Introduction to Applied Statistics
This course provides a comprehensive foundation in the practical application of statistical methods, transforming raw data into actionable insights through rigorous quantitative analysis. Students will explore fundamental concepts such as descriptive statistics, probability distributions, and hypothesis testing, while gaining hands-on experience with modern tools to perform regression analysis and determine statistical significance. By emphasizing real-world problem-solving and the interpretation of complex datasets, the curriculum ensures that learners can confidently navigate variability and uncertainty to drive data-informed decision-making across diverse industries.
- Level: intermediate
- Duration: 3 months
- 11 sections
- Price: Free
Topics: Applied Statistics, Data analysis, Data science, R, Hypothesis Testing, Regression
What's inside
- Introduction to Applied Statistics
- Chapter 1: Data and Data Distributions
- Chapter 2: Data Sets and Relationships
- Chapter 3: Randomness and Probability
- Chapter 4: Sampling Distributions
- Chapter 5: Introduction to Inference
- Chapter 6: Inference for Means and Proportions
- Chapter 7: Inference for Categorical Data
- Chapter 8: One-Way Analysis of Variance (ANOVA)
- Chapter 9: Two-Way Analysis of Variance (ANOVA)
- Chapter 10: Conclusion — Next Steps in Your Statistics Journey