This Quantitative Data Analysis course provides a comprehensive introduction to statistical analysis and research methods used in data-driven studies. It is designed for beginners and students who want to understand how to analyze data and interpret research results effectively.
The course begins by explaining the difference between descriptive and inferential statistics, helping learners understand how data is summarized and used to make predictions. It then explores research design, including how to structure studies and define research objectives.
You will learn about different types of variables, including independent, dependent, and control variables, which are essential for building strong research models. The course also covers levels of data measurement such as nominal, ordinal, interval, and ratio data.
In addition, it explains sampling methods, including probability and non-probability sampling, and how to select appropriate data samples. The course also introduces hypothesis writing and common mistakes to avoid in quantitative analysis.
Real-world examples are included to simplify complex topics and improve understanding.
By the end of this course, learners will have a solid foundation in quantitative data analysis, research methods, and statistical thinking, enabling them to conduct and interpret research effectively.
