4.) A person's muscle mass is expected to decrease with age. To explore this relationship, a researcher randomly selected10 persons from ages 40 to 79 years old and measured their muscle mass (unit). The result is as follows:X (age)Y (muscle mass)71 64 4367 56 73 68 56 76 6582 91 10068 87 73 78 80 65 84Based on the given data, do the following:a) Plot the scatter diagram of the given data. [3pts]b) Obtain the regression line equation. [4pts]c) Estimate the muscle mass when age of the person is 60 years old. [3pts]5.) Recognize how each shape has transformed. [2pts each]a.)b.)c.)

Step 1: Plot the Scatter DiagramGather the data points: Identify the values for age (X) and muscle…

Answered: 4.) A person's muscle mass is expected…

Elementary Geometry For College Students, 7e

7th Edition

ISBN:9781337614085

Author:Alexander, Daniel C.; Koeberlein, Geralyn M.

Publisher:Alexander, Daniel C.; Koeberlein, Geralyn M.

ChapterP: Preliminary Concepts

SectionP.CT: Test

Problem 1CT

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A manufacturing company is interested in predicting the number of defects that will be produced each hour on the assembly line. The managers believe that there is a relationship between the defect rate and the production rate per hour. The managers believe that they can use production rate to predict the number of defects. The following data were collected for 10 randomly selected hours. Defects (Y) Production rate per hour(X) 2 40 3 45 1 35 2 37 3 40 2 40 3 45 2 30 1 30 4 30 (a). Construct a scatter plot diagram and comment on the relationship between y and x (b). Calculate the correlation coefficient (r) between x and y and comment on the result. (c). Find the coefficient of determination and interpret the result.
For the following example indicate the type of data involved using the following: A = nominal data B = ordinal data C = interval data 1. Number of patients with coronary pathology in nursing homes in the U.S
c. Which of the following is the correct graph of the given data? -ОА. 10 1012 12 10 O C. 12- 81012 1012 Using the graph, explain the dramatic difference between the answers to parts (a) and (b). Choose the correct answer below. OA. The point (10,10) is not an outier, but it does have a strong effect on the least squares line and the correlation coefficient. OB. The point (10,10) does not have any effect on the least squares line and the correlation coefficient. OC. The point (10,10) is an outler that has a weak effect on the least squares line and the correlation coefficient. OD. The point (10,10) is an outlier that has a strong effect on the least squares line and the correlation coefficient.
The table lists the average gestation period (in days) and longevity (in years) for the following mammals, as reported in The World Almanac and Book of Facts 2006. Mammal Gestation, y(days) Longevity, x(years) Mammal Gestation, y(days) Longevity, x(years) Baboon 187 20 Camel 406 12 Bear, black 219 18 Cat 63 12 Bear, grizzly 225 25 Chimpanzee 230 20 Bear, polar 240 20 Chipmunk 31 6 Beaver 105 5 Cow 284 15 Buffalo 285 15 Deer 201 8 Dog 61 12 Monkey 164 15 Donkey 365 12 Moose 240 12 Elephant 645 40 Mouse 21 3 Elk 250 15 Opossum 13 1 Fox 52 7 Pig 112 10 Giraffe 457 10 Puma 90 12 Goat 151 8 Rabbit 31 5 Gorilla 258 20 Rhinoceros 450 15 Guinea pig 48 4 Sea lion 350 12 Hippopotamus 238 41 Sheep 154 12 Horse 330 20 Squirrel 44 10 Kangaroo…
The level of cretaine phosphokinase (CPK) in blood samples measures the amount of muscle damage for athletes. At Jock State University, the level of CPK was determined for each of 25 football players and 15 soccer players before and after practice. The two groups of athletes are trained independently. The data summary is as follows : For football players: n=25 Before Practice After Practice Difference (Before-After) Mean 254.73 225.6 29.13 Standard deviation 115.5 132.6 21.00 For soccer players: n=15 Before Practice After Practice Difference (Before-After) Mean 177.1 173.8 3.3 Standard deviation 60.7 64.4 6.88 Assume that all the data above are normal, use the information above to answer problem (7) Construct a 95% Confidence Interval for the difference in mean CPK values for football players BEFORE and AFTER exercises.
The data used is from college campuses. The variables used in the analysis below include: crime, total campus crime; enroll, total enrollment; police, employed officers. Use the estimated OLS models to answer the questions below: Model A: In(crime) = -6.631 + 1.270ln(enroll), (1.034) (.110) .5804 n = 97; R² = Model B: In(crime) = -4.794+.923ln(enroll) +.516ln(police), (.144) (.149) (1.112) n = 97; R² = .632 Using Model A, test the null hypothesis that elasticity of crime with respect to enrollment is unit elastic, i.e. equal to one (against a two-sided alternative). What is the conclusion of your test using a significance level of .01? Reject Fail to reject O Not enough information.
Here are the world record race times for women in the 10,000-meter run over several years. a) Which is the explanatory variable and which is the response variable? Year Race Time (seconds) 1967 2286.4 b) Make a scatterplot of these data. You do not have to draw the scatterplot for me. Describe what you see (form, direction, 1970 2130.5 1975 2100.4 strength, outliers). 1975 2041.4 c) Write the equation of the regression line for predicting race time from year. 1977 1995.1 1979 1972.5 d) Give the meaning of the slope of your line in terms of race time and year. What are the units of the slope in this problem? 1981 1950.8 1981 1937.2 e) What percent of the observed variation in 1982 1895.3 the race times can be explained by your 1983 1895.0 model? 1983 1887.6 f) Find the residual for the first data point or 1984 1873.8 the list (the 2286.4 seconds from 1967). 1985 1859.4 g) What does this linear model predict for th race time in the year 2075? Do you think 1986 1813.7 this is reasonable?…

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