ST 302: ST 302

Discover the process of using a one-sample t-test to validate a claim about average soft drink consumption. By calculating the test statistic and analyzing the corresponding P-value, we determine the validity of the researcher's assertion.

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 how a university dean estimates freshmen study hours using statistical methods. Understand the importance of z-scores, confidence levels, and sample sizes in making accurate predictions. Learn how to ensure results are within a desired error margin.

This video presents a comparison between two suppliers of plastic gears in terms of their mean impact strength. Using statistical tools like the two-sample t-test and confidence intervals, we evaluate which supplier offers stronger gears.

Uncover the relationship between confidence levels and interval widths. Grasp how the range of confidence intervals broadens with increasing confidence. Understand the trade-offs in statistical certainty and estimation.

Explore the claim that average daily water consumption is 123 gallons. Using statistical testing, we evaluate a new sample against the Old Farmer’s Almanac claim. Learn how to interpret p-values and t-scores in hypothesis testing.