mose that the model equation is the following and that a 5. y = 31 +0.89x₂ +0.07x₂-4.40x₂ + e LAUSE SALT What is the mean rating of acceptable weight (in kg) when extent of left lateral bending is 35 cm, dynamic hand grip endurance is 210 sec, and trunk extension ratio is 12 N/kg? kg If repeated observations on rating are made on different individuals, all of whom have the values of x₁, x₂, and x, specified in part (a), in the long run approximately what percentage of ratings will be between 14.05 kg and 34.05 kg? (Round your answer

mose that the model equation is the following and that a 5. y = 31 +0.89x₂ +0.07x₂-4.40x₂ + e LAUSE SALT What is the mean rating of acceptable weight (in kg) when extent of left lateral bending is 35 cm, dynamic hand grip endurance is 210 sec, and trunk extension ratio is 12 N/kg? kg If repeated observations on rating are made on different individuals, all of whom have the values of x₁, x₂, and x, specified in part (a), in the long run approximately what percentage of ratings will be between 14.05 kg and 34.05 kg? (Round your answer

Calculus For The Life Sciences

2nd Edition

ISBN:9780321964038

Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Chapter2: Exponential, Logarithmic, And Trigonometric Functions

Section2.CR: Chapter 2 Review

Problem 111CR: Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data...

