--- a/scripts/statistics/base/center.m
+++ b/scripts/statistics/base/center.m
@@ -35,7 +35,7 @@
     print_usage ();
   endif
 
-  if (!isnumeric (x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("center: X must be a numeric vector or matrix");
   endif
 
@@ -47,10 +47,7 @@
   sz = size (x);
   if (nargin != 2)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == fix (dim))
         || !(1 <= dim && dim <= nd))
@@ -58,25 +55,28 @@
     endif
   endif
 
-  n = size (x, dim);
+  n = sz(dim);
 
   if (n == 0)
     retval = x;
   else
-    retval = bsxfun (@minus, x, sum (x, dim) / n);
+    retval = bsxfun (@minus, x, mean (x, dim));
   endif
 
 endfunction
 
 %!assert(center ([1,2,3]), [-1,0,1])
+%!assert(center (single([1,2,3])), single([-1,0,1]))
 %!assert(center (int8 ([1,2,3])), [-1,0,1])
+%!assert(center (logical ([1, 0, 0, 1])), [0.5, -0.5, -0.5, 0.5])
 %!assert(center (ones (3,2,0,2)), zeros (3,2,0,2))
+%!assert(center (ones (3,2,0,2, 'single')), zeros (3,2,0,2, 'single'))
 %!assert(center (magic (3)), [3,-4,1;-2,0,2;-1,4,-3])
+%!assert(center ([1 2 3; 6 5 4], 2), [-1 0 1; 1 0 -1])
 
 %% Test input validation
 %!error center ()
 %!error center (1, 2, 3)
-%!error center ([true true])
 %!error center (1, ones(2,2))
 %!error center (1, 1.5)
 %!error center (1, 0)

--- a/scripts/statistics/base/cor.m
+++ b/scripts/statistics/base/cor.m
@@ -35,6 +35,7 @@
 
 endfunction
 
+
 %!test
 %! x = rand (10, 2);
 %! assert (cor (x), corrcoef (x), 5*eps);

--- a/scripts/statistics/base/corrcoef.m
+++ b/scripts/statistics/base/corrcoef.m
@@ -52,16 +52,15 @@
     print_usage ();
   endif
 
-  if (! (isnumeric (x) && isnumeric (y)))
-    error ("corrcoef: X and Y must be numeric matrices or vectors");
-  endif
+  ## Input validation is done by cov.m.  Don't repeat tests here
 
-  if (ndims (x) != 2 || ndims (y) != 2)
-    error ("corrcoef: X and Y must be 2-D matrices or vectors");
-  endif
-
+  ## Special case, scalar is always 100% correlated with itself
   if (isscalar (x))
-    retval = 1;
+    if (isa (x, 'single'))
+      retval = single (1);
+    else
+      retval = 1;
+    endif
     return;
   endif
 
@@ -79,20 +78,35 @@
 
 endfunction
 
+
 %!test
 %! x = rand (10);
 %! cc1 = corrcoef (x);
 %! cc2 = corrcoef (x, x);
-%! assert((size (cc1) == [10, 10] && size (cc2) == [10, 10]
-%! && abs (cc1 - cc2) < sqrt (eps)));
+%! assert (size (cc1) == [10, 10] && size (cc2) == [10, 10]);
+%! assert (cc1, cc2, sqrt (eps));
+
+%!test
+%! x = [1:3]';
+%! y = [3:-1:1]';
+%! assert (corrcoef (x,y), -1, 5*eps)
+%! assert (corrcoef (x,flipud (y)), 1, 5*eps)
+%! assert (corrcoef ([x, y]), [1 -1; -1 1], 5*eps)
 
-%!assert(corrcoef (5), 1);
+%!test
+%! x = single ([1:3]');
+%! y = single ([3:-1:1]');
+%! assert (corrcoef (x,y), single (-1), 5*eps)
+%! assert (corrcoef (x,flipud (y)), single (1), 5*eps)
+%! assert (corrcoef ([x, y]), single ([1 -1; -1 1]), 5*eps)
+
+%!assert (corrcoef (5), 1);
+%!assert (corrcoef (single(5)), single(1));
 
 %% Test input validation
 %!error corrcoef ();
 %!error corrcoef (1, 2, 3);
-%!error corrcoef ([true, true]);
-%!error corrcoef ([1, 2], [true, true]);
+%!error corrcoef ([1; 2], ["A", "B"]);
 %!error corrcoef (ones (2,2,2));
 %!error corrcoef (ones (2,2), ones (2,2,2));
 

--- a/scripts/statistics/base/cov.m
+++ b/scripts/statistics/base/cov.m
@@ -67,7 +67,8 @@
     print_usage ();
   endif
 
-  if (! (isnumeric (x) && isnumeric (y)))
+  if (   ! (isnumeric (x) || islogical (x))
+      || ! (isnumeric (y) || islogical (y)))
     error ("cov: X and Y must be numeric matrices or vectors");
   endif
 
@@ -75,7 +76,7 @@
     error ("cov: X and Y must be 2-D matrices or vectors");
   endif
 
-  if (nargin == 2 && isscalar(y))
+  if (nargin == 2 && isscalar (y))
     opt = y;
   endif
 
@@ -83,22 +84,27 @@
     error ("cov: normalization OPT must be 0 or 1");
   endif
 
+  ## Special case, scalar has zero covariance
   if (isscalar (x))
-    c = 0;
+    if (isa (x, 'single'))
+      c = single (0);
+    else
+      c = 0;
+    endif
     return;
   endif
 
-  if (rows (x) == 1)
-    x = x';
+  if (isrow (x))
+    x = x.';
   endif
   n = rows (x);
 
-  if (nargin == 1 || isscalar(y))
+  if (nargin == 1 || isscalar (y))
     x = center (x, 1);
     c = conj (x' * x / (n - 1 + opt));
   else
-    if (rows (y) == 1)
-      y = y';
+    if (isrow (y))
+      y = y.';
     endif
     if (rows (y) != n)
       error ("cov: X and Y must have the same number of observations");
@@ -110,17 +116,36 @@
 
 endfunction
 
+
 %!test
 %! x = rand (10);
 %! cx1 = cov (x);
 %! cx2 = cov (x, x);
-%! assert(size (cx1) == [10, 10] && size (cx2) == [10, 10] && norm(cx1-cx2) < 1e1*eps);
+%! assert(size (cx1) == [10, 10] && size (cx2) == [10, 10]);
+%! assert(cx1, cx2, 1e1*eps);
+
+%!test
+%! x = [1:3]';
+%! y = [3:-1:1]';
+%! assert (cov (x,y), -1, 5*eps)
+%! assert (cov (x,flipud (y)), 1, 5*eps)
+%! assert (cov ([x, y]), [1 -1; -1 1], 5*eps)
+
+%!test
+%! x = single ([1:3]');
+%! y = single ([3:-1:1]');
+%! assert (cov (x,y), single (-1), 5*eps)
+%! assert (cov (x,flipud (y)), single (1), 5*eps)
+%! assert (cov ([x, y]), single ([1 -1; -1 1]), 5*eps)
 
