These lecture notes were created with the intention of giving undergraduate and graduate students, particularly those studying social sciences, economics, and financial services, an approachable but technically sound introduction to the logic of systematic analyses of statistical data. They could also act as a broad guide for using quantitative-empirical research techniques.
The notes cover four major topics in an effort to promote the adoption of an interdisciplinary viewpoint on quantitative issues that arise in practice: I descriptive statistical processing of raw data; (ii) elementary probability theory; (iii) operationalization of one-dimensional latent statistical variables using Likert's widely used scaling approach; and (iv) null hypothesis significance testing within the frequentist approach to probability theory.
It is emphasized that effect sizes are important when drawing conclusions. These lecture notes are properly hyperlinked, giving you a quick link to both authentic scientific publications and fascinating biographical details. Additionally, they provide a long number of commands for the software programs R, SPSS, EXCEL, and OpenOffice that can be used to execute data analysis and statistical operations. Strongly advised is rapid participation in actual data analysis procedures.