正态性作图：
密度函数pdf

>> x=50:150;
>> y=normpdf(x,100,5);
>> plot(x,y);
>> hold on;                                      %使得图像具有刷新能力
>> y2=normpdf(x,100,10);
>> plot(x,y2);
>> legend('sigma=5','sigma=10');      %标两个标志
>> hold off;                                        %使得图像不轻易被刷新

分布函数cdf

>> x=50:100;
>> clear
>> x=50:150;
>> y1=normcdf(x,100,5);
>> plot(x,y1);
>> hold on;
>> y2=normcdf(x,100,10);
>> plot(x,y2);
>> legend('sigma=5','sigma=10');
>> hold off
>> 

K-S方法检验正态性

x=[97 130 156.5 135.2 137.7 180.5 205.2 190 188.6 196.7 180.3 210.8 196 223 238.2 263.5 292.6 317 335.4 327 321.9 253.5 297.8 436.8 465.7 476.7 462.6 460.8 501.8 501.5 489.5 542.3 512.2 559.8 542 567];
x=x';                  %转换成列向量
alpha=0.05;      %设定测定水平
[mu,sigma]=normfit(x);         %返回向量的mu和sigma
p1=normcdf(x,mu,sigma);    %根据样本算出均值方差和向量估计每个点分布函数对应的值
[h0,s1,ks,cv] = kstest(x,[x,p1],alpha);   

h0 = 

     0                                        %接受原假设

s1 =                                           

    0.3069                                     %0.1567往右走的概率为0.3069就接受原假设

ks =

    0.1567


cv =                                          %临界值       

    0.2212