1. A manufacturer of infant formula is running an experiment using the standard (control) formula, and two new formulas, A and B. The goal is to boost the immune system in infants. 120 infants in the study are randomly assigned to each of three groups: group A, group B, and a control group. There are 40 infants in each group and the study is run for 12 weeks. At the end of the study the variable measured is total IGA (in mg per dl), with higher values being more desirable. We are going to run a one-way ANOVA on this data. A partial ANOVA table is given below.

The P-value for testing

H₀: the mean IGA score is the same for all three formulas

H_a: the mean IGA score is not the same for all three formulas is

A. less than 0.001.
B. between 0.001 and 0.025.
C. greater than 0.10.

2. A manufacturer of infant formula is running an experiment using the standard (control) formula, and two new formulas, A and B. The goal is to boost the immune system in infants. 120 infants in the study are randomly assigned to each of three groups: group A, group B, and a control group. There are 40 infants per group and the study is run for 12 weeks. At the end of the study the variable measured is total IGA (in mg per dl), with higher values being more desirable. We are going to run a one-way ANOVA on these data. The ANOVA table is given below,as well as a table of means and standard deviations for the three groups.

Variable N Mean StDev
Control 40 0.1278 0.04392
Formula A 40 0.1436 0.05601
Formula B 40 0.1623 0.04985

Before collecting the data, one of the primary questions was formulated as a null hypothesis H0: with the alternative Ha: , where μA and μB are the means of formulas A and B, respectively, and μC is the control mean. The t statistic for testing contrast is

A. t = 1.41.
B. t = 2.60.
C. t = 3.07.