Activity #8 Correlation & Regression (AU23 in-person)

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Columbus State Community College *

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2200

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Statistics

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Feb 20, 2024

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STAT 1350 – Elementary Statistics Instructor: S. Hardin Lab Activity #8: Correlation and Regression Name: ______________________ Complete the following questions and submit the activity on Blackboard before the deadline. The sales manager at Sun City Real Estate Company is interested in describing the relationship between condo sales price and the number of weeks the condo is on the market before it sells. He has collected a random sample of condos that have sold within the past three months in their area. The data is shown below: Weeks on Market Selling Price (in thousands of $) 18 125 48 73 51 61 33 76.5 56 53 9 133 25 94 47 90 32 107 27 84 23 54 16 102 1. Draw the scatterplot for the relationship between weeks on the market and selling price. Don’t forget to label the axis. Based on the graph, what is the…. Form: ____________________ Direction: _________________ Strength: _________________ Outlier(s): ________________ List (if any) or say “none”

STAT 1350 – Elementary Statistics Semester: AU20 Instructor: S. Hardin Enter data into calculator and run LinReg(a+bx) to answer the following questions.  Input “Weeks on Market” into L1 and “Selling Price” into L2.  Press [STAT], → CALC menu, ↓ 4: LinReg (ax+b) 2. What is the value of the correlation coefficient? ____________ 3. Using your calculator output from LinReg (ax+b), to get the coefficients for the regression line. a = slope = _________ b = y-intercept = _________ 4. Write out the regression equation: _______________________ 5. Using the regression equation, predict the selling price (in thousands of $) for a condo that has been on the market for 35 weeks. 6. Using the regression equation, predict the selling price (in thousands of $) for a condo that has been on the market for 10 weeks. 7. Using the regression equation, predict the selling price (in thousands of $) for a condo that has been on the market for 72 weeks. 8. Find the proportion of variation in selling price that can be explained by its linear relationship with number of weeks on the market. 9. It turns out that the condo that has been on the market for 23 weeks and is selling for $54 thousand is an outlier. To remove this outlier, go back into your lists. Find 23 in L1 and delete it (using the [DEL] button). Then find 54 in L2 and delete it. Now, run LinReg(a+bx) again to recalculate the correlation coefficient. r = _____________ 10. Did the correlation (r) get stronger or weaker when you removed the outlier? Explain.

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