Regression
Regression
| Screencast | Description |
|---|---|
| Regression in Excel | LINEST and other Excel methods. CLS-Stats alternatives. |
| Regression Residuals | Calculation and interpretation of regression residuals |
| Regression and ANOVA | Variability partitioning in regression. Relationship between ANOVA and regression. |
| SOLVER basics 1 | Introduction to SOLVER. Finding local and global minima. SOLVER settings. |
| SOLVER basics 2 | Maximization. Finding roots. Troubleshooting SOLVER. |
| Regression with SOLVER | OLS fitting criterion. Using SOLVER to do regression analysis. |
| Properties of least-squares estimators | Inferential statistics with OLS parameter estimates |
| Linear vs nonlinear regression models | Distinction between linear and nonlinear regression models. Multiple linear regression in Excel. |
| Propagation of correlated error | Propagation of correlated random error using regression parameter estimates |
| Nonlinear regression | Use NLS lambda to perform nonlinear OLS regression |
| Polynomial regression and model selection | Polynomial regression with LINEST and PolyLS. Model selection. |
| Regression uncertainty bands | Creating confidence bands and prediction bands |
| Inverse regression 1 | Introduction to inverse regression (the "calibration problem") |
| Inverse regression 2 | Inverse polynomial regression. Exact vs approximate solutions, and edge cases. |
| Variable transformations | Mathematical transformation of X and/or Y variables. The power ladder. |
| Weighted least-squares regression | Introduction to weighted least-squares regression |
| Calibration with weighted LS regression | Calibration and inverse regression with weighted LS |