Introduction to statistical reasoning with basics of R – for Humanities students

elective courses
general courses

Students should have basic computer skills. Students will be expected to work on their own laptops.

Blended learning

The course is designed to help Humanities students better understand what they are really doing when using statistical methods and how they can interpret the results. Emphasis will be given to proper sample selection and evaluation and on a critical approach to statistical reasoning. The effectiveness of such an approach is the use of methods that are simple but that are fully understood by the author.

The use of the popular R statistical software, which is available free of charge, will allow classes to be conducted without the need to resort to complex mathematical formulae, which are usually an insurmountable barrier for most students. It will also provide them with a good starting point for their own explorations because R statistical software facilitates making analyses with a very broad range of complexity.

Humanities students, in general, leave the University unprepared for a critical approach to learning from academic publications that use even the simplest elements of statistics. As a result, in their future work they tend to avoid statistics completely to the detriment of their analyses. If some graduates are able to make use of appropriate statistical tests, in the majority of cases it simply boils down to the mechanical application of solutions taught during lectures. By giving students the opportunity to fully understand the basic methods, we are also giving them the tools to interpret results correctly.

Students attending the course will learn:

• what statistics is and how it can help them;

• what a statistical sample is, its proper selection, and how to evaluate its usefulness in the planned analyses;

• how to critically read publications that use statistical reasoning;

• how to test and interpret results consciously.

They will gain technical skills that allow them to:

• install and use basic features of R software;

• transform data before the actual analysis;

• perform calculations;

• create basic graphs.

This course is designed to introduce students to the theoretical basis and practical applications of the subjects covered. These topics will then be used to solve problems put to the whole group. This, in turn, will prepare the student to independently solve his homework. Final grades will depend mainly on the results of homework and the student’s ability to explain particular solutions.

Active participation in the lectures and honest self-study at home will suffice to fully benefit from the knowledge the course provides.

The course consists of 30 hours of organized teaching, 40 hours of unassisted work by the student (problem solving), and 5 hours of preparation for the exam and the exam itself. Therefore, the estimated total number of hours a student has to devote to achieve the learning outcomes intended by the course is 75 hours.

Upon completion of the course, the student will be able to:

• explain what statistics is and the problems it can help solve;

• explain what a statistical sample is;

• evaluate a statistical sample in terms of its usefulness in further analyses;

• make an appropriate selection of a sample to answer the question posed;

• recognize basic tests commonly used in publications (or will be able to identify their type correctly);

• say if the tests were used correctly and why;

• say if the statistical reasoning was conducted correctly;

• independently select statistical tests appropriate to the questions to be solved and the sample;

• analyse and interpret the results obtained;

• independently install R software;

• import and transform data using R software;

• perform an analysis using R;

• create basic graphs.

During the course students will be assigned work to be solved at home. The evaluation of their progress will be based on the way the problems are solved and the results obtained. Timely submission of the solutions and the student’s activity in class will also be taken into account. In addition, the student’s overall understanding of the subject will be assessed during an individual oral exam.