Statistical analysis in research Field of study: Computer Science
Programme code: W4-N2IN19.2020

Module name: Statistical analysis in research
Module code: W4-IN-N2-20-1-ASwPB
Programme code: W4-N2IN19.2020
Semester:
  • winter semester 2021/2022
  • summer semester 2020/2021
Language of instruction: Polish
Form of verification: course work
ECTS credits: 2
Description:
The purpose of the module is to present the basics of data analysis including: descriptive statistics, graphic methods for the presentation of qualitative and quantitative data, elements of statistical inference. Content: 1. Descriptive statistics: average measures, measures of variability, dispersion, asymmetry, correlation analysis. 2. Graphic methods for the presentation of qualitative and quantitative data: histogram, frequency diagram, scatter plot, box plot. 3. Elements of statistical inference: concepts of the null and alternative hypothesis, significance level and p-value. Selection of test depending on the hypothesis and the data: Student's t test, Wilcoxon test, Friedman test, Kruskal-Wallis test, Fisher test, chi-square test.
Prerequisites:
(no information given)
Key reading:
1. D.S. Moore, G.P. McCabe, Introduction to the Practice of Statistics, W.H. Freeman & Co., 2000. 2. C. Heumann, M. Schomaker, Shalabh, Introduction to Statistics and Data Analysis, Springer, 2016
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
The student has knowledge about the average measures, the measures of variability, dispersion, asymmetry, correlation analysis and is able to use them. [M_001]
 K_W01 [1/5] K_W09 [1/5] K_U03 [1/5] K_U08 [1/5]
The student has knowledge about various methods of graphic presentation of qualitative and quantitative data. She\He can choose the appropriate graph for the data and create it. [M_002]
 K_W09 [1/5] K_U01 [1/5]
The student has knowledge about statistical inference. She/He is able to use selected statistical tests to confirm the significance of the hypotheses. She/He can choose the right test depending on the hypothesis and data. [M_003]
 K_W01 [1/5] K_W09 [1/5] K_U01 [1/5] K_U03 [1/5] K_U09 [1/5]
She/He can use the selected program to perform statistical analysis and to confirm the hypotheses. Based on the obtained experimental results, she/he can draw conclusions and confirm their statistical significance. [M_004]
 K_U01 [1/5] K_U03 [1/5] K_U07 [1/5] K_K04 [1/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Examination reports [W_001]
Preparation of written reports and their oral presentation at a specified time as a verification of acquired skills during problems' solving.
 M_001 M_002 M_003 M_004
Test [W_002]
Verification of knowledge and skills based on the analysis of tasks solutions during written test.
 M_001 M_002 M_003
Form of teaching Student's own work Assessment of the learning outcomes
Type Description (including teaching methods) Number of hours Description Number of hours
lecture [Z_001]
Lecture presenting concepts and facts from the scope of program contents which are listed in the module and illustrating them with numerous examples
 10
Self-study of lectures and literature
 20 Test [W_002]
laboratory classes [Z_002]
Laboratory, during which students perform exercises with the help of the teacher, which develop the skills listed in the set of learning outcomes of the module
 10
Self-improvement of skills listed in the set of learning outcomes of the module
 20 Examination reports [W_001] Test [W_002]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)