 %!test
 %! x = [1:5];
 %! c = cov (x);
-%! assert(isscalar (c));
-%! assert(c, 2.5);
+%! assert (isscalar (c));
+%! assert (c, 2.5);
+
+%!assert(cov (5), 0);
+%!assert(cov (single(5)), single(0));
 
 %!test
 %! x = [1:5];
@@ -129,13 +154,10 @@
 %! c = cov (x, 1);
 %! assert(c, 2);
 
-%!assert(cov (5), 0);
-
 %% Test input validation
 %!error cov ();
 %!error cov (1, 2, 3, 4);
-%!error cov ([true, true]);
-%!error cov ([1, 2], [true, true]);
+%!error cov ([1; 2], ["A", "B"]);
 %!error cov (ones (2,2,2));
 %!error cov (ones (2,2), ones (2,2,2));
 %!error cov (1, 3);

--- a/scripts/statistics/base/gls.m
+++ b/scripts/statistics/base/gls.m
@@ -82,10 +82,21 @@
   if (rx != ry)
     error ("gls: number of rows of X and Y must be equal");
   endif
-  if (!issquare(o) || ro != ry*cy)
+  if (!issquare (o) || ro != ry*cy)
     error ("gls: matrix O must be square matrix with rows = rows (Y) * cols (Y)");
   endif
 
+  if (isinteger (x))
+    x = double (x);
+  endif
+  if (isinteger (y))
+    y = double (y);
+  endif
+  if (isinteger (o))
+    o = double (o);
+  endif
+
+  ## Start of algorithm
   o = o^(-1/2);
   z = kron (eye (cy), x);
   z = o * z;
@@ -116,7 +127,7 @@
 %! y = 3*x + 2;
 %! x = [x, ones(5,1)];
 %! o = diag (ones (5,1));
-%! assert (gls (y,x,o), [3; 2], 50*eps)
+%! assert (gls (y,x,o), [3; 2], 50*eps);
 
 %% Test input validation
 %!error gls ()

--- a/scripts/statistics/base/histc.m
+++ b/scripts/statistics/base/histc.m
@@ -61,7 +61,7 @@
     error ("histc: EDGES must be real-valued, not complex");
   else
     ## Make sure 'edges' is sorted
-    edges = edges (:);
+    edges = edges(:);
     if (!issorted (edges) || edges(1) > edges(end))
       warning ("histc: edge values not sorted on input");
       edges = sort (edges);
@@ -72,10 +72,7 @@
   sz = size (x);
   if (nargin < 3)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == fix (dim))
         || !(1 <= dim && dim <= nd))
@@ -103,25 +100,25 @@
     ## Prepare indices
     idx1 = cell (1, dim-1);
     for k = 1:length (idx1)
-      idx1 {k} = 1:sz(k);
+      idx1{k} = 1:sz(k);
     endfor
     idx2 = cell (length (sz) - dim);
     for k = 1:length (idx2)
-      idx2 {k} = 1:sz(k+dim);
+      idx2{k} = 1:sz(k+dim);
     endfor
 
     ## Compute the histograms
     for k = 1:num_edges-1
       b = (edges (k) <= x & x < edges (k+1));
-      n (idx1 {:}, k, idx2 {:}) = sum (b, dim);
+      n(idx1{:}, k, idx2{:}) = sum (b, dim);
       if (nargout > 1)
-        idx (b) = k;
+        idx(b) = k;
       endif
     endfor
     b = (x == edges (end));
-    n (idx1 {:}, num_edges, idx2 {:}) = sum (b, dim);
+    n(idx1{:}, num_edges, idx2{:}) = sum (b, dim);
     if (nargout > 1)
-      idx (b) = num_edges;
+      idx(b) = num_edges;
     endif
 
   else
@@ -160,6 +157,7 @@
 
 endfunction
 
+
 %!test
 %! x = linspace (0, 10, 1001);
 %! n = histc (x, 0:10);

--- a/scripts/statistics/base/iqr.m
+++ b/scripts/statistics/base/iqr.m
@@ -39,7 +39,7 @@
     print_usage ();
   endif
 
-  if (!(ismatrix (x) && isnumeric (x)) || isscalar(x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("iqr: X must be a numeric vector or matrix");
   endif
 
@@ -48,10 +48,7 @@
   nel = numel (x);
   if (nargin != 2)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == fix (dim))
         || !(1 <= dim && dim <= nd))
@@ -60,27 +57,33 @@
   endif
 
   ## This code is a bit heavy, but is needed until empirical_inv
-  ## takes other than vector arguments.
-  c = sz(dim);
+  ## can take a matrix, rather than just a vector argument.
+  n = sz(dim);
   sz(dim) = 1;
-  y = zeros (sz);
+  if (isa (x, 'single'))
+    y = zeros (sz, 'single');
+  else
+    y = zeros (sz);
+  endif
   stride = prod (sz(1:dim-1));
-  for i = 1 : nel / c;
+  for i = 1 : nel / n;
     offset = i;
     offset2 = 0;
     while (offset > stride)
       offset -= stride;
       offset2++;
     endwhile
-    offset += offset2 * stride * c;
-    rng = [0 : c-1] * stride + offset;
+    offset += offset2 * stride * n;
+    rng = [0 : n-1] * stride + offset;
 
-    y (i) = empirical_inv (3/4, x(rng)) - empirical_inv (1/4, x(rng));
+    y(i) = diff (empirical_inv ([1/4, 3/4], x(rng)));
   endfor
 
 endfunction
 
+
 %!assert (iqr (1:101), 50);
+%!assert (iqr (single(1:101)), single(50));
 
 %%!test
 %%! x = [1:100];
@@ -90,5 +93,6 @@
 %!error iqr ();
 %!error iqr (1, 2, 3);
 %!error iqr (1);
-%!error iqr ([true, true]);
+%!error iqr (['A'; 'B']);
 %!error iqr (1:10, 3);
+

--- a/scripts/statistics/base/kendall.m
+++ b/scripts/statistics/base/kendall.m
@@ -74,7 +74,8 @@
     print_usage ();
   endif
 
-  if (! (isnumeric (x) && isnumeric (y)))
+  if (   ! (isnumeric (x) || islogical (x))
+      || ! (isnumeric (y) || islogical (y)))
     error ("kendall: X and Y must be numeric matrices or vectors");
   endif
 
@@ -82,14 +83,14 @@
     error ("kendall: X and Y must be 2-D matrices or vectors");
   endif
 
-  if (rows (x) == 1)
-    x = x';
+  if (isrow (x))
+    x = x.';
   endif
   [n, c] = size (x);
 
   if (nargin == 2)
-    if (rows (y) == 1)
-      y = y';
+    if (isrow (y))
+      y = y.';
     endif
     if (rows (y) != n)
       error ("kendall: X and Y must have the same number of observations");
@@ -98,22 +99,36 @@
     endif
   endif
 
