The following data were collected in an experiment to study the relationship between extrusion pressure (in KPa) and wear (in mg). x 150 175 y 10.4 12.4 200 14.9 225 250 275 15 13.9 11.9 The least-squares quadratic model is y = -32.44571429 +0.43154286x - 0.00098286x2. Compute the coefficient of determination R2. (Round the final answer to five decimal places.)
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- 3. Fit a least squares quadratic curve to the following data and estimate Y at X = 2.4 fig. 03 2 3. 4. గోలిగౌజి రర్ Y 1.7 1.8 2.3 2.3 A. The required least squares quadratic curve(parabola) and the estimated value of Y at X=2.4? * 大 O Y= 2- 0.5X + 0.2X^2; Y = 1.952 Y= 2-0.6X+ 0.2X^2; Y = 1.712 O Y= 2.1 - 0.5X + 0.2X^2;Y = 2.052 Y= 2- 0.5X + 0.4X^2; Y = 3.104A representative sample of 190 students resulted in a regression equation between y = left hand spans (cm) and x = right hand spans (cm). The least squares regression equation is y = 1.4 + 0.97 x. For a student with a right and left hand span of 24 cm, what is the value of the residual? Give your answer to 2 decimal places.The scatter plot below shows data for the average cost of a high-end computer (y, in dollars) in the year x years since 2000. The least squares regression line is given by yˆ=−1677+314x. A coordinate plane has a horizontal x-axis labeled Year from 4 to 12 in increments of 2 and a vertical y-axis labeled Cost in dollars from 0 to 2000 in increments of 500. The following points are plotted: left-parenthesis 6 comma 250 right-parenthesis, left-parenthesis 7 comma 550 right-parenthesis, left-parenthesis 9 comma 1000 right-parenthesis, left-parenthesis 10 comma 1300 right-parenthesis, and left-parenthesis 11 comma 2000 right-parenthesis. A line rises from left to right, passing through left-parenthesis 7 comma 550 right-parenthesis and left-parenthesis 10 comma 1500 right-parenthesis. All coordinate are approximate. Interpret the y-intercept of the least squares regression line. Select the correct answer below: The predicted cost of a computer in the year 0 is…
- The following data shows the atmospheric pollutants yi(relative to an EPA standard) at half hour interval xi. Find the equation y=a+bx of the least square line that best fits the data points given by 2,1, 5,2, 7,3, 8,3. Hence predict the atmospheric pollutant at x=6 half hour.The peanut crop was harvested from five fields of various area. The following data are the mass of the crop from each field y (in kilograms) and the field area x (in hectares). X 6² Round your intermediate answers to four decimal places (e.g. 98.7654). (a) Fit the simple linear regression model using the method of least squares. Find the estimate of ². Round your answer to the nearest integer (e.g. 9876). i B₁ = (b) What change in the mean mass is expected when the field area changes by 1 hectare? Round your answer to the nearest integer (e.g. 9876). ŷ: 7280 15730 13590 19820 12860 = 2.01 3.93 3.68 4.33 2.33 (c) Calculate the fitted value of y corresponding to x = 2.01. Find the corresponding residual. Round your answer to the nearest integer (e.g. 9876). =Data on alcohol content and wine quality was collected from variants of a particular wine. From a sample of 46 wines, a model was created using the percentages of aloohol to predict wine quality Y-0.337 +0.5635X,, where X, in the alcohol content (%) and Y, is the rated quality of the wine. For these data, Syx 0.9316, X 10.63, and h 0.027260 when X 10. Complete parta (a) throi a. Construct a 05% confidence interval estimate of the mean wine quality rating for all wines that have 10% alcohol. 4.988 spypx= 10 s 5.608 (Type integers or decimals. Round to three decimal places as needed. Use ascending order) b. Construct a 95% prediction interval of the wine quality rating of an individual wine that has 10% alcohol. (Type integers or decimals. Round to three decimal places as needed. Use ascending order.)
- Lulu Hypermarket has a record showing data on sales per year (in thousands of rials) and advertisement (in hundreds of rials) for the last five years. The record gives the following details. EX = 132 ΣΧ3,502 EY = 96 EY² = 1,870 ΣΧΥ-2,553 a. Please develop the least squares estimated regression line. b. Using your regression line developed in Part a, predict the sales when advertisement is $3,000. c. At a = 0.05, determine if advertisement and sales are related (perform a t test). d. Develop a 95% confidence interval for estimating the mean sale for those years when advertisement was $3,000. e. Compute the coefficient of determination. ||The data in the accompanying table include the appraised value, land area of the property in acres, and age, in years, for a small sample of 30 single-family homes in a small city. Perform a multiple regression analysis to predict appraised value based on land area of the property X1 and age, in years, X2 and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity? Determine the VIF for each independent variable in the model.A study was conducted to assess the relationship between students’s score in final exam (y) and number of hours spent for exam (x) in each day. Data on a random sample 20 students were obtained and a regression model was estimated; and the least squares estimates obtained are: intercept a=28.5 and slope b=4.3 with SE(b)=Sb=0.017. The SS are: TSS=2540 and ESS=850. ****** QA) What is the difference between exam score obtained by two students one who studied 5 hours and the other who studied 9 hours per day. QB) In the above Question 1, find 95% CI for the slope and interpret it. In the above Question 1, find and interpret the coefficient of determination (r-square value).
- Arm circumferences (cm) and heights (cm) are measured from randomly selected adult females. The 139 pairs of measurements yield x = 31.99 cm, y = 163.33 cm, r= 0.032, P-value = 0.708, and y = 158 + 0.1703x. Find the best predicted value of y (height) given an adult female with an arm circumference of 35.0 cm. Let the predictor variable x be arm circumference and the response variable y be height. Use a 0.05 significance level. %3D ..... The best predicted value is cm. (Round to two decimal places as needed.)Please helpLulu Hypermarket has a record showing data on sales per year (in thousands of rials) and advertisement (in hundreds of rials) for the last five years. The record gives the following details. ΣΧ132 EX? = 3,502 ΣΥ- 96 EY? = 1,870 EXY = 2,553 a. Please develop the least squares estimated regression line. b. Using your regression line developed in Part a, predict the sales when advertisement is $3,000. c. At a = 0,05, determine if advertisement and sales are related (perform a t test). d. Develop a 95% confidence interval for estimating the mean sale for those years when advertisement was $3,000. e. Compute the coefficient of determination. nited States) Dadds lcaded succesfuly hp 10 4+ 144 %23 %24 4. 3. & 7. V. 6. 8. 6. Y P. 1. K L 17 1- 5 LI 37