The heights of students at a college are normally distributed with a mean of 175 cm and a standard deviation of 6 cm. One might expect in a sample of 1000 students that the number of students with heights less than 163 cm is:

25

Step-by-step explanation:

The Empirical Rule states that, for a normally distributed random variable:

68% of the measures are within 1 standard deviation of the mean.

95% of the measures are within 2 standard deviation of the mean.

99.7% of the measures are within 3 standard deviations of the mean.

In this problem, we have that:

Mean = 175cm

Standard deviation = 6 cm

Percentage of students below 163 cm

163 = 175 - 2*6

So 163 is two standard deviations below the mean.

By the Empirical rule, 95% of the heights are within 2 standard deviations of the mean. The other 100-95 = 5% are more than 2 standard deviations of the mean. Since the normal distribution is symmetric, 2.5% of them are more than 2 standard deviations below the mean (so below 163cm) and 2.5% are more than two standard deviations above the mean.

2.5% of the students have heights less than 163cm.

Out of 1000

0.025*1000 = 25

25 is the answer

Step-by-step explanation:

Since the heights of students at a college are normally distributed, we would apply the formula for normal distribution which is expressed as

z = (x - µ) / σ

Where

x = heights of students

µ = mean height

σ = standard deviation

From the information given,

µ = 175 cm

σ = 6 cm

The probability that the height of a student is less than 163 cm is expressed as

P (x < 163)

For x = 163

z = (163 - 175) / 6 = - 2

Looking at the normal distribution table, the probability corresponding to the z score is 0.023

Therefore, the expected number of students with heights lesser than 163 cm is

1000 * 0.023 = 23 students