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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":"b1"}and interceptb0{"version":"1.1","math":"b0"}.
    • 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?
  • 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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