机器学习的数学基础
高等数学
导数定义
导数和微分的概念
%3D%5Cunderset%7B%5CDelta%20x%5Cto%200%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf(%7B%7Bx%7D%7B0%7D%7D%2B%5CDelta%20x)-f(%7B%7Bx%7D%7B0%7D%7D)%7D%7B%5CDelta%20x%7D#card=math&code=f%27%28%7B%7Bx%7D%7B0%7D%7D%29%3D%5Cunderset%7B%5CDelta%20x%5Cto%200%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf%28%7B%7Bx%7D%7B0%7D%7D%2B%5CDelta%20x%29-f%28%7B%7Bx%7D_%7B0%7D%7D%29%7D%7B%5CDelta%20x%7D&id=WcEAT) (1)
或者:
%3D%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf(x)-f(%7B%7Bx%7D%7B0%7D%7D)%7D%7Bx-%7B%7Bx%7D%7B0%7D%7D%7D#card=math&code=f%27%28%7B%7Bx%7D%7B0%7D%7D%29%3D%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf%28x%29-f%28%7B%7Bx%7D%7B0%7D%7D%29%7D%7Bx-%7B%7Bx%7D_%7B0%7D%7D%7D&id=ya1wG) (2)
左右导数导数的几何意义和物理意义
函数#card=math&code=f%28x%29&id=B1Pio)在
处的左、右导数分别定义为:
左导数:%3D%5Cunderset%7B%5CDelta%20x%5Cto%20%7B%7B0%7D%5E%7B-%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf(%7B%7Bx%7D%7B0%7D%7D%2B%5CDelta%20x)-f(%7B%7Bx%7D%7B0%7D%7D)%7D%7B%5CDelta%20x%7D%3D%5Cunderset%7Bx%5Cto%20x%7B0%7D%5E%7B-%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf(x)-f(%7B%7Bx%7D%7B0%7D%7D)%7D%7Bx-%7B%7Bx%7D%7B0%7D%7D%7D%2C(x%3D%7B%7Bx%7D%7B0%7D%7D%2B%5CDelta%20x)#card=math&code=%7B%7B%7Bf%7D%27%7D%7B-%7D%7D%28%7B%7Bx%7D%7B0%7D%7D%29%3D%5Cunderset%7B%5CDelta%20x%5Cto%20%7B%7B0%7D%5E%7B-%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf%28%7B%7Bx%7D%7B0%7D%7D%2B%5CDelta%20x%29-f%28%7B%7Bx%7D%7B0%7D%7D%29%7D%7B%5CDelta%20x%7D%3D%5Cunderset%7Bx%5Cto%20x%7B0%7D%5E%7B-%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf%28x%29-f%28%7B%7Bx%7D%7B0%7D%7D%29%7D%7Bx-%7B%7Bx%7D%7B0%7D%7D%7D%2C%28x%3D%7B%7Bx%7D%7B0%7D%7D%2B%5CDelta%20x%29&id=H4Qjx)
右导数:%3D%5Cunderset%7B%5CDelta%20x%5Cto%20%7B%7B0%7D%5E%7B%2B%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf(%7B%7Bx%7D%7B0%7D%7D%2B%5CDelta%20x)-f(%7B%7Bx%7D%7B0%7D%7D)%7D%7B%5CDelta%20x%7D%3D%5Cunderset%7Bx%5Cto%20x%7B0%7D%5E%7B%2B%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf(x)-f(%7B%7Bx%7D%7B0%7D%7D)%7D%7Bx-%7B%7Bx%7D%7B0%7D%7D%7D#card=math&code=%7B%7B%7Bf%7D%27%7D%7B%2B%7D%7D%28%7B%7Bx%7D%7B0%7D%7D%29%3D%5Cunderset%7B%5CDelta%20x%5Cto%20%7B%7B0%7D%5E%7B%2B%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf%28%7B%7Bx%7D%7B0%7D%7D%2B%5CDelta%20x%29-f%28%7B%7Bx%7D%7B0%7D%7D%29%7D%7B%5CDelta%20x%7D%3D%5Cunderset%7Bx%5Cto%20x%7B0%7D%5E%7B%2B%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf%28x%29-f%28%7B%7Bx%7D%7B0%7D%7D%29%7D%7Bx-%7B%7Bx%7D%7B0%7D%7D%7D&id=Uz89o)
函数的可导性与连续性之间的关系
Th1: 函数#card=math&code=f%28x%29&id=THtfG)在
处可微
#card=math&code=%5CLeftrightarrow%20f%28x%29&id=tQ43D)在
处可导
Th2: 若函数在点处可导,则
#card=math&code=y%3Df%28x%29&id=zaygb)在点
处连续,反之则不成立。即函数连续不一定可导。
Th3: #card=math&code=%7Bf%7D%27%28%7B%7Bx%7D%7B0%7D%7D%29&id=wZUYV)存在%3D%7B%7B%7Bf%7D’%7D%7B%2B%7D%7D(%7B%7Bx%7D%7B0%7D%7D)#card=math&code=%5CLeftrightarrow%20%7B%7B%7Bf%7D%27%7D%7B-%7D%7D%28%7B%7Bx%7D%7B0%7D%7D%29%3D%7B%7B%7Bf%7D%27%7D%7B%2B%7D%7D%28%7B%7Bx%7D_%7B0%7D%7D%29&id=YuDpy)
平面曲线的切线和法线
切线方程 : (x-%7B%7Bx%7D%7B0%7D%7D)#card=math&code=y-%7B%7By%7D%7B0%7D%7D%3Df%27%28%7B%7Bx%7D%7B0%7D%7D%29%28x-%7B%7Bx%7D%7B0%7D%7D%29&id=hy71o)
法线方程:%7D(x-%7B%7Bx%7D%7B0%7D%7D)%2Cf’(%7B%7Bx%7D%7B0%7D%7D)%5Cne%200#card=math&code=y-%7B%7By%7D%7B0%7D%7D%3D-%5Cfrac%7B1%7D%7Bf%27%28%7B%7Bx%7D%7B0%7D%7D%29%7D%28x-%7B%7Bx%7D%7B0%7D%7D%29%2Cf%27%28%7B%7Bx%7D%7B0%7D%7D%29%5Cne%200&id=OJDB6)
四则运算法则
设函数%EF%BC%8Cv%3Dv(x)#card=math&code=u%3Du%28x%29%EF%BC%8Cv%3Dv%28x%29&id=ilnmp)]在点
可导则
(1) %7D’%3D%7Bu%7D’%5Cpm%20%7Bv%7D’#card=math&code=%28u%5Cpm%20v%7B%29%7D%27%3D%7Bu%7D%27%5Cpm%20%7Bv%7D%27&id=NYu4E)
%3Ddu%5Cpm%20dv#card=math&code=d%28u%5Cpm%20v%29%3Ddu%5Cpm%20dv&id=XsbIV)
(2)%7D’%3Du%7Bv%7D’%2Bv%7Bu%7D’#card=math&code=%28uv%7B%29%7D%27%3Du%7Bv%7D%27%2Bv%7Bu%7D%27&id=cm8Dw)
%3Dudv%2Bvdu#card=math&code=d%28uv%29%3Dudv%2Bvdu&id=kGx4w)
(3) %7D’%3D%5Cfrac%7Bv%7Bu%7D’-u%7Bv%7D’%7D%7B%7B%7Bv%7D%5E%7B2%7D%7D%7D(v%5Cne%200)#card=math&code=%28%5Cfrac%7Bu%7D%7Bv%7D%7B%29%7D%27%3D%5Cfrac%7Bv%7Bu%7D%27-u%7Bv%7D%27%7D%7B%7B%7Bv%7D%5E%7B2%7D%7D%7D%28v%5Cne%200%29&id=TVU4Q)
%3D%5Cfrac%7Bvdu-udv%7D%7B%7B%7Bv%7D%5E%7B2%7D%7D%7D#card=math&code=d%28%5Cfrac%7Bu%7D%7Bv%7D%29%3D%5Cfrac%7Bvdu-udv%7D%7B%7B%7Bv%7D%5E%7B2%7D%7D%7D&id=qy3Wt)
基本导数与微分表
(1) (常数)
(2) (
为实数)
(3)
特例: %7D’%3D%7B%7B%7Be%7D%7D%5E%7Bx%7D%7D%E2%80%8B#card=math&code=%28%7B%7B%7Be%7D%7D%5E%7Bx%7D%7D%7B%29%7D%27%3D%7B%7B%7Be%7D%7D%5E%7Bx%7D%7D%E2%80%8B&id=nQwbe)
%3D%7B%7B%7Be%7D%7D%5E%7Bx%7D%7Ddx%E2%80%8B#card=math&code=d%28%7B%7B%7Be%7D%7D%5E%7Bx%7D%7D%29%3D%7B%7B%7Be%7D%7D%5E%7Bx%7D%7Ddx%E2%80%8B&id=eNKXE)
(4)
特例:
%7D’%3D%5Cfrac%7B1%7D%7Bx%7D#card=math&code=%28%5Cln%20x%7B%29%7D%27%3D%5Cfrac%7B1%7D%7Bx%7D&id=sGl1a)
%3D%5Cfrac%7B1%7D%7Bx%7Ddx#card=math&code=d%28%5Cln%20x%29%3D%5Cfrac%7B1%7D%7Bx%7Ddx&id=hHvBB)
(5)
%3D%5Ccos%20xdx#card=math&code=d%28%5Csin%20x%29%3D%5Ccos%20xdx&id=WBZnW)
(6)
%3D-%5Csin%20xdx#card=math&code=d%28%5Ccos%20x%29%3D-%5Csin%20xdx&id=ln1Rs)
(7)
%3D%7B%7B%5Csec%20%7D%5E%7B2%7D%7Dxdx#card=math&code=d%28%5Ctan%20x%29%3D%7B%7B%5Csec%20%7D%5E%7B2%7D%7Dxdx&id=IBcco)
(8)
%3D-%7B%7B%5Ccsc%20%7D%5E%7B2%7D%7Dxdx#card=math&code=d%28%5Ccot%20x%29%3D-%7B%7B%5Ccsc%20%7D%5E%7B2%7D%7Dxdx&id=NPpZX)
(9)
%3D%5Csec%20x%5Ctan%20xdx#card=math&code=d%28%5Csec%20x%29%3D%5Csec%20x%5Ctan%20xdx&id=dlNZ5)
(10)
%3D-%5Ccsc%20x%5Ccot%20xdx#card=math&code=d%28%5Ccsc%20x%29%3D-%5Ccsc%20x%5Ccot%20xdx&id=PtLMW)
(11)
%3D%5Cfrac%7B1%7D%7B%5Csqrt%7B1-%7B%7Bx%7D%5E%7B2%7D%7D%7D%7Ddx#card=math&code=d%28%5Carcsin%20x%29%3D%5Cfrac%7B1%7D%7B%5Csqrt%7B1-%7B%7Bx%7D%5E%7B2%7D%7D%7D%7Ddx&id=s5Bah)
(12)
%3D-%5Cfrac%7B1%7D%7B%5Csqrt%7B1-%7B%7Bx%7D%5E%7B2%7D%7D%7D%7Ddx#card=math&code=d%28%5Carccos%20x%29%3D-%5Cfrac%7B1%7D%7B%5Csqrt%7B1-%7B%7Bx%7D%5E%7B2%7D%7D%7D%7Ddx&id=nTIyt)
(13)
%3D%5Cfrac%7B1%7D%7B1%2B%7B%7Bx%7D%5E%7B2%7D%7D%7Ddx#card=math&code=d%28%5Carctan%20x%29%3D%5Cfrac%7B1%7D%7B1%2B%7B%7Bx%7D%5E%7B2%7D%7D%7Ddx&id=dllP4)
(14)
%3D-%5Cfrac%7B1%7D%7B1%2B%7B%7Bx%7D%5E%7B2%7D%7D%7Ddx#card=math&code=d%28%5Coperatorname%7Barc%7D%5Ccot%20x%29%3D-%5Cfrac%7B1%7D%7B1%2B%7B%7Bx%7D%5E%7B2%7D%7D%7Ddx&id=avOCE)
(15)
%3Dchxdx#card=math&code=d%28shx%29%3Dchxdx&id=ORfh5)
(16)
%3Dshxdx#card=math&code=d%28chx%29%3Dshxdx&id=Ojq9H)
复合函数,反函数,隐函数以及参数方程所确定的函数的微分法
(1) 反函数的运算法则: 设#card=math&code=y%3Df%28x%29&id=lEh7s)在点
的某邻域内单调连续,在点
处可导且
%5Cne%200#card=math&code=%7Bf%7D%27%28x%29%5Cne%200&id=ItmIy),则其反函数在点
所对应的
处可导,并且有
(2) 复合函数的运算法则:若#card=math&code=%5Cmu%20%3D%5Cvarphi%20%28x%29&id=HK7uM)在点
可导,而
#card=math&code=y%3Df%28%5Cmu%20%29&id=wqc4u)在对应点
(
)可导,则复合函数
在点
可导,且
(3) 隐函数导数的求法一般有三种方法:
1)方程两边对求导,要记住
是
的函数,则
的函数是
的复合函数例如
等均是
的复合函数对
求导应按复合函数连锁法则做.
2)公式法.由知
%7D%7B%7B%7B%7B%7BF%7D’%7D%7D%7By%7D%7D(x%2Cy)%7D#card=math&code=%5Cfrac%7Bdy%7D%7Bdx%7D%3D-%5Cfrac%7B%7B%7B%7B%7BF%7D%27%7D%7D%7Bx%7D%7D%28x%2Cy%29%7D%7B%7B%7B%7B%7BF%7D%27%7D%7D%7By%7D%7D%28x%2Cy%29%7D&id=HmyEY),其中,#card=math&code=%7B%7B%7BF%7D%27%7D%7Bx%7D%7D%28x%2Cy%29&id=Fk4Ga),
#card=math&code=%7B%7B%7BF%7D%27%7D_%7By%7D%7D%28x%2Cy%29&id=tilau)分别表示#card=math&code=F%28x%2Cy%29&id=zG468)对
和
的偏导数
3)利用微分形式不变性
常用高阶导数公式
(1)%7B%7B%5C%2C%7D%5E%7B(n)%7D%7D%3D%7B%7Ba%7D%5E%7Bx%7D%7D%7B%7B%5Cln%20%7D%5E%7Bn%7D%7Da%5Cquad%20(a%3E%7B0%7D)%5Cquad%20%5Cquad%20(%7B%7B%7Be%7D%7D%5E%7Bx%7D%7D)%7B%7B%5C%2C%7D%5E%7B(n)%7D%7D%3D%7Be%7D%7B%7B%5C%2C%7D%5E%7Bx%7D%7D#card=math&code=%28%7B%7Ba%7D%5E%7Bx%7D%7D%29%7B%7B%5C%2C%7D%5E%7B%28n%29%7D%7D%3D%7B%7Ba%7D%5E%7Bx%7D%7D%7B%7B%5Cln%20%7D%5E%7Bn%7D%7Da%5Cquad%20%28a%3E%7B0%7D%29%5Cquad%20%5Cquad%20%28%7B%7B%7Be%7D%7D%5E%7Bx%7D%7D%29%7B%7B%5C%2C%7D%5E%7B%28n%29%7D%7D%3D%7Be%7D%7B%7B%5C%2C%7D%5E%7Bx%7D%7D&id=xdnH1)
(2)%7D%7B%7B%5C%2C%7D%5E%7B(n)%7D%7D%3D%7B%7Bk%7D%5E%7Bn%7D%7D%5Csin%20(kx%2Bn%5Ccdot%20%5Cfrac%7B%5Cpi%20%7D%7B%7B2%7D%7D)#card=math&code=%28%5Csin%20kx%7B%29%7D%7B%7B%5C%2C%7D%5E%7B%28n%29%7D%7D%3D%7B%7Bk%7D%5E%7Bn%7D%7D%5Csin%20%28kx%2Bn%5Ccdot%20%5Cfrac%7B%5Cpi%20%7D%7B%7B2%7D%7D%29&id=BUr7S)
(3)%7D%7B%7B%5C%2C%7D%5E%7B(n)%7D%7D%3D%7B%7Bk%7D%5E%7Bn%7D%7D%5Ccos%20(kx%2Bn%5Ccdot%20%5Cfrac%7B%5Cpi%20%7D%7B%7B2%7D%7D)#card=math&code=%28%5Ccos%20kx%7B%29%7D%7B%7B%5C%2C%7D%5E%7B%28n%29%7D%7D%3D%7B%7Bk%7D%5E%7Bn%7D%7D%5Ccos%20%28kx%2Bn%5Ccdot%20%5Cfrac%7B%5Cpi%20%7D%7B%7B2%7D%7D%29&id=xL6a6)
(4)%7B%7B%5C%2C%7D%5E%7B(n)%7D%7D%3Dm(m-1)%5Ccdots%20(m-n%2B1)%7B%7Bx%7D%5E%7Bm-n%7D%7D#card=math&code=%28%7B%7Bx%7D%5E%7Bm%7D%7D%29%7B%7B%5C%2C%7D%5E%7B%28n%29%7D%7D%3Dm%28m-1%29%5Ccdots%20%28m-n%2B1%29%7B%7Bx%7D%5E%7Bm-n%7D%7D&id=KBvW4)
(5)%7B%7B%5C%2C%7D%5E%7B(n)%7D%7D%3D%7B%7B(-%7B1%7D)%7D%5E%7B(n-%7B1%7D)%7D%7D%5Cfrac%7B(n-%7B1%7D)!%7D%7B%7B%7Bx%7D%5E%7Bn%7D%7D%7D#card=math&code=%28%5Cln%20x%29%7B%7B%5C%2C%7D%5E%7B%28n%29%7D%7D%3D%7B%7B%28-%7B1%7D%29%7D%5E%7B%28n-%7B1%7D%29%7D%7D%5Cfrac%7B%28n-%7B1%7D%29%21%7D%7B%7B%7Bx%7D%5E%7Bn%7D%7D%7D&id=uPSxD)
(6)莱布尼兹公式:若%5C%2C%2Cv(x)#card=math&code=u%28x%29%5C%2C%2Cv%28x%29&id=qGAkK)均
阶可导,则
%7D%5E%7B(n)%7D%7D%3D%5Csum%5Climits%7Bi%3D%7B0%7D%7D%5E%7Bn%7D%7Bc%7Bn%7D%5E%7Bi%7D%7B%7Bu%7D%5E%7B(i)%7D%7D%7B%7Bv%7D%5E%7B(n-i)%7D%7D%7D#card=math&code=%7B%7B%28uv%29%7D%5E%7B%28n%29%7D%7D%3D%5Csum%5Climits%7Bi%3D%7B0%7D%7D%5E%7Bn%7D%7Bc%7Bn%7D%5E%7Bi%7D%7B%7Bu%7D%5E%7B%28i%29%7D%7D%7B%7Bv%7D%5E%7B%28n-i%29%7D%7D%7D&id=mUycT),其中
%7D%7D%3Du#card=math&code=%7B%7Bu%7D%5E%7B%28%7B0%7D%29%7D%7D%3Du&id=H677f),
%7D%7D%3Dv#card=math&code=%7B%7Bv%7D%5E%7B%28%7B0%7D%29%7D%7D%3Dv&id=jq62A)
微分中值定理,泰勒公式
Th1:(费马定理)
若函数#card=math&code=f%28x%29&id=F7wMM)满足条件:
(1)函数#card=math&code=f%28x%29&id=xiNpG)在
的某邻域内有定义,并且在此邻域内恒有
