Correlation and its importance Types of correlation Partial correlation Mutiple correlation Correlation coefficients Regression Multiple regression

1. Correlation and Regression
-presented by group “Everest”
Anil Pokhrel
Amit Budachhetri
Ajit Pudasaini
Rikriti Koirala
Roji shrestha
Puja Neupane

2. Contents
Correlation and its importance
Types of correlation
Partial correlation
Mutiple correlation
Correlation coefficients
Regression
Multiple regression
Conclusion
Reference
2

3. Correlation and its importance
Correlation is defined as relation between two
variables.
Its importance are listed below:
There is necessary to correlate one subject with
another. No subject can be taught in isolation
 The effect of correlation is to reduce the range
of uncertainty. The prediction based on
correlation analysis is likely to be more variable
and near to reality.
3

4. TYPES OF CORRELATION
Partial correlation
Multiple correlation
Graph of the Correlation
4

5. Partial correlation
Partial correlation is a relationship between
two variables keeping the other variabes
constant or fixed.
5

6. Multiple correlation
• The relationship among three or more
variables at the same time
6

7. Coefficients of correlation
What is the Correlation Coefficient?
The correlation coefficient is a measure that determines
the degree to which two variables' movements are
associated.
 The range of values for the correlation coefficient is -1.0
to 1.0. If a calculated correlation is greater than 1.0 or
less than -1.0, a mistake has been made.
A correlation of -1.0 indicates a perfect negative
correlation, while a correlation of 1.0 indicates a perfect
positive correlation
7

8. Regression
In statistical modeling, regression analysis is a
statistical process for estimating the
relationships among variables.
More specifically, regression analysis helps one
understand how the typical value of the
dependent variable changes when any one of
the independent variables is varied
8

9. Multiple Regression
 It is a statistical technique that
simultaneously develops a mathematical
relationship between two or more
independent variables.
9

10. Conclusion
• Statistics can summarize and simplify large
amounts of numerical data
• Using statistics one can draw conclusions
about data.
• Statistics can help communicate findings
clearly and meaningfully to others
• Statistical data is not always 100 percent sure.
10

11. References
• Notes provided by our respected Prabin lal sir
• Google
• Wikipedia
• Course book
11