Assume that 200 births are randomly selected and 193 of the births are girls. Use subjective judgment to describe the number of girls as significantly​ high, significantly​ low, or neither significantly low nor significantly high.

In this scenario, we are assessing whether 193 girls out of 200 births can be considered significantly high using subjective judgment.

### Reasoning:
- **Typically**, for an equal chance of having a girl or a boy, the probability of having a girl in each birth is approximately 0.5 (50%).
- If we randomly select 200 births, the expected number of girls would be:
  \[
  \text{Expected Number of Girls} = 200 \times 0.5 = 100
  \]
- **193 girls** is far higher than the expected 100, which means the actual result deviates greatly from what we would expect under normal random conditions.
  
Since 193 girls are much higher than the expected value of 100 girls, this suggests a result that is not only unusual but likely to be **significantly high**.

### Conclusion:
The number of 193 girls out of 200 births is **significantly high** based on subjective judgment, as it deviates greatly from the expected 50% ratio.

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Would you like more details or have any questions?  
Here are some related questions:

1. What is the probability of getting exactly 193 girls in 200 births assuming a 50% chance for each birth?
2. How can we calculate the standard deviation for such a scenario?
3. What is the concept of "statistical significance" and how does it apply here?
4. How can we use a normal distribution to check the significance of this result?
5. What does subjective judgment mean in statistics?

**Tip:** When dealing with large sample sizes, considering the standard deviation helps determine whether a result is significantly high or low.

Analyze whether 193 girls out of 200 births can be considered significantly high using subjective judgment. Explore probability, expected value, and statistical significance concepts. Learn how to calculate the expected number of girls and understand the reasoning behind significant deviations.

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