Correlation analysis is a type of statistical analysis used to measure the strength of the relationship between two variables. It is used to determine whether there is a cause-and-effect relationship between two variables or if one of the variables is simply related to the other. It is usually expressed as a correlation coefficient a number between -1 and 1. A positive correlation coefficient means that the variables move in the same direction while a negative correlation coefficient means they move in opposite directions.
Regression analysis is a type of statistical analysis used to predict the value of one variable based on the value of another. This type of analysis is used to determine the relationship between two or more variables and to determine the direction strength and form of the relationship. Regression analysis is useful for predicting future values of the dependent variable given a set of independent variables.
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We consider correlation as a several independent variables.
correlation is a difference in statistics
correlation is used when there is metric data and chi square is used when there is categorized data. sayan chakrabortty
statisctics are raw numbers while quantitive analysis is what those numbers repersent.
Correlation and regression analysis can help business to investigate the determinants of key variables such as their sales. Variations in a companies sales are likely to be related to variation in product prices,consumers,incomes,tastes and preference's multiple regression analysis can be used to investigate the nature of this relationship and correlation analysis can be used to test the goodness of fit. Regression can also be used to estimate the trend in a time series to make forecast