A farm animal feed company is developing a new line of pig feed. It has created four different formulations and is interested in knowing which pig feed is most efficient at fattening them up. 12 pigs from 3 different litters (A,B and C) were selected, 3 pigs from each litter were exclusively fed one type of feed (1, 2, 3 or 4). After 2 years each pig was weighed. Litters were used as blocking effect to control for the possiblility of genetics playing a role in size. The total standard deviation of dataset was 1.64. Interactions were found to be not significant. A summary of the cell and column means is given below.

Feed	1	2	3	4
Litter A	109.64	112.75	?	108.87
Litter B	108.72	112.51	?	108.41
Litter C	109.87	112.55	110.79	109.17
Column Mean	109.41	112.61	110.40	108.82

Note that two of the cell means are not given on purpose, however the following partial ANOVA table is supplied.

Source	DF	SS	MS	F
Feed Type
Litter			1.355
Error
Total

Calculate the total degrees of freedom

Calculate the error degrees of freedom

Calculate the degrees of freedom for the blocking factor

Calculate the degrees of freedom for the feed type

Calculate the Sum of Squares for the Feed Type

Calculate the Sum of Squares for the litter

Calculate the Sum of Squares of the Error

Calculate the total Sum of Squares

Calculate the Mean Square for the Feed Type

Calculate the MSE

Calculate the F statistic for Feed Type

Is there a significant feed effect at = 0.01?

Yes there is a significant effect No there is not a significant effect

Calculate the F statistic for litter

Is there a significant litter effect at = 0.01?

Yes there is a significant effect No there is not a significant effect The feed company is interested in knowing which of the feed types is effective. How many pairwise comparisons must be made?

If = 0.01, what is the value of ^*?

What is the denominator of the pairwise test statistics for the feed type?

What is the test statistic for feed type 1 vs. 4?

What is the test statistic for feed type 2 vs. 3?