Types of correlation, Applied Statistics

Assignment Help:

Type of Correlation

1.      Positive and Negative Correlation:

2.      Simple Partial and Multiple Correlations.

3.      Linear and  Non linear or Correlations:

1. Positive and Negatives Correlations: If changes in two variables are in same direction. Increase in one variable is associated with the corresponding increase in other variable, the correlations is said to be positive. For example increase in price and increase  in supply, increase in father ages and increase  in sons ages, higher amount  of capital employed  associated with higher expected profit etc.

On the other hand if variations or fluctuations in two variables are in opposite direction or  in other  words the  increase in one  variable is associated with the corresponding   decreases  in other  or vice  versa  the correlation is said to be negative . For example, increase in price associated with the decrease in demand and vice versa .Thus price and demand have negative correlation. 

2. Linear and non linear Correlation: The distinction between linear and non linear correlation is based upon the constancy of the ratio of change between the two variables. If    the amount of changes in one variable tends to bear constant ratio of change in the other a variable, the correlation is said to be linear. For example, if in a factory raw material or numbers of direct workers are doubled, the production is also doubled, and vice versa correlation would be linear.

On the other hand correlation would be called curvilinear if the amount of change in one variable does not bear a constant ratio of change in the other variable. For example the amount spent on advertisement will not bring the change in the amount of sales in same ratio. It means the variations in both the variables are not inconstant ratio.

Thus linear and non linear correlation may also be positive or negative .It is clear from the following chart.

Thus it is clear from the above that:

1.      If changes in two variables are in the same direction and in constant ratio. The correlation s is linear positive. For example every10% increase in inflation results in 15% increase in general price level. Correlation   between inflation and general price level would be linear and positive.

2.      If changes in two variables are in the opposite direction in constant ratio, the correlation is linear negative. For example every 5% increase in price of a commodity is associated with 10% decrease in demand, the correlation between price and Demand would be negative linear.

3.       If changes in two variable are in the same direction but not inconstant ratio, the correlation is positive nonlinear. For example every increase  of 10%  quantity of money  in circulation, the general price level increases by 5or6%  the   correlation  between  inflation  and general price level would  be positive  curvi  linear.

4.      If changes is two variables are in opposite direction and not inconstant ratio, the correlation is negative curvilinear. For example for every  5%  increase in price  of a commodity is associated with 2%  to 10%  decrease in demand, the correlation between  price and demand is said to be negative and curivilinear  

3. Simple, Partial and Multiple Correlations: The distinction between simple, partial and multiple correlations   based   upon the number of variables studied. When only two variables are studied, it is as case    of simple correlation. On the other hand when three or more variable are studied, it is a problem of either multiple or partial correlation.

When three or more variable are studied simultaneously, it is called multiple correlation. When a study of yield per acre of wheat is studied with a unit change in fertilizers and the rainfall,it is a problem of multiple correlation, whereas  in partial correlation more than two  variables are studied, but consider the influence of a third variable on the two variables influencing variables being kept constant, it is a problems  of partial correlation. For example, if the change in yield of wheat and rice is studied with reference to a unit of fertiliser or rainfall, it is a case of partial correlation. 


Related Discussions:- Types of correlation

Calculate the damping ratio for each system, (i) Plot the step responses of...

(i) Plot the step responses of the following second order systems and state the nature of each system. For each case, find the poles and plot the location of the poles in the compl

Geometric mean, Geometric Mean The geometric mean   of numbers is defin...

Geometric Mean The geometric mean   of numbers is defined as the th root of the product of numbers .It is obtained by multiplying all the values of a variable and then extracti

Introduction to multiple regression, In simple regression the dependent var...

In simple regression the dependent variable Y was assumed to be linearly related to a single variable X. In real life, however, we often find that a dependent variable may depend o

Calculate the maximum weight of the engine, Determine the maximum weight in...

Determine the maximum weight in kN to one decimal point (1 DP) of the engine that can be supported without exceeding the tension given in  Parameter 1 (P1) in chain AB or 1.1 x P1

Find probability of remaining paint free - ball duel, In a three-cornered p...

In a three-cornered paint ball duel, A, B, and C successively take shots at each other until only one of them remains paint free. Once hit, a player is out of the game and gets no

the npv of the book , Bill Clinton reportedly was paid $10 million to writ...

Bill Clinton reportedly was paid $10 million to write his book My Way. The book took three years to write. In the time he spent writing, Clinton could have been paid to make speech

Regression, why we use dummy variable

why we use dummy variable

Convenience sampling, Convenience Sampling It means a convenient sample...

Convenience Sampling It means a convenient sample is obtained by selecting convents units from the universe. Convenient sample is also known as chunk. It   means a fraction of

Simple regression analysis, Construct your initial multivariate model by se...

Construct your initial multivariate model by selecting a dependent variable Y and two independent variables X. Clearly define what each variable represents and how this relates t

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd