STAT 321: STAT 321

Learn how to determine a 90% confidence interval for the proportion of people who watch educational television based on a survey. Understand how to utilize the z-score and interpret results, guiding decisions for a television company's publicity efforts.

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.

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.

Explore the intricacies of evaluating cereal box weights using Z-scores and normal distribution. By examining both individual boxes and a sample mean, understand the probabilities of achieving certain weight values. Gain insights into how statistical tools help interpret real-world product claims.

Examine the potential biases in a Parade Magazine survey about banning cell phone use while driving, focusing on the implications of voluntary response sampling.

Explore the steps to conduct a two-sample t-test using a control and supplemented group. Through hypothesis testing, standard deviation, and P-value interpretation, we analyze the means of both groups to determine statistical differences.