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Problem 1 (14 marks ) As a solution for improving quality consistency , a Six Sigma team suggested to a TV manufacturer to change the

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Problem 1 (14 marks ) As a solution for improving quality consistency , a Six Sigma team suggested to a TV manufacturer to change the supplier of a particular electronic board. The engineering department requires that the standard deviation of voltage of boards in each lot be less than or equal to (1.4 volt in order to accept it. A lot including 18 boards was delivered from a new supplier and the voltages of boards were measured. The average and standard deviation of sampled voltages were then calculated as 4 and 0.43, respectively. Assuming that the voltage of boards follows a normal distribution and based on the measured voltage from the delivered lot, answer to the following questions? 1) At a 95% confidence level, can the team recommend the new supplier to the company? (Describe the null and alternative hypotheses}. 2) Calculate the pvalue of your test and analyze your answer in (1), accordingly Problem 2 (16 marks ) Based on the Regression Analysis displayed below [with 5% significance level}, answer to the following questions: WmmmmmumMMwmmnn-am.mum. mlvlll a: Venue. Source n! m 55 M3 115 IVlllu bikini Recreation 2 3171.." 1585.92 1308.10 13.000 Hort 8:\" III: 1 302.15 392.45 322.\" 0.000 29! or m. 1. 2110.39 2719.20 2202.\" 0.000 Error 21 32.66 1.22 LICK-0241.1: 20 27.36 1.11 0.02 0.206 hare Error 3 5.50 1.8! 20:11 2! 320'.\" llbdll Sun-y 3 lt-sq l-IqudJl 11-"!le 1.10319 \".0?! 00.001 00.1\" Count-nan tun Court St Coo: 1-1!an 2-9311 VII Constant 122.03 2.25 43.01 0.000 Hort 130. I'll) -0.'H' 0.0359 47.\" 0.000 1.00 [a of man. 4.3m 0.0102 4.7.1, 0.000 1.00 aggression mtlll Hot Sauce Pm I 122.5! - c.5149 Ian kn rm - 3.351: no of Inch. 1) Identify the independent and response variables. What does the regression equation statistically indicate ? 2) Describe the null and alternative hypothesis in this regression analysis. 3) What RSq stands for? 4) Discuss whether or not the regression model is statistically significant based on the pvalue and RS

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