Statistics for naturalists
General data
Course ID: | 1100-2BO11 |
Erasmus code / ISCED: |
13.2
|
Course title: | Statistics for naturalists |
Name in Polish: | Statystyka dla przyrodników |
Organizational unit: | Faculty of Physics |
Course groups: |
ESOO - European programme in ophthalmic optics and optometry; 3rd year courses |
ECTS credit allocation (and other scores): |
4.00
|
Language: | Polish |
Prerequisites (description): | Student’s necessary mathematical skills required are limited to the fluent integral and differential calculus. |
Mode: | Classroom |
Short description: |
Lecture covers the subject of probability theory and classical mathematical statistics on the elemenary level and covers fundementals of probability calculus, probability distributions and mathematical statistics to the limited degree. |
Full description: |
1. HISTOGRAMS AND BASIC DISTRIBUTIONS 2. DISCRIPTIVE STATISTICS AND PARAMETERS OF RANDOM VARIABLE 3. PARAMETRIC ESTIMATION 4. HYPOTHESIS TESTS 5. CORRELATION AND REGRESSION |
Bibliography: |
Suggested main book: • J. Koronacki i J. Mielniczuk, Statystyka dla studentów kierunków technicznych i przyrodniczych, Wydawnictwo Naukowo-Techniczne, Warszawa, 2001 Additional books, light version: • J. Jóźwiak, J. Podgórski, Statystyka od podstaw, PWE Polskie Wydawnictwo Ekonomiczne, 2012; wersja uproszczona: J. Podgórski, Statystyka dla studiów licencjackich, PWE 2010 •J. Taylor, Wstęp do analizy błędu pomiarowego, Wydawnictwa Naukowe PWN 2012. Additional books, for the ambitious: • A. Plucińska i E. Pluciński, Probabilistyka, Wydawnictwo Naukowo-Techniczne, 2000 • R. Nowak, Statystyka dla fizyków, Wydawnictwa Naukowe PWN, 2002 (+ ćwiczenia, 2002) Problems (and solutions): • W. Krysicki i inni, Rachunek prawdopodobieństwa i statystyka matematyczna w zadaniach, część I i II, Wydawnictwo Naukowe PWN, Warszawa, 1995 Additional reading for fun: • A. Łomnicki, Wprowadzenie do statystyki dla przyrodników, Wydawnictwo Naukowe PWN, Warszawa, 1999 • P. Durka, Wstęp do współczesnej statystyki , Wydawnictwo Adamantan, 2003. |
Learning outcomes: |
Knowledge Student knows basic methods of statistical analyses of data Student understands limitations of these methods Competence Student identifies problems of data analyses in terms of statistical mathematics Student is able to implement basic methods of statistical analyses of data in simple cases Student knows how to interpret results of such analyses |
Assessment methods and assessment criteria: |
• Participation in lecture courses is mandatory, but absences are not penalized (but there will be no possibliity to write a test) • Participation in practicals is mandatory. In maximum 2 absences without leave are allowed • There will be homework given to students. It is not obligatory • There will be written short tests during lectures. • Course ends with written and oral examination |
Classes in period "Winter semester 2023/24" (past)
Time span: | 2023-10-01 - 2024-01-28 |
Navigate to timetable
MO TU WYK
CW
W TH FR |
Type of class: |
Classes, 30 hours, 30 places
Lecture, 15 hours, 30 places
|
|
Coordinators: | Marcin Konecki | |
Group instructors: | Marcin Konecki, Karol Łukanowski | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
Examination
Lecture - Examination |
Classes in period "Winter semester 2024/25" (future)
Time span: | 2024-10-01 - 2025-01-26 |
Navigate to timetable
MO TU WYK
CW
W TH FR |
Type of class: |
Classes, 30 hours, 30 places
Lecture, 15 hours, 30 places
|
|
Coordinators: | Marcin Konecki | |
Group instructors: | Marcin Konecki | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
Examination
Lecture - Examination |
Copyright by University of Warsaw.