%5Cle%20f(%7B%7Bx%7D%7B0%7D%7D)#card=math&code=f%28x%29%5Cle%20f%28%7B%7Bx%7D%7B0%7D%7D%29&id=y9agl)或
%5Cge%20f(%7B%7Bx%7D%7B0%7D%7D)#card=math&code=f%28x%29%5Cge%20f%28%7B%7Bx%7D%7B0%7D%7D%29&id=rOwsd),
(2) #card=math&code=f%28x%29&id=s3mRs)在
处可导,则有
%3D0#card=math&code=%7Bf%7D%27%28%7B%7Bx%7D_%7B0%7D%7D%29%3D0&id=rqCsq)
Th2:(罗尔定理)
设函数#card=math&code=f%28x%29&id=lQKfF)满足条件:
(1)在闭区间上连续;
(2)在#card=math&code=%28a%2Cb%29&id=UJynF)内可导;
(3)%3Df(b)#card=math&code=f%28a%29%3Df%28b%29&id=tlCSl);
则在#card=math&code=%28a%2Cb%29&id=s3Cbt)内一存在个
,使
%3D0#card=math&code=%7Bf%7D%27%28%5Cxi%20%29%3D0&id=UFCyg)
Th3: (拉格朗日中值定理)
设函数#card=math&code=f%28x%29&id=uSw0i)满足条件:
(1)在上连续;
(2)在#card=math&code=%28a%2Cb%29&id=AnkcS)内可导;
则在#card=math&code=%28a%2Cb%29&id=mfTG4)内一存在个
,使
-f(a)%7D%7Bb-a%7D%3D%7Bf%7D’(%5Cxi%20)#card=math&code=%5Cfrac%7Bf%28b%29-f%28a%29%7D%7Bb-a%7D%3D%7Bf%7D%27%28%5Cxi%20%29&id=rZbPr)
Th4: (柯西中值定理)
设函数#card=math&code=f%28x%29&id=q8Sfg),
#card=math&code=g%28x%29&id=tWG1a)满足条件:
(1) 在上连续;
(2) 在#card=math&code=%28a%2Cb%29&id=eC9Dg)内可导且
#card=math&code=%7Bf%7D%27%28x%29&id=rI1jz),
#card=math&code=%7Bg%7D%27%28x%29&id=riuhd)均存在,且
%5Cne%200#card=math&code=%7Bg%7D%27%28x%29%5Cne%200&id=HNQiD)
则在#card=math&code=%28a%2Cb%29&id=MbJZI)内存在一个
,使
-f(a)%7D%7Bg(b)-g(a)%7D%3D%5Cfrac%7B%7Bf%7D’(%5Cxi%20)%7D%7B%7Bg%7D’(%5Cxi%20)%7D#card=math&code=%5Cfrac%7Bf%28b%29-f%28a%29%7D%7Bg%28b%29-g%28a%29%7D%3D%5Cfrac%7B%7Bf%7D%27%28%5Cxi%20%29%7D%7B%7Bg%7D%27%28%5Cxi%20%29%7D&id=lwsov)
洛必达法则
法则Ⅰ (型)
设函数%2Cg%5Cleft(%20x%20%5Cright)#card=math&code=f%5Cleft%28%20x%20%5Cright%29%2Cg%5Cleft%28%20x%20%5Cright%29&id=eiO5Y)满足条件:
%3D0%2C%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2Cg%5Cleft(%20x%20%5Cright)%3D0#card=math&code=%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2Cf%5Cleft%28%20x%20%5Cright%29%3D0%2C%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D_%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2Cg%5Cleft%28%20x%20%5Cright%29%3D0&id=KTs5o);
%2Cg%5Cleft(%20x%20%5Cright)#card=math&code=f%5Cleft%28%20x%20%5Cright%29%2Cg%5Cleft%28%20x%20%5Cright%29&id=H9Fhn)在
的邻域内可导,(在
处可除外)且
%5Cne%200#card=math&code=%7Bg%7D%27%5Cleft%28%20x%20%5Cright%29%5Cne%200&id=zqtxq);
%7D%7B%7Bg%7D’%5Cleft(%20x%20%5Cright)%7D#card=math&code=%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D_%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7B%7Bf%7D%27%5Cleft%28%20x%20%5Cright%29%7D%7B%7Bg%7D%27%5Cleft%28%20x%20%5Cright%29%7D&id=lzacO)存在(或
)。
则:%7D%7Bg%5Cleft(%20x%20%5Cright)%7D%3D%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7B%7Bf%7D’%5Cleft(%20x%20%5Cright)%7D%7B%7Bg%7D’%5Cleft(%20x%20%5Cright)%7D#card=math&code=%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf%5Cleft%28%20x%20%5Cright%29%7D%7Bg%5Cleft%28%20x%20%5Cright%29%7D%3D%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D_%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7B%7Bf%7D%27%5Cleft%28%20x%20%5Cright%29%7D%7B%7Bg%7D%27%5Cleft%28%20x%20%5Cright%29%7D&id=SVW4q)。
法则 (
型)设函数
%2Cg%5Cleft(%20x%20%5Cright)#card=math&code=f%5Cleft%28%20x%20%5Cright%29%2Cg%5Cleft%28%20x%20%5Cright%29&id=PvoDV)满足条件:
%3D0%2C%5Cunderset%7Bx%5Cto%20%5Cinfty%20%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2Cg%5Cleft(%20x%20%5Cright)%3D0#card=math&code=%5Cunderset%7Bx%5Cto%20%5Cinfty%20%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2Cf%5Cleft%28%20x%20%5Cright%29%3D0%2C%5Cunderset%7Bx%5Cto%20%5Cinfty%20%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2Cg%5Cleft%28%20x%20%5Cright%29%3D0&id=Tsqba);
存在一个,当
时,
%2Cg%5Cleft(%20x%20%5Cright)#card=math&code=f%5Cleft%28%20x%20%5Cright%29%2Cg%5Cleft%28%20x%20%5Cright%29&id=dNxvB)可导,且
%5Cne%200#card=math&code=%7Bg%7D%27%5Cleft%28%20x%20%5Cright%29%5Cne%200&id=bG4x7);
%7D%7B%7Bg%7D’%5Cleft(%20x%20%5Cright)%7D#card=math&code=%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D_%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7B%7Bf%7D%27%5Cleft%28%20x%20%5Cright%29%7D%7B%7Bg%7D%27%5Cleft%28%20x%20%5Cright%29%7D&id=CuK9H)存在(或$\infty $)。
则:%7D%7Bg%5Cleft(%20x%20%5Cright)%7D%3D%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7B%7Bf%7D’%5Cleft(%20x%20%5Cright)%7D%7B%7Bg%7D’%5Cleft(%20x%20%5Cright)%7D#card=math&code=%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf%5Cleft%28%20x%20%5Cright%29%7D%7Bg%5Cleft%28%20x%20%5Cright%29%7D%3D%5Cunderset%7Bx%5Cto%20%7B%7Bx%7D%7B0%7D%7D%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7B%7Bf%7D%27%5Cleft%28%20x%20%5Cright%29%7D%7B%7Bg%7D%27%5Cleft%28%20x%20%5Cright%29%7D&id=WxqfG)
法则Ⅱ(型) 设函数
%2Cg%5Cleft(%20x%20%5Cright)#card=math&code=f%5Cleft%28%20x%20%5Cright%29%2Cg%5Cleft%28%20x%20%5Cright%29&id=WnIzo)满足条件:
; 在邻域内可导(在
处可除外)且
;
存在(或
)。则
同理法则
(
型)仿法则
可写出。
泰勒公式
设函数#card=math&code=f%28x%29&id=l4nHq)在点
处的某邻域内具有
阶导数,则对该邻域内异于
的任意点
,在
与
之间至少存在
一个
%7D%7D(%7B%7Bx%7D%7B0%7D%7D)%7D%7Bn!%7D%7B%7B(x-%7B%7Bx%7D%7B0%7D%7D)%7D%5E%7Bn%7D%7D%2B%7B%7BR%7D%7Bn%7D%7D(x)#card=math&code=%2B%5Cfrac%7B%7B%7Bf%7D%5E%7B%28n%29%7D%7D%28%7B%7Bx%7D%7B0%7D%7D%29%7D%7Bn%21%7D%7B%7B%28x-%7B%7Bx%7D%7B0%7D%7D%29%7D%5E%7Bn%7D%7D%2B%7B%7BR%7D%7Bn%7D%7D%28x%29&id=zulXz)
其中 %3D%5Cfrac%7B%7B%7Bf%7D%5E%7B(n%2B1)%7D%7D(%5Cxi%20)%7D%7B(n%2B1)!%7D%7B%7B(x-%7B%7Bx%7D%7B0%7D%7D)%7D%5E%7Bn%2B1%7D%7D#card=math&code=%7B%7BR%7D%7Bn%7D%7D%28x%29%3D%5Cfrac%7B%7B%7Bf%7D%5E%7B%28n%2B1%29%7D%7D%28%5Cxi%20%29%7D%7B%28n%2B1%29%21%7D%7B%7B%28x-%7B%7Bx%7D%7B0%7D%7D%29%7D%5E%7Bn%2B1%7D%7D&id=BzEEC)称为
#card=math&code=f%28x%29&id=cWHbk)在点处的
阶泰勒余项。
令,则
阶泰勒公式
%3Df(0)%2B%7Bf%7D’(0)x%2B%5Cfrac%7B1%7D%7B2!%7D%7Bf%7D’’(0)%7B%7Bx%7D%5E%7B2%7D%7D%2B%5Ccdots%20%2B%5Cfrac%7B%7B%7Bf%7D%5E%7B(n)%7D%7D(0)%7D%7Bn!%7D%7B%7Bx%7D%5E%7Bn%7D%7D%2B%7B%7BR%7D%7Bn%7D%7D(x)#card=math&code=f%28x%29%3Df%280%29%2B%7Bf%7D%27%280%29x%2B%5Cfrac%7B1%7D%7B2%21%7D%7Bf%7D%27%27%280%29%7B%7Bx%7D%5E%7B2%7D%7D%2B%5Ccdots%20%2B%5Cfrac%7B%7B%7Bf%7D%5E%7B%28n%29%7D%7D%280%29%7D%7Bn%21%7D%7B%7Bx%7D%5E%7Bn%7D%7D%2B%7B%7BR%7D%7Bn%7D%7D%28x%29&id=LNaOp)……(1)
其中 %3D%5Cfrac%7B%7B%7Bf%7D%5E%7B(n%2B1)%7D%7D(%5Cxi%20)%7D%7B(n%2B1)!%7D%7B%7Bx%7D%5E%7Bn%2B1%7D%7D#card=math&code=%7B%7BR%7D_%7Bn%7D%7D%28x%29%3D%5Cfrac%7B%7B%7Bf%7D%5E%7B%28n%2B1%29%7D%7D%28%5Cxi%20%29%7D%7B%28n%2B1%29%21%7D%7B%7Bx%7D%5E%7Bn%2B1%7D%7D&id=vXsnv),
在 0 与
之间.(1)式称为麦克劳林公式
常用五种函数在处的泰勒公式
(1) !%7D%7B%7Be%7D%5E%7B%5Cxi%20%7D%7D#card=math&code=%7B%7B%7Be%7D%7D%5E%7Bx%7D%7D%3D1%2Bx%2B%5Cfrac%7B1%7D%7B2%21%7D%7B%7Bx%7D%5E%7B2%7D%7D%2B%5Ccdots%20%2B%5Cfrac%7B1%7D%7Bn%21%7D%7B%7Bx%7D%5E%7Bn%7D%7D%2B%5Cfrac%7B%7B%7Bx%7D%5E%7Bn%2B1%7D%7D%7D%7B%28n%2B1%29%21%7D%7B%7Be%7D%5E%7B%5Cxi%20%7D%7D&id=GVwIt)
或 #card=math&code=%3D1%2Bx%2B%5Cfrac%7B1%7D%7B2%21%7D%7B%7Bx%7D%5E%7B2%7D%7D%2B%5Ccdots%20%2B%5Cfrac%7B1%7D%7Bn%21%7D%7B%7Bx%7D%5E%7Bn%7D%7D%2Bo%28%7B%7Bx%7D%5E%7Bn%7D%7D%29&id=XkIHH)
(2) !%7D%5Csin%20(%5Cxi%20%2B%5Cfrac%7Bn%2B1%7D%7B2%7D%5Cpi%20)#card=math&code=%5Csin%20x%3Dx-%5Cfrac%7B1%7D%7B3%21%7D%7B%7Bx%7D%5E%7B3%7D%7D%2B%5Ccdots%20%2B%5Cfrac%7B%7B%7Bx%7D%5E%7Bn%7D%7D%7D%7Bn%21%7D%5Csin%20%5Cfrac%7Bn%5Cpi%20%7D%7B2%7D%2B%5Cfrac%7B%7B%7Bx%7D%5E%7Bn%2B1%7D%7D%7D%7B%28n%2B1%29%21%7D%5Csin%20%28%5Cxi%20%2B%5Cfrac%7Bn%2B1%7D%7B2%7D%5Cpi%20%29&id=GEIZo)
或 #card=math&code=%3Dx-%5Cfrac%7B1%7D%7B3%21%7D%7B%7Bx%7D%5E%7B3%7D%7D%2B%5Ccdots%20%2B%5Cfrac%7B%7B%7Bx%7D%5E%7Bn%7D%7D%7D%7Bn%21%7D%5Csin%20%5Cfrac%7Bn%5Cpi%20%7D%7B2%7D%2Bo%28%7B%7Bx%7D%5E%7Bn%7D%7D%29&id=uKMbo)
(3) !%7D%5Ccos%20(%5Cxi%20%2B%5Cfrac%7Bn%2B1%7D%7B2%7D%5Cpi%20)#card=math&code=%5Ccos%20x%3D1-%5Cfrac%7B1%7D%7B2%21%7D%7B%7Bx%7D%5E%7B2%7D%7D%2B%5Ccdots%20%2B%5Cfrac%7B%7B%7Bx%7D%5E%7Bn%7D%7D%7D%7Bn%21%7D%5Ccos%20%5Cfrac%7Bn%5Cpi%20%7D%7B2%7D%2B%5Cfrac%7B%7B%7Bx%7D%5E%7Bn%2B1%7D%7D%7D%7B%28n%2B1%29%21%7D%5Ccos%20%28%5Cxi%20%2B%5Cfrac%7Bn%2B1%7D%7B2%7D%5Cpi%20%29&id=NKAEA)
或 #card=math&code=%3D1-%5Cfrac%7B1%7D%7B2%21%7D%7B%7Bx%7D%5E%7B2%7D%7D%2B%5Ccdots%20%2B%5Cfrac%7B%7B%7Bx%7D%5E%7Bn%7D%7D%7D%7Bn%21%7D%5Ccos%20%5Cfrac%7Bn%5Cpi%20%7D%7B2%7D%2Bo%28%7B%7Bx%7D%5E%7Bn%7D%7D%29&id=E6KB0)
(4) %3Dx-%5Cfrac%7B1%7D%7B2%7D%7B%7Bx%7D%5E%7B2%7D%7D%2B%5Cfrac%7B1%7D%7B3%7D%7B%7Bx%7D%5E%7B3%7D%7D-%5Ccdots%20%2B%7B%7B(-1)%7D%5E%7Bn-1%7D%7D%5Cfrac%7B%7B%7Bx%7D%5E%7Bn%7D%7D%7D%7Bn%7D%2B%5Cfrac%7B%7B%7B(-1)%7D%5E%7Bn%7D%7D%7B%7Bx%7D%5E%7Bn%2B1%7D%7D%7D%7B(n%2B1)%7B%7B(1%2B%5Cxi%20)%7D%5E%7Bn%2B1%7D%7D%7D#card=math&code=%5Cln%20%281%2Bx%29%3Dx-%5Cfrac%7B1%7D%7B2%7D%7B%7Bx%7D%5E%7B2%7D%7D%2B%5Cfrac%7B1%7D%7B3%7D%7B%7Bx%7D%5E%7B3%7D%7D-%5Ccdots%20%2B%7B%7B%28-1%29%7D%5E%7Bn-1%7D%7D%5Cfrac%7B%7B%7Bx%7D%5E%7Bn%7D%7D%7D%7Bn%7D%2B%5Cfrac%7B%7B%7B%28-1%29%7D%5E%7Bn%7D%7D%7B%7Bx%7D%5E%7Bn%2B1%7D%7D%7D%7B%28n%2B1%29%7B%7B%281%2B%5Cxi%20%29%7D%5E%7Bn%2B1%7D%7D%7D&id=WGCGk)
或 %7D%5E%7Bn-1%7D%7D%5Cfrac%7B%7B%7Bx%7D%5E%7Bn%7D%7D%7D%7Bn%7D%2Bo(%7B%7Bx%7D%5E%7Bn%7D%7D)#card=math&code=%3Dx-%5Cfrac%7B1%7D%7B2%7D%7B%7Bx%7D%5E%7B2%7D%7D%2B%5Cfrac%7B1%7D%7B3%7D%7B%7Bx%7D%5E%7B3%7D%7D-%5Ccdots%20%2B%7B%7B%28-1%29%7D%5E%7Bn-1%7D%7D%5Cfrac%7B%7B%7Bx%7D%5E%7Bn%7D%7D%7D%7Bn%7D%2Bo%28%7B%7Bx%7D%5E%7Bn%7D%7D%29&id=ib1BR)
(5) %7D%5E%7Bm%7D%7D%3D1%2Bmx%2B%5Cfrac%7Bm(m-1)%7D%7B2!%7D%7B%7Bx%7D%5E%7B2%7D%7D%2B%5Ccdots%20%2B%5Cfrac%7Bm(m-1)%5Ccdots%20(m-n%2B1)%7D%7Bn!%7D%7B%7Bx%7D%5E%7Bn%7D%7D#card=math&code=%7B%7B%281%2Bx%29%7D%5E%7Bm%7D%7D%3D1%2Bmx%2B%5Cfrac%7Bm%28m-1%29%7D%7B2%21%7D%7B%7Bx%7D%5E%7B2%7D%7D%2B%5Ccdots%20%2B%5Cfrac%7Bm%28m-1%29%5Ccdots%20%28m-n%2B1%29%7D%7Bn%21%7D%7B%7Bx%7D%5E%7Bn%7D%7D&id=dwmZs)
%5Ccdots%20(m-n%2B1)%7D%7B(n%2B1)!%7D%7B%7Bx%7D%5E%7Bn%2B1%7D%7D%7B%7B(1%2B%5Cxi%20)%7D%5E%7Bm-n-1%7D%7D#card=math&code=%2B%5Cfrac%7Bm%28m-1%29%5Ccdots%20%28m-n%2B1%29%7D%7B%28n%2B1%29%21%7D%7B%7Bx%7D%5E%7Bn%2B1%7D%7D%7B%7B%281%2B%5Cxi%20%29%7D%5E%7Bm-n-1%7D%7D&id=JAz0e)