See similar textbooks

Similar questions

If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data are at or below for respiratory rates in breath per minute during the first 3 years of infancy are given by y=101.82411-0.0125995x+0.00013401x2 for awake infants and y=101.72858-0.0139928x+0.00017646x2 for sleeping infants, where x is the age in months. Source: Pediatrics. a. What is the domain for each function? b. For each respiratory rate, is the rate decreasing or increasing over the first 3 years of life? Hint: Is the graph of the quadratic in the exponent opening upward or downward? Where is the vertex? c. Verify your answer to part b using a graphing calculator. d. For a 1- year-old infant in the 95 th percentile, how much higher is the walking respiratory rate then the sleeping respiratory rate? e. f.
A number of investigations have focused on the problem of assessing weights that can be lifted in a safe manner. A particular article proposed using a regression model to relate the following dependent variable (y) to k = 3 independent (predictor) variables. y = individual's rating of acceptable weight (kg) X1 = extent of left lateral bending (cm) dynamic hand grip endurance (sec) X2 = trunk extension ratio (N/kg) X3 Suppose that the model equation is the following and that o = 6. y = 29 + 0.91x, + 0.07x2 – 4.60x3 + e (a) What is the mean rating of acceptable weight (in kg) when extent of left lateral bending is 50 cm, dynamic hand grip endurance is 200 sec, and trunk extension ratio is 9 N/kg? kg (b) If repeated observations on rating are made on different individuals, all of whom have the values of x,, x, and x, specified in part (a), in the long run approximately what percentage of ratings will be between 35.1 kg and 59.1 kg? (Round your answer to four decimal places.) You may need…
A number of investigations have focused on the problem of assessing weights that can be lifted in a safe manner. A particular article proposed using a regression model to relate the following dependent variable (y) to k = 3 independent (predictor) variables. y = individual's rating of acceptable weight (kg) x₁ extent of left lateral bending (cm) X₂= dynamic hand grip endurance (sec) x= trunk extension ratio (N/kg) Suppose that the model equation is the following and that 6. y = 29 +0.89x, +0.06x₂ - 4.70x + e USE SALT (a) What is the mean rating of acceptable weight (in kg) when extent of left lateral bending is 45 cm, dynamic hand grip endurance is 210 sec, and trunk extension ratio is 11 N/kg? kg (b) If repeated observations on rating are made on different individuals, all of whom have the values of x₁, x₂, and x specified in part (a), in the long run approximately what percentage of ratings will be between 17.95 kg and 41.95 kg? (Round your answer to four decimal places.)
A number of investigations have focused on the problem of assessing weights that can be lifted in a safe manner. A particular article proposed using a regression model to relate the following dependent variable (y) to k = 3 independent (predictor) variables. y = individual's rating of acceptable weight (kg) x, = extent of left lateral bending (cm) x, = dynamic hand grip endurance (seconds) x, = trunk extension ratio (N/kg) Suppose that the model equation is the following and that o = 5. y = 31 + 0.91x, + 0.07x2 - 4.40x3 + e (a) What is the population regression function? y = (b) What are the values of the population regression coefficients? B1 = B2 = B3 = (c) Interpret the value of B,. When.Select::. v are fixed, the mean -Select--- in rating of acceptable load associated with a ---Select--- v increase in --Select-- is 0.91 kg. (d) Interpret the value of B3. When ---Select--- v are fixed, the mean ---Select--- v in rating of acceptable load associated with a ---Select--- v increase in…
A clothing manufacturer wants to estimate the amount of scrap cloth generated each day by its fabric cutting machines. Eight potential independent variables have been identified. These include the following. = amount of cloth run through cutting machines (in square feet) X2 = machine cutting speed (in feet per minute) age of machine (in years) The manufacturer selects 6 of the candidate independent variables to use in a multiple regression model for estimating y, the amount of scrap cloth (in square feet). Using data collected from 24 different cutting machines operating on different days, the model y = Bo+B1*1 +B,x2+ + Bax, is fit to the data. Fill in the blanks in the analysis of variance (ANOVA) table associated with this model. Do all ... calculations to at least three decimal places.
The accompanying Minitab regression output is based on data that appeared in the article "Application of Design of Experiments for Modeling Surface Roughness in Ultrasonic Vibration Turning."+ The response variable is surface roughness (um), and the independent variables are vibration amplitude (um), depth of cut (mm), feed rate (mm/rev), and cutting speed (m/min), respectively. The regression equation is Ra = -0.972 - 0.0312a + 0.557d + 18.3f + 0.00282v Predictor Coef SE Coef Constant -0.9723 0.3923 -2.48 0.015 -0.03117 0.01864 -1.67 0.099 d 0.5568 0.3185 1.75 0.084 18.2602 0.7536 24.23 0.000 0.002822 0.003977 0.71 0.480 S = 0.822059 Source R-Sq = 88.6 R-Sq (adj) = 88.04 DS MS 0.000 Regression Residual Error 4 401.02 100.25 148.35 76 51.36 0.68 Total 80 452.38 (a) How many observations were there in the data set? observations (b) Interpret the coefficient of multiple determination. O 8.0% of the observed variation in feed rate can be explained by the model relationship with vibration…
The authors of the paper "Weight-Bearing Activity during Youth Is a More Important Factor for Peak Bone Mass than Calcium Intake"t used a multiple regression model to describe the relationship between y = bone mineral density (g/cm³) body weight (kg) X1 %3D X2 = a measure of weight-bearing activity, with higher values indicating greater activity (a) The authors concluded that both body weight and weight-bearing activity were important predictors of bone mineral density and that there was no significant interaction between body weight and weight-bearing activity. What multiple regression function is consistent with this description? (Use a to represent the intercept. Use B, and ß, for the coefficients of x, and x2.) y = (b) The value of the coefficient of body weight in the multiple regression function given in the paper is 0.569. Interpret this value. O When the measure of weight-bearing activity is fixed, and body weight is increased by 0.569-kg, the mean bone mineral density…
A number of investigations have focused on the problem of assessing loads that can be manually handled in a safe manner. A particular article proposed using a regression model to relate the following dependent variable (y) to k = 3 independent (predictor) variables. y = individual's rating of acceptable load (kg)x1 = extent of left lateral bending (cm)x2 = dynamic hand grip endurance (sec)x3 = trunk extension ratio (N/kg) Suppose that the model equation is the following and that ? = 6. (a) What is the mean value of rating of acceptable load when extent of left lateral bending is 45 cm, dynamic hand grip endurance is 210 sec, and trunk extension ratio is 12 N/kg?(b) If repeated observations on rating are made on different individuals, all of whom have the values of x1, x2, and x3 specified in Part (a), in the long run approximately what proportion of ratings will be between 21.3 kg and 45.3 kg? (Use Table 2 in Appendix A. Round your answer to four decimal places.)
A particular article used a multiple regression model with the following four independent variables. y = error percentage for subjects reading a four-digit liquid crystal displayx1 = level of backlight (from 0 to 122 cd/m)x2 = character subtense (from .025 to 1.34)x3 = viewing angle (from 0 to 60)x4 = level of ambient light (from 20 to 1500 lx) The model equation suggested in the article is given below. (a) Assume that this is the correct equation. What is the mean value of y when x1 = 30, x2 = 0.6, x3 = 50 and x4 = 150?(b) What mean error percentage is associated with a backlight level of 40, character subtense of 0.6, viewing angle of 20, and ambient light level of 30?
The following result perspective in RapidMiner shows a multiple linear regression model. Based on the diagram, the model for our dependent variable Y is Predicted Y= (Insulation *0.420)+(Temperature *0.071)+(Avg_Age*0.065)+(Home_Size *0.311)+7.589 Attribute Insulation Temperature Avg Age Home Size (Intercept) O True O False Coefficient 3.323 -0.869 1.968 3.173 134.511 Std. Error 0.420 0.071 0.065 0.311 7.589 Std. Coefficient 0.164 -0.262 0.527 0.131 ? Tolerance 0.431 0.405 0.491 0.914 ? t-Stat 7.906 -12.222 30.217 10.210 17.725