One Way ANOVA
Perform a one-way analysis of variance.
Usage
var anova1 = require( '@stdlib/stats/anova1' );
anova1( x, factor[, opts] )
For an array or typed array of numeric values x
and an array of classifications factor
, a one-way analysis of variance is performed. The hypotheses are given as follows:
The function returns an object containing the treatment and error squared errors, degrees of freedom, mean squared errors, and both the p-value and F score.
var out;
var x;
var y;
x = [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 ];
y = [ 'Treatment A', 'Treatment B', 'Treatment C', 'Control', 'Treatment A', 'Treatment B', 'Treatment C', 'Control', 'Treatment A', 'Treatment B', 'Treatment C', 'Control' ];
out = anova1( x, y );
/* returns
{
'treatment': { 'df': 11, 'ss': 15, 'ms': 5 },
'error': { 'df': 8, 'ss': 128, 'ms': 16 },
'statistic': 0.3125,
'pValue': 0.81607947904798,
'means':
{ 'Treatment A': { 'mean': 5, 'sampleSize': 3, 'SD': 4 },
'Treatment B': { 'mean': 6, 'sampleSize': 3, 'SD': 4 },
'Treatment C': { 'mean': 7, 'sampleSize': 3, 'SD': 4 },
'Control': { 'mean': 8, 'sampleSize': 3, 'SD': 4 } },
'method': 'One-Way ANOVA'
}
*/
The returned object comes with a .print()
method which when invoked will print a formatted output of the results of the hypothesis test. print
accepts a digits
option that controls the number of decimal digits displayed for the outputs and a decision
option, which when set to false
will hide the test decision.
var out;
var x;
var y;
x = [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 ];
y = [ 'Treatment A', 'Treatment B', 'Treatment C', 'Control', 'Treatment A', 'Treatment B', 'Treatment C', 'Control', 'Treatment A', 'Treatment B', 'Treatment C', 'Control' ];
out = anova1( x, y );
console.log( out.print() );
/* =>
One-Way ANOVA
Null Hypothesis: All Means Equal
Alternate Hypothesis: At Least one Mean not Equal
df SS MS F Score P Value
Treatment 3 15 5 0.3125 0.8161
Errors 8 128 16
Fail to Reject Null: 0.8161 >= 0.05
*/
The function accepts the following options
:
- alpha:
number
in the interval[0,1]
giving the significance level of the hypothesis test. Default:0.05
. - decision: a
boolean
value indicating if function is to return a decision of either rejection of the null hypothesis or failure to reject the null hypothesis. Default:false
By default, the test is carried out at a significance level of 0.05
. To choose a custom significance level, set the alpha
option.
var x = [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 ];
var y = [ 'Treatment A', 'Treatment B', 'Treatment C', 'Control', 'Treatment A', 'Treatment B', 'Treatment C', 'Control', 'Treatment A', 'Treatment B', 'Treatment C', 'Control' ];
var out = anova1( x, y );
var table = out.print();
/* e.g., returns
One-Way ANOVA
Null Hypothesis: All Means Equal
Alternate Hypothesis: At Least one Mean not Equal
df SS MS F Score P Value
Treatment 3 15 5 0.3125 0.8161
Errors 8 128 16
Fail to Reject Null: 0.8161 >= 0.05
*/
out = anova1( x, y, {
'alpha': 0.9
});
table = out.print();
/* e.g., returns
One-Way ANOVA
Null Hypothesis: All Means Equal
Alternate Hypothesis: At Least one Mean not Equal
df SS MS F Score P Value
Treatment 3 15 5 0.3125 0.8161
Errors 8 128 16
Reject Null: 0.8161 <= 0.9
*/
Notes
- The calculation for the p value is based on an F distribution.
Examples
var anova1 = require( '@stdlib/stats/anova1' );
var x = [ 3, 4, 5, 6, 2, 5, 10, 12, 8, 10 ];
var f = [ 'control', 'treatA', 'treatB', 'control', 'treatA', 'treatB', 'control', 'treatA', 'treatB', 'control' ];
var out = anova1( x, f, {
'decision': true
});
console.log( out.print() );
out = anova1( x, f, {
'alpha': 0.9
});
console.log( out.print() );