Annual high temperatures in a certain location have been tracked for several years. Let X represent theyear and Y the high temperature. Based on the data shown below, calculate the regression line (each valueto two decimal places).y =XLO56789y26.9527.7629.0729.2832.391030.111 34.71X +

XYX.YX2526.95134.7525627.76166.5636729.07203.4949829.28234.2464932.39291.51811030.13011001134.71381.…

Answered: Annual high temperatures in a certain…

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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Use the data in the table below to complete parts (a) through (d). x 37 34 40 46 42 50 62 56 51 y 22 20 25 32 27 30 30 25 28 Find the equation of the regression line. y=
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 522 pounds? Use a significance level of 0.05. Chest size (inches) 58 50 65 59 59 48 D 414 312 499 450 456 260 Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. 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? The best predicted weight for a bear with a chest size of 63 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 522 pounds? O A. This result is not very close to the actual weight of the bear. O B. This result is exactly the same as the actual weight of the bear. O C. This result is close to the actual weight of the…
Annual high temperatures in a certain location have been tracked for several years. Let X represent the year and Y the high temperature. Assume that temperature is independent each year. Based on the data shown below, calculate the regression line (each value to two decimal places). First the slope and then the y-intercept. Y X 3 4 5 67 8 00 a 9 y 10.14 10.85 11.86 11.17 7.58 9.79 7.5 x+
M3
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 150 180 120 130 90 190 P (a)x= 170 calories (c) x 140 calories (b)x= 100 calories (d) x = 210 calories Sodium, y 430 480 350 370 290 530 REED Find the regression equation. ŷ=x+0) (Round to three decimal places as needed.) 4
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 1118 796 1161 918 1103 1219 Temperature (F) 82 72.2 92.2 73 87.5 94.4
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
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