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Introduction to Biostatistics and Research Methods by Muhammad Ibrahim: A Review


Introduction to Biostatistics and Research Methods by Muhammad Ibrahim: A Review




Biostatistics is the application of statistical methods to biological and medical data. It is an essential skill for researchers, clinicians, and students who want to design, conduct, analyze, and interpret health-related studies. Biostatistics can help answer questions such as:


Biostatistics Book By Muhammad Ibrahim



  • What is the prevalence of a disease in a population?



  • What are the risk factors for developing a disease?



  • What is the effectiveness of a new treatment or intervention?



  • What is the best way to compare different groups or treatments?



  • How can we account for confounding and bias in observational studies?



  • How can we deal with missing data and measurement errors?



To learn biostatistics, one needs a solid foundation of basic concepts, principles, and methods, as well as practical examples and applications. One book that provides such a comprehensive and accessible introduction to biostatistics is Introduction to Biostatistics and Research Methods by Muhammad Ibrahim.


Muhammad Ibrahim is a professor of biostatistics at King Saud University in Saudi Arabia. He has more than 30 years of experience in teaching and research in biostatistics, epidemiology, and public health. He has published several books and many scientific papers in reputed national and international journals. He is also a fellow of the Royal Statistical Society in London.


Introduction to Biostatistics and Research Methods is the second edition of his popular textbook that was first published in 2009. It is intended for clinical researchers, physiotherapists, nurses, and medical students who want to learn the basics of biostatistics and research methods. The book covers the following topics:


  • The role and scope of biostatistics in health research



  • Descriptive statistics: how to summarize and display data using tables, graphs, and measures of central tendency and dispersion



  • Probability: how to calculate and interpret probabilities using rules, formulas, and distributions



  • Inferential statistics: how to test hypotheses and draw conclusions using parametric and nonparametric tests



  • Correlation and regression: how to measure and model the relationship between two or more variables using simple linear regression, multiple regression, logistic regression, and other methods



  • Analysis of variance: how to compare means of more than two groups using one-way or two-way ANOVA



  • Survival analysis: how to analyze time-to-event data using life tables, Kaplan-Meier curves, log-rank tests, and Cox proportional hazards models



  • Research methods: how to plan and conduct quality research using different types of study designs, sampling me