Wrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as determined by ester carboxyl band absorbance, improves the wrinkleresistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and y = wrinkle resistance angle was read from a graph in the paper "Predicting the Performance of Durable Press Finished Cotton Fabric withInfrared Spectroscopy".†x 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651y 334 342 355 363365 372 381 392400 412 420Here is regression output from Minitab:PredictorConstantabsorbS = 3.60498Coef321.878156.711SOURCERegressionResidual ErrorTotalSE Coef2.4836.464R-Sq = 98.5%DF1910SS7639.0117.07756.0T129.6424.240.0000.000R-Sq (adj) = 98.3%MS7639.013.0FP587.81(a) Does the simple linear regression model appear to be appropriate? Explain.Yes, a scatter plot of the data shows a strong, linear pattern, and r² = 98.5%.Yes, a scatter plot of the data shows a weak, linear pattern, and ² = 98.5%.O No, a scatter plot of the data shows a strong, linear pattern, and r² = 98.5%.O No, a scatter plot of the data shows a weak, non-linear pattern, and 2 = 98.5%.P0.000(b) What wrinkle resistance angle would you predict for a fabric specimen having an absorbance of 0.315? (Round your answer to two decimal places.)(c) What would be the estimate of the expected wrinkle resistance angle when absorbance is 0.315? (Round your answer to two decimal places.)

(a) Draw the scatterplot by using MINITAB. MINITAB Procedure: Step 1: Choose Graph > Scatter…

