmus
5. Statistical Data Analysis

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Statistical Data Analysis - opis przedmiotu

Cel przedmiotu

The aim of the subject of statistical data analysis is to familiarize the student with the basic methods of statistical analysis and the program supporting these analyzes. All methods and issues will be illustrated with practical / real examples.

Wymagania wstępne

Zapisz zmiany

Mathematical analysis, linear algebra and  probability theory.

Zakres tematyczny

Lecture / Laboratory:

1. Presentation of practical methods of mathematical statistics for the analysis of statistical data:

·        point estimation,

·        interval estimation,

·        hypothesis testing (one-sample and two-sample tests),

·        analysis of variance,

·        correlation and association.

2. Use of an appropriate statistical package to perform statistical analyzes.

Metody kształcenia

Lecture: traditional; available in electronic form.

Laboratory: performing statistical analyzes with the use of a computer program; discussion on the analyzes carried out related to their application in selected fields (economics, sociology, physics, biology, medicine and others).

Efekty uczenia się i metody weryfikacji osiągania efektów uczenia się

Opis efektu	Symbole efektów	Metody weryfikacji	Forma zajęć

Warunki zaliczenia

1. Checking students' activities during classes.
2. Tests with the tasks of different difficulty.
3. Written exam with some questions, which verify knowledge of the theory and some questions, which verify skill to apply known methods of statistical inference.

The grade for the course consists of a laboratory grade (40%) and a written exam grade (60%). The condition for passing the course is positive grades from the laboratory and the exam.

Literatura podstawowa

1. A. D. Aczel, Complete Business Statistics, Sounderpandian, Jayavel, 2008.
2. P. Bruce, A. Bruce, Practical statistics for data scientists. 50 essential concepts, O'Reilly, 2017.
3. G. Cowan, Statistical data analysis, Clarendon Press Oxford, 1998.

Literatura uzupełniająca

1.    P. J. Bickel, K. A. Doksum, Mathematical Statistics, Holden-Day, Inc. San Francisco, 1977.

2.    G. James, D. Witten, T. Hastie, R. Tibshirani, An Introduction to Statistical Learning: with Applications in R, Springer 2013

Uwagi

Zmodyfikowane przez dr Dorota Głazowska (ostatnia modyfikacja: 18-04-2024 13:08)