The following data give the recovery of bromide from spiked samples of vegetablematter, measured using a gas-liquid chromatographic method. The same amount ofbromide was added to each specimen.764 µg g¯'782 ug g.1790773759778Tomato:758777782790770789Cucumber:765797(a) Test whether the recoveries from the two vegetables have variances which differsignificantly.(b) Test whether the mean recovery rates differ significantly.

a) The variance of recoveries for tomatoes is σ12 and the variance of recoveries for cucumber is…

Answered: The following data give the recovery of…

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 corrosive effects of various soils on coated and uncoated steel pipe was tested by using a dependent sampling plan. The data collected are summarized below, where d is the amount of corrosion on the coated portion subtracted from the amount of corrosion on the uncoated portion. Does this random sample provide sufficient reason to conclude that the coating is beneficial? Use a = 0.01 and assume normality. n- 40, Σd- 207, Σα? = 6199 (a) Find t. (Give your answer correct to two decimal places.) (ii) Find the p-value. (Give your answer correct to four decimal places.) (b) State the appropriate conclusion. O Reject the null hypothesis, there is significant evidence that the coating is beneficial. Reject the null hypothesis, there is not significant evidence that the coating is beneficial. Fail to reject the null hypothesis, there is significant evidence that the coating is beneficial. Fail to reject the null hypothesis, there is not significant evidence that the coating is beneficial.
Managers of an outdoor coffee stand in Coast City are examining the relationship between (hot) coffee sales and daily temperature, hoping to be able to predict a day's total coffee sales from the maximum temperature that day. The bivariate data values for the coffee sales (denoted by y , in dollars) and the maximum temperature (denoted by x , in degrees Fahrenheit) for each of fifteen randomly selected days during the past year are given below. These data are plotted in the scatter plot in Figure 1. Temperature, x(in degrees Fahrenheit) Coffee sales, y(in dollars) 53.1 2215.5 76.6 1982.7 70.1 1937.3 39.7 2251.1 72.5 1603.9 48.4 2024.2 46.7 2135.3 83.9 1536.5 58.4 1965.6 38.5 1944.3 68.2 1746.1 75.4 1472.1 65.6 1819.5 53.9 1627.4 45.1 1782.3 Send data to calculator Send data to Excel Coffee sales(in dollars) y 1200 1400 1600 1800 2000 2200 2400 x 40 50 60 70 80 90…
thill An experiment compares two different processes for producing steel plate. The measurements represent the thickness of the plate. The samples gave m = 8, X = 6.701, S1 = 0.108 n = 6, Y = 6.841, S2 = 0.155 %3D %3D Assume that the two populations are normal with equal variances, test Ho: H1 - H2 = 0 against H1 : µ1 - µ2#0 at a 0.05 significance level. 5.
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.
Managers of an outdoor coffee stand in Coast City are examining the relationship between (hot) coffee sales and daily temperature, hoping to be able to predict a day's total coffee sales from the maximum temperature that day. The bivariate data values for the coffee sales (denoted by y, in dollars) and the maximum temperature (denoted by x, in degrees Fahrenheit) for each of sixteen randomly selected days during the past year are given below. These data are plotted in the scatter plot in Figure 1. Temperature, x (in degrees Fahrenheit) Coffee sales, y (in dollars) 71.5 1970.9 58.7 1953.9 53.7 1791.1 2400+ 83.0 1570.3 2200+ 62.8 1852.7 74.6 1633.6 2000- ** 40.4 1973.9 1800- 51.5 2250.9 44.6 1808.5 1600- 45.5 1977.3 1400- 45.6 2190.5 1200 69.4 1789.1 55.0 1598.2 50 70 80 90 40.6 2272.0 74.0 1937.0 Figure 1 76.6 1547.1 Send data to Excel Continue Submit Assignment O 2021 McGraw-Hill Education. All Rights Reserved. Terms of Use Privacy Accessibility here to search 99+ 5 4.
A manufacturing company produces bearings. One line of bearings is specified to be 1.64 centimeters (cm) in diameter. A major customer requires that the variance of the bearings be no more than .001 cm². The producer is required to test the bearings before they are shipped, and so the diameters of 16 bearings are measured with a precise instrument, resulting in the following values. Assume bearing diameters are normally distributed. Use the data and a = 0.01 to test to determine whether the population of these bearings is to be rejected because of too high a variance. 1.68 1.62 1.63 1.70 1.66 1.63 1.65 1.71 1.64 1.69 1.57 1.64 1.59 1.66 1.63 1.65 Appendix A Statistical Tables (Round your answer to 2 decimal places, e.g. 15.25.) The value of the test statistic is and we reject the null hypothesis ⇒
The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of sixteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage x (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price y (in thousands of dollars) at which the Cadet was sold used. The least-squares regression line for these data has equation Ŷ=42.80-0.53x. This line is shown in the scatter plot below. (The 2nd picture contains the rest of the data as it would not fit in the first pic and it includes the question as well.)
Managers of an outdoor coffee stand in Coast City are examining the relationship between (hot) coffee sales and daily temperature, hoping to be able to predict a day's total coffee sales from the maximum temperature that day. The bivariate data values for the coffee sales (denoted by y, in dollars) and the maximum temperature (denoted by x, in degrees Fahrenheit) for each of randomly selected days during the past year are given below. These data are plotted in the scatter plot below. (a)For these data, temperature values that are less than the mean of the temperature values tend to be paired with coffee sales values that are ▼(Choose one) the mean of the coffee sales values. (b)According to the regression equation, for an increase of one degree in temperature, there is a corresponding ▼(Choose one) of 9.94 dollars in coffee sales. (c)From the regression equation, what is the predicted coffee sales value (in dollars) when the temperature is 74.6 degrees Fahrenheit? (Round your…

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