Step 1 :The given values are: sample mean (\(\bar{x}\)) is 74 inches, standard deviation (\(\sigma\)) is 3 inches, and sample size (\(n\)) is 48.
Step 2 :The formula for a confidence interval is \(\bar{x} \pm z \frac{\sigma}{\sqrt{n}}\), where \(z\) is the z-score corresponding to the desired level of confidence. For a 95% confidence interval, the z-score is approximately 1.96.
Step 3 :Substitute the given values into the formula to find the confidence interval: \(74 \pm 1.96 \frac{3}{\sqrt{48}}\).
Step 4 :Calculate the lower and upper bounds of the confidence interval to get approximately (73.151, 74.849).
Step 5 :The error bound is given by the formula \(EBM = z \frac{\sigma}{\sqrt{n}}\). Substitute the given values into the formula to get \(EBM = 1.96 \frac{3}{\sqrt{48}}\), which is approximately 0.849.
Step 6 :If the sample size is increased to 1,000, the size of the confidence interval will decrease. This is because a larger sample provides more information about the population and thus reduces uncertainty.