Lectures related to Response Compaction in VLSI Testing

Covers the basics of probability theory, random variables, joint probability, and inference.

Covers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.

Explores the probability of complementary events and unions, with examples on dice rolls and number selection.

Covers properties and calculations related to the normal distribution, including probabilities and quantiles.

Explores risk evaluation, equivalent value, and insurance premium in lotteries, as well as discount rate adjustments.

Introduces statistical analysis concepts like boxplot and normal distribution using real data examples.

Introduces the key concepts of convexity and its applications in different fields.

Covers fundamental concepts in probability and statistics, including the law of total probability, Bayes' theorem, and independence of events.