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I'm new to statistics and I ran into this question, what I know is $Y=A + BX$ but in the question the value of $B$ is negative, is it normal for the $B$ value to be negative?

Here is the question, you don't have to answer it, I just added as a reference.

Estimate the value of $Y$ when $X = 30$ for the following regression equation: $Y = 6.2 - 1.4 X$.

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$B = -1.4$ for you: $Y = 6.2 + (-1.4)X$. What this means is that same as if it were $+1.4$: that for every one-unit change in $X$, there is a $B$-unit change in $Y$. In this particular case, the change is that, for every one-unit change in $X$, $Y$ decreases by $1.4$ units.

$B<0$ is certainly acceptable. Consider a relationship like expected snowfall tomorrow as $Y$ and today's temperature as $X$.

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  • $\begingroup$ Your snowfall-temperature example is wrong, apart from that relation being very nonlinear, consider temperature $-15^\circ\text{C}$, there will not be snowing. Increase temperature with 10 degrees, expected snowfall will increase! $\endgroup$ – kjetil b halvorsen♦ Jul 30 '20 at 0:44
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Yes you can have negative weights. The simplest example of when this would happen is when you have a factor that has a negative correlation to the output Y. This would imply for every X unit increase, there should be a corresponding B * X decrease in Y. In your example, for every unit increase of X, Y should decrease by a factor of 1.4

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