a) Determine sum of squares of error (SSE) and correlation coefficient (R?) for the model.b) Estimate the parameters of reaction model with 95% confidence limits.c) Evaluate the fit of the model equation you obtained to your data.d) Estimate concentration of flavor compound after 17 days of storage by using the best model.TimeConcentration(d)(mg/L)561.00569.673.252.11258.407.107.957.113.221047.771050.831523.801522.95239.352310.20

c) Excel Procedure: Enter Time and Concentration in Excel>Data>Data Analysis>…

Answered: a) Determine sum of squares of error…

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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To illustrate the effects of driving under the influence (DUI) of alcohol, a police officer brought a DUI simulator to a local high school. Student reaction time in an emergency was measured with unimpaired vision and also while wearing a pair of special goggles to simulate the effects of alcohol on vision. For a random sample of nine teenagers, the time (in seconds) required to bring the vehicle to a stop from a speed of 60 miles per hour was recorded. Complete parts (a) and (b). Note: A normal probability plot and boxplot of the data indicate that the differences are approximately normally distributed with no outliers. Click the icon to view the data table. (a) Whether the student had unimpaired vision or wore goggles first was randomly selected. Why is this a good idea in designing the experiment? A. This is a good idea in designing the experiment because it controls for any "learning" that may occur in using the simulator. B. This is a good idea in designing the experiment because…
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".† x 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651 y 334 342 355 363 365 372 381 392 400 412 420 Here is regression output from Minitab: Predictor Constant absorb S = 3.60498 Coef 321.878 156.711 SOURCE Regression Residual Error Total SE Coef 2.483 6.464 R-Sq = 98.5% DF 1 9 10 SS 7639.0 117.0 7756.0 T 129.64 24.24 0.000 0.000 R-Sq (adj) = 98.3% MS 7639.0 13.0 F P 587.81 (a) Does the simple linear regression model appear to be…
A methodological study had established values for the MIC on a scale that measured physical function: The MIC for improvement (higher scores) was 4.0, and the MIC for deterioration (lower scores) was 3.0. Lawrence studied clinically significant change in physical functioning over a 1-year period for a sample of 100 patients with COPD. Some change score information is presented below for 10 patients. Which patients experienced clinically significant change in physical function in the 12-month period between assessments? Patient Baseline Score* 12-Month Score* 1 19 15 2 12 10 3 16 14 4 17 16 5 9 10 6 11 12 7 13 17 8 15 13 9 18 14 10 16 9 *Higher scores = higher level of physical function Which patients had clinically significant deterioration? Which patients had clinically significant improvement? Which patients had no clinically significant change?
Find the least square regression line.
The least-squares regression equation is y=784.6x+12,431 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7962. In a particular region, 26.5 percent of adults 25 years and older have at least a bachelor's degree. The median income in this region is $29,889. Is this income higher or lower than what you would expect? Why?
The marketing manager wants to estimate the effect of the MBA program on Salary controlling for the other factors. Which regression model is the MOST appropriate? Oa. Salary = B_0+B_1 MBA + ε Ob. Salary = 3_0+ B_1 MBA + B_2 Work + e c. Salary = B_0+B_1 MBA+B_2 Work + B_3 Age +8 Od. Salary = B_0+ B_1 MBA + B_2 Work + B_3 Age +B_4 Gender + ε
The amounts of 6 restaurant bills and the corresponding amounts of the tips are given in the below. Assume that bill amount is the explanatory variable and tip amount the response variable. Bill 32.98 49.72 52.44 64.30 97.34 88.01 Tip 4.50 5.28 7.00 7.70 16.00 10.00 (a) Find the correlation: r= (c) The regression equation is y^= . (d) If the amount of the bill is $90, the best prediction for the amount of the tip is $ .Note: Enter your answer as a number xx.xx (e) According to the regression equation, for every $5 increase in the bill, the tip should INCREASE or DECREASE) by $ .

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