ST 101: Test Webinar Session

Discover how to construct a confidence interval for understanding U.S. adult satisfaction. Using a sample from a 2010 Gallup Poll, we unveil the proportion of adults pleased with the state of affairs, backed by statistical calculations.

Explore the dynamics of Poisson distribution using both theoretical understanding and a practical application related to discovering uranium deposits. With the help of Bayes' formula and parameter adjustments, interpret various probabilities and outcomes for event occurrences.

Assess the distribution of computers across schools using statistical methods. Determine the probability of a randomly selected school having a specific number of computers. From fewer than 50 to more than 100 computers, derive insightful conclusions about school infrastructures.

Compare the mean returns and volatilities of two stocks using t-test and F-test methods. Through the application of hypothesis testing and P-value calculations, we determine which stock provides higher returns and which is riskier.

Compare the voltages of Brand X and Brand Y batteries using statistical analysis. Learn how to determine a 95% confidence interval for their mean differences. Understand the process from data collection to interpretation of results.

Unpack a Seattle-based study on Emergency Department asthma visits using the Poisson distribution. Explore the probability of visit frequencies and derive insights on healthcare patterns. Conclusions provide a statistical overview of asthma-related ED attendance.