In a normal distribution, a data value located 0.7 standard deviations below the mean has Standard Score: z = 

In a normal distribution, a data value located 2.5 standard deviations above the mean has Standard Score: z = 

In a normal distribution, the mean has Standard Score: z = 

In a normal distribution, the standard score (z-score) is calculated based on how many standard deviations a data value is from the mean.

1. A data value located **0.7 standard deviations below the mean** has a z-score of:
   \[
   z = -0.7
   \]

2. A data value located **2.5 standard deviations above the mean** has a z-score of:
   \[
   z = 2.5
   \]

3. The mean of the distribution has a z-score of:
   \[
   z = 0
   \]

If you have any questions or need further details, let me know! Here are some related questions you might consider:

1. What is the significance of the z-score in statistics?
2. How do you interpret a z-score of -1.5?
3. What percentage of data falls within one standard deviation of the mean in a normal distribution?
4. How can you convert a z-score back to a data value?
5. What is the relationship between z-scores and probabilities in a normal distribution?

**Tip:** When analyzing z-scores, remember that negative values indicate a position below the mean, while positive values indicate a position above the mean.

In a normal distribution, a data value located 0.7 standard deviations below the mean has Standard Score: z =. In a normal distribution, a data value located 2.5 standard deviations above the mean has Standard Score: z =. In a normal distribution, the mean has Standard Score: z =.

Explore the concept of z-scores in normal distribution, including calculations for values below and above the mean. Learn that a z-score of -0.7 indicates a value 0.7 standard deviations below the mean, and a z-score of 2.5 indicates a value 2.5 standard deviations above the mean. Suitable for high school students.

Math Problem Statement

Solution

Ask a new question for Free

By Image

Math Problem Analysis

Mathematical Concepts

Formulas

Theorems

Suitable Grade Level

Related Recommendation