Learning Outcomes

The learning outcomes aim to prepare graduates who are capable of collecting, organizing, and analyzing data using statistical methods and specialized software, and of drawing conclusions that contribute to interpreting phenomena and supporting decision-making.

Knowledge and Understanding:

• Understand the fundamental concepts and principles of descriptive and inferential statistics.
• Identify the principles of probability, statistical distributions, and sampling.
• Understand methods of data collection, classification, tabulation, and presentation.
• Understand the concepts of correlation, regression, time series, and index numbers.
• Identify the fundamentals of informatics and the software used in statistical analysis.

Practical and Specialized Skills:

• Collect and organize data and verify its quality and suitability for analysis.
• Apply appropriate statistical methods to investigate various problems and phenomena.
• Use specialized statistical software, such as R and Minitab, to analyze data in accordance with course requirements.
• Prepare statistical tables, graphs, indicators, and analytical reports.
• Apply regression, forecasting, and time series analysis methods when appropriate to the nature of the data.
• Use computational tools to process data and perform statistical calculations.

Analytical and Professional Skills:

• Interpret statistical results and draw conclusions based on evidence and data.
• Select statistical methods appropriate to the nature of the problem and the available data.
• Identify errors and unusual values and assess their impact on the results.
• Present statistical findings clearly and accurately through reports, tables, and graphs.
• Adhere to research ethics, maintain data confidentiality, and ensure objectivity in analyzing results.