The formula to calculate a z-score is:

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

where:

• $x$ is the data value,
• $\mu = 110$ is the mean,
• $\sigma = 21$ is the standard deviation.

For (b) $x = 95$:

$z = \frac{95 - 110}{21}$

$z = \frac{-15}{21}$

$z \approx -0.71$

Final Answer:

$z \approx -0.71$

Would you like more details or have any other questions?

Related Questions:

1. How do z-scores help compare different data points?
2. What does a negative z-score indicate?
3. How do you interpret a z-score of -0.71 in a normal distribution?
4. What percentage of data falls below a z-score of -0.71?
5. How can z-scores be used to detect outliers in a dataset?

Tip: A z-score of 0 means the data value is exactly equal to the mean.