3. Size of your brain. Use the data to complete and answer the following questions.BrainVolume(cm³)1005963103510271281127210511079103410701173107910671104134714391029110012041160IQscore9689878710110310396127126101969388948597114113124a. Regression equation:b. Correlation coefficient, r =c. Conclusion about correlation relationship?d. r² =e. Explained variation?f. Predict the IQ score of a person whose brainvolume is 1250 cm³:g. Predict the IQ score of a person whose brainvolume is 1400 cm³:h. Sketch the scatter graph.

The data values are shown below:Brain volumeIQ…

Answered: 3. Size of your brain. Use the data to…

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 following are the intelligence quotients (IQ) and the grade point average (GPA) of incoming Grade 12 students. If a significant relationship exists between the variables, perform a regression analysis. What GPA will students A and B obtain if their IQs are 159 and 92, respectively? Support your answer with computations/tables and draw the corresponding scatter diagram. Student IQ GPA 1 153 94 120 87 108 89 135 93 97 85 110 86 155 95 126 88 122 86 10 94 84 23455 6 7 8 9은
Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r=0.926
Draw the weights and heights scatter diagram of your data by using EXCEL and give your interpretation. Find the equation of the regression line from the following data
Weight (lbs.) 173 184 194 214 168 220 188 188 207 167 217 Systolic Blood Pressure 132 143 153 162 154 168 137 149 159 128 1 1. The sample correlation coefficient is _____________
Can movie rental revenue be predicted? A movie studio wishes to determine the relationship between the revenue from rental of comedies on streaming services and the revenue generated from the theatrical release of such movies. The studio has the following bivariate data from a sample of fifteen comedies released over the past five years. These data give the revenue x from theatrical release (in millions of dollars) and the revenue y from streaming service rentals (in millions of dollars) for each of the fifteen movies. Also shown are the scatter plot and the least-squares regression line for the data. The equation for this line is ŷ=3.38+0.15x. Theater revenue, x (in millions of dollars) Rental revenue, y (in millions of dollars) 21.0 5.5 60.9 10.0 61.0 16.0 27.5 3.1 36.7 12.7 30.6 5.7 14.8 2.0 49.6 15.7 13.1 10.2 25.9 8.9 44.1 6.5 66.9 9.5 27.5 11.8 24.9 7.9 6.9 1.5 Send data to calculator Send data to Excel Rental revenue (in millions of dollars) 18- 16+ x 14 12 10+ x 50 60 70…
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 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
Triples and Home Runs The data below show the number of three-base hits (triples) and the number of home runs hit during the season by a random sample of MLB teams. Triples 33, 37, 27, 29, 18, 21 Home runs 305, 345, 245, 265, 155, 185 The correlation coefficient for the data is r= 1 and a=.01. Should regression analysis be done? The regression analysis should not be done or The regression analysis should be done. Find the equation of the regression line. Round the coefficients to at least three decimal places, if necessary y'= a+bx a= b= find y' when x= 28. Round the answer to at least three decimal places, if necessary y'=
Let x be the weight of a car (in hundreds of pounds), and let y be the miles per gallon (mpg). Suppose a car weighs 3800 pounds. What does the data forecast for the miles per gallon expected? x= 27 44 32 47 23 40 34 52 y= 30 19 24 13 29 17 21 14 State the correlation coefficient and state the regression lin equation.
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $140 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 39 22 118 67 77 49 124 66 12 64 128 19 6. 147 9. 118 6. 99 75 127 107 95 99 64 109 209 44 8 293 48 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y =+x. (Round to one decimal place as needed.)
A physician wishes to know whether there is a relationship between a father’s weight (in pounds) and his new born sons’ weight (in pounds). The data are given here Fathers Weight 176 145 187 210 196 142 205 215 152 145 Sons Weight 6.6 8.2 9.2 7.1 8.8 9.3 7.1 8.6 7.8 6.0 Develop the regression equation for the sample Predict the sons weight based on the father’s weight of 300, 250 and 400.
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $135 million. Use a significance level of alpha equals 0.05 . Budget left parenthesis $ right parenthesis in Millions 45 24 115 74 72 48 117 67 4 60 124 24 6 152 8 Gross left parenthesis $ right parenthesis in Millions 115 10 95 69 127 112 93 101 50 102 223 26 18 282 56 The regression equation is ŷ = __ + __x. (Round to one decimal place as needed.)
The paired data below consists of heights and weights of 6 randomly selected adults. Find the linear correlation coefficient, the linear regression line, and predict the weight of a randomly selected person who is 1.69 meters tall. X Height (meters) 1.61 1.72 1.78 1.80 1.67 1.88 Y Weight (kg) 54 62 70 84 61 92

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