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Representative Methods - course description

General information
Course name Representative Methods
Course ID 11.1-WK-DEED-RM-S22
Faculty Faculty of Mathematics, Computer Science and Econometrics
Field of study Data Engineering
Education profile academic
Level of studies Second-cycle studies leading to MS degree
Beginning semester summer term 2022/2023
Course information
Semester 1
ECTS credits to win 7
Course type obligatory
Teaching language english
Author of syllabus
  • dr hab. Stefan Zontek, prof. UZ
Classes forms
The class form Hours per semester (full-time) Hours per week (full-time) Hours per semester (part-time) Hours per week (part-time) Form of assignment
Lecture 30 2 - - Exam
Laboratory 30 2 - - Credit with grade

Aim of the course

To familiarize the student with basic sampling schemes and data analysis methods used in finite population studies.

Prerequisites

Completed subjects: introduction to probability theory, statistical data analysis.

Scope

Lecture

1.       General population – parameters of a general population, complex survey, sample, representative sample. (2 hours)

2.       Sampling schemes; estimators of the mean and its properties; comparison of efficiency of sampling schemes: 

-          simple random sampling, depended random sampling, (4 hours)

-          stratified sampling, (6 hours)

-          cluster sampling, (4 hours)

-          systematic sampling, (4 hours)

-          two stage sampling. (6 hours)

3.       Ratio and regressive estimates. (2 hours)

4.       Repetition - students refers and are gradated. (2 hours)

Laboratory

1. Introductory and refresher classes on the software used. (2 hours.)

2. Based on book examples, comparative analysis of the effectiveness of estimators of the average value of a feature in the general population:

- sampling without replacement and sampling with replacement, (2 hours)
- stratified sampling (impact of division into strata), (2 hours)
- sampling without replacement and stratified sampling (proportional scheme), (2 hours)
- stratified sampling (proportional design) vs. stratified sampling (optimal design), (2 hours)
- cluster sampling (influence of division into clusters), (2 hours)
- cluster sampling vs. sampling without replacement, 2 hours)
- systematic sampling and sampling without replacement, 2 hours)
-systematic sampling vs. stratified sampling, (2 hours)
- ratio estimator and sample mean (sampling without replacement), (2 hours)
- linear regression estimator and sample mean (sampling without replacement, 2 hours)
- ratio estimator and stratified mean estimator (stratified sampling), (2 hours)
- linear regression estimator and stratified estimator (stratified sampling). (2 hours.)
3. Colloquium. (2x2 hours)

Teaching methods

Traditional lecture (chalk and blackboard only for the most important formulations, arguments, transformations of formulas), During the laboratory, visual verification of the correctness of the selection of procedures run at all computer workstations. Random review questions regarding the interpretation of the results of the procedures used.

Learning outcomes and methods of theirs verification

Outcome description Outcome symbols Methods of verification The class form

Assignment conditions

1. In the middle of the semester and at the end of the laboratory, there will be tests with tasks of varying difficulty, allowing for the assessment of whether the student has achieved the learning outcomes to a minimum extent.

2. Written examination (1st term) with questions relating directly to concepts, statements and questions checking the understanding of the acquired knowledge. Make-up exam in oral form, type of questions as above.

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

Recommended reading

1.  W.G. Cochran. Sampling techniques (Third ed.). Wiley, 1977.

2. S. K. Thompson, Sampling, John Wiley & Sons 2012, Print ISBN:9780470402313 |Online ISBN:9781118162934 |DOI:10.1002/9781118162934.

Further reading

1. S. Levy, S. Lemeshow, Sampling of Populations: methods and applictions, New York, John Wiley & Sons 1991. 

Notes


Modified by dr hab. Stefan Zontek, prof. UZ (last modification: 06-02-2024 13:48)