Linear Regression R-Squared [RSQ]

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The Linear Regression R-Squared function determines the extent of a linear relationship of a field to time over a given period of time using the square of the Pearson product moment correlation coefficient. Parameters ------------------ Data          The data to use in the relationship. This is typically a field in a data series or a calculated value. Period        The number of bars of data to include in the relationship, including the current value.                   For example, a period of 3 includes the current value and the two previous values. Function Value ------------------------ The Pearson product moment correlation coefficient is typically represented by the letter r. The square of its value has a range from 0 to 1. Value       Meaning ---------------------------------------------     1          Perfect Positive or Negative Correlation     0          No Correlation The relationship at the beginning of a data series is not defined until there are enough values to fill the given period. Note that this function uses the bar number and not the actual number of days. This makes it effective for determining trends over trading days. Since this function measures the linear relationship of a field to time, a value of 1 would indicate that the field has increased (or decreased) by the same amount in each new record. The Pearson product moment correlation coefficient (r) is frequently squared and then refered to as r-squared. The meaning and overall range of the values is the same, but squaring the value clusters less-correlated values closer to zero.