% % % Figure caption: The effect of the transformation y = a + bx % operating on a normally distributed random variable X having % mean muX and standard deviation sigmaX. The random variable Y = % a + bX is again normally distributed, with mean muY = a + b*muX % and standard deviation sigmaY = |b| sigmaX. The normal % distributions are displayed on the x and y axes; the linear % transformation is displayed as a line, which passes through the % point (muX, muY) so that it may be written, equivalently, as y - % muY = b(x - muX). % For Y = a + b*X, we use a = 0, b = 0.7. a = 0; b = 0.7; % Set up normal random variable X. xMu = 3; xSd = 0.35; % Set Y up as transformation of X. yMu = b*xMu+a; ySd = abs(b)*xSd; xMax = 2*xMu; % Used for setting x-axes. % Get a reasonable range of values to evaluate the PDF. xValues = (xMu - 4*xSd) : 0.01 : (xMu + 4*xSd) ; yValues = a + b * xValues; xDensity = normpdf(xValues, xMu, xSd); yDensity = normpdf(yValues, yMu, ySd); % Plot x first. plot(xValues, xDensity, 'k', 'LineWidth', 3) hold on; % Add y. plot(yDensity, yValues, 'k', 'LineWidth', 3) % Add lines from the mean of x and y to where they meet. line([xMu, xMu], [0, yMu], 'LineStyle', ':', ... 'Color', [0.8, 0.8, 0.8], 'LineWidth', 3) line([0, xMu], [yMu, yMu], 'LineStyle', ':', ... 'Color', [0.8, 0.8, 0.8], 'LineWidth', 3) % Set figure style. text(2.1, 3.1, '$\it{y}-\mu_y = b(x-\mu_x)$', ... 'FontSize', 22, 'Interpreter', 'LaTex') set(gca, 'Box', 'off', ... 'XLim', [0, xMax], 'YLim', [0, b*xMax+a], ... 'XTick', [], 'YTick', [], ... 'XColor', 'w', 'YColor', 'w') transformationLine = refline(b, a); set(transformationLine, 'Color', 'k', 'LineWidth', 3) set(gca, 'Ylim', [0, b*xMax+a-0.3]) xlabel('$\it\mu_x$', 'FontSize', 22, 'Color', 'k', 'Interpreter', 'LaTex') ylabel('$\it\mu_y$', 'FontSize', 22, 'Color', 'k', 'Interpreter', 'LaTex', ... 'Rotation', 0) xlabh = get(gca, 'XLabel'); ylabh = get(gca, 'YLabel'); set(xlabh, 'Position', [xMu, -0.07]); set(ylabh, 'Position', [-0.2, 2]); % Close and set position. set(gcf, 'Position', [100, 100, 1100, 800])