+  if (isa (x, 'single') || isa (y, 'single'))
+    cls = 'single';
+  else
+    cls = 'double';
+  endif
   r   = ranks (x);
-  m   = sign (kron (r, ones (n, 1)) - kron (ones (n, 1), r));
+  m   = sign (kron (r, ones (n, 1, cls)) - kron (ones (n, 1, cls), r));
   tau = corrcoef (m);
 
   if (nargin == 2)
-    tau = tau (1 : c, (c + 1) : columns (x));
+    tau = tau(1 : c, (c + 1) : columns (x));
   endif
 
 endfunction
 
 
+%!test
+%! x = [1:2:10];
+%! y = [100:10:149];
+%! assert (kendall (x,y), 1, 5*eps);
+%! assert (kendall (x,fliplr (y)), -1, 5*eps);
+
+%!assert (kendall (logical(1)), 1);
+%!assert (kendall (single(1)), single(1));
+
 %% Test input validation
 %!error kendall ();
 %!error kendall (1, 2, 3);
-%!error kendall ([true, true]);
-%!error kendall (ones(1,2), [true, true]);
+%!error kendall (['A'; 'B']);
+%!error kendall (ones(2,1), ['A'; 'B']);
 %!error kendall (ones (2,2,2));
 %!error kendall (ones (2,2), ones (2,2,2));
 %!error kendall (ones (2,2), ones (3,2));

--- a/scripts/statistics/base/kurtosis.m
+++ b/scripts/statistics/base/kurtosis.m
@@ -54,7 +54,7 @@
     print_usage ();
   endif
 
-  if (!isnumeric (x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("kurtosis: X must be a numeric vector or matrix");
   endif
 
@@ -62,10 +62,7 @@
   sz = size (x);
   if (nargin != 2)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == fix (dim))
         || !(1 <= dim && dim <= nd))
@@ -73,16 +70,14 @@
     endif
   endif
 
-  c = sz(dim);
+  n = sz(dim);
   sz(dim) = 1;
-  idx = ones (1, nd);
-  idx(dim) = c;
-  x = x - repmat (mean (x, dim), idx);
+  x = center (x, dim);  # center also promotes integer to double for next line
   retval = zeros (sz, class (x));
   s = std (x, [], dim);
+  idx = find (s > 0);
   x = sum (x.^4, dim);
-  ind = find (s > 0);
-  retval(ind) = x(ind) ./ (c * s(ind) .^ 4) - 3;
+  retval(idx) = x(idx) ./ (n * s(idx) .^ 4) - 3;
 
 endfunction
 
@@ -90,12 +85,14 @@
 %!test
 %! x = [-1; 0; 0; 0; 1];
 %! y = [x, 2*x];
-%! assert(all (abs (kurtosis (y) - [-1.4, -1.4]) < sqrt (eps)));
+%! assert (kurtosis (y), [-1.4, -1.4], sqrt (eps));
+
+%!assert (kurtosis (single(1)), single(0));
 
 %% Test input validation
 %!error kurtosis ()
 %!error kurtosis (1, 2, 3)
-%!error kurtosis (true(1,2))
+%!error kurtosis (['A'; 'B'])
 %!error kurtosis (1, ones(2,2))
 %!error kurtosis (1, 1.5)
 %!error kurtosis (1, 0)

--- a/scripts/statistics/base/logit.m
+++ b/scripts/statistics/base/logit.m
@@ -47,6 +47,7 @@
 
 endfunction
 
+
 %!test
 %! p = [0.01:0.01:0.99];
 %! assert(logit (p), log (p ./ (1-p)), 25*eps)

--- a/scripts/statistics/base/mahalanobis.m
+++ b/scripts/statistics/base/mahalanobis.m
@@ -34,7 +34,8 @@
     print_usage ();
   endif
 
-  if (! (isnumeric (x) && isnumeric (y)))
+  if (   ! (isnumeric (x) || islogical (x))
+      || ! (isnumeric (y) || islogical (y)))
     error ("mahalanobis: X and Y must be numeric matrices or vectors");
   endif
 
@@ -49,11 +50,16 @@
     error ("mahalanobis: X and Y must have the same number of columns");
   endif
 
+  if (isinteger (x))
+    x = double (x);
+  endif
+
   xm = mean (x);
   ym = mean (y);
 
-  x = x - ones (xr, 1) * xm;
-  y = y - ones (yr, 1) * ym;
+  ## Center data by subtracting means
+  x = bsxfun (@minus, x, xm);
+  y = bsxfun (@minus, y, ym);
 
   w = (x' * x + y' * y) / (xr + yr - 2);
 
@@ -63,11 +69,12 @@
 
 endfunction
 
+
 %% Test input validation
 %!error mahalanobis ();
 %!error mahalanobis (1, 2, 3);
-%!error mahalanobis ([true], [true]);
-%!error mahalanobis ([1, 2], [true, true]);
+%!error mahalanobis ('A', 'B');
+%!error mahalanobis ([1, 2], ['A', 'B']);
 %!error mahalanobis (ones (2,2,2));
 %!error mahalanobis (ones (2,2), ones (2,2,2));
 %!error mahalanobis (ones (2,2), ones (2,3));

--- a/scripts/statistics/base/mean.m
+++ b/scripts/statistics/base/mean.m
@@ -69,15 +69,15 @@
     error ("mean: X must be a numeric vector or matrix");
   endif
 
-  need_dim = 0;
+  need_dim = false;
 
   if (nargin == 1)
     opt = "a";
-    need_dim = 1;
+    need_dim = true;
   elseif (nargin == 2)
     if (ischar (opt1))
       opt = opt1;
-      need_dim = 1;
+      need_dim = true;
     else
       dim = opt1;
       opt = "a";
@@ -100,22 +100,15 @@
   sz = size (x);
   if (need_dim)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
+    (dim = find (sz > 1, 1)) || (dim = 1);
+  else
+    if (!(isscalar (dim) && dim == fix (dim))
+      || !(1 <= dim && dim <= nd))
+      error ("mean: DIM must be an integer and a valid dimension");
     endif
   endif
 
-  if (!(isscalar (dim) && dim == fix (dim))
-      || !(1 <= dim && dim <= nd))
-    error ("mean: DIM must be an integer and a valid dimension");
-  endif
-
-  if (dim > nd)
-    n = 1;
-  else
-    n = sz(dim);
-  endif
+  n = sz(dim);
 
   if (strcmp (opt, "a"))
     y = sum (x, dim) / n;
@@ -129,6 +122,7 @@
 
 endfunction
 
+
 %!test
 %! x = -10:10;
 %! y = x';
@@ -137,9 +131,12 @@
 %! assert(mean (y) == 0);
 %! assert(mean (z) == [0, 10]);
 
+%!assert(mean (magic(3), 1), [5, 5, 5]);
+%!assert(mean (magic(3), 2), [5; 5; 5]);
 %!assert(mean ([2 8], 'g'), 4);
 %!assert(mean ([4 4 2], 'h'), 3);
 %!assert(mean (logical ([1 0 1 1])), 0.75);
+%!assert(mean (single ([1 0 1 1])), single (0.75));
 
 %% Test input validation
 %!error mean ();

--- a/scripts/statistics/base/meansq.m
+++ b/scripts/statistics/base/meansq.m
@@ -52,7 +52,7 @@
     print_usage ();
   endif
 
-  if (!isnumeric (x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("mean: X must be a numeric vector or matrix");
   endif
 
@@ -60,29 +60,28 @@
   sz = size (x);
   if (nargin < 2)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
+    (dim = find (sz > 1, 1)) || (dim = 1);
+  else
+    if (!(isscalar (dim) && dim == fix (dim))
+        || !(1 <= dim && dim <= nd))
+      error ("mean: DIM must be an integer and a valid dimension");
     endif
   endif
 
