The question you're dealing with involves calculating and comparing the z-scores of two baseball players based on their number of home runs in different seasons. A z-score measures how many standard deviations a data point (in this case, the number of home runs) is from the mean. The formula for the z-score is:

$z = \frac{X - \mu}{\sigma}$

where:

• $X$ is the player's number of home runs (60 for player A, 66 for player B),
• $\mu$ is the mean number of home runs in the season,
• $\sigma$ is the standard deviation of home runs for that season.

To answer the question fully, I would need the mean ($\mu$) and standard deviation ($\sigma$) values for both seasons. You mentioned that there's an icon to view this data—could you provide those values?

Once I have that data, I can calculate the z-scores for both players, compare them, and determine whose performance was more impressive.

Let me know if you need more details on z-scores, or share the necessary information from the table! Would you like help with any further steps?

5 Related Questions:

1. What does a z-score indicate in terms of performance relative to the average?
2. How do standard deviation and mean affect the calculation of a z-score?
3. How can z-scores be used to compare data points from different datasets?
4. What conclusions can you draw if one z-score is positive and another is negative?
5. How can you interpret small vs. large absolute values of z-scores?

Tip:

A z-score close to 0 indicates that the data point is near the mean, while a higher absolute z-score (positive or negative) indicates that the data point is far from the mean, meaning it’s an unusually high or low value.