BIOST 394: BIOST 394

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.

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.

Unpack the potential biases in a survey about movie-watching habits based on its design and constraints. Learn how limiting to residential phones and specific time frames can affect results. Recommendations are made to ensure a broader, more accurate perspective.

Explore a statistical approach to analyze the claim about average tornado lengths. Understand the nuances of hypothesis testing, from setting null and alternative hypotheses to interpreting P-values. Witness a comprehensive breakdown of the evidence from a sample of 500 tornadoes.

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.

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.