或
%5Ccdots%20(m-n%2B1)%7D%7Bn!%7D%7B%7Bx%7D%5E%7Bn%7D%7D%2Bo(%7B%7Bx%7D%5E%7Bn%7D%7D)#card=math&code=%2B%5Cfrac%7Bm%28m-1%29%5Ccdots%20%28m-n%2B1%29%7D%7Bn%21%7D%7B%7Bx%7D%5E%7Bn%7D%7D%2Bo%28%7B%7Bx%7D%5E%7Bn%7D%7D%29&id=jpNb9)
函数单调性的判断
Th1: 设函数#card=math&code=f%28x%29&id=Fsq5M)在
#card=math&code=%28a%2Cb%29&id=IU6zl)区间内可导,如果对
#card=math&code=%5Cforall%20x%5Cin%20%28a%2Cb%29&id=jaRHl),都有
%3E0#card=math&code=f%5C%2C%27%28x%29%3E0&id=yjtmQ)(或
%3C0#card=math&code=f%5C%2C%27%28x%29%3C0&id=s02i5)),则函数
#card=math&code=f%28x%29&id=u2FhU)在
#card=math&code=%28a%2Cb%29&id=q1JCm)内是单调增加的(或单调减少)
Th2: (取极值的必要条件)设函数#card=math&code=f%28x%29&id=Pa5fJ)在
处可导,且在
处取极值,则
%3D0#card=math&code=f%5C%2C%27%28%7B%7Bx%7D_%7B0%7D%7D%29%3D0&id=Rc8L3)。
Th3: (取极值的第一充分条件)设函数#card=math&code=f%28x%29&id=JaehT)在
的某一邻域内可微,且
%3D0#card=math&code=f%5C%2C%27%28%7B%7Bx%7D%7B0%7D%7D%29%3D0&id=CLtGa)(或
#card=math&code=f%28x%29&id=thCvL)在处连续,但#card=math&code=f%5C%2C%27%28%7B%7Bx%7D%7B0%7D%7D%29&id=NySIp)不存在。)
(1)若当经过时,
#card=math&code=f%5C%2C%27%28x%29&id=iSpSI)由“+”变“-”,则#card=math&code=f%28%7B%7Bx%7D%7B0%7D%7D%29&id=MuXs4)为极大值;
(2)若当经过时,
#card=math&code=f%5C%2C%27%28x%29&id=oInBo)由“-”变“+”,则#card=math&code=f%28%7B%7Bx%7D%7B0%7D%7D%29&id=PuKdV)为极小值;
(3)若#card=math&code=f%5C%2C%27%28x%29&id=zuSpy)经过的两侧不变号,则#card=math&code=f%28%7B%7Bx%7D_%7B0%7D%7D%29&id=jfJHG)不是极值。
Th4: (取极值的第二充分条件)设#card=math&code=f%28x%29&id=NPkLJ)在点
处有
%5Cne%200#card=math&code=f%27%27%28x%29%5Cne%200&id=IK1iL),且
%3D0#card=math&code=f%5C%2C%27%28%7B%7Bx%7D%7B0%7D%7D%29%3D0&id=o2tHC),则 当%3C0#card=math&code=f%27%5C%2C%27%28%7B%7Bx%7D%7B0%7D%7D%29%3C0&id=Ut1gi)时,#card=math&code=f%28%7B%7Bx%7D%7B0%7D%7D%29&id=jAS8U)为极大值;
当%3E0#card=math&code=f%27%5C%2C%27%28%7B%7Bx%7D%7B0%7D%7D%29%3E0&id=PCHx1)时,#card=math&code=f%28%7B%7Bx%7D%7B0%7D%7D%29&id=qRHBP)为极小值。
注:如果%3C0#card=math&code=f%27%5C%2C%27%28%7B%7Bx%7D_%7B0%7D%7D%29%3C0&id=HLThx),此方法失效。
渐近线的求法
(1)水平渐近线 若%3Db#card=math&code=%5Cunderset%7Bx%5Cto%20%2B%5Cinfty%20%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2Cf%28x%29%3Db&id=aHcf2),或
%3Db#card=math&code=%5Cunderset%7Bx%5Cto%20-%5Cinfty%20%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2Cf%28x%29%3Db&id=RRVNo),则
称为函数
#card=math&code=y%3Df%28x%29&id=PWVpw)的水平渐近线。
(2)铅直渐近线 若 或
,则
称为
#card=math&code=y%3Df%28x%29&id=wvg18)的铅直渐近线。
(3)斜渐近线 若%7D%7Bx%7D%2C%5Cquad%20b%3D%5Cunderset%7Bx%5Cto%20%5Cinfty%20%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Bf(x)-ax%5D#card=math&code=a%3D%5Cunderset%7Bx%5Cto%20%5Cinfty%20%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Cfrac%7Bf%28x%29%7D%7Bx%7D%2C%5Cquad%20b%3D%5Cunderset%7Bx%5Cto%20%5Cinfty%20%7D%7B%5Cmathop%7B%5Clim%20%7D%7D%5C%2C%5Bf%28x%29-ax%5D&id=UNE5P),则
称为
#card=math&code=y%3Df%28x%29&id=bZUft)的斜渐近线。
函数凹凸性的判断
Th1: (凹凸性的判别定理)若在I上%3C0#card=math&code=f%27%27%28x%29%3C0&id=q9Mci)(或
%3E0#card=math&code=f%27%27%28x%29%3E0&id=KLVgx)),则
#card=math&code=f%28x%29&id=aTJNc)在I上是凸的(或凹的)。
Th2: (拐点的判别定理1)若在处
%3D0#card=math&code=f%27%27%28x%29%3D0&id=JZIil),(或
#card=math&code=f%27%27%28x%29&id=GpDqf)不存在),当
变动经过
时,
#card=math&code=f%27%27%28x%29&id=RwiW7)变号,则
)#card=math&code=%28%7B%7Bx%7D%7B0%7D%7D%2Cf%28%7B%7Bx%7D%7B0%7D%7D%29%29&id=J2Aoa)为拐点。
Th3: (拐点的判别定理2)设#card=math&code=f%28x%29&id=XS4ZI)在
点的某邻域内有三阶导数,且
%3D0#card=math&code=f%27%27%28x%29%3D0&id=wzmTG),
%5Cne%200#card=math&code=f%27%27%27%28x%29%5Cne%200&id=jnGp9),则
)#card=math&code=%28%7B%7Bx%7D%7B0%7D%7D%2Cf%28%7B%7Bx%7D%7B0%7D%7D%29%29&id=GBZA0)为拐点。
弧微分
曲率
曲线#card=math&code=y%3Df%28x%29&id=wN0Kb)在点
#card=math&code=%28x%2Cy%29&id=Zuk7d)处的曲率
%7D%5E%7B%5Ctfrac%7B3%7D%7B2%7D%7D%7D%7D#card=math&code=k%3D%5Cfrac%7B%5Cleft%7C%20y%27%27%20%5Cright%7C%7D%7B%7B%7B%281%2By%7B%7B%27%7D%5E%7B2%7D%7D%29%7D%5E%7B%5Ctfrac%7B3%7D%7B2%7D%7D%7D%7D&id=oKlTw)。
对于参数方程%20%5C%5C%20%20%26%20y%3D%5Cpsi%20(t)%20%5C%5C%20%5Cend%7Balign%7D%20%5Cright.%2C#card=math&code=%5Cleft%5C%7B%20%5Cbegin%7Balign%7D%20%20%26%20x%3D%5Cvarphi%20%28t%29%20%5C%5C%20%20%26%20y%3D%5Cpsi%20%28t%29%20%5C%5C%20%5Cend%7Balign%7D%20%5Cright.%2C&id=dd7wt)
%5Cpsi%20’’(t)-%5Cvarphi%20’’(t)%5Cpsi%20’(t)%20%5Cright%7C%7D%7B%7B%7B%5B%5Cvarphi%20%7B%7B’%7D%5E%7B2%7D%7D(t)%2B%5Cpsi%20%7B%7B’%7D%5E%7B2%7D%7D(t)%5D%7D%5E%7B%5Ctfrac%7B3%7D%7B2%7D%7D%7D%7D#card=math&code=k%3D%5Cfrac%7B%5Cleft%7C%20%5Cvarphi%20%27%28t%29%5Cpsi%20%27%27%28t%29-%5Cvarphi%20%27%27%28t%29%5Cpsi%20%27%28t%29%20%5Cright%7C%7D%7B%7B%7B%5B%5Cvarphi%20%7B%7B%27%7D%5E%7B2%7D%7D%28t%29%2B%5Cpsi%20%7B%7B%27%7D%5E%7B2%7D%7D%28t%29%5D%7D%5E%7B%5Ctfrac%7B3%7D%7B2%7D%7D%7D%7D&id=UrZ3q)。
曲率半径
曲线在点处的曲率
#card=math&code=k%28k%5Cne%200%29&id=qI87K)与曲线在点
处的曲率半径
。
线性代数
行列式
1.行列式按行(列)展开定理
(1) 设%7Bn%20%5Ctimes%20n%7D#card=math&code=A%20%3D%20%28%20a%7B%7Bij%7D%7D%20%29%7Bn%20%5Ctimes%20n%7D&id=yGxWE),则:
或即
其中:
%20%3D%20%7B(A%7B%7Bij%7D%7D)%7D%5E%7BT%7D#card=math&code=A%5E%7B%2A%7D%20%3D%20%5Cbegin%7Bpmatrix%7D%20A%7B11%7D%20%26%20A%7B12%7D%20%26%20%5Cldots%20%26%20A%7B1n%7D%20%5C%5C%20A%7B21%7D%20%26%20A%7B22%7D%20%26%20%5Cldots%20%26%20A%7B2n%7D%20%5C%5C%20%5Cldots%20%26%20%5Cldots%20%26%20%5Cldots%20%26%20%5Cldots%20%5C%5C%20A%7Bn1%7D%20%26%20A%7Bn2%7D%20%26%20%5Cldots%20%26%20A%7B%7Bnn%7D%7D%20%5C%5C%20%5Cend%7Bpmatrix%7D%20%3D%20%28A%7B%7Bji%7D%7D%29%20%3D%20%7B%28A%7B%7Bij%7D%7D%29%7D%5E%7BT%7D&id=DN3EJ)
#card=math&code=D%7Bn%7D%20%3D%20%5Cbegin%7Bvmatrix%7D%201%20%26%201%20%26%20%5Cldots%20%26%201%20%5C%5C%20x%7B1%7D%20%26%20x%7B2%7D%20%26%20%5Cldots%20%26%20x%7Bn%7D%20%5C%5C%20%5Cldots%20%26%20%5Cldots%20%26%20%5Cldots%20%26%20%5Cldots%20%5C%5C%20x%7B1%7D%5E%7Bn%20-%201%7D%20%26%20x%7B2%7D%5E%7Bn%20-%201%7D%20%26%20%5Cldots%20%26%20x%7Bn%7D%5E%7Bn%20-%201%7D%20%5C%5C%20%5Cend%7Bvmatrix%7D%20%3D%20%5Cprod%7B1%20%5Cleq%20j%20%3C%20i%20%5Cleq%20n%7D%5E%7B%7D%5C%2C%28x%7Bi%7D%20-%20x%7Bj%7D%29&id=Ho706)
(2) 设为
阶方阵,则
,但
不一定成立。
(3) ,
为
阶方阵。
(4) 设为
阶方阵,
(若
可逆),
(5)
,为方阵,但
%7D%5E%7B%7Bmn%7D%7D%7CA%7C%7CB%7C#card=math&code=%5Cleft%7C%20%5Cbegin%7Bmatrix%7D%20%7BO%7D%20%26%20A%7Bm%20%5Ctimes%20m%7D%20%5C%5C%20%20B%7Bn%20%5Ctimes%20n%7D%20%26%20%7B%20O%7D%20%5C%5C%20%5Cend%7Bmatrix%7D%20%5Cright%7C%20%3D%20%28%7B-%201%29%7D%5E%7B%7Bmn%7D%7D%7CA%7C%7CB%7C&id=tWtfm) 。
(6) 范德蒙行列式#card=math&code=D%7Bn%7D%20%3D%20%5Cbegin%7Bvmatrix%7D%201%20%26%201%20%26%20%5Cldots%20%26%201%20%5C%5C%20x%7B1%7D%20%26%20x%7B2%7D%20%26%20%5Cldots%20%26%20x%7Bn%7D%20%5C%5C%20%5Cldots%20%26%20%5Cldots%20%26%20%5Cldots%20%26%20%5Cldots%20%5C%5C%20x%7B1%7D%5E%7Bn%20-%201%7D%20%26%20x%7B2%7D%5E%7Bn%201%7D%20%26%20%5Cldots%20%26%20x%7Bn%7D%5E%7Bn%20-%201%7D%20%5C%5C%20%5Cend%7Bvmatrix%7D%20%3D%20%20%5Cprod%7B1%20%5Cleq%20j%20%3C%20i%20%5Cleq%20n%7D%5E%7B%7D%5C%2C%28x%7Bi%7D%20-%20x%7Bj%7D%29&id=QgkiP)
设是
阶方阵,
#card=math&code=%5Clambda%7Bi%7D%28i%20%3D%201%2C2%5Ccdots%2Cn%29&id=vfJst)是
的
个特征值,则

矩阵
矩阵:个数
排成
行
列的表格
称为矩阵,简记为
,或者
%7Bm%20%5Ctimes%20n%7D#card=math&code=%5Cleft%28%20a%7B%7Bij%7D%7D%20%5Cright%29_%7Bm%20%5Ctimes%20n%7D&id=utgyD) 。若
,则称
是
阶矩阵或
阶方阵。
矩阵的线性运算
1.矩阵的加法
设%2CB%20%3D%20(b%7B%7Bij%7D%7D)#card=math&code=A%20%3D%20%28a%7B%7Bij%7D%7D%29%2CB%20%3D%20%28b%7B%7Bij%7D%7D%29&id=XlQXJ)是两个
矩阵,则
矩阵%20%3D%20a%7B%7Bij%7D%7D%20%2B%20b%7B%7Bij%7D%7D#card=math&code=C%20%3D%20c%7B%7Bij%7D%7D%29%20%3D%20a%7B%7Bij%7D%7D%20%2B%20b_%7B%7Bij%7D%7D&id=sHFdx)称为矩阵
与
的和,记为
。
2.矩阵的数乘
设#card=math&code=A%20%3D%20%28a%7B%7Bij%7D%7D%29&id=pnA2t)是
矩阵,
是一个常数,则
矩阵#card=math&code=%28ka_%7B%7Bij%7D%7D%29&id=A3Qq3)称为数
与矩阵
的数乘,记为
。
3.矩阵的乘法
设#card=math&code=A%20%3D%20%28a%7B%7Bij%7D%7D%29&id=ONIsM)是
矩阵,#card=math&code=B%20%3D%20%28b%7B%7Bij%7D%7D%29&id=jvBz5)是
矩阵,那么
矩阵#card=math&code=C%20%3D%20%28c%7B%7Bij%7D%7D%29&id=oPF4f),其中称为
的乘积,记为
。
4. 、
、
三者之间的关系
(1) %7D%5E%7BT%7D%20%3D%20A%2C%7B(AB)%7D%5E%7BT%7D%20%3D%20B%5E%7BT%7DA%5E%7BT%7D%2C%7B(kA)%7D%5E%7BT%7D%20%3D%20kA%5E%7BT%7D%2C%7B(A%20%5Cpm%20B)%7D%5E%7BT%7D%20%3D%20A%5E%7BT%7D%20%5Cpm%20B%5E%7BT%7D#card=math&code=%7B%28A%5E%7BT%7D%29%7D%5E%7BT%7D%20%3D%20A%2C%7B%28AB%29%7D%5E%7BT%7D%20%3D%20B%5E%7BT%7DA%5E%7BT%7D%2C%7B%28kA%29%7D%5E%7BT%7D%20%3D%20kA%5E%7BT%7D%2C%7B%28A%20%5Cpm%20B%29%7D%5E%7BT%7D%20%3D%20A%5E%7BT%7D%20%5Cpm%20B%5E%7BT%7D&id=CSvRX)
(2) %5E%7B-%201%7D%20%3D%20A%2C%5Cleft(%20%7BAB%7D%20%5Cright)%5E%7B-%201%7D%20%3D%20B%5E%7B-%201%7DA%5E%7B-%201%7D%2C%5Cleft(%20%7BkA%7D%20%5Cright)%5E%7B-%201%7D%20%3D%20%5Cfrac%7B1%7D%7Bk%7DA%5E%7B-%201%7D%2C#card=math&code=%5Cleft%28%20A%5E%7B-%201%7D%20%5Cright%29%5E%7B-%201%7D%20%3D%20A%2C%5Cleft%28%20%7BAB%7D%20%5Cright%29%5E%7B-%201%7D%20%3D%20B%5E%7B-%201%7DA%5E%7B-%201%7D%2C%5Cleft%28%20%7BkA%7D%20%5Cright%29%5E%7B-%201%7D%20%3D%20%5Cfrac%7B1%7D%7Bk%7DA%5E%7B-%201%7D%2C&id=gMSPj)
但 %7D%5E%7B-%201%7D%20%3D%20A%5E%7B-%201%7D%20%5Cpm%20B%5E%7B-%201%7D#card=math&code=%7B%28A%20%5Cpm%20B%29%7D%5E%7B-%201%7D%20%3D%20A%5E%7B-%201%7D%20%5Cpm%20B%5E%7B-%201%7D&id=svfsW)不一定成立。
(3) %5E%7B%7D%20%3D%20%7CA%7C%5E%7Bn%20-%202%7D%5C%20A%5C%20%5C%20(n%20%5Cgeq%203)#card=math&code=%5Cleft%28%20A%5E%7B%2A%7D%20%5Cright%29%5E%7B%2A%7D%20%3D%20%7CA%7C%5E%7Bn%20-%202%7D%5C%20A%5C%20%5C%20%28n%20%5Cgeq%203%29&id=HsWGm),
%5E%7B%7D%20%3D%20B%5E%7B%7DA%5E%7B%7D%2C#card=math&code=%5Cleft%28%7BAB%7D%20%5Cright%29%5E%7B%2A%7D%20%3D%20B%5E%7B%2A%7DA%5E%7B%2A%7D%2C&id=xhE1U)
%5E%7B%7D%20%3D%20k%5E%7Bn%20-1%7DA%5E%7B%7D%7B%5C%20%5C%20%7D%5Cleft(%20n%20%5Cgeq%202%20%5Cright)#card=math&code=%5Cleft%28%20%7BkA%7D%20%5Cright%29%5E%7B%2A%7D%20%3D%20k%5E%7Bn%20-1%7DA%5E%7B%2A%7D%7B%5C%20%5C%20%7D%5Cleft%28%20n%20%5Cgeq%202%20%5Cright%29&id=SbXPC)
