11.4 The following data ware colloctod to dotarmine the rolationship botwoon pressure and the correspond- ing scale reading for the purposo of calibration. Pressuro, z (lb/sq In.) Salo Randing, y 10 13 10 10 10 10 50 18 16 15 20 86 90 50 50 50 50 88 88 92 (a) Find the equation of the regression line.
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4The 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.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 accuracy
- Following is a portion of the computer output for a regression analysis relating y = maintenance expense (dollars per month) to x = usage (hours per week) of a particular brand of computer terminal. The regression equation is Y = 6.1092 + .8951 X Predictor Coef SE Coef Constant 6.1092 0.9361 X 0.8951 0.1490 Analysis of Variance SOURCE DF SS MS Regression 1 1575.76 1575.76 Residual Error 8 349.14 43.64 Total 9 1924.90 Complete the estimated regression equation (to 4 decimals). = + x Use a t test to determine whether monthly maintenance expense is related to usage at the .05 level of significance.Compute the value of the t test statistic (to 2 decimals). What is the p-value? Use Table 1 of Appendix B.Selectless than .01between .01 and .02between .02 and .05between .05 and .10between .10 and .20between .20 and .40greater than .40Item 4 What is your conclusion?SelectConclude that monthly maintenance expense is related to usageCannot conclude that…Following is a portion of the computer output for a regression analysis relating y = maintenance expense (dollars per month) to x = usage (hours per week) of a particular brand of computer terminal. The regression equation is Y = 6.1092 + .8951 X Predictor Coef SE Coef Constant 6.1092 0.9361 X 0.8951 0.1490 Analysis of Variance SOURCE DF SS MS Regression 1 1575.76 1575.76 Residual Error 8 349.14 43.64 Total 9 1924.90 Complete the estimated regression equation (to 4 decimals). = + x Use a t test to determine whether monthly maintenance expense is related to usage at the .05 level of significance.Compute the value of the t test statistic (to 2 decimals).What is the p-value? Use Table 1 of Appendix B.Selectless than .01between .01 and .02between .02 and .05between .05 and .10between .10 and .20between .20 and .40greater than .40Item 4What is your conclusion?SelectConclude that monthly maintenance expense is related to usageCannot conclude that…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.)
- The following table shows the annual expenditures, in dollars, per customer unit for residential landline phone services and cellular phone services in the United States in the given year.† Year Landline Cell 2004 592 378 2006 542 524 2008 467 643 2010 401 760 Calculate the regression line for each type of service. (Let t be the time in years since 2004, L be the operating revenue of landline phone services and C be the expenditure of cellular services. Round your regression parameters to two decimal places.) L(t) = C(t) = Determine the expenditure level at which the two lines cross. Round your answer for the expenditure level to one decimal place. million dollarsWhich of the following best describes a regression coefficient in a bivariate setting? a. The change in Y predicted by a unit change in X b. The slope of a line that minimizes the sum of squared residuals c. The correlation coefficient multiplied by SDy/SDx d. All of the aboveConsider the following data set. x 1 2 3 4 5 y 2.2 2 1.9 1.6 1.1 Find the equation of the regression line. (Round the values to two decimal places.) y =
- The results of a sample of 7 data points are presented below in terms of the Average Daily Temperature (oF) and the Average Monthly Precipitation (inches): Average Daily temperature x 86 81 83 89 80 74 64 Average Monthly Precipitation y 3.4 1.8 3.5 3.6 3.7 1.5 0.2 d- Determine the regression line equation e- Plot the regression line on the scatter plot (on same graph) f- Calculate the standard error of estimate g- Find the 95% prediction interval for the 95oF average daily temperatureRun a regression analysis on the following data set, where yyis the final grade in a math class and xxis the average number of hours the student spent working on math each week. hours/weekxGradey445.6548661.4107710771284.81376.21699.41910020100 State the regression equation y=m⋅x+by=m⋅x+b, with constants accurate to two decimal places. What is the predicted value for the final grade when a student spends an average of 15 hours each week on math? Grade = Round to 1 decimal place.Consider the following computer output from a multiple regression analysis relating the price of a used car to the variables: age of car, mileage, and safety rating. Coefficients Coefficients Standard Error t� Stat P-value Intercept 38356.1138356.11 4686.294686.29 8.1858.185 0.00000.0000 Age (Year) −18219.29−18219.29 2196.312196.31 −8.295−8.295 0.00000.0000 Mileage(in Thousands) 1149.561149.56 1897.651897.65 0.6060.606 0.54720.5472 Safety Rating 1396.751396.75 159.64159.64 8.7498.749 0.00000.0000 Does the sign of the coefficient for the variable mileage make sense?
