(i)Consider the bivariate data set in the table below.3.65.97.03.41.24.45.22.25.03-23.91.06.25.72.38.2Find the equation of the regression line for this data, giving coefficients correctto 2 decimal places.(a)Calculate Pearson's correlation coefficient r for this data, and use is to statewhether or not the regression line found in part (a) is reliable for predictingpossible data pairs (x, y) close to the given data, giving a brief reason.(b)

a) Excel Procedure: Enter X and Y in Excel>Data>Data Analysis> ‘Regression’>Select Y…

Answered: Consider the bivariate data set in the…

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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Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r = -0.338 Calculate the coefficient of determination. (Round to three decimal places as needed.) % of the variation can be explained by the regression line (Round to one decimal place as needed.) % of the variation is unexplained and is due to other factors or to sampling error. (Round to one decimal place as needed.)
Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r= - 0.884 Calculate the coefficient of determination. (Round to three decimal places as needed.)
A corporation has asked you to prepare some multiple regression equations to estimate the effect of variables on fuel economy. The data for this study are shown below, and the dependent variable is miles per gallon. Complete parts a and b. Miles 43.3 Horsepower 50 Weight 1985 36.3 67 1885 32.7 51 1990 + ŷ =) ()×₁ + ( )×₂ (Round to four decimal places as needed.) 39.5 72 2090 36 62 1880 19.2 110 3370 19.1 142 3775 20.9 136 3560 19.9 101 3165 a. Prepare a regression equation that uses vehicle horsepower and vehicle weight as independent variables. Let x₁ be defined as horsepower and x₂ be defined as weight. 20.8 94 2720
On-base percentage plus slugging (OPS) is a statistic used in baseball to measure a team's batting success. The number of runs scored and OPS for 30 baseball teams was used to conduct a linear regression analysis. The scatterplot and computer output for the regression analysis is shown. 900- 850- 800- Number of 750- Runs Scored 700- 650- 600- 0.650 0.675 0.700 0.725 0.750 0.775 0.800 OPS Term Coef SE Coef Constant -838.40 77.99 OPS 2144.3 107.1 T-Value -10.75 20.01 P-Value <0.0001 < 0.0001 S = 19.516 R-Sq = 93.47% R-Sq(adj) 93.23% Which of the following is the most appropriate interpretation of the statistic 93.47% in the regression output? (A) There is a strong, positive, linear relationship between number of runs scored and OPS. (B) The typical deviation between observed and predicted number of runs scored is 0.9347. (C) For each one-unit increase in OPS, the regression model predicts an increase of 93.47 runs scored. (D) 93.47% of the observed number of runs scored are close to the…
894c3d916%#10001 MAT 213 OL1 Elementary Statistics Shayjunna Jones &| 0| 02/03/21 4:56 PM Homework: Homework 3 Save Score: 0 of 3 pts 17 of 20 (3 complete) ▼ HW Score: 10%, 6 of 60 pts 4.2.50 Question Help v Use the given data to do the following. a. Find the regression equation for the data points. b. Graph the regression equation and the data points. 4 3 y 4 -1 9 3 a. Find the regression equation for the data points. y = (Round to two decimal places as needed.) Enter your answer in the answer box and then click Check Answer. Check Answer 1 part remaining Clear Al 4:56 PM 2/3/2021 Cip
The number of initial public offerings of stock issued in a 10-year period and the total proceeds these offerings (in millions) are shown in the table. The equation of the regression line is y = 43.977x+ 19,528.57. Complete parts a and b. 379 55 18,716 29,004 42,559 30,325 67,231 65,155 21,100 12,473 31,455 27,712 Issues, x 424 457 695 500 499 74 180 158 Proceeds. (a) Find the coefficient of determination and interpret the result. (Round three decimal places as needed.)
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states, where is thousands of automatic weapons and y is murders per 100,000 residents. 11.6 8.4 6.8 3.7 2.8 2.6 2.6 0.8 y 13.7 10.9 9.7 7.1 6.4 6.3 5.9 4.4 Use your calculator to determine the equation of the regression line and write it in the y = a + bx form. Round to 2 decimal places. According to this model, how many murders per 100,000 residents can be expected in a state with 2.4 thousand automatic weapons? Round to 3 decimal places. According to this model, how many murders per 100,000 residents can be expected in a state with 3.7 thousand automatic weapons? Round to 3 decimal places.
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x Test score, y 4 (a) x = 2 hours (c) x = 13 hours (b) x= 2.5 hours (d) x = 4.5 hours 2 3 5 40 45 52 49 63 70 Find the regression equation. ý =x+ (O (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O A. OB. OC. OD. 80- 80- Hours studying Hours studying Hours studying Hours studying (a) Predict the value of y for x= 2. Choose the correct answer below. O A. 52.2 О В. 49.2 ОС. 64.2 O D. not meaningful (b) Predict the value of y for x = 2.5. Choose the correct answer below. O A. 115.4 О В. 52.2…
A physician wishes to know whether there is a relationship between a father’s weight (in pounds) and his new born sons’ weight (in pounds). The data are given here Fathers Weight 176 145 187 210 196 142 205 215 152 145 Sons Weight 6.6 8.2 9.2 7.1 8.8 9.3 7.1 8.6 7.8 6.0 Develop the regression equation for the sample Predict the sons weight based on the father’s weight of 300, 250 and 400.
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x 11.3 8.5 y 13.4 7 3.6 2.6 2.2 2.6 0.8 11 10.2 7.4 6 5.7 6.3 4.9 * = thousands of automatic weapons y = murders per 100,000 residents Determine the regression equation in y = ax + b form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 10.1 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 9.9 thousand automatic weapons? Answer = Round to 3 decimal places.
An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.
The table below shows (lifetime) peptic ulcer rates (per 100 population), UU, for various family incomes, xx, as reported by the 1989 National Health Interview Survey. Income 4000 6000 8000 12000 16000 20000 30000 45000 60000 Ulcer rate 14.1 13.1 13.8 12.6 11.8 11.7 11.5 9.3 7.6 (a) Find the equation of the regression line. Ulcer rate, U(x)= . (b) Estimate the peptic ulcer rate for an income level of x0= 25000 according to the linear model in part (a). Ulcer rate, U(x0)= .

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Consider the bivariate data set in the table below. 3.6 5.9 3.9 5.0 1-2 2-3 8-2 7.0 4-4 3-4 2.2 y 3-2 1.0 5-2 6-2 5.7 Find the equation of the regression line for this data, giving coefficients correc to 2 decimal places. (a)