The aim of studying and bibliography

The main aim of study: The aim of the module is to present the basics of data analysis: descriptive statistics, elements of probability calculus and mathematical statistics, and familiarizing students with the methodology of elaborating the results of statistical surveys and statistical inference.

The general information about the module: The module is implemented in the fourth semester. It consists of 30 hours of lectures and 15 hours of tutorials, 15 hours of laboratory and 15 hours of project.

Bibliography required to complete the module

Bibliography used during lectures

1	J. Koronacki, J. Mielniczuk	Statystyka dla studentów kierunków technicznych i przyrodniczych	WNT, Warszawa.	2010
2	M. Sobczyk	Statystyka	PWN, Warszawa.	2005
3	M. Startek	Podstawy rachunku prawdopodobieństwa z elementami statystyki matematycznej	Oficyna Wydawnicz PRz.	2005

Bibliography used during classes/laboratories/others

1	1. J. Koronacki, J. Mielniczuk	Statystyka dla studentów kierunków technicznych i przyrodniczych	WNT, Warszawa.	2010
2	M. Startek	Podstawy rachunku prawdopodobieństwa z elementami statystyki matematycznej	Oficyna Wydawnicza PRz.	2005

Bibliography to self-study

1

A. i E. Plucińscy

Probabilistyka

WNT, Warszawa.

2003

Basic requirements in category knowledge/skills/social competences

Formal requirements: Passing the module Probability Calculus. The student satisfies the formal requirements set out in the study regulations.

Basic requirements in category knowledge: Knowledge of the basics of probability and mathematical analysis.

Basic requirements in category skills: Knowledge of the R environment at the basic level.

Basic requirements in category social competences: Willingness to take objectively justified mathematical operations in order to solve the task .

Module outcomes

MEK	The student who completed the module	Types of classes / teaching methods leading to achieving a given outcome of teaching	Methods of verifying every mentioned outcome of teaching	Relationships with KEK	Relationships with PRK
01	He knows and can use statistical characteristics of the population and their sample equivalents.	lecture, exercises	written test, written exam	K_W01+ K_U02+	P6S_UW P6S_WG
02	knows and employs distributions used in statistical practice.	lecture, exercises	written test, written exam	K_W01+ K_U02+	P6S_UW P6S_WG
03	can make simple statistical inferences.	lecture, exercises, project	.written test, written exam, project presentation	K_W01+ K_U02+ K_U05+ K_U18+ K_K01+ K_K05+	P6S_KK P6S_KO P6S_UW P6S_WG
04	can make simple statistical inferences using statistical packages in R.	lecture, laboratory, project	observation,, project presentation	K_W02+ K_U03+ K_U07+ K_K01+ K_K05+	P6S_KK P6S_KO P6S_UW P6S_WG

Attention: Depending on the epidemic situation, verification of the achieved learning outcomes specified in the study program, in particular credits and examinations at the end of specific classes, can be implemented remotely (real-time meetings).

The syllabus of the module

Sem.	TK	The content	realized in	MEK
4	TK01	Descriptive statistics. Population, sample, feature, frequency distribution, histogram, empirical distribution, empirical cumulative distribution. Graphic presentation of data. Basic parameters of the description of the population and the sample. Distributions of statistics from the sample.	W1-W8, C1-C4, L1-L4	MEK01 MEK04
4	TK02	Probability distributions used in statistics: normal, uniform, Student t, chi-squared, Poisson, exponential. Standardization of a random variable.	W9-W16, C5-C8, L5-L8	MEK02 MEK04
4	TK03	Estimation. Estimators, their types and properties. Point and interval estimation. Confidence intervals.	W17-W22, C9-C10, L9-L10, P1-P5	MEK01 MEK03 MEK04
4	TK04	Statistical hypothesis testing. Types of hypotheses: simple, complex, parametrical and non-parametrical. Errors of the first and second types. Statistical test, test significance level, test power. Tests for basic distribution parameters: expected value, variance, fraction. Chi-square and Kolmogorov compatibility test. Tests for randomness testing of the sample. Tests for comparing two populations. Study of the interrelations of traits in the population. Correlation, correlation coefficient. Regression. Statistical experiments.	W23-W30, C11-C15, L11-L15, P6-P15	MEK03 MEK04

The student's effort

The type of classes	The work before classes	The participation in classes	The work after classes
Lecture (sem. 4)	The preparation for a test: 5.00 hours/sem.	contact hours: 30.00 hours/sem.	complementing/reading through notes: 4.00 hours/sem. Studying the recommended bibliography: 4.00 hours/sem.
Class (sem. 4)	The preparation for a Class: 5.00 hours/sem. The preparation for a test: 5.00 hours/sem.	contact hours: 15.00 hours/sem.	Finishing/Studying tasks: 2.00 hours/sem.
Laboratory (sem. 4)	The preparation for a Laboratory: 8.00 hours/sem.	contact hours: 15.00 hours/sem.	Finishing/Making the report: 10.00 hours/sem.
Project/Seminar (sem. 4)	The preparation for projects/seminars: 10.00 hours/sem.	contact hours: 15.00 hours/sem..	Doing the project/report/ Keeping records: 10.00 hours/sem. The preparation for the presentation: 2.00 hours/sem.
Advice (sem. 4)	The preparation for Advice: 1.00 hours/sem.	The participation in Advice: 2.00 hours/sem.
Exam (sem. 4)	The preparation for an Exam: 5.00 hours/sem.	The written exam: 2.00 hours/sem.

The way of giving the component module grades and the final grade

The type of classes	The way of giving the final grade
Lecture	Written test. Solve the obvious exercisses gives the grade 3.0. Solve extra exercisses gives better note.
Class	Written test. The obvious exercises and the extra exercises. The obvious exercises must be solved. Only the obvious exercises - 3.0.
Laboratory	credit by observation of laboratory tasks
Project/Seminar	presentation and passing the prepared project
The final grade	The final grade is the average (positive) grade of tests, a project and a written exam.

Sample problems

Required during the exam/when receiving the credit
(-)

Realized during classes/laboratories/projects
(-)

Others
(-)

Can a student use any teaching aids during the exam/when receiving the credit : yes

Available materials : Simple statistical tables.

The contents of the module are associated with the research profile: no