Chebyshev's theorem says that for any set of observations, the proportion of values that lie within k standard deviations of the mean is 1 - 1/k².
In statistics, Standard deviation is a measure of the variation of a set of values.
σ = standard deviation of population
N = number of observation of population
X = mean
μ = population mean
We know that Chebyshev's theorem states that for a large class of distributions, no more than 1/k² of the distribution will be k standard deviations away from the mean.
This means that 1 - 1/k² of the distribution will be within k standard deviations from the mean.
Lets k = 1.8, the amount of the distribution that is within 1.8 standard deviations from the mean is;
1 - 1/1.8² = 0.6914
= 69.14%
Hence, Chebyshev's theorem says that for any set of observations, the proportion of values that lie within k standard deviations of the mean is 1 - 1/k².
Learn more about standard deviation and variance:
https://brainly.com/question/11448982
#SPJ1