[1] The purpose of this reserch is to make clear what type of design can give good effects to win the high readership score. At the begining I had to know what factors decide the readership score, and how to change the quality of the desing into numerical value. I have used the method of multi-dimentional analysis with the help of a computer, and got the estimation formula, with 7 kinds of factors, as follows ; A^^〜=
B
+C+D+K+aE+
bF
+cG. A^^〜=estimated values of the readership score. 1)
B
, C, D, K : these four factors are given as category values (so we call them); each factor is classified into several categories.
B
=week day, classified into 7 categories. C=pages of a newspaper, which are characterized by the kinds of articles, news, and the other reading matters, classified into
22
categories. D=kinds of goods and trades of the advertizement, classified into 14 catedories. K=constants, given to each 13 surveys.
2
)
E
, F, G : these factors are given as numerical values. G=area of advertizement, measured by the unit of column in the whole page length, being classified into
6
kinds of area (
2
.
5
,
3
.
5
,
5
, 7, 10, 15) and 15 column means a whole page, about
2
,000cm^
2
.
E
, F are the marks obtained in the design of advertizements.
E
=sum of the marks obtained in each design element on the advertizement. F=the marks obtained on the whole effect of the design.
3
) a,
b
, c : coefficients Using the above formula with the category values and the coefficients, we can obtain the naked design effect from the actual value A of readership score: aE+
bF
=A-(
B
+C+D+K+cG). In this research, I used 1,829 data of readership score from 1960 to 1968, being obtained by 13 survevs, spring and autumn twice a year. The sample of size each survey was
3
,541,
2
,251, or 200 in the other 11 surveys. Multiple correlation coefficient between the estimated value A^^〜 and the actual value A is
0
.951. The table
2
^* shows the contribution indexes of each factor by
3
kinds of expression-(1) Range : the absolute difference between the maximum and the minimum category values, (
2
) Standard deviations of the category values, (
3
) Partial correlation coefficient : the relationship between the actual values A and each factors. *see the table
2
in the thesis in Japanese. [
2
] The important point was in the determination of the values of
E
, F.
E
is the sum of the marks obtained in each design element, classified into four kinds :
E
=
E
_1+
E
_
2
+
E
_
3
+
E
_
4
. design elements [table]
E
_1,
E
_
2
,
E
_
3
,
E
_
4
, these values have the
5
grades, as
0
, 1,
2
,
3
,
4
and
0
is given to the design that has no attractive effect or no applicable element. And
E
obtain the marks of
0
to
9
grades as the sum of them. The values of F have also
5
grades,
0
to
4
. The principles to determine the values of
E
, F are as follows : a) The marks obtained of
E
, F must be the relative values among the each survey, and at the same time, they must have constancy within the same survey-the same elements of design must win the same marks obtained.
b
) They must be determined as to win the highest multiple correlation coefficient, when they are put into the estimation formula. c) They must be reasonable. In order to justify them, we must carry many researches on the actual condition. The frequency of accurence of each grade of
E
, F values, as the table
5
-
4
, and
5
-
5
in the thesis in Japanese.
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