A company randomly samples 48 months of monthly output and monthly total cost data. The sampled data will be used to develop a total cost curve for the company. The company believes that its monthly total cost depends, to a large extent on its monthly output, and hopes that a simple linear regression model will be useful in analyzing how total costs vary as monthly output varies. The company proposes the following model: Total Cost = Fixed Cost + Variable Cost per Unit *Monthly Output. Recall that fixed costs do not vary with the level of monthly output, while the variable cost per unit describes the change in total costs when monthly output changes by one unit. Regression Statistics Standard Error 64.252 Observations 48
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.


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