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It looks like there's a small mix-up with the value of \( Z \) corresponding to a 95% confidence level! In fact, the correct \( Z \) value is typically around 1.96, not 2.56. The \( Z \) value represents how many standard deviations away from the mean you need to go to capture 95% of the data in a normal distribution. When you’re calculating confidence intervals, using the right \( Z \) value is crucial, as it directly affects the width of your interval. A common mistake is to confuse \( Z \) scores with other values used in statistical calculations, like \( t \) scores for smaller sample sizes, so double-check before you dive in!