Answer:
I understand you're asking about the coefficient of determination (R-squared) and its interpretation in the context of the provided data. Unfortunately, I don't have access to external content like the accompanying table you mentioned. However, I can explain what R-squared is and how to interpret it.
Step-by-step explanation:
R-squared (R²) is a statistical measure that represents the proportion of the variance in the dependent variable (usually the y variable) that is explained by the independent variable(s) (usually the x variable(s)) in a regression model. It's a value between 0 and 1, where:
R² = 0 means that the model explains none of the variance in the dependent variable.
R² = 1 means that the model explains all of the variance in the dependent variable.
In the context of your question, R² is used to assess how well the regression model fits the data. A higher R² value indicates that a larger proportion of the variability in the dependent variable is explained by the independent variable(s) in the model.
Based on the two options you provided:
A. "About % of the variance in Sales can be accounted for by the regression of Sales on Number of Sales People Working."
B. "About & of the variance in the Number of Sales People working can be accounted for by the regression of Sales on Number of Sales People Working."
The correct interpretation is option A. R-squared reflects the percentage of variance in the dependent variable (Sales) that can be explained by the regression model involving the independent variable (Number of Sales People Working). The higher the R-squared value, the better the regression model fits the data and captures the relationship between these variables.