For some data sets, the F statistic will reject the null hypothesis of no difference in mean yields, but the Tukey–Kramer method will not find any pair of means that can be concluded to differ. For the four sample means given in Exercise 14. assuming a
14. In an experiment to determine the effect of curing time on the compressive strength of a certain type of concrete, the mean strengths, in MPa, for specimens cured for each of four curing times were
- a. If MSE = 875.2, compute the value of the F statistic for testing the null hypothesis that all four curing times have the same mean strength. Can this null hypothesis be rejected at the 5% level?
- b. Use the Tukey–Kramer method to determine which pairs of curing times, if any, may be concluded to differ at the 5% level.
Want to see the full answer?
Check out a sample textbook solutionChapter 9 Solutions
Statistics for Engineers and Scientists
Additional Math Textbook Solutions
Pathways To Math Literacy (looseleaf)
College Algebra (Collegiate Math)
Thinking Mathematically (6th Edition)
Elementary Statistics ( 3rd International Edition ) Isbn:9781260092561
APPLIED STAT.IN BUS.+ECONOMICS
- Three different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 30 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 10 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST = 10,720; SSTR = 4,510. Set up the ANOVA table for this problem (to 2 decimals, if necessary). Round p-value to four decimal places. Source of Variation Sum of Squares Degrees of Freedom Mean Square F p-value Treatments Error Total Use = .05 to test for any significant difference in the means for the three assembly methods.The p-value is Selectless than .01between .01 and .025between .025 and .05between .05 and .10greater than .10Item 11 What is your…arrow_forwardThree different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 30 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 10 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST =10,890; SSTR =4600. a. Set up the ANOVA table for this problem (to 2 decimals but p-value to 4 decimals, if necessary). Source of Variation Sum of Squares Degrees of Freedom Mean Square F p-value Treatments Error Total b.Use a 0.05 to test for any significant difference in the means for the three assembly methods. %3D Calculate the value of the test statistic (to 2 decimals). The p-value is - Select your answer - What is your conclusion? - Select your answer -arrow_forwardIs the proportion of wildfires caused by humans in the south lower than the proportion of wildfires caused by humans in the west? 360 of the 501 randomly selected wildfires looked at in the south were caused by humans while 435 of the 588 randomly selected wildfires looked at the west were caused by humans. What can be concluded at the = 0.10 level of significance? For this study, we should use Select an answer t-test for the difference between two dependent population means z-test for the difference between two population proportions t-test for a population mean t-test for the difference between two independent population means z-test for a population proportion The null and alternative hypotheses would be: Select an answer μ1 p1 Select an answer < ≠ > = Select an answer μ2 p2 (please enter a decimal) Select an answer μ1 p1 Select an answer > ≠ < = Select an answer p2 μ2 (Please enter a decimal) The test statistic ? z t = (please show your…arrow_forward
- Three different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 30 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 10 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST = 10,950; SSTR = 4,570. (a) Set up the ANOVA table for this problem. (Round your values for MSE and F to two decimal places, and your p-value to four decimal places.) Source Sum Degrees of Freedom Mean F p-value of Variation of Squares Square Treatments Error Total (b) Use a = 0.05 to test for any significant difference in the means for the three assembly methods. State the null and alternative hypotheses. Ho: H1 = H2 = H3 O Ho: H1 = H2 = H3 : Not all the population means are equal. Not all the population means are…arrow_forwardThree different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 36 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 12 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST = 12,410; SSTR = 4,550. (a) Set up the ANOVA table for this problem. (Round your values for MSE and F to two decimal places, and your p-value to four decimal places.) Degrees of Freedom Source Sum Mean p-value of Variation of Squares Square Treatments Error Total (b) Use a = 0.05 to test for any significant difference in the means for the three assembly methods. State the null and alternative hypotheses. O H,: At least two of the population means are equal. H.: At least two of the population means are different. O…arrow_forwardYou may need to use the appropriate technology to answer this question. Three different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 36 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 12 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST = 12,620; SSTR = 4,520. (a) Set up the ANOVA table for this problem. (Round your values for MSE and F to two decimal places, and your p-value to four decimal places.) Sum Source of Variation Degrees Mean Square F of Squares of Freedom p-value Treatments Error Total (b) Use a = 0.05 to test for any significant difference in the means for the three assembly methods. State the null and alternative hypotheses. O Hg ² H₂ # H₂ # Hz H₂H₂ = H₂ = H₂ ⒸH₁…arrow_forward
