The following data were used in a regression study. Observation 1 2 3 4 5 6 7 8 9 xi 2 3 4 5 7 7 7 8 9 yi 4 5 4 7 4 6 9 5 11 (a) Develop an estimated regression equation for these data. (Round your numerical values to two decimal places.) ŷ =

The following data were used in a regression study. Observation 1 2 3 4 5 6 7 8 9 xi 2 3 4 5 7 7 7 8 9 yi 4 5 4 7 4 6 9 5 11 (a) Develop an estimated regression equation for these data. (Round your numerical values to two decimal places.) ŷ =

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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Observation	1	2	3	4	5	6	7	8	9
x_i	2	3	4	5	7	7	7	8	9
y_i	4	5	4	7	4	6	9	5	11

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Listed below are the numbers of commuters and the number of parking spaces at different Metro-North railroad stations. Use technology (calculator) to help you answer the following, and round to the 3 decimal places where rounding is necessary. . a. Find the linear regression line y = a + bx. b. Are the variables positively or negatively related? c. Find and interpret r2. Make sure to include what it means specific to this data set. d. Use your regression line to make a prediction for the number of parking spaces for a station with 900 e. Identify and interpret the slope of the linear model.
KidsFeet Regression Line y-Intercept The KidsFeet dataframe contains data collected on 39 fourth grade students in Ann Arbor, MI, in October 1997. Two of the measurements taken on the children were the length in centimeters, (length), and width in centimeters, (width), of their longest foot. This data could be used to answer the following Research Question: How is the width of a fourth-grade student's foot related to the length? Which of the following is the y-intercept of the regression line? ## ## Simple Linear Regression## ## Correlation coefficient r = 0.6411 ## ## Equation of Regression Line:## ## length = 9.817 + 1.658 * width ## ## Residual Standard Error: s = 1.025 ## R^2 (unadjusted): R^2 = 0.411 ( ) 1.0248 ( ) 1.6576 ( ) 22.8153 ( ) 0.411 ( ) 9.8172 ( )0.6411
The following data are the monthly salaries y and the grade point averages x for students who obtained a bachelor's degree in business administration. GPA 2.6 3.4 3.6 3.2 3.5 2.9 Monthly Salary ($) 3,500 3,900 4,200 3,800 4,200 3,900 The estimated regression equation for these data is ý = 1,970.72 + 608.11x and MSE = 18,671.17. (a) Develop a point estimate of the starting salary (in dollars) for a student with a GPA of 3.1. (Round your answer to the nearest cent). (b) Develop a 95% confidence interval for the mean starting salary (in dollars) for all students with a 3.1 GPA. (Round your answers to the nearest cent). to $ (c) Develop a 95% prediction interval (in dollars) for Ryan Dailey, a student with a GPA of 3.1. (Round your answers to the nearest cent). to $
The following data were used in a regression study. Observation 1 2 3 4 5 6 7 8 9 xi 2 3 4 5 7 7 7 8 9 yi 3 5 4 5 4 6 9 6 11 (a) Develop an estimated regression equation for these data. (Round your numerical values to two decimal places.) ŷ = ?? (b)Construct a plot of the residuals. A residual plot has 9 points plotted on it. The horizontal axis ranges from 0 to 10 and is labeled: x. The vertical axis ranges from −4 to 4 and is labeled: Residuals. There is a horizontal line that spans the graph at 0 on the vertical axis. 5 points lie below the line and 4 lie above it. The points tend to become closer to the line as x increases. The approximate locations of the points are: (2, 2.6), (3, −1.6), (4, 2.2), (5, −0.8), (7, −2.8), (7, −0.3), (7, −0.5), (8, 1.3), (9, 0.1). A residual plot has 9 points plotted on it. The horizontal axis ranges from 0 to 10 and is labeled: x. The vertical axis ranges from −4 to 4 and is labeled: Residuals. There…
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Which of the following is the most appropriate equation to model the data? ŷ = –10.89x + 0.85 ŷ = –0.85x + 10.89 ŷ = 10.89(0.85)x ŷ = 0.85(10.89)x
You may need to use the appropriate appendix table or technology to answer this question. The following data are the monthly salaries y and the grade point averages x for students who obtained a bachelor's degree in business administration. Monthly Salary ($) GPA 2.6 3,600 3.4 3,900 3.6 4,300 3.2 3,800 3.5 4,300 2.9 3,900 The estimated regression equation for these data is ŷ = 1,977.48 + 621.62x and MSE = 26,846.85. (a) Develop a point estimate of the starting salary (in dollars) for a student with a GPA of 3.0. (Round your answer to the nearest cent). 2$ (b) Develop a 95% confidence interval for the mean starting salary (in dollars) for all students with a 3.0 GPA. (Round your answers to the nearest cent). $ to $ (c) Develop a 95% prediction interval (in dollars) for Ryan Dailey, a student with a GPA of 3.0. (Round your answers to the nearest cent). $ to $
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 130 130 350 370 150 (a) x 160 calories (b)x= 100 calories Sodlum, y (c) x 140 calories (d) x=200 calories Find the regression equation. (Round to three decimal places as needed.) Choose the correct graph below. OA 560 Q Q 200 G Calories (a) Predict the value of y for x = 160. Choose the correct answer below. OA. 393.094 OB. 440.954 OC. 536.674 OD. not meaningful (b) Predict the value of y for x= 100. Choose the correct answer below. OA 297.374 OB. 536.674 OC. 393.094 OD. not meaningful (c) Predict the value of y for x = 140. Choose the correct answer below. OA 297.374 OB.…
The invasive diatom species Didymosphenia geminata has the potential to inflict substantial ecological and economic damage in rivers. An article described an investigation of colonization behavior. One aspect of particular interest was whether y = colony density was related to x = rock surface area. The article contained a scatterplot and summary of a regression analysis. Here is representative data. x 50 71 55 50 33 58 79 26 y 157 1934 53 27 7 10 40 12 x 69 44 37 70 20 45 49 y 274 43 176 18 48 190 30 (a) Fit the simple linear regression model to this data. (Round your numerical values to three decimal places.) y = Predict colony density when surface area = 70 and calculate the corresponding residual. (Round your answers to the nearest whole number.) colony density corresponding residual Predict colony density when surface area = 71 and calculate the corresponding residual. (Round your answers to the nearest whole number.) colony…
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
The following data shows memory scores collected from adults of different ages. Age (X) Memory Score (Y) 25 10 32 10 39 9 48 9 56 7 Use the data to find the regression equation for predicting memory scores from age. The regression equation is: Ŷ = 4.33X + 0.11 Ŷ = -0.11X + 4.33 Ŷ = -0.11X + 13.26 Ŷ = -0.09X + 5.4 Ŷ = -0.09X + 12.6 Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 28 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 43 For the calculations, leave two places after the decimal point and do not round: Use the regression equation you found in question 6 to find the predicted memory scores for the following age: 50 For the calculations, leave two places after the decimal point and do not round:
For a group of 20 students taking a PSDTF test, the mean heart rate was 96 beats per minute, and the standard deviation was 5. Find the 95% confidence interval of the true mean.