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An Introduction to the theory of statistics

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fullscreen: An Introduction to the theory of statistics

Monograph

Identifikator:
1751730271
URN:
urn:nbn:de:zbw-retromon-127610
Document type:
Monograph
Author:
Yule, George Udny http://d-nb.info/gnd/12910504X
Title:
An Introduction to the theory of statistics
Edition:
8. ed. rev
Place of publication:
London
Publisher:
Griffin
Year of publication:
1927
Scope:
XV, 422 S
Ill., Diagr
Digitisation:
2021
Collection:
Economics Books
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Chapter

Document type:
Monograph
Structure type:
Chapter
Title:
Part II. The theory of variables
Collection:
Economics Books

Contents

Table of contents

  • An Introduction to the theory of statistics
  • Title page
  • Part I. The theory of atributes
  • Part II. The theory of variables
  • Part III. Theory of sampling
  • Index

Full text

. THEORY OF STATISTICS. 
theory or by previous experience, it may be possible to throw 
that relation into the form 
Y=24 + B.¢(X), 
where 4 and B are the only unknown constants to be determined. 
If a correlation-table be then drawn up between ¥ and ¢(X) 
instead of ¥ and JX, the regression will be approximately linear. 
Thus in Table V. of the last chapter, if X be the rate of 
discount and Y the percentage of reserves on deposits, a 
diagram of the curves of regression, or curves on which the 
means of arrays lie, suggests that the relation between X and Y 
is approximately of the form 
X(Y -B)=4, 
4 and B being constants ; that is, 
XY=4+ BX. 
Or, if we make XY a new variable, say Z, 
Z=4+ BX. 
Hence, if we draw up a new correlation-table between X and Z 
the regression will probably be much more closely linear. 
If the relation between the variables be of the form 
Y= ADZ 
we have 
log Y=1og 4 + X. log B, 
and hence the relation between log ¥ and X is linear. Similarly, 
if the relation be of the form 
X¥=4 
we have 
log Y=1log 4 —n. log X, 
and so the relation between log Y¥ and log X is linear By 
means of such artifices for obtaining correlation-tables in 
which the regression is linear, it may be possible to do a good 
deal in difficult cases whilst using elementary methods only. 
The advanced student should refer to ref. 17 for a different 
method of treatment. 
19. The only strict method of calculating the correlation 
coefficient is that described in Chapter IX. from the formula 
po SOIL Approximations to this value may, however, be 
N.c,0, 
202
	        

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