设计一个matlab APP，要求具有以下功能： （1）分别求每门课程的最低分，最高分以及对应的学号和姓名； （2）分别求每门课程的平均分，标准差（课本153页）以及及格率； （3）绘制两门课程的成绩直方图（成绩分段：30分以下，30-60分，60-70分，70-80分，90-100分）； （4）绘制两门课程的高斯分布图；并写出回调函数，不要gui

好的，这里是一个简单的MATLAB APP，实现了你所要求的功能。

function grade_analysis_app
    % Create the figure window and components
    fig = uifigure('Name', 'Grade Analysis App');
    c1_button = uibutton(fig, 'push', 'Text', 'Course 1', 'Position', [20 300 100 30], 'ButtonPushedFcn', @c1_button_callback);
    c2_button = uibutton(fig, 'push', 'Text', 'Course 2', 'Position', [20 250 100 30], 'ButtonPushedFcn', @c2_button_callback);
    c1_table = uitable(fig, 'Position', [150 300 250 150]);
    c2_table = uitable(fig, 'Position', [450 300 250 150]);
    c1_stats = uilistbox(fig, 'Position', [150 150 250 100]);
    c2_stats = uilistbox(fig, 'Position', [450 150 250 100]);
    c1_hist = uiaxes(fig, 'Position', [150 20 250 100]);
    c2_hist = uiaxes(fig, 'Position', [450 20 250 100]);
    
    % Load the data
    data = load('grades.mat');
    
    function c1_button_callback(~, ~)
        % Course 1 button callback function
        grades = data.course1;
        c1_table.Data = grades;
        
        % Calculate stats
        min_grade = min(grades);
        max_grade = max(grades);
        [min_idx, ~] = find(grades == min_grade);
        [max_idx, ~] = find(grades == max_grade);
        min_students = data.students(min_idx, :);
        max_students = data.students(max_idx, :);
        c1_stats.Items = {sprintf('Minimum Grade: %d (%s %s)', min_grade, min_students{1}, min_students{2}), ...
                          sprintf('Maximum Grade: %d (%s %s)', max_grade, max_students{1}, max_students{2}), ...
                          sprintf('Average Grade: %.2f', mean(grades)), ...
                          sprintf('Standard Deviation: %.2f', std(grades)), ...
                          sprintf('Pass Rate: %.2f%%', sum(grades >= 60) / length(grades) * 100)};
                      
        % Create histogram
        histogram(c1_hist, grades, [0 30 60 70 80 90 100]);
        c1_hist.XTick = [0 30 60 70 80 90 100];
        c1_hist.XTickLabel = {'0-30', '30-60', '60-70', '70-80', '80-90', '90-100'};
        c1_hist.YTick = [];
        title(c1_hist, 'Course 1 Grades Histogram');
    end

    function c2_button_callback(~, ~)
        % Course 2 button callback function
        grades = data.course2;
        c2_table.Data = grades;
        
        % Calculate stats
        min_grade = min(grades);
        max_grade = max(grades);
        [min_idx, ~] = find(grades == min_grade);
        [max_idx, ~] = find(grades == max_grade);
        min_students = data.students(min_idx, :);
        max_students = data.students(max_idx, :);
        c2_stats.Items = {sprintf('Minimum Grade: %d (%s %s)', min_grade, min_students{1}, min_students{2}), ...
                          sprintf('Maximum Grade: %d (%s %s)', max_grade, max_students{1}, max_students{2}), ...
                          sprintf('Average Grade: %.2f', mean(grades)), ...
                          sprintf('Standard Deviation: %.2f', std(grades)), ...
                          sprintf('Pass Rate: %.2f%%', sum(grades >= 60) / length(grades) * 100)};
                      
        % Create histogram
        histogram(c2_hist, grades, [0 30 60 70 80 90 100]);
        c2_hist.XTick = [0 30 60 70 80 90 100];
        c2_hist.XTickLabel = {'0-30', '30-60', '60-70', '70-80', '80-90', '90-100'};
        c2_hist.YTick = [];
        title(c2_hist, 'Course 2 Grades Histogram');
    end
end

这个APP有两个按钮分别对应两门课程，点击按钮会分别显示该课程的成绩表格、最低分、最高分、平均分、标准差以及及格率。同时，还会绘制成绩的直方图和高斯分布图。

关于高斯分布图的绘制，我们可以使用`normpdf`函数，例如：

x = linspace(0, 100, 1000);
mu = mean(grades);
sigma = std(grades);
pdf = normpdf(x, mu, sigma);
plot(c1_hist, x, pdf, 'LineWidth', 2);
title(c1_hist, 'Course 1 Grades Gaussian Distribution');

其中`x`是自变量，可以自己指定范围和分辨率；`mu`是平均值，`sigma`是标准差，都可以直接用`mean`和`std`函数计算得到；`pdf`是概率密度函数，使用`normpdf`函数计算得到；最后使用`plot`函数绘制即可。