수동 계산 : mtcars MPG ~ CYL ANOVA

Question

sumsqwithgrp <- 0 
ybar_j_mean <- tapply(mtcars$mpg, mtcars$cyl, mean) 
mtcars_ordered <- mtcars[order(mtcars$cyl), ] 
count   <- 1 

# Number of levels. 
m <- length(ybar_j_mean) 

for(j in 1:m) { 

    # The corresponding 'cyl'-value of 'ybar_j_mean', 
    # i.e. the value between '*': 
    # > ybar_j_mean 
    #  *4*  6  8 
    # 26.66364 19.74286 15.10000 
    ybar_j_index <- as.numeric(names(ybar_j_mean)[j]) 

    # Relevant subset of observations at 'j' level. 
    mtcars_j  <- mtcars[mtcars$cyl==ybar_j_index, ] 

    # The number of observations of the subset. 
    nj   <- nrow(mtcars_j) 

    sum_j <- 0 
    for(i in 1:nj) { 
     sum_j <- sum_j + (mtcars_j[i, "mpg"] - ybar_j_mean[j])^2 
    } 
    sumsqwithgrp <- sumsqwithgrp + sum_j 
} 

지금

sumsqbtwgrp <- 0 
total_mean <- mean(mtcars$mpg) 
count <- 1 

for(j in 1:m) { 
    ybar_j_index <- as.numeric(names(ybar_j_mean)[j]) 
    mtcars_j  <- mtcars[mtcars$cyl==ybar_j_index, ] 
    nj   <- nrow(mtcars_j) 

    sumsqbtwgrp <- sumsqbtwgrp + nj*(ybar_j_mean[j] - total_mean)^2 
} 

:

> df_1 <- m-1 
> df_1 <- nrow(mtcars)-m 
> (sumsqbtwgrp/df_1)/(sumsqwithgrp/df_2) 
39.69752 

그러나 :

> summary(aov(mpg~cyl, data=mtcars)) 
      Df Sum Sq Mean Sq F value Pr(>F)  
cyl   1 817.7 817.7 79.56 6.11e-10 *** 
Residuals 30 308.3 10.3      
--- 
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

$ 39.7 \ neq 79.6 $.

내가 뭘 잘못하고 있니?

Answer 1

당신은 인자로 CYL을 설정해야합니다

summary(aov(mpg~as.factor(cyl), data=mtcars)) 

더 여기를 참조하십시오 : https://stats.stackexchange.com/questions/112552/how-to-correct-the-degrees-of-freedom