Answered: (a) Does the simple linear regression…

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter7: Analytic Trigonometry

Section7.6: The Inverse Trigonometric Functions

Problem 91E

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Wrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as determined by ester carboxyl band absorbance, improves the wrinkle resistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and y = wrinkle resistance angle was read from a graph in the paper "Predicting the Performance of Durable Press Finished Cotton Fabric with Infrared Spectroscopy".t 半 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651 334 342 355 363 365 372 381 392 400 412 420 Here is regression output from Minitab: Predictor Coef SE Coef P Constant 321.878 2.483 129.64 0.000 absorb 156.711 6.464 24.24 0.000 S = 3.60498 R-Sq = 98.5% R-Są (adj) - 98.3% SOURCE DF MS F P Regression 1 7639.0 7639.0 587.81 0.000 Residual Error 9 117.0 13.0 Total 10 7756.0 (a) Does the simple linear regression model appear to be…
Wrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as determined by ester carboxyl band absorbance, improves the wrinkle resistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and y = wrinkle resistance angle was read from a graph in the paper "Predicting the Performance of Durable Press Finished Cotton Fabric with Infrared Spectroscopy".t x 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651 y 334 342 355 363 365 372 381 400 392 412 420 Here is regression output from Minitab: Predictor Constant absorb S = 3.60498 Coef 321.878 156.711 SOURCE Regression Residual Error Total R-Sq= 98.5% DF SE Coef 2.483 6.464 1 9 10 SS 7639.0 117.0 7756..0 T 129.64 24.24 P 0.000 0.000. R-Sq (adj) 98.3% MS 7639.0 13.0 F 587.81 (a) Does the simple linear regression model appear to be appropriate?…
Arm circumferences (cm) and heights (cm) are measured from randomly selected adult females. The 146pairs of measurements yield x=34.69cm, y=163.25cm, r=0.075, P-value=0.368, and y=157+0.1826x. Find the best predicted value of y (height) given an adult female with an arm circumference of 40.0cm. Let the predictor variable x be arm circumference and the response variable y be height. Use a 0.05 significance level. The best predicted value is ____cm.
17.7 Butterfly wings. Researchers studied the morphological attributes of monarch butterflies (Danaus plexippus), a species that undertakes large seasonal migrations over North America. They measured the forewing weight (in milligrams, mg) of a sample of 92 monarch butterflies, all of which had been reared in captivity in identical conditions.° Figure 17.4 shows the output from the statistical software JMP. (The data are also available in the Large.Butterfly the data file if you wish to practice working with your own software.) Estimate with 95% confidence the mean forewing weight of monarch butterflies reared in captivity. Follow the four- step process as illustrated in Example 17.2. 4 STEP そMP FWweight 30 25 20 15 10 11 12 13 14 15 8 9 10 Summary Statistics Mean 11.795652 Std Dev 1.1759413 Std Err Mean 0.1226004 Upper 95% Mean Lower 95% Mean 1 FIGURE 17.4 Software output (JMP) for the forewing weight of monarch 12.039183 11.552122 92 N. butterflies. Count
Arm circumferences (cm) and heights (cm) are measured from randomly selected adult females. The 148 pairs of measurements yield x= 32.00 cm, y = 162.25 cm, r= 0.044, P-value = 0.596, and y = 159 +0.1111x. Find the best predicted value of y (height) given an adult female with an arm circumference of 32.0 cm. Let the predictor variable x be arm circumference and the response variable y be height. Use a 0.05 significance level. The best predicted value is cm. (Round to two decimal places as needed.)
Arm circumferences (cm) and heights (cm) are measured from randomly selected adult females. The 143 pairs of measurements yield x = 32.40 cm, y = 160.39 cm, r=0.072, P-value = 0.393, and y = 157 + 0.1075x. Find the best predicted value of y (height) given an adult female with an arm circumference of 34.0 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.) Enter your answer in the answer box. MacBook Pro 888 esc %24 % & 4. 9- E T. Y. H. K %#3
A sociologist investigating the recent upward shift in homicide trends throughout the country studied the extent to which the homicide rate per 100 000 people (v) is associated with population size in thousands (x ), the rate of unemployment (x,), and the percentage of families with annual incomes less than R24 000 (x3). Data are provided in the table for a sample of 20 cities. A regression analysis was performed on the data and the results indicated that the interaction model E(y) = B,+ Bx + Bx, + Bx; + B,xqx,+ B;xx; + Bzxzx; was a good model to fit to the data. %3D However, the residual plot for this model indicates that heteroscedasticity may exists for the percentage of families with annual incomes less than R24 000. How do I Conduct a test for heteroscedasticity by dividing the data into two subsamples, x,21 and x, > 21 using MSE for the first subsample = 582.3, MSE for the second subsample = 364.7 and a= 0.05. And how do I explain my conclusion.
I need help with part b, to plot the studentized residuals against x1,x2,and x3. Choose the correct graph
The relationship between yield of maize, date of planting, and planting density was investigated in an article. Let the variables be defined as follows. y = percent maize yield x = planting date (days after April 20) z = planting density (plants/ha) The following regression model with both quadratic terms where x₁ = x, X₂ = Z, X3 = x² and x4 = 2² provides a good description of the relationship between y and the independent variables. y =a +B₁x₁ + B₂X₂ + B3X3+B₁x₁ + e (a) If a = 21.07, B₁ = 0.653, B₂ = 0.0022, B3 = -0.0207, and B4 = 0.00002, what is the population regression function? y = 509 X (b) Use the regression function in Part (a) to determine the mean yield for a plot planted on May 7 with a density of 41,182 plants/ha. (Give the exact answer.) (c) Would the mean yield be higher for a planting date of May 7 or May 23 (for the same density)? The mean yield would be higher for [May 7 You may need to use the appropriate table in Appendix A to answer this question.
An experiment to compare the tension bond strength of polymer latex modified mortar (Portland cement mortar to which polymer latex emulsións have been added during mixing) to that of unmodified mortar resulted in x = 18.11 kgf/cm2 for the modified mortar (m = 42) and y = 16.88 kgf/cm2 for the unmodified mortar (n = 31). Let ₁ and ₂ be the true average tension bond strengths for the modified and unmodified mortars, respectively. Assume that the bond strength distributions are both normal. (a) Assuming that o₁ = 1.6 and ₂ = 1.3, test Ho: ₁ - ₂ = 0 versus H₂: H₁ - H₂> 0 at level 0.01. Calculate the test statistic and determine the P-value. (Round your test statistic to two decimal places and your P-value to four decimal places.) Z = P-value = State the conclusion in the problem context. O Fail to reject Ho. The data suggests that the difference in average tension bond strengths exceeds 0. Fail to reject Ho. The data does not suggest that the difference in average tension bond strengths…
An experiment to compare the tension bond strength of polymer latex modified mortar (Portland cement mortar to which polymer latex emulsions have been added during mixing) to that of unmodified mortar resulted in x = 18.18 kgf/cm2 for the modified mortar (m = 42) and y = 16.86 kgf/cm for the unmodified mortar (n = 30). Let µ1 and Hz be the true average tension bond strengths for the modified and unmodified mortars, respectively. Assume that the bond strength distributions are both normal. (a) Assuming that o1 = 1.6 and o2 = 1.3, test Ho: µ1 - 42 = 0 versus H3: µ1 – 42 > 0 at level 0.01. Calculate the test statistic and determine the P-value. (Round your test statistic to two decimal places and your P-value to four decimal places.) z = P-value = State the conclusion in the problem context. Fail to reject Ho: The data does not suggest that the difference in average tension bond strengths exceeds from 0. o Reject Ho: The data does not suggest that the difference in average tension bond…
A) In the screenshot i provided B) Does either explanatory variable improve the fit of the model that uses the other? Use a test statistic for each. Use α=0.05.

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