Can some one explan how to get part B, C, and E right?The data below represent the number of days absent, x, and the final grade, y. for a sample of college students at a large university. Complete parts (a) through (e)belowNo. of absences, x 0 1 2 3 4 5 6 1 89 0Final grade, y882 85 4 824 79.9 76.9 725 63.1 67.4 64.5 61.6(a) Find the least-squares regression line treating the number of absences, x, as the explanatory variable and the final grade, y, as the response variableX.3124 x (88249)(Round to three decimal places as needed)(b) Interpret the slope and y-intercept if appropriateInterpret the slope Select the corect choice belolw and. if necessary. fil in the answer box to complete your choice(Round to three decimal places as needed)L For zero days absent the final score is predicted to beFor a final score of zero. the number of days absent is predicted to bedaysC le d d taThe data below represent the number of days absent, x, and the final grade, y. for a sample of college students at a large university Complete parts (a) threbelowNo. of absences, x 0 1 2 3 4 5 6 7 8 9 0Final grade, y88.2 85.4 82.4 79.9 76.9 72.5 63.1 67.4 64.5 61.6(b) Interpret the slope and y-intercept, if appropriate.Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice(Round to three decimal places as needed)A For zero days absent, the final score is predicted to beOB For a final score of zero, the number of days absent is predicted to be daysOC For every unit change in the final grade, the number of days absent falls by days, on average0. For every day absent, the final grade falls by 3.124, on averageOLt is not appropriate to interpret the slopeInterpret the y-intercept. Select the correct choice below and, if necessary, fill in the answer box to complete your choice.(Round to three decimal places as needed.)OA For a final score of zero, the number of days absent is predicted to be daysB For zero days absent, the final score is predicted to be 88 249XC For every day absent, the final grade falls by. on averageOD For every unit change in the final grade, the number of days absent falls by days, on averageOL Ris not appropriate to interpret the y-intercept(c) Predict the final grade for a student who misses five class periods and compute the residual Is the observed final grade above or below average for thisnumber of absences?The predicted final grade is 726 This observation has a residual of -01, which indicates that the final grade is below average.(Round to one decimal place as needed)(d) Draw the least-squares regression line on the'scatter diagram of the data. Choose the correct graph below(0) Would it be reasonable to use the least-squares regression line to predict the final grade for a student who has missed 15 class periods? Why or why not?A. Yes-15 missed class perlods is possible and within the scope of the modelB. No-15 missed class periods is outside the scope of the model.OC No-15 missed class periods is not possible.OD No-15 missed class perlods is not possible and outside the scope of the modelOE More information regarding the student is necessary to be able to make a decision.

x No. of absent days y final grades x y 0 88.2 1 85.4 2 82.4 3 79.9 4 76.9 5…

Answered: of absences, x mal grade, y 012 3 4 5…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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 43 inches. Is the result close to the actual weight of 237 pounds? Use a significance level of 0.05. Chest_size_(inches) Weight_ (pounds)50 27954 33944 21954 29240 20136 116 Is the result close to the actual weight of 237 pounds? A. This result is close to the actual weight of the bear. B. This result is very close to the actual weight of the bear. C. This result is not very close to the actual weight of the bear. D. This result is exactly the same as the actual weight of the bear.
a) interpret the scatter plot. Give a reasonable estimate for the linear correlation r. b) use technology to find the equation of the least squares regression line describing the relationship between Year (t) and Global Temperature (G). Around to 0.0001. c) Plot the regression line on the scatterplot below. Clearly label three points including (t,G) on the LSRL. d) Clearly interpret the slope, intercept, and R^2 of the linear model on the context of the problem statement. Report with proper units. -slope: -intercept: -R^2: e) use the model to predict the Global Temperature in the year 2030. f) compute and mark the residual for the data point (2016, 14.80 degrees C) circled on the scatterplot. Data attached below
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.7 8.4 6.6 3.9 2.4 2.4 2.2 0.6 yy 14 10.9 9.4 7.5 6 5.8 5.8 4.4 xx = thousands of automatic weaponsyy = murders per 100,000 residents Use excel to determine the equation of the regression line. (Round to 2 decimal places)Determine the regression equation in y = b0 + bx(x) form and write it below. A) How many murders per 100,000 residents can be expected in a state with 10.7 thousand automatic weapons? B) How many murders per 100,000 residents can be expected in a state with 2.1 thousand automatic weapons?
The money raised and spent (both in millions of dollars) by all congressional campaigns for 8 recent 2-year periods are shown in the table. The equation of the regression line is y = 0.942x +27.609. Find the standard error of estimate s, and interpret the result. 793.9 1042.3 957.7 1203.3 450.7 673.7 745.1 778.6 Money raised, x Money spent, y 734.8 1024.2 929.1 1160.6 448.6 697.9 735.7 751.2 Find the standard error of estimate s, and interpret the result. (Round to three decimal places as needed.) How can the standard error of estimate be interpreted? O A. The standard error of estimate of the money raised for a specific amount of money spent is about s, million dollars. O B. The standard error of estimate of the money spent for a specific amount of money raised is about s, million dollars.
- 16. Find the least squares regression line for the points (0, 8), (4, 5), (5, 3), (8,-1), and (10,-2). Round numerical values in your answer to two decimal places. a. y=-1.07x+2.63 b. y=-1.27x+8.36 c. y=-1.07x+8.36 d.y=-1.07x+10.54 c. y=-1.27x+2.63
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 63 inches. Is the result close to the actual weight of 562 pounds? Use a significance level of 0.05. Chest_size_(inches) Weight_ (pounds)58 41450 31265 49959 45059 45648 260 What is the regression equation?^y = ____ + _____ x (round to one decimal place as needed.)What Is the best predicted weight of a bear with a chest size of 63 inches? ^y =____ pounds (round one decimal as needed)Is the result close to the actual weight of 452 pounds?(a) This result is very close to the actual weight of the bear.(b) This result is close to the actual weight of the bear.(c) This result is exactly…
The data show The chest size and weight of several bears find regression equation, letting chest size be the independent variable then find the best predicted weight of a bear with a chest size of 51 inches is the result close to the actual weight of 422 pounds use a significance level of 0.05 Chest size : 45, 50, 43, 43, 52, 52. Weight : 352, 374, 275, 314, 440, 367.
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The table shows the number of goals allowed and the total points earned (2 polnts for a win, and 1 point for an overtme or shootout loss) by 14 lce hockey teams over the course of a season The equation of the regression line is (a) Find the coefficient of determination,, and interpret the result (b) Find the standard error of the estimate, and interpret the resut Goals Allowed, x Points, y -0.560x 218.067 Use he data to answer the folowing questions 217 213 221 229 260 262 277 205 216 20s 217 208 257 246 66 70 105 105 0 83 47106 103 97 9182 91 88 Inco (a) r-O (Round to three decimal places as noeded.)
The data shows a systolic and a diastolic blood pressure of certain patients. Find the linear regression eqation, using the first variable (systolic) as the independent variable. Find the best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140. Use a significance level of x Systolic Diastolic 116 82 124 88 112 72 144 95 138 96 112 76 145 88 124 76 130 90 129 94 1)Find the correlation coefficient. 2)State the appropriate critical r value to use to test the claim that the correlation between systolic blood pressure and diastolic blood pressure is significantly different from 0 3)The correlation between diastolic blood pressure and systolic blood pressure is: significant, not significant, weak, none 4)The best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140 is closest to 1pts
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