# Low variation in the explanatory variable: scale of the predictor

As explained in this post - > There are low variations in the explanatory variables, low variation of your explanatory variable might affect your results.

The way I used to find that intuitive was graphically : if your values are concentrated on a small range of x then they would less reliable for estimating a slope.

I'm dealing with a continuous variable with low variation (0.3XXXXXXXX to 0.03XXXXXXXX) and I no longer see that explanation intuitive. It seems to me that the scale of X affects the reliability of the predictor. For instance, in an scale of 1.X, this values would be very close together hence affecting the slope, while in a scale of 0.1XXX the reliability of the slope would be different.

So how can I know if my continuous x variable have enough variation for providing a reliable effect on y?

• I agree. Good question. Apr 26, 2017 at 14:54
• What is a reliable effect? Small variation does not affect estimation within the range of x very much but it would increase the uncertainty for extrapolation. Apr 26, 2017 at 15:01
• The best way to assess a scatterplot when you are contemplating a regression is to standardize both variables so that each has the same standard deviation. Otherwise, "low variation" is meaningless.
– whuber
Dec 29, 2023 at 15:38