Absolute measure of dispersion indicates the amount of variation in a set of values in terms of units of observations.

The degree of variation is evaluated by various measures of dispersion. There are two kinds of measures of dispersion, namely
1. Absolute measure of dispersion
2. Relative measure of dispersion

Econometrics may be defined as the social science in which the tools of economic theory, mathematics and statistical inference are applied to the analysis of economic phenomena.

(i) Regression means going back and it is a mathematical measure showing the average relationship between two variables.
(ii) It indicates the cause and effect relationship between the variables and establishes functional relationship.

(i) Correlation is a statistical device that helps to analyse the covariation of two or more variables.
(ii) Correlation is the relationship between two or more variables which vary with the other in the same or the opposite direction.

Linear Correlation: Correlation is said to be linear when the amount of change in one variable tends to bear a constant ratio to the amount of change in the other.
Ex. Y= a + bx
Non Linear: The correlation would be non-linear if the amount of change in one variable
does not bear a constant ratio to the amount of change in the other variables.
Ex. Y= a + bx2

There are three types based upon the number of variables studied as
a) Simple Correlation
b) Multiple Correlation
c) Partial Correlation
Simple Correlation:
If only two variables are taken for study then it is said to be simple correlation. Ex. Y= a + bx
Multiple Correlations:
If three or more than three variables are studied simultaneously, then it is termed as multiple correlation.
Ex: Determinants of Quantity demanded
Qd = f (P, Pc, Ps, t, y)
Where Qd stands for Quantity demanded, f stands for function.
P is the price of the goods,
Pc is the price of competitive goods
Ps is the price of substituting goods
t is the taste and preference
y is the income.
Partial Correlation:
If there are more than two variables but only two variables are considered keeping the other variables constant, then the correlation is said to be Partial Correlation

Central Statistical Office (CSO)
(i)  It is responsible for co-ordination of statistical activities in the country and for evolving and maintaining statistical standards.
(ii) It compiles National Accounts, conducts Annual Survey of Industries and Economic Census, compiles Index of Industrial Production and Consumer Price Indices.
(iii) It deals with social statistics, training, international co-operation, Industrial Classification, etc.
National Sample Survey
Organisation
NSSO has four divisions:
(i) Survey Design and Research Division
(ii) Field Operations. Division
(iii) Data Processing Division
(iv) Co-ordination and Publication Division
The Programme Implementation Wing has 3 Divisions:
(i) Twenty Point Programme
(ii) Infrastructure Monitoring and Project Monitoring
(iii) Member of Parliament Local Area Development Scheme.
1. There is National Statistical Commission and one autonomous Institute, i.e., Indian Statistical Institute.

(i) Models in Mathematical Economics are developed based on Economic Theories, while Econometric Models are developed based on Economic Theories to test the validity of Economic Theories in reality through the actual data.
(ii) Regression Analysis in Statistics does not concentrate more on error term while Econometric Models concentrate more on error terms  

(i) The general objective of Econometrics is to give empirical content to economic theory
(ii) The specific objectives are :
(i) It helps to explain the behaviour of a forthcoming period that is forecasting economic phenomena.
(ii)  It helps to prove the old and established relationships among the variables or between the variables.
(iii) It helps to establish new theories and new relationships.
(iv) It helps to test the hypotheses and estimation of the parameter.

1. Find out the actual mean of given data (x̅)
2. Find out the deviation of each value from the mean (x = X - x̅ )
3. Square the deviations and take the total of squared deviations Σx²
4. Divided the total Σx² by the number of observation \(\left( { \frac { \sum { x } }{ n } }^{ 2 } \right) \)
5. The square root of \(\left( { \frac { \sum { x } }{ n } }^{ 2 } \right) \) is standard deviation.

BASIS FOR COMPARISON	QUALITATIVE DATA	QUANTITATIVE DATA
Meaning	Qualitative data is the data in which the classification of objects is based on attributes and properties.	Quantitative data are those that can be quantified in definite units of measurement
Examples	Eg. Gender, Community, honesty	Age, income, number of firms etc
Approach	Subjective	Objective
Collection of data	Unstructured	Structured
Sample	Small number of nonrepresentative samples	Large number of representative samples
Outcome	Develops initial understanding.	Recommends final course of action