Question

Price $329,744 $259,000 $296,950 219,000 $349,900 $374,900 $314,360 $314,360 $369,900 $395,342 $209,900 $275,000 $309,900 $317,750 $317,750 $279,699 $295,500 $239,900 $374,900 $331,900 $369,900 $463,055 $479,000 $470,000 $389,900 $559,000 roject Calculations art II. Correlation and Regression- Predicting a Listing Price 1. Refer to the sample data previously posted. Use EXCEL to create a scatter plot of price vs. square feet for the sample data. Plot square feet on the x-axis and price on the y- axis 2. Based on the scatter plot, describe the relationship (if any) between square feet and 3. Use EXCEL to calculate the correlation coefficient and explain what it tells you about the 4. Use EXCEL to calculate the least-squares regression line (trend line) for the data. Write 5. Interpret the slope of the least-squares regression line. Specifically what does it tell you 6. Use the equation of the least-squares regression line from #4 to estimate how much you price. relationship between square feet and price. the equation. about the relationship between square feet and price? should charge for your home (which has 2,235 square feet). How does it compare with the price recommended by the real estate agent? Copy Format Painter ニニー-幽Merge IN Clipboard Font Alignment A15 1 Square Feet 2 1550 3 1614 4 1715 5 1758 6 1794 7 1860 8 1877 9 1900 10 1911 11 1921 12 1921 13 2015 14 2118 15 2351 16 1800 17 2083 18 2100 19 2112 20 2112 21 2210 22 2260 Price 329,744 259,000 $295,100 $309,500 $282,900 $296,950 $219,000 $349,900 $374,900 $314,360 $314,360 $369,900 $395,342 $321,900 $209,900 $275,000 $309,900 $317,750 $317,750 $279,699 $295,500 $239,900 $374,900 5331,900 $369,900 23 2400 24 2416 25 2444 26 2600 27 3159 28 3200 29 3200 30 2580 31 3300 32 $479,000 $470,000 $389,900 $559,000 Prices Square Feet and Price O 222233323

Answer 1

Solution: Obtain the scatter plot. EXCEL procedure: Step 1: Write the values of Square Feet and Price in separate column in an EXCEL document Step 2: Select the columns of Sae Feet and Price Step 3: Click on Insert. Select Scatter. Step 4: Click on OK. EXCEL output Price 600000 ,事 300000 200000 500 1000 1500 2000 2500 3500 2. Conclusion

Based on the scatter plot, it can be concluded that there is a positive correlation between the square feet and Price Obtain the correlation coefficient. EXCEL procedure Step1: Write the values of Square Feet and Price in separate column in an EXCEL document. Step 2: Select Data. Click on Data Analysis. Step 3: Click on Correlation. Step 4: Select the columns of Square Feet and Price Step 5: Click on OK. EXCEL output: Column 1 Column 2 Column 1 Column 2 0.785630458 From the EXCEL output, the correlation coefficient between 2 variables is 0.7856, which is positive. Thus, it can be concluded, based on the correlation coefficient that there is a positive and strong correlation between Price and square feet. 4 Obtain the regression line

EXCEL procedure Step1: Write the values of Square Feet and Price in separate column in an EXCEL Step 2: Select Data. Click on Data Analysis Step 3: Click on Regression. Step 4: Select the columns of Square Feet in X range and Price in Y range Step 5: Click on OK. EXCEL output: SUMMARY OUTPUT ression Statistics Multiple R R Square Adjusted R Square Standard Error 0.785630458 0.617215216 0.603544331 49429.68672 30 ANOVA MS 1 11031E 11 1.1031E+11 45.14815317 2.70426E-07 28 68412230010 2443293929 29 1.78722E+11 Residual Tota Coefficients Standard Error 54857.30347 P-value Lower 95% uper 95% Lower 95.0% Upper 95.0% 2977, 78726 1.276410606 0.212296187-33178.70173 142893.3087-33178, 70173 142893.3087 19.01884554 6.719237544 2.70426E-07 88.83380246 166.7504795 88.83380246 166.7504795 t Stat Intercept X Variable 1 127.792141 From the EXCEL output, the regression line is, Price 54857.3035+127.7921Square Feet