two factor ANOVA indep measures exper. 2 level factor A 3 level factor B n=5 in each treatment

SS df ms
between 240 5
factor A ? 1 ? Fa=24
factor B ? 2 ?
AxB 60 2 30
within ? 24 5
are this answers right for SS
A=120
B=80
w/I=120

Your table might look like this using your data:

Source....SS....df....MS.....F
A....... 120 ... 1 .. 120... 24
B....... 80 .... 2 .. 40 ... 8
AxB.... 60 .... 2 ... 30... 6
Within.. ? ..... 19 ... 5
Total... ? ..... 24

I'm not sure what your SS(Total) or SS(Within) is supposed to be, and those values could change your value for SS(B). If your value for SS(B) is actually 80, then MS(B) would be 40 and F(B) would be 8. The other values should be okay.

To determine the correct values for the missing sum of squares (SS) and mean squares (MS) in the two-factor independent measures ANOVA with a 2-level factor A and a 3-level factor B, we can follow the steps below:

1. Start with the total sum of squares (SST). Since there are n = 5 in each treatment, SST can be calculated by multiplying the number of treatments (levels) by the number of observations per treatment and squaring that value.

SST = (2 * 5) * (3 * 5)^2
= 10 * 225
= 2250

2. Calculate the between-group sum of squares (SSbetween), which represents the variability between the different treatment groups. This can be obtained by subtracting the within-group sum of squares (SSwithin) from the total sum of squares (SST).

SSbetween = SST - SSwithin

3. Since both factors A and B have only one degree of freedom (df) each, we can allocate half of the total between-group sum of squares (SSbetween) to each factor.

SSbetween for factor A = SSbetween / df(factor A)
= 240 / 1
= 240

SSbetween for factor B = SSbetween / df(factor B)
= 240 / 1
= 240

4. Calculate the interaction sum of squares (SSinteraction). The value for SSinteraction is given as 60.

5. Once we have the separate contributions of factor A, factor B, and their interaction, we can calculate the within-group sum of squares (SSwithin) by subtracting these sums of squares from the total sum of squares (SST).

SSwithin = SST - (SSbetween for factor A) - (SSbetween for factor B) - SSinteraction
= 2250 - 240 - 240 - 60
= 1710

6. Finally, distribute the remaining within-group sum of squares (SSwithin) across the degrees of freedom for the within-group factor.

SSwithin for within-factor = SSwithin / df(within)
= 1710 / 24
= 71.25

Now, let's summarize the results for the missing values:

- SS for factor A = 240
- SS for factor B = 240
- SS for within-factor = 1710

Please note that these calculations are based on the information provided and assumptions made about the experimental design.