The authors of the paper "Weight-Bearing Activity during Youth Is a More Important Factor for Peak Bone Mass than CalciumIntake" studied a number of variables they thought might be related to bone mineral density (BMD). The accompanying data onx = weight at age 13 and y = bone mineral density at age 27 are consistent with summary quantities for women given in thepaper.Weight (kg) BMD (g/cm²)54.41.1559.31.2674.61.4262.01.0673.71.4470.81.0266.81.2666.71.3564.71.0271.80.9169.71.2864.71.1762.11.1268.51.2458.31.00A simple linear regression model was used to describe the relationship between weight at age 13 and BMD at age 27. Thefollowing values are given for this data.a = 0.5584SSTO= 0.356n = 15b = 0.0094SSResid= 0.31290(a) What percentage of observed variation in BMD at age 27 can be explained by the simple linear regression model? (Roundyour answer to two decimal places.)%(b) Give an estimate of o. (Round your answer to five decimal places.)Interpret this estimate.This is an average of weight values in the sample from the value predicted by the least-squares line.O This is a typical deviation of a weight value in the sample from the value predicted by the least-squares line.This is an average of bone mineral density values in the sample from the value predicted by the least-squares line.O This is a typical deviation of a bone mineral density value in the sample from the value predicted by the least-squaresline.(c) Give an estimate of the average change in BMD associated with a 1 kg increase in weight at age 13. (Round your answer tofour decimal places.)g/cm²(d) Compute an estimate of the mean BMD at age 27 for women whose weight at age 13 was 72 kg. (Round your answer tothree decimal places.)g/cm²

Given that Here given as a = 0.5584 b = 0.0094 n = 15 SSTo =0.356 SSResid = 0.31290 a) r2 = (SSTo…

Answered: (a) What percentage of observed…

College Algebra (MindTap Course List)

12th Edition

ISBN:9781305652231

Author:R. David Gustafson, Jeff Hughes

Publisher:R. David Gustafson, Jeff Hughes

Chapter4: Polynomial And Rational Functions

Section4.6: Rational Functions

Problem 11SC: Find the mean hourly cost when the cell phone described above is used for 240 minutes.

