STATISTICS AND DATA ANALYSIS

Course Aims

and Objectives:

The objective of this course is to introduce the concepts and techniques of clustering and multivariate and exploratory data analysis. This course also offers an opportunity to perform data analysis by using SPSS

Course Content:

The course aims at providing graduate students with an understanding of statistics and data analysis for managers. The course objective is to teach the methods to be followed after collecting data for a problem to be solved. The quality of research decisions depends to a great extent on the information available to decision makers. Data analysis transforms raw data into information which can help in this decision making process. It will provide prospective managers with an understanding of marketing research findings using SPSS for Windows

Course Learning Outcomes (CLOs):

(Knowledge, skills and competencies expected to be achieved at the end of the course)

On the successful completion of the course, students will be able to: 

1. Understand the fundamental concepts and principles of statistics and data analysis relevant to managerial and marketing research.

2. Describe and summarize quantitative data using appropriate tables, graphs, charts, measures of central tendency, variation, and dispersion.

3. Apply appropriate statistical techniques to analyze relationships and differences between variables, including correlation, t-tests, chi-square tests, and non-parametric tests.

4. Explain and apply the principles of statistical inference, significance testing, confidence intervals, and hypothesis testing in managerial decision-making.

5. Conduct and interpret analysis of variance (ANOVA), including one-way, repeated-measures, two-way, and mixed-design ANOVA.

6. Apply advanced multivariate and exploratory data analysis techniques, including partial correlation, factor analysis, reliability analysis, and multiple regression.

7. Analyze categorical and nominal data using advanced techniques such as log-linear analysis and multinomial logistic regression.

8. Use SPSS Statistics to enter, manage, analyze, and interpret data using appropriate statistical procedures.

9. Interpret statistical results and translate data analysis findings into meaningful information for managerial and marketing research decisions.

10.  Evaluate the quality and relevance of statistical evidence and communicate data analysis findings clearly and appropriately in a research or business context.

Responsible Use of AI

Students are encouraged to use artificial intelligence responsibly and in ways that support their learning. They are expected to familiarize themselves with, and comply with, the University’s Regulation on the Responsible Use of AI and the AI-use categories provided at the end of this course outline.