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Statistics and quantitative analysis in business

Course Description: This course introduces students to the fundamentals of statistics in business and its applications in managerial decision-making. The course begins with an overview of the importance of statistics in the business environment, followed by descriptive statistics techniques for summarizing and interpreting data. Students will learn to formulate and test hypotheses for single populations using statistical tests, analysis of variance, and correlation analysis. The course also integrates the use of statistical software for practical application of descriptive statistics, analysis of variance, correlation, simple linear regression, and multiple regression analysis, equipping students with the ability to analyze relationships between variables and draw evidence-based business conclusions.
Credit hours: 3
Objectives of the course :

Upon completion of this course, the student will be able to:
Explains the role and importance of statistics in business decision-making.
Analyzes and summarizes business data using appropriate statistical methods and tools.
Conduct hypothesis testing, analysis of variance, correlation, and regression analysis using statistical software.

Course outputs :

Knowledge and understanding:
Differentiates between descriptive statistics, hypothesis testing methods, and regression analysis techniques used in business statistics.
Discusses issues related to hypothesis formulation and testing using statistical tests, and analysis of variance
 Evaluates business problems using correlation analysis, simple linear regression, and multiple regression models.
2) Skills:
Processes quantitative and/or qualitative data and information using relevant digital tools and techniques in complex and advanced contexts related to statistics and quantitative analysis.
Clearly communicates information and advanced quantitative analysis outputs verbally.
3) Values, Responsibility, and Autonomy:
Applies professional and ethical standards when dealing with challenges in statistics and quantitative analysis.

Additional information:
  • Last updated: 2026-04-29

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