Non-Parametric Testing

Module Description

Module Description Conclude your journey through statistical analysis with our Non-Parametric Tests module, an essential part of the Statistics & Quantitative Analysis with SPSS course. This module focuses on non-parametric tests, robust statistical methods used when data do not meet the assumptions of parametric tests.

Key Topics Covered:

1. Introduction to Non-Parametric Tests: Understand the principles and applications of non-parametric tests. Learn why and when to use these tests in your data analysis, especially when dealing with non-normally distributed data or ordinal data.
2. Types of Non-Parametric Tests: Explore various non-parametric tests, such as the Mann-Whitney U test, Wilcoxon signed-rank test, Kruskal-Wallis test, and Spearman’s rank correlation. Gain insights into their specific applications and advantages.
3. Conducting Non-Parametric Tests in SPSS: Master the practical aspects of performing non-parametric tests using SPSS. Learn to set up, execute, and interpret these tests within the software, ensuring your analyses are accurate and reliable.
4. Interpreting Non-Parametric Test Results: Develop the skills to interpret the outputs of non-parametric tests. Understand how to read and report results, including significance levels and effect sizes, to draw meaningful conclusions from your data.
5. Applications and Case Studies: Discover real-world applications of non-parametric tests through case studies. See how these tests are used in various fields such as healthcare, social sciences, and market research to handle data that do not meet parametric assumptions.

By the end of this module, you will be proficient in using non-parametric tests for statistical analysis, enabling you to analyse a wider range of data types and distributions. Whether you are a student, researcher, or professional, these skills are invaluable for any quantitative analysis work.

Entry Requirements

• O’Level in Mathematics.
• Professional English.

Target Audience

The Statistics & Quantitative Analysis with SPSS course is meticulously designed to cater to a diverse range of learners, ensuring that everyone from beginners to seasoned professionals can benefit from its comprehensive curriculum. This course is ideal for:

1. Students and Academics:

• Undergraduate and graduate students looking to strengthen their statistical analysis skills.
• Researchers and academics who need a robust understanding of SPSS for their data-driven projects and publications.

2. Business and Data Analysts:

• Professionals working in business intelligence, data analytics, and market research who seek to enhance their quantitative analysis capabilities.
• Analysts who require advanced skills in SPSS to interpret complex data and support strategic decision-making.

3. Healthcare and Social Science Professionals:

• Healthcare researchers, epidemiologists, and public health professionals who need to analyze statistical data accurately.
• Social scientists and psychologists looking to apply quantitative methods to their research and practice.

4. Government and Non-Profit Sector Workers:

• Employees in government agencies and non-profit organizations who rely on statistical data to inform policy decisions and program evaluations.
• Public administrators and policy analysts who need to interpret data and present findings effectively.

5. Anyone Interested in Data Science and Statistics:

• Individuals with a keen interest in data science, statistics, and quantitative research who want to develop a solid foundation in SPSS.
• Lifelong learners aiming to acquire new skills to advance their careers or transition into data-focused roles.

Career Paths

• This course offers valuable insights and practical knowledge to help you succeed in Statistics & Quantitative Analysis with SPSS and become proficient in one of the most widely-used statistical software packages in the industry.

How you’ll be assessed

• This course does not include any formal assessments or evaluations.