-  if (!(isscalar (dim) && dim == fix (dim))
-      || !(1 <= dim && dim <= nd))
-    error ("mean: DIM must be an integer and a valid dimension");
-  endif
-
-  y = sumsq (x, dim) / size (x, dim);
+  y = sumsq (x, dim) / sz(dim);
 
 endfunction
 
 
-%!assert(meansq (1:5), 11)
-%!assert(meansq (magic (4)), [94.5, 92.5, 92.5, 94.5])
+%!assert(meansq (1:5), 11);
+%!assert(meansq (single(1:5)), single(11));
+%!assert(meansq (magic (4)), [94.5, 92.5, 92.5, 94.5]);
+%!assert(meansq (magic (4), 2), [109.5; 77.5; 77.5; 109.5]);
 
 %% Test input validation
 %!error meansq ()
 %!error meansq (1, 2, 3)
-%!error kurtosis ([true true])
+%!error meansq (['A'; 'B']);
 %!error meansq (1, ones(2,2))
 %!error meansq (1, 1.5)
 %!error meansq (1, 0)

--- a/scripts/statistics/base/median.m
+++ b/scripts/statistics/base/median.m
@@ -55,18 +55,19 @@
     print_usage ();
   endif
 
-  if (!isnumeric (x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("median: X must be a numeric vector or matrix");
   endif
 
+  if (isempty (x))
+    error ("median: X cannot be an empty matrix");
+  endif
+
   nd = ndims (x);
   sz = size (x);
-  if (nargin != 2)
+  if (nargin < 2)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == fix (dim))
         || !(1 <= dim && dim <= nd))
@@ -74,22 +75,19 @@
     endif
   endif
 
-  if (numel (x) > 0)
-    n = size (x, dim);
-    k = floor ((n+1) / 2);
-    if (mod (n, 2) == 1)
-      retval = nth_element (x, k, dim);
-    else
-      retval = mean (nth_element (x, k:k+1, dim), dim);
-    endif
-    ## Inject NaNs where needed, to be consistent with Matlab.
-    retval(any (isnan (x), dim)) = NaN;
+  n = sz(dim);
+  k = floor ((n+1) / 2);
+  if (mod (n, 2) == 1)
+    retval = nth_element (x, k, dim);
   else
-    error ("median: invalid matrix argument");
+    retval = mean (nth_element (x, k:k+1, dim), dim);
   endif
+  ## Inject NaNs where needed, to be consistent with Matlab.
+  retval(any (isnan (x), dim)) = NaN;
 
 endfunction
 
+
 %!test
 %! x = [1, 2, 3, 4, 5, 6];
 %! x2 = x';
@@ -101,13 +99,14 @@
 %! assert(median ([x2, 2*x2]) == [3.5, 7]);
 %! assert(median ([y2, 3*y2]) == [4, 12]);
 
+%!assert(median (single([1,2,3])), single(2));
 %!assert(median ([1,2,NaN;4,5,6;NaN,8,9]), [NaN, 5, NaN]);
 
 %% Test input validation
 %!error median ();
 %!error median (1, 2, 3);
 %!error median ({1:5});
-%!error median (true(1,5));
+%!error median (['A'; 'B']);
 %!error median (1, ones(2,2));
 %!error median (1, 1.5);
 %!error median (1, 0);

--- a/scripts/statistics/base/mode.m
+++ b/scripts/statistics/base/mode.m
@@ -39,18 +39,15 @@
     print_usage ();
   endif
 
-  if (!isnumeric(x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("mode: X must be a numeric vector or matrix");
   endif
 
   nd = ndims (x);
   sz = size (x);
-  if (nargin != 2)
+  if (nargin < 2)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == round (dim))
         || !(1 <= dim && dim <= nd))
@@ -78,11 +75,11 @@
   t = cat (dim, true (sz2), diff (xs, 1, dim) != 0);
 
   if (dim != 1)
-    t2 (permute (t != 0, perm)) = diff ([find(permute (t, perm))(:); prod(sz)+1]);
+    t2(permute (t != 0, perm)) = diff ([find(permute (t, perm))(:); prod(sz)+1]);
     f = max (ipermute (t2, perm), [], dim);
     xs = permute (xs, perm);
   else
-    t2 (t) = diff ([find(t)(:); prod(sz)+1]);
+    t2(t) = diff ([find(t)(:); prod(sz)+1]);
     f = max (t2, [], dim);
   endif
 
@@ -93,11 +90,12 @@
     m = zeros (sz2, class (x));
   endif
   for i = 1 : prod (sz2)
-    c{i} = xs (t2 (:, i) == f(i), i);
-    m (i) = c{i}(1);
+    c{i} = xs(t2(:, i) == f(i), i);
+    m(i) = c{i}(1);
   endfor
 endfunction
 
+
 %!test
 %! [m, f, c] = mode (toeplitz (1:5));
 %! assert (m, [1,2,2,2,1]);
@@ -116,13 +114,15 @@
 %! assert (f, sparse (f2));
 %! assert (c, cellfun (@(x) sparse (0), c2, 'uniformoutput', false));
 
-%!assert(mode([2,3,1,2,3,4],1),[2,3,1,2,3,4])
-%!assert(mode([2,3,1,2,3,4],2),2)
-%!assert(mode([2,3,1,2,3,4]),2)
+%!assert(mode ([2,3,1,2,3,4],1),[2,3,1,2,3,4]);
+%!assert(mode ([2,3,1,2,3,4],2),2);
+%!assert(mode ([2,3,1,2,3,4]),2);
+%!assert(mode (single([2,3,1,2,3,4])), single(2));
+%!assert(mode (int8([2,3,1,2,3,4])), int8(2));
 
-%!assert(mode([2;3;1;2;3;4],1),2)
-%!assert(mode([2;3;1;2;3;4],2),[2;3;1;2;3;4])
-%!assert(mode([2;3;1;2;3;4]),2)
+%!assert(mode ([2;3;1;2;3;4],1),2);
+%!assert(mode ([2;3;1;2;3;4],2),[2;3;1;2;3;4]);
+%!assert(mode ([2;3;1;2;3;4]),2);
 
 %!shared x
 %! x(:,:,1) = toeplitz (1:3);
@@ -157,7 +157,7 @@
 %!error mode ()
 %!error mode (1, 2, 3)
 %!error mode ({1 2 3})
-%!error mode (true(1,3))
+%!error mode (['A'; 'B'])
 %!error mode (1, ones(2,2))
 %!error mode (1, 1.5)
 %!error mode (1, 0)

--- a/scripts/statistics/base/moment.m
+++ b/scripts/statistics/base/moment.m
@@ -110,27 +110,27 @@
 
 function m = moment (x, p, opt1, opt2)
 
-  if ((nargin < 2) || (nargin > 4))
+  if (nargin < 2 || nargin > 4)
     print_usage ();
   endif
 
-  if (!isnumeric(x) || isempty(x) )
+  if (!(isnumeric (x) || islogical (x)) || isempty (x))
     error ("moment: X must be a non-empty numeric matrix or vector");
   endif
 
