样品 | 法A(%) | 法B(%) |
样1 | 0.2566 | 0.2477 |
样2 | 0.2889 | 0.2786 |
样3 | 0.4501 | 0.4334 |
样4 | 0.4211 | 0.4025 |
样5 | 0.2148 | 0.2061 |
样6 | 0.4662 | 0.4433 |
alphastatist 2013/07/26
我习惯用R软件(完全免费),简单易用。 > Avalue<-scan() 1: 0.2566 2: 0.2889 3: 0.4501 4: 0.4211 5: 0.2148 6: 0.4662 7: Read 6 items > Bvalue<-scan() 1: 0.2477 2: 0.2786 3: 0.4334 4: 0.4025 5: 0.2061 6: 0.4433 7: Read 6 items > cbind(Avalue,Bvalue) Avalue Bvalue [1,] 0.2566 0.2477 [2,] 0.2889 0.2786 [3,] 0.4501 0.4334 [4,] 0.4211 0.4025 [5,] 0.2148 0.2061 [6,] 0.4662 0.4433 > t.test(Avalue,Bvalue,paired=T) #R中成对比较只需设置该参数值即可。 Paired t-test data: Avalue and Bvalue t = 5.9463, df = 5, p-value = 0.001922 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: 0.008146513 0.020553487 sample estimates: mean of the differences 0.01435 > t.test(Avalue-Bvalue)#这是按我上面说的方法进行的检验 One Sample t-test data: Avalue - Bvalue t = 5.9463, df = 5, p-value = 0.001922 alternative hypothesis: true mean is not equal to 0 95 percent confidence interval: 0.008146513 0.020553487 sample estimates: mean of x 0.01435 检验结果是拒绝原假设,所以认为两种方法的结果有显著差异
alphastatist
第3楼2013/07/26
我习惯用R软件(完全免费),简单易用。
> Avalue<-scan()
1: 0.2566
2: 0.2889
3: 0.4501
4: 0.4211
5: 0.2148
6: 0.4662
7:
Read 6 items
> Bvalue<-scan()
1: 0.2477
2: 0.2786
3: 0.4334
4: 0.4025
5: 0.2061
6: 0.4433
7:
Read 6 items
> cbind(Avalue,Bvalue)
Avalue Bvalue
[1,] 0.2566 0.2477
[2,] 0.2889 0.2786
[3,] 0.4501 0.4334
[4,] 0.4211 0.4025
[5,] 0.2148 0.2061
[6,] 0.4662 0.4433
> t.test(Avalue,Bvalue,paired=T) #R中成对比较只需设置该参数值即可。
Paired t-test
data: Avalue and Bvalue
t = 5.9463, df = 5, p-value = 0.001922
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
0.008146513 0.020553487
sample estimates:
mean of the differences
0.01435
> t.test(Avalue-Bvalue)#这是按我上面说的方法进行的检验
One Sample t-test
data: Avalue - Bvalue
t = 5.9463, df = 5, p-value = 0.001922
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
0.008146513 0.020553487
sample estimates:
mean of x
0.01435
检验结果是拒绝原假设,所以认为两种方法的结果有显著差异