racing bikes. Brand Weight Price ($) A 17.8 2,100 B 16.1 6,350 14.9 8,370 15.9 6,200 17.2 4,000 F 13.1 8,600 16.2 6,000 H 17.1 2,680 17.6 3,400 14.1 8,000 ese data provided the estimated regression equation ý = 28,506 - 1,433x. For these data, SSE = 7,009,621.71 and SST = 51,682,800. Use the F test to determine whether the weight for a bike and the price are related at the 0.05 level of significa te the null and alternative hypotheses. O Hoi Bq = 0 H: B, = 0 O Hoi Bo = 0 H: Bo = 0 H: Bo = 0 Hi Bq < 0 d the value of the test statistic. (Round your answer to two decimal places.)
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- For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracyFor the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.For the following exercises, consider the data in Table 5, which shows the percent of unemployed ina city of people 25 years or older who are college graduates is given below, by year. 40. Based on the set of data given in Table 6, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient to three decimal places.
- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.Given below are results from the regression analysis where the dependent variable is the number of weeks a worker is unemployed due to a layoff (Unemploy) and the independent variables are the age of the worker (Age), the number of years of education received (Edu), the number of years at the previous job (Job Yr), a dummy variable for marital status (Married: 1=married, 0=otherwise), a dummy variable for head of household (Head: 1=yes, 0=no) and a dummy variable for management position (Manager: 1=yes, 0=no). We shall call this Model 1. The coefficient of partial determination (R2Yj.(All variables except j)) of each of the six predictors are, respectively, 0.2807, 0.0386, 0.0317, 0.0141, 0.0958, and 0.1201. Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are Age and Manager. The results of the regression analysis are given. Refer to model 1. Which of the following is the correct null hypothesis to test…A study of the amount of rainfall and the quantity of air pollution removed produced the following data shown in table below: Daily Rainfall x (0.01 cm) Particulate Removed y (μg/m3) 7 126 7.9 129.3 7.5 125.3 9.2 120.2 10.8 116.7 5.8 119.2 5.6 138.7 2.7 147.5 9.2 110.3 Compute and interpret the coefficient of determination, and coefficient of correlation for the given data. What will be the regression equation, when swapped depended and independent variable
- The following scores represent a nurse’s assessment (X) and a physician’s assessment (Y) of the condition of 10 patients at time of admission to a trauma centre: X: 18 13 18 15 10 12 8 4 7 3 Y: 23 20 18 16 14 11 10 7 6 4 a) Obtain the regression equation. b) What is the predicted physician’s assessment for a nurse’s assessment of; 16 scores? 21 scores? c) Distinguish between extrapolation and interpolationThe regional transit authority for a major metropolitan area wants to determine whetherthere is a relationship between the age of a bus and the annual maintenance cost. A sampleof ten buses resulted in the following data: a. Develop a scatter chart for these data. What does the scatter chart indicate about therelationship between age of a bus and the annual maintenance cost?b. Use the data to develop an estimated regression equation that could be used to predictthe annual maintenance cost given the age of the bus. What is the estimated regressionmodel?c. Test whether each of the regression parameters b0 and b1 is equal to zero at a 0.05level of significance. What are the correct interpretations of the estimated regressionparameters? Are these interpretations reasonable?d. How much of the variation in the sample values of annual maintenance cost does themodel you estimated in part b explain?e. What do you predict the annual maintenance cost to be for a 3.5-year-old bus?The personnel director of a large hospital is interested in determining the relationship (if any) between an employee’s age and the number of sick days the employee takes per year. The director randomly selects ten employees and records their age and the number of sick days which they took in the previous year. Employee 1 2 3 4 5 6 7 8 9 10Age 30 50 40 55 30 28 60 25 30 45Sick Days 7 4 3 2 9 10 0 8 5 2 The estimated regression equation and the standard error are given. Sick Days=14.310162−0.236900(Age) Se=1.682207 Find the 95% prediction interval for the average number of sick days an employee will take per year, given the employee is 34 . Round your answer to two decimal places.
- Consider the following data on x = weight (pounds) and y = price ($) for 10 road-racing bikes. These data provided the estimated regression equation ŷ = 28,240 − 1,419x. For these data, SSE = 7,209,342.96 and SST = 50,969,800. Use the F test to determine whether the weight for a bike and the price are related at the 0.05 level of significance. -Find the value of the test statistic. (Round your answer to two decimal places.)You may need to use the appropriate technology to answer this question. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume(units) Total Cost($) 400 3,900 450 4,900 550 5,500 600 5,900 700 6,400 750 7,100 This data was used to develop an estimated regression equation, ŷ = 970.67 + 8.08x, relating production volume and cost for a particular manufacturing operation. Use ? = 0.05 to test whether the production volume is significantly related to the total cost. (Use the F test.) State the null and alternative hypotheses. H0: ?1 = 0Ha: ?1 ≠ 0H0: ?1 ≥ 0Ha: ?1 < 0 H0: ?0 ≠ 0Ha: ?0 = 0H0: ?1 ≠ 0Ha: ?1 = 0H0: ?0 = 0Ha: ?0 ≠ 0 Set up the ANOVA table. (Round your p-value to three decimal places and all other values to two decimal places.) Sourceof Variation Sumof Squares Degreesof Freedom MeanSquare F p-value Regression Error Total Find the value of the test…The manager of the Bayville police department motor pool wants to develop a forecast model for annual maintenance on police cars, based on mileage in the past year and age of the cars. The following data have been collected for eight different cars: a. Using Excel, develop a multiple regression equation for these data. b. What is the coefficient of determination for this regression equation? c. Forecast the annual maintenance cost for a police car that is 5 years old and will be driven 10,000 miles in 1 year.