Cost accountants often estimate overhead based on the level of production. At the XYZ Company, they have collected information on overhead expenses and units produced at different plants and want to estimate a regression equation to predict future overhead. The data is available as given in the table below. Develop the regression equation for the cost accountants using Least Square Method. Predict overhead when 50 units are produced. Overhead Units 166 65 145 67 247 78 130 60 255 81 148 64 409 73 116 55 153 62 178 65
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
| Cost accountants often estimate overhead based on the level of production. At the XYZ Company, they have collected information on overhead expenses and units produced at different plants and want to estimate a regression equation to predict future overhead. The data is available as given in the table below. | ||||||||
| Develop the regression equation for the cost accountants using Least Square Method. | ||||||||
| Predict overhead when 50 units are produced. | ||||||||
| Overhead | Units | |||||||
| 166 | 65 | |||||||
| 145 | 67 | |||||||
| 247 | 78 | |||||||
| 130 | 60 | |||||||
| 255 | 81 | |||||||
| 148 | 64 | |||||||
| 409 | 73 | |||||||
| 116 | 55 | |||||||
| 153 | 62 | |||||||
| 178 | 65 | |||||||
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