-  if (!(isnumeric(p) && isscalar(p)))
+  if (! (isnumeric (p) && isscalar (p)))
     error ("moment: P must be a numeric scalar");
   endif
 
-  need_dim = 0;
+  need_dim = false;
 
   if (nargin == 2)
     type = "";
-    need_dim = 1;
+    need_dim = true;
   elseif (nargin == 3)
     if (ischar (opt1))
       type = opt1;
-      need_dim = 1;
+      need_dim = true;
     else
       dim = opt1;
       type = "";
@@ -151,10 +151,7 @@
   sz = size (x);
   if (need_dim)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == fix (dim)) ||
         !(1 <= dim && dim <= nd))
@@ -164,10 +161,8 @@
 
   n = sz(dim);
 
-  if any (type == "c")
-    rng = ones (1, length (sz));
-    rng(dim) = sz(dim);
-    x = x - repmat (sum (x, dim), rng) / n;
+  if (any (type == "c"))
+    x = center (x, dim);
   endif
   if any (type == "a")
     x = abs (x);
@@ -178,11 +173,21 @@
 endfunction
 
 
+%!test
+%! x = rand (10);
+%! assert (moment (x,1), mean (x), 1e1*eps);
+%! assert (moment (x,2), meansq (x), 1e1*eps);
+%! assert (moment (x,1,2), mean (x,2), 1e1*eps);
+%! assert (moment (x,1,'c'), mean (center (x)), 1e1*eps);
+%! assert (moment (x,1,'a'), mean (abs (x)), 1e1*eps);
+
+%!assert (moment (single([1 2 3]),1), single(2));
+
 %% Test input validation
 %!error moment ()
 %!error moment (1)
 %!error moment (1, 2, 3, 4, 5)
-%!error moment ([true true], 2)
+%!error moment (['A'; 'B'], 2)
 %!error moment (ones(2,0,3), 2)
 %!error moment (1, true)
 %!error moment (1, ones(2,2))

--- a/scripts/statistics/base/ols.m
+++ b/scripts/statistics/base/ols.m
@@ -100,6 +100,14 @@
     error ("ols: number of rows of X and Y must be equal");
   endif
 
+  if (isinteger (x))
+    x = double (x);
+  endif
+  if (isinteger (y))
+    y = double (y);
+  endif
+
+  ## Start of algorithm
   z = x' * x;
   rnk = rank (z);
 
@@ -118,6 +126,7 @@
 
 endfunction
 
+
 %!test
 %! x = [1:5]';
 %! y = 3*x + 2;

--- a/scripts/statistics/base/ppplot.m
+++ b/scripts/statistics/base/ppplot.m
@@ -77,6 +77,7 @@
 
 endfunction
 
+
 %% Test input validation
 %!error ppplot ();
 %!error ppplot (ones(2,2));

--- a/scripts/statistics/base/prctile.m
+++ b/scripts/statistics/base/prctile.m
@@ -40,52 +40,48 @@
 ## Author: Ben Abbott <bpabbott@mac.com>
 ## Description: Matlab style prctile function.
 
-function q = prctile (x, p, dim)
+function q = prctile (x, p = [], dim)
 
   if (nargin < 1 || nargin > 3)
     print_usage ();
   endif
 
-  if (!isnumeric(x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("prctile: X must be a numeric vector or matrix");
   endif
-  if (!isnumeric(p))
-    error ("prctile: P must be a numeric vector");
+
+  if (isempty (p))
+    p = [0, 25, 50, 75, 100];
   endif
 
-  if (nargin == 1)
-    p = [0, 25, 50, 75, 100];
+  if (! (isnumeric (p) && isvector (p)))
+    error ("prctile: P must be a numeric vector");
   endif
 
   nd = ndims (x);
   if (nargin == 2)
     if (nd == 2)
-      ## If a matrix or vector, use the 1st dimension.
+      ## If a matrix or vector, always use 1st dimension.
       dim = 1;
     else
       ## If an N-d array, find the first non-singleton dimension.
-      dim = find (size(v) > 1, 1);
-      if (isempty (dim))
-        dim = 1;
-      endif
+      (dim = find (sz > 1, 1)) || (dim = 1);
     endif
   else
-    if (!(isscalar (dim) && dim == fix (dim)) ||
-        !(1 <= dim && dim <= nd))
+    if (!(isscalar (dim) && dim == fix (dim))
+        || !(1 <= dim && dim <= nd))
       error ("prctile: DIM must be an integer and a valid dimension");
     endif
   endif
 
   ## Convert from percent to decimal.
-  p = p / 100;
+  p /= 100;
 
-  ## The 5th method is compatible with Matlab.
-  method = 5;
-
-  q = quantile (x, p, dim, method);
+  q = quantile (x, p, dim);
 
 endfunction
 
+
 %!test
 %! pct = 50;
 %! q = prctile (1:4, pct, 1);
@@ -171,8 +167,9 @@
 %% Test input validation
 %!error prctile ()
 %!error prctile (1, 2, 3, 4)
-%!error prctile ([true, false], 10)
+%!error prctile (['A'; 'B'], 10)
 %!error prctile (1:10, [true, false])
+%!error prctile (1:10, ones (2,2))
 %!error prctile (1, 1, 1.5)
 %!error prctile (1, 1, 0)
 %!error prctile (1, 1, 3)

--- a/scripts/statistics/base/probit.m
+++ b/scripts/statistics/base/probit.m
@@ -27,10 +27,18 @@
 
 function y = probit (p)
 
-  if (nargin == 1)
-    y = stdnormal_inv (p);
-  else
+
+  if (nargin != 1)
     print_usage ();
   endif
 
+  y = stdnormal_inv (p);
+
 endfunction
+
+%!assert(probit([-1, 0, 0.5, 1, 2]), [NaN, -Inf, 0, Inf, NaN]);
+
+%% Test input validation
+%!error probit ()
+%!error probit (1, 2)
+

--- a/scripts/statistics/base/quantile.m
+++ b/scripts/statistics/base/quantile.m
@@ -103,18 +103,26 @@
 ## Author: Ben Abbott <bpabbott@mac.com>
 ## Description: Matlab style quantile function of a discrete/continuous distribution
 
-function q = quantile (x, p, dim = 1, method = 5)
+function q = quantile (x, p = [], dim = 1, method = 5)
 
   if (nargin < 1 || nargin > 4)
     print_usage ();
   endif
 
-  if (nargin < 2)
+  if (! (isnumeric (x) || islogical (x)))
+    error ("quantile: X must be a numeric vector or matrix");
+  endif
+
+  if (isempty (p))
     p = [0.00 0.25, 0.50, 0.75, 1.00];
   endif
 
-  if (!(isscalar (dim) && dim == fix (dim)) ||
-      !(1 <= dim && dim <= ndims (x)))
+  if (! (isnumeric (p) && isvector (p)))
+    error ("quantile: P must be a numeric vector");
+  endif
+
+  if (!(isscalar (dim) && dim == fix (dim))
+      || !(1 <= dim && dim <= ndims (x)))
     error ("quantile: DIM must be an integer and a valid dimension");
   endif
 
