nycflights13数据集cor.test分析dep_delay与distance相关性报错求助

我需要基于nycflights13数据集，对dep_delay（出发延误）和distance（飞行距离）执行cor.test相关性检验，要求先剔除异常值，预期结果需包含t = -14.451, df = 326677, cor = -0.02527463这类信息。

已完成的异常值阈值计算 #

我通过分位数法确定了异常值阈值，代码如下：

delay_thresh = quantile(flights$dep_delay, p=c(0.003, 0.997), na.rm=T)
dist_thresh = quantile(flights$distance,p=c(0.003, 0.997), na.rm=T)
                  
Q1a <- which(flights$dep_delay>delay_thresh | flights$dep_delay<delay_thresh)
Q1b <- which(flights$distance>dist_thresh | flights$distance<dist_thresh)
Q1b <- na.omit(Q1b) 
Q1a <- na.omit(Q1a)

执行cor.test时的报错情况 #

后续执行cor.test时多次报错，具体尝试及错误如下：

1. 尝试写法1：

cor.test(flights$dep_delay ~ flights$distance)

报错信息：

Error in cor.test.formula(flights$dep_delay ~ flights$distance) :
'formula' missing or invalid

2. 尝试写法2：

cor.test(formula = dep_delay~distance, flights)

报错信息：

Error in cor.test.default(formula = dep_delay ~ distance, flights) :
'x' must be a numeric vector

3. 尝试写法3：

cor.test(delay_thresh, dist_thresh)

报错信息：

Error in cor.test.default(delay_thresh, dist_thresh) :
not enough finite observations

尝试索引法但结果不符合预期 #

我曾用索引法尝试得到结果，但并非剔除异常值后的预期结果：

> indices = union(
+       which(flights$dep_delay>delay_thresh[1] & flights$dep_delay<delay_thresh[2]),
+       which(flights$distance>dist_thresh[1] & flights$distance<dist_thresh[2]))
> Q2 <- cor.test(flights$dep_delay[indices], flights$distance[indices])
> Q2

Pearson's product-moment correlation

data:  flights$dep_delay[indices] and flights$distance[indices]
t = -13.897, df = 328459, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.02765802 -0.02082235
sample estimates:
        cor 
-0.02424047

后续尝试其他方法仍报错，包括样本量不足、向量长度不匹配等，研究多日仍未解决，寻求帮助。

内容的提问来源于stack exchange，提问作者Kdoyle73