Forest rangers use the diameter of a tree's trunk to predict the age of the tree. They have determined that a linear model isappropriate in these situations. To determine the linear model for a certain variety of trees, some data is collected on trees withknown ages. The data is given below. Find the linear regression equation for this data.Diameter (in inches)Age (in years)4.06.08.010.023415470Use the linear regression equation to estimate the age of a tree of this variety with a trunk diameter of 14.5 inches.Do not round your answer.Estimated Age =years

Solution-: We find the linear regression equation to estimate the age of a tree of this variety with…

Answered: Forest rangers use the diameter of a…

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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Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.5 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.9 per 10 million people? Click the icon to view the data. Data table Find the equation of the regression line. Internet Users Per 100 Nobel Laureates V = + (Round the constant to one decimal place as needed. Round the coefficient to three decimal places as needed.) 79 5.4 79.6 24.5 78.7 8.5 44.7 0.1 83.6 6.1 38.6 0.1 90.2 25.5 89.4 7.7 79.1 9. 83.1 12.8 52.7 1.9 76.8 12.7 57.1 3.3 79.8 1.5 92.3 11.5 93.8 25.7 64.7 3.1 58.2 1.9 67.3 1.7 94 31.8 84.5 31.3 87 18.9 77.1 10.7
Use the linear regression models above to answer this question. There are two break-even points. Find the larger production level where the company breaks even. Round to the nearest treadmill. treadmills
An instructor asked a random sample of eight students to record their study times at the beginning of a course. She then made a table for total hours studied (x) over 2 weeks and test score (y) at the end of the 2 weeks. The table is given below. Complete parts (a) through (f). x 10 13 10 18 6 15 16 21 y 93 79 81 74 85 81 85 80 a. Find the regression equation for the data points. b. Graph the regresson equation c. Describe the apparent relationship between the two variables. d. Identify the predictor and response variables. e. Identify outliers and potential influential observations. f.Predict the score for a student that studies for 17 hours.
The table shows the approximate chirping rate at various temperatures for one type of cricket. Use the linear regression feature on a graphing calculator to determine an equation of the line that best fits the data. Round to the hundredths. ⒸEncikAn/Shutterstock.com X Temperature (°F) 50 60 70 80 100 Chirps per Minute 20 80 115 150 250
Use the linear regression models above to answer this question. There are two break-even points. Find the smaller production level where the company breaks even. Round to the nearest treadmill. treadmills attached ss thanks
The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through c Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs = 247733.3 +(43.2000) x Billable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) b. Interpret the coefficients of your regression model. Specifically, what does the fixed component of the model mean to the consulting firm? Interpret the fixed term, bo. if appropriate. Choose the correct answer below. OA. The value of by is the predicted overhead costs for 0 billable hours. OB. For each increase of 1 unit in overhead costs, the predicted billable hours are estimated to increase by bo OC. It is not appropriate to interpret by. because its value is the predicted…
The table shows the lengths and weights of seven muskies captured by the Department of Natural Resources in Catfish Lake in Eagle River, Wisconsin. Use the linear regression feature on a graphing calculator to determine an equation of the line that best fits the data. Round to the hundredths. Musky 1 2 3 4 5 6 7 Length (in.) 26 27 29 33 35 36 38 Weight (lb) 5 8 9 12 14 14 19
Used cars 2010 Vehix.com offered several used ToyotaCorollas for sale. The following table displays the ages ofthe cars and the advertised prices. a) Make a scatterplot for these data.b) Do you think a linear model is appropriate? Explain.c) Find the equation of the regression line. d) Check the residuals to see if the conditions for infer-ence are met. Age (yr) Price ($) Age (yr) Price ($)1 15988 6 99951 13988 6 119882 14488 7 89903 10995 8 94883 13998 8 89954 13622 9 59904 12810 10 41005 9988 12 2995
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 924 1150 840 1166 1087 930 Temperature (°F) 77.5 84.6 74.1 91 79.6 79.7 What is the regression equation? What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? What is wrong with this predicted value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an approximation. An unrounded value would be considered accurate. D. Nothing is wrong with this value. It can be…
At an online diamond trader site, the price for a diamond is dependent upon the weight of the diamond. The pricing information is given in the table below. x: Weight (in carats) 0.5 0.6 0.7 0.8 0.9 1.0 y: Price (in dollars) 2600 3000 3500 3950 4800 5700 a) Find the linear regression equation for this data where x is the weight of a diamond (in carats) and y is the corresponding price of the diamond (in $). The slope and y-intercept for the linear regression equation are as follows: slope = Blank 1. Fill in the blank, read surrounding text. y-intercept = Blank 2. Fill in the blank, read surrounding text. b) Use the linear regression equation to estimate the price of a diamond that weighs 0.65 carats. Blank 3. Fill in the blank, read surrounding text. dollars (Do not use the $ sign in the answer box.)
In the graph shown below consider the horizontal line to represent the average y value for the data set and the slant line to represent the linear regression equation. use only the graph of the data to do the following:
The average top ticket price for Broadway musicals has increased dramatically between 1975 and 2003. 1985 1998 2000 2003 72.83 118.97 130.15 44.99 Year Average Ticket Price 1975 13.63 a. Using the data in the table, find the linear regression equation that best fits the data. (Let x = 0 represent the number of years since 1970.) y = (Round values to three decimal places.) b. Predict the average top ticket price for Broadway musicals in the year 2012 if the price continues to increase at the same rate. (Let x represent the number of years since 1970.) (Round to two decimal places.) c. Find the rate at which the price is rising. per year (Round to two decimal places.)

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