- Three different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 30 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 10 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST=10,800; SSTR =4550. a. Set up the ANOVA table for this problem (to 2 decimals but p-value to 4 decimals, if necessary). Source of Variation Sum of Squares Degrees of Freedom Mean Square Treatments Error Total 1000 000 The p-value is - Select your answer - + What is your conclusion? - Select your answer - F b.Use a = 0.05 to test for any significant difference in the means for the three assembly methods. Calculate the value of the test statistic (to 2 decimals). + p-value Check My Work (5 remaining)arrow_forwardA new runner has decided to purchase a new pair of running shoes. He has narrowed his choices to two brands, each of which would be appropriate for his use. His concern is whether there is a significant difference in the average wear between the two brands of shoes. He enlisted a random sample of 6 veteran runners to test the shoes. Each runner wore each brand of shoe until it wore out. What method of analysis is more appropriate to use for this problem? Group of answer choices Independent sample t-test Independent sample z-test paired difference z-test paired difference t-testarrow_forwardThree different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 30 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 10 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST = 10,800; SSTR = 4,520. (a) Set up the ANOVA table for this problem. (Round your values for MSE and F to two decimal places, and your p-value to four decimal places.) Sourceof Variation Sumof Squares Degreesof Freedom MeanSquare F p-value Treatments Error Total (b) Use ? = 0.05 to test for any significant difference in the means for the three assembly methods. State the null and alternative hypotheses. H0: Not all the population means are equal.Ha: ?1 = ?2 = ?3H0: ?1…arrow_forward
- Three different methods for assembling a product were proposed by an Industrial engineer. To investigate the number of units assembled correctly with each method, 36 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 12 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST = 12,750; SSTR = 4,510. (a) Set up the ANOVA table for this problem. (Round your values for MSE and F to two decimal places, and your p-value to four decimal places.) Source Degrees of Freedom Sum Mean of Variation of Squares Square p-value Treatments Error Total (b) Use a = 0.05 to test for any significant difference in the means for the three assembly methods. State the null and alternative hypotheses. Ho: H H2 H3 H H- H2=H3 O Ho: Hy=H2-H H H H2 Hy Ho: At least two of the population means are equal. H3: At least…arrow_forwardThree different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 39 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 13 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST = 13,220; SSTR = 4,520. (a) Set up the ANOVA table for this problem. (Round your values for MSE and F to two decimal places, and your p-value to four decimal places.) Source of Variation Sum of Squares Degrees of Freedom Mean Square F p-value Treatments Error Total B. Find the value of the test statistic. (Round your answer to two decimal places.) C. Find the p-value. (Round your answer to four decimal places.) p-value =arrow_forwardWhen only two treatments are involved, ANOVA and the Student’s t-test (Chapter 11) result in the same conclusions. Also, for computed test statistics, t2 = F. To demonstrate this relationship, use the following example. Fourteen randomly selected students enrolled in a history course were divided into two groups, one consisting of six students who took the course in the normal lecture format. The other group of eight students took the course in a distance format. At the end of the course, each group was examined with a 50-item test. The following is a list of the number correct for each of the two groups. Traditional Lecture Distance 36 45 31 35 40 45 34 35 33 45 38 36 43 41 a-1. Complete the ANOVA table. (Round your SS, MS, and F values to 2 decimal places and p-value, F crit to 4 decimal places.) Source of Variation SS df MS F p-value F crit Treatment 96.01 1 96.01 5.67 0.0350 Error 203.21 12 16.93 Total 299.21 13…arrow_forward
- Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw HillCollege Algebra (MindTap Course List)AlgebraISBN:9781305652231Author:R. David Gustafson, Jeff HughesPublisher:Cengage Learning