We have data on the lean body mass and resting metabolic rate for 12 women who are subjects in a study of dieting. Lean body mass,given in kilograms, is a person's weight leaving out all fat. Metabolic rate, in calories burned per 24 hours, is the rate at which thebody consumes energy.Mass46 47.7 47.7 38.8 52.1 48.8 48.5 36.8 42 51 43.9 46.7Rate 1240 1320 1220 1280 1430 1090 1590 990 1090 960 1520 1390|Find the least-squares regression line for predicting metabolic rate from body mass.ANSWER: ŷ

In the question, given that:The question's purpose is to determine the least-square regression line.

Answered: We have data on the lean body mass and…

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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Your Question: A psychologist believed that as children get older, they engage in more “inactive activities” such as playing computer games, watching TV and surfing the internet. She collected data from 10 children. She recorded the age of each child and the amount of activity (in hours) the child engaged in per week. The data is below: Age Activity 7 4.3 9 3.2 10 1 13 1.5 12 1.2 15 0.8 9 3 12 4 15 1.5 14 1.9 Using excel, obtain a scatterplot of the data. Discuss the relationship between age and activity based on the scatterplot. Using excel, obtain the simple linear regression linear regression line predicting activity from age. Interpret the intercept and slope of the regression line. By hand, predict the amount of activity for age = 14. By hand, calculate the residual for age = 14. Using excel, test the null hypothesis that the slope coefficient is zero using the p-value approach. Write one sentence interpreting the meaning of this result. Make sure to…
2. A professor wants to see how much students learn over the course of a semester. A pre test is given before the class begins to see what students know ahead of time, and the same test is given at the end of the semester to see what students know at the end. The data are below. Test for an improvement at the a = 0.05 level. Did scores increase? How much did scores increase? Pretest 90 Posttest Xp 89 60 66 95 99 93 91 95 100 64 67 89 91 90 95 95 94 83 89 75 82 87 92 82 83 85 82 88 93 66 90 69 90 93 100 86 95 91 96
Help me fast so that I will give Upvote.
Given this data estimate the population in 2060.
Take the following information about the theater industry. The theater seats are classified as either reserved or vacant. Among the reserved seats, 2 percent becomes vacant every period. Among the vacant seats, 8 percent become reserved periodically. What is the natural rate of seats that are vacant?
Researchers wondered whether the size of a person's brain was related to the individual's mental capacity. They selected a sample of 5 females and 5 males and measured their MRI image pixel counts and IQ scores. The data is reported to the right. Complete parts (a) through (d) below. Click the icon to view the critical values table. 1,080,000- 780,000 MRI 130 145 (a) Draw a scatter diagram treating MRI count as the explanatory variable and IQ as the response variable. Choose the correct diagram below. OA. Q Q OB. AMRI 1,080,000- 780,000 130 IQ 145 COLO Q Q SCIER O C. AIQ 145+ 130 780,000 Females MRI IQ 866,662 130 857,782 133 MRI IQ 935,494 141 1,079,550 141 852,244 132 1,001,121 140 951,545 137 955,466 133 790,619 135 1,038,438 139 MRI Males 1,080,000 C D. 145 AIQ 130- 780,000 MRI 1,080,000 Q (b) Compute the linear correlation coefficient between MRI count and IQ. Are MRI count and IQ linearly related? Select the correct choice below and, if necessary, fill in the answer box to…
A psychologist believed that as children get older, they engage in more “inactive activities” such as playing computer games, watching TV and surfing the internet. She collected data from 10 children. She recorded the age of each child and the amount of activity (in hours) the child engaged in per week. Age Activity 7 4.3 9 3.2 10 1 13 1.5 12 1.2 15 0.8 9 3 12 4 15 1.5 14 1.9 Using excel, obtain a scatterplot of the data. Discuss the relationship between age and activity based on the scatterplot. Using excel, obtain the simple linear regression linear regression line predicting activity from age. Interpret the intercept and slope of the regression line. By hand, predict the amount of activity for age = 14. By hand, calculate the residual for age = 14 Using excel output, test the null hypothesis that the slope coefficient is zero using the p-value approach. Write one sentence interpreting the meaning of this result. Make sure to report the test statistic…
Speed cameras (SC) are used to reduce the risk of accidents in accident-prone zones in metropolitan cities. To study the effectiveness of speed cameras, transport engineers would like to compare the average number of accidents in junction A (with SC) and junction B (without SC). The number of accidents in 105 weeks in two junctions are provided below. 6 7+ Number of Accidents 0 1 2 3 4 5 Observed frequency 40 20 15 16 10 3 1 0 Number of Accidents 0 1 2 3 4 5 6 7+ Junction B without SC Observed frequency 25 24 18 15 18 41 0 Junction A with SC Test the average number of accidents per week in junctions A and B are same at the 5% significance level.
2.1
Table 9.3 Total cholesterol in 25 patients after taking new statin drug. .. Population mean is 200. Cholesterol levels 219 191 198 214 163 264 248 182 235 209 152 148 145 189 213 230 181 180 100 219 102 249 282 188 264 D. b. Describe the effects of the statin drug on your sample. Do you see any change in the level of cholesterol after taking the drug? c. What is your research question? What are the null and alternative hypotheses? Decide if you want to do a one-tailed or two-tailed test. d. What test? Perform it? What is your critical value? Sketch a normal distribution and draw the critical value or values of z. f. What is your conclusion?
Cigarette smoking has important health consequences. Less well known are the consequences of quitting smoking. A study enrolled nurses, ages 50-54 years, who had smoked at least 1 pack per day and quit for at least 6 years. The nurses reported their weight before and 6 years after quitting smoking. The BMI (measure of obesity) are given in the following table. Determine whether BMI changed among heavy-smoking women. Before 25.6 24.4 31 20.4 22.3 22.2 20.8 23.5 26.6 23 After 31.1 27.6 36.6 20.8 23.2 23.8 26.1 31 29.2 24
5.8 Driving Safety Data How many miles does a car traveling at a mph cover in five hours? S

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