Alright, so Rsquare is the R-squared of the high of prices (y) with respect to bar number (x).
The slope, ALSO, is the high of prices (y) with respect to bar number(x)?

R-Square (r2) is the coefficient of determination, which measures the proportion of variation that is explained by the independent variable in a regression model. This function takes the value of CoeffR for the specified Length and squares the value. that is, CoeffR(Length) * CoeffR(Length). The RSquared value can be interpreted as the proportion of the variance of Price with respect to the specified period (’Length’).

Linear Regression is a concept also known as the "least squares method" or "best fit." Linear Regression attempts to fit a straight line between several data points in such a way that distance between each data point and the line is minimized.

Returns
A numeric value containing the slope of the current regression line.

Usage
The input Price can be hard coded with a bar attribute such as Close, Open, High, Low, and Volume or a numeric series type input. It can also be replaced with a valid EasyLanguage expression. For example: Close + Open, or Average(RSI(Close,14),14).

The input Length can be hard coded replaced with a numeric simple type input.