The value 1.96 is the z-score that corresponds to the 95% confidence level in a standard normal distribution (also known as the standard Z-distribution).

### Explanation:

1. **Standard Normal Distribution (Z-Distribution):**
   - The standard normal distribution is a normal distribution with a mean of 0 and a standard deviation of 1.
   - Z-scores are the number of standard deviations away from the mean.

2. **95% Confidence Level:**
   - A 95% confidence level means that we are 95% confident that the true population parameter lies within the calculated confidence interval.
   - In a normal distribution, 95% of the data falls within approximately 1.96 standard deviations from the mean (in both directions).

3. **Finding the Z-Score:**
   - The total area under the standard normal curve is 1 (or 100%).
   - For a 95% confidence level, we want the middle 95% of the distribution.
   - The remaining 5% is split equally between the two tails of the distribution, so each tail has 2.5% (0.025).
   - To find the z-score that corresponds to the upper 2.5%, we look up 0.975 (since 0.975 is the cumulative area up to that point) in the z-table, which gives us approximately 1.96.

   This value of 1.96 is therefore used as the critical value (z-score) for constructing a 95% confidence interval.

Would you like to explore this concept further, or do you have any other questions?

### Related Questions:
1. How do we calculate the z-score for other confidence levels like 90% or 99%?
2. Can we use a different method to find the z-score for a 95% confidence level?
3. What is the difference between a z-score and a t-score?
4. How does the central limit theorem relate to using the z-score in confidence intervals?
5. What happens to the z-score if we increase the confidence level to 99%?
6. How can we use a standard normal table to find the z-score manually?
7. Why is the standard normal distribution important in statistics?
8. How does the choice of confidence level affect the width of the confidence interval?

**Tip:** The z-score is a critical component of confidence intervals when the population standard deviation is known and the sample size is large.

Explore the significance of the 1.96 z-score in statistics and confidence intervals. Learn about its role in the standard normal distribution, 95% confidence level calculations, and the central limit theorem.

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