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Sagot :
Let's complete the ANOVA table step-by-step:
1. Sum of Squares for Factor (SS_B): Given as 55.
2. Degrees of Freedom for Factor (df_B): Given as 5.
3. Sum of Squares for Error (SS_W): Given as 39.
4. Degrees of Freedom for Error (df_W): Given as 14.
Next, we need to calculate the Mean Square for the Factor (MS_B) and Mean Square for the Error (MS_W), and then the F-value.
Mean Square for Factor (MS_B):
[tex]\[ MS_B = \frac{SS_B}{df_B} = \frac{55}{5} = 11.0 \][/tex]
Mean Square for Error (MS_W):
[tex]\[ MS_W = \frac{SS_W}{df_W} = \frac{39}{14} \approx 2.79 \][/tex]
F-value:
[tex]\[ F = \frac{MS_B}{MS_W} = \frac{11.0}{2.79} \approx 3.95 \][/tex]
So, to complete the ANOVA table:
a. [tex]\( MS_B = 11.00 \)[/tex]
b. [tex]\( MS_W = 2.79 \)[/tex]
c. [tex]\( F = 3.95 \)[/tex]
Here's the completed ANOVA table:
[tex]\[ \begin{array}{|r|c|r|r|r|} \hline \text{Source} & \text{SS} & \text{d.f.} & \text{MS} & \text{F} \\ \hline \text{Factor} & 55 & 5 & 11.00 & 3.95 \\ \hline \text{Error} & 39 & 14 & 2.79 & \\ \hline \end{array} \][/tex]
1. Sum of Squares for Factor (SS_B): Given as 55.
2. Degrees of Freedom for Factor (df_B): Given as 5.
3. Sum of Squares for Error (SS_W): Given as 39.
4. Degrees of Freedom for Error (df_W): Given as 14.
Next, we need to calculate the Mean Square for the Factor (MS_B) and Mean Square for the Error (MS_W), and then the F-value.
Mean Square for Factor (MS_B):
[tex]\[ MS_B = \frac{SS_B}{df_B} = \frac{55}{5} = 11.0 \][/tex]
Mean Square for Error (MS_W):
[tex]\[ MS_W = \frac{SS_W}{df_W} = \frac{39}{14} \approx 2.79 \][/tex]
F-value:
[tex]\[ F = \frac{MS_B}{MS_W} = \frac{11.0}{2.79} \approx 3.95 \][/tex]
So, to complete the ANOVA table:
a. [tex]\( MS_B = 11.00 \)[/tex]
b. [tex]\( MS_W = 2.79 \)[/tex]
c. [tex]\( F = 3.95 \)[/tex]
Here's the completed ANOVA table:
[tex]\[ \begin{array}{|r|c|r|r|r|} \hline \text{Source} & \text{SS} & \text{d.f.} & \text{MS} & \text{F} \\ \hline \text{Factor} & 55 & 5 & 11.00 & 3.95 \\ \hline \text{Error} & 39 & 14 & 2.79 & \\ \hline \end{array} \][/tex]
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