This is what I understand from what you are saying, you want to "exclude rows with a value of 1 in the completeness column" and "run summary statistics on my data without the rows that have the value of 1 in the completeness column".
Then this would do the job
# Details about the used libraries
library(dplyr)
# Sample data on a copy/paste friendly format
all_data_merged <- data.frame(
site = c(4, 4, 4, 4, 4, 4, 4, 4, 4),
Weight = c(7.76, 8.44, 7.67, 7.51, 10.19, 8.47, 4.81, 4.88, 5.46),
Completeness = c(2, 2, 1, 2, 4, 1, 1, 2, 4),
termination = c(2, 3, 0, 1, 5, 0, 0, 5, 5)
)
# Relevant code
all_data_merged %>%
filter(Completeness != 1) %>%
summary()
#> site Weight Completeness termination
#> Min. :4 Min. : 4.880 Min. :2.000 Min. :1.00
#> 1st Qu.:4 1st Qu.: 5.973 1st Qu.:2.000 1st Qu.:2.25
#> Median :4 Median : 7.635 Median :2.000 Median :4.00
#> Mean :4 Mean : 7.373 Mean :2.667 Mean :3.50
#> 3rd Qu.:4 3rd Qu.: 8.270 3rd Qu.:3.500 3rd Qu.:5.00
#> Max. :4 Max. :10.190 Max. :4.000 Max. :5.00
Note: Please notice the way I'm sharing the sample data and code, that would be the proper way of posting a reproducible example.