The given sample size is 8 and the sum is 56. Using these values, we can calculate the sample mean of the metric variable. Here's how:sample mean = (sum of values) / (sample size)sample mean = 56 / 8sample mean = 7.
Now, we know that the sample mean of the metric variable is 7.Now, we need to find out whether it is possible or not that the population mean of the metric variable is more than 300. For this, we need to use the concept of the central limit theorem.
According to the central limit theorem, the sample mean of a sufficiently large sample size follows a normal distribution with a mean equal to the population mean and a standard deviation equal to the population standard deviation divided by the square root of the sample size.
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