%%
%1.拿出数值
load stockreturns;
x4 = stocks(:,4);
%mean平均数
mean(x4)
%median中位数
median(x4)
%mode数据集中最多的值
mode(x4)
%prctile数据集的百分比
prctile(x4)
%max最大值
max(x4)
%min最小值
min(x4)
%std标准方差
std(x4)
%var方差
var(x4)

%%
%统计图表
x = 1:14;
freqy = [1 0 1 0 4 0 1 0 3 1 0 0 1 1];
subplot(1,3,1); bar(x,freqy); xlim([0 15]);
subplot(1,3,2); area(x,freqy); xlim([0 15]);
subplot(1,3,3); stem(x,freqy); xlim([0 15]);

%%
%box图表
marks = [80 81 81 84 88 92 92 94 96 97];
boxplot(marks)
prctile(marks, [25 50 75])
%box图表（stocks中的数据）
boxplot(stocks)

%%
%skewness偏斜状态图
X = randn([10 3])*3;
X(X(:,1)<0, 1) = 0; X(X(:,3)>0, 3) = 0;
boxplot(X, {'Right-skewed', 'Symmetric', 'Left-skewed'});
y = skewness(X)

%%
%exercise
y = skewness(stocks)
k = kurtosis(stocks)
boxplot(y,k)

%%
%置信区间
load stockreturns;
x1 = stocks(:,3); x2 = stocks(:,10);
boxplot([x1, x2], {'3', '10'});
[h,p] = ttest2(x1, x2)