R的t-test检验

1.t-test的功能：单因素二水平的假设检验。

H0:与我们想过要的结果相反的假设，比如我们想要的是两组数据的差异性，那么这个假设是：两组数据没有差异性。

H1或Ha：备择假设，与H0假设相反。

2.t-test的前提：正态性和方差齐性

3.R中的t-test的使用。

t.test(x, y = NULL,alternative = c("two.sided", "less", "greater"),mu = 0, paired = FALSE, var.equal = FALSE,conf.level = 0.95, ...)

或 t.test(formula, data, subset, na.action, ...)

> data
  druga drugb

> t.test(data$druga,data$drugb)

    Welch Two Sample t-test

data:  data$druga and data$drugb
t = -8.1742, df = 5.5846, p-value = 0.0002598
alternative hypothesis: true difference in means is not equal to
 percent confidence interval:
 -11.417221  -6.082779
sample estimates:
mean of x mean of y
    10.75     19.50 

> df
  drug effect

> t.test(effect~drug,data=df)

    Welch Two Sample t-test

data:  effect by drug
t = -8.1742, df = 5.5846, p-value = 0.0002598
alternative hypothesis: true difference in means is not equal to
 percent confidence interval:
 -11.417221  -6.082779
sample estimates:
mean in group  mean in group
          10.75           19.50 

结果解读：

t：t统计值。

df：自由度。

p：H0假设成立的概率。