1- Describe the similarities and differences between an F-ratio and a t statistic.

2- Explain why you should use ANOVA instead of several t tests to evaluate mean differences (i.e. differences between treatment groups) when an experiment consists of three or more treatment conditions.

3- A developmental psychologist is examining the development of language skills from age 2 to age 4. Three different groups of children are obtained, one for each age, with n = 15 children in each group. Each child is given a language-skills assessment test. The data from this experiment were analyzed with an ANOVA, and the results are summarized in the following table. Fill in all of the missing values. (Hint: start with the df column using the formula sheet partIV.) Source SS df MS or s2 F Between treatments. 30 Within treatments Total 225

IV. Determine critical regions (i.e. critical F ratio value between high & low probability) using table B.4 (pp. A-29ff) A. Significance level (should be given or decided prior to experiment) 1. or p levels a. = .05, use lightface type for critical F value b. = .01, use boldface type for critical F value B. Degrees of freedom 1. Numerator (between groups) a. dfBet = k (# of groups) - 1 2. Denominator (within groups, dfW) a. dfWith = (n1 + n2 + ... + nk) - k (# of groups) C. With degrees of freedom and level, find the critical F ratio value