The aim of the course is to introduce the fundamental concepts of statistics to students with no prior background in the subject. By the end of the course, students will be able to identify and distinguish between different types of data and select appropriate methods of analysis in a variety of contexts. They will also be able to analyse real-world data, from graphical representations to measures of central tendency and variability.
Basic mathematical knowledge.
The course combines lectures with the discussion of practical cases and examples from social research. Classroom exercises will be conducted with the active participation of students.
The examination is structured as follows:
The examination comprises a variable number of theoretical and practical questions, including multiple-choice and open-ended items. Students must bring a ruler and a calculator; smartphones may not be used during the examination. Each exercise is allocated a specific number of points, usually between one and three, for a maximum total of 30 points. The final grade will be expressed on a 30-point scale.
To achieve the course objectives, students will first be introduced to the main concepts of social research methodology, including the nature and aims of quantitative research, its principal tools, and data collection methods.
The course will then cover the fundamentals of descriptive statistics, including frequency distributions, percentages, cumulative relative frequencies, measures of central tendency (mode, median, and arithmetic mean), percentiles, and measures of variability (range and variance). Particular attention will also be given to the graphical presentation of statistical data.
Finally, students will be introduced to the basic principles of statistical inference, including sampling and sample statistics. Topics will include the sample mean, the mean squared deviation from the sample mean, interval estimation, random intervals, confidence levels, and confidence intervals for a population mean in both the known-variance and unknown-variance cases.
1) There is no distinction in the course programme between attending and non-attending students.
2) Following the written assessment, the instructor may require an additional oral examination, where deemed necessary, to verify the achievement of the course learning outcomes and to ensure the accurate assessment of student performance.
