regression - How to perform a 70/30 holdout in R -
i'm trying make prediction based on below linear regression model:
i want predict intercept (market share) based on formula given value each of response variables. formula these results , can plug numbers in each variable?
or need holdout/training sets first?
edit: added text of results.
summary(fit2) call: lm(formula = headache_panel_cleaned$private_label_cleaned ~ income_cleaned + age_cleaned + education_cleaned, data = headache_panel_cleaned) residuals: min 1q median 3q max -53.880 -33.804 -5.473 32.589 68.171 coefficients: estimate std. error t value pr(>|t|) (intercept) 52.02867 0.96849 53.721 <2e-16 *** income_cleaned -0.22711 0.01199 -18.949 <2e-16 *** age_cleaned -0.11363 0.01334 -8.516 <2e-16 *** education_cleaned 0.13104 0.01213 10.807 <2e-16 *** --- signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 residual standard error: 35.09 on 38115 degrees of freedom (8224 observations deleted due missingness) multiple r-squared: 0.0102, adjusted r-squared: 0.01012 f-statistic: 131 on 3 , 38115 df, p-value: < 2.2e-16
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