Scenario: A medical researcher wishes to see whether there is a relationship between a person's age, cholesterol level, and systolic blood pressure. Eight people are randomly selected. The data is listedin the table. First, find the multiple regression equation. Next, determine the coefficient of determination. Then, use the regression equation to predict a person's blood pressure reading if the personselected is 50 years old with a cholesterol reading of 220.AgeCholesterol levelBlood pressurePerson 138220116Person 241225120Person 345200123Person 448190131Person 551250142Person 653215145Person 757200148Person 861170150Discussion PromptsRespond to the following prompts in your initial post:1. Identify the explanatory variables and response variable for the data.2. What is the multiple regression equation for the data?3. What is the coefficient of determination?4. If a person 50 years old with a cholesterol of 220 is selected, what is that person's predicted blood pressure reading?

Since there are multiple sub-parts, as per the honor code the first three sub-parts will be solved.…

Respond to the following prompts in your initial post: 1. Identify the explanatory variables and response variable for the data. 2. What is the multiple regression equation for the data? 3. What is the coefficient of determination? 4. If a person 50 years old with a cholesterol of 220 is selected, what is that person's predicted blood pressure reading?

Respond to the following prompts in your initial post: 1. Identify the explanatory variables and response variable for the data. 2. What is the multiple regression equation for the data? 3. What is the coefficient of determination? 4. If a person 50 years old with a cholesterol of 220 is selected, what is that person's predicted blood pressure reading?

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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A real estate agent wanted to find the relationship between sale price of houses and the size of the house. Shecollected data on two variables recorded in the following table for 15 houses in Seattle. The two variables are PRICE= Sale price of houses in thousands of dollarsSIZE= Area of the entire house in square feet. The Excel working has been given. Note: the left hand side is Regression run(ans a).. The right hand side is 'new' regression run (for ans d). Question b) Interpret the slope and constant term with proper UNITS assigned. c) Comment on the explanatory power of the regression model from the required output. Copy that specificoutput into your assignment word document.Now to increase the explanatory power of the model the real estate agent decides to look at the age of thehouse and the garden size. For the 15 houses in our sample the new variables areAGE= Age of the house in years, since it was builtGARDEN= Area of the garden in acres. d) Once these two new variables are…
12. A consumer advocacy group recorded several variables on 140 models of cars. The resulting information was used to produce the following regression output that relates the city gas mileage (in mpg) and the engine displacement (in cubic inches). The regression equation is mpg:city= 33.4 0.0624 displacement Predictor Constant SE Coef T P 0.7762 43.00 0.000 displacement -0.0624 0.003810 0.000 S 3.13923 = R-Sq 66.0% R-Sq (adj) = 65.8% a. We have a car that has an engine with 150 cubic inches. Based on this output, what city gas mileage would you predict for this car? Coef 33.4 b. Based on this output what is the correlation between city gas mileage and displacement? C. I value: The test statistics for testing the slope is zero is missing. Calculate this The group o also recorded the power of the engine (in horsepower) for each car. The following regression output was produced. Predictor Constant horsepower The regression equation is mpg:city = 32.2 0.0572 horsepower Coef SE Coef 32.2 T…
. A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…
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Listed.below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 1000 mm Hg. Use a significance level of 0.05. Right Arm 102 101 94 79 79 O Left Arm 175 168 146 147 145 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y= X. (Round to one decimal place as needed.)
Suppose a study is conducted to determine the effect of physical exercise on the level of low-density lipoprotein (LDL) cholesterol. The following data are on the amount of weekly exercise and LDL are collected: a. Plot an appropriate graph for the data. b. Compute the sample correlation coefficient. Interpret the correlation coefficient. Test the hypothesis whether the correlation is significant at 0.05. c. Write the regression equation. Interpret the equation. d. Predict the LDL who exercise 3 hours per week. e. Test at the 5% significance level for slope? Would you suggest there is a strong enough association between the variables to conclude that physical exercise is beneficial for lowering LDL? f. Calculate the coefficient of determination and provide your interpretation.
Consider the following data: x¯ = 20, sx = 2, y¯ = −5, sy = 4, and b1 = 0.40. Which of the following is the sample regression equation?
I need help with these questions. I did part A with the regressional analysis and got 92.5% for the coefficient determination.
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + bjx, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 47 49 50 51 58 Bone Density 360 353 336 333 310 Table Copy Data Step 1 of 6: Find the estimated slope. Round your answer to three decimal places.
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