但%5E%7B%7D%20%3D%20A%5E%7B%7D%20%5Cpm%20B%5E%7B*%7D#card=math&code=%5Cleft%28%20A%20%5Cpm%20B%20%5Cright%29%5E%7B%2A%7D%20%3D%20A%5E%7B%2A%7D%20%5Cpm%20B%5E%7B%2A%7D&id=B1blF)不一定成立。
(4) %7D%5E%7BT%7D%20%3D%20%7B(A%5E%7BT%7D)%7D%5E%7B-%201%7D%2C%5C%20%5Cleft(%20A%5E%7B-%201%7D%20%5Cright)%5E%7B%7D%20%3D%7B(AA%5E%7B%7D)%7D%5E%7B-%201%7D%2C%7B(A%5E%7B%7D)%7D%5E%7BT%7D%20%3D%20%5Cleft(%20A%5E%7BT%7D%20%5Cright)%5E%7B%7D#card=math&code=%7B%28A%5E%7B-%201%7D%29%7D%5E%7BT%7D%20%3D%20%7B%28A%5E%7BT%7D%29%7D%5E%7B-%201%7D%2C%5C%20%5Cleft%28%20A%5E%7B-%201%7D%20%5Cright%29%5E%7B%2A%7D%20%3D%7B%28AA%5E%7B%2A%7D%29%7D%5E%7B-%201%7D%2C%7B%28A%5E%7B%2A%7D%29%7D%5E%7BT%7D%20%3D%20%5Cleft%28%20A%5E%7BT%7D%20%5Cright%29%5E%7B%2A%7D&id=G7anY)
5.有关的结论
(1)
(2) %2C%5C%20%5C%20%5C%20%5C%20%7B(kA)%7D%5E%7B%7D%20%3D%20k%5E%7Bn%20-1%7DA%5E%7B%7D%2C%7B%7B%5C%20%5C%20%7D%5Cleft(%20A%5E%7B%7D%20%5Cright)%7D%5E%7B%7D%20%3D%20%7CA%7C%5E%7Bn%20-%202%7DA(n%20%5Cgeq%203)#card=math&code=%7CA%5E%7B%2A%7D%7C%20%3D%20%7CA%7C%5E%7Bn%20-%201%7D%5C%20%28n%20%5Cgeq%202%29%2C%5C%20%5C%20%5C%20%5C%20%7B%28kA%29%7D%5E%7B%2A%7D%20%3D%20k%5E%7Bn%20-1%7DA%5E%7B%2A%7D%2C%7B%7B%5C%20%5C%20%7D%5Cleft%28%20A%5E%7B%2A%7D%20%5Cright%29%7D%5E%7B%2A%7D%20%3D%20%7CA%7C%5E%7Bn%20-%202%7DA%28n%20%5Cgeq%203%29&id=io4iS)
(3) 若可逆,则
%7D%5E%7B*%7D%20%3D%20%5Cfrac%7B1%7D%7B%7CA%7C%7DA#card=math&code=A%5E%7B%2A%7D%20%3D%20%7CA%7CA%5E%7B-%201%7D%2C%7B%28A%5E%7B%2A%7D%29%7D%5E%7B%2A%7D%20%3D%20%5Cfrac%7B1%7D%7B%7CA%7C%7DA&id=wZTSk)
(4) 若为
阶方阵,则:
%3D%5Cbegin%7Bcases%7Dn%2C%5Cquad%20r(A)%3Dn%5C%5C%201%2C%5Cquad%20r(A)%3Dn-1%5C%5C%200%2C%5Cquad%20r(A)%3Cn-1%5Cend%7Bcases%7D#card=math&code=r%28A%5E%2A%29%3D%5Cbegin%7Bcases%7Dn%2C%5Cquad%20r%28A%29%3Dn%5C%5C%201%2C%5Cquad%20r%28A%29%3Dn-1%5C%5C%200%2C%5Cquad%20r%28A%29%3Cn-1%5Cend%7Bcases%7D&id=Zfp87)
6.有关的结论
可逆
%20%3D%20n%3B#card=math&code=%5CLeftrightarrow%20AB%20%3D%20E%3B%20%5CLeftrightarrow%20%7CA%7C%20%5Cneq%200%3B%20%5CLeftrightarrow%20r%28A%29%20%3D%20n%3B&id=kG4Kp)
可以表示为初等矩阵的乘积;
。
7.有关矩阵秩的结论
(1) 秩#card=math&code=r%28A%29&id=Rt4Hc)=行秩=列秩;
(2) %20%5Cleq%20%5Cmin(m%2Cn)%3B#card=math&code=r%28A_%7Bm%20%5Ctimes%20n%7D%29%20%5Cleq%20%5Cmin%28m%2Cn%29%3B&id=AadP7)
(3) %20%5Cgeq%201#card=math&code=A%20%5Cneq%200%20%5CRightarrow%20r%28A%29%20%5Cgeq%201&id=n0V75);
(4) %20%5Cleq%20r(A)%20%2B%20r(B)%3B#card=math&code=r%28A%20%5Cpm%20B%29%20%5Cleq%20r%28A%29%20%2B%20r%28B%29%3B&id=yzNgS)
(5) 初等变换不改变矩阵的秩
(6) %20%2B%20r(B)%20-%20n%20%5Cleq%20r(AB)%20%5Cleq%20%5Cmin(r(A)%2Cr(B))%2C#card=math&code=r%28A%29%20%2B%20r%28B%29%20-%20n%20%5Cleq%20r%28AB%29%20%5Cleq%20%5Cmin%28r%28A%29%2Cr%28B%29%29%2C&id=vc8vG)特别若
则:%20%2B%20r(B)%20%5Cleq%20n#card=math&code=r%28A%29%20%2B%20r%28B%29%20%5Cleq%20n&id=oczVv)
(7) 若存在
%20%3D%20r(B)%3B#card=math&code=%5CRightarrow%20r%28AB%29%20%3D%20r%28B%29%3B&id=rUwiR) 若
存在
%20%3D%20r(A)%3B#card=math&code=%5CRightarrow%20r%28AB%29%20%3D%20r%28A%29%3B&id=Eglc9)
若%20%3D%20n%20%5CRightarrow%20r(AB)%20%3D%20r(B)%3B#card=math&code=r%28A%7Bm%20%5Ctimes%20n%7D%29%20%3D%20n%20%5CRightarrow%20r%28AB%29%20%3D%20r%28B%29%3B&id=Motsw) 若%20%3D%20n%5CRightarrow%20r(AB)%20%3D%20r%5Cleft(%20A%20%5Cright)#card=math&code=r%28A_%7Bm%20%5Ctimes%20s%7D%29%20%3D%20n%5CRightarrow%20r%28AB%29%20%3D%20r%5Cleft%28%20A%20%5Cright%29&id=ewutF)。
(8) %20%3D%20n%20%5CLeftrightarrow%20Ax%20%3D%200#card=math&code=r%28A_%7Bm%20%5Ctimes%20s%7D%29%20%3D%20n%20%5CLeftrightarrow%20Ax%20%3D%200&id=l6C0T)只有零解
8.分块求逆公式
;
;
;
这里,
均为可逆方阵。
向量
1.有关向量组的线性表示
(1)线性相关
至少有一个向量可以用其余向量线性表示。
(2)线性无关,
,
线性相关
可以由
唯一线性表示。
(3) 可以由
线性表示
%20%3Dr(%5Calpha%7B1%7D%2C%5Calpha%7B2%7D%2C%5Ccdots%2C%5Calpha%7Bs%7D%2C%5Cbeta)#card=math&code=%5CLeftrightarrow%20r%28%5Calpha%7B1%7D%2C%5Calpha%7B2%7D%2C%5Ccdots%2C%5Calpha%7Bs%7D%29%20%3Dr%28%5Calpha%7B1%7D%2C%5Calpha%7B2%7D%2C%5Ccdots%2C%5Calpha_%7Bs%7D%2C%5Cbeta%29&id=HEL3i) 。
2.有关向量组的线性相关性
(1)部分相关,整体相关;整体无关,部分无关.
(2) ① 个
维向量
线性无关
,
个
维向量
线性相关
。
② 个
维向量线性相关。
③ 若线性无关,则添加分量后仍线性无关;或一组向量线性相关,去掉某些分量后仍线性相关。
3.有关向量组的线性表示
(1) 线性相关
至少有一个向量可以用其余向量线性表示。
(2) 线性无关,
,
线性相关
可以由
唯一线性表示。
(3) 可以由
线性表示
%20%3Dr(%5Calpha%7B1%7D%2C%5Calpha%7B2%7D%2C%5Ccdots%2C%5Calpha%7Bs%7D%2C%5Cbeta)#card=math&code=%5CLeftrightarrow%20r%28%5Calpha%7B1%7D%2C%5Calpha%7B2%7D%2C%5Ccdots%2C%5Calpha%7Bs%7D%29%20%3Dr%28%5Calpha%7B1%7D%2C%5Calpha%7B2%7D%2C%5Ccdots%2C%5Calpha_%7Bs%7D%2C%5Cbeta%29&id=q5ZDH)
4.向量组的秩与矩阵的秩之间的关系
设%20%3Dr#card=math&code=r%28A_%7Bm%20%5Ctimes%20n%7D%29%20%3Dr&id=ewUhX),则
的秩
#card=math&code=r%28A%29&id=h1CLh)与
的行列向量组的线性相关性关系为:
(1) 若%20%3D%20r%20%3D%20m#card=math&code=r%28A_%7Bm%20%5Ctimes%20n%7D%29%20%3D%20r%20%3D%20m&id=KVULE),则
的行向量组线性无关。
(2) 若%20%3D%20r%20%3C%20m#card=math&code=r%28A_%7Bm%20%5Ctimes%20n%7D%29%20%3D%20r%20%3C%20m&id=dtlu0),则
的行向量组线性相关。
(3) 若%20%3D%20r%20%3D%20n#card=math&code=r%28A_%7Bm%20%5Ctimes%20n%7D%29%20%3D%20r%20%3D%20n&id=h9o6M),则
的列向量组线性无关。
(4) 若%20%3D%20r%20%3C%20n#card=math&code=r%28A_%7Bm%20%5Ctimes%20n%7D%29%20%3D%20r%20%3C%20n&id=PnbvA),则
的列向量组线性相关。
5.维向量空间的基变换公式及过渡矩阵
若与
是向量空间
的两组基,则基变换公式为:
%20%3D%20(%5Calpha%7B1%7D%2C%5Calpha%7B2%7D%2C%5Ccdots%2C%5Calpha%7Bn%7D)%5Cbegin%7Bbmatrix%7D%20%20c%7B11%7D%26%20c%7B12%7D%26%20%5Ccdots%20%26%20c%7B1n%7D%20%5C%5C%20%20c%7B21%7D%26%20c%7B22%7D%26%5Ccdots%20%26%20c%7B2n%7D%20%5C%5C%20%5Ccdots%20%26%20%5Ccdots%20%26%20%5Ccdots%20%26%20%5Ccdots%20%5C%5C%20%20c%7Bn1%7D%26%20c%7Bn2%7D%20%26%20%5Ccdots%20%26%20c%7B%7Bnn%7D%7D%20%5C%5C%5Cend%7Bbmatrix%7D%20%3D%20(%5Calpha%7B1%7D%2C%5Calpha%7B2%7D%2C%5Ccdots%2C%5Calpha%7Bn%7D)C#card=math&code=%28%5Cbeta%7B1%7D%2C%5Cbeta%7B2%7D%2C%5Ccdots%2C%5Cbeta%7Bn%7D%29%20%3D%20%28%5Calpha%7B1%7D%2C%5Calpha%7B2%7D%2C%5Ccdots%2C%5Calpha%7Bn%7D%29%5Cbegin%7Bbmatrix%7D%20%20c%7B11%7D%26%20c%7B12%7D%26%20%5Ccdots%20%26%20c%7B1n%7D%20%5C%5C%20%20c%7B21%7D%26%20c%7B22%7D%26%5Ccdots%20%26%20c%7B2n%7D%20%5C%5C%20%5Ccdots%20%26%20%5Ccdots%20%26%20%5Ccdots%20%26%20%5Ccdots%20%5C%5C%20%20c%7Bn1%7D%26%20c%7Bn2%7D%20%26%20%5Ccdots%20%26%20c%7B%7Bnn%7D%7D%20%5C%5C%5Cend%7Bbmatrix%7D%20%3D%20%28%5Calpha%7B1%7D%2C%5Calpha%7B2%7D%2C%5Ccdots%2C%5Calpha_%7Bn%7D%29C&id=nO8e4)
其中是可逆矩阵,称为由基
到基
的过渡矩阵。
6.坐标变换公式
若向量在基
与基
的坐标分别是
%7D%5E%7BT%7D#card=math&code=X%20%3D%20%7B%28x%7B1%7D%2Cx%7B2%7D%2C%5Ccdots%2Cx_%7Bn%7D%29%7D%5E%7BT%7D&id=FiXt6),
%5E%7BT%7D#card=math&code=Y%20%3D%20%5Cleft%28%20y%7B1%7D%2Cy%7B2%7D%2C%5Ccdots%2Cy%7Bn%7D%20%5Cright%29%5E%7BT%7D&id=o1LXz) 即: ,则向量坐标变换公式为
或
,其中
是从基到基的过渡矩阵。
7.向量的内积
%20%3D%20a%7B1%7Db%7B1%7D%20%2B%20a%7B2%7Db%7B2%7D%20%2B%20%5Ccdots%20%2B%20a%7Bn%7Db%7Bn%7D%20%3D%20%5Calpha%5E%7BT%7D%5Cbeta%20%3D%20%5Cbeta%5E%7BT%7D%5Calpha#card=math&code=%28%5Calpha%2C%5Cbeta%29%20%3D%20a%7B1%7Db%7B1%7D%20%2B%20a%7B2%7Db%7B2%7D%20%2B%20%5Ccdots%20%2B%20a%7Bn%7Db%7Bn%7D%20%3D%20%5Calpha%5E%7BT%7D%5Cbeta%20%3D%20%5Cbeta%5E%7BT%7D%5Calpha&id=w653A)
8.Schmidt正交化
若线性无关,则可构造
使其两两正交,且
仅是
的线性组合
#card=math&code=%28i%3D%201%2C2%2C%5Ccdots%2Cn%29&id=gSwzZ),再把
单位化,记
,则
是规范正交向量组。其中
,
%7D%7B(%5Cbeta%7B1%7D%2C%5Cbeta%7B1%7D)%7D%5Cbeta%7B1%7D#card=math&code=%5Cbeta%7B2%7D%20%3D%20%5Calpha%7B2%7D%20-%5Cfrac%7B%28%5Calpha%7B2%7D%2C%5Cbeta%7B1%7D%29%7D%7B%28%5Cbeta%7B1%7D%2C%5Cbeta%7B1%7D%29%7D%5Cbeta%7B1%7D&id=YxUSw) ,
%7D%7B(%5Cbeta%7B1%7D%2C%5Cbeta%7B1%7D)%7D%5Cbeta%7B1%7D%20-%5Cfrac%7B(%5Calpha%7B3%7D%2C%5Cbeta%7B2%7D)%7D%7B(%5Cbeta%7B2%7D%2C%5Cbeta%7B2%7D)%7D%5Cbeta%7B2%7D#card=math&code=%5Cbeta%7B3%7D%20%3D%5Calpha%7B3%7D%20-%20%5Cfrac%7B%28%5Calpha%7B3%7D%2C%5Cbeta%7B1%7D%29%7D%7B%28%5Cbeta%7B1%7D%2C%5Cbeta%7B1%7D%29%7D%5Cbeta%7B1%7D%20-%5Cfrac%7B%28%5Calpha%7B3%7D%2C%5Cbeta%7B2%7D%29%7D%7B%28%5Cbeta%7B2%7D%2C%5Cbeta%7B2%7D%29%7D%5Cbeta%7B2%7D&id=qUsvS) ,
…………
%7D%7B(%5Cbeta%7B1%7D%2C%5Cbeta%7B1%7D)%7D%5Cbeta%7B1%7D%20-%20%5Cfrac%7B(%5Calpha%7Bs%7D%2C%5Cbeta%7B2%7D)%7D%7B(%5Cbeta%7B2%7D%2C%5Cbeta%7B2%7D)%7D%5Cbeta%7B2%7D%20-%20%5Ccdots%20-%20%5Cfrac%7B(%5Calpha%7Bs%7D%2C%5Cbeta%7Bs%20-%201%7D)%7D%7B(%5Cbeta%7Bs%20-%201%7D%2C%5Cbeta%7Bs%20-%201%7D)%7D%5Cbeta%7Bs%20-%201%7D#card=math&code=%5Cbeta%7Bs%7D%20%3D%20%5Calpha%7Bs%7D%20-%20%5Cfrac%7B%28%5Calpha%7Bs%7D%2C%5Cbeta%7B1%7D%29%7D%7B%28%5Cbeta%7B1%7D%2C%5Cbeta%7B1%7D%29%7D%5Cbeta%7B1%7D%20-%20%5Cfrac%7B%28%5Calpha%7Bs%7D%2C%5Cbeta%7B2%7D%29%7D%7B%28%5Cbeta%7B2%7D%2C%5Cbeta%7B2%7D%29%7D%5Cbeta%7B2%7D%20-%20%5Ccdots%20-%20%5Cfrac%7B%28%5Calpha%7Bs%7D%2C%5Cbeta%7Bs%20-%201%7D%29%7D%7B%28%5Cbeta%7Bs%20-%201%7D%2C%5Cbeta%7Bs%20-%201%7D%29%7D%5Cbeta%7Bs%20-%201%7D&id=HZsZX)
9.正交基及规范正交基
向量空间一组基中的向量如果两两正交,就称为正交基;若正交基中每个向量都是单位向量,就称其为规范正交基。
线性方程组
1.克莱姆法则
线性方程组,如果系数行列式
,则方程组有唯一解,
,其中
是把
中第
列元素换成方程组右端的常数列所得的行列式。
2. 阶矩阵
可逆
只有零解。
总有唯一解,一般地,
%20%3D%20n%20%5CLeftrightarrow%20Ax%3D%200#card=math&code=r%28A_%7Bm%20%5Ctimes%20n%7D%29%20%3D%20n%20%5CLeftrightarrow%20Ax%3D%200&id=dHyCd)只有零解。
3.非奇次线性方程组有解的充分必要条件,线性方程组解的性质和解的结构
(1) 设为
矩阵,若
%20%3D%20m#card=math&code=r%28A_%7Bm%20%5Ctimes%20n%7D%29%20%3D%20m&id=VO8Ql),则对
而言必有
%20%3D%20r(A%20%5Cvdots%20b)%20%3D%20m#card=math&code=r%28A%29%20%3D%20r%28A%20%5Cvdots%20b%29%20%3D%20m&id=ytvFR),从而
有解。
(2) 设为
的解,则
当
时仍为
的解;但当
时,则为
的解。特别
为
的解;
#card=math&code=2x%7B3%7D%20-%20%28x%7B1%7D%20%2Bx_%7B2%7D%29&id=cDPFs)为
的解。
(3) 非齐次线性方程组无解
%20%2B%201%20%3Dr(%5Coverline%7BA%7D)%20%5CLeftrightarrow%20b#card=math&code=%5CLeftrightarrow%20r%28A%29%20%2B%201%20%3Dr%28%5Coverline%7BA%7D%29%20%5CLeftrightarrow%20b&id=xIRyM)不能由
的列向量
线性表示。
4.奇次线性方程组的基础解系和通解,解空间,非奇次线性方程组的通解
(1) 齐次方程组恒有解(必有零解)。当有非零解时,由于解向量的任意线性组合仍是该齐次方程组的解向量,因此
的全体解向量构成一个向量空间,称为该方程组的解空间,解空间的维数是
#card=math&code=n%20-%20r%28A%29&id=jODPe),解空间的一组基称为齐次方程组的基础解系。
(2) 是
的基础解系,即:
是
的解;
线性无关;
的任一解都可以由
线性表出.
