The following table gives indices of industrial production of registered unemployed (in hundred thousand) Year: 2000 2001 2002 2003 2004 2005 2006 2007 Index of Production 100 102 104 107 105 112 103 99 No. unemployed 15 12 13 11 12 12 19 26 Required: Identify the dependent and the independent variables By first computing the regression coefficient “a” and “b”, state the regression equation of y on x. Sketch your results in (ii) above
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
The following table gives indices of industrial production of registered unemployed (in hundred thousand)
|
Year: |
2000 |
2001 |
2002 |
2003 |
2004 |
2005 |
2006 |
2007 |
|
Index of Production |
100 |
102 |
104 |
107 |
105 |
112 |
103 |
99 |
|
No. unemployed |
15 |
12 |
13 |
11 |
12 |
12 |
19 |
26 |
Required:
Identify the dependent and the independent variables
By first computing the regression coefficient “a” and “b”, state the regression equation of y on x.
Sketch your results in (ii) above
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