diff --git a/statistics/exercises/correlationsignificance.m b/statistics/exercises/correlationsignificance.m
new file mode 100644
index 0000000..7a0f5f0
--- /dev/null
+++ b/statistics/exercises/correlationsignificance.m
@@ -0,0 +1,49 @@
+%% (a) generate correlated data
+n=1000;
+a=0.2;
+x = randn(n, 1);
+y = randn(n, 1) + a*x;
+
+%% (b) scatter plot:
+subplot(1, 2, 1);
+%scatter(x, y );   % either scatter ...
+plot(x, y, 'o' );  % ... or plot - same plot.
+
+%% (d) correlation coefficient:
+rd = corr(x, y);
+%rd = r(0, 1);
+fprintf('correlation coefficient = %.2f\n', rd );
+
+%% (f) permutation:
+nperm = 1000;
+rs = zeros(nperm,1);
+for i=1:nperm
+    xr=x(randperm(length(x)));  % shuffle x
+    yr=y(randperm(length(y)));  % shuffle y
+    rs(i) = corr(xr, yr);
+    %rs(i) = r(0,1);
+end
+
+%% (g) pdf of the correlation coefficients:
+[h,b] = hist(rs, 20 );
+h = h/sum(h)/(b(2)-b(1));  % normalization
+
+%% (h) significance:
+rq = quantile(rs, 0.95);
+fprintf('correlation coefficient at 5%% significance = %.2f\n', rq );
+if rd >= rq
+    fprintf('--> correlation r=%.2f is significant\n', rd);
+else
+    fprintf('--> r=%.2f is not a significant correlation\n', rd);
+end
+
+%% plot:
+subplot(1, 2, 2)
+hold on;
+bar(b, h, 'facecolor', 'b');
+bar(b(b>=rq), h(b>=rq), 'facecolor', 'r');
+plot( [rd rd], [0 4], 'r', 'linewidth', 2 );
+xlabel('correlation coefficient');
+ylabel('probability density');
+hold off;
+