1 0.94999999999999996 0.01 0.10 False 6 Regression 0 0 dialog False vertical 12 False end _OK True True True True True True False True 0 _Cancel True True True True True False True 1 _Help True True True True False True 2 True False True end 0 True False 0 none True False 12 12 6 6 6 12 True False Independent variable(s) (X) range: True variable1-range-edit 0 0 0 True True center True True 30 True Enter a single range that contains multiple independent variable observations (along columns or rows) 1 0 True True True 2 0 True False Dependent variable (Y) range: True variable2-range-edit 0 0 1 True True center True True 30 True The range that contains the dependent variable. 1 1 True True True 2 1 Both X and Y ranges have labels True True False start True 0 2 3 True False Results to: True output-range-edit 0 0 3 True True center True True 30 True The reference of the top left cell of the range where the results will be displayed. 1 3 True True True 2 3 True False Data False True 0 True False 0 none True False 12 12 6 6 6 12 Columns True True False True True True 0 0 Rows True True False True True groupedby-columns-radio 1 0 True False Grouped by False True 1 True False 0 none True False 12 12 6 6 6 12 Linear Regression True True False start center True True True Find a straight line in the form of y = a.x + b, where a is the slope and b is the intercept that best fits the data. 0 0 Logarithmic Regression True True False start center True True linear-radio Find a logarithmic curve in the form of y = a.ln(x) + b, where a is the slope, b is the intercept and ln(x) is the natural logarithm of x, that best fits the data. 0 1 Power Regression True True False start center True True linear-radio Find a power curve in the form of y = a.x^b, where a is the coefficient, b is the power that best fits the data. 0 2 True False Output Regression Types False True 2 True False 0 none True False 12 6 12 True False start center Confidence level confidencelevel-spin 0 0 Calculate residuals True True False True True The residuals give information on how far the actual data points deviate from the predicted data points, based on the regression model. 0 1 True True start center True 0.95 True confidencelevel-adjustment 2 True 0.94999999999999996 A value indicating a confidence level for the calculated prediction interval. 1 0 Force intercept to be zero True True False True Forces the regression curve to cross the origin. 1 1 True False Options False True 3 True False True True True 4 ok cancel help Produces the regression analysis of a data set