삼원배치법 (혼합모형) (반복없음)

데이터 구조

요인 A모수인자

요인 B모수인자

요인 R변량인자

xijk=μ+ai+bj+rk+(ab)ij+(ar)ik+(br)jk+eijk

  • i : 인자 A수준(i=1,2,,l)
  • j : 인자 B수준(j=1,2,,m)
  • k : 인자 R수준(k=1,2,,r)

분산분석표

요인 제곱합
SS
자유도
DF
평균제곱
MS
E(MS) F0 기각치 순변동
S´
기여율
\rho
A S_{_{A}} \nu_{_{A}}=l-1 V_{_{A}}=S_{_{A}}/\nu_{_{A}} \sigma_{_{E}}^{ \ 2}+m \ \sigma_{_{A \times R}}^{ \ 2}+mr \ \sigma_{_{A}}^{2} V_{_{A}}/V_{_{A \times R}} F_{1-\alpha}(\nu_{_{A}} \ , \ \nu_{_{A \times R}}) S_{_{A}}\acute{} S_{_{A}}\acute{}/S_{_{T}}
B S_{_{B}} \nu_{_{B}}=m-1 V_{_{B}}=S_{_{B}}/\nu_{_{B}} \sigma_{_{E}}^{ \ 2}+l \ \sigma_{_{B \times R}}^{ \ 2}+lr \ \sigma_{_{B}}^{2} V_{_{B}}/V_{_{B \times R}} F_{1-\alpha}(\nu_{_{B}} \ , \ \nu_{_{B \times R}}) S_{_{B}}\acute{} S_{_{B}}\acute{}/S_{_{T}}
R S_{_{R}} \nu_{_{R}}=r-1 V_{_{R}}=S_{_{R}}/\nu_{_{R}} \sigma_{_{E}}^{ \ 2}+lm \ \sigma_{_{R}}^{2} V_{_{R}}/V_{_{E}} F_{1-\alpha}(\nu_{_{R}} \ , \ \nu_{_{E}}) S_{_{R}}\acute{} S_{_{R}}\acute{}/S_{_{T}}
A \times B S_{_{A \times B}} \nu_{_{A \times B}}=(l-1)(m-1) V_{_{A \times B}}=S_{_{A \times B}}/\nu_{_{A \times B}} \sigma_{_{E}}^{ \ 2}+r \ \sigma_{_{A \times B}}^{2} V_{_{A \times B}}/V_{_{E}} F_{1-\alpha}(\nu_{_{A \times B}} \ , \ \nu_{_{E}}) S_{_{A \times B}}\acute{} S_{_{A \times B}}\acute{}/S_{_{T}}
A \times R S_{_{A \times R}} \nu_{_{A \times R}}=(l-1)(r-1) V_{_{A \times R}}=S_{_{A \times R}}/\nu_{_{A \times R}} \sigma_{_{E}}^{ \ 2}+m \ \sigma_{_{A \times R}}^{2} V_{_{A \times R}}/V_{_{E}} F_{1-\alpha}(\nu_{_{A \times R}} \ , \ \nu_{_{E}}) S_{_{A \times R}}\acute{} S_{_{A \times R}}\acute{}/S_{_{T}}
B \times R S_{_{B \times R}} \nu_{_{B \times R}}=(m-1)(r-1) V_{_{B \times R}}=S_{_{B \times R}}/\nu_{_{B \times R}} \sigma_{_{E}}^{ \ 2}+l \ \sigma_{_{B \times R}}^{2} V_{_{B \times R}}/V_{_{E}} F_{1-\alpha}(\nu_{_{B \times R}} \ , \ \nu_{_{E}}) S_{_{B \times R}}\acute{} S_{_{B \times R}}\acute{}/S_{_{T}}
E S_{_{E}} \nu_{_{E}}=(l-1)(m-1)(r-1) V_{_{E}}=S_{_{E}}/\nu_{_{E}} \sigma_{_{E}}^{ \ 2} S_{_{E}}\acute{} S_{_{E}}\acute{}/S_{_{T}}
T S_{_{T}} \nu_{_{T}}=lmr-1 S_{_{T}} 1