Task: In a certain factory, production can be accomplished by four different workers on five diffferent types of machines. A simple study, in context of a two-way design without repeated values, is being made with two fold objectives of examining whether the four workers differ with respect to mean productivity and whether the mean productivity is the same for the five different machines. The researcher involved in this study reports while analysing the gathered data as under : i: Sum of squares for variance between machines = 35.2 %3D (ii) Sum of squares for variance between workmen = 53.8 %3D (iii) Sum of squares for total variance = 174.2 Set up ANOVA table for the given information and draw the inference about variance at 5 per cent level of significance.

Hi, I'm stuck with question 2. Question 1 given the example for 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 = 12,120; SSTR = 4,540. (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 Mean Degrees of Freedom F p-value of Variation of Squares Square Treatments 4540 2270 9.88 Error 7580 33 229.70 Total 12120 35 (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 = "2 = H3 Ha: H1 * 42 + H3 Ho: H1 # H2 # 43 Ha: H1 = #2 = #3 Ho:…

1. A purification process for a chemical involves passing it, in solution, through a resin on which impurities are adsorbed. A chemical engineer wishing to test the efficiency of 3 different resins took a chemical solution and broke it into 15 batches. She tested each resin 5 times and then measured the concentration of impurities after passing through the resins. The results of the Analysis of Variance on the data are shown below. Analysis of Variance Table Response: concentration Df Sum Sq Mean Sq F value Pr(>F) resin 2 1.45E-05 7.27E-06 0.048737 0.9526 Residuals 12 0.001789 0.000149 a.) Interpret the result of the Analysis of Variance (ANOVA). What is the statistical decision and corresponding conclusion? b.) What is the implication of the results obtained from the analysis of the data?