Final answer:
Checking whether the population is approximately normal before constructing a confidence interval is necessary because confidence intervals are based on the assumption that the data follows a normal distribution. If the population is not approximately normal, alternative methods, such as non-parametric tests, may be used.
Step-by-step explanation:
Checking whether the population is approximately normal before constructing a confidence interval is necessary because confidence intervals are based on the assumption that the data follows a normal distribution. When the population distribution is normal, the sampling distribution of the sample mean is also normal, regardless of the sample size. This allows for the use of statistical tests and confidence intervals.
If the population is not approximately normal, the sampling distribution of the sample mean may not be normal, which can lead to inaccurate confidence intervals. In such cases, alternative methods, such as non-parametric tests, may be used. Therefore, it is important to assess the normality of the population before constructing a confidence interval.