A research study investigated the composition of wines from the Rhine and Moselle wine regionsof Germany. One component measured was the concentration of i-Butyl alcohol. The results ofthe study are listed in the following table:Regioni-Butyl alcohol (mg/100ml)Rhinex = 5.32, s = 2.24Moselle14x = 3.62, s-0.97(a) Assume that the underlying population variances from the two regions are identical. At the0.05 level of significance, test the null hypothesis that the mean concentration of i-Butylalcohol is the same for wines from the Rhine and Moselle regions.(b) Construct a 95% confidence interval for part (a).(c) Now assume that the underlying population variances from the two regions differ. At the 0.05level of significance, test the null hypothesis that the mean concentration of i-Butyl alcohol isthe same for wines from the Rhine and Moselle regions.(d) Construct a 95% confidence interval for part (c).(e) Ifyou were to provide a report to the investigators which of the above results wouldyouinclude and why?

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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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The Minitab output shown below was obtained by using paired data consisting of weights (in Ib) of 27 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4500 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 27 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. Minitab output The linear correlation coefficient is. (Round to three decimal places as needed.) The regression equation is Highway = 50.4- 0.00535 Weight %3D Predictor Сoef SE Coef T Constant 50.383 2.732 17.75 0.000 Weight - 0.0053502 0.0007856 -7.55 0.000 S= 2.17876 R-Sq = 65.1% R-…
Suppose a car's city miles per gallon rating can be determined by the car's weight. The means and standard deviations of these variables and the correlation coefficient between them are reported in the following table: What proportion of the variability in cars' miles per gallon ratings is explained by the least squares line with weight?
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A company manufactures an electrical cooling fan. When the fans are performing properly, samples of 200 fans average 12.5 watts with an average range of 1.2 watts. A 3σ control chart program is being used to monitor the performance of the fans, and these data from the 10 most recent samples were collected: Sample Number Sample Mean Sample Range 1 12.5 1.1 2 12.45 1.2 3 12.55 0.9 4 12.50 0.8 5 12.45 0.9 6 12.60 1.0 7 12.48 1.4 8 12.46 1.1 9 12.56 0.9 10 12.48 0.8 Compute the 3σ control limits and center line for an ⁻x chart. Compute the 3σ control limits and center line for an R chart. Plot the sample data on the ⁻x and R charts and decide if the performance of the fan is in control.
In a research setting, the efficiency of homecare workers (part-time and full-time) were compared. Data is given below. Is there a difference between full-time and part-time homecare workers? (Variances are assumed to be homogenous, α=0.05). Group Efficiency Points Group Efficiency Points Full-time 5 Part-time 1 Full-time 3 Part-time 3 Full-time 4 Part-time 4 Full-time 1 Part-time 4 Full-time 2 Part-time 2 Full-time 3 Part-time 0 Full-time 2
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Consider the following measurements of blood hemoglobin concentrations (in g/dL) from three human populations at different geographic locations: population1 = [ 14.7 , 15.22, 15.28, 16.58, 15.10 ] population2 = [ 15.66, 15.91, 14.41, 14.73, 15.09] population3 = [ 17.12, 16.42, 16.43, 17.33] If you run ANOVA on the data for the three populations, what is the range of the P-value? Greater than 0.05 between 0.05 and 0.025 between 0.025 and 0.01 less than 0.01
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