Bivariate data for the quantitative variables x and y are given in the table below. These data are plotted in the scatter plot shown next to the table. In the scatter plot, sketch an approximation of the least-squares regression line for the data. 7.5 8.8 11+ 2.9 1.8 10- 3.4 3.4 5.7 4.7 9+ 3.2 2.9 4.0 1.7 4.4 3.5 5.2 3.6 6.8 6.5 5+ 8.5 9.5 4.5 4.4 4+ 5.8 7.3 3+ 6.7 6.9 8.1 9.6 2+ 7.5 7.6 1+ 5.6 6.4 8.7 9.8 2. 9. 10 11 6.4 5.2

Is It Getting Harder to Win a Hot Dog Eating Contest?Every Fourth of July, Nathan’s Famous in New York City holds a hot dog eating contest. The table below shows the winning number of hot dogs and buns eaten every year from 2002 to 2015, and the data are also available in HotDogs. The figure below shows the scatterplot with the regression line. Year     Hot Dogs 2015   62 2014   61 2013   69 2012   68 2011   62 2010   54 2009   68 2008   59 2007   66 2006   54 2005   49 2004   54 2003   45 2002     50 Winning number of hot dogs in the hot dog eating contest Winning number of hot dogs and buns Click here for the dataset associated with this question.   (a) Is the trend in the data mostly positive or negative?     Positive   Negative   (b) Using the figure provided, is the residual larger in 2007 or 2008?Choose the answer from the menu in accordance to item (b) of the question statement  20072008 Is the residual positive or…

In baseball, two statistics, the ERA (Earned Run Average) and the WHIP (Walks and Hits per Inning Pitched), are used to measure the quality of pitchers. For both measures, smaller values indicate higher quality. The following computer output gives the results from predicting ERA by using WHIP in a least-squares regression for the 2017 baseball season. Variable DF Estimate SE T Intercept 1 -5.0 0.26 - 19.3 WHIP 1 6.8 0.14 47.4 Which of the following statements is the best interpretation of the value 6.8 shown in the output? ERA is predicted to increase by 6.8 units for each 1 unit increase of WHIP. WHIP is predicted to increase by 6.8 units for each 1 unit increase of ERA. For a pitcher with 0 units of WHIP, the ERA is predicted to be approximately 6.8 units. For a pitcher with 0 units of ERA, the WHIP is predicted to be approximately 6.8 units. Approximately 6.8% of the variability in ERA is due to its linear relationship with WHIP.

The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)