Four types of mortars—ordinary cement mortar (OCM). polymer impregnated mortar (PIM), resin mortar (RM), and polymer cement mortar (PCM)—were subjected to a compression test to measure strength (MPa). Three strength observations for each mortar type are given in the article “Polymer Mortar Composite Matrices for Maintenance-Free Highly Durable Ferrocement” (J. of Ferrocement, 1984: 337-345) and are reproduced here. Construct an ANOVA table. Using a .05 significance level, determine whether the data suggests that the true mean strength is not the same for all four mortar types. If you determine that the true mean strengths are not all equal, use Tukey's method to identify the significant differences.
OCM | 32.15 | 35.53 | 34.20 |
PIM | 126.32 | 126.80 | 134.79 |
RM | 117.91 | 115.02 | 114.58 |
PCM | 29.09 | 30.87 | 29.80 |
Want to see the full answer?
Check out a sample textbook solutionChapter 10 Solutions
Probability and Statistics for Engineering and the Sciences
- A factorial experiment was designed to test for any significant differences in the time needed to perform English to foreign language translations with two computerized language translators. Because the type of language translated was also considered a significant factor, translations were made with both systems for three different languages: Spanish, French, and German. Use the following data for translation time in hours. Language Spanish French German System 1 6 13 11 10 17 15 System 2 7 13 14 11 15 20 Test for any significant differences due to language translator system (Factor A), type of language (Factor B), and interaction. Use . Complete the following ANOVA table (to 2 decimals, if necessary). Round your p-value to 4 decimal places. Source of Variation Sum of Squares Degrees of Freedom Mean Square -value Factor A Factor B Interaction Error Totalarrow_forwardA factorial experiment was designed to test for any significant differences in the time needed to perform English to foreign language translations with two computerized language translators. Because the type of language translated was also considered a significant factor, translations were made with both systems for three different languages: Spanish, French, and German. Use the following data for translation time in hours. Language Spanish French German System 1 6 13 11 10 17 15 System 2 7 13 14 11 15 20 Test for any significant differences due to language translator system (Factor A), type of language (Factor B), and interaction. Use . Complete the following ANOVA table (to 2 decimals, if necessary). Round your p-value to 4 decimal places.arrow_forwardA factorial experiment was designed to test for any significant differences in the time needed to perform English to foreign language translations with two computerized language translators. Because the type of language translated was also considered a significant factor, translations were made with both systems for three different languages: Spanish, French, and German. Use the following data for translation time in hours. Language Spanish French German System 1 7 14 15 11 18 19 System 2 6 15 19 10 17 25 Test for any significant differences due to language translator system (Factor A), type of language (Factor B), and interaction. Use x=.05 Complete the following ANOVA table (to 2 decimals, if necessary). Round your p-value to 4 decimal places. Source of Variation Sum of Squares Degrees of Freedom Mean Square F P-value Factor A Factor B Interaction Error Total The p-value for Factor A is -…arrow_forward
- A factorial experiment was designed to test for any significant differences in the time needed to perform English to foreign language translations with two computerized language translators. Because the type of language translated was also considered a significant factor, translations were made with both systems for three different languages: Spanish, French, and German. Use the following data for translation time in hours. Language Spanish French German System 1 7 8 15 11 12 19 System 2 6 16 18 10 18 24 Test for any significant differences due to language translator system (Factor A), type of language (Factor B), and interaction. Use = .05. Complete the following ANOVA table (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 Factor A Factor B Interaction Error Total The p-value for Factor A is…arrow_forwardA simplified version of input output analysis of a national economy has the following input output matrixarrow_forwardA factorial experiment was designed to test for any significant differences in the time needed to perform English to foreign language translations with two computerized language translators. Because the type of language translated was also considered a significant factor, translations were made with both systems for three different languages: Spanish, French, and German. Use the following data for translation time in hours. Language Spanish French German System 1 8 14 15 12 18 19 System 2 4 17 17 8 19 23 Test for any significant differences due to language translator system (Factor A), type of language (Factor B), and interaction. Use . Complete the following ANOVA table (to 2 decimals, if necessary). Round your p-value to 4 decimal places. Source of Variation Sum of Squares Degrees of Freedom Mean Square -value Factor A Factor B Interaction Error Total The p-value for Factor A is: less than…arrow_forward
