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- A systems analyst tests a new algorithm designed to work faster than the currently-used algorithm. Each algorithm is applied to a group of 7373 sample problems. The new algorithm completes the sample problems with a mean time of 24.2824.28 hours. The current algorithm completes the sample problems with a mean time of 26.9726.97 hours. Assume the population standard deviation for the new algorithm is 3.5873.587 hours, while the current algorithm has a population standard deviation of 4.0394.039 hours. Conduct a hypothesis test at the 0.050.05 level of significance of the claim that the new algorithm has a lower mean completion time than the current algorithm. Let μ1μ1 be the true mean completion time for the new algorithm and μ2μ2 be the true mean completion time for the current algorithm. Step 1 of 4 : State the null and alternative hypotheses for the test.Authors of a computer algebra system wish to compare the speed of a new computational algorithm to the currently implemented algorithm. They apply the new algorithm to 50 standard problems; it averages 8.16 seconds with standard deviation 0.17 second. The current algorithm averages 8.22 seconds on such problems. Test, at the 1% level of significance, the alternative hypothesis that the new algorithm has a lower average time than the current algorithm.A systems analyst tests a new algorithm designed to work faster than the currently-used algorithm. Each algorithm is applied to a group of 7373 sample problems. The new algorithm completes the sample problems with a mean time of 24.2824.28 hours. The current algorithm completes the sample problems with a mean time of 26.9726.97 hours. Assume the population standard deviation for the new algorithm is 3.5873.587 hours, while the current algorithm has a population standard deviation of 4.0394.039 hours. Conduct a hypothesis test at the 0.050.05 level of significance of the claim that the new algorithm has a lower mean completion time than the current algorithm. Let μ1μ1 be the true mean completion time for the new algorithm and μ2μ2 be the true mean completion time for the current algorithm. Step 3 of 4 : Determine the decision rule for rejecting the null hypothesis H0H0. Round the numerical portion of your answer to three decimal places.
- (a) Compute four-week and five-week moving averages for the time series. 4-Week 5-Week Time Series Moving Average Forecast Moving Average Forecast Week Value 1 17 2 21 19 4 24 5 18 6 16 7 20 8 18 22 10 20 11 15 12 23 (b) Compute the MSE for the four-week moving average forecasts. (Round your answer to two decimal places.) Compute the MSE for the five-week moving average forecasts. (Round your answer to two decimal places.)A systems analyst tests a new algorithm designed to work faster than the currently-used algorithm. Each algorithm is applied to a group of 49 sample problems. The new algorithm completes the sample problems with a mean time of 11.01 hours. The current algorithm completes the sample problems with a mean time of 13.24 hours. The standard deviation is found to be 3.328 hours for the new algorithm, and 3.877 hours for the current algorithm. Conduct a hypothesis test at the 0.05 level of significance of the claim that the new algorithm has a lower mean completion time than the current algorithm. Let μ1μ1 be the true mean completion time for the new algorithm and μ2μ2 be the true mean completion time for the current algorithm. Step 1 of 4 : State the null and alternative hypotheses for the test.how to design the propensity rates of this set of equations to apply it to the gillespie algorithm
- A systems analyst tests a new algorithm designed to work faster than the currently-used algorithm. Each algorithm is applied to a group of 58 sample problems. The new algorithm completes the sample problems with a mean time of 16.44 hours. The current algorithm completes the sample problems with a mean time of 17.43 hours. Assume the population standard deviation for the new algorithm is 4.276 hours, while the current algorithm has a population standard deviation of 3.754 hours. Conduct a hypothesis test at the 0.1 level of significance of the claim that the new algorithm has a lower mean completion time than the current algorithm. Let u be the true mean completion time for the new algorithm and u2 be the true mean completion time for the current algorithm. Step 1 of 5: State the null and alternative hypotheses for the test.A systems analyst tests a new algorithm designed to work faster than the currently-used algorithm. Each algorithm is applied to a group of 58 sample problems. The new algorithm completes the sample problems with a mean time of 16.44 hours. The current algorithm completes the sample problems with a mean time of 17.43 hours. Assume the population standard deviation for the new algorithm is 4.276 hours, while the current algorithm has a population standard deviation of 3.754 hours. Conduct a hypothesis test at the 0.1 level of significance of the claim that the new algorithm has a lower mean completion time than the current algorithm. Let µ¡ be the true mean completion time for the new algorithm and µ2 be the true mean completion time for the current algorithm. Step 3 of 5: Find the p-value associated with the test statistic. Round your answer to four decimal places.Dimwit, a social media company, wants to become more competitive in the marketplace. They have developed an algorithm that tracks the response and resolution times when customers call for technical support. The company has a service standard of 4 days for the mean resolution time with the standard deviation of 10.3 days. However, the Director of the technical support group has been receiving some complaints of long resolution times. During one week, a sample of 36 customer calls resulted in a sample mean of 5.3. Even though the sample mean exceeds the 4-day standard, does the manager have sufficient evidence to conclude that the mean service time exceeds 4 days, or is this particular sample mean simply a result of sampling error? Use a significance level equal to 1% to test your hypothesis.
- A systems analyst tests a new algorithm designed to work faster than the currently-used algorithm. Each algorithm is applied to a group of 58 sample problems. The new algorithm completes the sample problems with a mean time of 16.44 hours. The current algorithm completes the sample problems with a mean time of 17.43 hours. Assume the population standard deviation for the new algorithm is 4.276 hours, while the current algorithm has a population standard deviation of 3.754 hours. Conduct a hypothesis test at the 0.1 level of significance of the claim that the new algorithm has a lower mean completion time than the current algorithm. Let µ¡ be the true mean completion time for the new algorithm and u2 be the true mean completion time for the current algorithm. Step 2 of 5: Compute the value of the test statistic. Round your answer to two decimal places.A systems analyst tests a new algorithm designed to work faster than the currently-used algorithm. Each algorithm is applied to a group of 38 sample problems. The new algorithm completes the sample problems with a mean time of 22.07 hours. The current algorithm completes the sample problems with a mean time of 22.33 hours. Assume the population standard deviation for the new algorithm is 4.674 hours, while the current algorithm has a population standard deviation of 5.185 hours. Conduct a hypothesis test at the 0.05 level of significance of the claim that the new algorithm has a lower mean completion time than the current algorithm. Let ?1be the true mean completion time for the new algorithm and ?2 be the true mean completion time for the current algorithm. Pay attention to spaces between words. H0: Ha: z-Test Statistic (round to two decimal places) = p-value (round to four decimal places) = Conclusion (write "R" for reject H0, and "F" for fail to reject H0):The MAKSI FEB UI program is considering buying a copier machine among 5 (five) types, namely the FC1, FC2, FC3, FC4 and FC5 types, where each type has different efficiency in terms of the speed of the number of pages (sheets) copied in one minute. Six staff members conducted an experiment to run each type of copier. The following data shows the number of copied pages (sheets) that can be produced in one minute according to the type of copier, 1 trial, and according to the staff assigned to run each type of copier: FC1 FC2 FC3 FC4 FC5 Staff 1 60 50 63 60 64 Staff 2 56 55 65 58 60 Staff 3 54 56 65 56 58 Staff 4 56 57 67 65 60 Staff 5 54 56 65 60 60 Staff 6 55 52 58 60 55 Some of the results of the calculation of the sum of squares (sum-square) and the average squared (mean square) required for the ANOVA test are provided in the following table: Source of Variation SS Df MS Fstat FTable CopierMachine 333.33 ……… ……… ……… ……… Staff ……….. ……… ……… ……… ……… Error 129.47 ……… ……… Total 532.67 …………