Applied Statistics: From Concept To Practice
 

Applied Statistics: From Concepts to Practice and with applications in STATA, R, Python, SPSS & Excel
What you'll learn
Understand different types of survey questions and how to apply them
Understanding statistics location and dispersion
Estimating confidence intervals
Performing hypothesis testing
Understanding regression and correlation
Applying statistics in Python, R, SPSS, STATA and Excel
Interpret and Communicate Statistical Results
Solve Real-World Problems Using Statistical Reasoning
Requirements
No programming experience required
No Prior Statistics Knowledge Required
Learners should be comfortable with high school-level algebra and arithmetic (e.g., percentages, averages, solving simple equations).
While no prior experience is needed, students should be open to learning how to use at least one of the following: Excel, R, SPSS, Python and STATA
Access to Statistical Software
Description
Applied Statistics: From Concepts to Practice and with applications in STATA, R, Python, SPSS & Excel is a comprehensive, beginner-to-intermediate level course designed to equip learners with both the theoretical foundation and practical skills to apply statistical methods across a range of disciplines. Whether you're a student, researcher, or professional, this all-in-one programme will guide you step by step through the full cycle of data analysis, from designing surveys to interpreting regression results, using the most widely used tools in academia and industry. The course is structured into 10 logically sequenced modules covering topics such as descriptive statistics, questionnaire design, survey methodology, probability and probability distributions, confidence intervals, hypothesis testing, chi-square and F-tests, and regression and correlation analysis. Each topic is not only explained clearly through intuitive theory, but also demonstrated with hands-on exercises using STATA, R, Python, SPSS, and Excel. No prior knowledge of statistics or coding is required. We start from the basics and gradually build your expertise. By the end of this course, you'll be confident in conducting your own statistical analyses, visualising data effectively, making data-driven decisions, and interpreting results in both academic and applied contexts. Whether you're preparing for research, a thesis, or a data-driven job, this course will provide the tools and confidence to succeed.
Who this course is for
University students and graduates in economics, business, social sciences, psychology, public health, or engineering who need a practical understanding of statistics.
Aspiring data analysts, researchers, and policy professionals who want to learn how to perform statistical analysis using STATA, R, Python, SPSS, and Excel.
Academics, educators, and thesis writers who need to analyse survey or experimental data and interpret statistical results effectively.
Professionals in business, healthcare, education, or government aiming to enhance their decision-making with data-driven insights.
Self-learners and career changers transitioning into analytics, research, or data science roles who need structured training with software applications.