https://file.aiquickdraw.com/mathbot/file/172680641564530rrsv7u.jpg

To solve the problem based on the image, we need to use the **experimental probability**.

### Step-by-Step Solution:
1. **Experimental probability** is calculated by dividing the number of favorable outcomes (in this case, tails) by the total number of trials (coin flips).
   
   From the image:
   - **Heads** = 24
   - **Tails** = 21
   - **Total flips** = 24 (heads) + 21 (tails) = 45

   So, the probability of landing on tails is:
   \[
   P(\text{Tails}) = \frac{21}{45} = \frac{7}{15}
   \]

2. You are asked to predict how many times tails will land in **15 flips**.

   Using the experimental probability, the expected number of tails in 15 flips can be calculated as:
   \[
   \text{Expected Tails} = P(\text{Tails}) \times 15 = \frac{7}{15} \times 15 = 7
   \]

### Answer:
The coin is expected to land on tails **7 times** in 15 flips.

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Would you like more details on any part of the solution?

Here are five related questions you can explore:
1. What is the probability of landing heads based on the data?
2. How does experimental probability differ from theoretical probability?
3. If the number of trials increased to 100, how would the prediction change?
4. How can we adjust the experiment to increase its accuracy?
5. What is the significance of a larger sample size in probability experiments?

**Tip:** Experimental probability becomes more accurate as the number of trials increases.

If you were to flip the coin 15 times, how many times will the coin land on tails based on the experimental probability?

Learn how to calculate the experimental probability of landing on tails in a coin flip experiment. With 24 heads and 21 tails in 45 flips, predict the number of tails in 15 flips. Suitable for students in Grades 6-8.

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