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`

.