Normal Distributions

Calculating Densities

The Problem

Let X be a random variable following a Normal (Gaussian) distribution. All Normal distributions have two parameters: mean and standard deviation (or variance). For this X, let μ = 13 and σ = 0.5. An example of where such a distribution may arise is the following:

You have a bag of candy made by Statistics, Inc. The weight of the pieces are not all the same, they are a random variable. This variable follows a Normal distribution with average weight 13 grams and standard deviation 0.5. Define the random variable X as the weight of a randomly selected peice of candy.

For those who like pictures, here is a graphic of the probability density function. It is not a probability, it is a density, a likelihood. It can be used to determine which values are more likely than others. From the graphic, we can tell that weights are more likely around 13 than around 12 or 13.75.

…  10.5 13 15.5  …

Continuing the candy example, let us calculate the probability density for a weight of 12.4605 grams; that is, calculate f(12.4605).

Your Answer

In the box below, please enter the value of f(12.4605), where X ~ Normal(μ=13; σ=0.5), then click on the “Check your answer!” button. Please round your answer to the ten-thousandths place.

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© Ole J. Forsberg, Ph.D. 2024. All rights reserved.   .