是
的通解,其中
是任意常数。
矩阵的特征值和特征向量
1.矩阵的特征值和特征向量的概念及性质
(1) 设是
的一个特征值,则
%2CA%5E%7BT%7D%2CA%5E%7B-%201%7D%2CA%5E%7B*%7D#card=math&code=%7BkA%7D%2C%7BaA%7D%20%2B%20%7BbE%7D%2CA%5E%7B2%7D%2CA%5E%7Bm%7D%2Cf%28A%29%2CA%5E%7BT%7D%2CA%5E%7B-%201%7D%2CA%5E%7B%2A%7D&id=Q09IP)有一个特征值分别为
%2C%5Clambda%2C%5Clambda%5E%7B-%201%7D%2C%5Cfrac%7B%7CA%7C%7D%7B%5Clambda%7D%2C#card=math&code=%7Bk%CE%BB%7D%2C%7Ba%CE%BB%7D%20%2B%20b%2C%5Clambda%5E%7B2%7D%2C%5Clambda%5E%7Bm%7D%2Cf%28%5Clambda%29%2C%5Clambda%2C%5Clambda%5E%7B-%201%7D%2C%5Cfrac%7B%7CA%7C%7D%7B%5Clambda%7D%2C&id=vq7Vz)且对应特征向量相同(
例外)。
(2)若为
的
个特征值,则
,从而
没有特征值。
(3)设为
的
个特征值,对应特征向量为
,
若: ,
则: 。
2.相似变换、相似矩阵的概念及性质
(1) 若,则
%20%3D%20r(B)#card=math&code=%7CA%7C%20%3D%20%7CB%7C%2C%5Csum%7Bi%20%3D%201%7D%5E%7Bn%7DA%7B%7Bii%7D%7D%20%3D%20%5Csum%7Bi%20%3D1%7D%5E%7Bn%7Db%7B%7Bii%7D%7D%2Cr%28A%29%20%3D%20r%28B%29&id=EqxVB)
,对
成立
3.矩阵可相似对角化的充分必要条件
(1)设为
阶方阵,则
可对角化
对每个
重根特征值
,有
%20%3D%20k%7Bi%7D#card=math&code=n-r%28%5Clambda%7Bi%7DE%20-%20A%29%20%3D%20k_%7Bi%7D&id=L8Pkq)
(2) 设可对角化,则由
有
,从而
(3) 重要结论
- 若
,则
.
- 若
,则
%20%5Csim%20f(B)%2C%5Cleft%7C%20f(A)%20%5Cright%7C%20%5Csim%20%5Cleft%7C%20f(B)%5Cright%7C#card=math&code=f%28A%29%20%5Csim%20f%28B%29%2C%5Cleft%7C%20f%28A%29%20%5Cright%7C%20%5Csim%20%5Cleft%7C%20f%28B%29%5Cright%7C&id=cOGwC),其中
#card=math&code=f%28A%29&id=B9wsF)为关于
阶方阵
的多项式。
- 若
为可对角化矩阵,则其非零特征值的个数(重根重复计算)=秩(
)
4.实对称矩阵的特征值、特征向量及相似对角阵
(1)相似矩阵:设为两个
阶方阵,如果存在一个可逆矩阵
,使得
成立,则称矩阵
与
相似,记为
。
(2)相似矩阵的性质:如果则有:
(若
,
均可逆)
(
为正整数)
,从而
有相同的特征值,从而
同时可逆或者不可逆
- 秩
%20%3D#card=math&code=%5Cleft%28%20A%20%5Cright%29%20%3D&id=kwZnL)秩
%2C%5Cleft%7C%20%7B%CE%BBE%7D%20-%20A%20%5Cright%7C%20%3D%5Cleft%7C%20%7B%CE%BBE%7D%20-%20B%20%5Cright%7C#card=math&code=%5Cleft%28%20B%20%5Cright%29%2C%5Cleft%7C%20%7B%CE%BBE%7D%20-%20A%20%5Cright%7C%20%3D%5Cleft%7C%20%7B%CE%BBE%7D%20-%20B%20%5Cright%7C&id=bjzor),
不一定相似
二次型
1.个变量
的二次齐次函数
%20%3D%20%5Csum%7Bi%20%3D%201%7D%5E%7Bn%7D%7B%5Csum%7Bj%20%3D1%7D%5E%7Bn%7D%7Ba%7B%7Bij%7D%7Dx%7Bi%7Dy%7Bj%7D%7D%7D#card=math&code=f%28x%7B1%7D%2Cx%7B2%7D%2C%5Ccdots%2Cx%7Bn%7D%29%20%3D%20%5Csum%7Bi%20%3D%201%7D%5E%7Bn%7D%7B%5Csum%7Bj%20%3D1%7D%5E%7Bn%7D%7Ba%7B%7Bij%7D%7Dx%7Bi%7Dy%7Bj%7D%7D%7D&id=FeHO7),其中#card=math&code=a%7B%7Bij%7D%7D%20%3D%20a%7B%7Bji%7D%7D%28i%2Cj%20%3D1%2C2%2C%5Ccdots%2Cn%29&id=C6MDM),称为
元二次型,简称二次型. 若令,这二次型
可改写成矩阵向量形式
。其中
称为二次型矩阵,因为#card=math&code=a%7B%7Bij%7D%7D%20%3Da_%7B%7Bji%7D%7D%28i%2Cj%20%3D1%2C2%2C%5Ccdots%2Cn%29&id=CMpyz),所以二次型矩阵均为对称矩阵,且二次型与对称矩阵一一对应,并把矩阵
的秩称为二次型的秩。
2.惯性定理,二次型的标准形和规范形
(1) 惯性定理
对于任一二次型,不论选取怎样的合同变换使它化为仅含平方项的标准型,其正负惯性指数与所选变换无关,这就是所谓的惯性定理。
(2) 标准形
二次型%20%3Dx%5E%7BT%7D%7BAx%7D#card=math&code=f%20%3D%20%5Cleft%28%20x%7B1%7D%2Cx%7B2%7D%2C%5Ccdots%2Cx_%7Bn%7D%20%5Cright%29%20%3Dx%5E%7BT%7D%7BAx%7D&id=ibEnA)经过合同变换
化为
称为
#card=math&code=f%28r%20%5Cleq%20n%29&id=Y6CDc)的标准形。在一般的数域内,二次型的标准形不是唯一的,与所作的合同变换有关,但系数不为零的平方项的个数由
#card=math&code=r%28A%29&id=t2eXX)唯一确定。
(3) 规范形
任一实二次型都可经过合同变换化为规范形
,其中
为
的秩,
为正惯性指数,
为负惯性指数,且规范型唯一。
3.用正交变换和配方法化二次型为标准形,二次型及其矩阵的正定性
设正定
%2CA%5E%7BT%7D%2CA%5E%7B-%201%7D%2CA%5E%7B*%7D#card=math&code=%5CRightarrow%20%7BkA%7D%28k%20%3E%200%29%2CA%5E%7BT%7D%2CA%5E%7B-%201%7D%2CA%5E%7B%2A%7D&id=tddlv)正定;
,
可逆;
,且
,
正定
正定,但
,
不一定正定
正定
%20%3D%20x%5E%7BT%7D%7BAx%7D%20%3E%200%2C%5Cforall%20x%20%5Cneq%200#card=math&code=%5CLeftrightarrow%20f%28x%29%20%3D%20x%5E%7BT%7D%7BAx%7D%20%3E%200%2C%5Cforall%20x%20%5Cneq%200&id=YZP9c)
的各阶顺序主子式全大于零
的所有特征值大于零
的正惯性指数为
存在可逆阵
使
存在正交矩阵
,使
其中正定
%2CA%5E%7BT%7D%2CA%5E%7B-%201%7D%2CA%5E%7B*%7D#card=math&code=%5CRightarrow%20%7BkA%7D%28k%20%3E0%29%2CA%5E%7BT%7D%2CA%5E%7B-%201%7D%2CA%5E%7B%2A%7D&id=S58tT)正定;
可逆;
,且
。
概率论和数理统计
随机事件和概率
1.事件的关系与运算
(1) 子事件:,若
发生,则
发生。
(2) 相等事件:,即
,且
。
(3) 和事件:(或
),
与
中至少有一个发生。
(4) 差事件:,
发生但
不发生。
(5) 积事件:(或
),
与
同时发生。
(6) 互斥事件(互不相容):=
。
(7) 互逆事件(对立事件):
2.运算律
(1) 交换律:
(2) 结合律:%5Cbigcup%20C%3DA%5Cbigcup%20(B%5Cbigcup%20C)#card=math&code=%28A%5Cbigcup%20B%29%5Cbigcup%20C%3DA%5Cbigcup%20%28B%5Cbigcup%20C%29&id=ZZOdw)
(3) 分配律:%5Cbigcap%20C%3DA%5Cbigcap%20(B%5Cbigcap%20C)#card=math&code=%28A%5Cbigcap%20B%29%5Cbigcap%20C%3DA%5Cbigcap%20%28B%5Cbigcap%20C%29&id=lqqif)
3.德$\centerdot $摩根律
4.完全事件组
两两互斥,且和事件为必然事件,即${{A}{i}}\bigcap {{A}{j}}=\varnothing, i\ne j ,\underset{i=1}{\overset{n}{\mathop \bigcup }},=\Omega $
5.概率的基本公式
(1)条件概率:%3D%5Cfrac%7BP(AB)%7D%7BP(A)%7D#card=math&code=P%28B%7CA%29%3D%5Cfrac%7BP%28AB%29%7D%7BP%28A%29%7D&id=FnLPp),表示
发生的条件下,
发生的概率。
(2)全概率公式:
$P(A)=\sum\limits{i=1}^{n}{P(A|{{B}{i}})P({{B}{i}}),{{B}{i}}{{B}{j}}}=\varnothing ,i\ne j,\underset{i=1}{\overset{n}{\mathop{\bigcup }}},{{B}{i}}=\Omega $
(3) Bayes公式:
%3D%5Cfrac%7BP(A%7C%7B%7BB%7D%7Bj%7D%7D)P(%7B%7BB%7D%7Bj%7D%7D)%7D%7B%5Csum%5Climits%7Bi%3D1%7D%5E%7Bn%7D%7BP(A%7C%7B%7BB%7D%7Bi%7D%7D)P(%7B%7BB%7D%7Bi%7D%7D)%7D%7D%2Cj%3D1%2C2%2C%5Ccdots%20%2Cn#card=math&code=P%28%7B%7BB%7D%7Bj%7D%7D%7CA%29%3D%5Cfrac%7BP%28A%7C%7B%7BB%7D%7Bj%7D%7D%29P%28%7B%7BB%7D%7Bj%7D%7D%29%7D%7B%5Csum%5Climits%7Bi%3D1%7D%5E%7Bn%7D%7BP%28A%7C%7B%7BB%7D%7Bi%7D%7D%29P%28%7B%7BB%7D%7Bi%7D%7D%29%7D%7D%2Cj%3D1%2C2%2C%5Ccdots%20%2Cn&id=CQaCE)
注:上述公式中事件的个数可为可列个。
(4)乘法公式:
%3DP(%7B%7BA%7D%7B1%7D%7D)P(%7B%7BA%7D%7B2%7D%7D%7C%7B%7BA%7D%7B1%7D%7D)%3DP(%7B%7BA%7D%7B2%7D%7D)P(%7B%7BA%7D%7B1%7D%7D%7C%7B%7BA%7D%7B2%7D%7D)#card=math&code=P%28%7B%7BA%7D%7B1%7D%7D%7B%7BA%7D%7B2%7D%7D%29%3DP%28%7B%7BA%7D%7B1%7D%7D%29P%28%7B%7BA%7D%7B2%7D%7D%7C%7B%7BA%7D%7B1%7D%7D%29%3DP%28%7B%7BA%7D%7B2%7D%7D%29P%28%7B%7BA%7D%7B1%7D%7D%7C%7B%7BA%7D%7B2%7D%7D%29&id=av0wq)
%3DP(%7B%7BA%7D%7B1%7D%7D)P(%7B%7BA%7D%7B2%7D%7D%7C%7B%7BA%7D%7B1%7D%7D)P(%7B%7BA%7D%7B3%7D%7D%7C%7B%7BA%7D%7B1%7D%7D%7B%7BA%7D%7B2%7D%7D)%5Ccdots%20P(%7B%7BA%7D%7Bn%7D%7D%7C%7B%7BA%7D%7B1%7D%7D%7B%7BA%7D%7B2%7D%7D%5Ccdots%20%7B%7BA%7D%7Bn-1%7D%7D)#card=math&code=P%28%7B%7BA%7D%7B1%7D%7D%7B%7BA%7D%7B2%7D%7D%5Ccdots%20%7B%7BA%7D%7Bn%7D%7D%29%3DP%28%7B%7BA%7D%7B1%7D%7D%29P%28%7B%7BA%7D%7B2%7D%7D%7C%7B%7BA%7D%7B1%7D%7D%29P%28%7B%7BA%7D%7B3%7D%7D%7C%7B%7BA%7D%7B1%7D%7D%7B%7BA%7D%7B2%7D%7D%29%5Ccdots%20P%28%7B%7BA%7D%7Bn%7D%7D%7C%7B%7BA%7D%7B1%7D%7D%7B%7BA%7D%7B2%7D%7D%5Ccdots%20%7B%7BA%7D_%7Bn-1%7D%7D%29&id=CbSfW)
6.事件的独立性
(1)与
相互独立
%3DP(A)P(B)#card=math&code=%5CLeftrightarrow%20P%28AB%29%3DP%28A%29P%28B%29&id=uU49C)
(2),
,
两两独立
%3DP(A)P(B)#card=math&code=%5CLeftrightarrow%20P%28AB%29%3DP%28A%29P%28B%29&id=eqbpc);
%3DP(B)P(C)#card=math&code=P%28BC%29%3DP%28B%29P%28C%29&id=r964h) ;
%3DP(A)P(C)#card=math&code=P%28AC%29%3DP%28A%29P%28C%29&id=aVKAT);
(3),
,
相互独立
%3DP(A)P(B)#card=math&code=%5CLeftrightarrow%20P%28AB%29%3DP%28A%29P%28B%29&id=bsX0V);
%3DP(B)P(C)#card=math&code=P%28BC%29%3DP%28B%29P%28C%29&id=lPV1t) ;
%3DP(A)P(C)#card=math&code=P%28AC%29%3DP%28A%29P%28C%29&id=QJraY) ;
%3DP(A)P(B)P(C)#card=math&code=P%28ABC%29%3DP%28A%29P%28B%29P%28C%29&id=DZ8BJ)
7.独立重复试验
将某试验独立重复次,若每次实验中事件A发生的概率为
,则
次试验中
发生
次的概率为:
%3DC%7Bn%7D%5E%7Bk%7D%7B%7Bp%7D%5E%7Bk%7D%7D%7B%7B(1-p)%7D%5E%7Bn-k%7D%7D#card=math&code=P%28X%3Dk%29%3DC%7Bn%7D%5E%7Bk%7D%7B%7Bp%7D%5E%7Bk%7D%7D%7B%7B%281-p%29%7D%5E%7Bn-k%7D%7D&id=HPA1q)
8.重要公式与结论P(%5Cbar%7BA%7D)%3D1-P(A)#card=math&code=%281%29P%28%5Cbar%7BA%7D%29%3D1-P%28A%29&id=zWiNt)
P(A%5Cbigcup%20B)%3DP(A)%2BP(B)-P(AB)#card=math&code=%282%29P%28A%5Cbigcup%20B%29%3DP%28A%29%2BP%28B%29-P%28AB%29&id=jS7ZF)
%3DP(A)%2BP(B)%2BP(C)-P(AB)-P(BC)-P(AC)%2BP(ABC)#card=math&code=P%28A%5Cbigcup%20B%5Cbigcup%20C%29%3DP%28A%29%2BP%28B%29%2BP%28C%29-P%28AB%29-P%28BC%29-P%28AC%29%2BP%28ABC%29&id=mFBWw)
P(A-B)%3DP(A)-P(AB)#card=math&code=%283%29P%28A-B%29%3DP%28A%29-P%28AB%29&id=et8X7)
P(A%5Cbar%7BB%7D)%3DP(A)-P(AB)%2CP(A)%3DP(AB)%2BP(A%5Cbar%7BB%7D)%2C#card=math&code=%284%29P%28A%5Cbar%7BB%7D%29%3DP%28A%29-P%28AB%29%2CP%28A%29%3DP%28AB%29%2BP%28A%5Cbar%7BB%7D%29%2C&id=eZYyM)
%3DP(A)%2BP(%5Cbar%7BA%7DB)%3DP(AB)%2BP(A%5Cbar%7BB%7D)%2BP(%5Cbar%7BA%7DB)#card=math&code=P%28A%5Cbigcup%20B%29%3DP%28A%29%2BP%28%5Cbar%7BA%7DB%29%3DP%28AB%29%2BP%28A%5Cbar%7BB%7D%29%2BP%28%5Cbar%7BA%7DB%29&id=mkSMn)
(5)条件概率#card=math&code=P%28%5Ccenterdot%20%7CB%29&id=PjAvz)满足概率的所有性质,
例如:. %3D1-P(%7B%7BA%7D%7B1%7D%7D%7CB)#card=math&code=P%28%7B%7B%5Cbar%7BA%7D%7D%7B1%7D%7D%7CB%29%3D1-P%28%7B%7BA%7D%7B1%7D%7D%7CB%29&id=Wwfpr)
%3DP(%7B%7BA%7D%7B1%7D%7D%7CB)%2BP(%7B%7BA%7D%7B2%7D%7D%7CB)-P(%7B%7BA%7D%7B1%7D%7D%7B%7BA%7D%7B2%7D%7D%7CB)#card=math&code=P%28%7B%7BA%7D%7B1%7D%7D%5Cbigcup%20%7B%7BA%7D%7B2%7D%7D%7CB%29%3DP%28%7B%7BA%7D%7B1%7D%7D%7CB%29%2BP%28%7B%7BA%7D%7B2%7D%7D%7CB%29-P%28%7B%7BA%7D%7B1%7D%7D%7B%7BA%7D%7B2%7D%7D%7CB%29&id=qTUlf)
%3DP(%7B%7BA%7D%7B1%7D%7D%7CB)P(%7B%7BA%7D%7B2%7D%7D%7C%7B%7BA%7D%7B1%7D%7DB)#card=math&code=P%28%7B%7BA%7D%7B1%7D%7D%7B%7BA%7D%7B2%7D%7D%7CB%29%3DP%28%7B%7BA%7D%7B1%7D%7D%7CB%29P%28%7B%7BA%7D%7B2%7D%7D%7C%7B%7BA%7D%7B1%7D%7DB%29&id=Vm8OY)
(6)若相互独立,则%3D%5Cprod%5Climits%7Bi%3D1%7D%5E%7Bn%7D%7BP(%7B%7BA%7D%7Bi%7D%7D)%7D%2C#card=math&code=P%28%5Cbigcap%5Climits%7Bi%3D1%7D%5E%7Bn%7D%7B%7B%7BA%7D%7Bi%7D%7D%7D%29%3D%5Cprod%5Climits%7Bi%3D1%7D%5E%7Bn%7D%7BP%28%7B%7BA%7D%7Bi%7D%7D%29%7D%2C&id=aPTdI)
%3D%5Cprod%5Climits%7Bi%3D1%7D%5E%7Bn%7D%7B(1-P(%7B%7BA%7D%7Bi%7D%7D))%7D#card=math&code=P%28%5Cbigcup%5Climits%7Bi%3D1%7D%5E%7Bn%7D%7B%7B%7BA%7D%7Bi%7D%7D%7D%29%3D%5Cprod%5Climits%7Bi%3D1%7D%5E%7Bn%7D%7B%281-P%28%7B%7BA%7D%7Bi%7D%7D%29%29%7D&id=lmgrm)
(7)互斥、互逆与独立性之间的关系:与
互逆
与
互斥,但反之不成立,
与
互斥(或互逆)且均非零概率事件$\Rightarrow $$A
B
%E8%8B%A5#card=math&code=%E4%B8%8D%E7%8B%AC%E7%AB%8B.%0A%288%29%E8%8B%A5&id=XmMlD){{A}{1}},{{A}{2}},\cdots ,{{A}{m}},{{B}{1}},{{B}{2}},\cdots ,{{B}{n}}
f({{A}{1}},{{A}{2}},\cdots ,{{A}{m}})
_g({{B}{1}},{{B}{2}},\cdots ,{{B}{n}})
f(\centerdot ),g(\centerdot )$分别表示对相应事件做任意事件运算后所得的事件,另外,概率为1(或0)的事件与任何事件相互独立.
