diff --git a/src/Statistics.jl b/src/Statistics.jl
index 0a3cba4..c6b3278 100644
--- a/src/Statistics.jl
+++ b/src/Statistics.jl
@@ -1024,7 +1024,7 @@ quantile!(v::AbstractVector, p::Real; sorted::Bool=false, alpha::Real=1.0, beta:
 
 # Function to perform partial sort of v for quantiles in given range
 function _quantilesort!(v::AbstractVector, sorted::Bool, minp::Real, maxp::Real)
-    isempty(v) && throw(ArgumentError("empty data vector"))
+    length(v) == 0 && throw(ArgumentError("empty data vector"))
     require_one_based_indexing(v)
 
     if !sorted
@@ -1051,7 +1051,7 @@ end
 
     n = length(v)
 
-    @assert n > 0 # this case should never happen here
+    n > 0 || throw(ArgumentError("quantile is undefined for a length-0 data vector"))
 
     m = alpha + p * (one(alpha) - alpha - beta)
     # Using fma here avoids some rounding errors when aleph is an integer
diff --git a/test/runtests.jl b/test/runtests.jl
index 78c02ea..f3ce7c5 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -709,6 +709,15 @@ end
     @test quantile(skipmissing([1, missing, 2]), 0.5) === 1.5
     @test quantile([1], 0.5) === 1.0
 
+    # length overflows to 0. Same error as an empty vector.
+    let r = typemin(Int):typemax(Int)
+        @test length(r) == 0
+        @test !isempty(r)
+        @test_throws ArgumentError("empty data vector") quantile!([0], r, [1])
+        @test_throws ArgumentError("empty data vector") quantile(r, 0.5; sorted=true)
+    end
+    @test_throws ArgumentError quantile(Int[], 0.5)
+
     # make sure that type inference works correctly in normal cases
     for T in [Int, BigInt, Float64, Float16, BigFloat, Rational{Int}, Rational{BigInt}]
         for S in [Float64, Float16, BigFloat, Rational{Int}, Rational{BigInt}]