In Weights, enter a numeric column of weights to perform weighted regression. Weighted regression is a method that can be used when the least squares assumption of constant variance in the residuals is violated (also called heteroscedasticity). With the correct weight, this procedure minimizes the sum of weighted squared residuals to produce residuals with a constant variance (also called homoscedasticity). For more information about determining the appropriate weight, go to Weighted regression.
The weights must be greater than or equal to zero. The weights column must have the same number of rows as the response column.
Enter the level of confidence for the confidence intervals for the coefficients and the fitted values.
Usually, a confidence level of 95% works well. A 95% confidence level indicates that, if you took 100 random samples from the population, the confidence intervals for approximately 95 of the samples would contain the mean response. For a given set of data, a lower confidence level produces a narrower interval, and a higher confidence level produces a wider interval.
To display the confidence intervals, you must go to the Results sub-dialog box, and from Display of results, select Expanded tables.
You can select a two-sided interval or a one-sided bound. For the same confidence level, a bound is closer to the point estimate than the interval. The upper bound does not provide a likely lower value. The lower bound does not provide a likely upper value.