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Answer :
To answer the question about the relationship between square footage and rent, let's go through the required steps in a simple way:
Step 1: Record the Data
We have the following data:
- Square Footage (x): 677, 765, 822, 784, 810, 897, 799
- Rent per Month (R): 1345, 1405, 1445, 1415, 1435, 1515, 1440
Step 2: Draw the Scatter Diagram
If you were to draw a scatter plot with 'square footage' on the x-axis and 'rent per month' on the y-axis, you would plot each pair as a point on the graph.
Step 3: Analyze the Scatter Diagram for Relation
By observing the scatter plot, we aim to determine if the points follow a recognizable pattern. In this situation, because the scatter plot shows that as the square footage increases, the rent tends to increase as well, this suggests a relationship.
Step 4: Determine the Type of Relationship
Given the nature of the points, if they fall close to a straight line, this indicates a linear relationship. The correlation value, which checks how closely data points fit a straight line, supports this type of analysis.
Result:
- Correlation Value: A correlation value very close to 1 (such as 0.99) suggests a strong positive linear relationship.
- Conclusion: Based on the high correlation, we conclude:
- _"A. There appears to be a linear relation between square footage and rent."_
Therefore, there's a strong linear relationship between square footage and rent.
Step 1: Record the Data
We have the following data:
- Square Footage (x): 677, 765, 822, 784, 810, 897, 799
- Rent per Month (R): 1345, 1405, 1445, 1415, 1435, 1515, 1440
Step 2: Draw the Scatter Diagram
If you were to draw a scatter plot with 'square footage' on the x-axis and 'rent per month' on the y-axis, you would plot each pair as a point on the graph.
Step 3: Analyze the Scatter Diagram for Relation
By observing the scatter plot, we aim to determine if the points follow a recognizable pattern. In this situation, because the scatter plot shows that as the square footage increases, the rent tends to increase as well, this suggests a relationship.
Step 4: Determine the Type of Relationship
Given the nature of the points, if they fall close to a straight line, this indicates a linear relationship. The correlation value, which checks how closely data points fit a straight line, supports this type of analysis.
Result:
- Correlation Value: A correlation value very close to 1 (such as 0.99) suggests a strong positive linear relationship.
- Conclusion: Based on the high correlation, we conclude:
- _"A. There appears to be a linear relation between square footage and rent."_
Therefore, there's a strong linear relationship between square footage and rent.
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