• Analyze a research topic - in order to identify available quantifiable information and formulate questions that can be answered by processing suitably collected data.
• Use graphical and numerical methods for exploring and summarizing data on a single categorical or quantitative variable.
• Describe basic probability and how probability helps us understand randomness, and explain the concept of a sampling distribution and how it relates to inference methods.
• Choose and justify appropriate descriptive and inferential methods for examining and analyzing data and drawing conclusions.
• Analyze of the association between variables, categorical, continuous and both, using contingency tables, correlation, regressions analysis, and analysis of variance.
• Communicate the conclusions of statistical analysis clearly and effectively, i.e interpret the numerical results in terms of the original research topic.

Statistics is both a science in itself and a technology with applications in almost every other branch of science. The course emphasizes conceptual understanding rather than just instrumental usage of statistical procedures. The focus is on the interpretation and understanding of basic statistical methods as applied in social sciences, business economy and political economy.
The curriculum includes:
· Descriptive statistics, both numerical and graphical.
· The basic laws of probability, and the most important probability distributions.
· Statistical inference; confidence intervals and significance tests about hypotheses.
· Analysis of categorical variables using contingency tables.
· Regression analysis; simple, multiple and logistic.
· One-way and two-way analysis of variance.