The expression `normalcdf(-E99, 215, 225, 10)` is used in statistics to calculate the cumulative distribution function (CDF) for a normal distribution. In this case, it appears you want to find the probability that a normally distributed random variable falls between 215 and 225, where the mean (\(\mu\)) is 225 and the standard deviation (\(\sigma\)) is 10.

Here's a breakdown of the parameters:
- **Lower bound**: \(-E99\) (effectively negative infinity)
- **Upper bound**: \(215\)
- **Mean**: \(225\)
- **Standard deviation**: \(10\)

### Calculation Steps

1. **Convert to Z-scores**:
   \[
   Z = \frac{X - \mu}{\sigma}
   \]
   For \(X = 215\):
   \[
   Z_{215} = \frac{215 - 225}{10} = -1
   \]
   For \(X = \infty\) (or \(-E99\)), \(Z\) approaches negative infinity.

2. **Look up CDF values**:
   The CDF at \(Z = -1\) can be found using standard normal distribution tables or a calculator.

   \[
   P(Z < -1) \approx 0.1587
   \]

3. **Final Probability**:
   Since we're looking for \(P(X < 215)\), the probability is approximately \(0.1587\).

If you want to calculate the probability that \(X\) is less than or equal to 215, you can also find:

\[
P(X < 215) \approx 0.1587
\]

### Summary
The cumulative probability from negative infinity to 215 for this normal distribution is approximately **15.87%**.

Would you like more details on normal distributions or any related topics? Here are some questions you might consider:

1. How do you calculate probabilities for other ranges in a normal distribution?
2. What is the significance of the standard normal distribution?
3. How can you interpret the results of normalcdf in real-world scenarios?
4. What are the implications of using extreme bounds like \(-E99\)?
5. How do you calculate Z-scores for different values in a normal distribution?

**Tip**: Always remember that using a calculator or statistical software can help simplify these calculations significantly.

Discover how to calculate the cumulative probability for a normal distribution using normalcdf(-E99,215,225,10). This example illustrates finding the probability that a normally distributed random variable falls between 215 and 225 with a mean of 225 and a standard deviation of 10. Ideal for students in Grades 10-12.

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