Fixed test error in Julia 1.3 and a couple README typos.

Author: chriselrod

README.md

@@ -173,7 +173,7 @@ At small sizes, this can be fast.
  <summaryClick me! ></summary>
 <p>
 
-The key to the `@avx` macro's performance gains is leveraging knowledge of exactly how data like `Float64`s and `Int`s are handled by a CPU. As such, it is not strightforward to generalize the `@avx` macro to work on arrays conatining structs such as `Matrix{Complex{Float64}}`. Instead, it is currently reccomended that users wishing to apply `@avx` to arrays of structs use packages such as [StructArrays.jl](https://github.com/JuliaArrays/StructArrays.jl) which transform an array where each element is a struct into a struct where each element is an array. Using StructArrays.jl, we can write a matrix multiply (gemm) kernel that works on matrices of `Complex{Float64}`s and `Complex{Int}`s:
+The key to the `@avx` macro's performance gains is leveraging knowledge of exactly how data like `Float64`s and `Int`s are handled by a CPU. As such, it is not strightforward to generalize the `@avx` macro to work on arrays containing structs such as `Matrix{Complex{Float64}}`. Instead, it is currently recommended that users wishing to apply `@avx` to arrays of structs use packages such as [StructArrays.jl](https://github.com/JuliaArrays/StructArrays.jl) which transform an array where each element is a struct into a struct where each element is an array. Using StructArrays.jl, we can write a matrix multiply (gemm) kernel that works on matrices of `Complex{Float64}`s and `Complex{Int}`s:
 ```julia 
 using LoopVectorization, LinearAlgebra, StructArrays, BenchmarkTools, Test
 

test/runtests.jl

@@ -345,7 +345,11 @@ using LinearAlgebra
     lsdot3 = LoopVectorization.LoopSet(dot3q);
     LoopVectorization.choose_order(lsdot3)
 
-    # dot3(x, A, y) = dot(x, A * y)
+    @static if VERSION < v"1.4"
+        dot3(x, A, y) = dot(x, A * y)
+    else
+        dot3(x, A, y) = dot(x, A, y)
+    end
     function dot3avx(x, A, y)
         M, N = size(A)
         s = zero(promote_type(eltype(x), eltype(A), eltype(y)))
@@ -450,7 +454,7 @@ using LinearAlgebra
 
         M, N = 47, 73;
         x = rand(T, M); A = rand(T, M, N); y = rand(T, N);
-        @test dot3avx(x, A, y) ≈ dot(x, A, y)
+        @test dot3avx(x, A, y) ≈ dot3(x, A, y)
 
     end
 end