随机变量及其概率分布
1.随机变量及概率分布
取值带有随机性的变量,严格地说是定义在样本空间上,取值于实数的函数称为随机变量,概率分布通常指分布函数或分布律
2.分布函数的概念与性质
定义: %20%3D%20P(X%20%5Cleq%20x)%2C%20-%20%5Cinfty%20%3C%20x%20%3C%20%2B%20%5Cinfty#card=math&code=F%28x%29%20%3D%20P%28X%20%5Cleq%20x%29%2C%20-%20%5Cinfty%20%3C%20x%20%3C%20%2B%20%5Cinfty&id=NZLRE)
性质:(1)%20%5Cleq%201#card=math&code=0%20%5Cleq%20F%28x%29%20%5Cleq%201&id=b0mQE)
(2) #card=math&code=F%28x%29&id=G5tWM)单调不减
(3) 右连续%20%3D%20F(x)#card=math&code=F%28x%20%2B%200%29%20%3D%20F%28x%29&id=IJmq0)
(4) %20%3D%200%2CF(%20%2B%20%5Cinfty)%20%3D%201#card=math&code=F%28%20-%20%5Cinfty%29%20%3D%200%2CF%28%20%2B%20%5Cinfty%29%20%3D%201&id=ycd15)
3.离散型随机变量的概率分布
%20%3D%20p%7Bi%7D%2Ci%20%3D%201%2C2%2C%5Ccdots%2Cn%2C%5Ccdots%5Cquad%5Cquad%20p%7Bi%7D%20%5Cgeq%200%2C%5Csum%7Bi%20%3D1%7D%5E%7B%5Cinfty%7Dp%7Bi%7D%20%3D%201#card=math&code=P%28X%20%3D%20x%7Bi%7D%29%20%3D%20p%7Bi%7D%2Ci%20%3D%201%2C2%2C%5Ccdots%2Cn%2C%5Ccdots%5Cquad%5Cquad%20p%7Bi%7D%20%5Cgeq%200%2C%5Csum%7Bi%20%3D1%7D%5E%7B%5Cinfty%7Dp_%7Bi%7D%20%3D%201&id=UMF67)
4.连续型随机变量的概率密度
概率密度#card=math&code=f%28x%29&id=aKSng);非负可积,且:
(1)%20%5Cgeq%200%2C#card=math&code=f%28x%29%20%5Cgeq%200%2C&id=ctd5m)
(2)%7Bdx%7D%20%3D%201%7D#card=math&code=%5Cint_%7B-%20%5Cinfty%7D%5E%7B%2B%5Cinfty%7D%7Bf%28x%29%7Bdx%7D%20%3D%201%7D&id=apKZC)
(3)为
#card=math&code=f%28x%29&id=bkVvf)的连续点,则:
%20%3D%20F’(x)#card=math&code=f%28x%29%20%3D%20F%27%28x%29&id=eGRSG)分布函数
%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7Bx%7D%7Bf(t)%7Bdt%7D%7D#card=math&code=F%28x%29%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7Bx%7D%7Bf%28t%29%7Bdt%7D%7D&id=Rdmat)
5.常见分布
(1) 0-1分布:%20%3D%20p%5E%7Bk%7D%7B(1%20-%20p)%7D%5E%7B1%20-%20k%7D%2Ck%20%3D%200%2C1#card=math&code=P%28X%20%3D%20k%29%20%3D%20p%5E%7Bk%7D%7B%281%20-%20p%29%7D%5E%7B1%20-%20k%7D%2Ck%20%3D%200%2C1&id=oHXFb)
(2) 二项分布:#card=math&code=B%28n%2Cp%29&id=cUaC2):
%20%3D%20C%7Bn%7D%5E%7Bk%7Dp%5E%7Bk%7D%7B(1%20-%20p)%7D%5E%7Bn%20-%20k%7D%2Ck%20%3D0%2C1%2C%5Ccdots%2Cn#card=math&code=P%28X%20%3D%20k%29%20%3D%20C%7Bn%7D%5E%7Bk%7Dp%5E%7Bk%7D%7B%281%20-%20p%29%7D%5E%7Bn%20-%20k%7D%2Ck%20%3D0%2C1%2C%5Ccdots%2Cn&id=SjNYk)
(3) Poisson分布:#card=math&code=p%28%5Clambda%29&id=zvKJf):
%20%3D%20%5Cfrac%7B%5Clambda%5E%7Bk%7D%7D%7Bk!%7De%5E%7B-%5Clambda%7D%2C%5Clambda%20%3E%200%2Ck%20%3D%200%2C1%2C2%5Ccdots#card=math&code=P%28X%20%3D%20k%29%20%3D%20%5Cfrac%7B%5Clambda%5E%7Bk%7D%7D%7Bk%21%7De%5E%7B-%5Clambda%7D%2C%5Clambda%20%3E%200%2Ck%20%3D%200%2C1%2C2%5Ccdots&id=wDhVK)
(4) 均匀分布#card=math&code=U%28a%2Cb%29&id=eeigh):$f(x) = { \begin{matrix} & \frac{1}{b - a},a < x< b \ & 0, \ \end{matrix} $
(5) 正态分布:%3A#card=math&code=N%28%5Cmu%2C%5Csigma%5E%7B2%7D%29%3A&id=nyvlN)
%20%3D%5Cfrac%7B1%7D%7B%5Csqrt%7B2%5Cpi%7D%5Csigma%7De%5E%7B-%20%5Cfrac%7B%7B(x%20-%20%5Cmu)%7D%5E%7B2%7D%7D%7B2%5Csigma%5E%7B2%7D%7D%7D%2C%5Csigma%20%3E%200%2C%5Cinfty%20%3C%20x%20%3C%20%2B%20%5Cinfty#card=math&code=%5Cvarphi%28x%29%20%3D%5Cfrac%7B1%7D%7B%5Csqrt%7B2%5Cpi%7D%5Csigma%7De%5E%7B-%20%5Cfrac%7B%7B%28x%20-%20%5Cmu%29%7D%5E%7B2%7D%7D%7B2%5Csigma%5E%7B2%7D%7D%7D%2C%5Csigma%20%3E%200%2C%5Cinfty%20%3C%20x%20%3C%20%2B%20%5Cinfty&id=misaw)
(6)指数分布:$E(\lambda):f(x) ={ \begin{matrix} & \lambda e^{-{λx}},x > 0,\lambda > 0 \ & 0, \ \end{matrix} $
(7)几何分布:%3AP(X%20%3D%20k)%20%3D%20%7B(1%20-%20p)%7D%5E%7Bk%20-%201%7Dp%2C0%20%3C%20p%20%3C%201%2Ck%20%3D%201%2C2%2C%5Ccdots.#card=math&code=G%28p%29%3AP%28X%20%3D%20k%29%20%3D%20%7B%281%20-%20p%29%7D%5E%7Bk%20-%201%7Dp%2C0%20%3C%20p%20%3C%201%2Ck%20%3D%201%2C2%2C%5Ccdots.&id=ZDnjW)
(8)超几何分布: %3AP(X%20%3D%20k)%20%3D%20%5Cfrac%7BC%7BM%7D%5E%7Bk%7DC%7BN%20-%20M%7D%5E%7Bn%20-k%7D%7D%7BC%7BN%7D%5E%7Bn%7D%7D%2Ck%20%3D0%2C1%2C%5Ccdots%2Cmin(n%2CM)#card=math&code=H%28N%2CM%2Cn%29%3AP%28X%20%3D%20k%29%20%3D%20%5Cfrac%7BC%7BM%7D%5E%7Bk%7DC%7BN%20-%20M%7D%5E%7Bn%20-k%7D%7D%7BC%7BN%7D%5E%7Bn%7D%7D%2Ck%20%3D0%2C1%2C%5Ccdots%2Cmin%28n%2CM%29&id=Ko8Li)
6.随机变量函数的概率分布
(1)离散型:%20%3D%20p%7Bi%7D%2CY%20%3D%20g(X)#card=math&code=P%28X%20%3D%20x%7B1%7D%29%20%3D%20p_%7Bi%7D%2CY%20%3D%20g%28X%29&id=garsU)
则: %20%3D%20%5Csum%7Bg(x%7Bi%7D)%20%3D%20y%7Bi%7D%7D%5E%7B%7D%7BP(X%20%3D%20x%7Bi%7D)%7D#card=math&code=P%28Y%20%3D%20y%7Bj%7D%29%20%3D%20%5Csum%7Bg%28x%7Bi%7D%29%20%3D%20y%7Bi%7D%7D%5E%7B%7D%7BP%28X%20%3D%20x_%7Bi%7D%29%7D&id=u4YwM)
(2)连续型:%2CY%20%3D%20g(x)#card=math&code=X%5Ctilde%7B%5C%20%7Df_%7BX%7D%28x%29%2CY%20%3D%20g%28x%29&id=AaYVS)
则:%20%3D%20P(Y%20%5Cleq%20y)%20%3D%20P(g(X)%20%5Cleq%20y)%20%3D%20%5Cint%7Bg(x)%20%5Cleq%20y%7D%5E%7B%7D%7Bf%7Bx%7D(x)dx%7D#card=math&code=F%7By%7D%28y%29%20%3D%20P%28Y%20%5Cleq%20y%29%20%3D%20P%28g%28X%29%20%5Cleq%20y%29%20%3D%20%5Cint%7Bg%28x%29%20%5Cleq%20y%7D%5E%7B%7D%7Bf%7Bx%7D%28x%29dx%7D&id=PMTYe), %20%3D%20F’%7BY%7D(y)#card=math&code=f%7BY%7D%28y%29%20%3D%20F%27_%7BY%7D%28y%29&id=oIR2y)
7.重要公式与结论
(1) %20%5CRightarrow%20%5Cvarphi(0)%20%3D%20%5Cfrac%7B1%7D%7B%5Csqrt%7B2%5Cpi%7D%7D%2C%5CPhi(0)%20%3D%5Cfrac%7B1%7D%7B2%7D%2C#card=math&code=X%5Csim%20N%280%2C1%29%20%5CRightarrow%20%5Cvarphi%280%29%20%3D%20%5Cfrac%7B1%7D%7B%5Csqrt%7B2%5Cpi%7D%7D%2C%5CPhi%280%29%20%3D%5Cfrac%7B1%7D%7B2%7D%2C&id=VHUow)
%20%3D%20P(X%20%5Cleq%20-%20a)%20%3D%201%20-%20%5CPhi(a)#card=math&code=%5CPhi%28%20-%20a%29%20%3D%20P%28X%20%5Cleq%20-%20a%29%20%3D%201%20-%20%5CPhi%28a%29&id=G4epC)
(2) %20%5CRightarrow%20%5Cfrac%7BX%20-%5Cmu%7D%7B%5Csigma%7D%5Csim%20N%5Cleft(%200%2C1%20%5Cright)%2CP(X%20%5Cleq%20a)%20%3D%20%5CPhi(%5Cfrac%7Ba%20-%5Cmu%7D%7B%5Csigma%7D)#card=math&code=X%5Csim%20N%5Cleft%28%20%5Cmu%2C%5Csigma%5E%7B2%7D%20%5Cright%29%20%5CRightarrow%20%5Cfrac%7BX%20-%5Cmu%7D%7B%5Csigma%7D%5Csim%20N%5Cleft%28%200%2C1%20%5Cright%29%2CP%28X%20%5Cleq%20a%29%20%3D%20%5CPhi%28%5Cfrac%7Ba%20-%5Cmu%7D%7B%5Csigma%7D%29&id=Oa5AR)
(3) %20%5CRightarrow%20P(X%20%3E%20s%20%2B%20t%7CX%20%3E%20s)%20%3D%20P(X%20%3E%20t)#card=math&code=X%5Csim%20E%28%5Clambda%29%20%5CRightarrow%20P%28X%20%3E%20s%20%2B%20t%7CX%20%3E%20s%29%20%3D%20P%28X%20%3E%20t%29&id=ecT95)
(4) %20%5CRightarrow%20P(X%20%3D%20m%20%2B%20k%7CX%20%3E%20m)%20%3D%20P(X%20%3D%20k)#card=math&code=X%5Csim%20G%28p%29%20%5CRightarrow%20P%28X%20%3D%20m%20%2B%20k%7CX%20%3E%20m%29%20%3D%20P%28X%20%3D%20k%29&id=lHA4O)
(5) 离散型随机变量的分布函数为阶梯间断函数;连续型随机变量的分布函数为连续函数,但不一定为处处可导函数。
(6) 存在既非离散也非连续型随机变量。
多维随机变量及其分布
1.二维随机变量及其联合分布
由两个随机变量构成的随机向量#card=math&code=%28X%2CY%29&id=hQE9q), 联合分布为
%20%3D%20P(X%20%5Cleq%20x%2CY%20%5Cleq%20y)#card=math&code=F%28x%2Cy%29%20%3D%20P%28X%20%5Cleq%20x%2CY%20%5Cleq%20y%29&id=nQUKG)
2.二维离散型随机变量的分布
(1) 联合概率分布律
(2) 边缘分布律
(3) 条件分布律
3. 二维连续性随机变量的密度
(1) 联合概率密度%3A#card=math&code=f%28x%2Cy%29%3A&id=swmMR)
%20%5Cgeq%200#card=math&code=f%28x%2Cy%29%20%5Cgeq%200&id=g96KO)
dxdy%7D%7D%20%3D%201#card=math&code=%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7B%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bf%28x%2Cy%29dxdy%7D%7D%20%3D%201&id=hDvdK)
(2) 分布函数:%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7Bx%7D%7B%5Cint%7B-%20%5Cinfty%7D%5E%7By%7D%7Bf(u%2Cv)dudv%7D%7D#card=math&code=F%28x%2Cy%29%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7Bx%7D%7B%5Cint%7B-%20%5Cinfty%7D%5E%7By%7D%7Bf%28u%2Cv%29dudv%7D%7D&id=uPDOC)
(3) 边缘概率密度: %20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bf%5Cleft(%20x%2Cy%20%5Cright)%7Bdy%7D%7D#card=math&code=f%7BX%7D%5Cleft%28%20x%20%5Cright%29%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bf%5Cleft%28%20x%2Cy%20%5Cright%29%7Bdy%7D%7D&id=sPWrY) %20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bf(x%2Cy)dx%7D#card=math&code=f%7BY%7D%28y%29%20%3D%20%5Cint_%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bf%28x%2Cy%29dx%7D&id=dRlFE)
(4) 条件概率密度:%20%3D%20%5Cfrac%7Bf%5Cleft(%20x%2Cy%20%5Cright)%7D%7Bf%7BY%7D%5Cleft(%20y%20%5Cright)%7D#card=math&code=f%7BX%7CY%7D%5Cleft%28%20x%20%5Cmiddle%7C%20y%20%5Cright%29%20%3D%20%5Cfrac%7Bf%5Cleft%28%20x%2Cy%20%5Cright%29%7D%7Bf%7BY%7D%5Cleft%28%20y%20%5Cright%29%7D&id=E6jv7) %20%3D%20%5Cfrac%7Bf(x%2Cy)%7D%7Bf%7BX%7D(x)%7D#card=math&code=f%7BY%7CX%7D%28y%7Cx%29%20%3D%20%5Cfrac%7Bf%28x%2Cy%29%7D%7Bf_%7BX%7D%28x%29%7D&id=JnMc1)
4.常见二维随机变量的联合分布
(1) 二维均匀分布:%20%5Csim%20U(D)#card=math&code=%28x%2Cy%29%20%5Csim%20U%28D%29&id=aNpCW) ,
%20%3D%20%5Cbegin%7Bcases%7D%20%5Cfrac%7B1%7D%7BS(D)%7D%2C(x%2Cy)%20%5Cin%20D%20%5C%5C%20%20%200%2C%E5%85%B6%E4%BB%96%20%20%5Cend%7Bcases%7D#card=math&code=f%28x%2Cy%29%20%3D%20%5Cbegin%7Bcases%7D%20%5Cfrac%7B1%7D%7BS%28D%29%7D%2C%28x%2Cy%29%20%5Cin%20D%20%5C%5C%20%20%200%2C%E5%85%B6%E4%BB%96%20%20%5Cend%7Bcases%7D&id=rup4L)
(2) 二维正态分布:%5Csim%20N(%5Cmu%7B1%7D%2C%5Cmu%7B2%7D%2C%5Csigma%7B1%7D%5E%7B2%7D%2C%5Csigma%7B2%7D%5E%7B2%7D%2C%5Crho)#card=math&code=%28X%2CY%29%5Csim%20N%28%5Cmu%7B1%7D%2C%5Cmu%7B2%7D%2C%5Csigma%7B1%7D%5E%7B2%7D%2C%5Csigma%7B2%7D%5E%7B2%7D%2C%5Crho%29&id=fEFHE),
%5Csim%20N(%5Cmu%7B1%7D%2C%5Cmu%7B2%7D%2C%5Csigma%7B1%7D%5E%7B2%7D%2C%5Csigma%7B2%7D%5E%7B2%7D%2C%5Crho)#card=math&code=%28X%2CY%29%5Csim%20N%28%5Cmu%7B1%7D%2C%5Cmu%7B2%7D%2C%5Csigma%7B1%7D%5E%7B2%7D%2C%5Csigma%7B2%7D%5E%7B2%7D%2C%5Crho%29&id=T08iT)
