This textbook serves as a comprehensive and meticulously structured guide to gain knowledge in Data Science. It begins with a robust “Introduction” to Data Science, covering its benefits, evolution, process, roles, applications, and crucial ethical considerations like data privacy and security. It then delves into the essential “Basic Statistical Foundation for Data Science,” explaining measures of central tendency and dispersion, probability theory, various distributions, sampling theory, and hypothesis testing.
