(d) Develop an estimated regression equation for the data of the form ý=ŷ= 162 +11.8x - 0.171xX(e) Use the results from part (d) to test for a significant relationship between x, x², and y. Use a = 0.05. Is the relationship between x, x², and y significant?Find the value of the test statistic. (Round your answer to two decimal places.)Find the p-value. (Round your answer to three decimal places.)p-value =bo + b₁x + b₂x². (Round b to one decimal place and b₁ to two decimal places and b₂ to four decimal places.)01Is the relationship between x, x², and y significant?Yes, the relationship is significant.No, the relationship is not significant.(f) Use the model from part (d) to predict the value of y when x = 25. (Round your answer to three decimal places.)128.725 X Consider the following data for two variables, x and y.Xy22 24 26 30 35 4013 2033 34 40 35(a) Develop an estimated regression equation for the data of the form ŷ = bỏ + b₁x. (Round bo to one decimal place and b₁ to three decimal places.)ŷ -5.5+ 1.175x(b) Use the results from part (a) to test for a significant relationship between x and y. Use a = 0.05.Find the value of the test statistic. (Round your answer to two decimal places.)F = 6.49Find the p-value. (Round your answer to three decimal places.)p-value = 0.063Is the relationship between x and y significant?Yes, the relationship is significant.No, the relationship is not significant.

Answered: Image /qna-images/answer/147cc6f4-4709-4eeb-b1d9-b4bd5c45553e.jpg

Answered: Consider the following data for two…

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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Consider the following data for two variables, x and y x 9 32 18 15 26 y 9 20 22 17 23 A. Develop an estimated regression equation for the data of the form ŷ = b0 + b1x. (Round b0 to two decimal places and b1 to three decimal places.) B. Develop an estimated regression equation for the data of the form ŷ = b0 + b1x + b2x2. (Round b0 to two decimal places and b1 to three decimal places and b2 to four decimal places.) C. Use the model from part (b) to predict the value of y when x = 20. (Round your answer to two decimal places.) Please be as detailed as possible in the solution so i may follow along. Thank you for the help!
The accompanying data are the length (in centimeters) and girths (in centimeters) of 12 harbor seals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a)x= 140 cm (b)x= 172 cm (c) x = 164 cm (d) x = 158 cm Click the icon to view the table of lengths and girths. The equation of the regression line is y=x+7 (Round to two decimal places as needed.). 4
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
The table shows the numbers of new-vehicle sales (in thousands) in the United States for Company A and Company B for 10 years. The equation of the regression line is y = 0.991x + 1,222.81. Complete parts (a) and (b) below. D New-vehicle sales (Company A), x New-vehicle sales (Company B), y 4,149 3,923 3,566 3,400 3,266 3,076 2,868 2,485 1,952 2,066 4,912 4,871 4,827 4,721 4,672 4,474 4,684 3,822 2,956 2,754 (a) Find the coefficient of determination and interpret the result. 12²=0 (Round to three decimal places as needed.) 1
Find the multiple regression equation with weight as the response variable and the dummy variable of sex and the variable of age as the explanatory variables.
You are given the following data, where X1 (final percentage in math class) and X2 (number of absences) are used to predict Y (standardized math test score in third grade): Y X1 X2 345 70 390 80 1 370 75 4 375 92 400 82 350 70 3 310 61 5 420 80 375 88 3 410 72 1 485 99 300 65 7 Determine the following multiple regression values. Report intercept and slopes for regression equation accurate to 3 decimal places: Intercept: a = Partial slope X1: bị = Partial slope X2: bz = Report sum of squares accurate to 3 decimal places: SSreg Test the significance of the overall regression model (report F-ratio accurate to 3 decimal places and P-value accurate to 4 decimal places): F-ratio = P-value = Report the variance of the residuals accurate to 3 decimal places: Sres = Report the results for the hypothesis test for the significance of the partial slope for final percentage in math class (report the test statistic for the regression coefficients accurate to 3 decimal places and P-value accurate to…
A set of n = 25 pairs of scores (X and Y values) produces a regression equation Y = 3X – 2. Findthe predicted Y value for each of the following X scores: 0, 1, 3, -2.
Data from 147 colleges from 1995 to 2005 (Lee,2008) were tested to predict the endowments (in billions) to a college from the average SAT score of students attending the college. The resulting regression equation was Y = -20.46 + 4.06 (X). This regression indicates that: a. for every one-point increase in SAT scores, a college can expect 4.06 billion more in endowments. b. most colleges have very high endowments. c. for every one-point increase in SAT scores, a college can expect 20.46 billion fewer in endowments. d. for every one-dollar increase in endowments, the college can expect a half-point increase in SAT scores.
The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, y = bo + b₁x. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 66 68 71 86 78 85 62 82 79 61 Grades on Final 90 63 82 96 72 83 79 91 84 65
A supermarket has a chain of 12 stores in Kuwait. Sales figures and profits for the stores are given in the following table. Obtain a regression equation for the data, and predict profit for a store assuming sales of $20 million. Show all calculations in detail. Sales, x (in millions of dollars) Profits, y (in millions of dollars) 7 0.12 2 0.1 6 0.13 12 0.15 14 0.25 16 0.2 10 0.24 12 0.2 14 0.27 20 0.15 7 0.34 8 0.17
The mortality rate of a sample of the population as a function of daily tobacco consumption can be seen below: Number of cigarettes "x": 3 5 6 15 20 Mortality rate "y" : 0.2 0.3 0.4 0.5 0.7 With these data, solve the following: a. Determine and interpret the correlation coefficient. b. Find the regression line of y on x. c. What will be the mortality rate for a consumer of 40 cigarettes per day?
The City of Bellmore’s police chief believes that maintenance costs on high-mileage police vehicles are much higher than those costs for low-mileage vehicles. If high-mileage vehicles are costing too much, it may be more economical to purchase more vehicles. An analyst in the department regresses yearly maintenance costs (Y) for a sample of 200 police vehicles on each vehicle’s total mileage for the year (X). The regression equation finds: Y = $50 + .030X with a r2 of .90 What is the IV? What is the DV? If the mileage increases by one mile, what is the predicted increase in maintenance costs? If a vehicle’s mileage for the year is 50,000, what is its predicted maintenance costs? What does an r2 of .90 tell us? Is this a strong or weak correlation? How can you tell?

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