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Logistic Distribution Function

The Logistic Distribution is a continuous single-parameter distribution which has been used extensively to represent growth functions

The Logistic Distribution is a continuous single-parameter distribution which has been used extensively to represent growth functions

Logistic Distribution Function

by Donald Schaefer
Logistic Distribution Function
Logistic Distribution Function
Logistic Distribution Function
Apple Watch
Logistic Distribution Function Apple Watch App
Logistic Distribution Function Offers Apple Watch App
Check the details on WatchAware

What is it about?

The Logistic Distribution is a continuous single-parameter distribution which has been used extensively to represent growth functions. The Logistic Distribution curve has a shape similar to the Normal Distribution.

Logistic Distribution Function

App Details

Version
1.5
Rating
NA
Size
7Mb
Genre
Education Productivity
Last updated
February 6, 2019
Release date
September 30, 2014
More info

App Screenshots

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App Store Description

The Logistic Distribution is a continuous single-parameter distribution which has been used extensively to represent growth functions. The Logistic Distribution curve has a shape similar to the Normal Distribution.

The Logistic Disribution Calculator accepts a random variable x and returns the probability that the random variable with a standard Logistic Distribution has a value less than variable x. The Logistic Distribution F(x) graph displays the Logistic Distribution as a bell-shaped curve for a given value of the random variable x.

The Data Tables and Graphs increment the x value 200 times with a 0.01 increment value with -1.0 <= x <= 1.0.

The graphs are touch enabled. Upon touching the graph a vertical line appears. Move the vertical line to the left or right to display the point (x/f(x)) data in the upper left of the graph.

The horizontal x-axis displays x values. The vertical y-axis plots a range of F(x) values.

Horizontal Max and Min dashed line display the Maximum and Minimum F(x) values

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