I understand that you want to compare the values in the Average column paired according to the Time. I invented a small data set since you only provided two rows of data and I did the analysis in two ways. In the first I used the t.test "formula interface" to express that Average should be compared at different values of Time. In the second version, I reshaped the data so that each row contains the associated Average values at Time = -5 and Time = 0. Compare the original DF to the reshaped DFwide to see how the values were repositioned. You can see that the t.test results are identical.
DF <- data.frame(Replica = rep(1:10, each = 2), Bay = "Vast",
Boat = "Small", Time = rep(c(-5, 0),10),
Depth = 1.5, Average = rnorm(20, mean = 2, sd = 1),
S.D. = runif(20), Difference = runif(20))
DF
#> Replica Bay Boat Time Depth Average S.D. Difference
#> 1 1 Vast Small -5 1.5 2.6417051 0.3804981 0.089201455
#> 2 1 Vast Small 0 1.5 2.4371311 0.1179992 0.483146503
#> 3 2 Vast Small -5 1.5 1.5411826 0.3809335 0.661100151
#> 4 2 Vast Small 0 1.5 2.1577250 0.8123062 0.858314304
#> 5 3 Vast Small -5 1.5 2.8430718 0.1873026 0.342631383
#> 6 3 Vast Small 0 1.5 2.0120656 0.2718236 0.501260335
#> 7 4 Vast Small -5 1.5 1.6510801 0.1848850 0.022939839
#> 8 4 Vast Small 0 1.5 1.1311523 0.9912124 0.007652733
#> 9 5 Vast Small -5 1.5 2.7574756 0.3490825 0.205818067
#> 10 5 Vast Small 0 1.5 2.0995803 0.5960672 0.529268654
#> 11 6 Vast Small -5 1.5 2.3222794 0.4882487 0.667002798
#> 12 6 Vast Small 0 1.5 2.1940413 0.4801476 0.122623173
#> 13 7 Vast Small -5 1.5 1.4695869 0.5236233 0.350077632
#> 14 7 Vast Small 0 1.5 2.5456604 0.1529702 0.534559767
#> 15 8 Vast Small -5 1.5 1.9984230 0.9445697 0.793341777
#> 16 8 Vast Small 0 1.5 0.1577001 0.9629901 0.281684059
#> 17 9 Vast Small -5 1.5 2.9099732 0.3908567 0.981132287
#> 18 9 Vast Small 0 1.5 2.1025757 0.4880733 0.501476942
#> 19 10 Vast Small -5 1.5 2.3203045 0.5813115 0.046676651
#> 20 10 Vast Small 0 1.5 1.7892412 0.2017480 0.904602418
t.test(Average ~ Time, paired = TRUE, data = DF)
#>
#> Paired t-test
#>
#> data: Average by Time
#> t = 1.502, df = 9, p-value = 0.1674
#> alternative hypothesis: true difference in means is not equal to 0
#> 95 percent confidence interval:
#> -0.1937574 0.9593993
#> sample estimates:
#> mean of the differences
#> 0.3828209
library(dplyr)
library(tidyr)
DFwide <- DF |> select(-S.D., -Difference) |>
pivot_wider(names_from = Time, values_from = Average, names_prefix = "T_") |>
rename(T_m5 = `T_-5`)
DFwide
#> # A tibble: 10 x 6
#> Replica Bay Boat Depth T_m5 T_0
#> <int> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 1 Vast Small 1.5 2.64 2.44
#> 2 2 Vast Small 1.5 1.54 2.16
#> 3 3 Vast Small 1.5 2.84 2.01
#> 4 4 Vast Small 1.5 1.65 1.13
#> 5 5 Vast Small 1.5 2.76 2.10
#> 6 6 Vast Small 1.5 2.32 2.19
#> 7 7 Vast Small 1.5 1.47 2.55
#> 8 8 Vast Small 1.5 2.00 0.158
#> 9 9 Vast Small 1.5 2.91 2.10
#> 10 10 Vast Small 1.5 2.32 1.79
t.test(x = DFwide$T_m5, y = DFwide$T_0, paired = TRUE)
#>
#> Paired t-test
#>
#> data: DFwide$T_m5 and DFwide$T_0
#> t = 1.502, df = 9, p-value = 0.1674
#> alternative hypothesis: true difference in means is not equal to 0
#> 95 percent confidence interval:
#> -0.1937574 0.9593993
#> sample estimates:
#> mean of the differences
#> 0.3828209
Created on 2022-07-04 by the reprex package (v2.0.1)
The problem with your use of t.test(),
t.test(Dist.T.10.S.V.R1, x = "Time", y = "Average", paired = TRUE, alternative = "two.sided")
was that you passed your data frame name, Dist.T.10.S.V.R1, as an unnamed argument. It got assigned to the mu argument, which is the expected difference in averages when you run a paired test. Here is the Help file description of the t.test function
t.test(x, y = NULL,
alternative = c("two.sided", "less", "greater"),
mu = 0, paired = FALSE, var.equal = FALSE,
conf.level = 0.95, ...)
You passed it x, y, paired, alternative, and the unnamed argument. Among the possible arguments, mu is the first one you have not explicitly named, so t.test() tried to use Dist.T.10.S.V.R1 as mu.