1. Solutions for Tutorial 1
(a) qualitative (categories,e.g., mountain, land, sea etc)
(b), ( c), and (d) quantitative.
(a) company assets (response,quantitative), return on a stock (predictor, quantitative), and net sales (predictor,quantitative). The former variable will increase with increasing the latter two.
(b) the distance of a race (response, [or predictor], quantitative), the time to run the race (predictor, [or response], quantitative), and the weather conditions at the time of running (predictor,qualitative). The distance will generally increase with increasing the running time, and the weather conditions will affect the distance of a race and the time to run.
(c) the height and weight of a child (responses, quantitative), his/her parents’ height and weight (predictors, quantitative), and the sex and age of the child (predictors, qualitative(sex)/quantitative(age)). The predictors can affect the values of the responses.
(a) see above.
(b) a) Multiple regression b) Multiple regression c) Multivariate regression.

2. 4. (a). Var(X)=114/(14-1)=8.769 Var(Y)=27768.36/(14-1)=2136
(b) from Table 2.6.
(a) wouldn’t agree since Cor(X,Y) takes values within [-1,1].
(b). wouldn’t agree since this means no Linear relationship or Linearly uncorrelated
but X and Y could has some nonlinear relationship.
Note that t(12,.05)=1.78, t(12,.1)=1.36.
(a) T=( )/3.355=1.24<1.78, can not reject H0 at 10%-significant level
(b) T=( )/3.355=-.25, |T|<1.78, can not reject H0 at 10%-significant level.
(c) T=( )/.505=1.0079<1.78, can not reject H0 at 10%-significant level.
(d) T=1.0079<1.36, can not reject H0 at 10%-significant level.