Transcript Document 7888405

Problems of Tutorial 1
1. Classify each of the following variables as quantitative or qualitative. For the latter case,
state the possible categories.
(a) Geographical region (b) Price of a house
( c) Temperature
(d) Employment rate
2. In each of the following sets of variables, identify the response variable and the
predictor variables. Explain why.
(a) Company assets, return on a stock, and net sales.
(b) The distance of a race, the time to run the race, and the weather conditions at the
time of running.
(c) The height and weight of a child, his/her parents’ height and weight, and the sex and
age of the child.
3. For each of the sets of variables in Problem 2,
(a) Classify each variable as either quantitative or qualitative.
(b) Which type of regression can be used in the analysis of the data
.
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ST3131, Tutorial 1
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4. Using the data in Table 2.6 (p. 28, or download the computer repair data from
the class website),
(a). Compute Var(X), and Var(Y).
n
(b). Prove or verify that
(y
i 1
i
 y)  0
Explain why you would or wouldn’t agree with each of the following
statements
5.
(a) Cov(X,Y) and Cor(X,Y) can take values between -
 and 
(b) If Cov(X,Y)=0 or Cor(X,Y)=0, one can conclude that there is no
relationship between X and Y.
6 Using the regression output in Table 2.9 (p. 36), test the following hypotheses
using  =0.1:
(a)
H0 : 0  0
(b) H 0 :  0  5
(c)
(d)
H 0 : 1  15
H1 :  0  0
versus H1 :  0  5
versus
versus H1 : 1  15
H 0 : 1  15 versus
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H1 : 1  15
ST3131, Tutorial 1
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