- A factorial experiment was designed to test for any significant differences in the time needed to perform English to foreign language translations with two computerized language translators. Because the type of language translated was also considered a significant factor, translations were made with both systems for three different languages: Spanish, French, and German. Use the following data for translation time in hours. Language Spanish French German System 1 7 12 14 11 16 18 System 2 4 12 18 8 14 24 Test for any significant differences due to language translator system (Factor A), type of language (Factor B), and interaction. Use a=.05 . Complete the following ANOVA table (to 2 decimals, if necessary). Round your p-value to 4 decimal places. Source of Variation Sum of Squares Degrees of Freedom Mean Square F P-value Factor A Factor B Interaction Error Totalarrow_forward1. When looking at the matrix for a two-way ANOVA, which means (row, column, or cell means) do we look at to assess if there is an interaction effect? A row and column means B just row means C just column means D cell means 2. A marketing company wanted to test what makes people purchase cereal more and tested box size and flashy graphics. Which of the following would be considered responsible for the main effects of this study? a the results of each box size and flashy graphics b the results for only box size c the results for only flashy graphics d behavior of purchasing cereal 3. A dentist wanted to test the effect of a new mouthwash and wondered how many seconds people would have to gargle in order for their breath to feel fresh. She had patients gargle the mouthwash for 10, 20 and 40 seconds (number of seconds; Factor A). She also wanted to know if there was age level (Factor B) interacted with number of…arrow_forwardA factorial experiment was designed to test for any significant differences in the time needed to perform English to foreign language translations with two computerized language translators. Because the type of language translated was also considered a significant factor, translations were made with both systems for three different languages: Spanish, French, and German. Use the following data for translation time in hours. Language Spanish French German System 1 8 13 14 12 17 18 System 2 8 14 16 12 16 22 Test for any significant differences due to language translator system (Factor A), type of language (Factor B), and interaction. Use x=0.05. Complete the following ANOVA table (to 2 decimals, if necessary). Round your p-value to 4 decimal places. Source of Variation Sum of Squares Degrees of Freedom Mean Square F p-value Factor A Factor B Interaction Error Total The p-value for Factor A is…arrow_forward
- To detect bivariate outliers between all predictor variables and the criterion variable, the researcher should use which of the following?: Group of answer choices a Box and Whisker plot. a matrix scatter plotarrow_forwardDoes college grade point average (GPA) depend on gender? Does it depend on class (freshman, sophomore, junior, senior)? In a study, the following GPA data were obtained for random samples of college students in each of the cells. Class Gender Freshman Sophomore Junior Senior Male 2.8 2.1 2.7 3.0 2.5 2.3 2.9 3.5 3.1 2.9 3.2 3.8 3.8 3.6 3.5 3.1 Female 2.3 2.9 3.5 3.9 2.6 2.4 3.3 3.6 2.6 3.6 3.3 3.7 3.2 3.5 3.8 3.6 Minitab Printout of GPA Based on Gender and Class Analysis of Variance for GPA Source DF SS MS F P Gender 1 0.281 0.281 1.26 0.273 Class 3 2.226 0.742 3.32 0.037 Interaction 3 0.286 0.095 0.43 0.736 Error 24 5.365 0.224 Total 31 8.159 (b) Use two-way ANOVA and the Minitab printout to determine if there is any evidence of interaction between the two factors at a level of significance of 0.01. F =? P-value =? (c) If there is no evidence of interaction, use two-way ANOVA and…arrow_forwardA researcher uncovers that there is a significant interaction between the factor of marital status (i.e., married or non-married) and participant sex (i.e., male or female) regarding well-being among a sample with n = 6 participants in each condition. A researcher decides to compare the difference in well-being between married men and women. The MSwithin treatments from the original two-factor analysis is MSwithin treatments = 1.00. What is the F-ratio for this comparison using the matrix below, which depicts descriptive statistics regarding married participants? __________________________________________________________________________________________ Participant Sex Males Females __________________________________________________________________ n = 6 n = 6 N =12 M = 4…arrow_forward
- Linear Algebra: A Modern IntroductionAlgebraISBN:9781285463247Author:David PoolePublisher:Cengage Learning