@@ -143,6 +151,7 @@
 
 endfunction
 
+
 %!test
 %! p = 0.5;
 %! x = sort (rand (11));
@@ -282,9 +291,14 @@
 %% Test input validation
 %!error quantile ()
 %!error quantile (1, 2, 3, 4, 5)
+%!error quantile (['A'; 'B'], 10)
+%!error quantile (1:10, [true, false])
+%!error quantile (1:10, ones (2,2))
 %!error quantile (1, 1, 1.5)
 %!error quantile (1, 1, 0)
 %!error quantile (1, 1, 3)
+%!error quantile ((1:5)', 0.5, 1, 0)
+%!error quantile ((1:5)', 0.5, 1, 10)
 
 ## For the cumulative probability values in @var{p}, compute the
 ## quantiles, @var{q} (the inverse of the cdf), for the sample, @var{x}.
@@ -304,41 +318,35 @@
     print_usage ();
   endif
 
-  if (!isnumeric (x))
-    error ("quantile: X must be a numeric vector or matrix");
-  endif
-
-  if (isinteger (x))
+  if (isinteger (x) || islogical (x))
     x = double (x);
   endif
 
-  ## Save length and set shape of quantiles.
-  n = numel (p);
+  ## set shape of quantiles to column vector.
   p = p(:);
 
   ## Save length and set shape of samples.
   ## FIXME: does sort guarantee that NaN's come at the end?
   x = sort (x);
   m = sum (! isnan (x));
-  mx = size (x, 1);
-  nx = size (x, 2);
+  [xr, xc] = size (x);
 
   ## Initialize output values.
-  inv = Inf(class (x)) * (-(p < 0) + (p > 1));
-  inv = repmat (inv, 1, nx);
+  inv = Inf (class (x)) * (-(p < 0) + (p > 1));
+  inv = repmat (inv, 1, xc);
 
   ## Do the work.
-  if (any(k = find((p >= 0) & (p <= 1))))
+  if (any (k = find ((p >= 0) & (p <= 1))))
     n = length (k);
-    p = p (k);
-    ## Special case.
-    if (mx == 1)
+    p = p(k);
+    ## Special case of 1 row.
+    if (xr == 1)
       inv(k,:) = repmat (x, n, 1);
-      return
+      return;
     endif
 
     ## The column-distribution indices.
-    pcd = kron (ones (n, 1), mx*(0:nx-1));
+    pcd = kron (ones (n, 1), xr*(0:xc-1));
     mm = kron (ones (n, 1), m);
     switch (method)
       case {1, 2, 3}
@@ -379,7 +387,7 @@
             p = kron (p, m-1) + 1;
 
           case 8
-            ## Median unbiased .
+            ## Median unbiased.
             p = kron (p, m+1/3) + 1/3;
 
           case 9
@@ -391,7 +399,7 @@
         endswitch
 
         ## Duplicate single values.
-        imm1 = mm == 1;
+        imm1 = (mm == 1);
         x(2,imm1) = x(1,imm1);
 
         ## Interval indices.

--- a/scripts/statistics/base/range.m
+++ b/scripts/statistics/base/range.m
@@ -37,20 +37,24 @@
 
 function y = range (x, dim)
 
+  if (nargin < 1 || nargin > 2)
+    print_usage ();
+  endif
+
   if (nargin == 1)
     y = max (x) - min (x);
-  elseif (nargin == 2)
+  else
     y = max (x, [], dim) - min (x, [], dim);
-  else
-    print_usage ();
   endif
 
 endfunction
 
-%!assert(range (1:10), 9)
-%!assert(range (magic (3)), [5, 8, 5])
-%!assert(range (magic (3), 2), [7; 4; 7])
-%!assert(range (2), 0)
+
+%!assert(range (1:10), 9);
+%!assert(range (single(1:10)), single(9));
+%!assert(range (magic (3)), [5, 8, 5]);
+%!assert(range (magic (3), 2), [7; 4; 7]);
+%!assert(range (2), 0);
 
 %% Test input validation
 %!error range ()

--- a/scripts/statistics/base/ranks.m
+++ b/scripts/statistics/base/ranks.m
@@ -37,7 +37,7 @@
     print_usage ();
   endif
 
-  if (!isnumeric(x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("ranks: X must be a numeric vector or matrix");
   endif
 
@@ -45,10 +45,7 @@
   sz = size (x);
   if (nargin != 2)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == fix (dim))
         || !(1 <= dim && dim <= nd))
@@ -89,18 +86,18 @@
 endfunction
 
 
-%!assert(ranks (1:2:10), 1:5)
-%!assert(ranks (10:-2:1), 5:-1:1)
-%!assert(ranks ([2, 1, 2, 4]), [2.5, 1, 2.5, 4])
-%!assert(ranks (ones(1, 5)), 3*ones(1, 5))
-%!assert(ranks (1e6*ones(1, 5)), 3*ones(1, 5))
-%!assert(ranks (rand (1, 5), 1), ones(1, 5))
+%!assert(ranks (1:2:10), 1:5);
+%!assert(ranks (10:-2:1), 5:-1:1);
+%!assert(ranks ([2, 1, 2, 4]), [2.5, 1, 2.5, 4]);
+%!assert(ranks (ones(1, 5)), 3*ones(1, 5));
+%!assert(ranks (1e6*ones(1, 5)), 3*ones(1, 5));
+%!assert(ranks (rand (1, 5), 1), ones(1, 5));
 
 %% Test input validation
 %!error ranks ()
 %!error ranks (1, 2, 3)
 %!error ranks ({1, 2})
-%!error ranks (true(2,1))
+%!error ranks (['A'; 'B'])
 %!error ranks (1, 1.5)
 %!error ranks (1, 0)
 %!error ranks (1, 3)

--- a/scripts/statistics/base/run_count.m
+++ b/scripts/statistics/base/run_count.m
@@ -36,7 +36,7 @@
     print_usage ();
   endif
 
-  if (!isnumeric(x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("run_count: X must be a numeric vector or matrix");
   endif
 
@@ -48,10 +48,7 @@
   sz = size (x);
   if (nargin != 3)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == fix (dim))
         || !(1 <= dim && dim <= nd))
@@ -59,6 +56,7 @@
     endif
   endif
 
+  ## Algorithm works on rows.  Permute array if necessary, ipermute back at end
   if (dim != 1)
     perm = [1 : nd];
     perm(1) = dim;
@@ -76,7 +74,7 @@
   infvec = Inf ([1, sz(2 : end)]);
 
   ind = find (diff ([infvec; x; -infvec]) < 0);
-  tmp(ind(2:end) - 1) = diff(ind);
+  tmp(ind(2:end) - 1) = diff (ind);
   tmp = tmp(idx{:});
 
   sz(1) = n;
@@ -86,7 +84,7 @@
     retval(idx{:}) = sum (tmp == k);
   endfor
   idx{1} = n;
-  retval (idx{:}) = sum (tmp >= n);
+  retval(idx{:}) = sum (tmp >= n);
 
   if (dim != 1)
     retval = ipermute (retval, perm);
@@ -105,7 +103,7 @@
 %!error run_count (1)
 %!error run_count (1, 2, 3, 4)
 %!error run_count ({1, 2}, 3)
-%!error run_count (true(3), 3)
+%!error run_count (['A'; 'A'; 'B'], 3)
 %!error run_count (1:5, ones(2,2))
 %!error run_count (1:5, 1.5)
 %!error run_count (1:5, -2)

