R-Squared

R²
= (regression sum of squares)/(total sum of squares)
= (regression sum of squares)/(regression sum of squares + error sum of squares)

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If R² > 50%, then
R²
= (regression sum of squares)/(regression sum of squares + error sum of squares) > 50%

∴ (regression sum of squares) > (error sum of squares)

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A low R² in the regression (equation) indicates that the slopes in the equation are very close to zero, indicating that the dependent variable is unaffected by the independent variables. For instance, if all the slopes in the equation equals zero, then the dependent variable equals the intercept(a₀, which is constant over time).