A successful basketball player has a height of 6 feet 6 ​inches, or 198 cm. Based on statistics from a data​ set, his height converts to the z score of 3.38. How many standard deviations is his height above the​ mean?

A z-score represents the number of standard deviations a data point is from the mean. The formula for calculating the z-score is:

\[ z = \frac{x - \mu}{\sigma} \]

where:
- \( x \) is the value in the dataset (the height in this case, 198 cm),
- \( \mu \) is the mean of the dataset,
- \( \sigma \) is the standard deviation of the dataset.

The given z-score is 3.38, which means the height of the basketball player is 3.38 standard deviations above the mean.

So, the player's height is 3.38 standard deviations above the mean.

Do you want details or have any questions?

Here are five questions you can ask:
1. How do you calculate the mean and standard deviation of a dataset?
2. What is the significance of a z-score in statistics?
3. Can you explain how to interpret a negative z-score?
4. How can z-scores be used to compare different datasets?
5. What are some common applications of z-scores in real-world scenarios?

**Tip:** Understanding z-scores is crucial for comparing individual data points to a population, especially when the data follows a normal distribution.

Explore how to interpret a z-score in statistics with an example of a basketball player's height. Learn how a z-score of 3.38 indicates the height is 3.38 standard deviations above the mean.

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