Correlation In Advance

Learn Karl Pearson Correlation and Spearman Rank Correlation

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Correlation In Advance

What You Will Learn!

  • Meaning of Correlation
  • Degree of Correlation
  • Karl Pearson’s Coefficient of correlation
  • Calculation of correlation by Direct Method
  • Spearman’s Rank Difference Method
  • Spearman’s Ranking method

Description

Meaning of Correlation

Examples of correlation

(i) Rain : Agricultural product = Relation

(ii) Supply : Price = Relation

(iii) Age : Playing Habit = Relation

(iv) Temperature : Sale of ice cream = Relation

(v) Temperature : Sale of Mobile = Relation

(vi) Weight : Height = Relation

Correlation and Cause-effect relationship

1. One variable may act upon the other

2. The two variables may act upon each other

3. The two variables may be acted upon by outside influences

4. A high correlation coefficient may be derived due to sheer coincidence

Degree of Correlation

Karl Pearson’s Coefficient of correlation

Meaning of Karl Pearson’s Coefficient of correlation

Karl Pearson’s Coefficient of correlation by Calculation of correlation by Direct Method

Karl Pearson’s Coefficient of correlation by Calculation of correlation by Shortcut Method

Karl Pearson’s Coefficient of correlation In discrete and continuous series  Or

Correlation in Bivariate frequency distribution      Or

Correlation in grouped series

Some Important Questions for Practice


Spearman’s Rank Difference Method

Meaning of Spearman’s Rank Difference Method

Spearman’s Ranking method

Problem of Similar marks


Probable Error

Meaning of Probable Error

Some Important practical problems for Practice


Meaning of Correlation :

The term correlation indicates the relationship in between two such variables in which with change in the value of one variable, the values of the other variable also changes. It is likely that such relationship may be obtained in two series relating to the height and weight of a group of a person. This analysis is a statistical procedure by which we can determine the degree of association or relationship between two or more variables.

Who Should Attend!

  • Any Student who pursuing in B,com M,com BBA MBA 11th & 12th Commerce C.A. C.S. and C.M.A.

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Tags

  • Accounting

Subscribers

1

Lectures

12

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