Normal Distribution by Malin Christersson
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This example demonstrates the normal distribution probability density function. Normal distribution is a crucial concept in probability and statistics, describing the distribution of many random variables. By adjusting the mean μ and standard deviation σ, you can observe changes in the normal distribution curve. This example uses GeoGebra function objects f and g, as well as text objects text1 and text2. Suitable for high school and above students learning probability and statistics, and random experiments.
GeoGebra Commands & Parameters
Numeric μ(1.8)Numeric σ(0.345)f(x) = (1 / ((σ * sqrt((2 * π)))) * ℯ^(((-(x - μ)^(2))) / ((2 * σ^(2)))))g(x) = (1 / sqrt((2 * π)) * ℯ^(((-x^(2))) / 2))
AI Drawing Prompt Reference
Draw a graph of a normal distribution probability density function, including two curves: one is a normal distribution curve with a mean of 1.8 and a standard deviation of 0.345, and the other is a standard normal distribution curve. Label the formulas and parameter values of both curves.
The prompt above was compiled from the original drawing commands and is for reference only.