EXCEL

.....Our assignment today is about linear regression and quadratic regeression.......


LINEAR REGRESSION

LINEAR REGRESSION  is an approach to modeling the relationship between a scalar variable y and one or more variables denoted X. In linear regression, models of the unknown parameters are estimated from the data using linear functions. Such models are called linear models. Most commonly, linear regression refers to a model in which the conditional mean of y given the value of X is an affine function of X. Less commonly, linear regression could refer to a model in which the median, or some other quantile of the conditional distribution of y given X is expressed as a linear function of X. Like all forms of regression analysis, linear regression focuses on the conditional probability distribution of y given X, rather than on the joint probability distribution of y and X, which is the domain of multivariate analysis.

QUADRATIC REGRESSION
 
QUADRATIC REGRESSION models are often used in economics areas such as utility function , forecasting, cost-befit analysis, etc. This JavaScript provides parabola regression model. This site also presents useful information about the characteristics of the fitted quadratic function.
Prior to using this JavaScript it is necessary to construct the scatter-diagram for your data.
If by visual inspection of the scatter-diagram, you cannot reject a "parabola shape", then you may use this JavaScript. Otherwise, visual inspection of the scatter-diagram enables you to determine what degree of polynomial regression models is the most appropriate for fitting to your data.