Module 1: Information Theory Lower Bounds

By the end of this module, you will be able to:
• Outline the concept of the information-theoretic lower bounds
• Describe the procedure for deriving lower bounds for compression problem and randomness generation
• Discuss the relationship between Shannon's source coding and Shannon entropy
• Explain the process for deriving lower bounds for random number generation
• Summarize the theorems of strong converse for source coding
• Identify the methods of deriving minmax lower bound for statistical estimation
• Recognize the significance of empirical mean in deriving a lower bound