Have a mean weight of 90.7 grams with a standard deviation of 6 g. A random sample of 60 kits is drawn. What is the probability that the sample mean weight is less than 91 g

65.17% probability that the sample mean weight is less than 91 g

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution:

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean and standard deviation , the zscore of a measure X is given by:

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central limit theorem:

The Central Limit Theorem estabilishes that, for a random variable X, with mean and standard deviation , the sample means with size n of at least 30 can be approximated to a normal distribution with mean and standard deviation

In this problem, we have that:

What is the probability that the sample mean weight is less than 91 g

This is the pvalue of Z when X = 91. So

By the Central Limit Theorem

has a pvalue of 0.6517

65.17% probability that the sample mean weight is less than 91 g