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Based on the distribution of the points on the residual plot, where the points are randomly dispersed and shows no obvious trend or pattern, then we can conclude that a Least Square Regression model is appropriate for the data .
- The graph of a residual plot is used to Analyse the the appropriateness of a linear regression to model a given data set.
- The residual values are plotted against the independent variable in other to make a residual plot of the data.
- The arrangement of the points on the residual graph is key to making a decision on the model.
Therefore, since the residual plot produced shows a random distribution of the residual values, then the least square regression model is appropriate for the data.
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Answer:
Based on the distribution of the points on the residual plot, where the points are randomly dispersed and shows no obvious trend or pattern, then we can conclude that a Least Square Regression model is appropriate for the data .
The graph of a residual plot is used to Analyse the the appropriateness of a linear regression to model a given data set.
The residual values are plotted against the independent variable in other to make a residual plot of the data.
The arrangement of the points on the residual graph is key to making a decision on the model.
Therefore, since the residual plot produced shows a random distribution of the residual values, then the least square regression model is appropriate for the data.
Step-by-step explanation:
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