Final answer:
The questions involve using statistical methods like ANOVA and hypothesis testing to analyze baseball data, comparing means of games won in the World Series and interpreting hit information from a table.
Step-by-step explanation:
The student's question pertains to the application of statistical methods, specifically ANOVA (Analysis of Variance) and hypothesis testing, to analyze baseball game data. In the context of the question, ANOVA might be used to compare the average number of games won in the World Series between the American League and National League teams. Hypothesis testing is subsequently applied to determine if there's a statistically significant difference between the two leagues' mean number of games won.
To conduct a hypothesis test as mentioned in question 97, one must first set up the null hypothesis that there is no difference in the mean number of games won between the two leagues (American and National Leagues). With the provided standard deviations and sample means, a t-test could be used to compare the two means. Assuming the data meets the required assumptions (normality, independent samples, etc.), we could compute the t-statistic and compare it to a critical value from the t-distribution to determine if the null hypothesis can be rejected or not.
For question 96, dealing with a table of hit information from baseball-almanac, we might be asked to calculate probabilities or utilize descriptive statistics, depending on the specifics of the question.
The side-by-side stem-and-leaf plot mentioned in the 'Try It' exercise helps to visually compare the distribution of wins and losses over the seasons. It is an excellent method for displaying data in a way that highlights the shape, central tendency, and variability.