how to compute f statistic in matlab

To compute the F-statistic in MATLAB, you can use the anova1 function from the Statistics and Machine Learning Toolbox. The anova1 function performs one-way analysis of variance.

Here is an example of how to use the anova1 function to compute the F-statistic:

main.m
% Sample data
group1 = [10, 12, 8, 7, 9];
group2 = [5, 6, 4, 3, 5];
group3 = [15, 18, 20, 19, 16];

% Combine the data into a single matrix
data = [group1, group2, group3];

% Create a grouping variable that indicates the group for each observation
group = [ones(size(group1)), 2 * ones(size(group2)), 3 * ones(size(group3))];

% Compute the F-statistic using the anova1 function
[~, tbl, stats] = anova1(data, group, 'off');

% Access the F-statistic and the corresponding p-value
f_statistic = tbl{2, 5};
p_value = tbl{2, 6};
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In this example, we have three groups of data (group1, group2, and group3). We combine the data into a single matrix called data, and create a grouping variable group to indicate the group for each observation. The anova1 function is then used to perform the analysis and compute the F-statistic. The output includes an tbl table that contains various statistics, including the F-statistic in the second row and fifth column. The corresponding p-value can be accessed from the same table in the second row and sixth column.

Note that in this example, the 'off' argument is passed to anova1 to suppress the display of the multiple comparison test. You can remove or modify this argument according to your needs.