Leisure Publishers Ltd. recently published 20 romantic novels by 20 different authors.
Sales ranged from just over 5,000 copies for one novel to about 24,000 copies for
another novel. Before publishing, each novel had been assessed by a reader who had
given it a rating between 1 and 10. The managing director suspects that the main
influence on sales is the cover of the book. The illustrations on the front covers were
drawn either by artist A or artist B. The short description on the back cover of the
novel was written by either editor C or editor D.
A multiple regression analysis was done using the following variables:
Y sales (millions of shillings).
1 if front cover is by artist A.
2 if front cover is by artist B.
1 if the short description of the novel is by editor C.
2 if the short description of the novel is by editor D.
The computer analysis produced the following results:
Correlation coefficient r = 0.921265
Standard error of estimate = 2.04485
Analysis of variance
Regression 3 375.37 125.12 29.923
Residue 16 66.903 1.1814
Individual analysis of variables:
Variable Coefficient Standard error F Value
Constant 15.7588 2.54389 38.375
1 -6.25485 0.961897 42.284
2 0.0851136 0.298272 0.081428
3 5.86599 0.922233 40.457741
1 – 0.307729 0 – 0.674104
1 0.123094 0.310838
(a) The regression equation. (3 marks)
(b) Does the regression analysis provide useful information? Explain. (3
(c) Explain whether the covers were more important for sales than known quality
of the novels. (4
(d) State with 95% confidence the difference in sales of a novel if its cover
illustrations were done by artist B instead of artist A.
(e) State with 95% confidence the difference in sales of a novel if its short
description was by editor D and not editor C.