In statistics, regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables.
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In regression analysis , heteroscedasticity means a situation in which the variance of the dependent variable varies across the data. Heteroscedasticity complicates analysis because many methods in regression analysis are based on an assumption of equal variance.
The marine regression analysis showed that the new subdivision was responsible for the coastline erosion.The wrinkle cream showed a regression in age lines.
A mix of linear regression and analysis of variance. analysis of covariance is responsible for intergroup variance when analysis of variance is performed.
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
used to predict the dependent variable