Veidlapa Nr. M-3 (8)

Course Description Status: Approved

Course Description Version: 25/26.P.1.00

Description Period: 2025./26 academic year pavasara semestris

Study Course Accepted: -

Study Course Description

Mathematical Statistics I

Main Study Course Information

Course Code
SL_008
Branch of Science
Mathematics
ECTS
3.00
Target Audience
Public Health
LQF
Level 6
Study Type And Form
Full-Time

Study Course Implementer

Course Supervisor
Ilze Balode
Structure Unit Manager
Andrejs Ivanovs
Structural Unit
Statistics Unit
Contacts

Kapseļu Street 23, 2nd floor, Riga, +371 67060897, statistika@rsu.lv, www.rsu.lv/statlab

About Study Course

Objective

To get basic knowledge about descriptive statistics, hypothesis testing and IBM SPSS options in data processing.

Preliminary Knowledge

Secondary school background in mathematics and informatics. Preferably informatics lectures should be taken during first year.

Learning Outcomes

Knowledge

1.As a result of successful acquisition of the course, students: • will name and explain the basis for the most important descriptive statistics and hypothesis testing in Latvian and English. • recognise basic situations in the processing of descriptive statistics and hypotheses at basic level.

Skills

1.As a result of successful acquisition of the course, students will be able to: • prepare data for processing in the IBM SPSS environment. • select data based on different criteria in the SPSS environment. • take decisions on the calculation of appropriate descriptive statistics, the design of charts and the verification of hypotheses at basic level. • calculate descriptive statistics, design charts and tables. • perform hypothesis testing at the base level in IBM SPSS environments. • interpret data processing results according to speciality.

Competences

1.As a result of successful learning of the course, students will be able to correctly interpret static indicators by reading scientific literature in a specialty.

Assessment

Individual work

Title
% from total grade
Grade
1.

Individual work
-
-
Independent Learning: Individual working with literature – preparing for a lesson, clarifying uncertain terms, performing home tasks.

Examination

Title
% from total grade
Grade
1.

Examination
-
10 points

Active participation in practice. Own-initiative work on the processing of data at the basic level of the testing of descriptive statistics and hypotheses, which requires calculation and interpretation of results. For each delayed lesson, a summary of the subject using the given literature (min one A4 page). At the end of the study course, a written examination: computerised test with 30 questions on representative name sets and decision-making in data processing – 50%, practical task resolution in the IBM SPSS environment – 30%, independent work -20%.

Study Course Theme Plan

FULL-TIME
Part 1

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Introduction to statistics, the role of statistics in research process. Statistical calculation programs (calculators, programs). Introduction to SPSS.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Data type. Variables and levels of measurement.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Tables and diagrams in IBM SPSS and Excel.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Descriptive statistics in IBM SPSS and Excel: frequency calculation, central tendency estimators, variability estimators.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Descriptive statistics in IBM SPSS and Excel: frequency calculation, central tendency estimators, variability estimators.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Descriptive statistics in IBM SPSS and Excel: frequency calculation, central tendency estimators, variability estimators.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Elements of probability theory. Theoretical data distributions. Normal distribution. Standard normal distribution.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Confidence intervals, generatng in SPSS and CI calculators.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Hypothesis testing. Two quantitative variables (2 samples). Parametric and nonparametric methods.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Hypothesis testing. Two quantitative variables (2 samples). Parametric and nonparametric methods.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Hypothesis testing. Differences between three or more groups quantitative variables. Parametric and nonparametric methods.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Hypothesis testing. Differences between three or more groups quantitative variables. Parametric and nonparametric methods.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Hypothesis testing. Qualitative data. 2 x 2 crosstables.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Hypothesis testing. Qualitative data. R x C crosstable.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Course summary. Independent work.

  1. Class/Seminar

Modality
Location
Contact hours
On site
Computer room
2

Topics

Independent work presentation.
Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam (Written)

Bibliography

Required Reading

1.

Teibe U. Bioloģiskā statistika. LU, 2007. (akceptējams izdevums)

Additional Reading

1.

A. Field. Discovering Statistics using IBM SPSS Statistics. 5th edition, 2018.Suitable for English stream

2.

Petrie A. & Sabin Caroline. Medical Statistics at a Glance. Willey Blackwell, 2020.Suitable for English stream