A marketing manager for Costco, is trying to determine if there is a relationship between shelf space (in feet) and sales (in hundreds of dollars). To do this, the manager selected the top 12 producing locations. The regression results produced the following adjusted R2 values: Model 1: 0.8874 and Model 2: 0.6028. Which model is a better prediction of the outcome? Model 1
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.
A marketing manager for Costco, is trying to determine if there is a relationship between shelf space (in feet) and sales (in hundreds of dollars). To do this, the manager selected the top 12 producing locations. The regression results produced the following adjusted R2 values: Model 1: 0.8874 and Model 2: 0.6028. Which model is a better prediction of the outcome?
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Model 1 |
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Model 2 |
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Both are equally suitable |
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Neither model explains anything about the dependent variable |
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