Write 3 short separate peer responses to (one for each of the following 3 discussions related to subject) and support your response with 2 scholars. Your response should explain your understanding for the “Central Limit Theorem” DQ1 The Central Limit Theorem states that the sampling distribution of the sample means approaches a normal distribution as the sample size gets larger — no matter what the shape of the population distribution (Statistics How To, n.d.). It enables the user to measure how much the mean of various samples will vary, without having to take any other sample means to compare it with. The theorem concerns the sampling distribution of the sample means. A normal distribution is to help determine the accuracy of many statistics, including the sample mean (Anderson et Al., 2015). We begin with a simple random sample with n individuals from a population of interest. From this sample, we can easily form a sample mean that corresponds to the mean of what measurement we are curious about in our population.Thus, the central limit theorem is important because under certain condition, you can approximate some distribution with normal distribution although the distribution is not normally distributed (Anderson et Al., 2015).