You can compute the slope of linear regression (without weights) by:
cor(x, y) * sd(y) / sd(x)
If we have add weights (w) in here as well - how do you compute the slope then?
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1Basically, you in general form you can use ordinary least squares, and with weights, you can use the [weighted form](https://en.wikipedia.org/wiki/Weighted_least_squares), is this what you ask, or is it if you can use correlations and variances for this? – Tim Jul 26 '19 at 17:01
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The duplicate threads were discovered by inspecting the highest-voted relevant hits in the search https://stats.stackexchange.com/search?tab=votes&q=weighted%20%22least%20squares%22. Other hits may be of interest, too. – whuber Jul 26 '19 at 17:09