You generate a scatter plot using Excel. You then have Excel plot the trend line and report the equation and the r value. The regression equation is reported as = 49.05 + - 28.13x and the r2 = 0.0361. What is the correlation coefficient for this data set? r =

You generate a scatter plot using Excel. You then have Excel plot the trend line and report the equation and the p2 value. The regression equation is reported as 27.84 + - 74.89x and the r2 = 0.2209. What is the correlation coefficient for this data set? r =

Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as 91.01x + 56.25 and r = 0.544. What proportion of the variation in y can be explained by the linear regression equation found above? % Report answer as a percentage accurate to one decimal place.

Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as Y = 71.95x + 52.94 and the r = - 0.148. - What proportion of the variation in y can be explained by the variation in the values of x? r2 =

Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y = 98.52x + 27.93 and the r = 0.247. What proportion of the variation in y can be explained by the variation in the values of x? r? = % Report answer as a percentage accurate to one decimal place.

Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported asy=29.62x+64.57y=29.62x+64.57and the r=0.784r=0.784.What proportion of the variation in y can be explained by the variation in the values of x? r2 = %Report answer as a percentage accurate to one decimal place.

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Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y=-59.97x+67.54 and the r=-0.31 What percentage of the variation in y can be explained by the variation in the values of x? r2 = % (Report exact answer, and do not enter the % sign) .

You generate a scatter plot using Excel. You then have Excel plot the trend line and report the equation and the r2 value. The regression equation is reported as y = - 61.46x + 41.55 and the r? = 0.16. What is the correlation coefficient for this data set? r =

Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as -36.51x+76.99 and r = -0.437. What proportion of the variation in y can be explained by the linear regression equation found above? % Report answer as a percentage accurate to one decimal place. Submit Question

You generate a scatter plot using Excel. You then have Excel plot the trend line and report the equation and the r2r2 value. The regression equation is reported asy=−38.54x+27.71y=-38.54x+27.71and the r2=0.36r2=0.36.What is the correlation coefficient for this data set?r =

Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y = – 17.88x + 41.39 and the r = - 0.405. What proportion of the variation in y can be explained by the variation in the values of x? r2 = Report answer as a percentage accurate to one decimal place.

Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor (x) variable. Find the best predicted tip for a ride that takes 30 minutes. How does the result compare to the actual tip amount of 4ドル.70? Use a significance level of 0.05. Distance 1.80 12.71 1.32 Time 1.65 8.51 1.40 1.02 2.47 Fare Tip 25.00 27.00 8.00 16.30 36.80 7.80 9.80 31.75 12.30 1.50 0.00 0.00 1.96 2.98 2.46 11.00 31.00 18.00 8.00 18.00 7.80 14.30 2.34 4.29 The regression equation is ŷ =+ (x. (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.)