3.1 1.6 1.1 1.4 2.3 3.6 2.6 3.5 3.3 3.8 3.6 1.9 1.3 1.1 2.6 2.7 3.8 1.5 3.8 3.7 etermine the least squares regression line for the data. Round values to four decima
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- (Handwriting neat and clear thank you)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…Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 11 9 12 8 11 13 4 13 6. 6 У 7.25 7 12.94 7.22 8.15 9.27 6.33 5.3 8.52 6.14 5.46 Create a scatterplot of the data. Choose the correct graph below. O B. OC. O D. O A. Ay 25- Ay 25- 25- 25- 20- 20 20- 20 15 15 15 15 10 10 10- 10 5- 5- 5- 5- 0- 05 10 15 20 25 05 10 15 20 25 0- 05 10 15 20 25 0 5 10 15 20 25 Find the equation of the regression line. (Round the constant two decimal places as needed. Round the coefficient to three decimal places as needed.) Identify a characteristic of the data that is ignored by the regression line. O A. There is no trend in the data. O B. The data has a pattern that is not a straight line. C. There is an influential point that strongly affects the graph of the regression line. D. There is no characteristic of the data that is ignored by the regression line. Click to select your answer(s).…
- R3.4 Stats teachers' cars A random sample of AP Statistics teachers was asked to report the age (in years) and mile- age of their primary vehicles. A scatterplot of the data, a least-squares regression printout, and a residual plot are provided below. R squared - 82.0% R squared (adjusted) -81.1% -19280 with 21 -2-19 degrees of freedom Variable Constant Carage Coefficient 7288.54 11630.6 se. of Coeff bratio prob LII 931 0.2826 6591 1249 0.0001 200 25 se 75 e.0 25 se 75 se.e CrgeA scatter plot shows the relationship between two quantitative variables. Each of the six scatter plots pictured shows the least-squares regression line for the corresponding data set. Classify each scatter plot according to whether the least-squares regression line has a meaningful ?y-intercept value.The data below represents commute times (in minutes) and scores on a well-being survey. Complete parts (a) through (d) below. Commute time (in minutes), x 5, 20, 25, 40, 60, 84, 105 Well-being index score, y 69.1, 67.8, 67.1, 66.3, 66.0, 64.3, 62.3 Find the least-squares regression line treating the commute time, x, as the explanatory variable and the index score, y, as the response variable. y=___x + ____ (round to three decimal places as needed).
- Bookstore sales revisited Recall the data we saw inChapter 6, Exercise 3 for a bookstore. The manager wantsto predict Sales from Number of Sales People Working. Number of SalesPeople Working Sales (in $1000)2 103 117 139 1410 1810 2012 2015 2216 2220 26 Dependent variable is SalesR-squared = 93.2,s = 1.477 Variable CoefficientIntercept 8.1006Num_Workers 0.9134 a) Write the regression equation. Define the variablesused in your equation.b) What does the slope mean in this context?c) What does the y-intercept mean in this context? Is itmeaningful?d) If 18 people are working, what Sales do you predict?e) If sales for the 18 people are actually $25,000, what isthe value of the residual?f) Have we overestimated or underestimated the sales?A simple regression model for 10 pair of data resulted in a standard error of 3.95 (i.e., Se = 3.95), and the. The sum of squares of error (SSE) is ______. a. 187.23 b. 171.63 c. 156.03 d. 140.42 e. 124.82Ch. 21 part 2 Run a regression analysis on the following bivariate set of data with y as the response variable. x y 43.8 54.1 41.3 51.2 35.3 60.1 48.1 44.9 42.8 51.8 44.7 50.8 39.4 56.6 38.2 56.6 40.7 53.5 45.3 51.1 45 46.7 41.1 52.2 Predict what value (on average) for the response variable will be obtained from a value of 40.1 as the explanatory variable. Use a significance level of α=0.05 to assess the strength of the linear correlation.What is the predicted response value? (Report answer accurate to one decimal place.)y = ________________
- Answer questions A_C show workHow much of the variation in average annual energy expenditures is explained by the least-squares regression line? Round the answer to at least one decimal place.Data for 50 U.S. “states" was used to examine the relationship between violent crime rate (violent crimes per 100,000 persons per year) and the independent variables of urbanization (percentage of the population living in urban areas) and poverty rate. 50 observations were examined. The Excel sheet output for the analysis of this data is shown in the Figure (with some information intentionally left blank). SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.69 Standard Error 8.54 Observations 50 ANOVA df SS MS Significance F Regression 2060 54.9 0.000 Residual 47 18.77 Total 2942 Coefficients Standard Error t Stat P-value B0 B1 B2 31.9 148.2 -2.17 0.035 -4.6 1.654 2.83 0.007 39.3 13.52 2.91 0.006