Group data refers to data that is illustrated in the form of a range such as 20-50. Ungrouped data shows single numbers such as 20,21,30,42. A good graphical technique to illustrate the prices of homes in a particular region is a bar graph. The bar graph can illustrate the different prices of homes in the area. The reason I choose a bar chart is because it reflects categorical data. Below is an example of a bar chart with five home prices ($100000, $150000, $200000, $175000, and $250000).
The basic formula used in a regression analysis is y = a + bx. In this formula the y represents the dependent variable. This variable is subject to the independent variables to find the result of the equation. The dependent variable cannot be controlled, but the result is influenced by the values of the independent variable or variables. If the formula illustrated above had multiple independent variables the regression formula would be a multiple regression. “In mathematics the independent variable is one whose value does not depend on any other variable” (Wisegeek, 2010). In the formula mentioned above the X represent the independent variable. B is the slope of the regression line, while A represents the intercept point of the regression line and the y axis. Regression analysis is a tool that is very useful due to the fact that it allows managers to forecast information. Once the regression equation is created the user can alter the independent variable in order to forecast something based on the model. The slope tells us how inclined is the regression line. An application that managers can use is forecasting its sales. The manager would have to input the sales of the company for multiple past periods such as ten years. Once the data is input into the linear regression the manager can forecast the future sales of the company.
Regression analysis can be extremely useful to forecast any type of business data. Managers have a need to forecast the future due to the fact