%20%3D%20%5Cfrac%7B1%7D%7B2%5Cpi%5Csigma%7B1%7D%5Csigma%7B2%7D%5Csqrt%7B1%20-%20%5Crho%5E%7B2%7D%7D%7D.%5Cexp%5Cleft%5C%7B%20%5Cfrac%7B-%201%7D%7B2(1%20-%20%5Crho%5E%7B2%7D)%7D%5Clbrack%5Cfrac%7B%7B(x%20-%20%5Cmu%7B1%7D)%7D%5E%7B2%7D%7D%7B%5Csigma%7B1%7D%5E%7B2%7D%7D%20-%202%5Crho%5Cfrac%7B(x%20-%20%5Cmu%7B1%7D)(y%20-%20%5Cmu%7B2%7D)%7D%7B%5Csigma%7B1%7D%5Csigma%7B2%7D%7D%20%2B%20%5Cfrac%7B%7B(y%20-%20%5Cmu%7B2%7D)%7D%5E%7B2%7D%7D%7B%5Csigma%7B2%7D%5E%7B2%7D%7D%5Crbrack%20%5Cright%5C%7D#card=math&code=f%28x%2Cy%29%20%3D%20%5Cfrac%7B1%7D%7B2%5Cpi%5Csigma%7B1%7D%5Csigma%7B2%7D%5Csqrt%7B1%20-%20%5Crho%5E%7B2%7D%7D%7D.%5Cexp%5Cleft%5C%7B%20%5Cfrac%7B-%201%7D%7B2%281%20-%20%5Crho%5E%7B2%7D%29%7D%5Clbrack%5Cfrac%7B%7B%28x%20-%20%5Cmu%7B1%7D%29%7D%5E%7B2%7D%7D%7B%5Csigma%7B1%7D%5E%7B2%7D%7D%20-%202%5Crho%5Cfrac%7B%28x%20-%20%5Cmu%7B1%7D%29%28y%20-%20%5Cmu%7B2%7D%29%7D%7B%5Csigma%7B1%7D%5Csigma%7B2%7D%7D%20%2B%20%5Cfrac%7B%7B%28y%20-%20%5Cmu%7B2%7D%29%7D%5E%7B2%7D%7D%7B%5Csigma%7B2%7D%5E%7B2%7D%7D%5Crbrack%20%5Cright%5C%7D&id=pwpBW)
5.随机变量的独立性和相关性
和
的相互独立:
%20%3D%20F%7BX%7D%5Cleft(%20x%20%5Cright)F%7BY%7D%5Cleft(%20y%20%5Cright)#card=math&code=%5CLeftrightarrow%20F%5Cleft%28%20x%2Cy%20%5Cright%29%20%3D%20F%7BX%7D%5Cleft%28%20x%20%5Cright%29F%7BY%7D%5Cleft%28%20y%20%5Cright%29&id=JeOTi):
(离散型)
%20%3D%20f%7BX%7D%5Cleft(%20x%20%5Cright)f%7BY%7D%5Cleft(%20y%20%5Cright)#card=math&code=%5CLeftrightarrow%20f%5Cleft%28%20x%2Cy%20%5Cright%29%20%3D%20f%7BX%7D%5Cleft%28%20x%20%5Cright%29f%7BY%7D%5Cleft%28%20y%20%5Cright%29&id=tGqZU)(连续型)
和
的相关性:
相关系数时,称
和
不相关,
否则称和
相关
6.两个随机变量简单函数的概率分布
离散型: %20%3D%20p%7B%7Bij%7D%7D%2CZ%20%3D%20g%5Cleft(%20X%2CY%20%5Cright)#card=math&code=P%5Cleft%28%20X%20%3D%20x%7Bi%7D%2CY%20%3D%20y%7Bi%7D%20%5Cright%29%20%3D%20p%7B%7Bij%7D%7D%2CZ%20%3D%20g%5Cleft%28%20X%2CY%20%5Cright%29&id=Bb6tY) 则:
%20%3D%20P%5Cleft%5C%7B%20g%5Cleft(%20X%2CY%20%5Cright)%20%3D%20z%7Bk%7D%20%5Cright%5C%7D%20%3D%20%5Csum%7Bg%5Cleft(%20x%7Bi%7D%2Cy%7Bi%7D%20%5Cright)%20%3D%20z%7Bk%7D%7D%5E%7B%7D%7BP%5Cleft(%20X%20%3D%20x%7Bi%7D%2CY%20%3D%20y%7Bj%7D%20%5Cright)%7D#card=math&code=P%28Z%20%3D%20z%7Bk%7D%29%20%3D%20P%5Cleft%5C%7B%20g%5Cleft%28%20X%2CY%20%5Cright%29%20%3D%20z%7Bk%7D%20%5Cright%5C%7D%20%3D%20%5Csum%7Bg%5Cleft%28%20x%7Bi%7D%2Cy%7Bi%7D%20%5Cright%29%20%3D%20z%7Bk%7D%7D%5E%7B%7D%7BP%5Cleft%28%20X%20%3D%20x%7Bi%7D%2CY%20%3D%20y_%7Bj%7D%20%5Cright%29%7D&id=vMK7B)
连续型: %20%5Csim%20f%5Cleft(%20x%2Cy%20%5Cright)%2CZ%20%3D%20g%5Cleft(%20X%2CY%20%5Cright)#card=math&code=%5Cleft%28%20X%2CY%20%5Cright%29%20%5Csim%20f%5Cleft%28%20x%2Cy%20%5Cright%29%2CZ%20%3D%20g%5Cleft%28%20X%2CY%20%5Cright%29&id=DaCkh)
则:
%20%3D%20P%5Cleft%5C%7B%20g%5Cleft(%20X%2CY%20%5Cright)%20%5Cleq%20z%20%5Cright%5C%7D%20%3D%20%5Ciint%7Bg(x%2Cy)%20%5Cleq%20z%7D%5E%7B%7D%7Bf(x%2Cy)dxdy%7D#card=math&code=F%7Bz%7D%5Cleft%28%20z%20%5Cright%29%20%3D%20P%5Cleft%5C%7B%20g%5Cleft%28%20X%2CY%20%5Cright%29%20%5Cleq%20z%20%5Cright%5C%7D%20%3D%20%5Ciint%7Bg%28x%2Cy%29%20%5Cleq%20z%7D%5E%7B%7D%7Bf%28x%2Cy%29dxdy%7D&id=TCv3e),%20%3D%20F’%7Bz%7D(z)#card=math&code=f%7Bz%7D%28z%29%20%3D%20F%27_%7Bz%7D%28z%29&id=idrXP)
7.重要公式与结论
(1) 边缘密度公式: %20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bf(x%2Cy)dy%2C%7D#card=math&code=f%7BX%7D%28x%29%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bf%28x%2Cy%29dy%2C%7D&id=RPTHV)
%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bf(x%2Cy)dx%7D#card=math&code=f%7BY%7D%28y%29%20%3D%20%5Cint_%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bf%28x%2Cy%29dx%7D&id=CxesY)
(2) %20%5Cin%20D%20%5Cright%5C%7D%20%3D%20%5Ciint%7BD%7D%5E%7B%7D%7Bf%5Cleft(%20x%2Cy%20%5Cright)%7Bdxdy%7D%7D#card=math&code=P%5Cleft%5C%7B%20%5Cleft%28%20X%2CY%20%5Cright%29%20%5Cin%20D%20%5Cright%5C%7D%20%3D%20%5Ciint%7BD%7D%5E%7B%7D%7Bf%5Cleft%28%20x%2Cy%20%5Cright%29%7Bdxdy%7D%7D&id=HFMZh)
(3) 若#card=math&code=%28X%2CY%29&id=Hxdv5)服从二维正态分布
#card=math&code=N%28%5Cmu%7B1%7D%2C%5Cmu%7B2%7D%2C%5Csigma%7B1%7D%5E%7B2%7D%2C%5Csigma%7B2%7D%5E%7B2%7D%2C%5Crho%29&id=LyiW6)
则有:
%2CY%5Csim%20N(%5Cmu%7B2%7D%2C%5Csigma%7B2%7D%5E%7B2%7D).#card=math&code=X%5Csim%20N%5Cleft%28%20%5Cmu%7B1%7D%2C%5Csigma%7B1%7D%5E%7B2%7D%20%5Cright%29%2CY%5Csim%20N%28%5Cmu%7B2%7D%2C%5Csigma%7B2%7D%5E%7B2%7D%29.&id=nFz9v)
与
相互独立
,即
与
不相关。
#card=math&code=C%7B1%7DX%20%2B%20C%7B2%7DY%5Csim%20N%28C%7B1%7D%5Cmu%7B1%7D%20%2B%20C%7B2%7D%5Cmu%7B2%7D%2CC%7B1%7D%5E%7B2%7D%5Csigma%7B1%7D%5E%7B2%7D%20%2B%20C%7B2%7D%5E%7B2%7D%5Csigma%7B2%7D%5E%7B2%7D%20%2B%202C%7B1%7DC%7B2%7D%5Csigma%7B1%7D%5Csigma%7B2%7D%5Crho%29&id=mNQ1O)
关于
的条件分布为:
%2C%5Csigma%7B1%7D%5E%7B2%7D(1%20-%20%5Crho%5E%7B2%7D))#card=math&code=N%28%5Cmu%7B1%7D%20%2B%20%5Crho%5Cfrac%7B%5Csigma%7B1%7D%7D%7B%5Csigma%7B2%7D%7D%28y%20-%20%5Cmu%7B2%7D%29%2C%5Csigma%7B1%7D%5E%7B2%7D%281%20-%20%5Crho%5E%7B2%7D%29%29&id=S18Ta)
关于
的条件分布为:
%2C%5Csigma%7B2%7D%5E%7B2%7D(1%20-%20%5Crho%5E%7B2%7D))#card=math&code=N%28%5Cmu%7B2%7D%20%2B%20%5Crho%5Cfrac%7B%5Csigma%7B2%7D%7D%7B%5Csigma%7B1%7D%7D%28x%20-%20%5Cmu%7B1%7D%29%2C%5Csigma%7B2%7D%5E%7B2%7D%281%20-%20%5Crho%5E%7B2%7D%29%29&id=W726b)
(4) 若与
独立,且分别服从
%2CN(%5Cmu%7B1%7D%2C%5Csigma%7B2%7D%5E%7B2%7D)%2C#card=math&code=N%28%5Cmu%7B1%7D%2C%5Csigma%7B1%7D%5E%7B2%7D%29%2CN%28%5Cmu%7B1%7D%2C%5Csigma%7B2%7D%5E%7B2%7D%29%2C&id=fi9sI)
则:%5Csim%20N(%5Cmu%7B1%7D%2C%5Cmu%7B2%7D%2C%5Csigma%7B1%7D%5E%7B2%7D%2C%5Csigma%7B2%7D%5E%7B2%7D%2C0)%2C#card=math&code=%5Cleft%28%20X%2CY%20%5Cright%29%5Csim%20N%28%5Cmu%7B1%7D%2C%5Cmu%7B2%7D%2C%5Csigma%7B1%7D%5E%7B2%7D%2C%5Csigma%7B2%7D%5E%7B2%7D%2C0%29%2C&id=tcio9)
.#card=math&code=C%7B1%7DX%20%2B%20C%7B2%7DY%5Ctilde%7B%5C%20%7DN%28C%7B1%7D%5Cmu%7B1%7D%20%2B%20C%7B2%7D%5Cmu%7B2%7D%2CC%7B1%7D%5E%7B2%7D%5Csigma%7B1%7D%5E%7B2%7D%20C%7B2%7D%5E%7B2%7D%5Csigma%7B2%7D%5E%7B2%7D%29.&id=R030y)
(5) 若与
相互独立,
#card=math&code=f%5Cleft%28%20x%20%5Cright%29&id=uASTA)和
#card=math&code=g%5Cleft%28%20x%20%5Cright%29&id=M5nmU)为连续函数, 则
#card=math&code=f%5Cleft%28%20X%20%5Cright%29&id=twAIE)和
#card=math&code=g%28Y%29&id=l4lkY)也相互独立。
随机变量的数字特征
1.数学期望
离散型:%20%3D%20%5Csum%7Bi%7D%5E%7B%7D%7Bx%7Bi%7Dp%7Bi%7D%7D#card=math&code=P%5Cleft%5C%7B%20X%20%3D%20x%7Bi%7D%20%5Cright%5C%7D%20%3D%20p%7Bi%7D%2CE%28X%29%20%3D%20%5Csum%7Bi%7D%5E%7B%7D%7Bx%7Bi%7Dp%7Bi%7D%7D&id=M0M9S);
连续型: %2CE(X)%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bxf(x)dx%7D#card=math&code=X%5Csim%20f%28x%29%2CE%28X%29%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bxf%28x%29dx%7D&id=aRS3H)
性质:
(1) %20%3D%20C%2CE%5Clbrack%20E(X)%5Crbrack%20%3D%20E(X)#card=math&code=E%28C%29%20%3D%20C%2CE%5Clbrack%20E%28X%29%5Crbrack%20%3D%20E%28X%29&id=IJANQ)
(2) %20%3D%20C%7B1%7DE(X)%20%2B%20C%7B2%7DE(Y)#card=math&code=E%28C%7B1%7DX%20%2B%20C%7B2%7DY%29%20%3D%20C%7B1%7DE%28X%29%20%2B%20C%7B2%7DE%28Y%29&id=suTiJ)
(3) 若和
独立,则
%20%3D%20E(X)E(Y)#card=math&code=E%28XY%29%20%3D%20E%28X%29E%28Y%29&id=OFCCw)
(4)%20%5Cright%5Crbrack%5E%7B2%7D%20%5Cleq%20E(X%5E%7B2%7D)E(Y%5E%7B2%7D)#card=math&code=%5Cleft%5Clbrack%20E%28XY%29%20%5Cright%5Crbrack%5E%7B2%7D%20%5Cleq%20E%28X%5E%7B2%7D%29E%28Y%5E%7B2%7D%29&id=hmi88)
2.方差:%20%3D%20E%5Cleft%5Clbrack%20X%20-%20E(X)%20%5Cright%5Crbrack%5E%7B2%7D%20%3D%20E(X%5E%7B2%7D)%20-%20%5Cleft%5Clbrack%20E(X)%20%5Cright%5Crbrack%5E%7B2%7D#card=math&code=D%28X%29%20%3D%20E%5Cleft%5Clbrack%20X%20-%20E%28X%29%20%5Cright%5Crbrack%5E%7B2%7D%20%3D%20E%28X%5E%7B2%7D%29%20-%20%5Cleft%5Clbrack%20E%28X%29%20%5Cright%5Crbrack%5E%7B2%7D&id=VTrML)
3.标准差:%7D#card=math&code=%5Csqrt%7BD%28X%29%7D&id=WzcBv),
4.离散型:%20%3D%20%5Csum%7Bi%7D%5E%7B%7D%7B%5Cleft%5Clbrack%20x%7Bi%7D%20-%20E(X)%20%5Cright%5Crbrack%5E%7B2%7Dp%7Bi%7D%7D#card=math&code=D%28X%29%20%3D%20%5Csum%7Bi%7D%5E%7B%7D%7B%5Cleft%5Clbrack%20x%7Bi%7D%20-%20E%28X%29%20%5Cright%5Crbrack%5E%7B2%7Dp%7Bi%7D%7D&id=vJZB8)
5.连续型:%20%3D%20%7B%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%5Cleft%5Clbrack%20x%20-%20E(X)%20%5Cright%5Crbrack%7D%5E%7B2%7Df(x)dx#card=math&code=D%28X%29%20%3D%20%7B%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%5Cleft%5Clbrack%20x%20-%20E%28X%29%20%5Cright%5Crbrack%7D%5E%7B2%7Df%28x%29dx&id=Ud53G)
性质:
(1)%20%3D%200%2CD%5Clbrack%20E(X)%5Crbrack%20%3D%200%2CD%5Clbrack%20D(X)%5Crbrack%20%3D%200#card=math&code=%5C%20D%28C%29%20%3D%200%2CD%5Clbrack%20E%28X%29%5Crbrack%20%3D%200%2CD%5Clbrack%20D%28X%29%5Crbrack%20%3D%200&id=oslfy)
(2) 与
相互独立,则
%20%3D%20D(X)%20%2B%20D(Y)#card=math&code=D%28X%20%5Cpm%20Y%29%20%3D%20D%28X%29%20%2B%20D%28Y%29&id=fvgxY)
(3)%20%3D%20C%7B1%7D%5E%7B2%7DD%5Cleft(%20X%20%5Cright)#card=math&code=%5C%20D%5Cleft%28%20C%7B1%7DX%20%2B%20C%7B2%7D%20%5Cright%29%20%3D%20C%7B1%7D%5E%7B2%7DD%5Cleft%28%20X%20%5Cright%29&id=tRJeu)
(4) 一般有 %20%3D%20D(X)%20%2B%20D(Y)%20%5Cpm%202Cov(X%2CY)%20%3D%20D(X)%20%2B%20D(Y)%20%5Cpm%202%5Crho%5Csqrt%7BD(X)%7D%5Csqrt%7BD(Y)%7D#card=math&code=D%28X%20%5Cpm%20Y%29%20%3D%20D%28X%29%20%2B%20D%28Y%29%20%5Cpm%202Cov%28X%2CY%29%20%3D%20D%28X%29%20%2B%20D%28Y%29%20%5Cpm%202%5Crho%5Csqrt%7BD%28X%29%7D%5Csqrt%7BD%28Y%29%7D&id=wSPkJ)
(5)%20%3C%20E%5Cleft(%20X%20-%20C%20%5Cright)%5E%7B2%7D%2CC%20%5Cneq%20E%5Cleft(%20X%20%5Cright)#card=math&code=%5C%20D%5Cleft%28%20X%20%5Cright%29%20%3C%20E%5Cleft%28%20X%20-%20C%20%5Cright%29%5E%7B2%7D%2CC%20%5Cneq%20E%5Cleft%28%20X%20%5Cright%29&id=TQpwx)
