Data Analysis in Excel
Course code
RAS6016.YK
old course code
Course title in Estonian
Andmete analüüs Excelis
Course title in English
Data Analysis in Excel
ECTS credits
4.0
Assessment form
Examination
lecturer of 2023/2024 Spring semester
Jaanika Meigas (language of instruction:Estonian)
lecturer of 2024/2025 Autumn semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
Course aims
The objective of the course is to enable development of practical knowledge and skills necessary for conducting quantitative analysis and presentation of results in widely used programme MS Excel.
Brief description of the course
To achieve this aim, students’ knowledge of statistical analysis, practical application of statistical methodology and graphical presentation of results are developed. Course is taught in practical classes using MS Excel programme. Theoretical aspects of data analysis are addressed briefly because prerequisite to participation in the course is knowledge of basic methods (incl. crosstabs, comparison of means, tests of statistical significance, different association coefficients, linear regression, correlation).
Following topics will be introduced: probability distributions examining difference between one sample and a population; relationships between variables; and groups on one or more variables. To promote students’ understanding of these topics, they have to complete three home assignments based on the dataset provided by the lecturer.
Following topics will be introduced: probability distributions examining difference between one sample and a population; relationships between variables; and groups on one or more variables. To promote students’ understanding of these topics, they have to complete three home assignments based on the dataset provided by the lecturer.
Learning outcomes in the course
Upon completing the course the student:
- has a basic understanding of the main quantitative data analysis methods;
- knows how to use most common tool of MS Excel for data analysis;
- has an understanding of how statistical inferences are reached and can present the results of the home assignments;
- has reached the level in statistical thinking where (s)he can reason using statistical terminology and apply the knowledge and skills to new research questions (problems).
- has a basic understanding of the main quantitative data analysis methods;
- knows how to use most common tool of MS Excel for data analysis;
- has an understanding of how statistical inferences are reached and can present the results of the home assignments;
- has reached the level in statistical thinking where (s)he can reason using statistical terminology and apply the knowledge and skills to new research questions (problems).
Teacher
Määramata
Prerequisite course 1
Prerequisite course 2
Study programmes containing that course