Course code InfT1002

Credit points 3

Informatics II

Total Hours in Course81

Number of hours for lectures16

Number of hours for seminars and practical classes16

Independent study hours49

Date of course confirmation04.09.2019

Responsible UnitInstitute of Computer Systems and Data Science

Course developer

author Mehānikas un dizaina institūts

Nataļja Vronska

Dr. paed.

Prior knowledge

InfT1001, Informatics I

Course abstract

The study course promotes development of knowledge and skills on MS Excel functions and embedded functions, creating charts, database different processing methods and forecast, is needed for course work and study project design and data analysis.

Learning outcomes and their assessment

Knowledge: understand MS Excel function, able to explain necessary data processing method for data analysis – lectures;
Skills: analyse and to evaluate relevant information important for practical activities, applying knowledge in order to perform the necessary works – practical works;
Competence: able to assess and use knowledge and skills on MS Excel function and data processing method for data analysis – practical works, test.

Course Content(Calendar)

1. Linear, growth series, date series, creating list for use. Simple calculations. Absolute, relative and mixed references. Most recently used function (Lecture – 1 h, practical work – 2 h).
2. Logical, math and statistical function. Creating embedded functions. Data validation (Lecture – 1 h, practical work – 2 h).
3. Newest technologies. 3D technologies (Lecture – 2 h).
4. Creating charts (Lecture – 1 h, practical work – 1 h).
5. 1st test about practical works theme (Lecture – 1 h).
6. Work with a database: new data, data sort, data filter (Lecture – 1 h, practical work – 1 h).
7. Conditional formatting. Subtotal function (Lecture – 1 h, practical work – 2 h).
8. Creating pivot tables and charts (Lecture – 2 h, practical work – 2 h).
9. Data consolidate. Goal Seek (Lecture – 1 h, practical work – 1 h).
10. Data advanced filter with criteria (Lecture – 2 h, practical work – 2 h).
11. Concluding statistics with analysis tool (Data Analysis) (Lecture – 2 h, practical work – 3 h).
12. 2nd test about practical works (Lecture – 1 h).

Requirements for awarding credit points

To get a test for students:
• 80% lecture attendance;
• successful assessment of the test works;
• all practical works must be passed.

Description of the organization and tasks of students’ independent work

Preparation for practical work and tests

Criteria for Evaluating Learning Outcomes

The assessment of the study course test mark depends on the cumulative evaluation of the test and test works.
The test mark is the arithmetic mean among a test and test works assessments.

Compulsory reading

• Arhipova I. Statistika ekonomikā un biznesā. Datorzinību centrs: 2006. 362 lpp.
• Izklājlapas. Rīga, LU. Pieejams:
• Excel for Windows apmācība. Pieejams:

Further reading

• Shelly G.B., Quasney J. Microsoft Office Excel 2010. Cengage Learning: 2011. 328 p.
• Walkenbach J. Microsoft Excel 2010 Formulas. Wiley Publishing: 2010. 814 p.


The mandatory course is intended for the second level professional higher education study program “Food technology” full and part time students.