undo homogenous changes

functions/sigprocfunc/transformcoords.m

@@ -100,7 +100,7 @@
         % pitch roll yaw rotation
         % -----------------------
         % pitch (x-axis); roll = y axis rotation; yaw = z axis
-        % see http://bishopw.loni.ucla.edu/AIR5/homogeneous.html
+        % see http://bishopw.loni.ucla.edu/AIR5/homogenous.html
         cp = cos(pitch); sp = sin(pitch);
         cr = cos(roll);  sr = sin(roll);
         cy = cos(yaw);   sy = sin(yaw);

functions/statistics/statcond.m

@@ -49,7 +49,7 @@
 %   'variance' = ['homegenous'|'inhomogenous'] this option is exclusively
 %                for parametric statistics using unpaired t-test. It allows
 %                to compute a more accurate value for the degree of freedom
-%                using the formula for inhomogeneous variance (see
+%                using the formula for inhomogenous variance (see
 %                ttest2_cell function). Default is 'inhomegenous'.
 %   'surrog'   = surrogate data array (see output).
 %   'stats'    = F- or T-value array (see output).
@@ -559,11 +559,11 @@
 
 % compute t-test
 % -------------------
-function [t, df] = ttest_cell_select( res, paired, homogeneous)
+function [t, df] = ttest_cell_select( res, paired, homogenous)
     if strcmpi(paired,'on')
         [t, df] = ttest_cell( res{1}, res{2});
     else
-        [t, df] = ttest2_cell( res{1}, res{2}, homogeneous);
+        [t, df] = ttest2_cell( res{1}, res{2}, homogenous);
     end
 
 % function to compute the number of dimensions

functions/statistics/ttest2_cell.m

@@ -10,8 +10,8 @@
 %   a,b       = data consisting of UNPAIRED arrays to be compared. The last 
 %               dimension of the data array is used to compute the t-test.
 %   'inhomogenous' = use computation for the degree of freedom using 
-%                    inhomogeneous variance. By default the computation of
-%                    the degree of freedom is done with homogeneous
+%                    inhomogenous variance. By default the computation of
+%                    the degree of freedom is done with homogenous
 %                    variances.
 %
 % Outputs:
@@ -36,7 +36,7 @@
 %
 % Author: Arnaud Delorme, SCCN/INC/UCSD, La Jolla, 2005
 %         (thank you to G. Rousselet for providing the formula for 
-%         inhomogeneous variances).
+%         inhomogenous variances).
 %
 % Reference:
 %   Schaum's outlines in statistics (3rd edition). 1999. Mc Graw-Hill.
@@ -76,19 +76,19 @@
         return;
     end
 
-    homogeneous = 'homogeneous';
+    homogenous = 'homogenous';
     if nargin > 1 && ischar(b)
-        homogeneous = b;
+        homogenous = b;
     end
     if nargin > 2 && ischar(c)
-        homogeneous = c;
+        homogenous = c;
     end
     if iscell(a), 
         b = a{2}; 
         a = a{1}; 
     end
-    if ~strcmpi(homogeneous, 'inhomogenous') && ~strcmpi(homogeneous, 'homogeneous')
-        error('Value for homogeneous parameter can only be ''homogeneous'' or ''inhomogenous''');
+    if ~strcmpi(homogenous, 'inhomogenous') && ~strcmpi(homogenous, 'homogenous')
+        error('Value for homogenous parameter can only be ''homogenous'' or ''inhomogenous''');
     end
 
     nd    = myndims(a);
@@ -97,8 +97,8 @@
     meana = mymean(a, nd);
     meanb = mymean(b, nd);
 
-    if strcmpi(homogeneous, 'inhomogenous')
-        % inhomogeneous variance from Howel, 2009, "Statistical Methods for Psychology"
+    if strcmpi(homogenous, 'inhomogenous')
+        % inhomogenous variance from Howel, 2009, "Statistical Methods for Psychology"
         % thank you to G. Rousselet for providing these formulas
         m  = meana - meanb;
         s1 = var(a,0,nd) ./ na;