# Course curriculum

• 1

### Chapter 1 - Descriptive Statistics

• Introduction
• Statistical Learning vs Machine Learning
• Datatypes
• Why data types are important
• Data Grouping
• Data summarization techniques
• Measures of location, spread, and shape
• Visual representation of summarized data
• Summary
• Additional Learning Resources
• Chapter 1 Quiz
• 2

### Chapter 2 - Probability

• Introduction to Probability
• Probability and Business decisions
• Deterministic and Probabilistic models
• 3 types of the probabilistic approach
• Understanding basic terminologies 1
• Measuring outcomes
• Understanding probability through Venn diagrams
• Understanding basic terminologies 2
• Types of probability
• Conditional law
• Laws of probability
• Probability distributions
• Binomial distribution
• Poisson distribution
• Continuous distributions
• Uniform distribution
• Normal distribution
• t - distribution
• Choosing an appropriate distribution
• Summary
• Additional Learning Resources
• Chapter 2 Quiz
• 3

### Chapter 3 - Inferential Statistics

• Inferential Statistics
• Key concepts and vocab
• Probability & Non-Probability sampling
• Sampling distribution and CLT theorem
• Estimating population parameters
• Confidence levels and Confidence Intervals
• Hypothesis testing
• Null and Alternate hypothesis
• Significance levels
• 2 methods to test significance
• Applying significance levels to decision making
• Chi-square test and their applicability in business scenarios
• One way ANOVA and their applicability in business scenarios
• Summary
• Additional Learning Resources
• Chapter 3 Quiz