Performs a one-way analysis of variance (ANOVA) and determines whether the factor has a significant effect on the experimental outcome.
Error conditions that occur before this node runs.
The node responds to this input according to standard error behavior.
Standard Error Behavior
Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.
Default: No error
Acceptable probability that this node incorrectly rejects a true null hypothesis.
significance level is a threshold value used to judge whether a factor has a significant effect on the experimental outcome.
Default: 0.05
Probability that a value sampled from the F distribution with dofa and dofe degrees of freedom is greater than fa, where dofa, dofe, and fa are elements in summary.
A 2-by-5 matrix that displays the obtained values for analysis.
where
Algorithm for Calculating Sums of Squares
This node calculates the sums of squares using the following equations:
where
Algorithm for Calculating Degrees of Freedom
This node calculates the degrees of freedom using the following equations:
where
Algorithm for Calculating Mean Squares
This node calculates the mean squares using the following equations:
where
Algorithm for Calculating the F Value
This node calculates the F value using the following equation:
where
Algorithm for Calculating the F Critical Value
F critical is the value satisfying the following equation:
where F dofa, dofe is the F distribution with dofa and dofe degrees of freedom.
Boolean value that indicates whether the factor has a significant effect on the experimental outcome.
True | significance is equal to or less than significance level, which means the factor has a significant effect on the experimental outcome. |
False | significance is greater than significance level, which means the factor does not have a significant effect on the experimental outcome. |
Error information.
The node produces this output according to standard error behavior.
Standard Error Behavior
Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.
Using age as a factor, this example demonstrates how to test whether age has a significant effect on the number of sit-ups a person can do.
The following table defines the levels of age.
Level 0 | 6 years old to 10 years old |
Level 1 | 11 years old to 15 years old |
Level 2 | 16 years old to 20 years old |
The following table lists the results of a random sampling of six people. The results are based on a series of observations of how many sit-ups people from different age groups can do.
Person 1 | 8 years old (Level 0) | 10 sit-ups |
Person 2 | 12 years old (Level 1) | 15 sit-ups |
Person 3 | 16 years old (Level 2) | 20 sit-ups |
Person 4 | 20 years old (Level 2) | 25 sit-ups |
Person 5 | 13 years old (Level 1) | 17 sit-ups |
Person 6 | 10 years old (Level 0) | 12 sit-ups |
The following table lists the inputs and outputs of this node.
levels | 3 | |
x | [10, 15, 20, 25, 17, 12] | |
index | [0, 1, 2, 2, 1, 0] | |
significance level | 0.05 | |
significance | 0.0367 | |
summary | ssa | 133 |
sse | 16.5 | |
dofa | 2 | |
dofe | 3 | |
msa | 66.5 | |
mse | 5.5 | |
fa | 12.0909 | |
0.0 | 0 | |
F critical | 9.55209 | |
0.0 | 0 | |
significant? | True |
Because significant? is True, you can conclude that based on the sampling data, age has a significant effect on the number of sit-ups a person can do.
Where This Node Can Run:
Desktop OS: Windows
FPGA: Not supported
Web Server: Not supported in VIs that run in a web application