Forecasting simple linear regression applications

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 or 'predictors'. More specifically, regression analysis helps one understand how the typical value of the dependent variable or 'criterion variable' changes when any one of the independent variables is varied, while the other independent variables are held fixed. Most commonly, regression analysis estimates the conditional expectation of the dependent variable given the independent variables — that is, the average value of the dependent variable when the independent variables are fixed.

Forecasting simple linear regression applications

The reason why the father wished to close down the branch was that it appeared to be making a loss. However, it is quite the reverse; if the branch was closed then, the positive contribution from the branch would be lost and overall profits would fall. This is because the indirect costs of production do not vary with output and, therefore, closure of a section of the firm would not lead to immediate savings.

This may mean that closing the branch would be a mistake on financial grounds.

Forecasting simple linear regression applications

This mistake is made due to a misunderstanding of nature of cost behavior. If the branch is closed then the only costs that would be saved are the costs directly related to the running of the branch: The costs are indirect in nature, in this example the marketing and central administration costs, would still have to be paid as they are unaffected by output.

For this decision to be made, we should use contribution as a guide for deciding whether or not to close a branch. This can also be applied to the production of certain product lines, or the cost effectiveness of departments.

On financial grounds, contribution is therefore, a better guide in making decisions.It seems your browser doesn't support frames - that means you cannot see the cool design of this page. If you see this for more than 5 seconds you should click this link to load the NOFRAME version.

Indecision and delays are the parents of failure.

Romanian Journal of Economic Forecasting

The site contains concepts and procedures widely used in business time-dependent decision making such as time series analysis for forecasting and other predictive techniques. Below is the formula for a simple linear regression.

The "y" is the value we are trying to forecast, the "b" is the slope of the regression line, the "x" is the value of our independent value, and. Linear regression analysis is a method of analyzing data that has two or more variables.

By creating the "best fit" line for all the data points in a two-variable system, values of y . The statistical tools used to analyze the data are: Co-relation analysis, Simple Linear Regression and Multiple Linear Regression.

The software used to analyze the data is Windostat version , developed by Indostat services, is an advanced level statistical software for .

Time Series Analysis for Business Forecasting

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