The statistical properties of least-squares frequency analysis of unequally spaced data are examined. It is shown that, in the least-squares spectrum of gaussian noise, the reduction in the sum of squares at a particular frequency is aX 2 2 variable. The reductions at different frequencies are not independent, as there is a correlation between the height of the spectrum at any two frequencies,f 1 andf 2, which is equal to the mean height of the spectrum due to a sinusoidal signal of frequencyf 1, at the frequencyf 2. These correlations reduce the distortion in the spectrum of a signal affected by noise. Some numerical illustrations of the properties of least-squares frequency spectra are also given.