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 = 14 and σ = 1.3. 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 14 grams and standard deviation 1.3. 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 14 than around 11.4 or 15.95.

…  11.5 14 16.5  …

Continuing the candy example, let us calculate the probability density for a weight of 12.1059 grams; that is, calculate f(12.1059).

Your Answer

In the box below, please enter the value of f(12.1059), where X ~ Normal(μ=14; σ=1.3), then click on the “Check your answer!” button. Please round your answer to the ten-thousandths place.

Assistance

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