Use Equations (3.5) and (3.6) to estimate the coefficients of the line y = ax + b such that the sumof the squared deviations between the line and the following data points is minimized.а. х1.02.33.74.26.17.0y3.63.03.25.15.36.8b. х29.148.272.792.0118140165y0.04930.08210.1230.1540.1970.2340.274с. х2.53.03.54.04.55.05.5у4.324.835.275.746.266.797.23For each problem, compute D and dmax to bound cmax. Compare the results to your solutions toProblem 2 in Section 3.2.For each problem, compute D and dmax to bound cmax. Compare the results to your solutions toProblem 2 in Section 3.2.REFERENCE:m Σy-Σx Σνm Σή - (Σx):a =the slope(3.5)b =the intercept(3.6)mΣή - (Σx):

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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Problem 1P

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The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x 11.8 8.2 6.8 3.5 2.8 2.8 2.3 0.5 y 13.9 10.8 10.1 7.2 6.5 6.5 6.3 4.8 x = thousands of automatic weapons y = murders per 100,000 residents This data can be modeled by the equation y = 0.81x + 4.35. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. A) How many murders per 100,000 residents can be expected in a state with 7 thousand automatic weapons? Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 7.8 thousand automatic weapons? Answer = Answer = Round to 3 decimal places.
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 40inches. Is the result close to the actual weight of 352pounds? Use a significance level of 0.05.a. Chest size (inches) 41 54 44 55 39 51 Weight (pounds) 328 528 418 580 296 503 a.What is the regression equation? b. The best predicted weight for a bear with a chest size of 39 inches is _______pounds.
Describe the explained variation about a regression line in words and in symbols. y x (xi, Yj). (,))) (x₁, y) y = y D Choose the correct answer below. O A. The explained variation is the sum of the squares of the differences between the predicted y-values and the mean of the y-values of the ordered pairs. B. The explained variation is the sum of the squares of the differences between the y-values of each ordered pair and the mean of the y-values of the ordered pairs. C. The explained variation is the sum of the squares of the differences between the observed y-values and the predicted y-values.
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 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x 11.8 8.2 6.9 3.9 2.3 2.4 2.6 0.6 y 14.2 11.2 10.2 7.5 5.9 6.4 6 4.3 x = thousands of automatic weaponsy = murders per 100,000 residents This data can be modeled by the equation y=0.88x+3.95. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. A) How many murders per 100,000 residents can be expected in a state with 7.2 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 1.6 thousand automatic weapons? Answer = Round to 3 decimal places.
The point (9.1,71) is a point on the scatterplot. Draw the graph of the regression line on the scatterplot on the back of this paper using the y-intercept and the point(I = 3,y = 191). Indicate the residual for z = 9.1 by drawing the vertical line between(9.1, 71) and the corresponding point on the regression line. Will the residual be a positive or negative value?(f) Find the value of the residual for x = 9.1.
The following table shows the mean weight in kilograms of members of a group of young children of various ages. Age (x years) 1.6 2.5 3.3 4.4 5.6 Weight ( y kg) 12 15 16 17 20 The relationship between the variables is modeled by the regression line with equation y=ax+by=ax+b a. Find the value of intercept and the slope
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The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. Xx Y 11.8 14.1 11.5 9.8 7.1 6.2 6.5 x = thousands of automatic weapons y = murders per 100,000 residents 8.6 7 3.3 2.5 2.5 2.6 6 This data can be modeled by the equation y = 0.85x +4.07. Use this equation to answer the following; Answer decimal places. = A) How many murders per 100,000 residents can be expected in a state with 1.2 thousand automatic weapons? Answer = decimal places. Round to 3 0.9 4.7 B) How many murders per 100,000 residents can be expected in a state with 8.5 thousand automatic weapons? Round to 3
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 58 inches. Is the result close to the actual weight of 662 pounds? Use a significance level of 0.05. Chest size (Inches) 46 57 53 41 40 40 Weight (Pounds) 384 580 542 358 306 320
Which of the following is the most appropriate equation to model the data? ŷ = 1.1x + 1.467 ŷ = 1.467x + 1.1 ŷ = 1.1(1.467)x ŷ = 1.467(1.1)x
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Use Equations (3.5) and (3.6) to estimate the coefficients of the line y = ax + b such that the sum of the squared deviations between the line and the following data points is minimized. a. x 1.0 2.3 3.7 4.2 6.1 7.0 y 3.6 3.0 3.2 5.1 5.3 6.8