I have two arrays (m and n) and each has one column with 100 elements. the first array is sampled from a normal distribution with mean 0 and standard deviation 1, the second one is sampled from a normal distribution with mean 0 and standard deviation 3.

I want to add these two arrays to get a new array. the question is how can I transform or standardize the two arrays?

```
m = randn(rng, Float64, (100, 1))
100×1 Array{Float64,2}:
0.18397640704112656
-1.2763483553703483
1.031320291955949
-0.9108047660076668
0.7546031994011986
-1.294747093887164
-0.3089435053618516
1.3066837674632528
1.4488604613960603
0.7781507199519165
0.6526940815724932
0.10432909231227107
0.7417843503426419
⋮
using Distributions
d = Normal(0,3)
n = rand(d,100)
100-element Array{Float64,1}:
4.943981277982362
0.923775176919609
1.3120277665167939
-3.413412184066308
0.35350629626912417
-3.0048652472107475
-4.584157706726311
-0.683813163262671
-2.7436028613278802
2.3003065716043736
0.3479689939195823
5.163561281577351
0.6694418345732615
⋮
```

I tried the `fit(ZScoreTransform, m; dims=nothing, center=true, scale=true)`

in Julia for m and n and I got error for m `X must contain at least two columns.`

and for n `TypeError: in keyword argument dims, expected Integer, got a value of type Nothing`

looks like the `ZScoreTransform`

is for matrix transformation, is there any way to standardize the arrays in Julia?

thanks