'Studentized residuals' presentation slideshows

Statistical Models in S

Statistical Models in S. The template is a multiple linear regression model: In matrix terms this would be written where y is the response vector, ? is the vector of regression coefficients, X is the model matrix or design matrix and e is the error vector. Model formulae.

1.55k views • 115 slides

The Agenda

731 views • 73 slides

BMTRY 701 Biostatistical Methods II

564 views • 40 slides

The Search for Synergism

The Search for Synergism. A Data Analytic Approach L. Wouters, J. Van Dun, L. Bijnens May 2003 Three Country Corner Royal Statistical Society. Overview. Combined action of drugs Screening for synergism Experimental Design Fitting concentration response curves, estimation of IC 50

887 views • 36 slides

Review of Univariate Linear Regression

Review of Univariate Linear Regression. BMTRY 726 3/4/14. Regression Analysis. We are interested in predicting values of one or more responses from a set of predictors Regression analysis is an extension of what we discussed with ANOVA and MANOVA

561 views • 32 slides

Multiple Regression 2

405 views • 32 slides

BMTRY 701 Biostatistical Methods II

408 views • 32 slides

Testing Assumptions of Linear Regression

Testing Assumptions of Linear Regression. Detecting Outliers Transforming Variables Logic for testing assumptions. Assumptions of regression.

1.11k views • 30 slides

Regression Model Building

Regression Model Building. Setting: Possibly a large set of predictor variables (including interactions). Goal: Fit a parsimonious model that explains variation in Y with a small set of predictors Automated Procedures and all possible regressions: Backward Elimination (Top down approach)

198 views • 15 slides

1. Independence of error assumption. In many business applications using

1. Independence of error assumption. In many business applications using regression, the independent variable is TIME. When the data (Y i ) is collected at regular intervals of time you have a time series. In such cases the errors are likely

201 views • 6 slides