A DETAILED PRESENTATION ON RELATIONS INSCIENTIFIC RESEARCH

1. A DETAILED PRESENTATION ON
RELATIONS IN
SCIENTIFIC RESEACH
BY
NUSRAT AZEEMA

2. Relations are the essence of knowledge
•What is important in science is not knowledge of
particulars but knowledge of the relations among
phenomena

4. Definition
•A relation is a bond, a connection, a kinship.
•The way in which two or more people or
things are connected; a thing's effect on or
relevance to another.

5. •Relation in science are always between
classes or set of objects.

6. Determining relations in research
Cartesian
Product
Any subset
of ordered
pairs drawn
from a x b is
a relation.

7. Determining relations in research
•We determine empirically which element of B
according to some criteria.
•Kershner and Wilcox say that a relation is “a
method for distinguish some ordered pairs from
others; it is a scheme for singling out certain
pairs from all of them”.

8. Rules of Correspondence and Mapping
•A rule of correspondence is a prescription or a
formula that tells how to map the objects of one
set on to the objects of another set.
•Objects especially numbers are assigned to other
objects– persons, place, number and so on ---
according to rules.

9. All the varied
ways of
expressing
relations– as
mapping,
corresponden
ces, equations,
set of points,
tables or
statistical
indices-

10. Graphs
•A graph is drawing in which the two members of
each ordered pair of a relation are plotted on two
axes, X and Y.

11. Graphs

12. Tables
•A table itself is a cross partition, often called a
crossbreak, in which one variable labels appear
on the top and side of the table.
•Tables of means are extremely important in
behavioral research, especially in experimental
research.

13. Tables

15. Correlation Coefficient

16. Graphs and Correlation

17. Multivariate Regression
•Multiple Regression is very popular among
social scientists.
•Most social phenomena have more than one
cause.
•It is very difficult to manipulate just one
social variable through experimentation.

18. Multivariate Regression
•Multiple Regression allows us to: Use several
variables at once to explain the variation in a
continuous dependent variable.

Y = a + b1X1+ b2X2
Mathematically, that plane is:

19. Multiple Regression
 For example:
A researcher may be interested in the relationship between
Education and Income and Number of Children in a family.
Independent Variables
Education
Family Income
Dependent Variable
Number of Children

20. Multiple Regression
Interactions
Another very important concept in multiple regression is
“interaction,” where two variables have a joint effect on
the dependent variable. The relationship between X1
and Y is affected by the value each person has on X2.

21. For example:
•Wages (Y) are decreased by being black (X1), and
wages (Y) are decreased by being female (X2).
However, being a black woman (X1* X2) increases
wages relative to being a black man.

22. Multiple variables…good orbad?
•Multiple regression is wonderful in that it allows you
to consider the effect of multiple variables
simultaneously.
•Multiple regression is extremely unpleasant because it
allows you to consider the effect of multiple variables
simultaneously.
•The relationships between the explanatory variables
are the key to understanding multiple regression.
DataAnalysisCourse
VenkatReddy
19