Heights (in centimeters) and weights (in kilograms) of 7 supermodels are given below. Find the regression equation, letting the firstvariable be the independent (x) variable, and predict the weight of a supermodel who is 167 cm tall.Height 176 168 172 174 166 178 176Weight54 505255 47 57 55The regression equation is ŷ=+x. The best predicted weight of a supermodel who is 167 cm tall is

The objective of this question is to find the regression equation using the given heights and…

Answered: Heights (in centimeters) and weights…

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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Heights (in centimeters) and weights (in kilograms) of 7 supermodels are given below. Find the regression equation, letting the first variable be the independent (x) variable, and predict the weight of a supermodel who is 167 cm tall. Height Weight 176 168 172 174 166 178 176 54 50 52 55 47 57 55 The regression equation is ŷ: _ -57.14 0.64 x. The best predicted weight of a supermodel who is 167 cm tall is 49.58
Write a multiple regression equation that can be used to analyze the data for a two-factorialdesign with two levels for factor A and three levels for factor B. Define all variables.
The accompanying data are the length (in centimeters) and girths (in centimeters) of 12 harbor seals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. Length, x Girth, y 136 105 168 131 151 117 144 106 160 126 159 119 123 102 138 103 156 120 147 111 148 106 147 109 The equation of the regression line is ŷ = ______ x + ______ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) (a) x = 140 cm, (b) x = 172 cm, (c) x = 164 cm, (d) x = 158 cm Use the regression equation to predict…
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 41 inches, Is the result close to the actual weight of 273 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 40 53 38 43 44 58 227 360 153 206 234 414 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.)
Scenario: A medical researcher wishes to see whether there is a relationship between a person's age, cholesterol level, and systolic blood pressure. Eight people are randomly selected. The data is listed in the table. First, find the multiple regression equation. Next, determine the coefficient of determination. Then, use the regression equation to predict a person's blood pressure reading if the person selected is 50 years old with a cholesterol reading of 220. Age Cholesterol level Blood pressure Person 1 38 220 116 Person 2 41 225 120 Person 3 45 200 123 Person 4 48 190 131 Person 5 51 250 142 Person 6 53 215 145 Person 7 57 200 148 Person 8 61 170 150 Discussion Prompts Respond to the following prompts in your initial post: 1. Identify the explanatory variables and response variable for the data. 2. What is the multiple regression equation for the data? 3. What is the coefficient of determination? 4. If a person 50 years old with a cholesterol of 220 is selected, what is that…
The number of megapixels in a digital camera is one of the most important factors in determining picture quality. But, do digital cameras with more megapixels cost more? The following data show the number of megapixels and the price ($) for 10 digital cameras(Consumer Reports, March 2009). Use these data to develop an estimated regression equation that can be used to predict the price of a digital camera given the number of megapixels. Brand and Model Megapixels Price (S) Canon PowerShot SD1100 IS Casio Exilim Card EX-510 8 180 200 230 10 Sony Cyber-shot DSC-T70 Pentax Optio M50 Canon PowerShot G10 120 470 15 8 Canon PowerShot A590 IS Canon PowerShot El 140 180 10 12 Fujifilm FinePix FOOFD Sony Cyber-shot DSC-W170 Canon PowerShot A470 310 10 250 110
Heights (in centimeters) and weights (in kilograms) of 7 supermodels are given below. Find the regression equation, letting the first variable be the independent (x) variable, and predict the weight of a supermodel who is 167 cm tall. \begin{array}{c|ccccccc} \mbox{Height} & 178 & 176 & 166 & 178 & 174 & 172 & 174 \cr \hline \mbox{Weight} & 58 & 54 & 47 & 57 & 55 & 53 & 54 \cr \end{array} The regression equation is \hat{y} = + x . The best predicted weight of a supermodel who is 167 cm tall is .
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed actress/actor ages in various years, find the best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 27 years. Is the result within 5 years of the actual Best Actor winner, whose age was 44 years? Best Actress 27 32 28 64 33 33 43 30 63 21 42 56 모 Best Actor 44 38 39 44 48 47 63 48 41 58 43 31 Find the equation of the regression line. (Round the constant to one decimal place as needed. Round the coefficient to three decimal places as needed.) The best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 27 years is years old. (Round to the nearest whole number as needed.) Is the result within 5 years of the actual Best Actor winner, whose age was 44 years? the predicted age is the actual winner's age.
The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1x. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 69 57 73 90 90 75 66 90 76 77 Grades on Final 84 74 72 98 76 72 60 75 76 60
The table shows the number of goals allowed and the total points earned (2 points for a win, and 1 point for an overtime or shootout loss) by 14 ice hockey teams over the course of a season. The equation of the regression line is ŷ= -0.556x+217.766. Use the data to answer the following questions. (a) Find the coefficient of determination, 12, and interpret the result. (b) Find the standard error of the estimate, Se, and interpret the result. 213 213 223 226 259 266 281 202 210 205 226 207 259 239 D Goals Allowed, x Points, y 109 109 102 91 88 80 52 105 107 98 95 85 68 66 (a)² = (Round to three decimal places as needed.) Interpret the coefficient of determination. Select the correct choice below and fill in the answer box to complete your choice. (Round to one decimal place as needed.) OA. About OB. About (b) Se = % of the variation in points earned can be explained by the relationship between number of goals allowed and points earned. The remaining variation is unexplained. % of the…
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years, construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $888 the equation of the regression line is y= 1.453x-47.386. Wages(state), X | 739|760|784|822|898|921|937|954|965| Wages (federal), Y |1,036|1,054|1,105|1,136|1,192|1,253|1,266|1,327|1,400|
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.)

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