COURSE TITLE: Statistical Data Analysis using SPSS

Course Code: RMEL 203
Credit Value: 3 Credits

Contact Hours

• Lectures: 2 hours/week

• Practical / Computer Laboratory: 2 hours/week

Duration: 15 Weeks (One Semester)
Prerequisite: RMEL 202 – Digital Data Collection and Management

1. Course Description

This course develops students' competencies in statistical data analysis using IBM SPSS Statistics for research, monitoring and evaluation, business, public administration, journalism, environmental science, health, and other applied disciplines. Students learn to manage datasets, perform descriptive and inferential statistical analyses, interpret statistical outputs, and communicate findings effectively for evidence-based decision-making.

The course integrates statistical concepts with practical application through extensive hands-on laboratory sessions using SPSS. Students apply statistical techniques to real-world datasets generated through research and monitoring activities, emphasising data quality, analytical accuracy, interpretation, visualisation, and professional reporting.

Practical laboratory sessions guide students through the complete analytical workflow, including data preparation, descriptive analysis, hypothesis testing, correlation, regression, analysis of variance, non-parametric techniques, and report generation. Emphasis is placed on selecting appropriate statistical procedures, interpreting outputs correctly, and presenting results according to accepted academic and professional standards.

The course prepares students for professional responsibilities involving research, programme evaluation, business analytics, market research, policy analysis, and organisational performance measurement.

2. Course Objectives

By the end of this course, students should be able to:

1. Explain fundamental statistical concepts used in applied research and programme evaluation.

2. Import, manage, clean, and prepare datasets using SPSS.

3. Perform descriptive statistical analyses and summarise data effectively.

4. Conduct appropriate inferential statistical analyses using SPSS.

5. Interpret statistical outputs accurately and make evidence-based conclusions.

6. Produce tables, charts, and graphical summaries for professional reporting.

7. Apply ethical standards in statistical analysis and data interpretation.

8. Prepare professional statistical reports suitable for research and organisational decision-making.

3. Learning Outcomes

Upon successful completion, students will be able to:

• Organise and prepare datasets for statistical analysis.

• Apply descriptive statistics to summarise quantitative data.

• Select and perform appropriate inferential statistical procedures.

• Test research hypotheses using SPSS.

• Interpret SPSS outputs confidently and accurately.

• Produce professional statistical tables and data visualisations.

• Present statistical findings in research and evaluation reports.

• Demonstrate competence in using SPSS for applied data analysis.