STAT331 Study Guide - Final Guide: Identity Function, Time Series, Linear Combination
22 Apr 2018
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Peter balka winter 2018 university of waterloo. 5. 1 least squares estimation of in mlr . 10. 1 interpretation of parameters for categorical 1, 1 variates. 10. 3 analysis of variance (anova) and additional sum of squares . 10. 5 testing if any variates are related to response . 11. 3 f-test special case: testing signi cance of all parameters of a model . 11. 4 f-test special case: testing signi cance of one additional parameter . 12. 1 di erence in response from reduced model . 13. 2 methods to address violated model assumptions . 14. 1 fitted residuals e vs errors . 15. 1 additional variation required for more precise parameter estimates in anova . 17. 1 leaps in r for model selection . 17. 3 forecasting time series data using linear regression models . 18. 1 fitting linear regression to account for seasonality in time series . 18. 2 (sample) acf rk vs process auto-correlation k . 20. 1 faculty salary study: regression model example .
