(c) Find the normalized (i.e., standardized) *z* score for *X* = +$18.

To find the standardized or normalized *z*-score for a given value *X*, we use the formula:

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

Where:
- *X* is the value for which we are calculating the *z*-score.
- $\mu$ is the mean of the population.
- $\sigma$ is the standard deviation of the population.

You provided $ X = +18 $, but we need the mean ($\mu$) and standard deviation ($\sigma$) to proceed with the calculation. If you provide those values, I can help you calculate the *z*-score.

Would you like to provide the mean and standard deviation, or do you have any questions so far?

Here are 5 related questions for further exploration:
1. How does the *z*-score help in understanding the position of a data point in a distribution?
2. What are typical values of *z*-scores that indicate a point is significantly far from the mean?
3. What is the relationship between *z*-scores and percentiles in a normal distribution?
4. How can you interpret a negative *z*-score?
5. How is the *z*-score used in hypothesis testing?

**Tip**: A *z*-score tells you how many standard deviations a data point is from the mean, helping you understand its relative position in a dataset.

(c) Find the normalized (i.e., standardized) z score for X = +18.

Learn how to find the standardized z-score for X = +18 using the formula z = (X - μ) / σ. Understand how z-scores indicate a data point's distance from the mean and how they are used in statistics. Suitable for Grades 9-12 students studying normal distribution and standardization.

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