Statistical Methods and Applications

The course deals mainly with descriptive statistics. In the course lectures, reference is made to the introductory concepts of types of statistical data and data collection methods , basic characteristics of numerical data, introduction and understanding of probabilities, the normal distribution and understanding of sampling, hypothesis testing, as well as, correlations and simple linear regression.

The aim of the course is to understand the basic statistical concepts and methods of descriptive statistics. Furthermore, it scopes to develop a statistical/ way of thinking and analyzing quantitative and qualitative data with an emphasis on familiarity with modern methods and tools for managing and analyzing this data.

The laboratory part of the course includes the following sections:

• Statistical analysis, graph creation, data presentation.
• Analysis of survey data from Google-type platforms.
• Learning SPSS.
• Data entry.
• Descriptive statistics.
• Description of variables.
• Inductive statistics.
• x2 test.
• t-test.
• One way Anova.
• Simple linear regression reliability analysis.

Upon successful completion of the course, students will:

• Understand basic principles of statistical science.
• Learn the required SPSS functions.
• Be able to analyze statistical data using statistical packages, extracting reliable conclusions for future research.