【回归分析】[3]--回归方程的显著性检验

【回归分析】[3]--回归方程的显著性检验

这篇文章准备使用一个例子来说明。

例子的数据：

data2 = {
   
   {391.95, 488.51}, {516.98, 798.30}, {355.63, 
    235.08}, {238.55, 299.45}, {537.78, 559.09}, {733.78, 
    1133.25}, {198.83, 348.74}, {252.62, 417.78}, {206.20, 
    344.52}, {231.18, 323.08}, {449.76, 620.75}, {288.57, 
    423.30}, {185.74, 202.61}, {1164.39, 1531.53}, {444.58, 
    553.48}, {412.87, 685.97}, {272.28, 324.24}, {781.80, 
    983.24}, {1209.22, 1762.02}, {825.51, 960.31}, {223.75, 
    284.61}, {354.84, 407.76}, {515.52, 982.66}, {220.46, 
    557.00}, {337.67, 440.92}, {197.12, 268.06}, {133.24, 
    262.05}, {374.01, 432.50}, {273.84, 338.36}, {570.36, 
    704.32}, {391.29, 585.68}, {201.86, 267.78}, {321.63, 
    408.34}, {838.90, 1165.57}};

这个是这次的要讲的内容顺序

1.B0，B1的性质（就不写公式了）

   (a).无偏性

   (b).x(i)越分散，就使方差越小

2.检验是否满足线性假定

(a).散点图--其实大多数