(6)%20%3D%200%20%5CLeftrightarrow%20P%5Cleft%5C%7B%20X%20%3D%20C%20%5Cright%5C%7D%20%3D%201#card=math&code=%5C%20D%28X%29%20%3D%200%20%5CLeftrightarrow%20P%5Cleft%5C%7B%20X%20%3D%20C%20%5Cright%5C%7D%20%3D%201&id=Kk1Wq)
6.随机变量函数的数学期望
(1) 对于函数#card=math&code=Y%20%3D%20g%28x%29&id=MOwDj)
为离散型:
%20%3D%20%5Csum%7Bi%7D%5E%7B%7D%7Bg(x%7Bi%7D)p%7Bi%7D%7D#card=math&code=P%5C%7B%20X%20%3D%20x%7Bi%7D%5C%7D%20%3D%20p%7Bi%7D%2CE%28Y%29%20%3D%20%5Csum%7Bi%7D%5E%7B%7D%7Bg%28x%7Bi%7D%29p%7Bi%7D%7D&id=Y6mdC);
为连续型:
%2CE(Y)%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bg(x)f(x)dx%7D#card=math&code=X%5Csim%20f%28x%29%2CE%28Y%29%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bg%28x%29f%28x%29dx%7D&id=br6wI)
(2) #card=math&code=Z%20%3D%20g%28X%2CY%29&id=NUnaD);
%5Csim%20P%5C%7B%20X%20%3D%20x%7Bi%7D%2CY%20%3D%20y%7Bj%7D%5C%7D%20%3D%20p%7B%7Bij%7D%7D#card=math&code=%5Cleft%28%20X%2CY%20%5Cright%29%5Csim%20P%5C%7B%20X%20%3D%20x%7Bi%7D%2CY%20%3D%20y%7Bj%7D%5C%7D%20%3D%20p%7B%7Bij%7D%7D&id=mpZqc);
%20%3D%20%5Csum%7Bi%7D%5E%7B%7D%7B%5Csum%7Bj%7D%5E%7B%7D%7Bg(x%7Bi%7D%2Cy%7Bj%7D)p%7B%7Bij%7D%7D%7D%7D#card=math&code=E%28Z%29%20%3D%20%5Csum%7Bi%7D%5E%7B%7D%7B%5Csum%7Bj%7D%5E%7B%7D%7Bg%28x%7Bi%7D%2Cy%7Bj%7D%29p%7B%7Bij%7D%7D%7D%7D&id=HjW6b)
%5Csim%20f(x%2Cy)#card=math&code=%5Cleft%28%20X%2CY%20%5Cright%29%5Csim%20f%28x%2Cy%29&id=buXqQ);
%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7B%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bg(x%2Cy)f(x%2Cy)dxdy%7D%7D#card=math&code=E%28Z%29%20%3D%20%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7B%5Cint%7B-%20%5Cinfty%7D%5E%7B%2B%20%5Cinfty%7D%7Bg%28x%2Cy%29f%28x%2Cy%29dxdy%7D%7D&id=w59GO)
7.协方差
%20%3D%20E%5Cleft%5Clbrack%20(X%20-%20E(X)(Y%20-%20E(Y))%20%5Cright%5Crbrack#card=math&code=Cov%28X%2CY%29%20%3D%20E%5Cleft%5Clbrack%20%28X%20-%20E%28X%29%28Y%20-%20E%28Y%29%29%20%5Cright%5Crbrack&id=JEdzZ)
8.相关系数
%7D%7B%5Csqrt%7BD(X)%7D%5Csqrt%7BD(Y)%7D%7D#card=math&code=%5Crho_%7B%7BXY%7D%7D%20%3D%20%5Cfrac%7BCov%28X%2CY%29%7D%7B%5Csqrt%7BD%28X%29%7D%5Csqrt%7BD%28Y%29%7D%7D&id=Poexd),
阶原点矩
#card=math&code=E%28X%5E%7Bk%7D%29&id=M1oWn);
阶中心矩
%5Crbrack%7D%5E%7Bk%7D%20%5Cright%5C%7D#card=math&code=E%5Cleft%5C%7B%20%7B%5Clbrack%20X%20-%20E%28X%29%5Crbrack%7D%5E%7Bk%7D%20%5Cright%5C%7D&id=o8wmf)
性质:
(1)%20%3D%20Cov(Y%2CX)#card=math&code=%5C%20Cov%28X%2CY%29%20%3D%20Cov%28Y%2CX%29&id=HfsSL)
(2)%20%3D%20abCov(Y%2CX)#card=math&code=%5C%20Cov%28aX%2CbY%29%20%3D%20abCov%28Y%2CX%29&id=BIGtm)
(3)%20%3D%20Cov(X%7B1%7D%2CY)%20%2B%20Cov(X%7B2%7D%2CY)#card=math&code=%5C%20Cov%28X%7B1%7D%20%2B%20X%7B2%7D%2CY%29%20%3D%20Cov%28X%7B1%7D%2CY%29%20%2B%20Cov%28X%7B2%7D%2CY%29&id=ZdfwO)
(4)%20%5Cright%7C%20%5Cleq%201#card=math&code=%5C%20%5Cleft%7C%20%5Crho%5Cleft%28%20X%2CY%20%5Cright%29%20%5Cright%7C%20%5Cleq%201&id=okHY7)
(5) %20%3D%201%20%5CLeftrightarrow%20P%5Cleft(%20Y%20%3D%20aX%20%2B%20b%20%5Cright)%20%3D%201#card=math&code=%5C%20%5Crho%5Cleft%28%20X%2CY%20%5Cright%29%20%3D%201%20%5CLeftrightarrow%20P%5Cleft%28%20Y%20%3D%20aX%20%2B%20b%20%5Cright%29%20%3D%201&id=Sl4oO) ,其中
%20%3D%20-%201%20%5CLeftrightarrow%20P%5Cleft(%20Y%20%3D%20aX%20%2B%20b%20%5Cright)%20%3D%201#card=math&code=%5Crho%5Cleft%28%20X%2CY%20%5Cright%29%20%3D%20-%201%20%5CLeftrightarrow%20P%5Cleft%28%20Y%20%3D%20aX%20%2B%20b%20%5Cright%29%20%3D%201&id=HnrSv)
,其中
9.重要公式与结论
(1)%20%3D%20E(X%5E%7B2%7D)%20-%20E%5E%7B2%7D(X)#card=math&code=%5C%20D%28X%29%20%3D%20E%28X%5E%7B2%7D%29%20-%20E%5E%7B2%7D%28X%29&id=E1hBi)
(2)%20%3D%20E(XY)%20-%20E(X)E(Y)#card=math&code=%5C%20Cov%28X%2CY%29%20%3D%20E%28XY%29%20-%20E%28X%29E%28Y%29&id=FZ2m1)
(3) %20%5Cright%7C%20%5Cleq%201%2C#card=math&code=%5Cleft%7C%20%5Crho%5Cleft%28%20X%2CY%20%5Cright%29%20%5Cright%7C%20%5Cleq%201%2C&id=EzKUH)且
%20%3D%201%20%5CLeftrightarrow%20P%5Cleft(%20Y%20%3D%20aX%20%2B%20b%20%5Cright)%20%3D%201#card=math&code=%5Crho%5Cleft%28%20X%2CY%20%5Cright%29%20%3D%201%20%5CLeftrightarrow%20P%5Cleft%28%20Y%20%3D%20aX%20%2B%20b%20%5Cright%29%20%3D%201&id=A20Ew),其中
%20%3D%20-%201%20%5CLeftrightarrow%20P%5Cleft(%20Y%20%3D%20aX%20%2B%20b%20%5Cright)%20%3D%201#card=math&code=%5Crho%5Cleft%28%20X%2CY%20%5Cright%29%20%3D%20-%201%20%5CLeftrightarrow%20P%5Cleft%28%20Y%20%3D%20aX%20%2B%20b%20%5Cright%29%20%3D%201&id=PQiF7),其中
(4) 下面5个条件互为充要条件:
%20%3D%200#card=math&code=%5Crho%28X%2CY%29%20%3D%200&id=eRAlk)
%20%3D%200#card=math&code=%5CLeftrightarrow%20Cov%28X%2CY%29%20%3D%200&id=uBqrM)
%20%3D%20E(X)E(Y)#card=math&code=%5CLeftrightarrow%20E%28X%2CY%29%20%3D%20E%28X%29E%28Y%29&id=lCGkr)
%20%3D%20D(X)%20%2B%20D(Y)#card=math&code=%5CLeftrightarrow%20D%28X%20%2B%20Y%29%20%3D%20D%28X%29%20%2B%20D%28Y%29&id=pWlkx)
%20%3D%20D(X)%20%2B%20D(Y)#card=math&code=%5CLeftrightarrow%20%20D%28X%20-%20Y%29%20%3D%20D%28X%29%20%2B%20D%28Y%29&id=lF0sb)
注:与
独立为上述5个条件中任何一个成立的充分条件,但非必要条件。
数理统计的基本概念
1.基本概念
总体:研究对象的全体,它是一个随机变量,用表示。
个体:组成总体的每个基本元素。
简单随机样本:来自总体的
个相互独立且与总体同分布的随机变量
,称为容量为
的简单随机样本,简称样本。
统计量:设是来自总体
的一个样本,
#card=math&code=g%28X%7B1%7D%2CX%7B2%7D%5Ccdots%2CX%7Bn%7D%29&id=WGaRo))是样本的连续函数,且
#card=math&code=g%28%29&id=M31Iu)中不含任何未知参数,则称#card=math&code=g%28X%7B1%7D%2CX%7B2%7D%5Ccdots%2CX_%7Bn%7D%29&id=fjAq4)为统计量。
样本均值:
样本方差:%7D%5E%7B2%7D#card=math&code=S%5E%7B2%7D%20%3D%20%5Cfrac%7B1%7D%7Bn%20-%201%7D%5Csum%7Bi%20%3D%201%7D%5E%7Bn%7D%7B%28X%7Bi%7D%20-%20%5Coverline%7BX%7D%29%7D%5E%7B2%7D&id=XBxsS)
样本矩:样本阶原点矩:
样本阶中心矩:
%7D%5E%7Bk%7D%2Ck%20%3D%201%2C2%2C%5Ccdots#card=math&code=B%7Bk%7D%20%3D%20%5Cfrac%7B1%7D%7Bn%7D%5Csum%7Bi%20%3D%201%7D%5E%7Bn%7D%7B%28X_%7Bi%7D%20-%20%5Coverline%7BX%7D%29%7D%5E%7Bk%7D%2Ck%20%3D%201%2C2%2C%5Ccdots&id=Dq3jK)
2.分布
分布:
#card=math&code=%5Cchi%5E%7B2%7D%20%3D%20X%7B1%7D%5E%7B2%7D%20%2B%20X%7B2%7D%5E%7B2%7D%20%2B%20%5Ccdots%20%2B%20X%7Bn%7D%5E%7B2%7D%5Csim%5Cchi%5E%7B2%7D%28n%29&id=UHz9K),其中相互独立,且同服从
#card=math&code=N%280%2C1%29&id=UdM8X)
分布:
#card=math&code=T%20%3D%20%5Cfrac%7BX%7D%7B%5Csqrt%7BY%2Fn%7D%7D%5Csim%20t%28n%29&id=jCA1m) ,其中
%2CY%5Csim%5Cchi%5E%7B2%7D(n)%2C#card=math&code=X%5Csim%20N%5Cleft%28%200%2C1%20%5Cright%29%2CY%5Csim%5Cchi%5E%7B2%7D%28n%29%2C&id=sN8pf)且
,
相互独立。
分布:
#card=math&code=F%20%3D%20%5Cfrac%7BX%2Fn%7B1%7D%7D%7BY%2Fn%7B2%7D%7D%5Csim%20F%28n%7B1%7D%2Cn%7B2%7D%29&id=FvEsi),其中
%2CY%5Csim%5Cchi%5E%7B2%7D(n%7B2%7D)%2C#card=math&code=X%5Csim%5Cchi%5E%7B2%7D%5Cleft%28%20n%7B1%7D%20%5Cright%29%2CY%5Csim%5Cchi%5E%7B2%7D%28n_%7B2%7D%29%2C&id=ffqg4)且
,
相互独立。
分位数:若%20%3D%20%5Calpha%2C#card=math&code=P%28X%20%5Cleq%20x%7B%5Calpha%7D%29%20%3D%20%5Calpha%2C&id=O1Whw)则称为
的
分位数
3.正态总体的常用样本分布
(1) 设为来自正态总体
#card=math&code=N%28%5Cmu%2C%5Csigma%5E%7B2%7D%29&id=WxIZg)的样本,
%7D%5E%7B2%7D%2C%7D#card=math&code=%5Coverline%7BX%7D%20%3D%20%5Cfrac%7B1%7D%7Bn%7D%5Csum%7Bi%20%3D%201%7D%5E%7Bn%7DX%7Bi%7D%2CS%5E%7B2%7D%20%3D%20%5Cfrac%7B1%7D%7Bn%20-%201%7D%5Csum%7Bi%20%3D%201%7D%5E%7Bn%7D%7B%7B%28X%7Bi%7D%20-%20%5Coverline%7BX%7D%29%7D%5E%7B2%7D%2C%7D&id=rvFYa)则:
%7B%5C%20%5C%20%7D#card=math&code=%5Coverline%7BX%7D%5Csim%20N%5Cleft%28%20%5Cmu%2C%5Cfrac%7B%5Csigma%5E%7B2%7D%7D%7Bn%7D%20%5Cright%29%7B%5C%20%5C%20%7D&id=a7EHU)或者
#card=math&code=%5Cfrac%7B%5Coverline%7BX%7D%20-%20%5Cmu%7D%7B%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D%5Csim%20N%280%2C1%29&id=huut3)
S%5E%7B2%7D%7D%7B%5Csigma%5E%7B2%7D%7D%20%3D%20%5Cfrac%7B1%7D%7B%5Csigma%5E%7B2%7D%7D%5Csum%7Bi%20%3D%201%7D%5E%7Bn%7D%7B%7B(X%7Bi%7D%20-%20%5Coverline%7BX%7D)%7D%5E%7B2%7D%5Csim%5Cchi%5E%7B2%7D(n%20-%201)%7D#card=math&code=%5Cfrac%7B%28n%20-%201%29S%5E%7B2%7D%7D%7B%5Csigma%5E%7B2%7D%7D%20%3D%20%5Cfrac%7B1%7D%7B%5Csigma%5E%7B2%7D%7D%5Csum%7Bi%20%3D%201%7D%5E%7Bn%7D%7B%7B%28X%7Bi%7D%20-%20%5Coverline%7BX%7D%29%7D%5E%7B2%7D%5Csim%5Cchi%5E%7B2%7D%28n%20-%201%29%7D&id=RqTL0)
%7D%5E%7B2%7D%5Csim%5Cchi%5E%7B2%7D(n)%7D#card=math&code=%5Cfrac%7B1%7D%7B%5Csigma%5E%7B2%7D%7D%5Csum%7Bi%20%3D%201%7D%5E%7Bn%7D%7B%7B%28X%7Bi%7D%20-%20%5Cmu%29%7D%5E%7B2%7D%5Csim%5Cchi%5E%7B2%7D%28n%29%7D&id=E3oMI)
4)#card=math&code=%7B%5C%20%5C%20%7D%5Cfrac%7B%5Coverline%7BX%7D%20-%20%5Cmu%7D%7BS%2F%5Csqrt%7Bn%7D%7D%5Csim%20t%28n%20-%201%29&id=JRCyQ)
4.重要公式与结论
(1) 对于#card=math&code=%5Cchi%5E%7B2%7D%5Csim%5Cchi%5E%7B2%7D%28n%29&id=HEtYV),有
)%20%3D%20n%2CD(%5Cchi%5E%7B2%7D(n))%20%3D%202n%3B#card=math&code=E%28%5Cchi%5E%7B2%7D%28n%29%29%20%3D%20n%2CD%28%5Cchi%5E%7B2%7D%28n%29%29%20%3D%202n%3B&id=uXRQl)
(2) 对于#card=math&code=T%5Csim%20t%28n%29&id=ryyjs),有
%20%3D%200%2CD(T)%20%3D%20%5Cfrac%7Bn%7D%7Bn%20-%202%7D(n%20%3E%202)#card=math&code=E%28T%29%20%3D%200%2CD%28T%29%20%3D%20%5Cfrac%7Bn%7D%7Bn%20-%202%7D%28n%20%3E%202%29&id=fk2KY);
(3) 对于#card=math&code=F%5Ctilde%7B%5C%20%7DF%28m%2Cn%29&id=CGvpC),有
%2CF%7Ba%2F2%7D(m%2Cn)%20%3D%20%5Cfrac%7B1%7D%7BF%7B1%20-%20a%2F2%7D(n%2Cm)%7D%3B#card=math&code=%5Cfrac%7B1%7D%7BF%7D%5Csim%20F%28n%2Cm%29%2CF%7Ba%2F2%7D%28m%2Cn%29%20%3D%20%5Cfrac%7B1%7D%7BF%7B1%20-%20a%2F2%7D%28n%2Cm%29%7D%3B&id=u3U8O)
(4) 对于任意总体,有
%20%3D%20E(X)%2CE(S%5E%7B2%7D)%20%3D%20D(X)%2CD(%5Coverline%7BX%7D)%20%3D%20%5Cfrac%7BD(X)%7D%7Bn%7D#card=math&code=E%28%5Coverline%7BX%7D%29%20%3D%20E%28X%29%2CE%28S%5E%7B2%7D%29%20%3D%20D%28X%29%2CD%28%5Coverline%7BX%7D%29%20%3D%20%5Cfrac%7BD%28X%29%7D%7Bn%7D&id=lrf0h)
