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Two catalysts are being analyzed to determine how they affect the average yield of the chemical process. The higher the yield in percentage, the better the catalyst is. Catalyst A is a commercial catalyst that is currently being used. Catalyst B is developed by our research group based on a geopolymer material. The following table is the summarized result from the test runs in the pilot plant. Based on the normal probability plot, it is valid to assume normal distribution from these data. A B sample mean 92.0 94.0 sample standard 2.0 1.5 deviation sample size 12 10 Would there be any difference in the average yield at a 5 % level of significance? Is it valid to assume equal variances at a 5 % level of significance? Show the solution using statistical inference based on hypothesis testing by filling in the blanks. Express your numerical answers in 2 decimal places (e.g., 0.23, 0.01, or -2.10) unless specified and choose the right words as suggested in < text1, text2 > if provided. The parameter of interest is the average process yield using catalyst A (H1) and catalyst B ((H2), and we will be interested to know if there is a statistically significant difference at a= 5 %. Then, the null hypothesis (Ho) is (H1 - H2) = 0 . The alternative hypothesis (Ha) is (u1 - H2) # 0. This is a test using the test statistic from distribution. The computed test statistic from the sample data is and its p-value is

Two catalysts are being analyzed to determine how they affect the average yield of the chemical process. The higher the yield in percentage, the better the catalyst is. Catalyst A is a commercial catalyst that is currently being used. Catalyst B is developed by our research group based on a geopolymer material. The following table is the summarized result from the test runs in the pilot plant. Based on the normal probability plot, it is valid to assume normal distribution from these data. A B sample mean 92.0 94.0 sample standard 2.0 1.5 deviation sample size 12 10 Would there be any difference in the average yield at a 5 % level of significance? Is it valid to assume equal variances at a 5 % level of significance? Show the solution using statistical inference based on hypothesis testing by filling in the blanks. Express your numerical answers in 2 decimal places (e.g., 0.23, 0.01, or -2.10) unless specified and choose the right words as suggested in < text1, text2 > if provided. The parameter of interest is the average process yield using catalyst A (H1) and catalyst B ((H2), and we will be interested to know if there is a statistically significant difference at a= 5 %. Then, the null hypothesis (Ho) is (H1 - H2) = 0 . The alternative hypothesis (Ha) is (u1 - H2) # 0. This is a test using the test statistic from distribution. The computed test statistic from the sample data is and its p-value is

MATLAB: An Introduction with Applications
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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Reject the null hypothesis if the test statistic is greater than the critical value at the right which is equal to Or reject the null hypothesis if the test statistic is less than the critical value at left = Otherwise, we "fail to reject" the null hypothesis since the p-value is than a = 0.05 At the 5 % level of significance, we do <not have, have> strong evidence to conclude that catalyst B results in an average yield that differs from the average yield when catalyst A is used. Would you recommend the adoption of Catalyst B if it is cheaper than Catalyst A (write "yes" if correct, otherwise, write "no") ? <yes,no> Is the equal variance assumption valid which was used as a basis for hypothesis testing of the difference between means? The parameters of interest are the variances of process yields from the two catalysts and the null hypothesis assumes equal variances (01 = 02) whereas the alternative hypothesis assumes the variances are not equal. The computed test statistic is . The test statistic is then compared to the critical value from the distribution.
Transcribed Image Text:Reject the null hypothesis if the test statistic is greater than the critical value at the right which is equal to Or reject the null hypothesis if the test statistic is less than the critical value at left = Otherwise, we "fail to reject" the null hypothesis since the p-value is than a = 0.05 At the 5 % level of significance, we do <not have, have> strong evidence to conclude that catalyst B results in an average yield that differs from the average yield when catalyst A is used. Would you recommend the adoption of Catalyst B if it is cheaper than Catalyst A (write "yes" if correct, otherwise, write "no") ? <yes,no> Is the equal variance assumption valid which was used as a basis for hypothesis testing of the difference between means? The parameters of interest are the variances of process yields from the two catalysts and the null hypothesis assumes equal variances (01 = 02) whereas the alternative hypothesis assumes the variances are not equal. The computed test statistic is . The test statistic is then compared to the critical value from the distribution.
Two catalysts are being analyzed to determine how they affect the average yield of the chemical process. The higher the yield in percentage, the better the catalyst is. Catalyst A is a commercial catalyst that is currently being used. Catalyst B is developed by our research group based on a geopolymer material. The following table is the summarized result from the test runs in the pilot plant. Based on the normal probability plot, it is valid to assume normal distribution from these data. A B sample mean 92.0 94.0 sample standard 2.0 1.5 deviation sample size 12 10 Would there be any difference in the average yield at a 5 % level of significance? Is it valid to assume equal variances at a 5 % level of significance? Show the solution using statistical inference based on hypothesis testing by filling in the blanks. Express your numerical answers in 2 decimal places (e.g., 0.23, 0.01, or -2.10) unless specified and choose the right words as suggested in < text1, text2 > if provided. The parameter of interest is the average process yield using catalyst A (H) and catalyst B ((H2), and we will be interested to know if there is a statistically significant difference at a= 5 %. Then, the null hypothesis (Ho) is (H1 - H2) = 0 . The alternative hypothesis (Ha) is (P1 - H2) # 0. This is a <write either "one-tailed" or "two-tailed"> test using the test statistic from distribution. The computed test statistic from the sample data is and its p-value is
Transcribed Image Text:Two catalysts are being analyzed to determine how they affect the average yield of the chemical process. The higher the yield in percentage, the better the catalyst is. Catalyst A is a commercial catalyst that is currently being used. Catalyst B is developed by our research group based on a geopolymer material. The following table is the summarized result from the test runs in the pilot plant. Based on the normal probability plot, it is valid to assume normal distribution from these data. A B sample mean 92.0 94.0 sample standard 2.0 1.5 deviation sample size 12 10 Would there be any difference in the average yield at a 5 % level of significance? Is it valid to assume equal variances at a 5 % level of significance? Show the solution using statistical inference based on hypothesis testing by filling in the blanks. Express your numerical answers in 2 decimal places (e.g., 0.23, 0.01, or -2.10) unless specified and choose the right words as suggested in < text1, text2 > if provided. The parameter of interest is the average process yield using catalyst A (H) and catalyst B ((H2), and we will be interested to know if there is a statistically significant difference at a= 5 %. Then, the null hypothesis (Ho) is (H1 - H2) = 0 . The alternative hypothesis (Ha) is (P1 - H2) # 0. This is a <write either "one-tailed" or "two-tailed"> test using the test statistic from distribution. The computed test statistic from the sample data is and its p-value is
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