# Heating cost data gas <- c(6.1, 7.2, 5.4, 5.8, 6.3, 6.7, 7.4, 6.4) electricity <- c(8.2, 7.5, 8.7, 7.4, 7.8, 9.2) solar <- c(5.2, 6.1, 5.7, 5.4, 6.2) # Combine the data into a single data frame heating_data <- data.frame(Heating = c(rep("Gas", length(gas)), rep("Electricity", length(electricity)), rep("Solar", length(solar))), Cost = c(gas, electricity, solar)) # Perform one-way ANOVA result <- aov(Cost ~ Heating, data = heating_data) # Print the ANOVA table summary(result) # Check the p-value p_value <- summary(result)[[1]]$`Pr(>F)`[1] # Compare p-value with the significance level (e.g., 0.05) if (p_value < 0.05) { conclusion <- "There is a significant difference in heating costs among the three heating systems." } else { conclusion <- "There is no significant difference in heating costs among the three heating systems." } # Print the conclusion cat("Conclusion:", conclusion) change this code to alpa 0.1