A researcher wants to know if the way people choose to spend their free time affects their mood. She recruits three groups of participants and asks each group to do a different activity for one hour each day: go for a walk (Walk), watch TV (Television), or read a book (Book). She has each participant take a short mood survey after the hour is up. The survey (mood) is scored on a scale from 0 to 10 (0 = bad mood, 10 = great mood). Assuming the data is normally distributed and using an a-level = .05, she analyzed her data in R. Part of her output is below: > tapply(freetimeSmood, freetimesactivity, mean) Book Television 6.08 6.07 walk 8.00 > tapply(freetimesmood, freetimesactivity, sd) Book Television walk 1. 548411 1.342807 1.310409 > aov (mood-activity,data-freetime) call: aov (formula - mood ~ activity, data - freetime) Terms: activity Residuals sum of squares 247.0467 585.8700 Deg. of Freedom 2 297 Residual standard error: 1.404502 Estimated effects may be unbalanced * al <-aov (mood~-activity,data-freetime) * anova(al) Analysis of variance Table Response: mood of Sum sq Mean Sq F value PrOF) activity 2 247.05 123.523 62.619 < 2. 2e-16 *** Residuals 297 585.87 1.973 signif. codes: 0 *a..* 0.001 ***' 0.01 *** 0.05 *. 0.1 * * 1