--- a/scripts/statistics/base/runlength.m
+++ b/scripts/statistics/base/runlength.m
@@ -30,11 +30,12 @@
 ## @end deftypefn
 
 function [count, value] = runlength (x)
+
   if (nargin != 1)
     print_usage ();
   endif
 
-  if (!isnumeric (x) || !isvector (x))
+  if (!(isnumeric (x) || islogical (x)) || !isvector (x))
     error ("runlength: X must be a numeric vector");
   endif
 
@@ -47,8 +48,10 @@
   if (nargout == 2)
     value = x(idx);
   endif
+
 endfunction
 
+
 %!assert (runlength([2 2 0 4 4 4 0 1 1 1 1]), [2 1 3 1 4]);
 %!assert (runlength([2 2 0 4 4 4 0 1 1 1 1]'), [2 1 3 1 4]);
 %!test
@@ -59,5 +62,5 @@
 %% Test input validation
 %!error runlength ()
 %!error runlength (1, 2)
-%!error runlength (true(1,2))
+%!error runlength (['A'; 'B'])
 %!error runlength (ones(2,2))

--- a/scripts/statistics/base/skewness.m
+++ b/scripts/statistics/base/skewness.m
@@ -51,7 +51,7 @@
     print_usage ();
   endif
 
-  if (!isnumeric(x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("skewness: X must be a numeric vector or matrix");
   endif
 
@@ -59,10 +59,7 @@
   sz = size (x);
   if (nargin != 2)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == round (dim))
         || !(1 <= dim && dim <= nd))
@@ -70,19 +67,18 @@
     endif
   endif
 
-  c = sz(dim);
-  idx = ones (1, nd);
-  idx(dim) = c;
-  x = x - repmat (mean (x, dim), idx);
+  n = sz(dim);
   sz(dim) = 1;
+  x = center (x, dim);  # center also promotes integer to double for next line
   retval = zeros (sz, class (x));
   s = std (x, [], dim);
-  ind = find (s > 0);
+  idx = find (s > 0);
   x = sum (x .^ 3, dim);
-  retval(ind) = x(ind) ./ (c * s(ind) .^ 3);
+  retval(idx) = x(idx) ./ (n * s(idx) .^ 3);
 
 endfunction
 
+
 %!assert(skewness ([-1,0,1]), 0);
 %!assert(skewness ([-2,0,1]) < 0);
 %!assert(skewness ([-1,0,2]) > 0);
@@ -92,10 +88,12 @@
 %! y = [x, 2*x];
 %! assert(all (abs (skewness (y) - [0.75, 0.75]) < sqrt (eps)));
 
+%!assert (skewness (single(1)), single(0));
+
 %% Test input validation
 %!error skewness ()
 %!error skewness (1, 2, 3)
-%!error skewness ([true true])
+%!error skewness (['A'; 'B'])
 %!error skewness (1, ones(2,2))
 %!error skewness (1, 1.5)
 %!error skewness (1, 0)

--- a/scripts/statistics/base/spearman.m
+++ b/scripts/statistics/base/spearman.m
@@ -39,11 +39,12 @@
 
 function rho = spearman (x, y = [])
 
-  if ((nargin < 1) || (nargin > 2))
+  if (nargin < 1 || nargin > 2)
     print_usage ();
   endif
 
-  if (! (isnumeric (x) && isnumeric (y)))
+  if (   ! (isnumeric (x) || islogical (x))
+      || ! (isnumeric (y) || islogical (y)))
     error ("spearman: X and Y must be numeric matrices or vectors");
   endif
 
@@ -51,30 +52,43 @@
     error ("spearman: X and Y must be 2-D matrices or vectors");
   endif
 
-  if (rows (x) == 1)
-    x = x';
+  if (isrow (x))
+    x = x.';
   endif
-  n = rows (x);
 
   if (nargin == 1)
     rho = corrcoef (ranks (x));
   else
-    if (rows (y) == 1)
-      y = y';
+    if (isrow (y))
+      y = y.';
     endif
-    if (rows (y) != n)
+    if (rows (x) != rows (y))
       error ("spearman: X and Y must have the same number of observations");
     endif
     rho = corrcoef (ranks (x), ranks (y));
   endif
 
+  ## Restore class cleared by ranks
+  if (isa (x, 'single') || isa (y, 'single'))
+    rho = single (rho);
+  endif
+
 endfunction
 
+
+%!test
+%! x = 1:10;
+%! y = exp (x);
+%! assert (spearman (x,y), 1, 5*eps);
+%! assert (spearman (x,-y), -1, 5*eps);
+
+%!assert(spearman ([1 2 3], [-1 1 -2]), -0.5, 5*eps)
+
 %% Test input validation
 %!error spearman ();
 %!error spearman (1, 2, 3);
-%!error spearman ([true, true]);
-%!error spearman (ones(1,2), [true, true]);
+%!error spearman (['A'; 'B']);
+%!error spearman (ones(1,2), {1, 2});
 %!error spearman (ones (2,2,2));
 %!error spearman (ones (2,2), ones (2,2,2));
 %!error spearman (ones (2,2), ones (3,2));

--- a/scripts/statistics/base/statistics.m
+++ b/scripts/statistics/base/statistics.m
@@ -38,7 +38,7 @@
     print_usage ();
   endif
 
-  if (!isnumeric(x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("statistics: X must be a numeric vector or matrix");
   endif
 
@@ -46,10 +46,7 @@
   sz = size (x);
   if (nargin != 2)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == round (dim))
         || !(1 <= dim && dim <= nd))
@@ -68,16 +65,22 @@
 
 endfunction
 
+
 %!test
-%! x = rand(7,5);
+%! x = rand (7,5);
 %! s = statistics (x);
-%! m = median (x);
-%! assert (m, s(3,:), eps);
+%! assert (min (x), s(1,:), eps);
+%! assert (median (x), s(3,:), eps);
+%! assert (max (x), s(5,:), eps);
+%! assert (mean (x), s(6,:), eps);
+%! assert (std (x), s(7,:), eps);
+%! assert (skewness (x), s(8,:), eps);
+%! assert (kurtosis (x), s(9,:), eps);
 
 %% Test input validation
 %!error statistics ()
 %!error statistics (1, 2, 3)
-%!error statistics ([true true])
+%!error statistics (['A'; 'B'])
 %!error statistics (1, ones(2,2))
 %!error statistics (1, 1.5)
 %!error statistics (1, 0)

--- a/scripts/statistics/base/std.m
+++ b/scripts/statistics/base/std.m
@@ -67,7 +67,7 @@
     print_usage ();
   endif
 
-  if (! (isnumeric (x)))
+  if (! (isnumeric (x) || islogical (x)))
     error ("std: X must be a numeric vector or matrix");
   endif
 
@@ -78,18 +78,25 @@
     error ("std: normalization OPT must be 0 or 1");
   endif
 
