List of CalculatorsControl Limit For C Chart Control Limits for IMR Chart Control Limits for NP Chart Control Limits for P Chart Control Limit For U Chart Control Limits for Xbar-R chart Control Limits for Xbar-S chart Cost of Poor Quality Guide to Master Black Belt Competency Guide to select the right Hypothesis Test Little’s Law Net Present Value Overall Equipment Efficiency (OEE) Process capability calculator Process Cycle Efficiency R Square Adjusted Sample size calculator for mann whitney test Sample Size Calculator for 1 Proportion Test Sample Size Calculator For 2 Proportion Test Sample Size Calculator For 1 Proportion Test (Finite Population) Sample Size Calculator For 2 Proportion Test (Finite Population) Sample Size calculator For 1 Sample T Test Sample Size Calculator For 2 Sample T Test Sample Size Calculator For 1 Sample T Test (Finite Population) Sample Size Calculator For 2 Sample T Test (Finite Population) Sample Size Estimation (Mean) Sample Size Estimation(Proportion Data) Sigma Level Calculator (Continuous Data) Sigma Level Calculator (Discrete Data – Defects) Sigma Level Calculator (Discrete Data – Defectives) Takt Time R Square Adjusted Calculator Use this calculator to compute the R square adjusted (adjusted coefficient of determination) value for your regression equation R squareEnter the observed R square (coefficient of determination) as obtained after running regression. E.g. if R square is 90.54%, enter 90.54 (i.e. without the % sign)Sample SizeEnter the number of observations in the sample or the sample sizeNumber of independent predictorsEnter the number of independent predictors in the modelNumber1 R square adjusted cannot be calculatedFor the given sample size and number of predictors, R Square Adjusted cannot be calculated. Kindly check and enter correct numbersR square adjustedCalculated R Square Adjusted (adjusted coefficient of determination). A negative value indicates that the predictors to sample size ratio is high (i.e. a lower sample size was considered) or it can also indicate the presence of correlated predictors. Δ