X1 <- c(3,3,5,4,4,5,7,4,8,2) X2 <- c(2,3,4,5,6,6,7,8,6,9) X3 <- c(4,3,5,4,3,5,7,4,8,4) Y <- c(8,7,8,8,6,7,7,6,5,9)
data <- data.frame(X1, X2, X3, Y)
model <- lm(Y ~ X1 + X2 + X3, data = data)
summary(model)
coef_model <- coef(model) persamaan <- paste0(“Y =”, round(coef_model[1], 3), ” + “, round(coef_model[2], 3),” X1 + “, round(coef_model[3], 3),” X2 + “, round(coef_model[4], 3),” X3”) persamaan
anova(model)
summary(model)
pvals <- summary(model)\(coefficients[,4] names(pvals) <- rownames(summary(model)\)coefficients) pvals
data_std <- as.data.frame(scale(data)) model_std <- lm(Y ~ X1 + X2 + X3, data = data_std) beta_standar <- coef(model_std) # koefisien beta standar beta_standar
R2 <- summary(model)\(r.squared adjR2 <- summary(model)\)adj.r.squared
cat(“R-squared =”, round(R2,3), “→”, round(R2*100,1), “% variasi Y dijelaskan oleh model.”) cat(“Adjusted R-squared =”, round(adjR2,3), “→ proporsi penjelasan setelah penyesuaian jumlah variabel.”)