create a matrix with random values based on a normal distrubition

Let take the following data

Mini <- c(8500, 11000,  10500,  12000,  9500,   10500, 12000, 11500)
Kleinwagen <- c(8500,  10500,   10500,  10500,  12500,  12000,  13000,  13500)
Kompatklass <- c(11000, 13000,  12500,  13000,  13500,  15500,  15500,  17500)
minivans <- c(6000, 11500,  10500,  13000,  13000,  14000,  14500,  19000)
sportswagen <- c(12000,  12000, 14000,  18000,  16000,  17000,  26000,  21500)
utilities <- c(7500, 11000, 11500,  11000,  12000,  16500,  16500,  21500)
mittleklass <- c(11000, 12000,  14000,  14000,  15000,  17500,  28000, 26000)
oberemittle <- c(11000,  13500, 14000,  14500,  17000,  20000,  25000, 30500)
bigvans <- c(13000,  12500, 16000,  15000,  16000,  17000,  18500, 37500)

Dist.table <- t(data.frame(Mini, Kleinwagen, Kompatklass, minivans, sportswagen, utilities, mittleklass, oberemittle, bigvans))

Now I assume each value is the mean.

I assume a constant standard deviation of 0.7%

If I use

b <- rnorm(1, mean = Dist.table[1,1], sd=(Dist.table[1,1]*0.7)

I generate a random number for [1,1].

But I want to create a full matrix of random variables