Anova1w: Difference between revisions
Jump to navigation
Jump to search
imported>Jeremy No edit summary |
|||
(One intermediate revision by one other user not shown) | |||
Line 10: | Line 10: | ||
===Description=== | ===Description=== | ||
Calculates one way ANOVA table and tests significance of between factors variation (it is assumed that each column of the data represents a different treatment). Inputs are the data table (dat) and the optional desired confidence level (alpha), expressed as a fraction (e.g. 0.99, 0.999). {default = 0.95}. A text table is displayed if no output is requested. | Calculates one way ANOVA table and tests significance of between factors variation (it is assumed that each column of the data represents a different treatment). Inputs are the data table (dat) and the optional desired confidence level (alpha), expressed as a fraction (e.g. 0.99, 0.999). {default = 0.95}. A text table is displayed if no output is requested. For more information see the <code>anova1wdemo</code>. | ||
====Inputs==== | ====Inputs==== | ||
Line 36: | Line 36: | ||
: '''.table''' : cell array containing the the text description of the results (same as displayed with no outputs). | : '''.table''' : cell array containing the the text description of the results (same as displayed with no outputs). | ||
===See Also=== | ===See Also=== | ||
[[anova2w]], | [[anova2w]], [[anovadoe]], [[ftest]], [[statdemo]] |
Latest revision as of 08:53, 3 September 2019
Purpose
One-way analysis of variance.
Synopsis
- anova1w(dat,alpha)
- results = anova1w(dat,alpha)
Description
Calculates one way ANOVA table and tests significance of between factors variation (it is assumed that each column of the data represents a different treatment). Inputs are the data table (dat) and the optional desired confidence level (alpha), expressed as a fraction (e.g. 0.99, 0.999). {default = 0.95}. A text table is displayed if no output is requested. For more information see the anova1wdemo
.
Inputs
- dat = Data table where columns are factors.
Optional Inputs
- alpha = desired confidence level expressed as a fraction (default = 0.95)
Outputs
- results = A structure array containing all the contents of the table including the fields:
- .ssq : Sum of Squares (with sub-fields for factors, residual and total)
- .dof : Degrees of Freedom (with sub-fields for factors, residual and total)
- .mean_sq : Mean Square (with sub-fields for factors and residual)
- .F : F-test value for factors
- .F_crit : F-test critical value (for given alpha)
- .alpha : provided alpha
- .p : p-value for F-test value (alpha where F is significant)
- .table : cell array containing the the text description of the results (same as displayed with no outputs).