2.51.50.56.101214161820Percentage of drivers under age 21Upon visual inspection, you determine that the variables do have a linear relationship. After a linear pattern has been established visually, you now proceed withperforming linear regression analysis. The results are as follows:TABLE. LINEAR REGRESSION OUTPUTFOR U.S. DEPARTMENT OF TRANSPORTATION PROBLEMCoefficientsStandard Errort Statisticp-valueIntercept-1.59740.3717-4.29790.0001Percent Under 210.28710.02949.76710.0000What is the predicted value for accidents per 1000 licenses for a city that has 13% of its licensed drivers under age 21, according to the estimated regressionequation?O 2.962O 2.135O 2.634O 1.142......00Fatal accidents per 100 U.S. Department of TransportationAs an auto insurance risk analyst, it is your job to research risk profiles for various types of drivers. One common area of concern for auto insurance companiesis the risk involved when offering policies to younger, less experienced drivers. The U.S. Department of Transportation recently conducted a study in which itanalyzed the relationship between 1) the number of fatal accidents per 1000 licenses, and 2) the percentage of licensed drivers under the age of 21 in a sampleof 42 cities.Your first step in the analysis is to construct a scatterplot of the data.FIGURE. SCATTERPLOT FOR U.S. DEPARTMENT OF TRANSPORATION PROBLEMU.S. Department of TransportationThe Relationship Between Fatal Accident Frequency and Driver Age4.54.3.53.2.51.50.50.6.8101214161820Percentage of drivers under age 21pon visual inspection, you determine that the variables do have a linear relationship. After a linear pattern has been established visually, you now proceed witherforming linear regression analysis. The results are as follows:2.1.Fatal accidents per 1000 licenses

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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 regression analysis was performed to predict weight (y, in kg) using height (x, in cm) among 150 children. The coefficient of determination was . Which of the following is a valid interpretation? a. For each 1-cm increase in height, weight tends to increase by about 0.32 kg b. There is no association between weight and height c. Height accounts for about 32% of the total variability in weight d. The correlation between weight and height is about 0.32
8.6 Cherry Trees: Timber yield is approximately equal to the volume of a tree, however, this value is difficult to measure without first cutting the tree down. Instead, other variables, such as height and diameter, may be used to predict a tree's volume and yield. Researchers wanting to understand the relationship between these variables for black cherry trees collected data from 31 such trees in the Allegheny National Forest, Pennsylvania. Height is measured in feet, diameter in inches (at 54 inches above ground), and volume in cubic feet. (Hand, 1994) Estimate Std. Error t value P(>|t|) (Intercept) -57.99 8.64 -6.71 0.00 height 0.34 0.13 2.61 0.01 diameter 4.71 0.26 17.82 0.00
Refer to the data presented in Exercise 2.86. Note that there were 50% more accidents in the 25 to less than 30 age group than in the 20 to less than 25 age group. Does this suggest that the older group of drivers in this city is more accident- prone than the younger group? What other explanation might account for the difference in accident rates?
Q9 The explanatory variable in linear correlation/regression model is recorded on which of thesemeasurement scales: A. categorical B. ordinal C. quantitative D. none of the above
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the fight 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 90 mm Hg. Use a significance level of 0.05. Right Arm Left Arm % 102 101 94 80 79 177 172 143 143 143 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.). Given that the systolic blood pressure in the right arm is 90 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg. (Round to one decimal place as needed) M H N H & C Copyright ©2022 Pearson Education Inc. All rights reserved. | Terms of Use | Privacy Policy | Permissions | Contact Us | a 33 M 0 8 K Vi 1. fio 11 O More (2) { 87°F Next [ insert prt sc 7:46 8/5/2 backspace
A healthcare provider monitors the number of CAT scans perfomed each month in each of its clinics. The most recent year of data for a particular clinics follows (the reported variable is the number of CAT scans each month expressed as the number of CAT scans per thousand members of the health plan): 2.31, 2.09, 2.36, 1.95, 1.98, 2.25, 2.16, 2.07, 1.88, 1.94, 1.97, 2.02. Find a two-sided 95% confidence interval for the standard deviation. What should you do to address any reservations about this confidence interval? Round your answers to two decimal places (e.g. 98.76).
What is the odds ratio for a study with a logistic regression coefficient -0.2524? 0.78 1.00 -0.78 -2524
Run a regression analysis on the following data set with y as the response variable. y 114 67.1 40.3 87.2 89 91.4 26.5 92.3 9.8 94.9 22.2 88.3 -0.5 What is the predicted value of the response variable when x = 82.5? y= || Round to 1 decimal place. xin
A social scientist would like to analyze the relationship between educational attainment(in years of higher education) and anual salary (in $1,000s). He collects data on 20 individuals. A portion of the data is as follows: Salary Education 43 52 1 : 2 40 : 0 A.What is the predicted salary for an individual who completed 6 years of higher education? (Round coefficient estimates to at least 4 decimal places and final answer to the nearest whole number.) B:Find the sample regression equation for the model: Salary = β0 + β1Education + ε. (Round answers to 2 decimal places.) Data Salary Education 43 1 52 2 80 9 42 3 62 1 50 8 104 10 41 0 35 5 57 1 91 4 47 4 66 8 59 7 141 11 41 0 77 2 67 4 131 8 40 0 SUMMARY OUTPUT Regression Statistics Multiple R 0.68022955 R Square 0.462712241 Adjusted R Square 0.432862921 Standard Error…
A car dealership would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on theemployee's number of years of sales experience. The accompanying regression output was developed based on a random sample of employees. a. Predict the sales next month for an employee with 2.5 years of experience. The predicted sales is 8.6 cars. b. Compute the coefficient of determination and interpret its meaning. The coefficient of determination is 0.234 Therefore, about _________% of the variation in monthly sales is explained by the years of sales experience. (Type an integer or decimal rounded to one decimal place as needed.)
A research firm regularly conducts customer satisfaction surveys for an amusement park. A survey of 200 randomly selected park visitors on a weekday in May concluded the average age of visitors to the park was 39 years. When the survey was repeated with 200 randomly selected park visitors on a Saturday in May, the average age of visitors to the park was determined to be 17 years. Does the information represents a quantitative or qualitative variable? What is the age of the visitor? Does the visitor have a season pass?
a ift = The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, bo + b₁x, 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. tab ** Answer How to enter your answer (opens in new window) Step 2 of 6: Find the estimated y-Intercept. Round your answer to three decimal places. esc 1945 ! 1 q alt a Z ebook x360 ng from any angle. @ 2 W S →>> X # 3 e d C $ 4 C r f Age Bone Density 359 % 5 V t g 36 51 63 66 70 357 328 314 310 Oll A 6 b y hp h & 7 O n u j * 8 N O i m ( 9 k O 100- 4 Tables ctrl { [ Keypad Keyboard Shortcuts Previous step answers Submit Answer D + = 11 : 90 ; ? Copy Data O SEAR Dec 2 Table ] USE YOUR SMARTPHONE FOR…

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What is the predicted value for accidents per 1000 licenses for a city that has 13% of its licensed drivers under age 21, according to the estimated regression equation? O2.962 O 2.135 O 2.634 O 1.142