Page 17 - DMGT209_QUANTITATIVE_TECHNIQUES_II

Quantitative Techniques-II

Notes

Did u know? What is Skewness?

The measures of the direction and degree of symmetry are called measures of the skewness.
Another characteristic of the frequency distribution is the shape of the peak, when it is
plotted on a graph paper.

Did u know? What is Kurtosis?
The measures of the peakedness are called measures of Kurtosis.

(iii) Correlation: Correlation coefficient measures the degree to which the change in one
variable (the dependent variable) is associated with change in the other variable
(independent one). For example, as a marketing manager, you would like to know if there
is any relation between the amount of money you spend on advertising and the sales you
achieve. Here, sales are the dependent variable and advertising budget is the independent
variable. Correlation coefficient, in this case, would tell you the extent of relationship
between these two variables, whether the relationship is directly proportional (i.e. increase
or decrease in advertising is associated with increase or decrease in sales) or it is an
inverse relationship (i.e. increasing advertising is associated with decrease in sales and
vice-versa) or there is no relationship between the two variables.

!

Caution Correlation coefficient does not indicate a casual relationship, Sales is not a direct
result of advertising alone, and there are many other factors which affect sales.
Correlation only indicates that there is some kind of association-whether it is casual or
causal can be determined only after further investigation. You may find a correlation
between the height of your salesmen and the sales, but obviously it is of no significance.
(iv) Regression Analysis: For determining causal relationship between two variables you
may use regression analysis. Using this technique you can predict the dependent variables
on the basis of the independent variables. In 1970, NCAER (National Council of Applied
‘
and Economic Research) predicted the annual stock of scooters using a regression model
in which real personal disposable income and relative weighted price index of scooters
were used as independent variable.
The correlation and regression analysis are suitable techniques to find relationship between
two variables only. But in reality you would rarely find a one-to-one causal relationship;
rather you would find that the dependent variables are affected by a number of independent
variables.

Example: Sale affected by the advertising budget, the media plan, the content of the
advertisements, number of salesmen, price of the product, efficiency of the distribution network
and a host of other variables.

For determining causal relationship involving two or more variables, multi-variate
statistical techniques are applicable. The most important of these are the multiple regression
analysis, discriminant analysis and factor analysis.
(v) Time Series Analysis: A time series consists of a set of data (arranged in some desired
manner) recorded either at successive points in time or over successive periods of time.
The changes in such type of data from time to time are considered as the resultant of the

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