Hi Please review my homework for errors, please look carefully

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2. You will perform a regression analysis of the data within the provided attachment. The following items must be provided within this analysis:

• Identify the independent and dependent variable.
• Create a scatterplot and perform a trendline analysis in Excel. This analysis will provide you with your regression equation and coefficient of determination. Upload this Excel file containing these results to your main discussion post. Go to You Tube and perform a search on terms that include your version of Excel, create scatterplot, and trendline to access hundreds of video tutorials. Choose the tutorial that matches your version Excel.
• State your regression equation in terms of your independent and dependent variable. Interpret what the slope and y-intercept represent within the context of this application.
• State and interpret your coefficient of determination within the context of this application.
• If you take the square root of your coefficient of determination, you will obtain the correlation coefficient. Determine the correlation coefficient and interpret it within the context of this application.

3. Reply to at least TWO other student posts in a mathematically substantive way to contribute to this week's discussion.

Team Name Team Code Revenue ($mil) Current Value ($mil) Atlanta Hawks ATL 105 295 Boston Celtics BOS 151 452 Charlotte Bobcats CHA 98 281 Chicago Bulls CHI 169 511 Cleveland Cavaliers CLE 161 355 Dallas Mavericks DAL 146 438 Denver Nuggets DEN 113 316 Detroit Pistons DET 147 360 Golden State Warriors GSW 119 363 Houston Rockets HOU 153 443 Indiana Pacers IND 95 269 Los Angeles Clippers LAC 102 305 Los Angeles Lakers LAL 214 643 Memphis Grizzlies MEM 92 266 Miami Heat MIA 124 425 Milwaukee Bucks MIL 92 258 Minnesota Timberwolves MIN 95 264 New Jersey Nets NJN 89 312 New Orleans Hornets NOH 100 280 New York Knicks NYK 226 655 Oklahoma City Thunder OKC 118 329 Orlando Magic ORL 108 385 Philadelphia 76ers PHI 110 330 Phoenix Suns PHX 147 411 Portland Trail Blazers POR 127 356 Sacramento Kings SAC 103 293 San Antonio Spurs SAS 135 404 Toronto Raptors TOR 138 399 Utah Jazz UTA 121 343 Washington Wizards WAS 107 3224)R-squared is the statistical measure of how close the data are to the fitted regression line. R- Scatterplot and perform a trendline analysis in Excel squared=0.889 (88.9%). Meaning 88.9% of the data fit the regression line. Usually, a higher coefficient indicates a better Scatter Plot of Revenue and Value for NBA Teams fit for the model. 700 y = 2.7684x + 17.647 R = 0.889 600 5) Correlation coefficient R=(0.889) 0.5=0.943 The correlation coefficient determines the relationship between the dependent and independent 500 variables. Value of R close to +1 indicates a perfectly positive correlation, and R =-1 shows a perfectly 400 negative correlation. Value ($millions) 300 200 100 0 50 100 150 200 250 Revenues ($millions) 1) Independent Variable (x)-Revenue Dependent variable (y)-Current value, Because the current On-Screen Keyboard value will be dependent on the past revenues, it will be a dependent variable and represented on Lac 9 0 - Home PgUp the y axis. In contrast, revenue will be independent of the current value and described on the x- Tab Del End PgDn axis. Caps Enter Insert Pause Shift Shift PrtSon ScrLk Do Fn Ctr Alt Alt Ctr choose y as dependent variable and x as 8 124.9132 -5.91325 -0.51331 25.86207 102 9 150.6446 2.35536 0.204459 29.31034 103 independent variable > click on residual plot > normal probability plot 10 94.67886 0.321139 0.027877 32.75862 107 11 106.258 -4.25799 -0.36962 36.2069 108 12 214.9731 -0.97312 -0.08447 39.65517 110 The independent and dependent variable. 13 93.71393 - -1.71393 -0.14878 43.10345 113 14 144.8551 -20.8551 - 1 -1.81035 46.55172 118 15 91.14079 0.859206 0.074584 50 119 D G H 1 16 93.07065 1.929351 0.167479 53.44828 121 SUMMARY OUTPUT 17 108.5095 -19.5095 -1.69354 56.89655 124 2 3 Regression Statistics 18 98.21693 1.783073 0.154781 60.34483 127 4 Multiple P 0.941642955 63.7931 135 5 R Square 0.886691454 19 218.8328 7.167169 0.622153 6 Adjusted R Square 0.882333433 20 113.9774 4.022594 0.349185 67.24138 138 7 Standard Error 11.91719996 21 131.9894 -23.9894 -2.08242 70.68966 146 8 Observations 9 22 114.299 -4.29905 -0.37318 74.13793 147 10 ANOVA 23 140.3521 6.647917 0.577079 77.58621 147 11 of SS MS Significance F 12 Regression 28895.59611 28895.59611 203.4619512 8.31467E-14 24 122.6618 4.338249 0.376586 81.03448 151 13 Residual 26 3692.511029 142.019655 27 25 102.3983 0.601721 0.052233 84.48276 153 14 Total 32588.10714 15 26 138.1006 -3.10059 -0.26915 87.93103 161 16 Coefficients Standard Error t Stat P-value Lower 95% Upper 9576 ower 95.09pper 95.0%% 27 136.4924 1.507626 0.130871 91.37931 169 17 Intercept 8.646495952 8.687008117 0.995336465 0.32874635 -9.209904966 26.50289687 -9.2099 26.5029 18 295 0.320782894 0.022488972 14.26400895 8.314678-14 0.274556151 0.367009638 0.274556 0.36701 28 118.4804 2.519601 0.218717 94.82759 214 19 29 111.7259 -4.72591 -0.41024 98.27586 226 20