1. Verkennen van data
1.1 Descriptives
Pagina 6 Statistic Std. Error
Variabele Mean A N
95% Confidence Lower Bound B
Interval for Mean Upper Bound C
5% Trimmed Mean D
Median E
Variance F
Std. Deviation G
Minimum H
Maximum I
Range J
Interquartile Range K
Skewness L O
Kurtosis M P
𝐺
Std. Error (N) =
√𝑛−1
2. Regressie
2.1 Model Summary
Pagina 50 Adjusted Std. Error of
Model R R Square R Square the Estimate
1 A B C D
𝐸 𝐹
R² (B) = = 1 – (→ Zie 2.2 Anova)
𝐺 𝐺
𝐿
R²adj (C) = 1 – (→ Zie 2.2 Anova)
𝑀𝑆𝑇
Std. Error of the Estimate (D) = √𝑀𝑆𝐸 (𝐿) (→ Zie 2.2 Anova)
2.2 Anova
Pagina 50 Sum of
Model Squares df Mean Square F Sig.
1 Regression E H K M N
Residual F I L
Total G J
𝐸 𝐹 𝐺
E = SSM F = SSE G = SST K = MSM = L = MSE = MST =
𝐻 𝐼 𝐽
H = p I = n–p–1 J = n–1
𝐸 𝐹
K = L =
𝐻 𝐼
𝐾
M (F-waarde) =
𝐿
1.1 Descriptives
Pagina 6 Statistic Std. Error
Variabele Mean A N
95% Confidence Lower Bound B
Interval for Mean Upper Bound C
5% Trimmed Mean D
Median E
Variance F
Std. Deviation G
Minimum H
Maximum I
Range J
Interquartile Range K
Skewness L O
Kurtosis M P
𝐺
Std. Error (N) =
√𝑛−1
2. Regressie
2.1 Model Summary
Pagina 50 Adjusted Std. Error of
Model R R Square R Square the Estimate
1 A B C D
𝐸 𝐹
R² (B) = = 1 – (→ Zie 2.2 Anova)
𝐺 𝐺
𝐿
R²adj (C) = 1 – (→ Zie 2.2 Anova)
𝑀𝑆𝑇
Std. Error of the Estimate (D) = √𝑀𝑆𝐸 (𝐿) (→ Zie 2.2 Anova)
2.2 Anova
Pagina 50 Sum of
Model Squares df Mean Square F Sig.
1 Regression E H K M N
Residual F I L
Total G J
𝐸 𝐹 𝐺
E = SSM F = SSE G = SST K = MSM = L = MSE = MST =
𝐻 𝐼 𝐽
H = p I = n–p–1 J = n–1
𝐸 𝐹
K = L =
𝐻 𝐼
𝐾
M (F-waarde) =
𝐿
