3. Given are five observations collected in a regression study on two variables.Xi1326920Yi7 18 918926 23a. Develop a scatter diagram for these data.b. Develop the estimated regression equation for these data.C.Use the estimated regression equation to predict the value of y when x = 6.

Solution-: Given data: X: 2,6,9,13,20 Y: 7,18,9,26,23 Our aim to find (a) Draw the scatter diagram…

Answered: 3. Given are five observations…

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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c) Show that the coefficient of determination, R², can also be obtained as the squared correlation between actual Y values and the Y values estimated from the regression model where Y is the dependent variable. Note that the coefficient of correlation between Y and X is Eyixi r = And also that ỹ = ŷ (18.75)
9. Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x Sodium, y 160 130 330 120 70 190 (a) x = 170 calories (c) x = 150 calories 180 (b) x = 80 calories 420 470 360 250 530 (d) x = 210 calories Find the regression equation. x+( (Round to three decimal places as needed.) y = Choose the correct graph below. OA. О В. OC. OD. 560- 560 560 560- 200 G 0IN T> 200 200 Calories Calories Calories Calories (a) Predict the value of y for x = 170. Choose the correct answer below. O A. 411.632 O B. 543.752 O C. 455.672 O D. not meaningful (b) Predict the value of y for x = 80. Choose the correct answer below. O A. 411.632 О В. 257.492 O C.…
1. Correlation analysis is used to determine the equation of the regression line b. a specific value of the dependent variable for a given value of the independent variable the strength of the relationship between the dependent and the independent variables d. a. с. None of these alternatives is correct.
5. For the following set of data: Y 1 10 5 4 4 13 a. Find the regression equation for predicting Y from X. b. Does the regression equation account for a significant portion of the variance in the Y scores? Use a = .05 to evaluate the F-ratio %3D X27 33
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. Xx Y 11.8 14.1 11.5 9.8 7.1 6.2 6.5 x = thousands of automatic weapons y = murders per 100,000 residents 8.6 7 3.3 2.5 2.5 2.6 6 This data can be modeled by the equation y = 0.85x +4.07. Use this equation to answer the following; Answer decimal places. = A) How many murders per 100,000 residents can be expected in a state with 1.2 thousand automatic weapons? Answer = decimal places. Round to 3 0.9 4.7 B) How many murders per 100,000 residents can be expected in a state with 8.5 thousand automatic weapons? Round to 3
I. Show complete solutions. Simple Linear Regression and Correlation: a.) Results of a study on the occurrence of sodium and chloride in surface streams in a coastal area. The following data are chloride concentration (y) in mg/liter and road-way area in the watershed (x) in %. Y 0.24 4.6 1. What is the value of the correlation coefficient? 2. What is the interpretation for this case? 3. What is the estimated chloride concentration if road way 0.3 6.4 0.45 9.8 area in the watershed is 1.30% 0.75 10.7 4. What is the equation of the prediction line? 0.57 10.6 0.75 10.9 0.4 11.7 0.8 12.5 0.6 14 0.78 14.7 0.85 15.1 0.68 18.3 0.69 19.2 1.4 23.1 1.15 27.3 1.05 27.7 1.69 32 1.62 38.4
The following table contains ACT scores and the GPA for eight college students. Estimate the relationship between GPA (yi) and ACT (x;) using OLS regression by hand. Report the intercept and slope estimates: Student 1 2 3 4 5 6 7 8 GPA 2.8 3.4 3.0 3.5 3.6 3.0 2.7 3.7 ŷ₁ =B₁ + B₁x₁ ACT 21 24 26 27 29 25 25 30 y X ŷ₁
Below are the results of Multiple Regression Analysis. Write down the interpretation of the following tables: R Model R Square .560a .314 Change Statistics F Change df1df2 1 .314 7.210 9 142 a. Predictors: (Constant), Horsepower, Wheelbase, Fuel efficiency, Width, Price in thousands, Fuel capacity, Length, Engine size, Curb weight b. Dependent Variable: Sales in thousands Adjusted R Square Model Summaryb .270 Std. Error of the Estimate 58.895390 R Square Change Sig. F Change .000
Consider the following data,Study Hours (Y): 2, 4 ,6 ,8 ,10 ,13, 7Sleeping Hours (X): 10, 9, 8, 7,6 ,7, 5 i) Calculate and analyze the fitted regression line between the number of study hours and the number of sleeping hours of different intakes of CSE students.ii) Find the coefficient of determination and interpret your data.iii) Predict study hour when he/she sleeps 11 hours.
A Moving to another questiof! Question 27 ry .dock Provide an appropriate response. In order for applicants to work for the foreign-service department, they must take a test in the language of the country where they plan to work. The data below shows the relationship between the number of years that applicants have studied a particular language and the grades they received on the proficiency exam. Find the equation of the regression line for the given data. DOCK tigation n.Lab Number of years, x Grades on test, y O - 6.910x- 46.261 reen Shot --05...3.58 PM O = 46.261x + 6.910 O = 46.261x -6.910 O - 6,910x + 46.261 Sterling's Daily Food Log.pdt W A Moving to another question will save this response. arling's lntakeS Question 27 of 28 > Goals Ans and Outs of Energy (1).docx Screen Shot 22-059.03 AM Screen 2022-05 AM Screen Shot x 2022-05.9.31 AM 2022-05.0.09 Screen Sho

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3. Given are five observations collected in a regression study on two variables. 2 6 9 13 20 Yi 7 18 9 26 23 a. Develop a scatter diagram for these data. b. Develop the estimated regression equation for these data. C. Use the estimated regression equation to predict the value of y when x = 6.