Dive into a comprehensive 10-hour statistics course designed for data science applications. Explore essential statistical concepts through real-life lecture formats, working through various examples to gain a deep understanding of standard deviation, normal distribution, bivariate analysis, and more. Focus on grasping underlying concepts rather than memorizing formulas and calculations. Cover topics including sampling distributions, hypothesis testing, confidence intervals, t-tests, ANOVA, chi-square tests, and linear regression. Learn how to apply statistical methods in data science contexts, with additional resources available for implementing concepts using R programming. Enhance your statistical knowledge with practical examples, clear explanations, and a focus on real-world applications in data science.