As a test I made up a sine wave in MATLAB of this form

    y = 5*sin((2 * pi * freq).*x + 1.4) - 6;

where `freq` is `10` and `x` varies from $0$ to $1.5$ with a resolution of `1/1000` as shown below

    fs = 1000;
    x = 0:1/fs: 1.5 - (1/fs);

So I already know the frequency to be able to verify it with `fft`. After computing the amplitude FFT `abs(fft(yy))`, I find that the frequency bin with the highest magnitude is $16$. Since I have $1500$ samples which correspond to a sampling frequency of $1000$ then the 16$^\rm{th}$ bin corresponds to

$$\mathrm{\frac{Frequency \ Bin \times Sampling \ Frequency}{Number \ of\ Samples} = \frac{16 \times 1000}{1500} = 10.6667\ Hz}$$

However I know that my frequency I hardcoded is actually $10\ \rm Hz$. This can be repeated with different values and the same inaccurate result keeps occurring. And the smaller the hardcoded frequency the  larger the error in the result. Why is this happening?