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ckcode ⌲ chapter-x3-modeling-relationships

require(coursekata) # find best-fitting model Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) # add code to visualize the new model on the jitter plot gf_jitter(PriceK ~ Neighborhood, data = Ames, width = .1) # find best-fitting model Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) # add code to visualize the new model on the jitter plot gf_jitter(PriceK ~ Neighborhood, data = Ames, width = .1) %>% gf_model(Neighborhood_model) ex() %>% { check_function(., "gf_model") %>% check_arg("object") %>% check_equal() check_or(., check_function(., "gf_model") %>% check_arg("model") %>% check_equal(), override_solution(., "gf_jitter(PriceK ~ Neighborhood, data = Ames) %>% gf_model(PriceK ~ Neighborhood)") %>% check_function(., "gf_model") %>% check_arg("model") %>% check_equal() ) }
CK Code: X3_Code_RtoFit_01
require(coursekata) # we have saved the Neighborhood model for you Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) # write code to generate predictions using this model # no need to save the predictions # we have saved the Neighborhood model for you Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) # write code to generate predictions using this model # no need to save the predictions predict(Neighborhood_model) ex() %>% check_function("predict") %>% check_result() %>% check_equal()
CK Code: X3_Code_RtoFit_02
require(coursekata) # we have saved the Neighborhood model for you Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) # print out the best-fitting parameter estimates # we have saved the Neighborhood model for you Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) # print out the best-fitting parameter estimates Neighborhood_model ex() %>% check_output_expr("Neighborhood_model")
CK Code: X3_Code_RtoFit_03
require(coursekata) # This codes saves the best-fitting models empty_model <- lm(PriceK ~ NULL, data=Ames) Neighborhood_model <- lm(PriceK ~ Neighborhood, data=Ames) # This code squares and sums the residuals from the empty model sum(resid(empty_model)^2) # Write code to square and sum the residuals from the Neighborhood model # This codes saves the best-fitting models empty_model <- lm(PriceK ~ NULL, data=Ames) Neighborhood_model <- lm(PriceK ~ Neighborhood, data=Ames) # This code squares and sums the residuals from the empty model sum(resid(empty_model)^2) # Write code to square and sum the residuals from the Neighborhood model sum(resid(Neighborhood_model)^2) ex() %>% { check_function(., "sum", 1) %>% check_result() %>% check_equal() check_function(., "sum", 2) %>% check_result() %>% check_equal() }
CK Code: X3_Code_ErrorR_01
library(coursekata) # edit the Neighborhood_model code to create HomeSizeK_model Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) # save the predictions of the HomeSizeK_model as a new variable in Ames Ames$HomeSizeK_predict <- # this code prints out the first 6 observations head(select(Ames, PriceK, HomeSizeK, HomeSizeK_predict)) # edit the Neighborhood_model code to create HomeSizeK_model HomeSizeK_model <- lm(PriceK ~ HomeSizeK, data = Ames) # save the predictions of the HomeSizeK_model as a new variable in Ames Ames$HomeSizeK_predict <- predict(HomeSizeK_model) # this code prints out the first 6 observations head(select(Ames, PriceK, HomeSizeK, HomeSizeK_predict)) ex() %>% { check_object(., "HomeSizeK_model") %>% check_equal() check_object(., "Ames") %>% check_column("HomeSizeK_predict") %>% check_equal() }
CK Code: X3_Code_Quantitative_01
library(coursekata) # saves the home size model HomeSizeK_model <- lm(PriceK ~ HomeSizeK, data = Ames) # print it out # saves the home size model HomeSizeK_model <- lm(PriceK ~ HomeSizeK, data = Ames) # print it out HomeSizeK_model ex() %>% check_output_expr("HomeSizeK_model")
CK Code: X3_Code_Interpreting_01
require(coursekata) # this calculates SST empty_model <- lm(PriceK ~ NULL, data=Ames) print("SST") sum(resid(empty_model)^2) # this calculates SSE HomeSizeK_model <- lm(PriceK ~ HomeSizeK, data = Ames) print("SSE") sum(resid(HomeSizeK_model)^2) # no test ex() %>% check_error()
CK Code: X3_Code_ErrorH_01
library(coursekata) empty_model <- lm(PriceK ~ NULL, data = Ames) Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) # modify this line of code supernova(empty_model) empty_model <- lm(PriceK ~ NULL, data = Ames) Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) # modify this line of code supernova(Neighborhood_model) ex() %>% check_function("supernova") %>% check_result() %>% check_equal()
CK Code: X3_Code_ANOVA_01
require(coursekata) empty_model <- lm(PriceK ~ NULL, data=Ames) Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) # This generates predictions from empty model Ames$empty_predict <- predict(empty_model) # This generates predictions from Neighborhood model Ames$Neighborhood_predict <- predict(Neighborhood_model) # Here are the differences # Square and sum these differences to calculate SSM (Ames$empty_predict - Ames$Neighborhood_predict) # This generates predictions from empty model Ames$empty_predict <- predict(empty_model) # This generates predictions from Neighborhood model Ames$Neighborhood_predict <- predict(Neighborhood_model) # Here are the differences # Square and sum these differences to calculate SSM sum((Ames$empty_predict - Ames$Neighborhood_predict)^2) ex() %>% check_function('sum') %>% check_result() %>% check_equal()
CK Code: X3_Code_Conceptualizing_01
require(coursekata) # Produces ANOVA table for Neighborhood model Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) supernova(Neighborhood_model) # Write additional code to produce ANOVA table for HomeSizeK model HomeSizeK_model <- lm(PriceK ~ HomeSizeK, data = Ames) # Produces ANOVA table for Neighborhood model Neighborhood_model <- lm(PriceK ~ Neighborhood, data = Ames) supernova(Neighborhood_model) # Write additional code to produce ANOVA table for HomeSizeK model HomeSizeK_model <- lm(PriceK ~ HomeSizeK, data = Ames) supernova(HomeSizeK_model) ex() %>% check_function("supernova", 2) %>% check_result() %>% check_equal()
CK Code: X3_Code_Conceptualizing_02

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