4. A Zumba instructor remembers the data given in the following table, which shows therecommended maximum exercise heart rates for individuals of the given ages.Age (x years)20 4060Maximum heart rate 170 153 136(y beats per minute)a. Find the linear correlation coefficient for the data.b. What is the significance of the value found in part a?c. Find the equation of the least-squares line.d. Use the equation from part c to predict the maximum exercise heart rate for a person who is72.e. Is the procedure in part d an example of interpolation or extrapolation?

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Answered: 4. A Zumba instructor remembers the…

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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19. You might think that increasing the resources available would elevate the number of plant spe- cies that an area could support, but the evidence suggests otherwise. The data in the accompany- ing table are from the Park Grass Experiment at Rothamsted Experimental Station in the U.K., where grassland field plots have been fertilized annually for the past 150 years (collated by Harpole and Tilman 2007). The number of plant species recorded in 10 plots is given in response to the number of different nutrient types added Plot 1 2 3 4 5 6 7 8 9 10 Number of nutrients added 0 0 0 3144 E2 3 Number of plant species 36 36 32 34 33 30 20 23 21 16
The data below was collected from manufacturer advertisements of their vehicles horsepower (x) and highway gas mileage (mpg=y). Use this data to answer the following questions. horsepower 146 250 340 350 390 190 220 mpg 33 28 15 17 11 35 42 1. Find the p-value to determine if there is a linear correlation between horsepower and highway gas mileage (mpg). Record the p-value below. Round to four decimal places.p-value==2. Is there a linear correlation between horsepower and highway gas mileage (mpg)? 3. If there is a linear correlation, write the correlation coefficient below. Otherwise, leave it blank. Round your final answer to four decimal places. Be careful with your sign.r=r= 4. If there is a linear correlation, write the regression equation below. Otherwise, leave it blank. Round all numbers to four decimal places.ˆy=y^=5. Using the data shown above, predict the the highway gas mileage (mpg) for a car that has a horsepower of 225. Round your final answer to two decimal…
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. X Y 11.4 8.6 7.2 3.6 13.5 11.3 10.1 x = thousands of automatic weapons y = murders per 100,000 residents 2.4 2.8 2.3 0.9 7 6.1 6.6 5.9 4.7 This data can be modeled by the equation y = 0.83x +4.06. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. Answer = A) How many murders per 100,000 residents can be expected in a state with 2.7 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 11 thousand automatic weapons? Round to 3 decimal places.
JUST ANSWER THE LETTER D AND E A Zumba instructor remembers the data given in the following table, which shows the recommended maximum exercise heart rates for individuals of the given ages. Age (x years) 20 40 60 Maximum heart rate 170 153 136 (y beats per minute) a. Find the linear correlation coefficient for the data. b. What is the significance of the value found in part a? c. Find the equation of the least-squares line. d. Use the equation from part c to predict the maximum exercise heart rate for a person who is 72. e. Is the procedure in part d an example of interpolation or extrapolation?
11. For temperature (x) and number of ice cream cones sold per hour (y). (65, 8), (70, 10), (75, 11), (80,13), (85, 12), (90, 16). Interpret the coefficient of determination. Optional Answers: 1. 88.2% of the variability in the number of cones sold is explained by the least-squares regression model. 2. 93.9% of the variability in the number of cones sold is explained by the least-squares regression model. 3. 88.2% of the variability in the temperature is explained by the least-squares regression model. 4. 93.9% of the variability in the temperature is explained by the least-squares regression model.
The table below shows the age of 8 individuals and the packs of medicine they consume each year. Age 17 27 54 35 42 31 46 23 Medicine (in packs) 17 7 12 6 2 a. Determine the correlation coefficient r between the two variables. Answer rounded to at least 4 decimal places. b. Determine the slope coefficient B1 for the regression of medicine packs consumed on age. Answer rounded to at least 4 decimal places. c. Determine the y-intercept Bo for the regression of medicine packs consumed on age. Answer rounded to at least 4 decimal places. d. What will be the expected packs of medicines consumed per year by a person of age 33. Answer rounded to at least 4 decimal places. packs
2. An aerobic exercise instructor submitted to the shipping company the data given in the following table, which shows the recommended maximum exercion heart rate for individuals of the given ages. See table below. If the Chief engineer is 62 years old, predict. naximum exercise heart rate. Age (x years) Maximum heart rate (y beats per minute) 20 40 60 170 153 136 A. What is the coefficient of correlation of the age and the maximum rate of the chief engineer? a. -100 b. 100 C. -0.99 d. 0.65
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