Correlation refers to statistical relationships between two random variables. The correlation coefficient r ranges from -1 to 1, indicating the direction and strength of the relationship. Karl Pearson and Spearman methods can be used to calculate r. While correlation indicates an association, it does not imply causation. Correlation is used in business, government, education, medicine, and agriculture to study relationships and make predictions.
2. Correlation
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Correlation refers to statistical relationships
involving two random variables or sets of
data
The correlation coefficient is denoted by ‘r’
and ranges from -1 to +1
Tells the Direction and Measure of the
Relationship between two variables
3. Coefficient of Correlation
The coefficient of correlation can be:
perfectly negative
r=-1
strong negative
-1<r<0 and r closer to 1
weak negative
-1<r<0 and r closer to 0
independent
r=0
strong positive
0<r<1 and r closer to 1
weak positive
0<r<0 and r closer to 0
perfect positive
r=1
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14. Business
• Marketing Expenditure and Sales Volume
correlation (to measure the efficiency of
marketing department)
• Correlation between prices of two securities
in the stock market.
• Price of a commodity to supply(or demand)
correlation.
15. Government
• Year on Year Revenue and Expenditure
Correlation (to forecast revenue based on
expenditure)
• Tool in formulating various Economic Policies
by correlating past trends.
• Yardstick to measure performance
(Correlation between Planned and Actual
Revenue)
16. Education Models
• Forecasting of student input flows towards
elementary education (Correlation between
birth rate data and enrollment in
elementary grades)
• Forecasting of dropped out student flows at
different levels of education (intermediate,
graduate, post graduate)
17. Medicine
• Finding out after effects of interactions
between different medicines.
• Estimating the best treatment where
various methods are applicable
(Correlation between individual
treatments’ results and severity of
disease.
18. Agriculture
• Correlation between certain weather
conditions and Productivity.
• Correlation between irrigating and
Productivity.
• Correlation between price and production
or price and demand, to study demand
supply pattern of crops in different seasons.
19. Conclusion
• Correlation is one of the many effective
ways of forecasting and predicting
possible outcomes based on past
observations.
• Though other statistical methods too
need to be implemented to get a
complete picture of the situation.