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If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at? Regression
If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at?
- Regression Equation:Provide the regression equation for the line of best fit using the scatterplot from the Module Two assignment.
- Determiner:Determinerand what it means. (What is the relationship between the variables?)
- Determine the strength of the correlation (weak, moderate, or strong).
- Discuss how you determine the direction of the association between the two variables.
- Is there a positive or negative association?
- What do you see as the direction of the correlation?
- Examine the Slope and Intercepts:Examine the slopeb1{"version":"1.1","math":""}and interceptb0{"version":"1.1","math":""}.
- Draw conclusions from the slope and intercept in the context of this problem.
- Does the intercept make sense based on your observation of the line of best fit?
- Determine the value of the land only. Note:You can assume, when the square footage of the house is zero, that the price is the value of just the land. This happens whenx=0, which is they-intercept. Does this value make sense in context?
- Draw conclusions from the slope and intercept in the context of this problem.
- Determine theR-squared Coefficient:Determine theR-squared value.
- Discuss whatR-squared means in the context of this analysis.
- Conclusions:Reflect on the Relationship: Reflect on the relationship between square feet and sales price by answering the following questions:
- Is the square footage for homes in your selected region different than for homes overall in the United States?
- For every 100 square feet, how much does the price go up (i.e., can you use slope to help identify price changes)?
- What square footage range would the graph be best used for?
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