https://file.aiquickdraw.com/mathbot/file/1727839645402s2mvhr1q.jpg

The formula shown in the image is:

\[
Mp = \frac{\sum (x_i \times w_i)}{\sum w_i}
\]

### Explanation:
This formula represents the calculation of the weighted mean (or weighted average), where:

- \( x_i \) represents the individual values.
- \( w_i \) represents the weights associated with each \( x_i \).
- \( \sum (x_i \times w_i) \) is the sum of the products of values and their respective weights.
- \( \sum w_i \) is the sum of all weights.

The weighted mean \( Mp \) gives more importance to some values based on their associated weights.

Would you like a detailed breakdown of this formula or an example? Here are some related questions you might find helpful:

1. What is the significance of using a weighted mean versus a regular mean?
2. How do you choose the weights \( w_i \) for each value \( x_i \)?
3. Can this formula be applied to non-numeric datasets?
4. How does changing the weights affect the value of the weighted mean?
5. What are some real-world applications of the weighted mean?

**Tip:** Weighted means are useful when different data points contribute unequally to the final average, like calculating the average grade with different assignment weights.

What is the formula and explanation of the weighted mean calculation?

Learn how to calculate the weighted mean using the formula Mp = (Σ(x_i × w_i)) / Σ(w_i). This statistical method gives different importance to each value based on its associated weight, making it essential in cases where certain data points carry more significance than others. This guide is perfect for high school students and covers key statistical concepts.

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