ider the following graphic results from a 2 x 2 factorial experiment. These results show 100 A1 50 A2 a. there is a significant main effect for factor A, no other significant effects b. there is...
A factorial experiment involving two levels of factor A and three levels of factor B resulted in the following data. Factor B Level 1 Level 2 Level 3 125 100 65 Level 1 155 76 103 Factor A 105 147 140 Level 2 95 125 156 Test for any significant main effects and any interaction. Use . Round Sum of Squares, value, Mean Square to two decimals, if necessary and -value to four decimals. Source of Variation Sum of Squares Degrees...
A factorial experiment involving two levels of factor A and three levels of factor B resulted in the following data. Factor B Level 1 Level 2 Level 3 135 90 75 Level 1 165 93 Factor A 135 127 120 Level 2 85 105 136 Test for any significant main effects and any interaction. Use α-.05. Round Sum of Squares, F value, Mean Square to two decimals, if necessary. Source of Variation Factor A Factor B Interaction Error Total Sum...
The results of a two-factor, independent-measures, equal n experiment are summarized in the following matrix. The numerical value in each cell is the mean score obtained from the sample in that treatment condition B B2 А M=4 M-2 M- Az M = 6 M-8 ME M M Compute the overall means for the scores in A, the scores in Az, the scores in B, and the scores in B2. Enter each of the means to the right of the appropriate...
The following two-way table gives data for a 2 × 2 factorial experiment with two observations per factor-level combination: The data are saved in the LM.TXT file. Factor B Level 1 2 Factor A 1 29.6, 35.2 47.3, 42.1 2 12.9, 17.6 28.4, 22.7 a. Identify the treatments for this experiment. Calculate and plot the treatment means, using the response variable as y-axis and the levels of factor B as the x-axis. Use the levels of factor A as plotting symbols. Do...
The following results are from an independent-measures, two-factor study with n condition. 10 participants in each treatment Factor B Factor A 2 T 40 M=4.00 SS = 50 T=50 M = 5.00 SS = 60 T= 10 M 1.00 SS 30 T=20 M 2.00 SS 40 N = 40; G = 120; Σ? = 640 Use a two-factor ANOVA with α =。05 to evaluate the main effects and the interaction Source df MS Between treatments AxB Within treatments Total For...
QUESTION 42 Make up an example of a study that uses a 2 x 2 factorial design, and fill in a table of cell means that would show no main effects and no interaction effect. (Do not use an example from your textbook class lectures, or your classmates.) Explain the pattern of the cell means you created within the context of your example. T T T Arial Path: p Click Save and Submit to save and submit. Click Save All...
please show work for each! ΑΙ Factor B B. B2 T = 40 T = 10 M=4 M= 1 SS-50 SS = 30 Factor A A2 T-50 M=5 SS - 60 T = 20 M = 2 SS = 40 N-40 G = 120 EX =640 Use a two-way ANOVA with a=0.05 to evaluate the main effects and the interaction. m Source SS df MS F Between treatments | 1 6.67 I 2.00 Factor A (ROWS) 18.00 Factor B (COLUMNS)...
The following table represents a two-factor experiment, with each factor having two levels. The numbers in each cell are the mean performance scores of each group after the experimental treatment. Note that one mean value is not given. What value of the missing mean would result in no interaction effect of factor A & factor B? B1 B2 A1 50 25 A2 35 ? A. 5 B. 10 C. 15 D. 20 E. 25
The calculations for a factorial experiment involving four levels of factor A, three levels of factor B, and three replications resulted the following data: SST 291, SSA 26, SSB 25, SSAB 180. =.05, Show entries to 2 decimals, If necessary Set up the ANOVA table and test for significance using the answer is zero enter "0". Source of Variation Sum of Squares Degrees of Freedom Mean Square F p-value X X Factor A Factor B Interaction 24 Error 35 Total...
A single replicate 24 experiment is designed. The experiment has factors A, B, C, and D, each of which can be set to +1 or -1. We conduct a single replicate of this experiment, collecting the response for each possible combination of factor settings. This data is in the file HW_DOEInterp_180.csv . We compute the factorial and interaction effects from this data, and determine that the following effects are significant: Factorial Effect B = -15.265 Factorial Effect C = -11.433...