+  nd = ndims (x);
   sz = size (x);
   if (nargin < 3)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
+    (dim = find (sz > 1, 1)) || (dim = 1);
+  else
+    if (!(isscalar (dim) && dim == fix (dim))
+        || !(1 <= dim && dim <= nd))
+      error ("std: DIM must be an integer and a valid dimension");
     endif
   endif
 
-  n = size (x, dim);
+  n = sz(dim);
   if (n == 1)
-    retval = zeros (sz);
+    if (isa (x, 'single'))
+      retval = zeros (sz, 'single');
+    else
+      retval = zeros (sz);
+    endif
   elseif (numel (x) > 0)
     retval = sqrt (sumsq (center (x, dim), dim) / (n - 1 + opt));
   else
@@ -102,14 +109,20 @@
 %!test
 %! x = ones (10, 2);
 %! y = [1, 3];
-%! assert(std (x) == [0, 0] && abs (std (y) - sqrt (2)) < sqrt (eps));
-%! assert (std (x, 0, 3), zeros (10, 2))
-%! assert (std (ones (3, 1, 2), 0, 2), zeros (3, 1, 2))
+%! assert(std (x) == [0, 0]);
+%! assert(std (y), sqrt (2), sqrt (eps));
+%! assert(std (x, 0, 2), zeros (10, 1));
+
+%!assert(std (ones (3, 1, 2), 0, 2), zeros (3, 1, 2));
+%!assert(std ([1 2], 0), sqrt(2)/2, 5*eps);
+%!assert(std ([1 2], 1), 0.5, 5*eps);
+%!assert(std(1), 0);
+%!assert(std(single(1)), single(0));
 
 %% Test input validation
 %!error std ();
 %!error std (1, 2, 3, 4);
-%!error std (true(1,2))
+%!error std (['A'; 'B'])
 %!error std (1, -1);
 %!error std ([], 1);
 

--- a/scripts/statistics/base/table.m
+++ b/scripts/statistics/base/table.m
@@ -60,6 +60,7 @@
 
 endfunction
 
+
 %% Test input validation
 %!error table ()
 %!error table (1, 2, 3)

--- a/scripts/statistics/base/var.m
+++ b/scripts/statistics/base/var.m
@@ -64,7 +64,7 @@
     print_usage ();
   endif
 
-  if (!isnumeric (x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("var: X must be a numeric vector or matrix");
   endif
 
@@ -75,16 +75,25 @@
     error ("var: normalization OPT must be 0 or 1");
   endif
 
+  nd = ndims (x);
+  sz = size (x);
   if (nargin < 3)
-    dim = find (size (x) > 1, 1);
-    if (isempty (dim))
-      dim = 1;
+    ## Find the first non-singleton dimension.
+    (dim = find (sz > 1, 1)) || (dim = 1);
+  else
+    if (!(isscalar (dim) && dim == fix (dim))
+        || !(1 <= dim && dim <= nd))
+      error ("var: DIM must be an integer and a valid dimension");
     endif
   endif
 
-  n = size (x, dim);
+  n = sz(dim);
   if (n == 1)
-    retval = zeros (size (x), class (x));
+    if (isa (x, 'single'))
+      retval = zeros (sz, 'single');
+    else
+      retval = zeros (sz);
+    endif
   elseif (numel (x) > 0)
     retval = sumsq (center (x, dim), dim) / (n - 1 + opt);
   else
@@ -93,15 +102,17 @@
 
 endfunction
 
-%!assert (var (13), 0)
-%!assert (var ([1,2,3]), 1)
-%!assert (var ([1,2,3], 1), 2/3, eps)
-%!assert (var ([1,2,3], [], 1), [0,0,0])
+
+%!assert(var (13), 0);
+%!assert(var (single(13)), single(0));
+%!assert(var ([1,2,3]), 1);
+%!assert(var ([1,2,3], 1), 2/3, eps);
+%!assert(var ([1,2,3], [], 1), [0,0,0]);
 
 %% Test input validation
 %!error var ()
 %!error var (1,2,3,4)
-%!error var (true(1,2))
+%!error var (['A'; 'B'])
 %!error var (1, -1);
 %!error var ([],1)
 

--- a/scripts/statistics/base/zscore.m
+++ b/scripts/statistics/base/zscore.m
@@ -31,28 +31,21 @@
 ## Author: KH <Kurt.Hornik@wu-wien.ac.at>
 ## Description: Subtract mean and divide by standard deviation
 
-function t = zscore (x, dim)
+function z = zscore (x, dim)
 
   if (nargin != 1 && nargin != 2)
     print_usage ();
   endif
 
-  if (! isnumeric(x))
+  if (! (isnumeric (x) || islogical (x)))
     error ("zscore: X must be a numeric vector or matrix");
   endif
 
-  if (isinteger (x))
-    x = double (x);
-  endif
-
   nd = ndims (x);
   sz = size (x);
   if (nargin != 2)
     ## Find the first non-singleton dimension.
-    dim = find (sz > 1, 1);
-    if (isempty (dim))
-      dim = 1;
-    endif
+    (dim = find (sz > 1, 1)) || (dim = 1);
   else
     if (!(isscalar (dim) && dim == fix (dim))
         || !(1 <= dim && dim <= nd))
@@ -60,27 +53,30 @@
     endif
   endif
 
-  c = sz(dim);
-  if (c == 0)
-    t = x;
+  n = sz(dim);
+  if (n == 0)
+    z = x;
   else
-    idx = ones (1, nd);
-    idx(dim) = c;
-    t = x - repmat (mean (x, dim), idx);
-    t = t ./ repmat (max (cat (dim, std(t, [], dim), ! any (t, dim)), [], dim), idx);
+    x = center (x, dim); # center also promotes integer to double for next line
+    z = zeros (sz, class (x));
+    s = std (x, [], dim);
+    s(s==0) = 1;
+    z = bsxfun (@rdivide, x, s);
   endif
 
 endfunction
 
+
 %!assert(zscore ([1,2,3]), [-1,0,1])
-%!assert(zscore (int8 ([1,2,3])), [-1,0,1])
-#%!assert(zscore (ones (3,2,0,2)), zeros (3,2,0,2))
+%!assert(zscore (single([1,2,3])), single([-1,0,1]))
+%!assert(zscore (int8([1,2,3])), [-1,0,1])
+%!assert(zscore (ones (3,2,2,2)), zeros (3,2,2,2))
 %!assert(zscore ([2,0,-2;0,2,0;-2,-2,2]), [1,0,-1;0,1,0;-1,-1,1])
 
 %% Test input validation
 %!error zscore ()
 %!error zscore (1, 2, 3)
-%!error zscore ([true true])
+%!error zscore (['A'; 'B'])
 %!error zscore (1, ones(2,2))
 %!error zscore (1, 1.5)
 %!error zscore (1, 0)

--- a/scripts/statistics/distributions/logistic_inv.m
+++ b/scripts/statistics/distributions/logistic_inv.m
@@ -31,7 +31,11 @@
     print_usage ();
   endif
 
-  inv = zeros (size (x));
+  if (isa (x, 'single'))
+    inv = zeros (size (x), 'single');
+  else
+    inv = zeros (size (x));
+  endif
 
   k = find ((x < 0) | (x > 1) | isnan (x));
   if (any (k))