[ANOVA test] Testing the difference in means between groups

Testing the difference in means between groups

(1) Opening the file

  team_score = read.csv('data/TEAM_SCORE.csv')
  team_score

##    TEAM SCORE
## 1     A     0
## 2     A    15
## 3     A     5
## 4     A    10
## 5     A    10
## 6     B     8
## 7     B    12
## 8     B    10
## 9     B    10
## 10    B    20
## 11    C    10
## 12    C    11
## 13    C     9
## 14    C     9
## 15    C    11

  nrow(team_score)

## [1] 15

There are three groups having a numerical variable: TEAM(A,B and C) and SCORE(0~20)

(2) Using aggregate( ), calculating means of each group and drawing their boxplots

  aggregate(SCORE ~ TEAM, data=team_score, mean)

##   TEAM SCORE
## 1    A     8
## 2    B    12
## 3    C    10

  boxplot(SCORE ~ TEAM, data=team_score)

(3) Using aov( ), testing the difference in means between the groups

  result = aov(SCORE ~ TEAM, data=team_score)
  summary(result)

##             Df Sum Sq Mean Sq F value Pr(>F)
## TEAM         2     40    20.0   1.081   0.37
## Residuals   12    222    18.5

As F-value is 0.37 here, the null hypothesis stating that there is no difference in means between the groups is rejected. Therefore, the difference in means among A,B and C teams (at least between two groups) is statistically significant.

Reference

• 패스트 캠퍼스 데이터 분석 입문 올인원 패키지 강의