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Find the mean hourly cost when the cell phone described above is used for 240 minutes.
Glaucoma is a leading cause of blindness in the United States, N. Ehlers measured the difference in corneal thickness (in microns) between the two eyes of eight patients. Each patient had one eye that had glaucoma and one eye that was normal. The difference was measured as the corneal thickness of normal eye – corneal thickness of eye with Glaucoma. Corneal thickness is important because it can mask an accurate reading of eye pressure. Question:If the t statistic falls below the effect size in which we reject the null, but the p value is greater than 0.05. Do i reject the null? As my scenario had no population mean because the differences were recorded, do i set a test value of 10 or keep it at 0?
A researcher is interested in testing the relationship between smoking and BMI (kg/m2) in adults aged 30-45. In order to test this association, the researcher divides smoking into currently more than a pack a day, currently less than a pack a day, and never smokers. The following table represents the BMIs for each participant enrolled by their respective smoking category. Current Smoker (≥1pack/day) Current Smoker (<1 pack/day Never Smoked 26.7 29.4 22.1 29.4 28.6 30.4 24.3 27.4 21.3 28.4 23.2 26.4 21.6 20.1 19.7 27.4 20.6 19.8 26.8 19.7 21.6 36.4 19.6 22.3 31.5 21.6 24.3 27.4 21.5 *Continue as though all assumptions for ANOVA are met. A) Calculate the MSW and MSB for the data represented above. B) Carry out a formal test for a one-way analysis of variance among the groups and interpret your results.
The authors of the paper "Weight-Bearing Activity during Youth Is a More Important Factor for Peak Bone Mass than Calcium Intake" studied a number of variables they thought might be related to bone mineral density (BMD). The accompanying data on x = weight at age 13 and y = bone mineral density at age 27 are consistent with summary quantities for women given in the paper. Weight (kg) BMD (g/cm2) 54.4 1.15 59.3 1.26 74.6 1.42 62.0 1.06 73.7 1.44 70.8 1.02 66.8 1.26 66.7 1.35 64.7 1.02 71.8 0.91 69.7 1.28 64.7 1.17 62.1 1.12 68.5 1.24 58.3 1.00 A simple linear regression model was used to describe the relationship between weight at age 13 and BMD at age 27. The following values are given for this data. a = 0.5584 b = 0.0094 n = 15SSTo = 0.356 SSResid = 0.31290 (a) What percentage of observed variation in BMD at age 27 can be explained by the simple linear regression model? (Round your answer to two decimal places.) %…
The authors of the paper "Weight-Bearing Activity during Youth Is a More Important Factor for Peak Bone Mass than Calcium Intake" studied a number of variables they thought might be related to bone mineral density (BMD). The accompanying data on x = weight at age 13 and y = bone mineral density at age 27 are consistent with summary quantities for women given in the paper. Weight (kg) BMD (g/cm2) 54.4 1.15 59.3 1.26 74.6 1.42 62.0 1.06 73.7 1.44 70.8 1.02 66.8 1.26 66.7 1.35 64.7 1.02 71.8 0.91 69.7 1.28 64.7 1.17 62.1 1.12 68.5 1.24 58.3 1.00 A simple linear regression model was used to describe the relationship between weight at age 13 and BMD at age 27. The following values are given for this data. a = 0.5584 b = 0.0094 n = 15SSTo = 0.356 SSResid = 0.31290 (a) What percentage of observed variation in BMD at age 27 can be explained by the simple linear regression model? (Round your answer to two decimal places.)…
Glaucoma is a leading cause of blindness in the United States, N. Ehlers measured the difference in corneal thickness (in microns) between the two eyes of eight patients. Each patient had one eye that had glaucoma and one eye that was normal. The difference was measured as the corneal thickness of normal eye – corneal thickness of eye with Glaucoma. Corneal thickness is important because it can mask an accurate reading of eye pressure. Question: If a participant has the same corneal thickness in their normal eye as the eye with Glaucoma, what would be the value for difference: measured as the corneal thickness of normal eye – corneal thickness of eye with Glaucoma.
Glaucoma is a leading cause of blindness in the United States, N. Ehlers measured the difference in corneal thickness (in microns) between the two eyes of eight patients. Each patient had one eye that had glaucoma and one eye that was normal. The difference was measured as the corneal thickness of normal eye – corneal thickness of eye with Glaucoma. Corneal thickness is important because it can mask an accurate reading of eye pressure. Question: Write a report summarizing your findings When writing the report consider that medical staff estimate that a difference of 4.5 microns or more could impact on their ability to interpret eye pressure correctly.
A paper gives data on x = change in Body Mass Index (BMI, in kilograms/meter?) and y = change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. The table below contains a subset of the data given in the paper and are approximate values read from a scatterplot in the paper. BMI Change (kg/m²) 0.5 -0.5 0.1 0.7 0.8 1 1.5 1.2 1 0.4 0.4 Depression Score Change -1 4 4 5 8 13 14 17 18 12 14 The accompanying computer output is from Minitab. Fitted Line Plot Depression score change = 6.512 + 5.472 BMI change 5.26270 20- R-Sq R-Sq (adj) 19.88% 27.16% 15- 10- 5- 0- -0.5 0.0 0.5 1.0 1.5 BMI change R-są 5.26270 27.16% Coefficients Term Coef SE Coef T-Value P-Value VIF 6.512 5.472 Constant 2.26 2.88 0.0164 BMI change 2.83 1.93 0.0823 1.00 Regression Equation Depression score change = 6.512 + 5.472 BMI change (a) What percentage of observed variation in depression score change can be explained by the simple linear regression…
5.60 • Determining the age of an animal can sometimes be a difficult task. One method of estimating the age of harp seals is based on the width of the pulp canal in the seal's canine teeth. To investigate the relationship between age and the width of the pulp canal, researchers measured age and canal width in seals of known age. The following data on x = age (in years) and y = canal length (in mil- limeters) are a portion of a larger data set that appeared in the paper "Validation of Age Estimation in the Harp Seal Using Dentinal Annuli" (Canadian Journal of Fisheries and Aquatic Science [1983]: 1430-1441): * 0.25 0.25 0.50 0.50 0.50 0.75 0.75 1.00 400 y 700 675 525 500 350 300 300 1.00 1.00 1.00 1.00 1.25 1.25 1.50 1.50 250 230 150 100 200 100 100 125 * 2.00 60 2.00 2.50 2.75 3.00 4.00 4.00 5.00 y 140 60 50 10 10 10 10 * 5.00 5.00 5.00 6.00 6.00 15 y 10 10 15 10 Construct a scatterplot for this data set. Would you de- scribe the relationship between age and canal length as lin- ear?…
iDENTIFY THE TYPE AND LEVEL OF MEASUREMENT OF THE FOLLOWING VARIABLES gender - either male or female runtime - time to run 1.5 miles (in min) age - age of the gym member in years weight - weight of the gym member (in kg) oxygen consumption - measure of the ability to use oxygen in the blood stream (in ml/min) rest pulse - resting pulse rate (in bpm) maximum pulse - maximum pulse rate during the run (in bpm)
Shortleaf Pines. The ability to estimate the volume of a tree based on a simple measurement, such as the diameter of the tree, is important to the lumber industry, ecologists, and conservationists. Data on volume, in cubic feet, and diameter at breast height, in inches, for 70 shortleaf pines was reported in C. Bruce and F. X. Schumacher’s Forest Mensuration (New York: McGraw-Hill, 1935) and analyzed by A. C. Akinson in the article “Transforming Both Sides of a Tree” (The American Statistician, Vol. 48, pp. 307–312). The data are provided on the WeissStats site. a. obtain and interpret the standard error of the estimate. b. obtain a residual plot and a normal probability plot of the residuals. c. decide whether you can reasonably consider Assumptions 1–3 for regression inferences met by the two variables under consideration.
a study was done involving data from all major US cities that compares the number of parks in each city to the average number of times an individual exercises each week. Pearson's r=.76 What does the value of r suggest?

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