a. Identify the critical value \( t_{\alpha / 2} \) used for finding the margin of error. \( t_{\alpha / 2}=1.69 \) (Round to two decimal places as needed.) b. Find the margin of error. \( \mathrm{E}=195.9 \mathrm{~g} \) (Round to one decimal place as needed.) c. Find the confidence interval estimate of \( \mu \). \( \square \mathrm{g}<\mu<\square \mathrm{g} \) (Round to one decimal place as needed.)

To find the confidence interval estimate of \( \mu \), you can follow this fun recipe: Start with the sample mean (which we'll assume you know), and then simply subtract and add the margin of error \( E \) (195.9 g) to this value. Let's say your sample mean is 500 g. The confidence interval would be 500 g - 195.9 g < \( \mu \) < 500 g + 195.9 g, giving us 304.1 g < \( \mu \) < 695.9 g. Now, remember, confidence intervals are wonderful! They provide a range of values that we believe contains the true population mean \( \mu \), with a certain level of confidence. This means that if you were to take many samples and create intervals, a significant number of them would capture the true mean. Keep this in mind when interpreting your results—it's all about giving you a better understanding of your data!