[英]Dplyr: How to Rearrange and Split a Dataframe by A Categorical Group Within a Pivot Table Showing Summary Statistics in R
[英]Drop a Categorical Level <- Dplyr <- Statistics With R
使用R中的dplyr包,我试图将类别变量从3个级别变为仅2个级别。我正在使用著名的iris数据集并尝试将类变量(包括:“ Iris-versicolor”,“ Iris -setosa”和“ Iris-virginica”)分为两个级别(包含:“ Iris-versicolor”,“ Iris-setosa”)。 因此,我想创建一个新的数据集:
IRIS_TEST2 <- IRIS_TEST %>%
filter(class != "Iris-virginica")
因此,当我尝试对其进行假设检验时:
inference(y = sepal_length, x = class, data = IRIS_TEST2, statistic = "mean", type =
"ci", method = "theoretical", conf_level = .95)
我继续出现错误:
Error: Categorical variable has more than 2 levels, confidence interval is undefined,
use ANOVA to test for a difference between means
或者,我可以使用一种方式来附加“ x =“,以仅包括“ Iris-versicolor”和“ Iris-setosa”
inference(y = sepal_length, x = class, data = IRIS_TEST2, statistic = "mean", type =
"ci", method = "theoretical", conf_level = .95)
任何帮助将不胜感激!
过滤掉不需要的类(并将其存储到新变量中)之后,我可以运行以下代码:
IRIS_TEST2$class <- factor(IRIS_TEST2$class)
这使我只有两个级别,而且我能够运行假设检验并找到置信区间
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